NUREG-1575, Rev. 2, Multi-Agency Radiation Survey and Site Investigation Manual (Marssim), Draft for Public Comment: Difference between revisions

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{{#Wiki_filter:NUREG-1575, Revision 2 EPA-402-P-20-001 DOE/AU-0002 MULTI-AGENCY RADIATION SURVEY AND SITE INVESTIGATION MANUAL (MARSSIM)
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DRAFT FOR PUBLIC COMMENT Revision 2                        May 2020
 
NUREG-1575, Rev. 2 MULTI-AGENCY RADIATION SURVEY AND SITE MAY 2020 EPA-402-P-20-001      INVESTIGATION MANUAL (MARSSIM)
Revision 2 DOE/AU-0002              DRAFT FOR PUBLIC COMMENT
 
ABSTRACT The Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) provides information on planning, conducting, evaluating, and documenting building surface and surface soil radiological surveys for demonstrating compliance with requirements, often as part of a dose- or risk-based regulation or standard. 1 MARSSIM is a multi-agency consensus document that was developed collaboratively by four Federal agencies having authority and control over radioactive materials: Department of Defense (DOD), Department of Energy (DOE),
Environmental Protection Agency (EPA), and Nuclear Regulatory Commission (NRC).
MARSSIMs objective is to describe a consistent approach for planning, performing, and assessing building surface and surface soil radiological surveys to meet established dose or risk-based release criteria, while concurrently encouraging an effective use of resources.
1 MARSSIM uses the word should as a recommendation, not as a requirement. Each recommendation in this manual is not intended to be taken literally and applied at every site. MARSSIMs survey planning documentation will address how to apply the process on a site-specific basis.
May 2020                                                    i                        NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                            DO NOT CITE OR QUOTE
 
DISCLAIMER This manual was prepared by four agencies of the United States Government. Neither the United States Government nor any agency or branch thereof, or any of their employees, makes any warranty, expressed or implied, or assumes any legal liability of responsibility for any third partys use, or the results of such use, of any information, apparatus, product, or process disclosed in this manual, or represents that its use by such third party would not infringe on privately owned rights.
References within this manual to any specific commercial product, process, or service by trade name, trademark, or manufacturer does not constitute an endorsement or recommendation by the United States Government.
NUREG-1575, Revision 2                            ii                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
ACKNOWLEDGMENTS The Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) came about as a result of individualsat the management levelwithin the Environmental Protection Agency (EPA), Nuclear Regulatory Commission (NRC), Department of Energy (DOE), and Department of Defense (DOD) who recognized the necessity for a standardized guidance document for investigating radioactively contaminated sites. The creation of the MARSSIM was facilitated by the cooperation of subject matter specialists from these agencies with managements support and a willingness to work smoothly together toward reaching the common goal of creating a workable and user-friendly guidance manual. Special appreciation is extended to Robert A.
Meck of the NRC and Anthony Wolbarst of EPA for developing the concept of a multi-agency work group and bringing together representatives from the participating agencies.
The MARSSIM could not have been possible without the technical work group members who contributed their time, talent, and efforts to develop this consensus guidance document:
CDR Colleen F. Petullo, U.S. Public Health Service, EPA, Chair EPA: Mark Doehnert                            DOE: Hal Peterson, CHP Anthony Wolbarst, Ph.D.                      Kenneth Duvall H. Benjamin Hull                              Andrew Wallo III Sam Keith, CHP*
Jon Richards NRC: Robert A. Meck, Ph.D.                    DOD: David Alberth (Army)
Anthony Huffert                              LCDR Lino Fragoso, Ph.D. (Navy)
George E. Powers, Ph.D.                      Lt. Col. Donald Jordan (Air Force)
David Fauver, CHP                            Capt. Kevin Martilla (Air Force)
Cheryl Trottier                              Capt. Julie Coleman (Air Force)
Special mention is extended to the Federal agency contractors for their assistance in developing the MARSSIM:
EPA: Scott Hay (S. Cohen & Associates, Inc.)
Todd Peterson, Ph.D. (S. Cohen & Associates, Inc.)
Harry Chmelynski, Ph.D. (S. Cohen & Associates, Inc.)
Ralph Kenning, CHP (S. Cohen & Associates, Inc.)
NRC: Eric Abelquist, CHP (Oak Ridge Institute of Science and Education)
James Berger (Auxier & Associates)
Carl Gogolak, Ph.D. (DOE/EML, under contract with NRC)
* Formerly with EPA National Air and Radiation Environmental Laboratory (NAREL). Currently with the Agency for Toxic Substances and Disease Registry (ATSDR).
May 2020                                          iii                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
DOE: Robert Colement, CHP (Oak Ridge National Laboratory)
John Kirk Williams (Oak Ridge National Laboratory)
Romance Carrier (Oak Ridge National Laboratory)
A special thank you is extended to Emilio Braganza (EPA), Gregory Budd (EPA), Mary Clark, Ph.D. (EPA), Brian Littleton (EPA), John Karhnak (EPA), Sarah Seeley (EPA), Rett Sutton (EPA/SEE), Juanita Beeson (NRC), Stephen A. McGuire, Ph.D. (NRC), Walter Oliu (NRC),
LT James Coleman (Navy), CDR David E. Farrand (Navy), CAPT David George (Navy),
CDR Garry Higgins (Navy), CAPT James Malinoski (Navy), Harlan Keaton (State of Florida),
J. Michael Beck, J.D. (EMS), Tom McLaughlin, Ph.D. (SC&A), Kevin Miller, Ph.D. (DOE/EML),
and the members of the EPAs Science Advisory Board (SAB) for their assistance in developing the manual.
The membership of the SAB Radiation Advisory Committees Review Subcommittee that conducted an extensive peer review of the MARSSIM includes:
Chair James E. Watson, Jr., Ph.D., University of North Carolina at Chapel Hill Members William Bair, Ph.D., (Retired), Battelle Pacific Northwest Laboratory Stephen L. Brown, Ph.D., R2C2 (Risks of Radiation and Chemical Compounds)
June Fabryka-Martin, Ph.D., Los Alamos National Laboratory Thomas F. Gesell, Ph.D., Idaho State University F. Owen Hoffman, Ph.D., SENES Oak Ridge, Inc.
Janet Johnson, Ph.D., Shepherd Miller, Inc.
Bernd Kahn, Ph.D., Georgia Institute of Technology Ellen Mangione, M.D., Colorado Department of Health Paul J. Merges, Ph.D., New York State Department of Environmental Conservation SAB Consultants Michael E. Ginevan, Ph.D., M.E. Ginevan & Associates David G. Hoel, Ph.D., University of South Carolina David E. McCurdy, Ph.D., Yankee Atomic Electric Company Frank L. Parker, Ph.D., Vanderbilt University [Liaison from Environmental Management Advisory Board, U.S. Department of Energy]
Science Advisory Board Staff K. Jack Kooyoomjian, Ph.D., Designated Federal Official, EPA Mrs. Diana L. Pozun, Staff Secretary, EPA NUREG-1575, Revision 2                          iv                                May 2020 DRAFT FOR PUBLIC COMMENT                                              DO NOT CITE OR QUOTE
 
ACKNOWLEDGMENTS The work group meetings were open to the public, and the following people attended meetings as technical experts at the request of the work group or as observers:
K. Allison      A.T. Kearney                        N. Lailas        EPA L. Abramson    NRC                                H. Larson        NRC R. Abu-Eid      NRC                                G. Lindsey      International Atomic W. Beck        Oak Ridge Institute of                                Energy Agency Science and Education            J. Lux          Kerr-McGee Corporation A. Boerner      Oak Ridge Institute of              M. Mahoney      Army Science and Education            J. Malaro        NRC Lt. E. Bonano Air Force                            H. Morton        Morton Associates M. Boyd        EPA                                H. Mukhoty      EPA J. Buckley      NRC                                A.J. Nardi      Westinghouse B. Burns        Army                                D. Ottlieg      Westinghouse Hanford W. Cottrell    Oak Ridge National                                    Company Laboratory                        V. Patania      Oak Ridge D. Culberson    Nuclear Fuel Services, Inc.                            National Laboratory M.C. Daily      NRC                                C.L. Pittiglio  NRC M. Eagle        EPA                                C. Raddatz      NRC M. Frank        Booz, Allen & Hamilton              L. Ralston      SC&A, Inc.
F. Galpin      RAE Corp.                          P. Reed          NRC R. Gilbert      Pacific Northwest                  R. Rodriguez    Oak Ridge Laboratory                                          National Laboratory J.E. Glenn      NRC                                N. Rohnig        -
J. Hacala      Booz, Allen & Hamilton              R. Schroeder    Army L. Hendricks    Nuclear Environmental              C. Simmons      Kilpatrick & Cody Services                          E. Stamataky    EPA K. Hogan        EPA                                R. Story        Foster Wheeler R. Hutchinson National Institute of                E. Temple        EPA Standards and Technology            D. Thomas        Air Force G. Jablonowski EPA                                  S. Walker        EPA P. White        EPA R. Wilhelm      EPA May 2020                                        v                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                              DO NOT CITE OR QUOTE
 
ACKNOWLEDGEMENTS FOR REVISION 2 The four federal agencies that originally published MARSSIM came to an agreement in 2010 that MARSSIM needed a comprehensive revision due to changes in the science of radiation measurement and lessons learned over the 14-year time-span that had passed since its original issuance. The Workgroup began by soliciting comments from the Government agencies and members of the public on revisions to MARSSIM. In addition, the Workgroup held a consultation with the EPA Science Advisory Boards Radiation Advisory Committee to solicit additional comments on the document. Subject matter experts from all four Federal agencies contributed their time and expertise to updating portions of the original document based on the comments and suggestions received, in some cases writing new sections and appendices in order to provide the most comprehensive update possible.
Revision 2 to MARSSIM could not have been possible without the technical workgroup members and their colleagues who contributed their time, talent, and efforts to develop this consensus guidance document:
Kathryn Snead, EPA, Chair EPA:    Nidal Azzam                        DOE:    Amanda Anderson, CHP Eugene Jablonowski                          Carlos Corredor Larainne Koehler                            Derek Favret, CHP Anthony Nesky                                Wayne Glines, CHP Lyndsey Nguyen                              Tim Vitkus, CHP David Pawel, Ph.D.                          Alexander Williams, Ph.D.
Colleen Petullo Oleg Povetko, Ph.D.                DoD:    Erik Abkemeier, CHP (Navy)
David P. Alberth (Army)
NRC: Boby Abu-Eid, Ph.D.                              Craig Bias, Ph.D., CHP (Air Force)
Cynthia Barr                                Ramachandra Bhat, Ph.D., CHP (Air Force)
Luis Benevides                              David Bytwerk, Ph.D., CHP (Army)
John Clements                                Col. (Ret.) Robert Cherry, Ph.D., CHP Mark Fuhrmann, Ph.D.                          (Army)
Anthony Huffert, Ph.D.                      Steven Doremus, Ph.D. (Navy)
Tanya Oxenberg, Ph.D.                        Gerald Falo, Ph.D., CHP (Army)
Duane Schmidt, CHP                          Lt. Col. Alan C. Hale, CHP (Air Force)
G. Neil Keeney, CHP (Air Force)
Capt. Nathan Krzyaniak (Air Force)
Bret Rodgers (Air Force) 1st Lt. Trey Slauter (Air Force)
NUREG-1575, Revision 2                          vi                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Special mention is extended to the Federal agency contractors for their assistance in developing MARSSIM, Revision 2:
Harry Chmelynski, Ph.D. (S. Cohen & Associates, Inc.)
Melody Geer (Trinity Engineering Associates, Inc.)
Jana Dawson (Trinity Engineering Associates, Inc.)
Carl Gogolak, Ph.D. (S. Cohen & Associates, Inc.)
Scott Hay (S. Cohen & Associates, Inc.)
Aris Papadopoulos (S. Cohen & Associates, Inc.)
Karene Riley (S. Cohen & Associates, Inc.)
David Stuenkel, Ph.D., CHP (Trinity Engineering Associates, Inc.)
Robert Thielke (Trinity Engineering Associates, Inc.)
A special thank you is extended to the following for their contributions to the document:
Lynn Albin (State of Washington), Mary Clark (EPA), E.S. Chandrasekaran (TVA), Phil Egidi (EPA), Paul Giardina (EPA), Sandra Gogol (DHS), Jenny Goodman (State of New Jersey),
Robert Meck (SATS, LLC), Richard Vojtech (DHS), and Andrew Wallo (DOE).
[Add acknowledgement for SAB Review when completed.]
DEDICATION The MARSSIM Workgroup notes, with much sadness, the sudden loss of Dr. George Edward Powers of the U.S. Nuclear Regulatory Commission staff. Dr. Powers passed away in late 2011, as the effort to revise the MARSSIM manual was getting underway. As a member of the MARSSIM Workgroup, he made significant contributions on MARSSIM, both on the original document, on its revision in 2001, and on this latest revision. Dr. Powers also contributed in an important way to the development of the MARSAME and MARLAP manuals; his participation in the development of all three documents (MARSSIM, MARSAME, and MARLAP) is well recognized. The MARSSIM Workgroup members also are aware of the many contributions he made as an NRC employee, including his involvement in several USNRC NUREG publications over the years. Dr. Powers was truly a visionary in encouraging development of multi-agency documents in this collaborative and collegial manner for use by many people. Dr. Powers sense of humor enhanced his ability to work so well in a positive manner with many of his colleagues in multi-agency settings. He was a technically accomplished, kind, and courteous man who contributed much to the Workgroups efforts.
May 2020                                        vii                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
CONTENTS Abstract........................................................................................................................................i Disclaimer ................................................................................................................................... ii Acknowledgements .................................................................................................................... iii Acknowledgements for Revision 2 ............................................................................................. vi Dedication .................................................................................................................................. vi Contents ................................................................................................................................... vii Tables ...................................................................................................................................... xvi Figures ...................................................................................................................................... xx Abbreviations ..........................................................................................................................xxiii Symbols, Nomenclature, and Notations ................................................................................ xxviii Conversion Factors ............................................................................................................... xxxv 1    Introduction ..................................................................................................................... 1-1
 
==1.1    Purpose and Scope==
of MARSSIM ............................................................................. 1-1 1.2    Structure of the Manual............................................................................................. 1-6 1.3    Use of the Manual ..................................................................................................... 1-7 1.4    Missions of the Federal Agencies Producing MARSSIM ........................................... 1-8 1.4.1      Environmental Protection Agency ...................................................................... 1-8 1.4.2      Nuclear Regulatory Commission ........................................................................ 1-8 1.4.3      Department of Energy ........................................................................................ 1-8 1.4.4      Department of Defense ...................................................................................... 1-9 2    Overview of the Radiation Survey and Site Investigation Process ................................... 2-1 2.1    Introduction ............................................................................................................... 2-1 2.2    Understanding Key MARSSIM Terminology.............................................................. 2-2 2.2.1      Key MARSSIM Terminology .............................................................................. 2-2 2.2.2      Classification Assessment ................................................................................. 2-6 2.3    Making Decisions Based on Survey Results ............................................................. 2-7 2.3.1      Planning Effective SurveysPlanning Phase .................................................... 2-9 2.3.2      Evaluating Sources of Variability in Survey ResultsImplementation Phase ... 2-14 2.3.3      Evaluating Survey ResultsAssessment Phase ............................................. 2-14 2.3.4      Uncertainty in Survey Results .......................................................................... 2-15 2.3.5      Reporting Survey Results ................................................................................ 2-17 2.4    Radiation Survey and Site Investigation Process .................................................... 2-18 2.4.1      Site Identification ............................................................................................. 2-19 2.4.2      Historical Site Assessment............................................................................... 2-19 2.4.3      Scoping Survey................................................................................................ 2-25 2.4.4      Characterization Survey ................................................................................... 2-26 2.4.5      Remedial Action Support Survey ..................................................................... 2-27 2.4.6      Final Status Survey .......................................................................................... 2-27 NUREG-1575, Revision 2                                              viii                                                        May 2020 DRAFT FOR PUBLIC COMMENT                                                                              DO NOT CITE OR QUOTE
 
2.4.7    Regulatory Agency Confirmation and Verification Survey ................................ 2-28 2.5  Demonstrating Compliance with Dose- or Risk-Based Criteria ................................ 2-28 2.5.1    The Decision to Use Statistical Tests ............................................................... 2-29 2.5.2    Categorization and Classification ..................................................................... 2-32 2.5.3    Design Considerations for Small Areas of Elevated Activity ............................. 2-33 2.5.4    Design Considerations for Relatively Uniform Distributions of Residual Radioactive Material ........................................................................................................... 2-34 2.5.5    Developing an Integrated Survey Design ......................................................... 2-35 2.6  Flexibility in Applying MARSSIM Approach ............................................................. 2-37 2.6.1    Alternate Statistical Methods............................................................................ 2-37 2.6.2    Integrating MARSSIM with Other Survey Designs ........................................... 2-38 3  Historical Site Assessment .............................................................................................. 3-1 3.1  Introduction ............................................................................................................... 3-1 3.2  Data Quality Objectives ............................................................................................ 3-3 3.3  Site Identification ...................................................................................................... 3-5 3.4  Preliminary Investigation ........................................................................................... 3-5 3.4.1    Existing Radiation Data...................................................................................... 3-8 3.4.2    Contacts and Interviews ................................................................................... 3-10 3.5  Site Reconnaissance .............................................................................................. 3-10 3.6  Evaluation of Historical Site Assessment Information.............................................. 3-11 3.6.1    Identify Potential Sources of Residual Radioactive Material ............................. 3-12 3.6.2    Identify Potential Areas with Residual Radioactive Material ............................. 3-13 3.6.3    Identify Potential Media with Residual Radioactive Material ............................. 3-13 3.6.4    Develop a Conceptual Model of the Site .......................................................... 3-20 3.6.5    Professional Judgment .................................................................................... 3-21 3.7  Determining the Next Step in the Site Investigation Process ................................... 3-23 3.8  Historical Site Assessment Report .......................................................................... 3-24 3.9  Review of the HSA .................................................................................................. 3-24 4  Considerations for Planning Surveys ............................................................................... 4-1 4.1  Introduction ............................................................................................................... 4-1 4.1.1    Purpose ............................................................................................................. 4-1 4.1.2    Scope ................................................................................................................ 4-1 4.1.3    Overview of Survey Planning ............................................................................. 4-1 4.2  Data Quality Objectives Process ............................................................................... 4-2 4.2.1    Planning Phase.................................................................................................. 4-3 4.2.2    Quality System................................................................................................... 4-4 4.3  Survey Types ............................................................................................................ 4-5 4.3.1    Scoping.............................................................................................................. 4-5 4.3.2    Characterization................................................................................................. 4-6 4.3.3    Remedial Action Support ................................................................................... 4-6 4.3.4    Final Status ........................................................................................................ 4-6 4.3.5    Simplified Procedures ........................................................................................ 4-8 4.3.6    A Note on Subsurface Assessments .................................................................. 4-8 May 2020                                                      ix                                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                        DO NOT CITE OR QUOTE
 
4.3.7    Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA) Sites ............... 4-8 4.4  The Unity Rule .......................................................................................................... 4-9 4.5  Radionuclides ......................................................................................................... 4-10 4.5.1    Radionuclides of Concern ................................................................................ 4-10 4.5.2    Release Criteria and Derived Concentration Guideline Levels ......................... 4-10 4.5.3    Applying DCGLs .............................................................................................. 4-12 4.5.4    Investigation Levels ......................................................................................... 4-19 4.5.5    Conclusions ..................................................................................................... 4-19 4.6  Area and Site Considerations ................................................................................. 4-20 4.6.1    Area Classification ........................................................................................... 4-20 4.6.2    Identification of Survey Units............................................................................ 4-22 4.6.3    Selection of Background Reference Areas....................................................... 4-23 4.7  Statistical Considerations ........................................................................................ 4-24 4.7.1    Basic Terms ..................................................................................................... 4-25 4.7.2    Recommended Statistical Tests ....................................................................... 4-25 4.7.3    Considerations on the Choice of a Statistical Test ........................................... 4-26 4.7.4    Deviations from MARSSIM Statistical Test Recommendations ........................ 4-26 4.7.5    An Important Statistical Note............................................................................ 4-26 4.8  Measurements ........................................................................................................ 4-26 4.8.1    Quality Control and Quality Assurance............................................................. 4-26 4.8.2    Measurement Quality Objectives ..................................................................... 4-27 4.8.3    Selecting a Measurement Technique ............................................................... 4-28 4.8.4    Selection of Instruments for Field Measurements ............................................ 4-30 4.8.5    Selection of Sample Collection Methods .......................................................... 4-33 4.8.6    Selection of Measurement Techniques ............................................................ 4-36 4.8.7    Data Conversion .............................................................................................. 4-37 4.8.8    Additional Planning Considerations Related to Measurements ........................ 4-37 4.9  Site Preparation ...................................................................................................... 4-39 4.9.1    Consent for Survey .......................................................................................... 4-39 4.9.2    Property Boundaries ........................................................................................ 4-39 4.9.3    Physical Characteristics of Site ........................................................................ 4-40 4.9.4    Clearing to Provide Access .............................................................................. 4-42 4.9.5    Reference Coordinate System ......................................................................... 4-43 4.10 Health and Safety ................................................................................................... 4-49 4.11 Documentation........................................................................................................ 4-50 4.12 Examples ................................................................................................................ 4-26 4.12.1 Scenario A or Scenario B? ............................................................................... 4-26 4.12.2 DCGL Calculations .......................................................................................... 4-27 4.12.3 Required number of Samples for a Single Radionuclide .................................. 4-28 4.12.4 Required Number of Samples for the Multiple Radionuclides ........................... 4-30 4.12.5 Instrument Efficiencies ..................................................................................... 4-33 4.12.6 Data Conversion .............................................................................................. 4-36 4.12.7 Example of a Deviation from a Recommended Statistical Test ........................ 4-37 4.12.8 Release Criteria for Discrete Radioactive Particles .......................................... 4-37 4.12.9 Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA) Sites ............. 4-30 5  Survey Planning and Design ........................................................................................... 5-1 NUREG-1575, Revision 2                                      x                                                          May 2020 DRAFT FOR PUBLIC COMMENT                                                                    DO NOT CITE OR QUOTE
 
5.1  Introduction ............................................................................................................... 5-1 5.2  Preliminary Surveys .................................................................................................. 5-5 5.2.1    Scoping Surveys ................................................................................................ 5-5 5.2.2    Characterization Surveys ................................................................................... 5-9 5.2.3    Remedial Action Support Surveys.................................................................... 5-19 5.3  Final Status Surveys ............................................................................................... 5-21 5.3.1    Selecting the Appropriate Scenario .................................................................. 5-26 5.3.2    Application of Release Criteria ......................................................................... 5-27 5.3.3    Determining Numbers of Data Points for Statistical Tests for Residual Radioactive Material Present in Background....................................................................... 5-27 5.3.4    Determining Numbers of Data Points for Statistical Tests for Residual Radioactive Material Not Present in Background ................................................................ 5-33 5.3.5    Determining the Number of Discrete Data Points for Small Areas of Elevated Activity............................................................................................................. 5-36 5.3.6    Determining the Scan Area .............................................................................. 5-42 5.3.7    Determining Survey Locations ......................................................................... 5-44 5.3.8    Determining Investigation Levels ..................................................................... 5-48 5.3.9    Developing an Integrated Survey Strategy ....................................................... 5-50 5.3.10 Evaluating Survey Results ............................................................................... 5-55 5.3.11 Documentation................................................................................................. 5-55 6  Field Measurement Methods and Instrumentation ........................................................... 6-1 6.1  Introduction ............................................................................................................... 6-1 6.2  Data Quality Objectives ............................................................................................ 6-2 6.2.1    Identifying Data Needs for Field Measurement Methods .................................... 6-2 6.2.2    Measurement Performance Indicators ............................................................... 6-3 6.2.3    Instrument Performance Indicators .................................................................... 6-4 6.3  Detection Capability .................................................................................................. 6-6 6.3.1    Detection Capability for Direct Measurements ................................................... 6-6 6.3.2    Detection Capability for Scans ......................................................................... 6-11 6.4  Measurement Uncertainty ....................................................................................... 6-26 6.4.1    Systematic and Random Uncertainties ............................................................ 6-27 6.4.2    Statistical Counting Uncertainty ....................................................................... 6-28 6.4.3    Uncertainty Propagation .................................................................................. 6-29 6.4.4    Reporting Confidence Intervals ........................................................................ 6-30 6.5  Select a Service Provider to Perform Field Data Collection Activities ...................... 6-31 6.6  Select a Measurement Method ............................................................................... 6-32 6.6.1    Select a Measurement Technique.................................................................... 6-33 6.6.2    Select Instrumentation ..................................................................................... 6-35 6.6.3    Display and Recording Equipment ................................................................... 6-37 6.6.4    Instrument Calibration ...................................................................................... 6-38 6.6.5    Select Instrumentation ..................................................................................... 6-44 6.6.6    Select a Measurement Method ........................................................................ 6-45 6.7  Data Conversion ..................................................................................................... 6-46 6.7.1    Surface Activity ................................................................................................ 6-46 6.7.2    Soil Radionuclide Concentration and Exposure Rates ..................................... 6-52 May 2020                                                      xi                                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                        DO NOT CITE OR QUOTE
 
6.8  Radon Measurements............................................................................................. 6-52 6.8.1    Direct Radon Measurements ........................................................................... 6-55 6.8.2    Radon Progeny Measurements ....................................................................... 6-59 6.8.3    Radon Flux Measurements .............................................................................. 6-60 6.9  Special Equipment .................................................................................................. 6-60 6.9.3    Local Microwave and Sonar Positioning Systems ............................................ 6-61 6.9.2    Laser Positioning Systems ............................................................................... 6-61 6.9.3    Mobile Systems with Integrated Positioning Systems....................................... 6-61 6.9.4    Radar, Magnetometer, and Electromagnetic Sensors ...................................... 6-62 6.9.5    Aerial Radiological Surveys ............................................................................. 6-64 7  SAMPLING AND PREPARATION FOR LABORATORY MEASUREMENTS................... 7-1 7.1  Introduction ............................................................................................................... 7-1 7.2  Data Quality Objectives ............................................................................................ 7-2 7.2.1    Identifying Data Needs....................................................................................... 7-2 7.2.2    Data Quality Indicators....................................................................................... 7-3 7.3  Communications with the Laboratory ........................................................................ 7-8 7.3.1    Communications During Survey Planning .......................................................... 7-8 7.3.2    Communications Before and During Sample Collection ..................................... 7-9 7.3.3    Communications During Sample Analysis.......................................................... 7-9 7.3.4    Communications Following Sample Analysis ................................................... 7-10 7.4  Selecting a Radioanalytical Laboratory ................................................................... 7-10 7.5  Sampling ................................................................................................................. 7-11 7.5.1    Surface Soil ..................................................................................................... 7-12 7.5.2    Building Surfaces ............................................................................................. 7-15 7.5.3    Other Media ..................................................................................................... 7-16 7.6  Field Sample Preparation and Preservation ............................................................ 7-16 7.6.1    Surface Soil ..................................................................................................... 7-16 7.6.2    Building Surfaces ............................................................................................. 7-17 7.6.3    Other Media ..................................................................................................... 7-17 7.7  Analytical Procedures ............................................................................................. 7-17 7.7.1    Photon Emitting Radionuclides ........................................................................ 7-19 7.7.2    Beta Emitting Radionuclides ............................................................................ 7-21 7.7.3    Alpha Emitting Radionuclides .......................................................................... 7-21 7.8  Sample Tracking ..................................................................................................... 7-22 7.8.1    Field Tracking Considerations .......................................................................... 7-22 7.8.2    Transfer of Custody ......................................................................................... 7-23 7.8.3    Radiochemical Holding Times .......................................................................... 7-24 7.8.4    Laboratory Tracking ......................................................................................... 7-24 7.9  Packaging and Transporting Samples..................................................................... 7-25 7.9.1    U.S. Nuclear Regulatory Commission Regulations .......................................... 7-26 7.9.2    U.S. Department of Transportation Regulations ............................................... 7-26 7.9.3    U.S. Postal Service Regulations ...................................................................... 7-27 7.9.4    International Atomic Energy Agency Regulations............................................. 7-27 8  Interpretation of Survey Results ...................................................................................... 8-1 NUREG-1575, Revision 2                                      xii                                                          May 2020 DRAFT FOR PUBLIC COMMENT                                                                        DO NOT CITE OR QUOTE
 
8.1    Introduction ............................................................................................................... 8-1 8.2    Data Quality Assessment .......................................................................................... 8-1 8.2.1    Review the Data Quality Objectives, Measurement Quality Objectives, and Survey Design ............................................................................................................... 8-2 8.2.2    Conduct a Preliminary Data Review................................................................... 8-3 8.2.3    Select the Statistical Test ................................................................................. 8-11 8.2.4    Verify the Assumptions of the Statistical Tests ................................................. 8-13 8.2.5    Draw Conclusions from the Data...................................................................... 8-15 8.3    Radionuclide Not Present in Background ................................................................ 8-18 8.3.1    Sign Test ......................................................................................................... 8-19 8.3.2    Applying the Sign Test ..................................................................................... 8-22 8.4    Radionuclide Present in Background ...................................................................... 8-27 8.4.1    Wilcoxon Rank Sum Test and Quantile Test .................................................... 8-27 8.4.2    Applying the Wilcoxon Rank Sum Test ............................................................ 8-29 8.4.3    Applying the Quantile Test - Only used in Scenario B ..................................... 8-32 8.4.4    Multiple Radionuclides ..................................................................................... 8-37 8.5    Scan-Only Surveys ................................................................................................. 8-44 8.6    Evaluate the Results: The Decision ........................................................................ 8-45 8.6.1    Elevated Measurement Comparison ................................................................ 8-46 8.6.2    Interpretation of Statistical Test Results ........................................................... 8-47 8.6.3    If the Survey Unit Fails ..................................................................................... 8-48 8.6.4    Removable Radioactive Material...................................................................... 8-50 8.7    Documentation........................................................................................................ 8-50 References .......................................................................................................................... Ref-1 A    Example of MARSSIM Applied to a Final Status Survey.................................................. A-1 A.1 Introduction ............................................................................................................... A-1 A.2 Survey Preparations ................................................................................................. A-1 A.3 Survey Design .......................................................................................................... A-9 A.4 Conducting Surveys ................................................................................................ A-16 A.5 Evaluating Survey Results ...................................................................................... A-16 B    Simplified Procedure for Certain Users of Sealed Sources, Short Half-life Materials, and Small Quantities ...................................................................................................................... B-1 C Regulations and Requirements Associated with Radiation Surveys and Site Investigations ...................................................................................................................C-1 C.1 EPA Statutory Authorities.......................................................................................... C-1 C.2 DOE Regulations and Requirements ........................................................................ C-3 C.3 NRC Regulations and Requirements ........................................................................ C-9 C.4 DOD Regulations and Requirements ...................................................................... C-12 C.5 State and Local Regulations and Requirements ..................................................... C-16 D    MARSSIM PROJECT-LEVEL QUALITY SYSTEM COMPONENTS ................................ D-1 D.1    The Planning Phase ................................................................................................ D-2 D.2    The Implementation Phase .................................................................................... D-38 May 2020                                                        xiii                                NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                            DO NOT CITE OR QUOTE
 
D.3    The Assessment Phase ......................................................................................... D-42 D.4    Data Verification and Validation ............................................................................. D-47 E    RANKED SET SAMPLING .............................................................................................. E-1 E.1 Introduction ............................................................................................................... E-1 E.2 Integration of RSS into MARSSIM ............................................................................ E-6 E.3 Summary Example of an FSS Survey Using RSS ................................................... E-18 F    The Relationship Between the Radiation Survey and Site Investigation Process, the CERCLA Remedial or Removal Process, and the RCRA Corrective Action Process ............. F-1 G    Historical Site Assessment Information Sources .............................................................G-1 H    Description of Field Survey and Laboratory Analysis Equipment ..................................... H-1 H.1 Introduction ...............................................................................................................H-1 H.2 Field Survey Equipment ............................................................................................ H-3 H.3 Laboratory Instruments ........................................................................................... H-35 I    Statistical Tables and Procedures .................................................................................... I-1 I.1    Normal Distribution .................................................................................................... I-1 I.2    Sample Sizes for Statistical Tests .............................................................................. I-2 I.3    Critical Values for the Sign Test ................................................................................. I-4 I.4    Critical Values for the WRS Test ................................................................................ I-6 I.5    Probability of Detecting an Elevated Area ............................................................... 1-11 I.6    Test Statistics for the Quantile Test ........................................................................ 1-16 I.7    Random Numbers .................................................................................................... I-22 J    Derivation of Alpha Scanning Equations Presented in Section 6.6.2.2..............................J-1 K    Comparison Tables Between Quality Assurance Documents .......................................... K-1 L    Stem and Leaf Displays and Quantile Plots ..................................................................... L-1 L.1    Stem and Leaf Display .............................................................................................. L-1 L.2    Quantile Plots ........................................................................................................... L-2 M      Calculation of Power Curves .......................................................................................M-1 M.1    Power Calculations for the Statistical Tests.............................................................. M-1 N      Effect of Precision on Planning and Performing Surveys ............................................. N-1 N.1    Introduction ...............................................................................................................N-1 N.2    Summary ..................................................................................................................N-5 O Detailed Calculations for Statistical Tests and Illustrative Examples for the Determination of DCGLs ....................................................................................................................................O-1 O.1 Introduction ...............................................................................................................O-1 O.2 The WRS Test ..........................................................................................................O-1 O.3 The Sign Test ...........................................................................................................O-3 O.4 Calculating Area Factors and the DCGL for the EMC ...............................................O-4 NUREG-1575, Revision 2                                            xiv                                                          May 2020 DRAFT FOR PUBLIC COMMENT                                                                            DO NOT CITE OR QUOTE
 
O.5  Release Criteria for Discrete Radioactive Particles ...................................................O-8 O.6  Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA) Sites ......................O-8 Glossary................................................................................................................................GL-1 May 2020                                                          xv                                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                            DO NOT CITE OR QUOTE
 
TABLES 1.1: Scope of MARSSIM ......................................................................................................... 1-4 2.1: The Data Life Cycle used to Support the Radiation Survey and Site Investigation Process ......................................................................................................................... 2-25 2.2: Recommended Conditions for Demonstrating Compliance Based on Survey Unit Classification for a Final Status Survey ......................................................................... 2-36 2.3: Examples of Alternate Statistical Tests .......................................................................... 2-39 3.1: Questions Useful for the Preliminary Investigation ........................................................... 3-9 4.1: Suggested Area for Surveys .......................................................................................... 4-22 4.2: Examples of Direct Measurement Instruments ............................................................... 4-34 4.3: Sample Results for Unity Rule Example ......................................................................... 4-58 5.1: Null and Alternative Hypothesis for Scenarios A and B .................................................. 5-26 5.2: Values of N/2 for Use with the Wilcoxon Rank Sum Test, .............................................. 5-32 5.3: Values of N for Use with the Sign Test ........................................................................... 5-35 5.4: Example FSS Investigation Levels ................................................................................. 5-49 5.5: Recommended Survey Coverage for Structures and Land Areas .................................. 5-51 6.1: Examples of Estimated Detection Capabilities for Alpha and Beta Survey Equipment (Static one minute counts for 238U calculated using Equations 6.3, 6.4, and 6.5) ...................... 6-11 6.2: Values of d' for Selected True Positive and False Positive Proportion ............................ 6-14 6.3: NaI(Tl) Scintillation Detector Scan MDCs for Common Radionuclides and Radioactive Materials ....................................................................................................................... 6-23 6.4: Probability of Detecting 300 dpm/100 cm2 of Alpha Activity While Scanning with Alpha Detectors Using an Audible Output (calculated using Equation 6-16) ............................ 6-26 6.5: Common Uncertainty Propagation Equations ................................................................. 6-30 6.6: Areas Under Various Intervals About the Mean of a Normal Distribution ........................ 6-30 6.7: Potential Applications for Instrumentation and Measurement Technique Combinations . 6-44 6.8: Advantages and Disadvantages of Instrumentation and Measurement Technique Combinations ................................................................................................................ 6-45 6.9: Radiation Detectors with Applications to Radon Surveys ............................................... 6-56 7.1: Soil Sampling Equipment ............................................................................................... 7-13 7.3: Typical Measurement Sensitivities for Laboratory Radiometric Procedures.................... 7-20 8.1: Summary of Statistical Tests and Evaluation Methods ................................................... 8-13 8.2: Methods for Checking the Assumptions of Statistical Tests ............................................ 8-15 8.3: Summary of Statistical Tests for Radionuclide not in Background and Radionuclide-Specific Measurement ................................................................................................................ 8-15 NUREG-1575, Revision 2                                          xvi                                                          May 2020 DRAFT FOR PUBLIC COMMENT                                                                          DO NOT CITE OR QUOTE
 
8.4: Summary of Statistical Tests for Radionuclide in Background or Radionuclide Non-Specific (Gross) Measurements .................................................................................................. 8-16 8.5: Summary of Results for Scan-Only Surveys................................................................... 8-17 8.6: Final Status Survey Parameters for Example Survey Units for Scenario A ..................... 8-18 8.7: Final Status Survey Parameters for Example Survey Units for Scenario B ..................... 8-19 8.8: Example Sign Analysis: Class 2 Exterior Soil Survey Unit .............................................. 8-24 8.9: Sign Test Example Data for Class 3 Exterior Survey Unit .............................................. 8-26 8.10: WRS Test for Class 2 Interior Drywall Survey Unit in Example 7 .................................. 8-31 8.11: WRS and Quantile Test Under Scenario B for Class 2 Interior Drywall Survey Unit in Example ........................................................................................................................ 8-34 8.12: Calculation of 2 for Example 9 ................................................................................... 8-36 8.13: Analysis of Variance for Example 9 Data...................................................................... 8-36 8.14: Example 10 WRS Test for Two Radionuclides ............................................................. 8-40 8.15: Example 11 WRS Test for Two Radionuclides ............................................................. 8-41 A.1: Class 1 Interior Concrete Survey Unit and Reference Area Data ................................... A-17 A.2: Stem and Leaf Displays for Class 1 Interior Concrete Survey Units ............................... A-17 A.3: WRS Test for Class 1 Interior Concrete Survey Unit ...................................................... A-20 C.1 DOE Authorities, Orders, and Regulations Related to Radiation Protection ...................... C-4 C.2 Agreement States ........................................................................................................... C-17 C.3 States That Regulate Diffuse NORM .............................................................................. C-17 D.1: Representation of Decision Errors for a Final Status Survey (FSS) Using Scenario A for the True Condition of the Survey Unit.................................................................................. D-19 D.2: Representation of Decision Errors for a Final Status Survey Using Scenario B for the True Condition of the Survey Unit .......................................................................................... D-19 D.3: Suggested Content or Consideration, Impact if Not Met, and Considerations for Data Descriptors .................................................................................................................... D-50 D.4: Use of Quality Control Data ........................................................................................... D-56 D.5: Minimum Considerations for Precision, Impact if Not Met, and Corrective Actions......... D-57 D.6: Minimum Considerations for Bias, Impact if Not Met, and Corrective Actions ................ D-59 D.7: Minimum Considerations for Representativeness, Impact if Not Met, and Corrective Actions
    ...................................................................................................................................... D-62 D.8: Minimum Considerations for Comparability, Impact if Not Met, and Corrective Actions.. D-64 D.9: Minimum Considerations for Completeness, Impact if Not Met, and Corrective Actions. D-66 E.1: Required Number of Laboratory Samples for RSS Sign Test for 5 Sets Per Cycle .......... E-8 May 2020                                                            xvii                                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                                DO NOT CITE OR QUOTE
 
E.2: Required Number of Laboratory Samples for RSS Sign Test for 4 Sets Per Cycle .......... E-9 E.3: Required Number of Laboratory Samples for RSS Sign Test for 3 Sets Per Cycle ........ E-10 E.4: Critical Values for the RSS Sign Test............................................................................. E-16 E.5: Critical Values for the SRS Sign Test............................................................................. E-17 F.1: Program Comparison ....................................................................................................... F-5 F.2: Data Elements for Site Assessments ............................................................................. F-11 F.3: Comparison of Sampling Emphasis between Remedial Site Assessment and Removal Site Assessment................................................................................................................... F-11 G.1: Site Assessment Information Sources (Organized by Information Source) ......................G-2 G.2: Site Assessment Information Sources (Organized by Information Needed) ...................G-11 H.1: AMS Detection Limits .................................................................................................... H-51 H.2: Radiation Detectors with Applications to Alpha Surveys ................................................ H-59 H.3: Radiation Detectors with Applications to Beta Surveys .................................................. H-61 H.4: Radiation Detectors with Applications to Gamma and X-Ray Surveys ........................... H-63 H.5: Radiation Detectors with Applications to Large Area Mobile Detector Arrays................. H-67 H.6: Radiation Detectors with Applications to Radon Surveys ............................................... H-68 H.7: Systems that Measure Atomic Mass or Emissions......................................................... H-70 H.8: Special Techniques and Equipment............................................................................... H-72 I.1: Cumulative Normal Distribution Function z ...................................................................... I-1 I.2: Sample Sizes for Sign Test ................................................................................................ I-2 I.3: Sample Sizes for Wilcoxon Rank Sum Test ....................................................................... I-3 I.4: Critical Values for the Sign Test Statistic S+ ...................................................................... I-4 I.5: Critical Values for the WRS Test ........................................................................................ I-6 I.6: Risk that an Elevated Area with Length L/G and Shape S will not be Detected and the Area
(%) of the Elevated Area Relative to a Triangular Sample Grid Area of 0.866 G2 ........... I-11 I.7: Values of r and k for the Quantile Test When  Is Approximately 0.01 ............................. I-16 I.8: Values of r and k for the Quantile Test When  Is Approximately 0.025 ........................... I-17 I.9: Values of r and k for the Quantile Test When  Is Approximately 0.05 ............................. I-19 I.10: Values of r and k for the Quantile Test When  Is Approximately 0.10 ........................... I-20 I.11: 1,000 Random Numbers Uniformly Distributed between Zero and One ......................... I-22 K.1 Comparison of EPA QA/R-5 and EPA QAMS-005/80 ....................................................... K-2 K.2: Comparison of EPA QA/R-5 and ASME NQA-1 ............................................................... K-3 K.3: Comparison of EPA QA/R-5 and DOE Order 414.1D ....................................................... K-4 NUREG-1575, Revision 2                                      xviii                                                        May 2020 DRAFT FOR PUBLIC COMMENT                                                                        DO NOT CITE OR QUOTE
 
K.4: Comparison of EPA QA/R-5 and ISO 9000 ...................................................................... K-5 K.5: Comparison of EPA QA/R-5 and UFP-QAPP................................................................... K-6 L.1: Data for Quantile Plot ....................................................................................................... L-3 L.2: Ranked Reference Area Concentrations .......................................................................... L-5 L.3: Interpolated Ranks for Survey Unit Concentrations .......................................................... L-6 M.1: Values of Pr and p2 for Computing the Mean and Variance of WMW ............................... M-4 O.1: Values of Pr for Given Values of the Relative Shift, /, when the Radionuclide is Present in Background................................................................................................O-1 O.2: Percentiles Represented by Selected Values of  and  .................................................O-2 O.3: Values of Ps for Given Values of the Relative Shift, /, when the Radionuclide is Not Present in Background .........................................................................................O-3 O.4: Illustrative Examples of Outdoor Area Factors .................................................................O-6 O.5: Illustrative Examples of Indoor Area Factors ...................................................................O-6 May 2020                                                    xix                                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                      DO NOT CITE OR QUOTE
 
FIGURES 1.1: Compliance Demonstration .............................................................................................. 1-2 2.1: The Data Life Cycle.......................................................................................................... 2-9 2.2: The Data Quality Objectives Process ............................................................................. 2-11 2.3: The Assessment Phase of the Data Life Cycle (EPA 2006a) ......................................... 2-16 2.4: The Radiation Survey and Site Investigation Process in Terms of Area Classification ... 2-20 2.5: The Historical Site Assessment Portion of the Radiation Survey and Site Investigation Process ......................................................................................................................... 2-21 2.6: The Scoping Survey Portion of the Radiation Survey and Site Investigation Process..... 2-22 2.7: The Characterization and Remedial Action Support Survey Portion of the Radiation Survey and Site Investigation Process ...................................................................................... 2-23 2.8: The Final Status Survey Portion of the Radiation Survey and Site Investigation Process2-24 3.1: Historical Site Assessment Process Flowchart ................................................................. 3-2 3.2: Example Showing How a Site Might be Categorized Prior to Cleanup Based on the Historical Site Assessment ............................................................................................ 3-22 4.1: Sequence of Preliminary Activities Leading to Survey Design .......................................... 4-7 4.2: Flow Diagram for Selection of Field Survey Instrumentation for Direct Measurements and Analysis of Samples ...................................................................................................... 4-38 4.3: Indoor Grid Layout with Alphanumeric Grid Block Designation: Walls and Floors are Diagramed as Though They Lay Along the Same Horizontal Plane .............................. 4-46 4.4: Example of a Grid System for Survey of Site Grounds Using Compass Directions......... 4-47 4.5: Example of a Grid System for Survey of Site Grounds Using Distances Left or Right of the Baseline ........................................................................................................................ 4-48 5.1: The Scoping Survey Portion of the Radiation Survey and Site Investigation Process....... 5-2 5.2: The Characterization and Remedial Action Support Survey Portions of the Radiation Survey and Site Investigation Process ........................................................................................ 5-3 5.3: The Final Status Survey Portion of the Radiation Survey and Site Investigation Process . 5-4 5.4: Process for Designing an Integrated Survey Plan for a Final Status Survey ................... 5-23 5.5: Process for Identifying Discrete Measurement Locations ............................................... 5-24 5.6: Identifying Data Needs for Assessment of Potential Areas of Elevated Activity in Class 1 Survey Units .................................................................................................................. 5-25 5.7: Gray Region for Scenario A ........................................................................................... 5-28 5.8: Gray Region for Scenario B ........................................................................................... 5-29 6.1: Graphically Represented Probabilities for Type I and Type II Errors in Detection Capability for Instrumentation with a Background Response............................................................ 6-8 NUREG-1575, Revision 2                                            xx                                                          May 2020 DRAFT FOR PUBLIC COMMENT                                                                            DO NOT CITE OR QUOTE
 
6.2: The Physical Probe Area of a Detector: Gas Flow Proportional Detector with Physical Probe Area of 126 cm2............................................................................................................. 6-50 8.1: Examples of Posting Plots................................................................................................ 8-7 8.2: Sample GIS Visualization, Modified from Figures 3.4 and 7.8 in NUREG/CR-7021 (NRC 2012). .............................................................................................................................. 8-9 8.3: Example of a Frequency Plot (a) and Other Statistical Information Output from Visual Sample Plan v. 7 (b) ...................................................................................................... 8-10 8.4: ProUCL Worksheet for Example 12................................................................................ 8-42 8.5: ProUCL Select Variables Window for Hypothesis Testing for Example 12 ..................... 8-42 8.6: ProUCL Hypothesis Testing Options Window for Example 12 ........................................ 8-43 8.7: ProUCL Output for Example 12 ...................................................................................... 8-44 A.1: Plot Plan of the Specialty Source Manufacturing Company ............................................. A-3 A.2: Building Floor Plan........................................................................................................... A-4 A.3: Examples of Scanning Patterns for Each Survey Unit Classification ................................ A-7 A.4: Reference Coordinate System for the Class 1 Interior Concrete Survey Unit .................. A-8 A.5: Decision Performance Goal Diagram for the Class 1 Interior Concrete Survey Unit....... A-10 A.6 Prospective Power Curve for the Class 1 Interior Concrete Survey Unit ......................... A-13 A.7: Measurement Grid for the Class 1 Interior Concrete Survey Unit ................................... A-14 A.8: Quantile-Quantile Plot for the Class 1 Interior Concrete Survey Unit.............................. A-18 A.9: Retrospective and Prospective Power Curves for the Class 1 Interior Concrete Survey Unit
    ...................................................................................................................................... A-21 D.1: The Data Quality Objectives Process .............................................................................. D-4 D.2: Repeated Application of the DQO Process throughout the Radiation Survey and Site Investigation Process ...................................................................................................... D-5 D.3: Example of the Parameter of Interest for the Case wherein the Radionuclide does not appear in Background ................................................................................................... D-12 D.4: Example of the Parameter of Interest for the Case wherein the Radionuclide appears in Background ................................................................................................................... D-14 D.5: Statement of the Null Hypothesis for the Final Status Survey Addressing the Issue of Compliance ................................................................................................................... D-22 D.6: Statement of the Null Hypothesis for the Final Status Survey Addressing the Issue of Indistinguishability from Background Using Scenario B ................................................. D-24 D.7: Geometric Probability of Sampling at Least One Point of an Area of Elevated Activity as a Function of Sample Density with Either a Square or Triangular Sampling Pattern ......... D-30 May 2020                                                              xxi                                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                                DO NOT CITE OR QUOTE
 
D.8: Example of a Scenario A Power Chart Illustrating the Decision Rule for the Final Status Survey ........................................................................................................................... D-31 D.9: Example of a Scenario A Error Chart Illustrating the Decision Rule for the Final Status Survey ........................................................................................................................... D-32 D.10: The Assessment Phase ............................................................................................... D-43 D.11: Graphical Representation of Accuracy......................................................................... D-60 E.1: Power Curve for 10 Cycles of 3 Sets per Cycle for a Critical Value of 19 ( = 0.018) and SRS Power Curve for the Same Critical Value ( = 0.005) .......................................... E-12 E.2: Power Curve for 6 Cycles of 5 Sets per Cycle for a Critical Value of 18 ( = 0.032) and SRS Power Curve for the Same Critical Value ( = 0.100) .......................................... E-12 F.1 Comparison of the Radiation Survey and Site Investigation Process with the CERCLA Superfund Process and the RCRA Corrective Action Process ........................................ F-2 J.1: Probability (P) of getting one or more counts when passing over a 100 cm2 area containing residual radioactive material at 500 dpm/100 cm2 alpha. .................................................. J-4 J.2: Probability (P) of getting one or more counts when passing over a 100 cm2 area containing residual radioactive material at 1,000 dpm/100 cm2 alpha. ...............................................J-5 J.3: Probability (P) of getting one or more counts when passing over a 100 cm2 area containing residual radioactive material at 5,000 dpm/100 cm2 alpha. ...............................................J-6 J.4: Probability (P) of getting two or more counts when passing over a 100 cm2 area containing residual radioactive material at 500 dpm/100 cm2 alpha. ..................................................J-7 J.5: Probability (P) of getting two or more counts when passing over a 100 cm2 area containing residual radioactive material at 1,000 dpm/100 cm2 alpha. ...............................................J-8 J.6: Probability (P) of getting two or more counts when passing over a 100 cm2 area containing residual radioactive material at 5,000 dpm/100 cm2 alpha. ...............................................J-9 L.1: Example of a Stem and Leaf Display................................................................................ L-2 L.2: Example of a Quantile Plot ............................................................................................... L-4 L.3: Quantile Plot for Example Class 2 Exterior Survey Unit of Section 8.3.2 .......................... L-4 L.4: Example Quantile-Quantile Plot ....................................................................................... L-7 M.1: Retrospective Power Curve for Class 3 Exterior Survey Unit.......................................... M-2 M.2: Retrospective Power Curve for Class 2 Interior Drywall Survey Unit .............................. M-5 NUREG-1575, Revision 2                                          xxii                                                          May 2020 DRAFT FOR PUBLIC COMMENT                                                                            DO NOT CITE OR QUOTE
 
ABBREVIATIONS 1st Lt.      First Lieutenant AARST        American Association of Radon Scientists and Technologists AEA          Atomic Energy Act AEC          Atomic Energy Commission AFI          Air Force Instructions AGL          above ground level AL          action level ALARA        as low as reasonably achievable AMC          Army Materiel Command AMS          accelerator mass spectrometry ANSI        American National Standards Institute AR          Army Regulations ARA          Army Radiation Authorization ASQ          American Society for Quality ASTM        American Society of Testing and Materials ATSDR        Agency for Toxic Substances and Disease Registry CAA          Clean Air Act Capt.        Captain (Air Force)
CAPT        Captain (Navy)
CDR          Commander CED          committed effective dose CEDE        committed effective dose equivalent CERCLA      Comprehensive Environmental Response, Compensation, and Liability Act CERCLIS      Comprehensive Environmental Response, Compensation, and Liability Information System CFR          Code of Federal Regulations CHP          Certified Health Physicist COC          chain of custody Col.        Colonel CV          coefficient of variation DCF          dose conversion factor DCGL        derived concentration guideline level DCGLEMC      DCGL for small areas of elevated activity, used with the EMC DCGLW        DCGL for average concentrations over a wide area, used with statistical tests DEFT        Decision Error Feasibility Trials DGPS        differential global positioning system DHS          Department of Homeland Security DL          discrimination limit DLC          Data Life Cycle DOD          U.S. Department of Defense May 2020                                  xxiii                NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                        DO NOT CITE OR QUOTE
 
DOE          U.S. Department of Energy DOT          Department of Transportation DQA          Data Quality Assessment DQIs          Data Quality Indicators DQO          Data Quality Objectives ED            electronic dosimeter EERF          Eastern Environmental Radiation Facility Ehf          human factors efficiency EIC          electret ion chamber EMC          elevated measurement comparison EML          Environmental Measurements Laboratory EMMI          Environmental Monitoring Methods Index EPA          U.S. Environmental Protection Agency EPIC          Environmental Photographic Interpretation Center ERAMS        Environmental Radiation Ambient Monitoring System FA-MS        flowing afterglow mass spectrometer FEMA          Federal Emergency Management Agency FIRM          Flood Insurance Rate Maps FRDS          Federal Reporting Data System FSP          Field Sampling Plan FSS          Final Status Survey FUSRAP        Formerly Utilized Sites Remedial Action Program FWPCA        Federal Water Pollution Control Act GCS          geographic coordinate system GEMS          Geographical Exposure Modeling System GIS          geographic information system GM            Geiger-Mueller GPR          ground-penetrating radar GPS          global positioning system GRIDS        Geographic Resources Information Data System GWSI          Ground Water Site Inventory HASP          Health and Safety Plan HPS          Health Physics Society HSA          Historical Site Assessment HSWA          Hazardous and Solid Waste Amendments HRS          Hazard Ranking System HTD          hard-to-detect HWP          hazard work permit IAEA          International Atomic Energy Agency ICP          inductively coupled plasma ICP-AES/MS    inductively coupled plasma-atomic emission spectrometry/mass spectrometry ICP-MS        inductively coupled plasma mass spectrometer IEEE          Institute of Electrical and Electronics Engineers NUREG-1575, Revision 2                      xxiv                              May 2020 DRAFT FOR PUBLIC COMMENT                                        DO NOT CITE OR QUOTE
 
IR-MS        isotope ratio mass spectrometer ISGS        in situ gamma spectroscopy ISI          Information System Inventory ISO          International Organization for Standardization IV          independent verification JSA          job safety analysis KPA          kinetic phosphorescence analysis LA-ICP-AES  laser ablation-inductively coupled plasma-atomic emission spectrometry LA-ICP-MS    laser ablation-inductively coupled plasma-mass spectrometry LANL        Los Alamos National Laboratory LBGR        lower bound of the gray region LCD          liquid crystal display LCDR        Lieutenant Commander LLD          lower limit of detection LLNL        Lawrence Livermore National Laboratory LLRWPA      Low-Level Radioactive Waste Policy Act, as Amended LSC          liquid scintillation counter Lt.          Lieutenant (Air Force)
LT          Lieutenant (Navy)
Lt. Col. Lieutenant Colonel MARLAP      Multi-Agency Radiation Laboratory Analytical Protocols (Manual)
MARSAME      Multi-Agency Radiation Survey and Assessment of Materials and Equipment (Manual)
MARSSIM      Multi-Agency Radiation Survey and Site Investigation Manual MCA          multichannel analyzer MDA          minimum detectable activity MDC          minimum detectable concentration MDCR        minimum detectable count rate MDER        minimum detectable exposure rate MDLEST      Mobile Demonstration Laboratory for Environmental Screening Technologies MED          Manhattan Engineering District MeV          megaelectron volt MQC          minimal quantifiable concentration MQO          Measurement Quality Objectives MS          mass spectrometry MS/MD        matrix spike/matrix duplicate NAREL        National Air and Radiation Environmental Laboratory NARM        naturally occurring and accelerator produced radioactive material NCAPS        National Corrective Action Prioritization System NCP          National Contingency Plan NCRP        National Council on Radiation Protection and Measurements NIST        National Institute of Standards and Technology May 2020                                  xxv                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                      DO NOT CITE OR QUOTE
 
NORM          naturally occurring radioactive material NPDC          National Planning Data Corporation NPDES        National Pollutant Discharge Elimination System NPL          National Priorities List NRC          U.S. Nuclear Regulatory Commission NWPA          Nuclear Waste Policy Act NWWA          National Water Well Association ODES          Ocean Data Evaluation System ORISE        Oak Ridge Institute for Science and Education ORNL          Oak Ridge National Laboratory OSHA          U.S. Occupational Safety and Health Administration OSL          optically stimulated luminescence OSLNs        optically stimulated luminescence devices sensitive to neutrons PAEC          potential alpha energy concentration PCi          picocurie PE            performance evaluation PERALS        photon electron rejecting alpha liquid scintillator PIC          pressurized ionization chamber PMT          photomultiplier tube PPE          personal protective equipment QA            quality assurance QAM          Quality Assurance Manual QAPP          Quality Assurance Project Plan QC            quality control QMP          Quality Management Plan RAGS/HHEM    Risk Assessment Guidance for Superfund/Human Health Evaluation Manual RAS          Remedial Action Support RASP          Radiological Affairs Support Program RCRA          Resource Conservation and Recovery Act RCRIS        Resource Conservation and Recovery Information System RFI/CMS      RCRA Facility Investigation/Corrective Measures Study RFP          Request for Proposal RI/FS        Remedial Investigation/Feasibility Study ROD          Record of Decision RODS          Records of Decision System RSS          Ranked Set Sampling RSSI          Radiation Survey and Site Investigation RWP          radiation work permit SADA          Visual Sample Plan and Spatial Analysis and Decision Assistance SAP          Sampling and Analysis Plan SARA          Superfund Amendments and Reauthorization Act SDWA          Safe Drinking Water Act SFMP          Surplus Facilities Management Program NUREG-1575, Revision 2                    xxvi                                May 2020 DRAFT FOR PUBLIC COMMENT                                          DO NOT CITE OR QUOTE
 
SOPs        Standard Operating Procedures SOR          sum of the ratios SOW          statement of work SPP          systematic planning process SRS          simple random sampling STORET      Storage and Retrieval for Water Quality Data TED          total effective dose TEDE        total effective dose equivalent TENORM      technologically enhanced naturally occurring radioactive material TIMS        thermal ionizing mass spectrometry TLD          thermoluminescent dosimeter TOF-MS      time-of-flight mass spectrometry TRU          transuranic TSCA        Toxic Substances Control Act TVA          Tennessee Valley Authority UBGR        upper boundary of the gray region UCL          upper confidence limit UFP          Uniform Federal Policy UFP-QAPP    Uniform Federal Policy for Quality Assurance Project Plans UFP-QS      Uniform Federal Policy for Implementing Environmental Quality Systems UMTRCA      Uranium Mill Tailings Radiation Control Act USGS        United States Geological Survey USPHS        United States Public Health Service USRADS      Ultrasonic Ranging and Data System UXO          unexploded ordnance VOCs        volatile organic compounds WATSTORE    National Water Data Storage and Retrieval System WL          working level WQX          Water Quality Exchange WRS          Wilcoxon Rank Sum WSR          Wilcoxon signed rank WT          Wilcoxon test May 2020                                  xxvii                NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                      DO NOT CITE OR QUOTE
 
Symbols, Nomenclature, and Notations
<            less than
>            greater than less than or equal to greater than or equal to
&deg;            degrees (angle or temperature)
%            percent 1          statistical power of a hypothesis test Type I decision-error rate Q            alpha used for the quantile test S            alpha scintillation survey meter a            half-width of a rectangular or triangular probability distribution A            area A            overall sensitivity of a measurement Ac            actinium (isotope listed: 228Ac)
AEA          area of elevated activity ALi          action level value an individual radionuclide (i = 1, 2, , n)
ALmeas,mod    modified action level for the radionuclide being measured when it is used as a surrogate for other radionuclide(s)
ALmeas        action level for the radionuclide being measured ALinfer      action level for the inferred radionuclide (in surrogate measurements)
Am            area factor Am            americium (isotope listed: 241Am)
AS            surface activity Type II decision-error rate b            background count rate bi            the average number of counts in the background interval (scanning)
B            mean background counts Be            beryllium (isotope listed: 7Be)
Bi            bismuth (isotopes listed: 210Bi, 212Bi, 214Bi)
Bq            becquerel S            gamma scintillation (gross)
C            carbon (isotope listed: 14C)
C            radionuclide concentration or activity C            constant number of background counts
+      number of gross counts Ci            curie Ci            concentration value an individual radionuclide (i = 1, 2, , n)
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ci          sensitivity coefficient ci(xi)      component of the uncertainty in y due to xi Cinfer/Cmeas ratio of amount of the inferred radionuclide to that of the measured surrogate radionuclide CS          concentration for the surrogate radionuclide
&deg;C          degrees Celsius cm          centimeter cm2          square centimeter cm3          cubic centimeter Cd          cadmium (isotope listed: 109Cd)
Co          cobalt (isotopes listed: 57Co, 60Co) cpm          counts per minute Cr          chromium (isotope listed: 51Cr)
Cs          cesium (isotope listed: 137Cs)
CsI(Tl)      cesium iodide (thallium activated)
CZT          cadmium-zinc telluride estimate of the mean concentration of residual radioactive material in the survey unit shift (width of the gray region, UBGR-LBGR)
/          relative shift ti          the observation interval d            parameter in the Stapleton Equation for the critical net signal width of the detector in the direction of the scan d          detectability index (scanning)
DCGL gross  derived concentration guideline level for a gross measurement DCGL      derived concentration guideline level of the ith component leading to dose or risk DCGLmin      lowest of the derived concentration guideline levels DCGLS-mod    modified derived concentration guideline level of the surrogate radionuclide DCGLS-unmod  derived concentration guideline level of the surrogate radionuclide before modification dpm          disintegrations per minute instrument efficiency s          surface (or source) efficiency t          total efficiency of the instrument eV          electron-volt E          energy of a gamma photon of concern in kiloelectron-volts (keV)
Ei          energy of a photon of interest
&deg;F          degrees Fahrenheit fi          relative fraction of activity contributed by radionuclide i to the total ft          foot (feet)
May 2020                                    xxix                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
ft3          cubic foot (feet)
Fe            iron (isotopes listed: 55Fe, 59Fe) g            gram activity GBq          gigabecquerel (1x109 becquerels)
GGAL          gross gamma action level GM            Geiger-Mueller survey meter GP          gas-flow proportional counter ( mode)
GP          gas-flow proportional counter ( mode) h            hour H            hydrogen (isotope listed: 3H [tritium])
H0            null hypothesis H1            alternative hypothesis Hz            hertz i            ith sample or measurement in a set i            observation time interval length (scanning)
I            iodine (isotopes listed: 123I, 125I, 131I) in.          inch Ir            iridium (isotope listed: 192Ir)
IS          in situ gamma spectrometry k            k-statistic for the quantile test k            coverage factor for the expanded uncertainty, U k            Poisson probability sum for  and  (assuming  and  are equal) k            critical value of the sign test K            potassium (isotope listed: 40K)
Kd            distribution coefficient kBq          kilobecquerel (1x103 becquerels) keV          kiloelectron-volt (1x103 electron-volts) kg            kilogram km            kilometer kQ            multiple of the standard deviation defining yQ, usually chosen to be 10 L            length L            liter L            grid size spacing LC            critical level LD            detection limit LEA          revised spacing of the systematic pattern LaBr          lanthanum bromide lb            pound micro (106) true mean NUREG-1575, Revision 2                        xxx                                  May 2020 DRAFT FOR PUBLIC COMMENT                                          DO NOT CITE OR QUOTE
 
theoretical mean of a population distribution (en /)air  mass energy absorption coefficient in air centimeters squared per gram (cm2/g)
Bq          microbecquerel Ci          microcuries R          microroentgen (1x106 roentgen)
Sv          microsievert m            number of reference measurements (WRS test or Quantile test) m            number of ranking categories adjusted reference sample measurements m            meter m2          square meter Mi          total amount of [dose counts, activity, etc.]
mBq          millibecquerels MDCRsurveyor required number of net source counts MeV          megaelectron-volt (1x106 electron-volt) mg          milligram(s) mGy          milligray mm          millimeter(s)
Mn          manganese (isotope listed: 54Mn)
M/R          mass-to-charge ratio mR          milliroentgen mrad        millirad mrem        millirem (1x103 rem) mSv          milliseivert (1x103 Sv) n            number of survey unit measurements (WRS test or Quantile test) n            nth sample or measurement in a set n            number of laboratory samples (for the Ranked Set Sampling test)
N            sample size (i.e., number of data points [or samples]) for the Sign test N            number of field screening measurements (for the Ranked Set Sampling test) nEA          survey unit area divided by the maximum area corresponding to the area factor, which yields the number of measurements needed so the scan MDC is adequate Na          sodium (isotope listed: 22Na)
NaI          sodium iodide NaI(Tl)      sodium iodide (thallium activated) nBq          nanobecquerels nEA          required number of data points for assessing small areas of elevated activity ng          nanogram Ni          nickel (isotope listed: 57Ni, 63Ni)
Np          neptunium (isotope listed: 237Np)
B          non-Poisson variance component of the background count rate correction May 2020                                    xxxi                NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                        DO NOT CITE OR QUOTE
 
p            coverage probability for expanded uncertainty p            efficiency of a less than ideal surveyor (scanning)
P            probabilityr Pa            protactinium (isotopes listed: 234Pa, 234mPa)
PA            probe area Pb            lead (isotopes listed: 212Pb, 214Pb)
PC            personal computer pCi          picocurie (1x1012 curies)
PIC          pressurized ionization chamber Pm            promethium (isotope listed: 147Pm)
Po            polonium (isotopes listed: 210Po, 212Po, 214Po, 216Po) ppt          parts per trillion Pu            plutonium (isotopes listed: 238P, 239Pu, 240Pu, 241Pu) q            critical value for statistical tests density (Xi,Xj)      correlation coefficient for two input quantities, Xi and Xj r            number of cycles random number from a data set r            r-statistic for the quantile test R            ratio R            roentgen (exposure rate)
Ra            radium (isotopes listed: 224Ra, 226Ra, 228Ra)
RB            mean background count rate Ri            established ratio of the concentration of the ith radionuclinde to the concentration of the surrogate radionuclide for I = 2,n RI            mean interference count rate Rh            rhodium Rn            radon (isotopes listed: 220Rn, 222Rn)
Rnet          net counting rate Ru            ruthenium (isotope listed: 106Ru) r(xi,xj)      correlation coefficient for two input estimates, xi and xj theoretical total standard deviation of the population distribution being sampled 2            theoretical total variance of the population distribution being sampled M            theoretical measurement standard deviation of the population distribution being sampled, estimated by the combined standard uncertainty of the measurement M2          theoretical measurement variance of the population distribution being sampled MR          required measurement method standard deviation (upper limit) n            standard deviation of the net count rate result r            estimate of the measurement variability in the reference area NUREG-1575, Revision 2                        xxxii                                  May 2020 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
s            estimate of the measurement variability in the survey unit S2          theoretical sampling variance of the population distribution being sampled (Xi, Xj)      covariance for two input quantities, Xi and Xj total uncertainty s            standard deviation of the survey unit S+            Sign test statistic s(x)          sample standard deviation of the input estimate, xi 2        mean square between reference areas SC            critical value of the net instrument signal SD            mean value of the net signal that gives a specified probability, 1, of yielding an observed signal greater than its critical value SC si            minimum detectable number of net source counts in the observation interval (scanning) si,surveyor  minimum detectable number of net source counts in the observation interval by a less than ideal surveyor (scanning)
Sr            strontium (isotope listed: 90Sr)
Sv            seivert 2        mean square within reference areas t            t-test statistic t            number of less than values T            weighted sum t1/2          half-life Tc            techicium (isotopes listed: 99Tc, 99mTc)
Th            thorium (isotopes listed: 228Th: 230Th, 232Th, 234Th)
Th nat        natural thorium Tl            thalium (isotopes listed: 201Tl, 204Tl, 208Tl) tb            count time for the background ti            time interval tS            count time for the source tS+b          gross count time U            expanded uncertainty U            uranium (isotopes listed: 234U, 235U, 238U)
U nat        natural uranium u(xi)        standard uncertainty of the input estimate, xi u(xi)/ l xi l relative standard uncertainty of xi u(xi,xj)      covariance of two input estimates, xi and xj uc(y)        combined standard uncertainty of y uc(y)/y      relative combined standard uncertainty of the output quantity for a particular measurement uc2(y)        combined variance of y ui(y)        component of the combined standard uncertainty, uc(y), generated by the standard uncertainty of the input estimate xi, u(xi), multiplied by the sensitivity coefficient, ci May 2020                                    xxxiii                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
uM            measurement method uncertainty uMR          required measurement method uncertainty MR          required relative measurement method uncertainty (xi)        relative standard uncertainty of a nonzero input estimate, xi, for a particular measurement. (xi) = u(xi)/xi (z)          cumulative normal distribution function V            volt(s) scan speed 2
variance W            physical probe area Wr            sum of the ranks of the (adjusted) reference measurements (WRS test)
Ws            sum of the ranks of the (adjusted) sample measurements (WRS test)
WS            weighted instrument sensitivity x            estimate of the input quantity, X x            reference area measurement sample mean X            maximum length X[k]I        survey unit measurements results of the individual samples Xi            an input quantity xC            the critical value of the response variable, x xQ            minimum quantifiable value of the response variable, x y            year y            estimate of the output quantity for a particular measurement, Y Y            maximum width Y            yttrium Y            output quantity, measurand yC            critical value of the concentration yD            minimum detectable concentration (MDC) yQ            minimum quantifiable concentration (MQC) yd            yard yd3          cubic yard z            adjusted reference area measurements Z            atomic number z1-          (1  )-quantile of the standard normal distribution z1-          (1  )-quantile of the standard normal distribution ZnS(Ag)      zinc sulfide (silver activated)
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CONVERSION FACTORS To Convert                                                  To Convert To            Multiply By                                To          Multiply By From                                                      From acre                hectare            0.405              meter (m)          inch              39.4 m2                  4,050                                  mile              0.000621 ft2                43,600              m2                acre              0.000247 Bq                  Ci                  2.7x10-11                              hectare          0.0001 dps                1                                      ft2              10.8 pCi                27                                    square mile      3.86x10-7 Bq/kg                pCi/g              0.027              m3                liter            1,000 Bq/m2                dpm/100 cm2        0.60                mrem              mSv              0.01 Bq/m3                Bq/L                0.001              mrem/y            mSv/y            0.01 pCi/L              0.027              mSv                mrem              100 centimeter          inch                0.394              mSv/y              mrem/y            100 (cm)
Ci                  Bq                  3.70x1010          ounce (oz)        L                0.0296 pCi                1x1012              pCi                Bq                0.037 dps                  dpm                60                                    dpm              2.22 pCi                27                  pCi/g              Bq/kg            37 dpm                  dps                0.0167              pCi/L              Bq/m3            37 pCi                0.451              rad                Gy                0.01 gray (Gy)            rad                100                rem                mrem              1,000 hectare              acre                2.47                                  mSv              10 liter (L)            cm3                1000                                  Sv                0.01 m3                  0.001              seivert (Sv)      mrem              100,000 ounce oz            33.8                                  mSv              1,000 (fluid) rem              100 Abbreviations: m = meter; ft = foot; Bq = becquerel; Ci = curie; dps = decays per second; pCi = picocurie; kg =
kilogram; g = gram; L = liter; cm = centimeter; in. = inch; dpm = decays per minute; oz = ounce; mrem = millirem; mSv
= millisievert; y = year; Gy = gray; Sv = sievert.
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MARSSIM                                                                                    Introduction 1                                        1 INTRODUCTION 2
 
==1.1    Purpose and Scope==
of MARSSIM 3 Radioactive materials have been produced, processed, used, and stored at thousands of sites 4 throughout the United States. Many of them at one time had or now have residual radioactive 5 material in excess of natural background. The sites range in size from Federal weapons-6 production facilities covering hundreds of square kilometers to the nuclear medicine 7 departments of small hospitals. Owners and managers would like to find and remove any 8 excess residual radioactive material and release these sites for restricted use or for unrestricted 9 public use.
10 The U.S. Environmental Protection Agency (EPA), the U.S. Nuclear Regulatory Commission 11 (NRC), and the U.S. Department of Energy (DOE), and the U.S. Department of Defense (DoD) 12 are responsible for the release of federally controlled sites after cleanup. Such sites include 13 DOE and DoD sites, sites licensed by the NRC and its Agreement States, and former 14 unlicensed industrial facilities that handled ores containing radioactive materials that are 15 addressed under Federal or State regulatory programs.
16 The Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) provides a 17 nationally consistent consensus approach to conducting radiation surveys and investigations at 18 sites with the potential for residual radioactive material. This approach is both scientifically 19 rigorous and flexible enough to be applied to a diversity of site cleanup conditions.
20 To release a site after remediation, it is normally necessary to demonstrate to the responsible 21 Federal or State agency that the cleanup effort was successful and that the release criteria 22 (specific regulatory limits) were met. In MARSSIM, the Final Status Survey (FSS) provides this 23 demonstration. This manual assists site personnel or others in performing or assessing such a 24 demonstration. (MARSSIM may also serve to guide or monitor other types of remediation 25 efforts.)
26 As illustrated in Figure 1.1, the demonstration of compliance with respect to conducting surveys 27 is comprised of three interrelated parts:
28 I. Translate: Translating the cleanup/release criteria (e.g., mSv/y, mrem/y, specific risk) into 29    corresponding derived concentration guideline levels (e.g., Bq/kg or pCi/g in soil) through 30    the use of environmental pathway modeling.
31 II. Measure: Acquiring scientifically sound and defensible site-specific data on the levels and 32    distribution of residual radioactive material, as well as levels and distribution of radionuclides May 2020                                          1-1                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Introduction                                                                                        MARSSIM 1      present in the background, by employing suitable field and/or laboratory measurement 2      techniques. 1 3 III. Decide: Determining that the data obtained from sampling support the conclusion that the 4      site meets the release criteria, within an acceptable degree of uncertainty, through 5      application of a statistically based decision rule.
Release Criteria Translate                          Measure                            Decide Default Modeling or                              Survey Interpret Results, Site-Specific Modeling                        &
Statistical Test Sample (DCGLs)
MARSSIM 6
7 Figure 1.1: Compliance Demonstration 8 MARSSIM provides standardized and consistent approaches for planning, conducting, 9 evaluating, and documenting environmental radiological surveys, with a specific focus on the 10 FSSs that are carried out to demonstrate compliance with cleanup regulations. The MARSSIM 1
Measurements include field and laboratory analyses; however, MARSSIM leaves detailed discussions of laboratory sample analyses to another manual (i.e., a companion document, the Multi-Agency Radiation Laboratory Analytical Protocols [MARLAP] manual).
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MARSSIM                                                                                Introduction 1 process gathers comprehensive technical informationspecifically for II and III aboveon 2 residual radioactive material in surface soils and on building surfaces. This information is used 3 in a performance-based approach for demonstrating compliance with a dose- or risk-based 4 regulation. This approach includes processes that identify data quality needs and may reveal 5 limitations on the data that can be collected from a survey. MARSSIMs approach supports 6 decision-making at sites with residual radioactive material in surface soil and on building 7 surfaces. In particular, MARSSIM describes generally acceptable approaches for the following:
8
* planning and designing scoping, characterization, remediation-support, and FSSs for sites 9      with residual radioactive material in surface soil and on building surfaces 10
* Historical Site Assessment (HSA) 11
* quality assurance/quality control (QA/QC) in data acquisition and analysis 12
* conducting surveys 13
* field and laboratory methods and instrumentation, and interfacing with radiation laboratories 14
* statistical hypothesis testing, and the interpretation of statistical data 15
* documentation 16 Table 1.1 summarizes the scope of MARSSIM. Several issues related to releasing sites are 17 beyond the scope of MARSSIM. These include the translation of dose or risk standards into 18 radionuclide-specific concentrations or demonstrating compliance with ground water or surface 19 water regulations. MARSSIM can be applied to surveys performed at vicinity propertiesthose 20 not under Government or licensee controlbut the decision to apply MARSSIM at vicinity 21 properties is a regulatory decision outside the scope of MARSSIM. Information on designing, 22 implementing, and assessing radiological surveys of materials and equipment is presented in 23 the Multi-Agency Radiation Survey and Assessment of Materials and Equipment (MARSAME) 24 supplement to MARSSIM. The potential presence of residual radioactive material in other media 25 (e.g., subsurface soil, ground water) is not addressed by MARSSIM. MARSSIMs main focus is 26 on FSSs, so the processes in this manual may follow remediation activities that remove below-27 surface residual radioactive material. Therefore, some of the reasons for limiting the scope of 28 the document to surface soils and building surfaces include 29
* Residual radioactive material is limited to these media for many sites following remediation.
30
* Because many sites have surface soil and building surface residual radioactive material as 31      the leading source of exposure to radiation, existing computer models used for calculating 32      the concentrations based on dose or risk generally consider only surface soils or building 33      surfaces as a source term.
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Introduction                                                                                    MARSSIM 1 Table 1.1: Scope of MARSSIM Within Scope of MARSSIM                              Beyond Scope of MARSSIM Technical        MARSSIM provides technical,          Regulation    MARSSIM does not set new Information      performance-based guidance                          regulations or requirements, or on conducting radiation surveys                    address non-technical issues and site investigations,                            (e.g., legal or policy) for site remediation and restoration                        cleanup. Release criteria will be activities, and demonstration of                    provided rather than calculated compliance with dose- or risk-                      using MARSSIM.
based regulations. MARSSIM includes a framework for developing a phased approach to site investigations that include stakeholder involvement, and which emphasizes the development of the final status survey (FSS) for site release.
Tool Box        MARSSIM can be thought of as        Tool Box      Many topics are beyond the an extensive tool box with many                    scope of MARSSIM. For componentssome within the                          example text of MARSSIM, others by
* a public participation program reference.
* staging, classification, packaging, and transportation of wastes for disposal
* remediation and stabilization techniques
* training Stakeholder      MARSSIM encourages                  Stakeholder    Specific guidance is determined Involvement      stakeholder involvement but          Involvement    by the individual Federal and does not provide specific                          State agencies.
guidance.
Measurement      The information given in            Procedure      The approaches suggested in MARSSIM is performance-                            MARSSIM vary depending on based and directed toward                          the various site data needs acquiring site-specific data and                    there are no set procedures for goals.                                              sample collection, measurement techniques, storage, or disposal established in MARSSIM.
Modeling        The interface between                Modeling      Environmental pathway environmental pathway                              modeling and ecological modeling and MARSSIM is an                          endpoints in modeling are important survey design                            beyond the scope of MARSSIM.
consideration addressed in MARSSIM.
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MARSSIM                                                                                        Introduction Within Scope of MARSSIM                              Beyond Scope of MARSSIM Soil and        The two main media of interest      Other Media    MARSSIM does not cover other Buildings        in MARSSIM are surface soil                        media, including construction and building surfaces affected                      materials, equipment, by residual radioactive material.                  subsurface soil, surface or subsurface water, biota, air, sewers, or sediments.
Final Status    The focus of MARSSIM is on          Instruments    MARSSIM does not recommend Survey          the FSS, as this is the deciding    and Radiation  the use of any specific radiation factor in judging whether the        Detection      detection equipmentthere is site meets the restricted or        Equipment      too much variability in the types unrestricted release criteria.                      of radiation sites.
Radiation        MARSSIM considers only              Chemicals      MARSSIM does not consider radiation-derived hazards.                          any hazards posed by chemicals.
Remediation      MARSSIM assists users in            Remediation    MARSSIM does not discuss Method          determining when sites are          Method        selection and evaluation of ready for an FSS and provides                      remediation alternatives, public information on how to determine                    involvement, legal if remediation was successful.                      considerations, and policy decisions related to planning.
Data Quality    MARSSIM presents a                  DQO Process    MARSSIM does not provide Objectives      systemized approach for                            prescriptive or default DQOs.
(DQO)            designing surveys to collect Process          data needed for making decisions, such as whether to release a site.
Data Quality    MARSSIM provides a set of            DQA            MARSSIM does not prescribe a Assessment      statistical tests for evaluating                    statistical test for use at all sites.
(DQA)            data and lists alternate tests that may be applicable at specific sites.
Radon            MARSSIM does address                Radon          MARSSIM does not include Assessment      measurements of radon                Assessment    measurements of radon in (concentration or flux) at sites                    ambient air, air emissions, with the immediate radon                            effluents, water, or indoor air at parents present because of                          sites with none of the immediate previous site operations.                          radon parents present because of previous site operations.
1 MARSSIM also recognizes that there may be other factors that have an impact on designing 2 surveys, such as cost or stakeholder concerns. Guidance on how to address these specific 3 concerns is outside the scope of MARSSIM. Unique site-specific cases may arise that require a 4 modified approach beyond what is presently described in MARSSIM. This includes examples 5 such as May 2020                                            1-5                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Introduction                                                                            MARSSIM 1
* sites affected by naturally occurring radioactive material (NORM) or technically enhanced 2    naturally occurring radioactive material (TENORM) in which the concentrations 3    corresponding to the release criteria are close to the variability of the background 4
* sites where a reference background cannot be established 5 However, the process of planning, implementing, assessing, and making decisions about a site 6 described in MARSSIM is applicable to all sites, even if the examples in this manual do not 7 meet a sites specific objectives.
8 Of MARSSIMs many topics, the Data Quality Objective (DQO) approach to data acquisition and 9 analysis and the Data Quality Assessment (DQA) for determining that data meet stated 10 objectives are a consistent theme throughout the manual. The DQO process and DQA 11 approach, described in Chapter 2, present a scientific, common-sense method for designing 12 and conducting surveys and making best use of the obtainable information. A formal framework 13 for systematizing the planning of data acquisition surveys can ensure that the information can 14 support important decisions, such as whether to release a particular site following remediation.
15 DQOs must be developed on a site-specific basis. The approaches presented in MARSSIM may 16 not meet the DQOs at every site, so other methods may be used to meet site-specific DQOs, as 17 long as an equivalent level of performance can be demonstrated.
18 1.2    Structure of the Manual 19 Chapter 2 provides an overview of the Radiation Survey and Site Investigation (RSSI) process.
20 Figures 2.4 through 2.8 are flowcharts that summarize the steps taken and decisions made in 21 the process. Chapter 3 provides instructions for performing an HSAa detailed investigation to 22 collect existing information on the site or facility and to develop a conceptual site model. The 23 results of the HSA are used to plan surveys, perform measurements, and collect additional 24 information at the site. Chapter 4 covers issues that arise in all types of surveys. Detailed 25 information on performing specific types of surveys is included in Chapter 5. Information on 26 selecting the appropriate measurement method combining instruments and measurement 27 techniques is included in Chapters 6 and 7. Chapter 6 discusses direct measurements and 28 scanning surveys, and Chapter 7 discusses sampling and sample preparation for laboratory 29 measurements. The interpretation of survey results is described in Chapter 8.
30 MARSSIM also contains several appendices to provide additional information on specific topics.
31 Appendix A presents an example of how to apply the MARSSIM process to a specific site 32 through an FSS. Appendix B describes a simplified procedure for compliance demonstration 33 that may be applicable at certain types of sites. Appendix C summarizes the regulations and 34 requirements associated with radiation surveys and site investigations for each of the agencies 35 involved in the development of MARSSIM. Detailed information on the EPA Quality System is in 36 Appendix D. The ranked set sampling approach, a form of double sampling that can be useful 37 for hard-to-detect radionuclides, is in Appendix E. Appendix F describes the relationships 38 among MARSSIM; the Comprehensive Environmental Response, Compensation, and Liability 39 Act (CERCLA); and the Resource Conservation and Recovery Act (RCRA). Sources of 40 information used during site assessment are listed in Appendix G. Appendix H describes field NUREG-1575, Revision 2                            1-6                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                                  Introduction 1 survey and laboratory analysis equipment that may be used for radiation surveys and site 2 investigations. Appendix I offers tables of statistical data and supporting information for 3 interpreting survey results described in Chapter 8. The derivation of the alpha scanning 4 detection limit calculations used in Chapter 6 is described in Appendix J. Comparison tables 5 for QA documents are in Appendix K. Appendix L includes guidance for the use of stem and 6 leaf displays and quantile plots. Instructions for the calculation of power curves are included in 7 Appendix M. Appendix N includes three illustrative examples demonstrating the potential 8 consequences of using methods with different levels of precision for planning and designing an 9 FSS and for actually performing the FSS. Appendix O provides additional information about the 10 Wilcoxon Rank Sum test (WRS) and Sign test and illustrates examples of the derived 11 concentration guideline level (DCGL) determinations.
12 MARSSIM is presented in a modular format, with each module containing information on 13 conducting specific aspects of, or activities related to, the survey process. Followed in order, 14 each module leads to the generation and implementation of a complete survey plan. Although 15 this approach may involve some overlap and redundancy in information, it also allows many 16 users to concentrate only on those portions of the manual that apply to their own particular 17 needs or responsibilities. The procedures within each module are listed in order, and options 18 are provided to let the user skip portions of the manual that may not be applicable to a specific 19 site. Where appropriate, checklists condense and summarize major points in the process. The 20 checklists may be used to verify that every suggested step is followed or explain why a step was 21 not needed.
22 MARSSIM contains a simplified procedure (see Appendix B) that many users of radioactive 23 materials may be able to employ to demonstrate compliance with the release criteriawith the 24 approval of the responsible regulatory agency. Sites that may qualify for simplified release 25 procedures are those in which the radioactive materials used were 26
* of relatively short half-life (e.g., t1/2  120 days) and have since decayed to insignificant 27    quantities 28
* kept only in small enough quantities so as to be exempted or not requiring a specific license 29    from a regulatory authority 30
* used or stored only in the form of non-leaking sealed sources 31
* combinations of the above 32 1.3    Use of the Manual 33 Potential users of this manual are Federal, State, and local government agencies with 34 regulatory authority and control of residual radioactive material in the environment; their 35 contractors; and other parties, such as organizations with licensed authority to possess and use 36 radioactive materials. The manual is intended for a technical audience having knowledge of 37 radiation health physics and statistics, as well as experience with the practical applications of 38 radiation protection. An understanding of instrumentation and methodologies and expertise in 39 planning, approving, and implementing surveys of environmental levels of radioactive material is May 2020                                            1-7                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Introduction                                                                            MARSSIM 1 assumed. This manual has been written so that individuals responsible for planning, approving, 2 and implementing radiological surveys will be able to understand and apply the information 3 provided here. Certain situations and sites may require consultation with personnel with specific 4 types of expertise and experience.
5 MARSSIM uses the word should as a recommendation, not as a requirement. Each 6 recommendation in this manual is not intended to be taken literally and applied at every site.
7 MARSSIMs survey planning documentation will address how to apply the process on a site-8 specific basis.
9 As previously stated, MARSSIM supports compliance with dose- or risk-based regulations. The 10 translation of the regulatory dose limit to a corresponding concentration level is not addressed in 11 MARSSIM, so the information in this manual is applicable to a broad range of regulations, 12 including concentration-based regulations. The terms dose, risk, and dose-based and risk-13 based regulation are used throughout the manual, but these terms are not intended to limit the 14 use of the manual.
Note that Federal or State agencies that can approve a demonstration of compliance may support requirements that differ from what is presented in this version of MARSSIM. It is essential, therefore, that the persons carrying out the surveys remain in close communication with the proper Federal or State regulatory authorities throughout the compliance demonstration process.
15 1.4    Missions of the Federal Agencies Producing MARSSIM 16 MARSSIM is the product of a multi-agency workgroup with representatives from EPA, NRC, 17 DOE, and DoD. This section briefly describes the missions of the participating agencies.
18 Regulations and requirements governing site investigations for each of the agencies associated 19 with radiation surveys and site investigations are presented in Appendix C.
20 1.4.1    U.S. Environmental Protection Agency 21 The mission of the EPA is to improve and preserve the quality of the environment, on both 22 national and global levels. The EPAs scope of responsibility includes implementing and 23 enforcing environmental laws, setting guidelines, monitoring pollution, performing research, and 24 promoting pollution prevention. EPA Headquarters maintains overall planning, coordination, and 25 control of EPA programs, and EPAs 10 regional offices are responsible for executing EPAs 26 programs within the boundaries of each region. EPA also coordinates with State and local 27 governments pollution control activities and supports further research and development.
28 1.4.2    U.S. Nuclear Regulatory Commission 29 The mission of the NRC is to ensure adequate protection of public health and safety, the 30 common defense and security, and the environment in the use of certain radioactive materials in 31 the United States. The NRCs scope of responsibility includes regulation of commercial nuclear 32 power reactors; nonpower research, test, and training reactors; fuel cycle facilities; medical, NUREG-1575, Revision 2                            1-8                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                                              Introduction 1 academic, and industrial uses of nuclear materials; and the transport, storage, and disposal of 2 nuclear materials and waste. The Energy Reorganization Act of 1974 and the Atomic Energy 3 Act of 1954, as amended, provide the foundation for regulation of the Nations commercial use 4 of radioactive materials.
5 1.4.3  U.S. Department of Energy 6 The mission of the DOE is to develop and implement a coordinated national energy policy to 7 ensure the availability of adequate energy supplies and to develop new energy sources for 8 domestic and commercial use. In addition, DOE is responsible for the development, 9 construction, and testing of nuclear weapons for the U.S. Military. DOE is also responsible for 10 managing the low- and high-level radioactive wastes generated by past nuclear weapons and 11 research programs and for constructing and maintaining a repository for civilian radioactive 12 wastes generated by commercial nuclear reactors. DOE has the lead in remediating facilities 13 and sites previously used in atomic energy programs.
14 1.4.4  U.S. Department of Defense 15 The global mission of the DoD is to provide for the defense of the United States. In doing this, 16 DoD is committed to protecting the environment. Each military service has specific regulations 17 addressing the use of radioactive sources and the development of occupational health 18 programs and radiation protection programs. The documents describing these regulations are 19 used as guidance in developing environmental radiological surveys within DoD and are 20 discussed in Appendix C.
21 In accordance with section 91b of the Atomic Energy Act of 1954, as amended, DoD (including 22 separate military services) has authority to acquire nuclear reactor systems and special nuclear 23 materials. Additionally, DoD (including separate military services) is the lead federal agency for 24 environmental remediation under several federal regulatory programs.
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MARSSIM                                Overview of the Radiation Survey and Site Investigation Process 1              2 OVERVIEW OF THE RADIATION SURVEY AND SITE 2                                        INVESTIGATION PROCESS 3 2.1    Introduction 4 The purpose of the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) is 5 to provide a standardized approach to demonstrating compliance with release criteria. 1 This 6 chapter provides a brief overview of the Radiation Survey and Site Investigation (RSSI) process, 7 several important aspects of this process, and its underlying principles. The purpose of this 8 chapter is to provide the overview information required to understand the rest of this manual.
9 The concepts introduced here are discussed in detail throughout the manual.
10
* Section 2.2 introduces and defines key terms used throughout the manual. Some of these 11    terms may be familiar to the MARSSIM user, while others are new terms developed 12    specifically for this manual.
13
* Section 2.3 describes the flow of information used to decide whether a site or facility 14    complies with release criteria. The section describes the framework that is used to 15    demonstrate compliance with the release criteria and is the basis for all information 16    presented in this manual. The decision-making process is broken down into four phases:
17    (1) planning, (2) implementation, (3) assessment, and (4) decision-making.
18
* Section 2.4 introduces the RSSI process, which can be used for compliance demonstration 19    at many sites. The section describes a series of surveys that form the core of this process.
20    Each survey has specified goals and objectives to support a final decision on whether a site 21    or facility complies with the appropriate criteria. Flow diagrams are provided showing how 22    the different surveys support the overall process, along with descriptions of the information 23    obtained through each type of survey.
24
* Section 2.5 presents major considerations that relate to the decision-making and survey-25    design processes. This section, in addition to the examples discussed in detail throughout 26    the manual, focuses on residual radioactive material in surface soils and on building 27    surfaces. Recommended survey designs for demonstrating compliance are presented, 28    along with the rationale for selecting these designs.
29
* Section 2.6 recognizes that the methods presented in MARSSIM may not represent the 30    most appropriate survey design at all sites. Some alternate methods for applying the RSSI 31    process are discussed. Different methods for demonstrating compliance that are technically 32    defensible may be developed with the approval of the responsible regulatory agency.
33 MARSSIM provides an approach that is technically defensible and flexible enough to be applied 34 to a variety of site-specific conditions. Applying this approach to dose- or risk-based criteria 1
MARSSIM uses the word should as a recommendation, not as a requirement. Each recommendation in this manual is not intended to be taken literally and applied at every site. MARSSIMs survey planning documentation will address how to apply the process on a site-specific basis.
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Overview of the Radiation Survey and Site Investigation Process                          MARSSIM 1 provides a consistent approach to protecting human health and the environment. The manuals 2 performance-based approach to decision-making provides the flexibility needed to address 3 compliance demonstration at individual sites.
4 2.2    Understanding Key MARSSIM Terminology and Survey Unit Classification 5 2.2.1    Key MARSSIM Terminology 6 The first step in understanding the RSSI process is accomplished by understanding this 7 manuals scope, the terminology, and the concepts. Some terms were developed specifically for 8 MARSSIM, for the purposes of this manual, while other commonly used terms were adopted.
9 This section explains some of the terms roughly in the order of their presentation in the manual.
10 The italicized terms in this section are all defined in the Glossary of this document.
11 The process described in MARSSIM begins with the premise that release criteria have already 12 been provided in terms of a measurement quantity. The methods presented in MARSSIM are 13 generally applicable and are not dependent on the value of the release criteria.
14 Release criteria are regulatory limits expressed in terms of dose (millisieverts/year or 15 millirem/year) or risk (cancer morbidity or cancer mortality) or concentrations of radioactive 16 material specified in regulations or standards. The terms release limit and cleanup standard 17 are also used to describe this term. Release criteria that are typically based on dose (e.g., total 18 effective dose [TED], committed effective dose [CED], total effective dose equivalent [TEDE], or 19 committed effective dose equivalent [CEDE]) or risk (e.g., risk of cancer incidence [morbidity] or 20 risk of cancer death [mortality]) generally cannot be measured directly.
21 Exposure pathway modeling is an analysis of various exposure pathways and scenarios used to 22 convert dose or risk into concentration. Exposure pathway modeling is used to calculate a 23 radionuclide-specific predicted concentration of radioactive material or surface area 24 concentration of radioactive material of specific nuclides that could result in a dose or risk equal 25 to the release criteria within the required performance period. In this manual, such a 26 concentration is termed the derived concentration guideline level (DCGL). In many cases, 27 DCGLs can be derived from applicable requirements or regulatory agency guidance based on 28 default modeling input parameters (e.g., screening-level analyses) if site conditions are 29 consistent with the underlying assumptions in the default modeling or screening analyses; in 30 other cases, it may be necessary to develop site-specific parameters. In general, the units for 31 the DCGL are the same as the units for measurements performed to demonstrate compliance 32 (e.g., becquerel/kilogram [Bq/kg] or picocurie/gram [pCi/g], becquerel/square meter [Bq/m2] or 33 decays per minute [dpm]/100 cm2). This allows direct comparisons between the survey results 34 and the DCGL. A discussion of the uncertainty associated with using DCGLs to demonstrate 35 compliance is included in Appendix D, Section D.1.6.
36 An investigation level is a derived media-specific, radionuclide-specific concentration that, if 37 exceeded, triggers some response, such as further investigation or remediation. An 38 investigation level may be used early in the process to identify areas requiring further 39 investigation; it may also be used as a screening tool during compliance demonstration to 40 identify potential problem areas. A DCGL is an example of a specific investigation level that is 41 based on the release criteria.
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MARSSIM                                Overview of the Radiation Survey and Site Investigation Process 1 While the derivation of DCGLs is outside the scope of MARSSIM, it is important to understand 2 the assumptions that underlie this derivation of DCGLs to ensure consistency with the statistical 3 approach used to demonstrate compliance with regulatory criteria. For example, the estimated 4 dose, and consequently the cleanup level or DCGL, may be sensitive to assumptions regarding 5 the lateral extent (i.e., area) of residual radioactive material for relatively small exposure areas 6 (e.g., areas that do not approximate an infinite source for external radiation exposure, or areas 7 that would not support crop cultivation in quantities consistent with the assumed annual 8 consumption rates of contaminated produce for the resident farmer scenario). Other important 9 factors may include depth of residual radioactive material, chemical and physical form of the 10 source, hydrogeological considerations, and potential exposure scenarios. For more information 11 on environmental pathway modeling, check with your regulators guidance on the topic.
12 MARSSIM defines two potential DCGLs based on the area of residual radioactive material:
13
* Evenly distributed activityIf the residual radioactive material is evenly distributed over a 14      large area, MARSSIM looks at the average or median concentration of radioactive material 15      over the entire area. The DCGLW 2 (the DCGL used when applying the Wilcoxon Rank Sum 16      [WRS] or Sign tests; see Section 2.5.1.2) is derived based on assuming an average 17      concentration over a wide area in the exposure pathway modeling.
18
* Small areas of elevated concentrations of radioactive materialIf the residual radioactive 19      material appears as small areas of elevated concentrations of radioactive material 3 within a 20      larger area, MARSSIM also considers the results of individual measurements. The DCGLEMC 21      (the DCGL used for the elevated measurement comparison [EMC], see Section 2.5.1.1) is 22      derived separately for these small areas and generally from different exposure assumptions 23      than those used for larger areas.
24 Surface soil is the top layer of soil on a site that is available for direct exposure, growing plants, 25 resuspension of particles for inhalation, and mixing from human disturbances. Surface soil may 26 also be defined as the thickness of soil that can be measured using direct measurement or 27 scanning techniques. Historically, this layer has often been represented as the top 15 cm 28 (6 inches) of soil (40 CFR 192), but it will vary depending on radionuclide, surface 29 characteristics, measurement method, and pathway modeling assumptions. For the purposes of 30 MARSSIM, surface soil may be considered to include gravel fill, waste piles, concrete, or 31 asphalt paving. Similarly, a building surface is defined as the thickness of building surface 32 material that can be measured using direct measurement or scanning techniques and will also 2
The W in DCGLW historically stood for Wilcoxon Rank Sum test, which is the statistical test recommended in MARSSIM for demonstrating compliance when the radionuclide is present in background. However, as the Sign test is also a recommended test in MARSSIM for demonstrating compliance when the radionuclide is not present in background, the term now colloquially refers to wide-area or average.
3 A small area of elevated concentration of radioactive material, or maximum point estimate of residual radioactive material, might also be referred to as a hot spot. This term has been purposefully omitted from MARSSIM because the term often has different meanings based on operational or local program concerns. As a result, there may be problems associated with defining the term and reeducating MARSSIM users in the proper use of the term.
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Overview of the Radiation Survey and Site Investigation Process                              MARSSIM 1 vary depending on radionuclide, surface characteristics, measurement technique, and pathway 2 modeling assumptions.
3 A site is any installation, facility, or discrete, physically separate parcel of land, or any building or 4 structure or portion thereof that is being considered for survey and investigation. Area is a very 5 general term that refers to any portion of a site, up to and including the entire site.
6 Remediation includes those actions that are consistent with a permanent remedy taken instead 7 of, or in addition to, removal action in the event of a release or threatened release of a 8 hazardous substance into the environment, to prevent or minimize the release of hazardous 9 substances so that they do not migrate to cause substantial danger to present or future public 10 health or welfare or the environment.
11 Decommissioning is a term for the process of safely removing a site from service, reducing the 12 concentration of residual radioactive material through remediation to a level that permits release 13 of the property, and termination of the license or other authorization for site operation.
14 A survey unit is a physical area consisting of structures or land areas of specified size and 15 shape at a site for which a separate decision will be made as to whether the unit meets the 16 release criteria. (This decision is made as a result of the final status survey [FSS]the survey in 17 the RSSI process used to demonstrate compliance with release criteria.) Survey units are 18 established to facilitate the survey process and the statistical analysis of survey data. The size 19 and shape of the survey unit are based on such factors as the potential for residual radioactive 20 material, the expected distribution of residual radioactive material, and any physical boundaries 21 (e.g., buildings, fences, roads, soil type, and surface water body) at the site. Survey units are 22 generally formed by grouping contiguous site areas with a similar use history and the same 23 classification of potential for residual radioactive material.
24 Measurement in MARSSIM is used interchangeably to mean (1) the act of using a detector to 25 determine the level or quantity of radioactive material on a surface or in a sample of material 26 removed from a media being evaluated, or (2) the quantity obtained by the act of measuring.
27 Direct measurements are obtained by placing a detector near the surface or media being 28 surveyed for a prescribed amount of time. An indication of the resulting concentration of 29 radioactive material is read out directly.
30 Scanning is a measurement technique performed by moving a portable radiation detector at a 31 specified speed and distance next to a surface to detect radiation.
32 Sampling is the process of collecting a portion of an environmental medium as being 33 representative of the locally remaining medium. The collected portion, or aliquot, of the medium 34 is then analyzed to identify the radionuclide and determine the concentration. The word sample 35 may also refer to a set of individual measurements drawn from a population whose properties 36 are studied to gain information about the entire population. The latter is primarily used for 37 statistical discussions.
38 The graded approach is defined as the process where the level of application of managerial 39 controls for an item or work is determined according to the intended use of the results and the NUREG-1575, Revision 2                              2-4                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                            Overview of the Radiation Survey and Site Investigation Process 1 degree of confidence needed in the quality of the results. To make the best use of resources for 2 decommissioning, MARSSIM places greater survey efforts on areas that have, or had, the 3 highest potential for residual radioactive material. The FSS uses statistical tests to support 4 decision-making. These statistical tests are performed using survey data from areas with 5 common characteristics, such as potential for residual radioactive material, which are 6 distinguishable from other areas with different characteristics.
7 Categorization is the act or result of separating an area or survey unit into one of two 8 categories: impacted or non-impacted. Areas that have no reasonable potential for residual 9 radioactive material are categorized as non-impacted areas. These areas have no radiological 10 impact from site operations and are typically identified early in the cleanup process. Areas with 11 some reasonable potential for residual radioactive material are categorized as impacted areas.
12 Classification is the process by which impacted areas or survey units are separated into 13 Class 1, Class 2, or Class 3 areas according to radiological characteristics. Survey unit 14 classification determines the FSS design and the procedures used to develop this design.
15 Preliminary area classifications, made earlier in the MARSSIM process, are useful for planning 16 subsequent surveys.
17 The background reference area is a geographical area from which representative reference 18 measurements are performed for comparison with measurements performed in specific survey 19 units. If the radionuclide of concern is present in the background, or if the measurement system 20 used to determine concentration in the survey unit is not radionuclide-specific, background 21 measurements are compared to the survey unit measurements to determine the concentration 22 of residual radioactive material. The site radiological reference area is defined as an area that 23 has similar physical, chemical, radiological, and biological characteristics as the survey unit(s) 24 being investigated but has not been affected by site activities (i.e., non-impacted).
25 The Data Life Cycle is the process of planning the survey, implementing the survey plan, and 26 assessing the survey results before making a decision. Survey planning uses the Data Quality 27 Objectives (DQO) Process, which is a series of logical steps to create a plan for the resource-28 effective acquisition of environmental data, to ensure that the survey results are of sufficient 29 quality and quantity to support the final decision. Measurement Quality Objectives (MQOs) are 30 the specific analytical data requirements of the DQOs. Quality assurance (QA) is an integrated 31 system of management activities involving planning, implementation, assessment, reporting, 32 and quality improvement to ensure that a process, item, or service is of the type and quality 33 needed and expected by the customer. Quality control (QC) is the overall system of technical 34 activities that measure the attributes and performance of a process, item, or service against 35 defined standards to verify that they meet the stated requirements established by the customer, 36 operational techniques, and activities that are used to fulfill requirements for quality. QA/QC 37 procedures are performed during implementation of the survey plan to collect information 38 necessary to evaluate the survey results. Data Quality Assessment (DQA) is the scientific and 39 statistical evaluation of data to determine if the data are of the right type, quality, and quantity to 40 support their intended use.
41 A systematic process and structure for quality should be established to provide confidence in 42 the quality and quantity of data collected to support decision-making. The data used in decision-May 2020                                          2-5                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                                              MARSSIM 1 making should be supported by a planning document that records how quality assurance and 2 quality control are applied to obtain the types and quality of results that are needed and 3 expected. There are several terms used to describe a variety of planning documents, some of 4 which document only a small part of the survey design process. MARSSIM uses the term 5 Quality Assurance Project Plan (QAPP) to describe a written document outlining the procedures 6 a monitoring project will use to ensure the data it collects and analyzes meets project 7 requirements. This term conforms to consensus guidance ANSI/ASQC E4-1994 (ASQC 1995) 8 and U.S. Environmental Protection Agency (EPA) guidance (EPA 2001b; EPA 2002a), and its 9 use is recommended to promote consistency. The use of the term QAPP in MARSSIM does not 10 exclude the use of other terms (e.g., Decommissioning Plan, Sampling and Analysis Plan, Field 11 Sampling Plan) to describe survey documentation, provided that the information included in the 12 documentation supports the objectives of the survey. The QAPP is a plan for obtaining data of 13 sufficient quality and quantity to satisfy data needs; it describes policy, organization, and 14 functional activities and includes DQOs and MQOs.
15 2.2.2    Classification Assessment 16 Impacted areas are divided into three classifications:
17
* Class 1 Areas: Areas that have, or had before remediation, a potential for residual 18      radioactive material (based on site operating history) or known residual radioactive material 19      (based on previous radiation surveys) above the DCGLW. Examples of Class 1 areas 20      include 21      o  site areas previously subjected to remedial actions 4 22      o  locations where leaks or spills are known to have occurred 23      o  former burial or disposal sites 24      o  waste storage sites 25      o  areas with residual radioactive material in discrete solid pieces of material and high 26          specific activity 27
* Class 2 Areas: Areas that have, or had before remediation, a potential for residual 28      radioactive material or known residual radioactive material but are not expected to exceed 29      the DCGLW. To justify changing an areas classification from Class 1 to Class 2, the existing 30      data (from the Historical Site Assessment [HSA], scoping surveys, or characterization 31      surveys) should provide a high degree of confidence that no individual measurement would 32      exceed the DCGLW. Other justifications for this change in an areas classification may be 4 Remediated areas are identified as Class 1 areas because the remediation process often results in less than 100 percent removal of the radioactive material. The residual radioactive material that remains on the site after remediation is often associated with relatively small areas with elevated levels of radioactive material. This results in a non-uniform distribution of the radionuclide and a Class 1 classification. If an area is expected to have no potential to exceed the DCGLW and was remediated to demonstrate the residual radioactive material is as low as reasonably achievable, the remediated area might be classified as Class 2 for the final status survey.
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MARSSIM                            Overview of the Radiation Survey and Site Investigation Process 1      appropriate based on the outcome of the DQO process. Examples of areas that might be 2      classified as Class 2 for the FSS include 3      o  locations where radioactive materials were present in an unsealed form (e.g., process 4          facilities) 5      o  residual radioactive material potentially along transport routes 6      o  areas downwind from stack release points 7      o  upper walls, roof support frameworks, and ceilings of some buildings or rooms subjected 8          to airborne radioactive material 9      o  areas where low concentrations of radioactive materials were handled 10      o  areas on the perimeter of former buffer or radiological control areas 11
* Class 3 Areas: Any impacted areas that are not expected to contain any residual radioactive 12      material or are expected to contain levels of residual radioactive material at a small fraction 13      of the DCGLW, based on site operating history and previous radiation surveys. To justify 14      changing an areas classification from Class 1 or Class 2 to Class 3, the existing data (from 15      the HSA, scoping surveys, or characterization surveys) should provide a high degree of 16      confidence that there is either no residual radioactive material, or that any levels of residual 17      radioactive material are a small fraction of the DCGLW. Other justifications for this change in 18      an areas classification may be appropriate based on the outcome of the DQO process.
19      Examples of areas that might be classified as Class 3 include buffer zones around Class 1 20      or Class 2 areas, and areas with very low potential for residual radioactive material but 21      insufficient information to justify a non-impacted classification.
22 Class 1 areas have the greatest potential for residual radioactive material and, therefore, 23 receive the highest degree of survey effort for the FSS using a graded approach, followed by 24 Class 2, and then by Class 3.
25 Survey units should be classified as Class 1 unless there is sufficient justification for classifying 26 the survey as Class 2 or Class 3. Likewise, the classification of a survey unit should not be 27 reduced without sufficient justification.
28 Non-impacted areas do not receive any level of survey coverage, because they have no 29 reasonable potential for residual radioactive material. Non-impacted areas are determined on a 30 site-specific basis from information collected during site identification, the HSA, and scoping and 31 characterization surveys. Examples of areas that would be non-impacted rather than impacted 32 usually include administrative, residential, or other buildings that have not contained radioactive 33 materials except such devices as smoke detectors or exit signs with sealed radioactive sources.
34 2.3    Making Decisions Based on Survey Results 35 Compliance demonstration is simply a decision as to whether a survey unit meets the release 36 criteria. For most sites, this decision is based on the results of one or more surveys. When May 2020                                          2-7                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                                        MARSSIM 1 survey results are used to support a decision, the decision maker 5 needs to ensure that the data 2 will support that decision with satisfactory confidence. Uncertainty in the survey results is 3 unavoidable, so the possibility of errors in decisions supported by the survey results is 4 unavoidable. For this reason, actions must be taken to manage the uncertainty in the survey 5 results so that sound and defensible decisions can be made. These actions include proper 6 survey planning to control known causes of uncertainty, proper application of QC procedures 7 during implementation of the survey plan to detect and control significant sources of error, and 8 careful analysis of uncertainty before the data are used to support decision-making. These 9 actions describe the flow of data throughout each type of survey and are combined in the Data 10 Life Cycle, as shown in Figure 2.1.
11 There are four phases of the Data Life Cycle:
12
* Planning Phase: The survey design is developed and documented using the DQO process.
13      QA/QC procedures are developed and documented in the QAPP. The QAPP is the principal 14      product of the planning process, which incorporates the DQOs as it integrates all technical 15      and quality aspects for the life cycle of the project, including planning, implementation, and 16      assessment. The QAPP contains plans for survey operations and provides a specific format 17      for obtaining the type and quality of data needed for decision-making. The QAPP elements 18      are presented in the order of the Data Life Cycle and are grouped into two types of 19      elements: (1) project management and (2) collection and evaluation of environmental data 20      (ASQC 1995). The DQO process is described in Appendix D and applied in Chapters 3, 4, 21      and 5 of this manual. Development of the QAPP is described in Appendix D and applied 22      throughout the RSSI process.
23
* Implementation Phase: The survey is carried out in accordance with the standard operating 24      procedures (SOPs) and QAPP, and it generates raw data. Chapters 6-7 and Appendix H 25      provide information on the selection of data collection techniques. The QA and QC 26      measurements, discussed in Chapters 6-7, also generate data and other important 27      information that will be used during the Assessment Phase.
28
* Assessment Phase: The data generated during the Implementation Phase first are verified 29      to ensure that the SOPs specified in the QAPP were followed and that the measurement 30      systems performed in accordance with the criteria specified in the QAPP. Then the data are 31      validated to ensure that the results of data collection activities support the objectives of the 32      survey as documented in the QAPP or permit a determination that these objectives should 33      be modified. The DQA process is then applied using the validated data to determine if the 34      quantity and quality of the data satisfy their intended use. The DQA process is described in 35      Appendix D and is applied in Chapter 8.
36
* Decision-making Phase: A decision is made, in coordination with the regulatory agency, 37      based on the conclusions drawn from the assessment process. The ultimate objective is to 38      make technically defensible decisions with a specified level of confidence (Chapter 8).
5 The term decision maker is used throughout this section to describe the person, team, board, or committee responsible for the final decision regarding release of the survey unit.
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MARSSIM                            Overview of the Radiation Survey and Site Investigation Process Planning Phase Plan for data collection using the Data Objectives Process and develop a Quality Assurance Project Plan Implementation Phase Collect data using documented measurement techniques and associated quality assurance and quality control activities Assessment Phase Evaluate the collected data against the survey objectives using Data Verification, Data Validation, and Data Quality Assessment Decision-Making Phase Make a technically defensible decisions with a specified level of confidence are made in coordination with regulating agencies 1
2 Figure 2.1: The Data Life Cycle 3 2.3.1  Planning Effective SurveysPlanning Phase 4 The first step in designing effective surveys is planning. The DQO process is a series of 5 planning steps based on the scientific method for establishing criteria for data quality and 6 developing survey designs (ASQC 1995, EPA 2006a, EPA 1987a, EPA 1987b). Planning 7 radiation surveys using the DQO process improves the survey effectiveness and efficiency, and 8 thereby the defensibility of decisions. Proper data collection planning minimizes expenditures by 9 eliminating unnecessary, duplicative, or overly precise data. Using the DQO process ensures 10 that the type, quantity, and quality of environmental data used in decision making will be May 2020                                            2-9                        NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                      DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                          MARSSIM 1 appropriate for the intended application. MARSSIM supports the use of the DQO process to 2 design surveys for input to both evaluation techniques (elevated measurement comparison and 3 the statistical test). The DQO process provides systematic procedures for defining the criteria 4 that the survey design should satisfy, including whether to perform scan-only surveys or scan 5 surveys in conjunction with direct measurements/sampling, what type of measurements to 6 perform, when and where to perform measurements, the level of decision errors for the survey, 7 and how many measurements to perform.
8 The level of effort associated with planning a survey is based on the complexity of the site.
9 Large and complicated sites generally receive a significant amount of effort during the planning 10 phase, while smaller sites may not require as much planning. In addition, the complexity of the 11 survey depends not only on the size of the site or survey unit, but also on the physical and 12 chemical characteristics of the site and the radioactive materials on the site. This graded 13 approach defines data quality requirements according to the type of survey being designed, the 14 risk of making a decision error based on the data collected, and the consequences of making 15 such an error. This approach provides a more effective survey design combined with a basis for 16 judging the usability of the data collected.
17 DQOs are qualitative and quantitative statements derived from the outputs of the DQO process 18 that 19
* clarify the study objective 20
* define the most appropriate type of data to collect 21
* determine the most appropriate conditions (e.g., environmental, legal, safety) for collecting 22    the data 23
* specify limits on decision errors, which will be used as the basis for establishing the quantity 24    and quality of data needed to support the decision 25 The DQO process consists of seven steps, as shown in Figure 2.2. Each step is discussed in 26 detail in Appendix D. Although all of the outputs of the DQO process are important for 27 designing efficient surveys, there are some that are referred to throughout the manual. These 28 DQOs are mentioned briefly here and are discussed in detail throughout MARSSIM and in 29 Appendix D.
30 The minimum information (outputs) required from the DQO process to proceed with the 31 methods described in MARSSIM are 32
* Classify and specify boundaries of survey units. This can be accomplished at any time but 33    must be finalized during FSS planning (Section 4.6, Section 4.9).
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MARSSIM                          Overview of the Radiation Survey and Site Investigation Process Step 1. State the problem Define the problem that motivates the study Identify the planning team, examine budget, and schedule Step 2. Identify the goal of the study State how environmental data will be used in solving the problem Identify study questions and define alternative outcomes Step 3. Identify information inputs Identify data and information needed to answer study questions Step 4. Define the boundaries of the study Specify the target population and characteristics of interest Define spatial and temporal limits and scale of inference Step 5. Develop the analytic approach Define the parameter of interest, specify the type of inference, and develop logic for drawing conclusions from the findings Statistical                                              Estimation and Other Hypothesis Testing                                            Analytical Approaches Step 6. Specify performance or Acceptance Criteria Develop performance criteria for new data being collected Develop acceptance criteria for data already collected Step 7. Develop the Detailed Plan for Obtaining Data Select the most resource effective sampling and analysis plan that satisfies the performance or acceptance criteria 1
* 2 Figure 2.2: The Data Quality Objectives Process May 2020                                          2-11                        NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                            MARSSIM 1
* Determine if Scenario A or Scenario B will be used to evaluate the survey unit. Scenario A 2    uses a null hypothesis that assumes the concentration of radioactive material in the survey 3    unit exceeds the DCGLW. Scenario A is sometimes referred to as presumed not to comply 4    or presumed not clean. Scenario B uses a null hypothesis that assumes the level of 5    concentration of radioactive material in the survey unit is less than or equal to the 6    discrimination level. Scenario B is sometimes referred to as indistinguishable from 7    background or presumed clean (Section 5.3.1).
8
* State the null hypothesis (H0). For Scenario A, the concentration of residual radioactive 9    material in the survey unit exceeds the release criteria (Section 2.5, Appendix D, 10    Section D.1.6). For Scenario B, the residual radioactive material in the survey unit does not 11    exceed the release criteria (Section 2.5, Appendix D, Section D.1.6).
12
* Specify a gray region where the consequences of decision errors are considered relatively 13    minor. For Scenario A the upper bound of the gray region is defined as the DCGLW, and the 14    lower bound of the gray region (LBGR) is a site-specific variable generally chosen to be a 15    conservative (slightly higher) estimate of the concentration of residual radioactive material 16    remaining in the survey unit and adjusted to provide an acceptable value for the relative 17    shift. For Scenario B the LBGR is the action level (AL), and the upper bound is defined by a 18    discrimination limit (DL) that can be reliably distinguished from the AL (Section 5.3.3.1, 19    Section 5.3.4.1, Appendix D, Section D.1.7.3).
20
* Define decision errors and assign their probability limits for the chosen Scenario (A or B).
21    The probability of making a Type I decision error () or a Type II decision error () is a site-22    specific variable (Section 5.3.2, Appendix D, Section D.1.6).
23
* Estimate the standard deviation of the measurements in the survey unit. The standard 24    deviation () is a site-specific variable, typically estimated from preliminary survey data.
25
* Specify the relative shift (/). The relative shift is equal to the width of the gray region ()
26    which in Scenario A is equal to (DCGLW - LBGR) and for Scenario B is equal to (DL - AL) 27    divided by an estimate of the uncertainty (). The relative shift is generally designed to have 28    a value greater than one (Section 5.3.3.2, Section 5.3.4.2).
29
* Select a survey strategy based on the measurement requirements and site classifications to 30    include one of the following:
31    o  a combination of scanning and direct measurements or sample collection and analysis 32    o  scanning only, provided that the scanning measurement system meets the detection 33        capability and uncertainty requirements of a scan-only survey design (Section 5.3.6.1, 34        Section 5.3.9) 35
* For surveys utilizing the Sign or WRS test, calculate the estimated number of measurements 36    (N) and specify the measurement locations required to demonstrate compliance. The 37    number of measurements depends on the relative shift, Type I and Type II decision error 38    rates, and the potential for small areas of elevated activity (Sections 5.3.3 and 5.3.4).
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MARSSIM                            Overview of the Radiation Survey and Site Investigation Process 1
* Determine the percentage of scanning coverage for survey units based on the assigned 2    classification of the survey unit and relative shift. Class 1 areas and survey units will have 3    scan coverage of 100 percent, while the scan coverage of Class 2 and Class 3 areas and 4    survey units will vary between 10 percent and 100 percent as a function of the relative shift 5    (Section 5.3.6).
6
* Specify the documentation requirements for the survey, including survey planning 7    documentation. Documentation supporting the decision on whether or not the site complies 8    with the release criteria is determined on a site-specific basis (Appendix D, Section D.2).
9
* Specify the required MQOs for all measurement techniques (scanning, direct measurement, 10    and sample analysis) specified in the QAPP. The MQOs are unique for each measurement 11    system (Sections 6.2-6.4).
12 MQOs are an important subset of inputs into the DQO process that define performance 13 requirements and objectives for the measurement system. MQOs that should be considered 14 include the following:
15
* Method uncertainty: Method uncertainty is the sum of the random and systematic 16    uncertainties in the measurement system. MARSSIM uses the term measurement method 17    uncertainty to refer to the predicted uncertainty of a measured value that would be 18    calculated if the method were applied to a hypothetical sample with a specified 19    concentration, typically the release limit. Reasonable values for measurement method 20    uncertainty can be predicted for a particular measurement technique based on typical 21    values for specific parameters (e.g., count time, efficiency) and previous surveys of the 22    areas being investigated. The MQO for the required measurement method uncertainty is 23    calculated based on the width of the gray region and is related to the minimum detectable 24    concentration (MDC).
25
* Detection capability: The MDC is recommended as the MQO for defining the detection 26    capability of the measurement system, which is the net response level that can be expected 27    to be seen using a detector with a fixed level of confidence. To account for cases where 28    decisions are being made based on multiple measurements, the MDC should be less than 29    50 percent of the DCGL in Scenario A and the DL in Scenario B.
30
* Range: The method range is the lowest and highest concentration of an analyte that a 31    method can accurately detect. The expected concentration range for a radionuclide of 32    concern may be an important MQO. Most radiation measurement techniques are capable of 33    measuring over a wide range of radionuclide concentrations. However, if the expected 34    concentration range is large, the range should be identified as an important measurement 35    method performance characteristic, and an MQO should be developed. The MQO for the 36    acceptable range should be a conservative estimate. This will help prevent the selection of 37    measurement techniques that cannot accommodate the actual concentration range.
38
* Specificity: Specificity is the ability of the measurement method to measure the radionuclide 39    of concern in the presence of interferences. To determine if specificity is an important MQO, 40    the planning team needs information on expected concentration ranges for the radionuclides May 2020                                            2-13                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                        MARSSIM 1    of concern and other chemical and radionuclide constituents, along with chemical and 2    physical attributes of the residual radioactive material being investigated.
3
* Ruggedness: For a project that involves field measurements that are performed in difficult or 4    variable environments, or laboratory measurements that are complex in terms of chemical 5    and physical characteristics, the measurement methods ruggedness may be an important 6    MQO. Ruggedness refers to the relative stability of the measurement techniques 7    performance when small variations in method parameter values are made. For field 8    measurements, the changes may include temperature, humidity, or atmospheric pressure.
9    For laboratory measurements, variability in sample conditions (e.g., pH) or laboratory 10    conditions may be important. To determine if ruggedness is an important measurement 11    method performance characteristic, the planning team needs detailed information on the 12    chemical and physical characteristics of the soil or surfaces being investigated and 13    operating parameters for the radiation instruments used by the measurement technique.
14 Precision, bias, representativeness and sensitivity, comparability, and completeness are the 15 Data Quality Indicators (DQIs) recommended for quantifying the amount of error for survey data 16 (EPA 2002a). These DQIs are discussed in detail in Appendix D, Section D.1.6.
17 2.3.2  Evaluating Sources of Variability in Survey ResultsImplementation Phase 18 To encourage flexibility and the use of appropriate measurement techniques for a specific site, 19 MARSSIM does not provide detailed recommendations on specific techniques to be used.
20 Instead, MARSSIM encourages the decision maker to evaluate available techniques based on 21 the survey DQOs and MQOs. Information on evaluating whether these objectives have been 22 met, such as the required measurement method uncertainty and minimum detectable 23 concentration, is provided.
24 QC programs can both lower the chances of making an incorrect decision and help the data 25 user understand the level of uncertainty that surrounds the decision (EPA 2002a). As discussed 26 previously, QC data are collected and analyzed during implementation to provide an estimate of 27 the uncertainty associated with the survey results. QC measurements (scans, direct 28 measurements, and samples) are technical activities performed to measure the attributes and 29 performance of the survey. During any survey, a certain number of measurements should be 30 taken for QC purposes.
31 2.3.3  Evaluating Survey ResultsAssessment Phase 32 Assessments of environmental data are used to evaluate whether the data meet the objectives 33 of the survey and are sufficient to determine compliance with the DCGL (EPA 1992a, EPA 34 1992b, EPA 2006a). The assessment phase of the Data Life Cycle consists of three phases:
35 data verification, data validation, and DQA.
36
* Data verification is used to ensure that the requirements stated in the planning documents 37    are implemented as prescribed (see Appendix D.4.1).
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MARSSIM                            Overview of the Radiation Survey and Site Investigation Process 1
* Data validation is used to ensure that the results of the data collection activities support the 2    objectives of the survey as documented in the QAPP or to permit a determination that these 3    objectives should be modified (see Appendix D.4.2).
4
* DQA is the scientific and statistical evaluation of data to determine if the data are of the right 5    type, quality, and quantity to support their intended use (EPA 2006a). DQA helps complete 6    the Data Life Cycle by providing the assessment needed to determine that the planning 7    objectives are achieved (see Section 8.2). Figure 2.3 illustrates where data verification, 8    data validation, and DQA fit into the Assessment Phase of the Data Life Cycle.
9 There are five steps in the DQA process:
10
* review the DQOs and survey design 11
* conduct a preliminary data review 12
* select the statistical test(s) 13
* verify the assumptions of the statistical test(s) 14
* draw conclusions from the data 15 The strength of DQA is its design that progresses in a logical and efficient manner to promote 16 an understanding of how well the data meet the intended use. The Assessment Phase is 17 described in more detail in Appendix D. Section 2.6 discusses the flexibility of the Data Life 18 Cycle and describes the use of survey designs other than those described later in MARSSIM.
19 2.3.4  Uncertainty in Survey Results 20 Uncertainty in survey results arises primarily from two sourcessurvey design errors and 21 measurement errors:
22
* Survey design errors occur when the survey design is unable to capture the complete extent 23    of variability that exists for the radionuclide distribution in a survey unit. Because it is 24    impossible in every situation to measure the concentration of residual radioactive material at 25    every point in space and time, the survey results will be incomplete to some degree. It is 26    also impossible to know with complete certainty the concentration of residual radioactive 27    material at locations that were not measured, so the incomplete survey results give rise to 28    uncertainty. The greater the natural or inherent variation in residual radioactive material, the 29    greater the uncertainty associated with a decision based on the survey results. The 30    unanswered question is, How well do the survey results represent the true level of residual 31    radioactive material in the survey unit?
32
* Measurement errors create uncertainty by masking the true level of residual radioactive 33    material and may be classified as random or systematic errors. Random errors affect the 34    precision of the measurement system and show up as variations among repeated 35    measurements. Systematic errors show up as measurements that are biased to give results May 2020                                          2-15                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                                  MARSSIM 1    that are consistently higher or lower than the true value. Measurement uncertainty is 2    discussed in Section 6.4.
QUALITY ASSURANCE ASSESSMENT QC/Performance Routine Data Evaluation Data PLANNING Data Quality Objectives Process INPUTS Quality Assurance Project Plan Development DATA VERIFICATION/VALIDATION
* Verify measurement performance IMPLEMENTATION
* Verify measurement procedure and reporting Field Data Collection and Associated              specifications Quality Assurance/Quality Control Activities OUTPUT Verified/Validated Data ASSESSMENT Data Verification/Validation Data Quality Assessment INPUT DATA QUALITY ASSESSMENT
* Review project objectives and sampling design
* Conduct preliminary data review
* Select statistical method
* Verify assumptions of the method
* Draw conclusions from the data OUTPUT Project Conclusions 3
4 Figure 2.3: The Assessment Phase of the Data Life Cycle (EPA 2006a) 5 MARSSIM uses the Data Life Cycle to control and estimate the uncertainty in the survey results 6 on which decisions are made. Adequate planning should minimize known sources of 7 uncertainty. QC data collected during implementation of the survey plan provide an estimate of 8 the uncertainty. Statistical hypothesis testing or comparison to an upper confidence limit during 9 the assessment phase provides a level of confidence for the final decision. There are several 10 levels of decisions included within each survey type. Some decisions are quantitative, based on NUREG-1575, Revision 2                          2-16                                              May 2020 DRAFT FOR PUBLIC COMMENT                                                      DO NOT CITE OR QUOTE
 
MARSSIM                            Overview of the Radiation Survey and Site Investigation Process 1 the numerical results of measurements performed during the survey. Other decisions are 2 qualitative based on the available evidence and best professional judgment. The Data Life 3 Cycle can and should be applied consistently to both types of decisions.
4 2.3.5  Reporting Survey Results 5 The process of reporting survey results is an important consideration in planning the survey.
6 Again, the level of effort for reporting should be based on the complexity of the survey. A simple 7 survey with relatively few results may require a single report, while a more complicated survey 8 may require several reports to meet the objectives of the survey. Reporting requirements for 9 individual surveys should be developed during planning and clearly documented in the QAPP.
10 These requirements should be developed with cooperation from the people performing the 11 analyses (e.g., the analytical laboratory should be consulted on reporting results for samples).
12 The Health Physics Society and Multi-Agency Radiological Laboratory Analytical Protocols 13 (MARLAP) have provided several suggestions for reporting survey results (EPA 1980a, NRC 14 2004):
15
* Report the actual result of the analysis. Do not report data as less than the detection limit.
16    Even negative results and results with large uncertainties can be used in the statistical tests 17    to demonstrate compliance. Results reported only as < MDC cannot be fully used and, for 18    example, complicate even such simple analyses as an average. Although the nonparametric 19    tests described in Sections 8.3-8.4 and the upper confidence limit comparison described in 20    Section 8.5 can accommodate situations where up to 40 percent of the results as non-21    detects, it is better to report the actual results.
22
* Report results using the correct units and the correct number of significant digits. The choice 23    of reporting results using International System units (e.g., Bq/kg, Bq/m2) or conventional 24    units (e.g., pCi/g, dpm/100 cm2) is made on a site-specific basis. Generally, MARSSIM 25    recommends that all results be reported in the same units as the DCGLs. Sometimes the 26    results may be more convenient to work with as counts directly from the detector. In these 27    cases, the user should decide what the appropriate units are for a specific survey based on 28    the survey objectives. MARLAP suggests that the uncertainty and MDC should be reported 29    to two significant figures, while environmental radiation measurements seldom warrant more 30    than two or three significant figures.
31
* Report the measurement uncertainty for every analytical result or series of results, such as 32    for a measurement system. This uncertainty, while not directly used for demonstrating 33    compliance with the release criteria, is used for survey planning and data assessment 34    throughout the RSSI process. In addition, the uncertainty is used for evaluating the 35    performance of measurement systems using QC measurement results (as described in 36    Section 6.2 for scans and direct measurements, and in Section 7.2 for laboratory analysis 37    of samples). The uncertainty is also used for comparing individual measurements to the 38    action level, which is especially important in the early stages of the RSSI process (scoping, 39    characterization, and remedial action support surveys described in Section 2.4) when 40    decisions are made based on a limited number of measurements. Section 6.4 discusses 41    methods for calculating the measurement uncertainty.
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Overview of the Radiation Survey and Site Investigation Process                            MARSSIM 1
* Report the MDC for the measurement system as well as the method used to calculate the 2    MDC. The MDC is an a priori estimate of the capability for detecting an activity concentration 3    with a specific measurement system (EPA 1980a). As such, this estimate is valuable for 4    planning and designing radiation surveys. Optimistic estimates of the MDC (calculated using 5    ideal conditions that may not apply to actual measurements) overestimate the ability of a 6    technique to detect residual radioactive material, especially when scanning for alpha or low-7    energy beta radiations. This can invalidate survey results, especially for scanning surveys.
8    Using a more realistic MDC during scoping and characterization surveys, as described in 9    Section 6.3, helps in the proper classification of survey units for FSSs and minimizes the 10    possibility of designing and performing subsequent surveys because of errors in 11    classification. Estimates of the MDC that minimize potential decision errors should be used 12    for planning surveys.
13 Reporting requirements for individual surveys should be developed during planning and clearly 14 documented in the QAPP.
15 2.4    Radiation Survey and Site Investigation Process 16 The Data Life Cycle discussed in Section 2.3 is the basis for the performance-based approach 17 in MARSSIM. The RSSI process is a series of surveys designed to demonstrate compliance 18 with dose- or risk-based criteria for sites with residual radioactive material. The size, complexity, 19 and amount of existing information on the site will determine how many of the surveys in the 20 series will be necessary.
21 There are six principal steps in the RSSI process:
22
* site identification 23
* HSA 24
* scoping survey 25
* characterization survey 26
* remedial action support survey 27
* FSS 28 Table 2.1 provides a simplified overview of the principal steps in the RSSI process and how the 29 Data Life Cycle can be used in an iterative fashion within the process. Each of these steps is 30 briefly described in the Sections 2.4.1-2.4.6 and described in more detail in Chapter 5. In 31 addition, there is a brief description of regulatory agency confirmation and verification 32 (Section 2.4.7). Because MARSSIM focuses on demonstrating compliance with release criteria, 33 specifically by using an FSS, some of these surveys have additional objectives that are not fully 34 discussed in MARSSIM (e.g., health and safety of workers, supporting selection of values for 35 exposure pathway model parameters).
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MARSSIM                            Overview of the Radiation Survey and Site Investigation Process 1 Figure 2.4 illustrates the RSSI process in terms of area classification and lists the major 2 decision to be made for each type of survey. The flowchart demonstrates one method for 3 quickly estimating the survey unit classification early in the MARSSIM process based on limited 4 information. This figure is a useful tool for visualizing the classification process, but there are 5 site-specific characteristics that may cause variation from this scheme. This illustration is not 6 designed to comprehensively consider every possibility that may occur at individual survey 7 units.
8 The flowcharts in Figures 2.5-2.8 present the principal steps and decisions in the site 9 investigation process and shows the relationship of the survey types to the overall assessment 10 process. As shown in these figures, there are several sequential steps in the site investigation 11 process and each step builds on information provided by its predecessor. Properly applying 12 each sequential step in the RSSI process should provide a high degree of assurance that the 13 release criteria have not been exceeded.
14 2.4.1  Site Identification 15 Often, sites where radioactive material is known or suspected to have been used or stored are 16 readily identified before decommissioning or cleanup. Any facility preparing to terminate an NRC 17 or agreement state license would be identified as a site. Formerly terminated NRC licenses may 18 also become sites for the EPA Superfund Program. Portions of military bases or 19 U.S. Department of Energy facilities may be identified as sites based on records of authorization 20 to possess or handle radioactive materials. Where records are incomplete, site identification can 21 be more difficult. In addition, information obtained during the performance of survey activities 22 may identify additional potential radiation sites related to the site being investigated. More 23 detailed information on site identification is provided in Section 3.4.
24 2.4.2  Historical Site Assessment 25 The primary purpose of the HSA is to collect existing information concerning the site and its 26 surroundings.
27 The primary objectives of the HSA are to 28
* Identify potential sources of residual radioactive material.
29
* Determine whether sites pose an imminent threat to human health and the environment.
30
* Differentiate impacted from non-impacted areas.
31
* Provide input to scoping and characterization survey designs.
32
* Provide an assessment of the likelihood of migration of radioactive material.
33
* Identify additional potential sites containing radioactive material related to the site being 34    investigated.
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Overview of the Radiation Survey and Site Investigation Process                                  MARSSIM Initially Assumes a Class 1 Projected Final Status Historical Site          Survey Classification Assessment Yes/Unknown              Scoping Survey Is the Area No Impacted?
Does the Area Potentially Contain No Residual Radioactive Non-Impacted                                                Material?
No Survey Required Characterization Survey Does the Area Actually Contain            Perform Class 3 Final Residual Radioactive  No Status Survey Material?
Is the Probability No                      of Exceeding the DCGLW Small?
Yes Is the Probability Remedial Action No                of Exceeding the Support Survey DCGLEMC Small?
Yes Is There Sufficient Class 1 Final Status                                                        Class 2 Final Status No              Information to Support  Yes Survey                                                                      Survey Classification as Class 2?
1 2 Figure 2.4: Radiation Survey and Site Investigation Process in Terms of Area Classification NUREG-1575, Revision 2                                    2-20                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                        DO NOT CITE OR QUOTE
 
MARSSIM                            Overview of the Radiation Survey and Site Investigation Process Survey Objectives Identify Site                  1. Identify potential sources of residual radioactive material
: 2. Determine whether site poses a threat to human health Section 3.3              and the environment
: 3. Differentiate impacted from non-impacted areas
: 4. Provide input to scoping and characterization survey Design HSA Using                      designs DQO Process                      5. Provide an assessment of the likelihood of radionuclide migration Section 3.2          6. Identify additional potential radiation sites related to the site being investigated Reassess DQOs Perform HSA No                            Sections 3.4, 3.5, & 3.6 Validate Data Are the DQOs and Assess Satisfied?
Data Quality Does Site Pose Immediate Risk to                            Refer to the Appropriate Yes Human Health and                                Regulatory Authority Environment?
Yes/Unknown Does Site Possibly Document Findings Contain Residual Radioactive                                                                    Decision to Supporting Non-Impacted Material in Excess of Natural                                                                Release Area Classification Background or Fallout Levels?                                                      Sections 3.8 No To Figure Document Findings of 2.6 HSA Sections 3.8 1
2 Figure 2.5: The Historical Site Assessment Portion of the Radiation Survey and Site 3 Investigation Process May 2020                                                  2-21                                NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                    DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                                  MARSSIM 1
From Figure                Survey Objectives 2.5                  1. Perform a preliminary hazard assessment
: 2. Support classification of all or part of the site as a Class 3 area
: 3. Evaluate whether survey plan can be optimized for use in characterization or Design Scoping Survey            final status survey Plan Using              4. Provide input to the characterization DQO Process                survey design.
Perform Reassess DQOs Scoping Survey No Are the DQOs                  Validate Data and Satisfied?                  Assess Data Quality Is There Sufficient                                    To Figure Yes            Information to Support      No/Unknown                      2.7 Classification as Class 3?
Document Findings Supporting Class 3 Classification To Figure 2.8 2
3 Figure 2.6: The Scoping Survey Portion of the Radiation Survey and Site Investigation 4 Process NUREG-1575, Revision 2                          2-22                                              May 2020 DRAFT FOR PUBLIC COMMENT                                              DO NOT CITE OR QUOTE
 
MARSSIM                                            Overview of the Radiation Survey and Site Investigation Process From Figure 2.6 Survey Objectives
: 1. Determine the nature and extent of the residual radioactive material Design                          2. Evaluate remedial alternatives and Reassess DQOs                                    Characterization                        technologies Survey Plan Using                      3. Evaluate whether survey plan can be DQO Process                            used as the final status survey No                                                                            4. Provide input to the final status survey design Perform Are the DQOs Characterization Satisfied?
Survey Yes Validate Data Classify Areas as                                  and Assess Class 1, Class 2,                                  Data Quality or Class 3 Determine Remedial Alternative and Site-Specific DCGLs Is Area Class 1 or Class 2?
No              Remediate the Area Yes Yes Perform Remedial Action Support Survey Is Area Remediation Required?
Does the Remedial Action Support Survey Indicate          Yes the Remediation is Complete?
No        Reassess Remedial Alternative and Site-No Specific DCGLs Is From                  To Figure Reassessment of Figure                    2.8 Yes              Remedial Alternative and Site-Specific DCGLs                              2.8*
Necessary?
* The point where survey units that fail to demonstrate compliance in the final status survey in Figure 2.8 re-enter the process 1
2 Figure 2.7: The Characterization and Remedial Action Support Survey Portion of the 3 Radiation Survey and Site Investigation Process May 2020                                                                  2-23                                        NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                                            DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                                                          MARSSIM From Figure 2.6 and Figure                              Survey Objectives 2.7                                1. Select/verify survey unit classification
: 2. Demonstrate that the potential dose or risk from residual radioactive material is below the release criteria for each survey unit Design Final Status Survey                      3. Demonstrate that the potential dose Plan Using DQO Process                            from residual elevated areas is below the release criteria for each survey unit Perform Final Status                Perform Final Status                    Perform Final Status Survey for Class 1                  Survey for Class 2                    Survey for Class 3 Survey Units                        Survey Units                            Survey Units Reassess DQOs Validate Data Are the DQOs                                                                  Perform Additional No                                                    and Assess Satisfied?                                                                        Surveys Data Quality Yes                                                                              No Do Final Status Survey Is Additional Results Contain Residual No                              Remediation Radioactive Material Required?
Less than DCGLs?
Yes Yes To Figure Document Results in the Final 2.7*
Status Survey Report
* Connects with the Remedial Action Support Survey portion of the process in Figure 2.7 1
2 Figure 2.8: The Final Status Survey Portion of the Radiation Survey and Site Investigation 3 Process NUREG-1575, Revision 2                                          2-24                                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                                          DO NOT CITE OR QUOTE
 
MARSSIM                                Overview of the Radiation Survey and Site Investigation Process 1 The HSA typically consists of three phases: identification of a candidate site, preliminary 2 investigation of the facility or site, and site visits or inspections. Information collected during the 3 HSA is then used to evaluate the site.
4 2.4.3    Scoping Survey 5 If the data collected during the HSA indicate that an area is impacted, a scoping survey may be 6 performed. Scoping surveys provide site-specific information based on limited measurements.
7 The primary objectives of a scoping survey are to 8
* Perform a preliminary hazard assessment.
9
* Support classification of all or part of the site as a Class 3 area, if appropriate.
10
* Evaluate whether the survey plan can be optimized for use in the characterization survey or 11      FSS.
12
* Provide data to complete the site prioritization scoring process (Comprehensive 13      Environmental Response, Compensation, and Liability Act [CERCLA] and Resource 14      Conservation and Recovery Act [RCRA] sites only).
15
* Provide input to the characterization survey design, if necessary.
16 Table 2.1 provides an overview of how the Data Life Cycle (Plan, Implement, Assess, and 17 Decide) can be used to support each of the steps in the RSSI process up through the FSS.
18 Table 2.1: The Data Life Cycle 6 used to Support the Radiation Survey and Site 19 Investigation Process RSSI Process        Data Life Cycle                      MARSSIM Methodology Site Identification                        Provides information on identifying potential radiation sites (Section 3.3)
Historical Site      Historical Site      Provides information on collecting and assessing Assessment            Assessment            existing site data (Sections 3.4-3.9) and potential Data Life Cycle      sources of information (Appendix F)
Scoping Survey        Scoping Data          Discusses the purpose and general approach for Life Cycle            performing scoping surveys, especially as sources of information when planning final status surveys (Section 5.2.1) 6 The steps of the Data Life Cycle can be found in Figure 2.1. The DQO process for each of the steps can be found in Figure 2.2.
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Overview of the Radiation Survey and Site Investigation Process                            MARSSIM RSSI Process      Data Life Cycle                MARSSIM Methodology Characterization    Characterization  Discusses the purpose and general approach for Survey              Data Life Cycle  performing characterization surveys, especially as sources of information when planning final status surveys (Section 5.2.2)
Remedial Action    Remedial Action  Discusses the purpose and general approach for Support Survey      Data Life Cycle  performing remedial action support surveys, especially as sources of information when planning final status surveys (Section 5.2.3)
Final Status        Final Status Data Provides detailed information for planning final Survey              Life Cycle        status surveys (Chapter 4, Section 5.3), selecting measurement techniques (Chapter 6, Chapter 7, Appendix H), and assessing the data collected during final status surveys (Chapter 8, Appendix D) 1 Scoping surveys can be conducted after the HSA is completed and typically consist of judgment 2 measurements based on the HSA data. If the results of the HSA indicate that an area is Class 3 3 and no residual radioactive material is found during a scoping survey, the area may be 4 classified as Class 3, and a Class 3 FSS is performed. If the scoping survey locates residual 5 radioactive material, the area may be considered as Class 1 (or Class 2) for the FSS, and a 6 characterization survey is typically performed. Sufficient information should be collected to 7 identify situations that require immediate radiological attention. For sites where the CERCLA 8 requirements are applicable, the scoping survey should collect sufficient data to complete the 9 Hazard Ranking System (HRS) scoring process. For sites where the RCRA requirements are 10 applicable, the scoping survey should collect sufficient data to complete the National Corrective 11 Action Prioritization System (NCAPS) scoring process. Sites that meet the National Contingency 12 Plan (NCP) criteria for a removal should be referred to the Superfund removal program (EPA 13 1996c). A comparison of the MARSSIM approach to CERCLA and RCRA requirements is 14 provided in Appendix F.
15 2.4.4    Characterization Survey 16 If the results of the HSA and scoping survey indicate that an area could be classified as Class 17 1 or Class 2 for the FSS, a characterization survey may be warranted. The characterization 18 survey is planned based on the HSA and scoping survey results. This type of survey typically is 19 a detailed radiological environmental characterization of the area.
20 The primary objectives of a characterization survey are as follow:
21
* Determine the nature and extent of the residual radioactive material.
22
* Collect data to support evaluation of remedial alternatives and technologies.
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MARSSIM                          Overview of the Radiation Survey and Site Investigation Process 1
* Support a hazard assessment of the potential dose and risk to workers or the public during 2    remediation.
3
* Evaluate whether the survey plan can be optimized for use in the FSS.
4
* Support remedial investigation/feasibility study requirements (CERCLA sites only) or facility 5    investigation/corrective measures study requirements (RCRA sites only).
6
* Provide input to the FSS design.
7 The characterization survey can be the most comprehensive of all the survey types and typically 8 generates the most data. This can include preparing a reference grid, taking systematic or 9 judgment measurements, and performing surveys of different media (e.g., surface soils, interior 10 and exterior surfaces of buildings). The decision as to which media will be surveyed is site-11 specific and will be addressed throughout the RSSI process.
12 2.4.5  Remedial Action Support Survey 13 If an area is adequately characterized and has concentrations of residual radioactive material 14 above the DCGLs, a remediation plan should be prepared. A remedial action support survey is 15 performed while remediation is being conducted and guides the remediation in a real-time 16 mode.
17 Remedial action support surveys are conducted to 18
* support remediation activities 19
* determine when a site or survey unit is ready for the FSS 20
* provide updated estimates of site-specific parameters used for planning the FSS 21 This manual does not provide information on the routine operational surveys used to support 22 remediation activities. The determination that a survey unit is ready for an FSS following 23 remediation is an important step in the RSSI process. In addition, remedial activities result in 24 changes to the distribution of residual radioactive material within the survey unit. For most 25 survey units, the site-specific parameters used during FSS planning (e.g., variability in the 26 radionuclide concentration, probability of small areas of elevated activity) will need to be re-27 established following remediation. Obtaining updated values for these critical parameters should 28 be considered when planning a remedial action support survey.
29 2.4.6  Final Status Survey 30 The FSS is used to demonstrate compliance with release criteria. This type of survey is the 31 major focus of this manual.
32 The primary objectives of the FSS are as follow:
33
* Verify that survey unit classification is correct.
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Overview of the Radiation Survey and Site Investigation Process                            MARSSIM 1
* Demonstrate that the total potential dose or risk from all residual radioactive material in each 2      survey unit is below the release criteria.
3
* Demonstrate that the potential dose or risk from any small areas of elevated concentration 4      of radioactive material is below the release criteria for each survey unit, if necessary.
5 The FSS provides data to demonstrate that all radiological parameters satisfy the established 6 guideline values and conditions. Data from other surveys conducted during the RSSI process 7 such as scoping, characterization, and remedial action support surveyscan provide valuable 8 information for planning an FSS, provided they are of sufficient quality.
9 Professional judgment in sampling is often used for locating and characterizing the extent of 10 residual radioactive material at a site. However, the MARSSIM focus is on planning the FSS, 11 which utilizes a more systematic approach to sampling. Systematic sampling is based on rules 12 that endeavor to achieve the representativeness in sampling consistent with the application of 13 statistical tests.
14 2.4.7    Regulatory Agency Confirmation and Verification Survey 15 The regulatory agency responsible for the site often confirms whether the site may be released.
16 Terms for this process can include confirmatory surveys or independent verification. This 17 confirmation may be accomplished by the agency or an impartial party either as an ongoing 18 activity during site remediation or after remediation and the FSS has been completed. Although 19 some actual measurements may be performed, much of the work required for confirmation and 20 verification will involve evaluation and review of documentation and data from survey activities, 21 though the evaluation may include site visits to observe survey and measurement procedures or 22 split-sample analyses by the regulatory agencys laboratory. Therefore, accounting for 23 confirmation and verification activities during the planning stages is important to each type of 24 survey. In some cases, post-remedial sampling and analysis may be performed by an impartial 25 party. The review of survey results should include verifying that the DQOs and MQOs are met, 26 reviewing the analytical data used to demonstrate compliance, and verifying that the statistical 27 test results support the decision to release the site.
28 2.5    Demonstrating Compliance with Dose- or Risk-Based Criteria 29 MARSSIM presents a process for demonstrating compliance with dose- or risk-based criteria.
30 The RSSI process provides flexibility in planning and performing surveys based on site-specific 31 considerations. Dose- or risk-based criteria usually allow one to account for radionuclide and 32 site-specific differences.
33 The FSS is designed to demonstrate compliance with the release criteria. The earlier surveys in 34 the RSSI process are performed to support decisions and assumptions used in the design of the 35 FSS. These preliminary surveys (e.g., scoping, characterization) may have other objectives in 36 addition to compliance demonstration that need to be considered during survey planning that 37 are not fully discussed in this manual. For this reason, MARSSIM focuses on FSS design. To 38 allow maximum flexibility in the survey design, MARSSIM provides information on designing a 39 survey using the RSSI process. This allows users with few resources available for planning to 40 develop an acceptable survey design. The rationale for the development of the information in NUREG-1575, Revision 2                          2-28                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                            Overview of the Radiation Survey and Site Investigation Process 1 MARSSIM is presented in the following sections. Users with available planning resources are 2 encouraged to investigate alternate survey designs for site-specific applications using the 3 information provided in Section 2.6.
4 2.5.1    The Decision to Use Statistical Tests 5 The objective of compliance demonstration is to provide an acceptable level of confidence that 6 the release criteria are not exceeded. As previously stated, 100 percent confidence in a decision 7 cannot be proven because the data always contain some uncertainty. The use of statistical 8 methods is necessary to provide a quantitative estimate of the probability that average 9 concentration of radioactive material at a particular site results in a dose or risk above the 10 release criteria. Statistical methods provide for specifying (controlling) the probability of making 11 decision errors and for extrapolating from a set of measurements to the entire site in a 12 scientifically valid fashion (EPA 1994a).
13 Clearly stating the null hypothesis is necessary before statistical hypothesis testing can be 14 performed. MARSSIM provides the option to establish the null hypothesis under either 15 Scenario A or Scenario B. The Scenario A null hypothesis in MARSSIM is the concentration of 16 residual radioactive material in the survey unit exceeds the release criteria. This statement 17 directly addresses the issue of compliance demonstration for the regulator and places the 18 burden of proof for demonstrating compliance on the site owner or responsible party. The 19 Scenario B null hypothesis in MARSSIM is the concentration of residual radioactive material in 20 the survey unit does not exceed the release criteria. This statement also addresses the issue of 21 compliance demonstration for the regulator; however, it places the burden of proof for 22 demonstrating a lack of compliance on the regulator.
23 In Scenario B, the burden of proof is no longer on the individuals designing the survey and thus 24 should be used with caution and only in those situations where Scenario A is not an effective 25 alternative and regulators have agreed on the use of Scenario B. Regardless of the scenario 26 selected, the probability of rejecting the null hypothesis (i.e., the statistical power) will depend on 27 the variability in the survey unit and the tolerable Type II error probability (i.e., ). Under 28 Scenario A, this type of decision error can result in deciding that a survey unit does not meet the 29 release criteria when it actually does. However, under Scenario B, this type of decision error can 30 result in deciding that a survey unit does meet the release criteria when it actually does not. For 31 this reason, the value of  under Scenario B should be chosen carefully and in consultation with 32 regulatory authorities.
33 Because inadequate statistical power under Scenario B can result in a decision error that a 34 survey meets release criteria when it does not, individuals designing a MARSSIM Survey using 35 Scenario B should make conservative assumptions for  so that, even if the variability in the 36 survey unit is higher than expected, the power of the resulting survey (1-) will still be sufficient 37 to ensure that survey units with residual radioactive material in excess of the DCGL will be 38 discovered at least 1- percent of the time. To ensure adequate statistical power, a 39 retrospective power analysis that indicates that regulatory agency requirements on  were met 40 needs to be completed following the completion of Scenario B MARSSIM Surveys. See 41 Chapter 8 and Appendix I for more information on performing retrospective power analyses.
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Overview of the Radiation Survey and Site Investigation Process                                MARSSIM 1 The information needed to perform a statistical test is determined by the assumptions used to 2 develop the test. MARSSIM recommends the use of nonparametric statistical tests because 3 these tests use fewer assumptions and, consequently, require less information to verify these 4 assumptions. If a large number of measurements will be made (scan-only surveys), then 5 MARSSIM recommends comparison to an upper confidence limit. If the radionuclide is not part 6 of the natural background and radionuclide-specific measurements will be made, MARSSIM 7 recommends the Sign test. If the radionuclide is part of the natural background, or radionuclide-8 specific measurements will not be made, MARSSIM recommends the WRS test. For 9 Scenario B, MARSSIM also recommends the quantile test and a retrospective power analysis.
10 These additional tests provide assurance that when the null hypothesis is not rejected, it is not 11 because there is insufficient power in the statistical tests. The retrospective power analysis can 12 also be useful for Scenario A in identifying the reasons why the null hypothesis was not 13 rejected. The tests described in MARSSIM (see Chapter 8) are relatively easy to understand 14 and implement. Ranked set sampling (see Appendix E) is another method for performing 15 statistical testing of samples and can be useful for hard-to-detect radionuclides. For the reasons 16 described above, Scenario A is preferred to Scenario B. Scenario B should be used instead of 17 Scenario A only when there is sufficient justification for its use.
18 Site conditions can potentially affect the validity of statistical tests. The distribution of residual 19 radioactive material is particularly of concern. Is the residual radioactive material distributed 20 uniformly, or is it located in small areas? Is the residual radioactive material present in the 21 surface soil or on building surfaces, or does it extend into the subsurface? MARSSIM addresses 22 only surface soil and building surfaces for the FSS to demonstrate compliance. This represents 23 a situation that is expected to commonly occur at sites with residual radioactive material, and it 24 allows the survey design to account for the ability to directly measure surface radioactivity using 25 scanning techniques. Radioactive material in other media may be identified during the HSA or 26 preliminary surveys (i.e., scoping, characterization, remedial action support). If radioactive 27 material in other media (e.g., subsurface soils or building materials) is identified, methodologies 28 for demonstrating compliance other than those described in this manual may need to be 29 developed or evaluated. Situations where scanning techniques may not be effective 30 (e.g., volumetric or subsurface radioactive material) are discussed in existing guidance (EPA 31 1989a, EPA 1994a, EPA 2001a).
32 2.5.1.1 Small Areas of Elevated Activity 33 While the development of DCGLs is outside the scope of MARSSIM, this manual assumes that 34 DCGLs will be developed using exposure pathway models that assume a relatively uniform 35 distribution of radioactive material. While this represents an ideal situation, small areas of 36 elevated activity are a concern at many sites.
37 MARSSIM addresses the concern for small areas of elevated activity by using a simple 38 comparison to an investigation level as an alternative to statistical methods. Using the EMC is a 39 conservative approach, because additional investigation is required unless every measurement 40 is below the investigation level. For Class 1 survey units, the investigation level for this 41 comparison is called the DCGLEMC. The DCGLEMC can be higher than the DCGLW due to the 42 lower dose or risk resulting from a smaller area of radioactive material. In the case of multiple 43 areas of elevated activity in a survey unit, a posting plot (discussed in Section 8.2.2.2) or similar NUREG-1575, Revision 2                            2-30                                        May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                          Overview of the Radiation Survey and Site Investigation Process 1 representation of the distribution of activity in the survey unit can be used to determine any 2 pattern in the location of these areas.
3 If elevated levels of residual radioactive material are found in an isolated area in addition to 4 residual radioactive material distributed relatively uniformly across the survey unit, the unity rule 5 (Section 4.4) can be used to ensure that the total dose or risk meets the release criteria. If there 6 is more than one of these areas, a separate term should be included in the calculation for each 7 area of elevated activity. As an alternative to the unity rule, the dose or risk from the actual 8 distribution of residual radioactive material can be calculated if there is an appropriate exposure 9 pathway model available. Note that these considerations generally only apply to Class 1 survey 10 units, since areas of elevated activity should not be present in Class 2 or Class 3 survey units.
11 2.5.1.2 Relatively Uniform Distribution of Residual Radioactive Material 12 As discussed previously, the development of a DCGL starts with the assumption of a relatively 13 uniform distribution of residual radioactive material. Some variability in the measurements is 14 expected. This is primarily due to a random spatial distribution of residual radioactive material 15 and uncertainties in the measurement process.
16 With a scan-only survey, the upper confidence limit (UCL) for the mean derived from the 17 arithmetic mean, the variance, and the number of the measurements would represent the 18 parameter of interest for demonstrating compliance. Survey units where a large number of 19 measurements are taken (scan-only surveys) can utilize this technique. Instructions on 20 generating a UCL from scan-only survey data are provided in Section 8.5.
21 When statistical sampling is performed, whether the radionuclide of concern is present in 22 background helps determine the form of the statistical test. The WRS test is recommended for 23 comparisons of survey unit radionuclide concentrations with background. When the radionuclide 24 of concern is not present in background, the Sign test is recommended. Instructions on 25 performing these tests are provided in Section 8.3 and Section 8.4.
26 The WRS and Sign tests are designed to determine whether the level of residual activity 27 uniformly distributed throughout the survey unit exceeds the DCGLW. Because these methods 28 are based on ranks or number of measurements below the DCGL, the statistical tests are tests 29 of the median. When the underlying measurement distribution is symmetric, the mean is equal 30 to the median. When the underlying distribution is asymmetric, these tests are still true tests of 31 the median but only approximate tests of the mean. However, numerous studies show that this 32 is a fair approximation (Hardin and Gilbert, 1993). The assumption of symmetry is less 33 restrictive than that of normality, because the normal distribution is itself symmetric. If, however, 34 the measurement distribution is skewed to the right, the mean will generally be greater than the 35 median. In severe cases, the mean may exceed the DCGLW while the median does not. For this 36 reason, MARSSIM recommends comparing the arithmetic mean of the survey unit data to the 37 DCGLW as a first step in the interpretation of the data (see Section 8.2.2.1). A mean survey unit 38 concentration less than the DCGLW is a necessary, but not sufficient, condition for a survey unit 39 to meet the release criteria.
40 The WRS test compares the distribution of a set of measurements in a survey unit to that of a 41 set of measurements in a reference area. In scenario A, the test is performed by first adding the May 2020                                          2-31                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                              MARSSIM 1 value of the DCGLW to each measurement in the reference area. The combined set of survey 2 unit data and adjusted reference area data are listed, or ranked, in increasing numerical order. If 3 the ranks of the adjusted reference site measurements are significantly higher than the ranks of 4 the survey unit measurements, the survey unit demonstrates compliance with the release 5 criteria.
6 The quantile test is a statistical test to account for non-uniform distributions of radioactive 7 material. The quantile test was developed to detect differences between the survey unit and the 8 reference area that consist of a shift to higher values in only a fraction of the survey unit. The 9 quantile test is only performed when Scenario B is used, and only if the null hypothesis is not 10 rejected for the WRS test. Using the quantile test and the WRS test in tandem results in higher 11 statistical power to identify survey units that do not meet the release criteria than either test by 12 itself.
13 The Sign test compares the distribution of a set of measurements in a survey unit to a fixed 14 value, namely the DCGLW. First, the value for each measurement in the survey unit is 15 subtracted from the DCGLW. The resulting distribution is tested to determine if the center of the 16 distribution is greater than zero. If the adjusted distribution is significantly greater than zero, the 17 survey unit demonstrates compliance with the release criteria.
18 Information on performing the statistical tests and presenting graphical representations of the 19 data are provided in Chapter 8 and Appendix I.
20 2.5.2    Categorization and Classification 21 Categorizing and classifying a survey unit determine the level of survey effort based on the 22 potential for residual radioactive material. Areas are initially categorized as impacted or non-23 impacted based on the results of the HSA. Non-impacted areas have no reasonable potential 24 for residual radioactive material and require no further evidence to demonstrate compliance with 25 the release criteria, although documentation of the decision to categorize an area as non-26 impacted would still be needed. When planning the FSS, impacted areas may be further 27 classified into survey units. If a survey unit is given a less restrictive classification than is 28 warranted, the potential for making decision errors increases. For this reason, all impacted 29 areas are initially assumed to be Class 1. Class 1 areas require the highest level of survey effort 30 because they are known to have concentrations of residual radioactive material above the 31 DCGLW, or the residual radioactive material concentrations are unknown.
32 Information indicating the potential or known residual radioactive material concentration is less 33 than the DCGLW can be used to support re-classification of an area or survey unit as Class 2 or 34 Class 3.
35 There is a certain amount of information necessary to demonstrate compliance with the release 36 criteria. The amount of this information that is available and the level of confidence in this 37 information are reflected in the area classification. The initial assumption for affected areas is 38 that none of the necessary information is available. This results in a default Class 1 39 classification.
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MARSSIM                          Overview of the Radiation Survey and Site Investigation Process 1 Not all of the information available for an area will have been collected for purposes of 2 compliance demonstration. For example, data are collected during characterization surveys to 3 determine the extent, and not necessarily the amount, of residual radioactive material. This 4 does not mean that the data do not meet the objectives of compliance demonstration, but it may 5 mean that statistical tests would be of little or no value because the data have not been 6 collected using appropriate protocols or design. Rather than discard potentially valuable 7 information, MARSSIM allows for a qualitative assessment of existing data (Chapter 3). Non-8 impacted areas represent areas where all of the information necessary to demonstrate 9 compliance is available from existing sources. For these areas, no statistical tests are 10 considered necessary. A classification as Class 2 or Class 3 indicates that some information on 11 describing the potential for residual radioactive material is available for that survey unit. The 12 data collection recommendations are modified to account for the information already available, 13 and the statistical tests are performed on the data collected during the FSS. The HSA 14 (described in Chapter 3) is used to provide an initial categorization for the area of impacted or 15 non-impacted based on existing data and professional judgment.
16 2.5.3  Design Considerations for Small Areas of Elevated Activity 17 Scanning surveys are typically used to identify small areas of elevated activity. The size of the 18 area of elevated activity that the survey is designed to detect affects the DCGLEMC, which in turn 19 determines the ability of a scanning technique to detect these areas. Larger areas have a lower 20 DCGLEMC and are more difficult to detect than smaller areas. Ranked set sampling (RSS), as 21 described in Appendix E, provides an alternative approach for identifying small areas of hard-22 to-detect radionuclides through a combination of field measurements and samples to identify 23 small areas.
24 The percentage of the survey unit to be covered by scans is also an important consideration.
25 One-hundred percent coverage means that the entire surface area of the survey unit has been 26 covered by the field of view of the scanning instrument. One-hundred percent scanning 27 coverage provides a high level of confidence that all areas with elevated concentrations of 28 radioactive material have been identified. One-hundred percent coverage is recommended for 29 all Class 1 survey units. If the available information concerning the survey unit provides 30 information demonstrating that areas of elevated concentrations of radioactive material may not 31 be present, the survey unit may be classified as Class 2 or Class 3. Because there is already 32 some level of confidence that areas of elevated activity are not present, 100 percent coverage 33 may not be necessary to demonstrate compliance. Section 5.3.6 provides information on 34 determining the scan area for Class 2 and 3 areas. For Class 2 areas, the scan area will be 35 based on the width of the gray region and the uncertainty, typically somewhere between 10-36 100 percent of the area, with a combination of systematic scanning and scanning in areas 37 judged to have the highest potential for residual radioactive material. For Class 3 areas, the 38 scan area is the same as Class 2 survey units, except for surveys where samples and/or direct 39 measurements are collected, in which case the scan area can be less than 10 percent and is 40 typically only in areas judged to have the highest potential for residual radioactive material. A 41 general recommendation when deciding which areas to scan is to always err in the direction that 42 minimizes the decision error. In general, scanning the entire survey unit is less expensive than 43 finding areas of elevated concentrations of radioactive material later in the survey process.
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Overview of the Radiation Survey and Site Investigation Process                            MARSSIM 1 Finding such areas will lead to performing additional surveys due to survey unit 2 misclassification.
3 Another consideration for scanning surveys is the selection of scanning locations. This is not an 4 issue when 100 percent of the survey unit is scanned. Whenever less than 100 percent of the 5 survey unit is scanned, a decision must be made on what areas should be scanned. The 6 general recommendation is that when large amounts of the survey unit are scanned (e.g., less 7 than 50%), the scans should be systematically performed along transects of the survey unit.
8 When smaller amounts of the survey unit are scanned, selecting areas based on professional 9 judgment may be more appropriate and efficient for locating areas of elevated activity 10 (e.g., drains, ducts, piping, ditches, floor joints, sumps). A combination of 100 percent scanning 11 in portions of the survey unit based on professional judgment and less coverage (e.g., 20-12 50 percent) for all remaining areas may result in an efficient scanning survey design for some 13 survey units.
14 2.5.4    Design Considerations for Relatively Uniform Distributions of Residual 15          Radioactive Material 16 The survey design for areas with relatively uniform distributions of residual radioactive material 17 is primarily controlled by classification and the requirements of the statistical test. Again, the 18 recommendations provided for Class 1 survey units are designed to minimize the decision error.
19 Recommendations for Class 2 or Class 3 surveys may be based on existing information if the 20 level of confidence associated with this information is sufficient.
21 The first consideration is the identification of survey units. The identification of survey units may 22 be accomplished early (e.g., scoping) or late (e.g., final status) in the survey process but must 23 be accomplished before performing an FSS. Early identification of survey units can help in 24 planning and performing surveys throughout the RSSI process. Late identification of survey 25 units can prevent misconceptions and problems associated with reclassification of areas based 26 on results of subsequent surveys. The area of an individual survey unit is determined based on 27 the area classification and modeling assumptions used to develop the DCGLW. Identification of 28 survey units is discussed in Section 4.6.
29 When performing surveys for which the Sign or WRS test is used, another consideration is the 30 estimated number of measurements to demonstrate compliance using the statistical tests.
31 Sections 5.3.3-5.3.4 describe the calculations used to estimate the number of measurements.
32 These calculations use information that is usually available from planning or from preliminary 33 surveys (i.e., scoping, characterization, remedial action support).
34 The information needed to perform these calculations is 35
* acceptable values for the probabilities of making Type I or Type II decision errors 36
* the estimates of the measurement variability in the survey unit (s) and the reference area 37    (r) if necessary 38 *  , or the shift NUREG-1575, Revision 2                            2-34                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                  Overview of the Radiation Survey and Site Investigation Process 1 MARSSIM recommends that site-specific values be determined for each of these parameters.
2 When selecting site-specific values for decision error rates and , MARSSIM recommends that 3 an initial value be selected and adjusted to develop a survey design that is appropriate for a 4 specific site. For Scenario A, the DCGLW is chosen as the upper bound of the gray region, and 5 the lower bound of the gray region is typically chosen to represent a conservative (slightly 6 higher) estimate of the concentration of residual radioactive material remaining in the survey 7 unit at the beginning of the FSS. For Scenario B, the AL is chosen as the lower bound of the 8 gray region and the upper bound is the DL, a value that represents how much effort will be 9 taken to determine there is no residual radioactive material. For decision error rates, a value 10 that minimizes the risk of making a decision error is recommended for the initial calculations.
11 The number of measurements can be recalculated using different values for the LBGR, DL, or 12 decision error rates until an appropriate survey design is obtained. 7 A prospective power curve 13 (see Appendix M) that considers the effects of these parameters can be very helpful in 14 designing a survey and considering alternative values for these parameters and is highly 15 recommended.
16 To ensure that the desired power is achieved with the statistical test and to account for 17 underestimated values of the measurement variability, MARSSIM recommends that the 18 estimated number of measurements calculated using the formulas in Sections 5.3.3-5.3.4 be 19 increased by 20 percent to account for a reasonable amount of uncertainty in the parameters 20 used to calculate and still allow flexibility to account or some lost or unusable data. Insufficient 21 numbers of measurements may result in failure to achieve the DQO for power and result in 22 increased Type II decision errors, where survey units below the release criteria fail to 23 demonstrate compliance in Scenario A. Of more concern to the regulator, Type II decision 24 errors for Scenario B lead to the incorrect release of survey units with average or median 25 concentrations above the release criteria.
26 Once survey units are identified and the number of measurements is determined, measurement 27 locations should be selected. The statistical tests assume that the measurements are taken 28 from random locations within the survey unit. A systematic grid with a random starting point is 29 used for Class 1 and Class 2 survey units. A systematic grid with a random starting point or a 30 random survey design is used for Class 3 survey units.
31 2.5.5      Developing an Integrated Survey Design 32 To account for assumptions used to develop the DCGLW and the realistic possibility of small 33 areas of elevated activity, if required, an integrated survey design should be developed to 34 include all the design considerations. An integrated survey design combines a scanning survey 35 for areas of elevated activity with random measurements for relatively uniform distributions of 36 radioactive material. Table 2.2 presents the recommended conditions for demonstrating 37 compliance for an FSS based on classification.
7 Note that for some areas, an appropriate survey design may not be possible within initial survey design constraints, such as the requirements on  and survey power (1-), available funds, and estimated values for the average and variability of the concentration of residual radioactive material remaining at the site. In these cases, the planning team will have to reconsider the survey design constraints or their decision to conduct a final status survey, in consultation with their regulator.
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Overview of the Radiation Survey and Site Investigation Process                                            MARSSIM 1 Table 2.2: Recommended Conditions for Demonstrating Compliance Based on 2 Survey Unit Classification for a Final Status Survey Elevated          Sampling and Statistical Survey Unit Classification                          Measurement              Direct                Scanning Test(s)a Comparison        Measurementsb Impacted          Class 1            Yes              Yes              Systematic            100% Coverage Class 2            Yes              Yes              Systematic                10-100%
Systematic/
Judgmental Class 3            Yes              Yes              Random or                10-100%c Systematic              Systematic/
Judgmental Non-Impacted                  No                No                    No                    None 3 a Statistical tests may consist of the Sign test, Wilcoxon Rank Sum test, quantile test, or comparison to an upper 4  confidence limit, depending on the survey design chosen.
5 b For scan-only surveys, omit the sampling and direct measurements.
6 c For surveys utilizing sampling and/or direct measurements, this percentage can be lower than 10% judgmental.
7 Random-start systematic grids are used for Class 1 and Class 2 survey units because there is 8 an increased probability of small areas of elevated activity. The use of a systematic grid allows 9 the decision maker to draw conclusions about the size of any potential areas of elevated activity 10 based on the area between measurement locations, while the random starting point of the grid 11 provides an unbiased method for determining measurement locations for the statistical tests.
12 The random start numbers should be furnished by an unbiased source to ensure that the survey 13 results are similarly unbiased.
14 Random measurement patterns are used for Class 3 survey units to ensure that the 15 measurements are independent and meet the requirements of the statistical tests.
16 Scan-only surveys can be used in place of direct measurements and/or sampling and analysis if 17 the scanning measurement system has an MDC that is less than 50 percent of the DCGLW and 18 meets requirements for measurement method uncertainty. When scanning is used alongside 19 sampling and/or direct measurements, it is used to identify locations within the survey unit that 20 exceed the investigation level. These locations are marked and receive additional investigations 21 to determine the concentration, area, and extent of the residual radioactive material. For Class 1 22 areas, scanning surveys are designed to detect small areas of elevated activity that are not 23 detected by the measurements using the systematic grids. For this reason, the measurement 24 locations and the number of measurements may need to be adjusted based on the sensitivity of 25 the scanning technique (see Section 5.3.5). This is also the reason for recommending 26 100 percent coverage for the scanning survey.
27 Scanning surveys in Class 2 areas are also performed primarily to find areas of elevated activity 28 not detected by the measurements using the systematic pattern. However, the measurement 29 locations are not adjusted based on sensitivity of the scanning technique, and scanning is only NUREG-1575, Revision 2                                    2-36                                            May 2020 DRAFT FOR PUBLIC COMMENT                                                              DO NOT CITE OR QUOTE
 
MARSSIM                          Overview of the Radiation Survey and Site Investigation Process 1 performed in portions of the survey unit. The level of scanning effort should be proportional to 2 the potential for finding areas of elevated activity. In Class 2 survey units that have 3 concentrations of residual radioactive material closer to the release criteria or a higher variability 4 across the survey unit, a larger portion of the survey unit would be scanned; for survey units that 5 are closer to background or have a lower variability, scanning a smaller portion of the survey 6 unit may be appropriate. Class 2 survey units have a lower probability for areas of elevated 7 activity than Class 1 survey units, but some portions of the survey unit may have a higher 8 potential than others. Judgmental scanning surveys would focus on the portions of the survey 9 unit with the highest probability for areas of elevated activity. If the entire survey unit has an 10 equal probability for areas of elevated activity, or the judgmental scans do not cover at least 11 10 percent of the area, systematic scans along transects of the survey unit or scanning surveys 12 of randomly selected grid blocks are performed.
13 Class 3 areas have the lowest potential for areas of elevated activity. For scan-only surveys, the 14 scan area and methodology are the same as for Class 2, but for surveys that contain both 15 statistical sampling and scanning, scanning surveys should be performed in areas of highest 16 potential (e.g., corners, ditches, and drains) based on professional judgment. This provides a 17 qualitative level of confidence that no areas of elevated activity were missed by the random 18 measurements or that there were no errors made in the classification of the area.
19 2.6    Flexibility in Applying MARSSIM Approach 20 Section 2.5 describes an example that applies the performance-based approach presented in 21 Sections 2.3-2.4 to design a survey for a site with residual radioactive material in surface soils 22 and/or building surfaces. Obviously, this design cannot be uniformly applied at every site with 23 residual radioactive material, so flexibility has been provided in the form of a performance-based 24 approach. This approach encourages the user to develop a site-specific survey design to 25 account for site-specific characteristics. It is expected that most users will adopt the portions of 26 the MARSSIM methodology that apply to their site. In addition, changes to the overall survey 27 design that account for site-specific differences would be presented as part of the survey plan.
28 The plan should also demonstrate that the extrapolation from measurements performed at 29 specific locations to the entire site or survey unit is performed in a technically defensible 30 manner.
31 Where Section 2.5 describes the development of a generic survey design that will be applicable 32 at most radiation sites, this section describes the flexibility available within the MARSSIM for 33 designing a site-specific survey design. Alternate methods for accomplishing the demonstration 34 of compliance are briefly described, and references for obtaining additional information on these 35 alternate methods are provided.
36 2.6.1    Alternate Statistical Methods 37 MARSSIM encourages the use of statistics to provide a quantitative estimate of the probability 38 that the release criteria are not exceeded at a site. While it is unlikely that any site will be able to 39 demonstrate compliance with dose- or risk-based criteria without at least considering the use of 40 statistics, MARSSIM recognizes that the use of statistical tests may not always provide the most 41 effective method for demonstrating compliance. For example, MARSSIM recommends a simple May 2020                                          2-37                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Overview of the Radiation Survey and Site Investigation Process                            MARSSIM 1 comparison to an investigation level to evaluate the presence of small areas of elevated activity 2 in place of complicated statistical tests.
3 MARSSIM recommends the use of nonparametric statistical tests for evaluating environmental 4 data. There are two reasons for this recommendation: (1) Environmental data are usually not 5 normally distributed, and (2) there are often a significant number of qualitative survey results 6 (e.g., less than MDC). Either one of these conditions means that parametric statistical tests may 7 not be appropriate. If one can demonstrate that the data are normally distributed and that there 8 are sufficient results to support a decision concerning the survey unit, parametric tests will 9 generally provide higher power (or require fewer measurements to support a decision 10 concerning the survey unit). The tests to demonstrate that the data are normally distributed 11 generally require more measurements than the nonparametric tests. EPA provides guidance on 12 selecting and performing statistical tests to demonstrate that data are normally distributed (EPA 13 2006a). Guidance is also available for performing parametric statistical tests (NRC 1992a, EPA 14 1989a, EPA 1994a, EPA 2006a).
15 There are a wide variety of statistical tests designed for use in specific situations. These tests 16 may be preferable to the generic statistical tests recommended in MARSSIM when the 17 underlying assumptions for these tests can be verified. Table 2.3 lists several examples of 18 statistical tests that may be considered for use at individual sites or survey units. A brief 19 description of the tests and references for obtaining additional information on these tests are 20 also listed in the table. Applying these tests may require consultation with a statistician.
21 2.6.2    Integrating MARSSIM with Other Survey Designs 22 2.6.2.1 Accelerated Cleanup Models 23 There are a number of approaches designed to expedite site cleanups. These approaches can 24 save time and resources by reducing sampling, preventing duplication of effort, and reducing 25 inactive time periods between steps in a cleanup process. Although Section 2.4 describes the 26 RSSI process recommended in MARSSIM as one with seven principal steps, MARSSIM is not 27 intended to be a serial process that would slow site cleanups. Rather, MARSSIM supports 28 existing programs and encourages approaches to expedite site cleanups. Planning in 29 MARSSIM promotes saving time and resources.
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Table 2.3: Examples of Alternate Statistical Tests MARSSIM May 2020 Probability Model Alternate Tests                          Type of Test            Reference              Advantages                Disadvantages Assumed Alternate 1-Sample Tests (No Reference Area Measurements)
Overview of the Radiation Survey and Site Investigation Process DRAFT FOR PUBLIC COMMENT Students t Test    Normal              Parametric test for H0: Guidance for Data      Appropriate if data        Relies on a non-robust Mean < t                Quality Assessment,    appear to be normally      estimator for &#xb5; and .
EPA QA/G-9,            distributed and            Sensitive to outliers
: p. 3.2-2.              symmetric.                  and departures from normality.
t Test Applied to  Lognormal          Parametric test for H0: Guidance for Data      A well-known and            Relies on a non-robust Logarithms                              Median < t              Quality Assessment,    easy-to-apply test.        estimator for .
EPA QA/G-9,            Useful for a quick          Sensitive to outliers
: p. 3.2-2.              summary of the              and departures from situation if the data are  lognormality.
skewed to right.
2-39            Minimum            Lognormal          Parametric estimates    Gilbert, Statistical  A good parametric test Inappropriate if the Variance                                for mean and variance  Methods for          to use if the data are data are not lognormal.
Unbiased                                of lognormal            Environmental        lognormal.
NUREG-1575, Revision 2 Estimator for                          distribution            Pollution Monitoring, Lognormal Mean                                                  p. 164, 1987.
Chen Test          Skewed to right,    Parametric test for H0: Journal of the        A good parametric test Applicable only for including          Mean > 0                American Statistical  to use if the data are testing H0: survey unit lognormal                                  Association (90),      lognormal.            is clean. Survey unit DO NOT CITE OR QUOTE
: p. 767, 1995.                                must be significantly greater than 0 to fail.
Inappropriate if the data are not skewed to higher values.
 
Overview of the Radiation Survey and Site Investigation Process Probability Model NUREG-1575, Revision 2 Alternate Tests                            Type of Test              Reference              Advantages              Disadvantages Assumed Bayesian          Varies, but a        Parametric test for H0:  DeGroot, Optimal      Permits use of            Decisions based on Approaches        family of            Mean < L                  Statistical Decisions, subjective expert        expert judgment may probability                                    2005.                  judgment in              be difficult to explain distributions must                                                    interpretation of data. and defend.
DRAFT FOR PUBLIC COMMENT be selected Bootstrap          No restriction      Nonparametric; uses  Hall, Annals of    Avoids assumptions              Computer-intensive resampling methods to Statistics (22),    concerning the type of          analysis required.
estimate sampling    p. 2011-2030, 1994. distribution.                    Accuracy of the results variance                                                                  can be difficult to assess.
Lognormal          Lognormal            Uses resampling          Angus, The            Nonparametric method      Computer-intensive Confidence                              methods to estimate      Statistician (43),    applied within a          analysis required.
Intervals Using                        one-sided confidence      p. 395, 1994.          parametric lognormal      Accuracy of the results Bootstrap                              interval for lognormal                          model.                    can be difficult to mean                                                                      assess.
2-40 Alternate 2-Sample Tests (Reference Area Measurements Are Required)
May 2020 Students t Test  Symmetric, normal Parametric test for          Guidance for Data      Easy to apply.            Relies on a non-robust difference in means          Quality Assessment,    Performance for non-      estimator for ;
Ho: &#xb5;x < &#xb5;y                  EPA QA/G-9,            normal data are          therefore, test results
: p. 3.3-2.              acceptable.              are sensitive to outliers.
DO NOT CITE OR QUOTE MARSSIM
 
MARSSIM Probability Model May 2020 Alternate Tests                            Type of Test            Reference              Advantages                Disadvantages Assumed Mann-Whitney      No restrictions      Nonparametric test      Hollander,            Equivalent to the WRS      Assumes that the only Test                                    difference in location  Nonparametric          test, but used less        difference between the Ho: &#xb5;x < &#xb5;y              Statistical Methods,  often. Similar to          test and reference Overview of the Radiation Survey and Site Investigation Process 2014.                  resampling, because        areas is a shift in DRAFT FOR PUBLIC COMMENT test is based on set of    location.
all possible differences between the two data sets.
Kolmogorov-        No restrictions      Nonparametric test for  Hollander,            A robust test for          May reject because Smirnov                                any difference          Nonparametric          equality of two sample      variance is high, between the two          Statistical Methods,  distributions against all  although mean is in distributions            2014.                  alternatives.              compliance.
Bayesian          Varies, but a        Parametric tests for  Box and Tiao,            Permits use of expert      Decisions based on Approaches        family of            difference in means or Bayesian Inference      judgment in the            expert judgment may probability          difference in variance in Statistical          interpretation of data. be difficult to explain 2-41                              distributions must                          Analysis, 2011.                                      and defend.
be selected NUREG-1575, Revision 2 2-Sample          No restrictions      Nonparametric test for EPA, Methods for        Will detect if survey      Applicable only for Quantile Test                          difference in shape    Evaluating the          unit distribution          testing H0: survey unit and location          Attainment of            exceeds reference          is clean. Survey unit Cleanup Standards,      distribution in the        must be significantly Vol. 3, p. 7.1, 1994. upper quantiles.            greater than 0 to fail.
DO NOT CITE OR QUOTE Sign Test when    No restrictions      Nonparametric test for  Abelquist,            Less computationally        Less powerful than the Background is                          difference in location  Decommissioning        intensive. Consistent      Wilcoxon Rank Sum Present                                assuming uniform        Health Physics: A      with pre-MARSSIM            Test because of background              Handbook for          survey designs.            assumptions MARSSIM Users,                                    concerning background 2nd Edition, 2014.                                distributions.
 
Overview of the Radiation Survey and Site Investigation Process Probability Model NUREG-1575, Revision 2 Alternate Tests                                      Type of Test                Reference                Advantages          Disadvantages Assumed Bootstrap and    No restrictions                Nonparametric; uses  Hall, Annals of                  Avoids assumptions      Computer-intensive Other Resampling                                resampling methods to Statistics (22),                concerning the type of analysis required.
Methods                                          estimate sampling    p. 2011, 1994.                  distribution. Generates variance                                              informative resampling DRAFT FOR PUBLIC COMMENT distributions for graphing.
Alternate to Statistical Tests Decision Theory          No restrictions        Incorporates loss        DOE, Statistical and          Combines elements of    Limited experience in function in the decision Cost-Benefit                  cost-benefit analysis  applying the method to theory approach          Enhancements to              and risk assessment    compliance the DQO Process for          into the planning      demonstration and Characterization              process.                decommissioning.
Decisions, 1996.                                      Computer-intensive analysis required.
2-42            Abbreviations: H0 = null hypothesis; t: = t-test statistic, L = bayesian test statistic; &#xb5; = mean;  = standard deviation.
May 2020 DO NOT CITE OR QUOTE MARSSIM
 
MARSSIM                                Overview of the Radiation Survey and Site Investigation Process 1 Sandia National Laboratories in New Mexico used a combination of the observational approach, 2 process knowledge, judgmental soil sampling, and Global Positioning System (GPS)/gamma 3 survey techniques to identify and remediate potential residual radioactive material during 4 execution of the Environmental Restoration Project there. Depleted uranium was almost 5 exclusively the radionuclide of concern. There were 268 individual designated test locations on 6 the site ranging from tens of square meters to hundreds of acres, necessitating the application 7 of a flexible, graded approach, as appropriate. GPS/gamma in situ surveys were particularly 8 valuable in cost-effectively screening large areas and identifying sub-areas that warranted more 9 rigorous investigation than other, non-affected areas. As-completed survey maps and data files 10 consisted of ArcGIS figures generated from the GPS/gamma surveys (before and after) 11 supplemented by analytical laboratory results which were correlated to the GPS/gamma 12 surveys, when both were used. Use of in situ GPS/gamma surveys complemented by ArcGIS 13 analytical tools enabled convenient statistical treatment of thousands of data points, making 14 demonstration of successful remediation much easier to present, as well as easier to 15 understand by the stakeholders.
16 At the U.S. Department of Energys Hanford Site, the parties to the Tri-Party Agreement 17 negotiated a method to implement the CERCLA process in order to (1) accelerate the 18 assessment phase, and (2) coordinate RCRA and CERCLA requirements whenever possible, 19 thereby resulting in cost savings. The Hanford Past Practice Strategy was developed in 1991 to 20 accelerate decision-making and initiation of remediation through activities that include 21 maximizing the use of existing data consistent with DQOs (DOE 1991).
22 The Adaptive Sampling and Analysis Programs at the Environmental Science Division of 23 Argonne National Laboratory quantitatively fuse soft data (e.g., historical records, aerial photos, 24 nonintrusive geophysical data) with hard sampling results to estimate residual radioactive 25 material extent, measure the uncertainty associated with these estimates, determine the 26 benefits from collecting additional samples, and assist in siting new sample locations to 27 maximize the information gained (DOE 2001).
28 2.6.2.2 Superfund Soil Screening Guidance 29 The Soil Screening Guidance for Radionuclides (EPA 1996a, EPA 1996b) is a tool developed 30 by EPA to help standardize and accelerate the evaluation and cleanup of radioactively 31 contaminated soils at sites on the National Priorities List (NPL) where future residential land use 32 is anticipated. The guidance provides a methodology for calculating risk-based, site-specific soil 33 screening levels for radionuclides in soil that may be used to identify areas needing further 34 investigation at NPL sites. The Soil Screening Guidance assumes that there is a low probability 35 of residual radioactive material and does not account for small areas of elevated activity. These 36 assumptions correlate to a Class 3 area in MARSSIM. Because the Soil Screening Guidance is 37 designed as a screening tool instead of a final demonstration of compliance, the specific values 38 for decision error levels, the bounds of the gray region, and the number and location of 39 measurements are developed to support these objectives. However, the MARSSIM approach 40 can be integrated with the survey design in the Soil Screening Guidance using this guidance as 41 an alternate MARSSIM survey design.
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Overview of the Radiation Survey and Site Investigation Process                        MARSSIM 1 The Soil Screening Guidance survey design is based on collecting samples, so scan surveys 2 and direct measurements are not considered. To reduce analytical costs, the survey design 3 recommends compositing samples and provides a statistical test for demonstrating compliance.
4 If utilizing the Soil Screening Guidance in conjunction with MARSSIM, factor in the effects of the 5 compositing technique when calculating measurement method uncertainty and detection 6 capability and in the determination of areas of elevated radioactive material.
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MARSSIM                                                                              Historical Site Assessment 1                              3 HISTORICAL SITE ASSESSMENT 2 3.1    Introduction 3 The Radiation Survey and Site Investigation (RSSI) process uses a graded approach that starts 4 with the Historical Site Assessment (HSA) and is later followed by other surveys that lead to the 5 final status survey (FSS). The HSA is an investigation to collect existing information describing a 6 sites complete history from the start of site activities to the present time. During the HSA 7 process, additional information is collected to categorize the site or areas within the site as 8 impacted or non-impacted and to make preliminary site classification assessments. In this 9 chapter 1 10
* Section 3.1 provides an overview of the HSA.
11
* Section 3.2 describes the Data Quality Objectives (DQO) process, utilized to establish 12    criteria for planning HSA data collection activities.
13
* Section 3.3 describes how site identification is used to establish a site or an area within a 14    site as having the potential to have residual radioactive material based on prior activities at 15    the site.
16
* Section 3.4 describes the preliminary investigation, utilized to obtain sufficient information to 17    determine an initial categorization of a site or survey unit.
18
* Section 3.5 explains how site reconnaissance is utilized to gather sufficient information to 19    support decisions on further action.
20
* Section 3.6 covers the evaluation of HSA data to differentiate sites that need further action 21    from those that pose little to no threat from the environment.
22
* Section 3.7 describes how to utilize the data gathered from the HSA to determine the next 23    step in the RSSI process.
24
* Section 3.8 covers the preparation of an HSA report to summarize what is known about a 25    site, assumptions and inferences made about the site, activities conducted during the HSA, 26    and all researched information.
27
* Section 3.9 provides a review of the HSA process.
28
* Figure 3.1 presents a flowchart of HSA activities and Figure 3.2 provides initial 29    categorization of the site or survey unit 2 as impacted or non-impacted.
1 MARSSIM uses the word should as a recommendation, not as a requirement. Each recommendation in this manual is not intended to be taken literally and applied at every site. MARSSIMs survey planning documentation will address how to apply the process on a site-specific basis.
2 Refer to Section 4.6.2 for a discussion of survey units.
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Historical Site Assessment                                                                                          MARSSIM Survey Objectives Identify Site                  1. Identify potential sources of residual radioactive material
: 2. Determine whether site poses a threat to human health Section 3.3              and the environment
: 3. Differentiate impacted from non-impacted areas
: 4. Provide input to scoping and characterization survey Design HSA Using                      designs DQO Process                      5. Provide an assessment of the likelihood of radionuclide migration Section 3.2          6. Identify additional potential radiation sites related to the site being investigated Reassess DQOs Perform HSA No                            Sections 3.4, 3.5, & 3.6 Validate Data Are the DQOs and Assess Satisfied?
Data Quality Does Site Pose Immediate Risk to                            Refer to the Appropriate Yes Human Health and                                Regulatory Authority Environment?
Yes/Unknown Does Site Possibly Document Findings Contain Residual Radioactive                                                                    Decision to Supporting Non-Impacted Material in Excess of Natural                                                                Release Area Classification Background or Fallout Levels?                                                      Sections 3.8 No To Figure Document Findings of 5.1 HSA Sections 3.8 1
* 2 Figure 3.1: Historical Site Assessment Process Flowchart NUREG-1575, Revision 2                                  3-2                                                        May 2020 DRAFT FOR PUBLIC COMMENT                                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                                    Historical Site Assessment 1 The HSA may provide information needed to calculate derived concentration guideline levels 2 (DCGLs, initially described in Section 2.2), as well as information that reveals the magnitude of 3 a sites DCGLs. This information is used for comparing historical data to potential DCGLs and 4 determining the suitability of the existing data for assessment of the site. The HSA also supports 5 emergency response and removal activities within the context of the the U.S. Environmental 6 Protection Agencys (EPA) Superfund program, fulfills public information needs, and furnishes 7 appropriate information about the site early in the RSSI process. For a large number of sites, 8 such as currently licensed facilities, site identification and reconnaissance may not be needed.
9 For certain response activities, such as reports concerning the possible presence of radioactive 10 material, preliminary investigations may consist more of site reconnaissance and a scoping 11 survey in conjunction with collection of historical information.
12 This chapter describes three sections of an HSA: (1) identification of a candidate site 13 (Section 3.3), (2) preliminary investigation of the facility or site (Section 3.4), and (3) site 14 reconnaissance (Section 3.5). The site reconnaissance is not a scoping survey, however, 15 because the intent is to find physical conditions that may affect the investigative process and not 16 to collect measurements. The HSA is followed by an evaluation of the site based on information 17 collected during the HSA.
18 The amount of detailed information and effort needed to conduct an HSA depends on the type 19 of site, associated historical events, regulatory framework, and availability of documented 20 information. For example, information for an HSA is readily available at some facilities that 21 routinely maintain records throughout their operations, such as licensees of the U.S. Nuclear 22 Regulatory Commission (NRC) or Agreement States. At other facilities, such as Comprehensive 23 Environmental Response, Compensation, and Liability Act (CERCLA) sites, a comprehensive 24 search may be necessary to gather information for an HSA (see Appendix F). In the former 25 case, the HSA is essentially complete, and a review of the following sections will serve to 26 ensure that the information justifies the recommendation. In the latter case, the HSA process 27 has identified data gaps that will be addressed in subsequent scoping or characterization 28 surveys. In still other cases, where sealed sources or small amounts of radionuclides are 29 described by the HSA, the site may qualify for a simplified decommissioning procedure (see 30 Appendix B).
31 3.2    Data Quality Objectives 32 The Data Quality Objectives (DQO) process assists in directing the planning of data collection 33 activities performed during the HSA. Information gathered during the HSA can also support the 34 DQOs of subsequent surveys.
35 Three inputs to the HSA/DQO process are expected:
36
* identifying an individual or a list of planning team members, including the decision maker 37    (DQO Step 1, Appendix D, Section D.1) 38
* concisely describing the problem (DQO Step 1, Appendix D, Section D.1) 39
* initially classifying site and survey unit as impacted or non-impacted (DQO Step 4, 40    Appendix D, Section D.2.2)
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Historical Site Assessment                                                                MARSSIM 1 Other inputs may accompany these three, and this added information may be useful in 2 supporting subsequent applications of the DQO process.
3 The planning team clarifies and defines the DQOs for a site-specific survey. This 4 multidisciplinary team of technical experts offers the greatest potential to solve the problems 5 encountered in designing a survey. Including a stakeholder group representative is an important 6 consideration when assembling this team. Once formed, the team can also consider the role of 7 public participation in this assessment and the possible surveys to follow. The number of team 8 members is directly related to the scope and complexity of the problem. For a small site or 9 simplified situations, planning may be performed by the site owner. For a large, complex facility, 10 the team may include project managers, site managers, scientists, engineers, community and 11 local government representatives, health physicists, statisticians, and regulatory agency 12 representatives. A reasonable effort should be made to include other individualsthat is, 13 specific decision makers or data userswho may use the study findings sometime in the future.
14 The role of the regulatory agency representatives is to facilitate survey planningwithout direct 15 participation in survey plan developmentby offering comments and information based on past 16 precedent, current guidance, and potential pitfalls. A regulatory agency representative may also 17 be included at specific sites when needed (e.g., CERCLA).
18 The planning team is generally led by a member who is referred to as the decision maker. This 19 individual is often the person with the most authority over the study and may be responsible for 20 assigning the roles and responsibilities to planning team members. Overall, the decisionmaking 21 process arrives at final decisions based on the planning teams recommendations. The problem 22 or situation description provides background information on the fundamental issue to be 23 addressed by the assessment (EPA 2006b). The following steps may be helpful during DQO 24 development:
25
* Describe the conditions or circumstances surrounding the problem or situation and the 26    reason for undertaking the survey.
27
* Describe the problem or situation as it is currently understood by briefly summarizing 28    existing information.
29
* Conduct literature searches and interviews.
30
* Examine past or ongoing studies to ensure that the problem is correctly defined. Consider 31    breaking complex problems into more manageable pieces.
32 Section 3.5 provides information on gathering existing site data and determining the usability of 33 this data.
34 The initial classification of the site involves developing a conceptual model based on the existing 35 information collected during the preliminary investigation. Conceptual models describe a site or 36 facility and its environs and present hypotheses regarding the radionuclides for known and 37 potential residual radioactive material (EPA 1987a, 1987b). The classification of the site is 38 discussed in Section 3.7.
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MARSSIM                                                                  Historical Site Assessment 1 Several steps in the DQO process may be addressed initially during the HSA. This information 2 or decision may be based on limited or incomplete data. As the site assessment progresses and 3 as decisions become more difficult, the iterative nature of the DQO process allows for re-4 evaluation of preliminary decisions. This is especially important for classification of sites and 5 survey units where the final classification is not made until the FSS is planned.
6 3.3    Site Identification 7 A site may already be known for its prior use and presence of radioactive materials. Elsewhere, 8 potential radioactive materials sites may be identified through such situations and information as 9 the following:
10
* records of authorization to possess or handle radioactive materials, including 11    o    NRC or NRC Agreement State License 12    o    U.S. Department of Energy facility records 13    o    Naval Radioactive Materials Permit 14    o    U.S. Air Force Master Materials License 15    o    Army Radiation Authorization 16    o    State Authorization for Naturally Occurring and Accelerator Produced Radioactive 17          Material (NARM) 18
* notification to government agencies of possible releases of radioactive substances 19
* citizens filing a petition under section 105(d) of the Superfund Amendments and 20    Reauthorization Act of 1986 (EPA 1986) 21
* ground and aerial radiological surveys 22
* contacts with knowledge of the site 23 Once identified, the name, location, and current legal owner or custodian (where available) of 24 the site should be recorded.
25 3.4    Preliminary Investigation 26 The preliminary investigation serves to collect readily available information concerning the 27 facility or site and its surroundings. The investigation is designed to obtain sufficient information 28 to provide initial categorization of the site or survey unit as impacted or non-impacted.
29 Information on the potential distribution of residual radioactive material may be used for 30 classifying each site or survey unit as Class 1, Class 2, or Class 3 and is useful for planning 31 scoping and characterization surveys.
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Historical Site Assessment                                                                      MARSSIM 1 Table 3.1 provides a set of questions that can be used to assist in the preliminary investigation.
2 Apart from obvious cases (e.g., NRC licensees), this table focuses on characteristics that 3 identify a previously unrecognized or known but undeclared source of potential residual 4 radioactive material. Furthermore, these questions may identify confounding factors for 5 selecting reference sites.
6 Table 3.1: Questions Useful for the Preliminary Investigation Question                                      Purpose of Question
: 1. Was the site ever licensed for the              Indicates a higher probability that the area is manufacture, use, or distribution of          impacted.
radioactive materials under Agreement State Regulations, U.S. Nuclear Regulatory Commission licenses, or Armed Services permits, or for the use of 91B material?
: 2. Did the site ever have permits to dispose of    Evidence of radioactive material disposal indicates or incinerate radioactive material onsite? Is  a higher probability that the area is impacted.
there evidence of such activities?
: 3. Has the site ever had deep wells for injection Indicates a higher probability that the area is or permits for such?                          impacted.
: 4. Did the site ever have permits to perform      Research that may have resulted in the release of research with radiation-generating devices or radioactive material indicates a higher probability radioactive materials except medical or        that the area is impacted.
dental X-ray machines?
: 5. As a part of the sites radioactive materials  Leak-test records of sealed sources may indicate license, were there ever any soil moisture    whether a storage area is impacted. Evidence of density gauges (americium-beryllium or        radioactive material disposal indicates a higher plutonium-beryllium sources) or radioactive    probability that the area is impacted.
thickness monitoring gauges stored or disposed of onsite?
: 6. Was the site used to create radioactive        Indicates a higher probability that the area is material by activation?                        impacted.
: 7. Were radioactive sources stored at the site?    Leak-test records of sealed sources may indicate whether or not a storage area is impacted.
: 8. Is there evidence that the site was involved    Indicates a higher probability that the area is in the Manhattan Project or any Manhattan      impacted.
Engineering District activities (1942-1946)?
: 9. Was the site ever involved in the support of    Indicates a higher probability that the area is nuclear weapons testing (1945-1962)?          impacted.
: 10. Were any facilities on the site used as a      Indicates a higher probability that the area is weapons storage area? Was weapons              impacted.
maintenance ever performed at the site?
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MARSSIM                                                                        Historical Site Assessment Question                                        Purpose of Question
: 11. Was there ever any decontamination,              Indicates a higher probability that the area is maintenance, or onsite storage of ships,        impacted.
vehicles, or planes with residual radioactive material?
: 12. Is there a record of any aircraft accident at or May include other considerations, such as evidence near the site (e.g., depleted uranium            of radioactive material that was not recovered.
counterbalances, thorium alloys, radium dials)?
: 13. Are there records indicating use or storage of Indicates a higher probability that the area is radium dials and other radioactive luminous      impacted.
devices as a source?
: 14. Was there ever any radiopharmaceutical          Indicates a higher probability that the area is manufacturing, storage, transfer, or disposal    impacted.
onsite?
: 15. Was animal research ever performed at the        Evidence that radioactive material was used for site?                                            animal research indicates a higher probability that the area is impacted.
: 16. Were naturally occurring radioactive material    Indicates a higher probability that the area is (NORM) or technologically enhanced              impacted or results in a potential increase in naturally occurring radioactive material        background variability.
(TENORM)such as uranium, thorium, or radium compoundsused in manufacturing, research, or testing at the site, or were these compounds stored at the site?
: 17. Has the site ever been involved in the          Indicates a higher probability that the area is processing or production of NORM or              impacted or results in a potential increase in TENORM (e.g., radium, fertilizers,              background variability.
phosphorus compounds, vanadium compounds, refractory materials, rare earth elements, or precious metals) or mining, milling, processing, or production of uranium or thorium?
: 18. Were coal or coal products used onsite? If      May indicate other considerations, such as a yes, did combustion of these substances          potential increase in background variability.
leave ash or ash residues onsite? If yes, are runoff or production ponds onsite?
: 19. Was there ever any onsite disposal of            May indicate other considerations, such as a material known to be high in naturally          potential increase in background variability.
occurring radioactive material (e.g., monazite sands used in sandblasting)?
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Historical Site Assessment                                                                                MARSSIM Question                                            Purpose of Question
: 20. Did the site contain or use pipe from the oil          Indicates a higher probability that the area is and gas industries?                                  impacted or results in a potential increase in background variability.
: 21. Is there any reason to expect that the site            See Section 3.7.
may contain radioactive material (other than previously listed)?
1 Definition: 91B = highly classified radioactive material covered under Section 91(b) of the Atomic Energy Act (AEA) 2 of 1954 associated with current nuclear weapons material, legacy nuclear weapons maintenance wastes, residuals 3 from nuclear weapons accident/incidents, some residuals from atmospheric testing of nuclear weapons, and 4 residuals from nuclear reactor operations. (George Air Force Base, n.d.)
5 Appendix G of this document provides a general listing and cross-reference of information 6 sourceseach with a brief description of the information contained in each source.
7 3.4.1    Existing Radiation Data 8 Sources of useful information for an HSA include site files; monitoring data; former site 9 evaluation data; and Federal, State, and local investigations or emergency actions. Existing site 10 data may provide specific details about the identity, concentration, and areal distribution of 11 residual radioactive material. However, these data should be examined carefully because 12
* Previous survey and sampling efforts may not be compatible with HSA objectives or may not 13      be extensive enough to characterize the facility or site fully.
14
* Measurement protocols and standards may not be known or compatible with HSA objectives 15      (e.g., quality assurance/quality control [QA/QC] procedures, limited analysis rather than full-16      spectrum analysis) or may not be extensive enough to characterize the facility or site fully.
17
* Conditions may have changed since the site was last sampled (i.e., substances may have 18      been released, migration may have spread the residual radioactive material, additional 19      waste disposal may have occurred, or decontamination may have been performed).
20 Existing data can be evaluated using the Data Quality Assessment (DQA) process described in 21 Appendix D. (Also see DOE 1987 and EPA 1980a, 1992a, 1992b, 2006a for additional 22 guidance on evaluating data.)
23 3.4.1.1 Licenses, Site Permits, and Authorizations 24 The facility or site radioactive materials license and supporting or associated documents are 25 potential sources of information for licensed facilities. If a license does not exist, there may be a 26 permit or other document that authorized site operations involving radioactive material. These 27 documents may specify the quantities of radioactive material authorized for use at the site, the 28 chemical and physical form of the materials, operations for which the materials are (or were) 29 used, locations of these operations at the facility or site, and total quantities of material used at 30 the site during its operating lifetime.
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MARSSIM                                                                  Historical Site Assessment 1 EPA and State agencies maintain files on a variety of environmental programs. These files may 2 contain permit applications and monitoring results with information on specific waste types and 3 quantities, sources, type of site operations, and operating status of the facility or site. Some of 4 these information sources are listed in Appendix G.
5 3.4.1.2 Operating Records 6 Records and other information sources useful for site evaluations include those describing 7 onsite activities, current and past radiation control procedures, and past operations involving 8
* demolition 9
* effluent releases 10
* discharge to sewers or onsite septic systems 11
* production of residues 12
* land filling 13
* waste and material storage 14
* pipe and tank leaks 15
* spills and accidental releases 16
* release of facilities or equipment from radiological controls 17
* onsite or offsite radioactive and hazardous waste disposal 18 Some records may be or may have been classified for national security purposes, and means 19 should be established to review all pertinent records. Past operations should be summarized in 20 chronological order, along with information about permits and approvals. Estimates of the total 21 amount of radioactive material disposed of or released at the site and the physical and chemical 22 form of the radioactive material should also be included. Records on waste disposal, 23 environmental monitoring, site inspection reports, license applications, operational permits, 24 waste disposal material balance and inventory sheets, and purchase orders for radioactive 25 materials are useful for estimating total activity. Information on accidentssuch as fires, 26 flooding, spills, unintentional releases, or leakageshould be collected, because they indicate 27 potential sources of residual radioactive material. Possible areas of localized radioactive 28 material should be identified.
29 Site plats or plots, blueprints, drawings, and sketches of structures are especially useful to 30 illustrate the location and layout of buildings on the site. Site photographs, aerial surveys, and 31 maps can help verify the accuracy of these drawings or indicate changes after the drawings 32 were prepared. Processing locations, waste streams to and from the site, and the presence of 33 stockpiles of raw materials and finished product should be noted on these photographs and 34 maps. Buildings or outdoor processing areas may have been modified or converted to other May 2020                                          3-9                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Historical Site Assessment                                                                    MARSSIM 1 uses or configurations. The locations of sewers, pipelines, electric lines, water lines, etc., should 2 also be identified. This information facilitates planning the site reconnaissance and subsequent 3 surveys, developing a site conceptual model, and increasing the efficiency of the survey 4 program.
5 Corporate contract files may also provide useful information during subsequent stages of the 6 RSSI process. Older facilities may not have complete operational records, especially for 7 obsolete or discontinued processes. Financial records may also provide information on 8 purchasing and shipping that, in turn, help to reconstruct a sites operational history.
9 While operating records can be useful tools during the HSA, the investigator should be careful 10 not to place too much emphasis on this type of data. These records are often incomplete and 11 lack information on substances previously not considered hazardous. Out-of-date blueprints and 12 drawings may not show modifications made during the lifetime of a facility, but they may be 13 useful to identify additional areas that should be investigated.
14 3.4.2    Contacts and Interviews 15 Conduct interviews with current or previous employees to collect first-hand information about 16 the site or facility and to verify or clarify information gathered from records. Interviews cover 17 general topics, such as radioactive waste handling procedures. Results from interviews 18 conducted early in the process are useful in guiding subsequent data collection activities.
19 Interviews scheduled late in the data gathering process can also be very useful. Questions can 20 be directed to specific areas of the investigation that need additional information or clarification.
21 Photographs and sketches can be used to assist the interviewer and allow the interviewees to 22 recall information of interest. Conducting interviews onsite where the employees performed their 23 tasks often stimulates memories and facilitates information gathering. In addition to interviewing 24 managers, engineers, and facility workers, interviews may be conducted with laborers and truck 25 drivers to obtain information from their perspective.
26 The investigator should be cautious in the use of interview information. Whenever possible, 27 anecdotal evidence should be assessed for accuracy, and results of interviews should be 28 backed up with supporting data. To ensure that specific information is confirmed and properly 29 recorded, it may be advisable to hire trained investigators and take affidavits.
30 3.5    Site Reconnaissance 31 The objective of the site reconnaissance or site visit is to gather sufficient information to support 32 a decision regarding further action. Reconnaissance activity is not a risk assessment, a scoping 33 survey, or a study of the full extent of residual radioactive material at a facility or site. The 34 reconnaissance offers an opportunity to record information concerning hazardous site 35 conditions as they apply to conducting future survey work. In this regard, information describing 36 physical hazards, structural integrity of buildings, or other conditions defines potential problems 37 that may impede future work. Site reconnaissance is most applicable to sites with less available 38 information and may not be necessary at other sites having greater amounts of records, such as 39 NRC licensed facilities.
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MARSSIM                                                                    Historical Site Assessment 1 To prepare for the site reconnaissance, begin by reviewing what is known about the facility or 2 site and identify data gaps. Given the site-specific conditions, consider whether a site 3 reconnaissance is necessary and practical. This type of effort may be deemed necessary if a 4 site is abandoned or not easily observed from areas of public access, or if file searches disclose 5 little information. These same circumstances may also make a site reconnaissance risky for 6 health and safety reasonsin view of the many unknownsand may make entry difficult. This 7 investigative step may be less critical for active facilities whose operators grant access and 8 provide requested information. Remember to arrange for proper site access and prepare an 9 appropriate health and safety plan, if required, before initiating the site visit.
10 Investigators should acquire signed consent forms from the site or equipment owner to gain 11 access to the property to conduct the reconnaissance. Investigators are to determine if State 12 and Federal officials, and local individuals, should be notified of the reconnaissance schedule. If 13 needed, local officials should arrange for public notification. Guidance on obtaining access to 14 sites can be found in Entry and Continued Access Under CERCLA (EPA 1987c).
15 A study plan should be prepared before the site reconnaissance to anticipate every 16 reconnaissance activity and identify specific information to be gathered. This plan should 17 incorporate a survey of the sites surroundings and provide details for activities that verify or 18 identify the location of nearby residents, worker populations, drinking water or irrigation wells, 19 and foods, as well as other site environs information.
20 Materials and equipment for a site reconnaissance should be prepared in advance. This 21 includes a camera to document site conditions, as well as health and safety monitoring 22 instruments, including a radiation detection meter, a GPS receiver or extra copies of 23 topographic maps to mark target locations, water distribution areas, and other important site 24 features.
25 A logbook is critical to keeping a record of field activities and observations as they occur. The 26 Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) recommends that the 27 logbook be completed in waterproof ink, preferably by one individual. Furthermore, each page of 28 the logbook should be signed and dated, including the time of day, after the last entry on the 29 page. Corrections should be documented and approved. Alternatively, a computerized logbook 30 may also be used, with the adequate provision of controls to ensure appropriate quality 31 assurance and version control. For example, logbook entries should be signed daily and closed 32 out, so that future revisions would require date/time stamping and signature of the individual 33 making changes.
34 3.6      Evaluation of Historical Site Assessment Information 35 The main purpose of the HSA is to determine the current status of the site or facility, but the 36 data collected may also be used to differentiate sites that need further action from those that 37 pose little or no threat to human health and the environment. The information gathered during 38 this screening process can show the need for additional surveys or may be sufficient to 39 recommend a site release. Because much of the information collected during HSA activities is 40 qualitative, and analytical data may be of unknown quality, many decisions regarding a site are 41 the result of professional judgment.
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Historical Site Assessment                                                                  MARSSIM 1 Historical analytical data indicating the presence of residual radioactive material in 2 environmental media (surface soil, subsurface soil, surface water, ground water, air, or 3 buildings) can be used to support the hypothesis that radioactive material was released at the 4 facility or site. A decision that the site does not meet release criteria can be made regardless of 5 the quality of the data, its attribution to site operations, or its relationship to background levels.
6 In such cases, elevated results are sufficient to support the hypothesisit is not necessary to 7 definitively demonstrate that a problem exists. Conversely, historical analytical data can also be 8 used to support the hypothesis that no release has occurred. However, these data should not 9 be the sole basis for this hypothesis. If historical analytical data constitute the principal evidence 10 for ruling out the presence of residual radioactive material, the data must be of sufficient quality 11 to clearly demonstrate that a problem does not exist.
12 In most cases, it is assumed there will be some level of process knowledge available in addition 13 to historical analytical data. If process knowledge suggests that no residual radioactive material 14 should be present, and the historical analytical data also suggests that no residual radioactive 15 material is present, the process knowledge provides an additional level of confidence and 16 supports categorizing the area as non-impacted. However, if process knowledge suggests no 17 residual radioactive material should be present, but the historical analytical data indicate the 18 presence of residual radioactive material, the area will probably be categorized as impacted.
19 The following sections describe the recommended information to accurately and completely 20 support a site release recommendation. If some of the information is not available, it should be 21 identified as a data need for future surveys. Data needs are collected during Step 3 of the DQO 22 process (Identify Inputs to the Decision) as described in Appendix D, Section D.1.3.
23 Section 3.6.5 provides information on professional judgment and how it may be applied to the 24 decisionmaking process.
25 3.6.1    Identify Potential Sources of Residual Radioactive Material 26 An efficient HSA gathers information sufficient to identify the radionuclides used at the site, 27 including their chemical and physical form. The first step in evaluating HSA data is to estimate 28 the potential for residual radioactive material from these radionuclides.
29 Site operations are a strong indicator of the potential for residual radioactive material 30 (NRC 1992a). An operation that handled only encapsulated sources is expected to have a low 31 potential for residual radioactive materialassuming that the integrity of the sources was not 32 compromised. A review of leak-test records for such sources may be adequate to demonstrate 33 the low probability of residual radioactive material. A chemical manufacturing process facility 34 would likely have residual radioactive material in piping, ductwork, and process areas, with a 35 potential for residual radioactive material in soil where spills, discharges, or leaks occurred.
36 Sites using large quantities of radioactive oresespecially those with outside waste collection 37 and treatment systemsare likely to have residual radioactive material on the premises. If loose 38 dispersible materials were stored outside or process ventilation systems were poorly controlled, 39 then windblown surface deposition of residual radioactive material may be possible.
40 Consider how long the site was operational. If enough time elapsed since the site discontinued 41 operations, radionuclides with short half-lives may no longer be present in significant quantities.
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MARSSIM                                                                  Historical Site Assessment 1 In this case, calculations demonstrating that residual activity could not exceed the DCGL may 2 be sufficient to evaluate the potential residual radioactive material at the site. A similar 3 evaluation can be made based on knowledge of a radionuclides chemical and physical form.
4 Such a determination relies on records of radionuclide inventories, chemical and physical forms, 5 total amounts of material and activity in waste shipments, and purchasing records to document 6 and support this decision. However, a number of radionuclides experience significant decay 7 product ingrowth, which should be considered when evaluating existing site information.
8 3.6.2    Identify Potential Areas with Residual Radioactive Material 9 Information gathered during the HSA should be used to provide an initial categorization of the 10 site areas as impacted or non-impacted.
11 Impacted areas are either known to contain residual radioactive material based on radiological 12 surveillance or are suspected of containing it based on historical information. This includes 13 areas where 14
* Radioactive material was used and stored.
15
* Records indicate spills, discharges, or other unusual occurrences that could result in the 16    spread of radioactive material.
17
* Radioactive material was buried or disposed.
18 Areas immediately surrounding or adjacent to these locations are also considered impacted 19 because of the potential for inadvertent spread of radionuclides.
20 Non-impacted areas are those areas where there is no reasonable possibility for residual 21 radioactive material based on site history or previous survey information. The criteria used for 22 this distinction need not be as strict as those used to demonstrate final compliance. However, 23 the reasoning for categorizing an area as non-impacted should be maintained as a written 24 record.
25 All potential sources of radioactive material in impacted areas should be identified and their 26 dimensions recorded (in two or three dimensions, to the extent they can be measured or 27 estimated). Sources can be delineated and characterized through visual inspection during the 28 site reconnaissance; interviews with knowledgeable personnel; and historical information 29 concerning disposal records, waste manifests, and waste sampling data. The HSA should 30 address potential residual radioactive material from the site whether it is physically within or 31 outside of site boundaries. This approach describes the site in a larger context, but as noted in 32 Chapter 1, MARSSIMs scope concerns releasing a site and does not include areas outside a 33 sites boundaries.
34 3.6.3    Identify Potential Media with Residual Radioactive Material 35 The next step in evaluating the data gathered during the HSA is to identify media at the site with 36 a potential for containing residual radioactive material. Identification of those media that do not May 2020                                        3-13                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Historical Site Assessment                                                                  MARSSIM 1 contain residual radioactive material and those that may contain it is necessary for both 2 preliminary area classification (Section 4.4) and planning subsequent survey activities.
3 This section provides information on evaluating the likelihood for release of radioactive material 4 into the following environmental media: surface soil, subsurface soil, sediment, surface water, 5 ground water, air, and buildings. Although MARSSIMs scope is focused on surface soils and 6 building surfaces, other media will still need to be considered.
7 The evaluation will result in a finding either of suspected residual radioactive material or of no 8 suspected residual radioactive material. The finding may be based on analytical data, 9 professional judgment, or a combination of the two.
10 Subsequent sections describe the environmental media and pose questions pertinent to each 11 type. Each question is accompanied by a commentary. Carefully consider the questions within 12 the context of the site and the available data. Avoid spending excessive amounts of time on 13 particular questions, because answers to every question are unlikely to be available at each 14 site. Questions that cannot be answered based on existing data can be used to direct future 15 surveys of the site. Also, keep in mind the numerous differences in site-specific circumstances 16 and that the questions do not identify every characteristic that might apply to a specific site.
17 Additional questions or characteristics identified during a specific site assessment should be 18 included in the HSA report (Section 3.9; EPA 1991e).
19 3.6.3.1 Surface Soil 20 Surface soil is the top layer of soil on a site that is available for direct exposure, growing plants, 21 resuspension of particles for inhalation, and mixing from human disturbances. Surface soil may 22 also be defined as the thickness of soil that can be measured using direct measurement or 23 scanning techniques. Historically, this layer has often been represented as the top 24 15 centimeters (cm; 6 inches [in.]) of soil (40 CFR 192), but will vary depending on radionuclide, 25 surface characteristics, measurement technique, and pathway modeling assumptions. For the 26 purposes of MARSSIM, surface soil may be considered to include gravel fill, waste piles, 27 concrete, or asphalt paving. For many sites where radioactive material was used, one first 28 assumes that radioactive material on the site exists on surfaces, and the evaluation is used to 29 identify areas of high and low probability of residual radioactive material (Class 1, Class 2, or 30 Class 3 areas).
31
* Were all radiation sources used at the site encapsulated sources? A site where only 32    encapsulated sources were used would be expected to have a low potential for residual 33    radioactive material. A review of the leak-test records and documentation of encapsulated 34    source location may be adequate to make a finding of no suspected residual radioactive 35    material.
36
* Were radiation sources used only in specific areas of the site? Evidence that 37    radioactive material was confined to certain areas of the site may be helpful in determining 38    which areas are impacted and which are non-impacted.
39
* Was surface soil regraded or moved elsewhere for fill or construction purposes? This 40    helps identify additional potential sites of radioactive material.
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MARSSIM                                                                      Historical Site Assessment 1 3.6.3.2 Subsurface Soil and Other Subsurface Media 2 Subsurface soil and other subsurface media are defined as any solid materials beneath the 3 surface soil layer. The purpose of these subsurface investigations is to locate and define the 4 lateral and vertical extent of the potential residual radioactive material in the subsurface.
5 Subsurface measurements can be expensive, especially for beta- or alpha-emitting 6 radionuclides. To effectively use project resources, subsurface investigations should be biased 7 (e.g., limited to known or potential areas containing subsurface radioactive material). After 8 identifying areas of subsurface concern, further subsurface investigations would be necessary 9 to delineate the lateral and vertical extent of radioactive material during the remedial 10 investigation and design phase. The latter would aid in planning the necessary resources 11 (e.g., budgets, contractors, obtaining access) and to set the schedule for the remedial action 12 phase.
13
* Is there evidence of changes in surface features? Understanding the development 14    history of an area can aid the investigation in identifying subsurface areas of potential 15    concern. Historically, industrial wastes potentially containing radioactive material were used 16    as fill material (e.g., to fill in old streams, wetlands, low-lying areas) or as subgrade material 17    (e.g., beneath buildings, basement floors). Changes in surface features over time can affect 18    the distribution of radioactive material. Reviewing historical records can be of great benefit in 19    identifying subsurface areas of potential concern and in providing subsequent cost effective 20    and defensible graded approaches to better characterize the site. Examples of helpful 21    records include aerial photographs, topography maps, railroad/road maps, navigation maps, 22    Sanborn Fire Insurance Maps, construction photographs, postcards, and correspondence.
23
* Are there areas of known or suspected residual radioactive material in surface soil?
24    Residual radioactive material in surface soil can migrate deeper into the soil. Surface soil 25    sources should be evaluated based on radionuclide mobility, soil permeability, and 26    infiltration rate to determine the potential for residual radioactive material in the subsurface.
27    Computer modeling may be helpful for evaluating these types of situations.
28
* Is there a ground water plume without an identifiable source? Radioactive material in 29    ground water indicates that a source of residual radioactive material is present. If no source 30    is identified during the HSA, residual radioactive material in the subsurface is a probable 31    source.
32
* Is there potential for enhanced mobility of radionuclides in soils? Radionuclide mobility 33    can be enhanced by the presence of solvents or other chemicals that affect the sorption 34    capacity of soil.
35
* Is there evidence that the surface has been disturbed? Recent or previous excavation 36    activities are obvious sources of surface disturbance. Areas with developed plant life 37    (forested or old growth areas) may indicate that the area remained undisturbed during the 38    operating life of the facility. Areas where vegetation is removed during previous excavation 39    activity may be distinct from mature plant growth in adjacent areas. If a site is not purposely 40    replanted, vegetation may appear in a sequence starting with grasses that are later replaced May 2020                                            3-15                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Historical Site Assessment                                                                MARSSIM 1    by shrubs and trees. Typically, grasslands recover within a few years, sagebrush or low 2    ground cover appears over decades, and mature forests may take centuries to develop.
3
* Is there evidence of subsurface disturbance? Non-intrusive, non-radiological 4    measurement techniques may provide evidence of subsurface disturbance. Magnetometer 5    surveys can identify buried metallic objects, and ground-penetrating radar can identify 6    subsurface anomalies such as trenches or dump sites. Techniques involving special 7    equipment are discussed in Section 6.9.
8
* Are surface structures present? Structures constructed during a sites operational history 9    may cover residual radioactive material below ground. Some consideration for residual 10    radioactive material that may exist beneath parking lots, buildings, or other onsite structures 11    may be warranted as part of the investigation. There may be underground piping, drains, 12    sewers, or tanks that caused the spread of residual radioactive material.
13 3.6.3.3 Surface Water 14 Surface waters include streams and rivers, lakes, coastal tidal waters, and oceans. Note that 15 certain ditches and intermittently flowing streams also qualify as surface water. The evaluation 16 determines whether radionuclides are likely to migrate to surface waters or their sediments.
17 Where a previous release is not suspected, the potential for future release depends on the 18 distance to surface water and the flood potential at the site. One can also consider the 19 interaction between soil and water in relation to seasonal factors, including soil cracking 20 because of freezing, thawing, and desiccation that influence the dispersal or infiltration of 21 radionuclides.
22
* Is surface water nearby? The proximity of residual radioactive material to local surface 23    water is essentially determined by runoff and radionuclide migration through the soil. The 24    definition for nearby depends on site-specific conditions and the time performance period. If 25    the terrain is flat, precipitation is low, and soils are sandy, nearby may be within several 26    meters. If annual precipitation is high or occasional precipitation events are high, within 27    1,200 meters (3/4 mile) might be considered nearby.
28
* Is the waste quantity particularly large? Depending on the physical and chemical form of 29    the waste and its location, large is a relative term. A small quantity of liquid waste may be of 30    more importance (i.e., a greater risk or hazard) than a large quantity of solid waste stored in 31    watertight containers.
32
* Is the drainage area large? The drainage area includes the area of the site itself plus the 33    upgradient area that produces runoff flowing over the site. Larger drainage areas generally 34    produce more runoff and increase the potential for residual radioactive material in surface 35    water.
36
* Is precipitation heavy? If the site and surrounding area are flat, a combination of heavy 37    precipitation and low infiltration rate may cause precipitation to pool on the site. Otherwise, 38    these characteristics may contribute to high runoff rates that carry radionuclides overland to 39    surface water. Total annual precipitation exceeding one meter (40 in.), or a once in 2-years NUREG-1575, Revision 2                              3-16                                  May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                      Historical Site Assessment 1    24-hour precipitation event exceeding 5 cm (2 in.) might be considered heavy.
2 3    The amount of precipitation varies for locations across the continental United States from 4    high (e.g., approximately 200 cm/year [y; 89 in./y], Mt. Washington, New Hampshire) to low 5    values (e.g., approximately 10.7 cm/y [4.2 in./y], Las Vegas, Nevada). Certified data on 6    precipitation rates for locations throughout the United States can be obtained from the 7    National Centers for Environmental Information (https://www.ncdc.noaa.gov).
8
* Is the infiltration rate low? Infiltration rates range from very high in gravelly and sandy 9    soils to very low in fine silt and clay soils. Paved sites prevent infiltration and generate 10    runoff.
11
* Are sources of residual radioactive material poorly contained or prone to runoff?
12    Proper containment that prevents radioactive material from migrating to surface water 13    generally uses engineered structures such as dikes, berms, run-on and runoff control 14    systems, and spill collection and removal systems. Sources prone to releases via runoff 15    include leaks, spills, exposed storage piles, or intentional disposal on the ground surface.
16    Sources not prone to runoff include underground tanks, aboveground tanks, and containers 17    stored in a building.
18
* Is a runoff route well defined? A well-defined runoff routealong a gully, trench, berm, 19    wall, etc.will more likely contribute to migration to surface water than a poorly defined 20    route. However, a poorly defined route may contribute to dispersion of radioactive material 21    to a larger area of surface soil.
22
* Has deposition of waste into surface water been observed? Indications of this type of 23    activity will appear in records from past practice at a site or from information gathered during 24    personal interviews.
25
* Is ground water discharge to surface water probable? The hydrogeology and 26    geographical information of the area around and inside the site may be sufficiently 27    documented to indicate discharge locations.
28
* Does analytical or circumstantial evidence suggest residual radioactive material in 29    surface water? Any condition considered suspicious can be considered circumstantial 30    evidence.
31
* Is the site prone to flooding? The Federal Emergency Management Agency publishes 32    flood insurance rate maps that delineate 100-year and 500-year flood plains. Ten-year 33    floodplain maps may also be available. Generally, a site on a 500-year floodplain is not 34    considered prone to flooding.
35 3.6.3.4 Ground Water 36 Proper evaluation of ground water includes a general understanding of the local geology and 37 subsurface conditions. Of particular interest is descriptive information relating to subsurface 38 stratigraphy, aquifers, and ground water use.
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Historical Site Assessment                                                                              MARSSIM 1
* Are sources poorly contained? Proper containmentwhich prevents radioactive material 2    from migrating to ground watergenerally uses engineered structures, such as liners, layers 3    of low permeability soil (e.g., clay), and leachate collection systems.
4
* Is the source likely to affect ground water? Underground tanks, landfills, 3 surface 5    impoundments, and lagoons are examples of sources that are likely to release residual 6    radioactive material that migrates to ground water. Aboveground tanks, drummed solid 7    wastes, or sources inside buildings are less likely to contribute to residual radioactive 8    material in ground water.
9
* Is waste quantity particularly large? Depending on the physical and chemical form of the 10    waste and its location, large is a relative term. A small quantity of liquid waste may be of 11    more importance (i.e., greater risk or hazard) than a large quantity of solid waste stored in 12    watertight containers.
13
* Is precipitation heavy? If the site and surrounding area are flat, a combination of heavy 14    precipitation and low infiltration rate may cause precipitation to pool on the site. Otherwise, 15    these characteristics may contribute to high runoff rates that carry radionuclides overland to 16    surface water. Total annual precipitation exceeding one meter (40 in.), or a once in 2-years 17    24-hour precipitation event exceeding 5 cm (2 in.) might be considered heavy.
18 19    The amount of precipitation varies for locations across the continental United States from 20    high (e.g., approximately 200 cm/y [89 in/y] in Mt. Washington, New Hampshire) to low 21    values (e.g., approximately 10.7 cm/y [4.2 in/y] in Las Vegas, Nevada). Certified data on 22    precipitation rates for locations throughout the United States can be obtained from the 23    National Centers for Environmental Information (https://www.ncdc.noaa.gov).
24
* Is the infiltration rate high? Infiltration rates range from very high in gravelly and sandy 25    soils to very low in fine silt and clay soils. Unobstructed surface areas are potential 26    candidates for further examination to determine infiltration rates.
27
* Is the site located in an area of karst terrain? In karst terrain, ground water moves rapidly 28    through channels caused by dissolution of the rock material (usually limestone) that 29    facilitates migration of radioactive material and chemicals.
30
* Is the subsurface highly permeable? Highly permeable soils favor downward movement 31    of water that may transport radioactive materials. Well logs, local geologic literature, or 32    interviews with knowledgeable individuals may help answer this question.
33
* What is the distance from the surface to an aquifer? The shallower the source of ground 34    water, the higher the threat of residual radioactive material. It is difficult to determine 35    whether an aquifer may be a potential source of drinking water in the future (e.g., next 3 Landfills can affect the geology and hydrogeology of a site and produce heterogeneous conditions. It may be necessary to consult an expert on landfills and the conditions they generate.
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MARSSIM                                                                  Historical Site Assessment 1    1,000 years). Use the shallowest aquifer below the site when determining the distance to the 2    surface.
3
* Are suspected radionuclides highly mobile in ground water? Mobility in ground water 4    can be estimated based on the distribution coefficient (Kd) of the radionuclide. Elements with 5    a high Kd, like thorium (e.g., Kd = 3,200 cm3/gram [g]), are not mobile while elements with a 6    low Kd, like hydrogen (e.g., Kd = 0 cm3/g), are very mobile. EPA provides a compilation of Kd 7    values. These values can be influenced by site-specific considerations such that site-8    specific Kd values need to be evaluated or determined. Also, the mobility of a radionuclide 9    can be enhanced by the presence of solvents or other chemicals.
10
* Does analytical or circumstantial evidence suggest residual radioactive material in 11    ground water? Evidence for residual radioactive material may appear in current site data; 12    historical, hydrogeological, and geographical information systems records; or as a result of 13    personal interviews.
14 3.6.3.5 Air 15 Evaluation of air is different than evaluation of other media with a potential for residual 16 radioactive material. Air is evaluated as a pathway for resuspending and dispersing radioactive 17 material.
18
* Were there observations of releases of radioactive material into the air? Direct 19    observation of a release to the air might occur where radioactive materials are suspected to 20    be present in particulate form (e.g., mine tailings, waste pile) or adsorbed to particulates 21    (e.g., radioactive material in soil), and where site conditions favor air transport (e.g., dry, 22    dusty, windy).
23
* Does analytical or circumstantial evidence suggest a release to the air? Other 24    evidence for releases to the air might include areas of residual radioactive material in 25    surface soil that do not appear to be caused by direct deposition or overland migration of 26    radioactive material.
27
* For radon exposure only, are there elevated amounts of radium (226Ra) in the soil or 28    water that could act as a source of radon in the air? The source 226Ra decays to 222Rn, 29    which is radon gas. Once radon is produced, the gas needs a pathway to escape from its 30    point of origin into the air. Radon is readily released from water sources that are open to air.
31    Soil, however, can retain radon gas until it has decayed (see Section 6.8). The rate that 32    radon is emitted by a solid (i.e., radon flux) can be measured directly to evaluate potential 33    sources of radon.
34
* Is there a prevailing wind direction and a propensity for windblown transport of 35    radioactive material? Information pertaining to geography, ground cover (e.g., amount and 36    types of local vegetation), meteorology (e.g., wind speed at 7 meters [23 feet] above ground 37    level) for and around the site, and site-specific parameters related to surface soil 38    characteristics enter into calculations used to describe particulate transport. Mean annual May 2020                                          3-19                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Historical Site Assessment                                                                  MARSSIM 1    wind speed can be obtained from the National Weather Service surface station nearest to 2    the site.
3 3.6.3.6 Structures 4 Structures used for storage, maintenance, or processing of radioactive materials are potential 5 sources of residual radioactive material. The questions presented in Table 3.1 help determine 6 whether a building might be affected by residual radioactive material. The questions listed in this 7 section are for identifying structures, or portions of structures, that might not be identified using 8 Table 3.1 but have a potential for residual radioactive material. Section 4.8.3.1 also presents 9 useful information on identifying structures with residual radioactive material.
10
* Were adjacent structures used for the storage, maintenance, or processing of 11    radioactive material? Adjacent is a relative term for this question. A processing facility with 12    a potential for venting radioactive material to the air could deposit residual radioactive 13    material on buildings downwind. A facility with little potential for release outside of the 14    structures handling the material would be less likely to deposit radioactive material on 15    nearby structures.
16
* Is a building, its addition, or a new structure located on a former radioactive waste 17    burial site or on land with residual radioactive material? Comparing past and present 18    photographs or site maps and retrieving building permits or other structural drawings and 19    records in relation to historical operations information will reveal site locations where 20    structures may have been built over buried waste or land with residual radioactive material.
21
* Was the building constructed using materials containing residual radioactive 22    material? Building materials (e.g., concrete, brick, plaster, cement, wood, metal, cinder 23    block) may contain residual radioactive material.
24
* Does the potentially non-impacted portion of the building share a drainage system or 25    ventilation system with areas with potential residual radioactive material? Technical 26    and architectural drawings for site structures, along with visual inspections, are required to 27    determine if this is a concern in terms of current or past operations.
28
* Is there evidence that previously identified areas of residual radioactive material were 29    remediated by painting or similar methods of immobilization? Removable sources of 30    residual radioactive material were sometimes immobilized by painting, partition, or the 31    addition of floor layers (e.g., tiles, carpet). These sources may be more difficult to locate and 32    may need special consideration when planning subsequent surveys.
33 3.6.4  Develop a Conceptual Model of the Site 34 Starting with project planning activities, gather and analyze available information to develop a 35 conceptual site model. The model is essentially a site diagram showing locations of known 36 radioactive material, areas of suspected residual radioactive material, types and concentrations 37 of radionuclides in impacted areas, media with potential residual radioactive material, and 38 locations of potential reference (background) areas. The diagram should include the general 39 layout of the site, including buildings and property boundaries. When possible, one should NUREG-1575, Revision 2                              3-20                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                    Historical Site Assessment 1 produce three-dimensional diagrams. The conceptual site model will be upgraded and modified 2 as information becomes available throughout the RSSI process. The process of developing this 3 model is also briefly described in Attachment A of EPA 1996a.
4 The model is used to assess the nature and the extent of residual radioactive material; to 5 identify potential sources of residual radioactive material, release mechanisms, exposure 6 pathways, and human and environmental receptors; and to develop exposure scenarios.
7 Further, this model helps identify data gaps and determine media to be sampled, and it assists 8 staff in developing strategies for data collection. Site history and preliminary survey data 9 generally are extremely useful sources of information for developing this model. The conceptual 10 site model should include known and suspected sources of residual radioactive material, the 11 types of radioactive material, and affected media. Such a model can also illustrate known or 12 potential routes of migration and known or potential human and environmental receptors.
13 The site should be classified or initially divided into similar areas. Classification may be based 14 on the operational history of the site or observations made during the site reconnaissance (see 15 Section 3.5). After the site is classified using current and past site characteristics, further divide 16 the site or facility based on anticipated future use. This classification can help (1) assign limited 17 resources to areas that are anticipated to be released without restrictions, and (2) identify areas 18 with little or no possibility of unrestricted release. Figure 3.2 shows an example of how a site 19 might be classified in this manner. Further classification of a site may be possible based on site 20 disposition recommendations (unrestricted vs. release with passive controls).
21 3.6.5    Professional Judgment 22 In some cases, traditional sources of information, data, models, or scientific principles are 23 unavailable, unreliable, conflicting, or too costly or time consuming to obtain. In these instances, 24 professional expert judgment may be the only practical tool available to the investigator or 25 regulator. Expert judgment, or expert elicitation, means using the judgments obtained from 26 experts about their field of expertise that are explicitly stated and documented for review and 27 appraisal by others. It is a formal, highly structured, and well-documented process for obtaining 28 the judgment of multiple experts regarding a scientific inquiry or decisionmaking (NRC 1990).
29 For most instances, the issue is not whether to use judgment, but whether to use it in an explicit 30 and disciplined fashion or in an ad hoc manner. An important interrelated question is when and 31 whose judgment should be used. For this guidance, it is often useful to formalize the elicitation 32 and use of judgment for significant technical, environmental, and socioeconomic problems. For 33 general applications, this type of judgment is a routine part of scientific investigation where 34 knowledge is incomplete. For MARSSIM guidance, professional judgment can be used as an 35 independent review of historical data to support decision-making during the HSA or the use of 36 statistical tools or methodology. Professional or expert judgment should be used as necessary, 37 particularly in situations where data are not reasonably obtainable by collection, 38 experimentation, field measurements, or when the cost of data collection is prohibitive.
39 Typically, the process of recruiting professionals for expert judgment should be documented and 40 as unbiased as possible. The credentials of the selected individual or individuals should 41 enhance the credibility of the elicitation, and their ability to communicate their reasoning is a 42 primary determinant of the quality of the results. Qualified expert professionals can be identified May 2020                                          3-21                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Historical Site Assessment                                                MARSSIM 1
2 Figure 3.2: Example Showing How a Site Might be Categorized Before Cleanup Based on 3 the Historical Site Assessment NUREG-1575, Revision 2                  3-22                                May 2020 DRAFT FOR PUBLIC COMMENT                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                                  Historical Site Assessment 1 by different sources, including the planning team, professional organizations, government 2 agencies, universities, consulting firms, and public interest groups. The selection criteria for the 3 professionals should include potential conflict of interest (economic or personal), evidence of 4 expertise in a required topic, objectiveness, and availability.
5 3.7    Determining the Next Step in the Site Investigation Process 6 Upon completion, the HSA will support one of three possible recommendations:
7 1. An emergency action may be necessary to reduce the risk to human health and the 8      environment, such as a Superfund removal action, which is discussed in detail by EPA 9      (EPA 1988a).
10 2. The site or area is categorized as impacted, and further investigation is needed before a 11      decision regarding final release can be made. The area may be classified as Class 1, 12      Class 2, or Class 3, and a scoping survey or a characterization survey may be performed as 13      necessary. Information collected during the HSA can be very useful in planning these 14      subsequent survey activities.
15 3. The site or area is categorized as non-impacted, a term that is applied where there is no 16      reasonable potential to contain radionuclide concentration(s) or radioactive material above 17      background (10 CFR 50). The site or area can be released.
18 As stated in Section 1.1, the purpose of this manual is to describe a process-oriented approach 19 for demonstrating that the concentration of residual radioactive material does not exceed the 20 release criteria. The highest probability of demonstrating this can be obtained by sequentially 21 following each step in the RSSI process. In some cases, however, performing each step in the 22 process is not practical or necessary. This section provides information on how the results of the 23 HSA can be used to determine the next step in the process.
24 The best method for determining the next step is to review the purpose for each type of survey 25 described in Chapter 5. For example, a scoping survey is performed to provide sufficient 26 information for determining (1) whether the present residual radioactive material warrants further 27 evaluation, and (2) initial estimates of the level of effort for decontamination and for preparing a 28 plan for a more detailed survey. If the HSA demonstrates that this information is already 29 available, do not perform a scoping survey. On the other hand, if the information obtained during 30 the HSA is limited, a scoping survey may be necessary to narrow the scope of the 31 characterization survey.
32 The exception to conducting additional surveys before an FSS is the use of HSA results to 33 release a site. Generally, the analytical data collected during the HSA are not adequate to 34 statistically demonstrate compliance for impacted areas as described in Chapter 8. This means 35 that the decision to release the site will be based on professional judgment. This determination 36 will ultimately be decided by the responsible regulatory agency.
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Historical Site Assessment                                                                MARSSIM 1 3.8  Historical Site Assessment Report 2 A narrative report is generally the best format to summarize what is known about the site, what 3 is assumed or inferred, activities conducted during the HSA, and all researched information.
4 Cite a supporting reference for each factual statement given in the report. Attach copies of 5 references (i.e., those not generally available to the public) to the report. The narrative portion of 6 the report should be written in plain English and avoid the use of technical terminology.
7 A sample HSA report format is provided in Example 1. Additional information not identified in 8 the outline may be requested by the regulatory agency at its discretion. The level of effort to 9 produce the report should reflect the amount of information gathered during the HSA.
10 3.9  Review of the HSA 11 The planning team should ensure that someone (a first reviewer) conducts a detailed review of 12 the HSA report for internal consistency and as a QC mechanism. A second reviewer with 13 considerable site assessment experience should then examine the entire information package 14 to ensure consistency and to provide an independent evaluation of the HSA conclusions. The 15 second reviewer also evaluates the package to determine if special circumstances exist where 16 radioactive material may be present but not identified in the HSA. Both the first reviewer and the 17 second independent reviewer should examine the HSA written products to ensure internal 18 consistency in the reports information, summarized data, and conclusions. The site review 19 ensures that the HSAs recommendations are appropriate.
20 An important QA objective is to find and correct errors. A significant inconsistency indicating 21 either an error or a flawed conclusion, if undetected, could contribute to an inappropriate 22 recommendation. Identifying such a discrepancy directs the HSA investigator and site reviewers 23 to re-examine and resolve the apparent conflict.
24 Under some circumstances, experienced investigators may have differing interpretations of site 25 conditions and draw differing conclusions or hypotheses regarding the likelihood of residual 26 radioactive material. Any such differences should be resolved during the review. If a reviewer's 27 interpretations contradict those of the HSA investigator, the two should discuss the situation and 28 reach a consensus. This aspect of the review identifies significant points about the site 29 evaluation that may need detailed explanation in the HSA narrative report to fully support the 30 conclusions. Throughout the review, the HSA investigator and site reviewers should keep in 31 mind the need for conservative judgments in the absence of definitive proof to avoid 32 underestimating the presence of residual radioactive material, which could lead to an 33 inappropriate HSA recommendation.
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MARSSIM                                                                Historical Site Assessment Example 1: HSA Report Format
: 1. Glossary of Terms, Acronyms, and Abbreviations
: 2. Executive Summary
: 3. Purpose of the Historical Site Assessment
: 4. Property Identification
: 1. Physical Characteristics
: 1. NameCERCLIS ID# (if applicable) owner/operator name, address
: 2. Locationstreet address city county state geographical coordinates
: 3. TopographyUSGS 7.5-minute quadrangle or equivalent
: 4. Stratigraphy
: 2. Environmental Setting
: 1. Geology
: 2. Hydrogeology
: 3. Hydrology
: 4. Meteorology
: 5. Historical Site Assessment Methodology
: 1. Approach and Rationale
: 2. Boundaries of Site
: 3. Documents Reviewed
: 4. Property Inspections
: 5. Personal Interviews
: 6. History and Current Usage
: 1. Historyyears of operation, type of facility, description of operations, regulatory involvement permits and licenses, waste handling procedures
: 2. Current Usagetype of facility, description of operations, probable source types and sizes, description of spills or releases, waste manifests, radioactive inventories, emergency or removal actions
: 3. Adjacent Land Usagesensitive areas, such as wetlands or preschools
: 7. Findings
: 1. Potential Sources of Residual Radioactive Material
: 2. Potential Areas with Residual Radioactive Material
: 1. Impacted AreasKnown and Potential
: 2. Non-Impacted Areas
: 3. Potential Media with Residual Radioactive material
: 4. Related Environmental Concerns
: 8. Conclusions
: 9. References
: 10. Appendices A. Conceptual Model and Site Diagram Showing Classifications B. List of Documents C. Photo Documentation Log
: a. Original Photographs of the Site and Pertinent Site Features 1
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MARSSIM                                                                    Considerations for Planning Surveys 1                  4 CONSIDERATIONS FOR PLANNING SURVEYS 2 4.1    Introduction 3 4.1.1    Purpose 4 This chapter is intended to introduce the Multi-Agency Radiation Survey and Site Investigation 5 Manual (MARSSIM) user to general considerations for planning MARSSIM-based surveys by 6 presenting areas of consideration common to Radiation Surveys and Site Investigations (RSSIs) 7 with an emphasis on final status surveys (FSSs). 1 Detailed technical information about planning 8 surveys will follow in the subsequent chapters. For the purposes of this chapter, it is assumed 9 that a Historical Site Assessment (HSA) has been performed, and the results are available to 10 the survey design team.
11 4.1.2    Scope 12 The emphasis in MARSSIM is on FSSs of surface soil and surfaces of buildings and outdoor 13 areas to demonstrate compliance with cleanup regulations. However, MARSSIM discusses four 14 types of surveys:
15
* Scoping 16
* Characterization 17
* Remedial Action Support (RAS) 18
* Final status 19 These survey types are discussed in more detail in Chapter 5. The emphasis on FSSs should 20 be kept in mind during the design phase of all surveys. The topics discussed in this chapter 21 focus on planning the FSS.
22 4.1.3    Overview of Survey Planning 23 In the following sections of this chapter, you will be introduced to many potentially unfamiliar 24 concepts, terms, definitions, etc., specifically related to planning surveys. Informal definitions will 25 be given in this chapter; however, the reader should refer to the Glossary for complete 26 definitions. The following topics related to survey planning are discussed in this chapter:
27
* Data Quality Objectives (DQO) process: The DQO process is used to develop performance 28    and acceptance criteria that clarify study objectives, define the appropriate type of data, and 29    specify tolerable levels of potential decision errors that will be used as the basis for 30    establishing the quality and quantity of data needed to support decisions.
31
* Survey types: There are four MARSSIM survey types: scoping, characterization, RAS, and 32    final status. The emphasis of this chapter will be on FSSs.
1 MARSSIM uses the word should as a recommendation, not as a requirement. Each recommendation in this manual is not intended to be taken literally and applied at every site. MARSSIMs survey planning documentation will address how to apply the process on a site-specific basis.
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Considerations for Planning Surveys                                                      MARSSIM 1
* Unity rule: The unity rule is used when more than one radionuclide is present at a 2    concentration that is distinguishable from background and where a single concentration 3    comparison does not apply. In this case, the mixture of radionuclides is compared against 4    default concentrations by applying the unity rule. This is accomplished by determining:
5    (1) the ratio between the concentration of each radionuclide in the mixture, and (2) the 6    concentration for that radionuclide in an appropriate listing of default values. The sum of the 7    ratios for all radionuclides in the mixture should not exceed 1.
8
* Radionuclides and derived concentration guideline levels (DCGLs): The design team needs 9    to determine the radionuclides of concern and final form of the DCGLs. The DCGLs are 10    typically based on dose (or risk) pathway modeling, which is used to determine release 11    criteria expressed in measurable radiological quantities. These can be a soil concentration, 12    surface (areal) concentration, or external dose (or exposure) rate.
13
* Area and site considerations: Properly classifying areas as impacted or non-impacted, 14    identifying survey units, and selecting background reference areas is critical for the 15    successful execution of a FSS.
16
* Statistical considerations: MARSSIM recommends the use of statistical hypothesis testing in 17    all but the simplest of surveys (See Appendix B). The MARSSIM user must be conversant 18    with the statistical concepts discussed in the manual and should consider incorporating a 19    statistician in the design team.
20
* Measurements: The detection capabilities of all the measurement (sampling included) 21    techniques must be evaluated to ensure that the data and measurement quality objectives 22    are met.
23
* Site preparation: Site preparation includes efforts to gain permission to access the site, 24    ensuring that the survey team and equipment can operate safely, and establishing the 25    logistical means to perform the survey should be started early.
26
* Health and safety: The health and safety of the workers is a high priority, so each site must 27    have a documented health and safety plan.
28
* Survey design examples: A few simplified examples are presented in Section 4.12 to 29    illustrate the process for planning surveys.
30 4.2    Data Quality Objectives Process 31 DQOs were introduced in Chapter 1, expanded upon in Chapter 2, and discussed in detail in 32 Appendix D. The survey design team must be familiar with the DQO process to properly design 33 a survey. The DQO process can be summarized in seven steps:
34 1. State the problem.
35 2. Identify the decisions to be made.
36 3. Identify inputs to the decision.
37 4. Define the study boundaries.
38 5. Develop a decision rule.
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MARSSIM                                                          Considerations for Planning Surveys 1 6. Specify limits on decision errors.
2 7. Optimize the survey design.
3 4.2.1  Planning Phase 4 Using the DQO process allows the survey design team to use a graded approach to ensure that 5 the level of effort meets the design goals in a technically defensible and cost-effective manner.
6 The intent of any survey is to ensure that the decision makers have the appropriate type, 7 quantity, and quality of environmental data needed to make the correct decision. DQOs are 8 qualitative and quantitative statements derived from the DQO process that do the following:
9
* Clarify the study objective: The first step in any survey is to determine the objectives of the 10    survey (DQO Steps 1 and 2). Depending on the data available from the previous RSSI 11    activities (e.g., HSA review), the objectives of a survey can range from augmenting HSA 12    information to be used as input in designing a characterization survey to releasing a survey 13    unit. An important part of this clarification is the determination of the initial condition of each 14    survey unit: The survey unit is assumed to be not clean (Scenario A) or clean 15    (Scenario B). See Section 2.5.1 and Sections D.1.1 and D.1.2 of Appendix D for more 16    details.
17
* Define the most appropriate type of data to collect: Once the objectives of the survey have 18    been agreed upon, the design team needs to determine what data need to be collected 19    (DQO Step 3). Implicit in this step is the determination of the radionuclides of concern, 20    choice of equipment, detection limits, analytical methods, statistical tests, etc., that will be 21    used to meet the objectives of the survey.
22
* Determine the most appropriate conditions for collecting the data: In general, the study 23    boundaries of a survey (DQO Step 4) are spatial; for example, the selection of the survey 24    units. However, if the objective of the survey is to collect data for classification, then the 25    spatial boundary of the survey might be the entire site under consideration. Throughout the 26    RSSI process, decisions need to be made; for example, based on a review of the HSAs 27    conclusions and the results of scoping/characterization surveys, the decision maker will 28    determine survey unit boundaries and classifications.
29
* Specify limits on decision errors that will be used as the basis for establishing the quantity 30    and quality of data needed to support the decision: To make decisions, the outputs of the 31    survey must be in a form amenable to decision-making (DQO Step 5). MARSSIM 32    recommends the use of statistical hypothesis testing to make decisions to release a survey 33    unit. Because of the overall uncertainty in the surveying process, there is always a chance 34    of a decision error (e.g., incorrectly concluding that a survey unit meets the release criteria, 35    when in fact it does not). The chance of a decision error cannot be eliminated; however, it 36    can be controlled (DQO Step 6). The survey design team must be aware of the chance of 37    decision errors and take measures to control them (e.g., collecting more samples, using 38    more precise measurement techniques, and using better surveying and sampling designs).
39 When the previous steps are completed, the survey design team can optimize the survey plan 40 (DQO Step 7); the team might need to work through this step several times to arrive at the best 41 design. Appendix D discusses the planning phase of the data life cycle in detail. The MARSSIM 42 user should read and be conversant with Appendix D.
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Considerations for Planning Surveys                                                      MARSSIM 1 Regardless of the survey type under consideration, the DQOs remain the overarching guide for 2 planning; the design team needs to explain the who, what, where, when, why, and how for a 3 survey.
4 4.2.2    Quality System 5 MARSSIM requires that all environmental data collection and use take place in accordance with 6 a site-specific systematic planning process that incorporates industry-established quality 7 assurance and quality control (QA/QC). The goal of a QA/QC program is to identify and 8 implement sampling and analytical methodologies which limit the introduction of error into 9 analytical data. For MARSSIM data collection and evaluation, a quality system is needed to 10 ensure that radiation surveys produce results that are of the type and quality needed and 11 expected for their intended use. A quality system is a management system that describes the 12 elements necessary to plan, implement, and assess the effectiveness of QA/QC activities. This 13 system establishes many functions, including 14
* quality management policies and guidelines for the development of organization- and 15    project-specific quality plans 16
* criteria and guidelines for assessing data quality 17
* assessments to ascertain the effectiveness of QA/QC implementation 18
* training programs related to QA/QC implementation.
19 A quality system ensures that MARSSIM decisions will be supported by sufficient data of 20 adequate quality and usability for their intended purpose, and it further ensures that such data 21 are authentic, appropriately documented, and technically defensible. MARSSIM uses the 22 project-level components of a quality system as a framework for planning, implementing, and 23 assessing environmental data collection activities.
24 In accordance with the environmental data quality system described in Appendix D, all 25 environmental data collection and use are to take place in accordance with a site-specific 26 systematic planning process (SPP) that consists of planning, implementation, and assessment 27 phases. The results of the SPP are usually documented in a Quality Assurance Project Plan 28 (QAPP). A QAPP integrates all technical and quality aspects and defines in detail how specific 29 QA/QC activities will be implemented during the survey project will be developed. The Uniform 30 Federal Policy (UFP) for QAPPs (EPA 2005a, 2005b, 2005c) was developed to provide 31 procedures and guidance for consistently implementing the national consensus standard 32 ANSI/ASQ E-4, Quality Systems for Environmental Data and Technology Programs, for the 33 collection and use of environmental data. The UFP for QAPPs is presented in three volumes:
34
* Part 1, UFP-QAPP Manual (EPA-505-B-04-900A, DTIC ADA 427785) (EPA 2005a.)
35
* Part 2A, UFP-QAPP Workbook (EPA-505-B-04-900C, DTIC ADA 427486) (EPA 2005c.)
36
* Part 2B, Quality Assurance/Quality Control Compendium: Minimum QA/QC Activities (EPA-37    505-B-04-900B, DTIC ADA 426957) (EPA 2005b.)
38 Using this scientific, logical approach to planning for data collection and assessment at a site 39 helps ensure that the amounts and types of data collected are appropriate for decisionmaking 40 and that the physical, environmental, chemical, and radiological characteristics of the site are NUREG-1575, Revision 2                          4-4                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                        Considerations for Planning Surveys 1 adequately defined. The development of a QAPP is one of the first team-based QA/QC activities 2 performed in the project planning stage.
3 The objective of the UFP-QAPP is to provide a single national consensus document for 4 consistently and systematically implementing the project-specific requirements of ANSI/ASQ E4 5 (ASQC 1995) and help ensure the quality, objectivity, utility, and integrity of environmental data.
6 Information on selecting the number and type of QC measurements for a specific project are 7 provided in Section 3.4; Tables 4, 5, and 6 of the UFP-QAPP Part 1; and Worksheet 28 of the 8 UFP-QAPP Part 2A.
9 Minimum QA/QC activities are specified for all environmental data collection and use in the 10 UFP-QAPP Part 2B. However, this matrix of minimum requirements is not meant to be a 11 replacement for a site-specific QAPP. A wide range of site-specific guidelines for data collection 12 activities specified in the survey plan should be determined that relate to the ultimate use of the 13 data. These guidelines include, but are not limited to 14
* types of decisions that will be supported by the data 15
* project quality objectives 16
* acceptance criteria for data quality indicators (also known as measurement performance 17    criteria) 18
* survey plan, including location of environmental and QC samples and measurements 19
* types of radionuclides and analyses that require laboratory analysis (on-site, field, or fixed 20    lab) 21 The QA/QC activities specified in the QA matrix represent a minimum list of activities. Other 22 QA/QC activities may be added, depending on the decisions to be made and on site-specific 23 conditions. The matrix of minimum QA/QC activities is organized by 24
* survey type (i.e., scoping or characterization) for surveys prior to the FSS 25
* data uses (e.g., confirmatory measurements) for RAS surveys 26
* data type (i.e., screening versus definitive data) 27
* project stage (i.e., plan, implement, assess, decide) 28 4.3    Survey Types 29 4.3.1    Scoping 30 MARSSIM defines a scoping survey as a type of survey that is conducted to identify 31 (1) radionuclides present, (2) relative radionuclide ratios, and (3) general concentrations and 32 extent of residual radioactive material. In conjunction with an HSA, the results of a scoping 33 survey can help determine (1) preliminary radionuclides of concern, (2) interim site and survey 34 unit boundaries, (3) initial area classifications, (4) data gaps, and (5) initial estimates of the level 35 of effort for remediation, and (6) information for planning a more detailed survey, such as a 36 characterization survey. Methods for planning, conducting, and documenting scoping surveys 37 are described in Section 5.2.1.
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Considerations for Planning Surveys                                                        MARSSIM 1 4.3.2    Characterization 2 MARSSIM defines a characterization survey as a type of survey that includes facility or site 3 sampling, monitoring, and analysis activities to determine the extent and nature of residual 4 radioactive material. Characterization surveys provide the basis for acquiring necessary 5 technical information to develop, analyze, and select appropriate cleanup techniques.
6 Characterization surveys can be developed to meet a very broad range of objectives, many of 7 which are outside the scope of MARSSIM. The guidance in Section 5.2.2 concentrates on 8 providing characterization survey planning information with an emphasis on the FSS design.
9 4.3.3    Remedial Action Support 10 MARSSIM defines remedial action as Those actions that are consistent with a permanent 11 remedy taken instead of, or in addition to, removal action in the event of a release or threatened 12 release of a hazardous substance into the environment, to prevent or minimize the release of 13 hazardous substances so that they do not migrate to cause substantial danger to present or 14 future public health or welfare or the environment. A RAS survey supports remediation 15 activities and is used to monitor the effectiveness of remediation efforts intended to reduce 16 residual radioactive material to acceptable levels. The general objectives of an RAS are to 17 (1) support remediation activities, (2) determine when a site or survey unit is ready for the FSS, 18 and (3) provide updated estimates of site-specific parameters to use for planning the FSS.
19 Methods for planning, conducting, and documenting an RAS are described in Section 5.2.3.
20 4.3.4    Final Status 21 4.3.4.1 Survey 22 MARSSIM defines an FSS as measurements and sampling to describe the radiological 23 conditions of a site, following completion of remediation activities (if any) in preparation for 24 release. An FSS is performed to demonstrate that a survey unit meets the agreed-upon release 25 criteria. In other words, that FSS is designed to answer the question, Does the concentration of 26 residual radioactive material in each survey unit satisfy the predetermined criteria for release for 27 unrestricted use or, where appropriate, for use with designated limitations (restricted release)?
28 The primary objective of MARSSIM is the FSS. The design of FSSs is discussed in detail in 29 Section 5.3, with the remainder of MARSSIM expanding on the design, execution, and 30 assessment of FSSs.
31 Figure 4.1 illustrates the sequence of activities described in this chapter and their relationship to 32 the survey design process.
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MARSSIM                                                        Considerations for Planning Surveys Survey Objectives
: 1. Identify radionuclides of concern
: 2. Identify associated radionuclides
: 3. Identify conditions to be evaluated Identify Radionuclides          Section 4.3      or measured Establish DCGLs              Section 4.4 Classify Areas by Potential for Section 4.5 Residual Radioactive Material Group/Separate Areas into Survey Units              Section 4.6 Is Radionuclide SELECT BKGD Present in                Yes REFERENCE AREAS Background?
Section 4.5 To Figure 4.2 From Figure 4.2 Prepare Site for Section 4.9 Survey Access Establish Survey Location Section 4.9.5 Reference System Design Surey          Chapter 5 1
2 Figure 4.1: Sequence of Preliminary Activities Leading to an FSS Design May 2020                                            4-7                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Considerations for Planning Surveys                                                      MARSSIM 1 4.3.4.2 Verification Process 2 Historically, regulators commissioned verification surveys after the completion of an FSS.
3 However, the application of the DQO process to the verification process has led to the 4 development of more effective processes, such as in-process decommissioning inspections 5 (Abelquist, 2014). For example, NRC (2008) and DOE (2011c) require verification inspections of 6 some sort; these documents can be used as guides for including verification processes in the 7 FSS design project. The personnel who plan and execute an FSS should be familiar with 8 independent verification (IV) process and be prepared to work with regulators and their 9 contractors to support the verification process during all phases of the FSS. Abelquist (2014) 10 provides an example of decommissioning inspection plan that might be useful when designing 11 an FSS.
12 Bailey (2008) summarized the experiences from IV activities of Oak Ridge Institute for Science 13 and Education (ORISE) in support of U.S. Department of Energy decommissioning projects. In 14 conclusion, Bailey (2008) states that 15          Independent verification should be integrated into the planning stages rather than 16          after the cleanup contractor has completed the remediation work and 17          demobilized from the site. The IV of onsite remediation and FSS activities should 18          be coordinated and if possible implemented in parallel with the contractor to 19          minimize schedule impacts. A well-implemented and thorough IV program for a 20          site requires IV involvement throughout the D&D [Decontamination and 21          Decommissioning] process. Independent verification is not a substitute for routine 22          contractor quality assurance; however, IV activities often improve the contractors 23          performance. IV recommendations often improve the contractors FSS 24          procedures and results, while increasing the probability of complete remediation 25          and documentation.
26 4.3.5    Simplified Procedures 27 The design team should be aware that under certain conditions (e.g., sites where only small 28 quantities of radioactive materials exempted from or not requiring a specific license) a simplified 29 procedure might be able to be used to demonstrate regulatory compliance. The design team 30 should refer to Appendix B and seek regulatory approval before using this simplified procedure.
31 4.3.6    A Note on Subsurface Assessments 32 Many users might need to assess subsurface residual radioactive materials. Strictly speaking, 33 this is beyond the scope of MARSSIM; however, the general concepts contained in MARSSIM 34 (e.g., the DQO process, statistical survey and sampling design, etc.) may be appropriate to 35 address subsurface contamination. As always, any approach to site decommissioning needs to 36 be discussed with the appropriate regulatory authorities.
37 4.3.7    Uranium Mill Tailings Radiation Control Act of 1978 Sites 38 At Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA) sites, EPAs Health and 39 Environmental Protection Standards for Uranium and Thorium Mill Tailings (see 40 CFR 192) 40 are applicable. However, the technical requirements in these standards are not always 41 consistent with some of the recommendations in MARSSIM. Specifically, the soil cleanup 42 standards for 226Ra and 228Ra are specified as averages over an area of 100 square meters 43 (m2). Additional details for planning at UMTRCA site are provide in Section 4.12.9.
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MARSSIM                                                          Considerations for Planning Surveys 1 4.4      The Unity Rule 2 The unity rule is used to ensure that the total dose (risk) from all sources (or media) and all 3 radionuclides associated with each source does not exceed the release criteria. It is to be used 4 when more than one radionuclide is present and distinguishable from background and a single 5 concentration does not apply. Essentially, this means that if measurements of different 6 quantities are made at a location, then the unity rule must be used. For example, the unity rule 7 would be used if two radionuclides are measured in each soil sample or if gross alpha and gross 8 beta measurements are made at each location and the results are being compared to specific 9 DCGLs.
10 The total amount of anything, whether dose, counts, or activity, is simply the sum of its parts 11 ( ):
Total = 1 + 2 +  +  +  +  =                      (4-1)
                                                                          =1 12 Dividing both sides of Equation (4-1) by the total yields the following fundamental equation 13 (Equation (4-2)):
1 = 1 + 2 + +  +  +  =                      (4-2)
                                                                      =1 14 The basic statement of this equation is that sum of all fractions must add to unity (1).
15 When using the sum of fractions to demonstrate compliance in MARSSIM, each fraction is 16 determined by dividing each part (e.g., the concentration of residual radioactive material due to 17 a specific radionuclide/source) by the respective release criterion (e.g., a derived concentration 18 guideline level [DCGL]). In an FSS for a survey unit to be released, the dose or risk from all 19 radionuclides and all sources in a survey unit must be less than or equal to the applicable 20 release criterion, and the sum of fractions for multiple radionuclides/sources must be less than 21 or equal to unity:
Total Dose or Risk =  (Dose or Risk Component)  Release Criterion              (4-3)
                                  =1 22 Dividing the terms in Equation (4-3) by the applicable release criterion:
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Considerations for Planning Surveys                                                      MARSSIM Total Dose or Risk            Dose or Risk Component
                                    =                                  1            (4-4)
Release Criterion                Release Criterion       
                                      =1 1 If the dose/risk components and release criteria are expressed as concentrations (e.g., express 2 the dose/risk as concentration and release criterion as DCGLs as discussed above),
3 Equation (4-4) can be written in terms of concentrations (see Equation (4-5)):
Dose or Risk Component                    C
                                                    =              1              (4-5)
Release Criterion DCGL 
                  =1                                    =1 4 where 5
* C is the concentration of the th component (e.g., radionuclide or source) leading to dose 6      or risk.
7
* DCGL is the derived concentration guideline level of the th component (e.g., radionuclide 8      or source) leading to dose or risk.
9 This is the traditional form of the unity rule as used and defined in MARSSIM.
10 Other applications of Equation (4-1) or derivatives, such as deriving a gross activity DCGL, will 11 be covered in the corresponding section of this and other chapters as needed.
12 4.5    Radionuclides 13 4.5.1    Radionuclides of Concern 14 During the design of an FSS, the survey team should thoroughly review of all the remediation 15 activities conducted before the FSS to determine the radionuclides of concern and their 16 expected concentrations in each survey unit. The team should also determine if the 17 concentrations of the radionuclides of concern in the background need to be accounted for in 18 the FSS design; for example, if a radionuclide is not present in the background, the FSS can be 19 designed based on the one-sample Sign test.
20 If neither remedial action nor HSA data exist, then the survey design team should make the 21 identification of the radionuclides of concern a primary objective of the teams actions. Whether 22 through an HSA, a scoping survey, a characterization survey, or some combination of them, the 23 team must make an initial characterization of the types, concentrations, and distribution of the 24 residual radioactive material at the site.
25 4.5.2    Release Criteria and Derived Concentration Guideline Levels 26 The decommissioning process ensures that residual radioactive material will not result in 27 individuals being exposed to unacceptable levels of radiation dose or risk. Regulatory agencies 28 establish radiation dose standards based on risk considerations and scientific data relating dose 29 to risk. These radiation dose standards are the fundamental release criteria; however, they are 30 not measurable. To translate these release criteria into measurable quantities, residual levels of NUREG-1575, Revision 2                            4-10                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                Considerations for Planning Surveys 1 radioactive material corresponding to the release criteria are derived (calculated) by analysis of 2 various pathways (e.g., direct radiation, inhalation, and ingestion) and scenarios (e.g., resident 3 farmer, industrial, recreational) through which exposures could occur.
4 These DCGLs are usually presented in terms of surface or mass activity concentrations of 5 radioactive material (typically becquerels [Bq]/m2, disintegrations per minute/centimeters 6 squared [dpm/100 cm2], Bq/kilogram [Bq/kg], or picocurie/gram [pCi/g], respectively). The 7 details of the derivation of DCGLs are beyond of the scope of MARSSIM. However, the survey 8 design team should understand how DCGLs were derived, because the models and 9 assumptions used to derive DCGLs can drive how measurements are made. For example, if 10 DCGLs for soil were derived based on an assumption that the residual radioactive material was 11 restricted to the top 15 cm of soil, a condition verified in a characterization survey, then for the 12 FSS it would not be appropriate to collect soil samples from the top 30 cm of soil. In many 13 cases, generally applicable DCGLs can be obtained from the relevant regulatory agency. In 14 other cases, DCGLs derived for site-specific conditions can be used with permission of the 15 relevant regulatory agency.
16 There are two types of DCGLs (DCGLW and DCGLEMC) 2 applicable to satisfying 17 decommissioning objectives:
18
* The DCGLW is the mean 3 concentration of residual radioactive material within a survey unit 19      that corresponds to release criteria (e.g., regulatory limit in terms of dose or risk).
20
* The DCGLEMC accounts for the smaller area of elevated residual radioactive material and is 21      typically derived based on dose (or risk) pathway modeling. The DCGLEMC is always greater 22      than or equal to the DCGLW.
23 The contributions to dose or risk from both the uniform area and areas of elevated residual 24 radioactive material, if applicable, must meet the condition expressed in Equation 8-4 in 25 Section 8.6.2. The development of regulatory requirements leading to the establishment of a 26 DCGLEMC is beyond the scope of MARSSIM and is determined strictly through the requirements 27 of regulatory agencies. Therefore, it is important to work with the applicable regulatory agency 28 to determine whether requirements for a DCGLEMC should be consistent with the approach 29 presented in MARSSIM or those in regulatory documents. When properly justified to and 30 accepted by the regulatory agency, no DCGLEMC requirement may be needed at all. DCGLEMCs 31 and associated requirements for areas of elevated radioactive material should be clearly stated 32 and properly approved, and surveys should demonstrate compliance with those requirements.
33 More discussion about elevated areas of radioactive material and their consideration during 34 radiological survey activities can be found in Section 5.3.5.
35 To prove compliance with requirements for discrete radioactive particles, some surveys have 36 used the MARSSIM Elevated Measurement Comparison (EMC) process (see Section 8.6.1).
37 As discussed in Section 4.12.8, the MARSSIM EMC process might not apply to discrete 38 radioactive particles; the survey design team should use the DQO process to address such 39 particles in surface soils or building surfaces. More discussion about discrete radioactive 2 The W in DCGL colloquially refers to wide-area or average. The EMC in DCGL W                                                                  EMC refers to the Elevated Measurement Comparison.
3 The mean is sum of the values divided by the number of measurements and is commonly called the average.
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Considerations for Planning Surveys                                                      MARSSIM 1 particles and their consideration during radiological survey activities can be found in 2 Section 4.12.8.
3 The MARSSIM user should remember five things about release criteria and DCGLs:
4
* The fundamental release criteria are dose or risk based and cannot be measured.
5
* The fundamental release criteria are translated into measurable DCGLs.
6
* The determination of acceptable DCGLs must be coordinated with the regulator.
7
* The derivation of radionuclide-specific DCGLs is beyond the scope of MARSSIM.
8
* The application of radionuclide-specific DCGLs to derive operational DCGLs for FSSs is the 9      responsibility of MARSSIM user.
10 4.5.3    Applying DCGLs 11 This section focuses on introducing the application and modifications of DCGLs to derive 12 operational DCGLs for various situations commonly encountered while planning FSSs. An 13 operational DCGL is any modification or combination of radionuclide-specific DCGLs to derive 14 measurable quantity (e.g., a gross beta activity DCGL). The simplest application of a DCGL is 15 when a single radionuclide is distributed uniformly throughout a survey unit. When multiple 16 radionuclides are present in a survey unit, (1) the ratios of the concentrations of radionuclides 17 are roughly constant (correlated), or (2) the concentrations are unrelated. There are statistical 18 tests that can be performed to calculate the degree of correlation among the concentrations.
19 Ultimately, sound judgment must be used when interpreting the results of the calculations. If 20 there is no physical reason for the concentrations to be correlated, then they are likely not.
21 However, if there is sound evidence of correlation, then that evidence should be used. The 22 survey design team should consult closely with the appropriate regulatory agency during the 23 design phase.
24 Fundamentally, the measurement of residual radioactive material involves one or more of the 25 following:
26
* radionuclide-specific analyses 27
* gross activity measurements 28
* external radiation measurements 29 The choice of the operational DCGL depends on the types of measurements being made. If 30 multiple radionuclides are considered using gross activity measurements, then it might be 31 acceptable to use the smallest DCGL of the radionuclides present. To use surrogate 32 measurements to demonstrate compliance, all significant radionuclides should be identified, the 33 contributions of the various radionuclides should be known, and DCGLs should be developed 34 for each of the radionuclides of concern. If there is a well-established correlation between 35 radionuclide concentrations, then a weighted gross activity DCGL or surrogate-based DCGL 36 might be acceptable. If no correlation exists or a combination of the above options is proposed, 37 then the unity rule must be used.
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MARSSIM                                                        Considerations for Planning Surveys 1 4.5.3.1 DCGLs for a Single Radionuclide 2 For a single radionuclide, compliance can be easily demonstrated if all the measurements in the 3 survey unit are below the DCGL. Otherwise, an appropriate statistical test must be used. This is 4 straightforward when there is one radionuclide (e.g., Sr/Y-90) where radioactive decay products 5 are included in the DCGL. If the radioactive decay products are not included in the DCGL, and 6 the radioactive decay products are present, the survey team must use one of the methods 7 outlined below. Additionally, the methods described below can be used for radionuclides that 8 are not part of the same decay chain (e.g., presence of a mix of fission products, such as Sr-90 9 and Cs-137).
10 If a DCGL for the parent of a serial decay chain includes contributions from the progeny, then 11 the direct application of that DCGL is possible. It is incumbent on the design team to determine 12 if the radionuclides of concern are parents of a decay series and if progeny are accounted for in 13 all DCGLs. For example, values for natural thorium (Th-nat) and natural uranium (U-nat) 14 typically include progeny; however, the design team must confirm this for each case. For 15 information on serial radioactive decay, see Section 4.5.3.8.
16 4.5.3.2 Most Conservative DCGL Approach for Multiple Radionuclides 17 If there are multiple radionuclides in a survey unit, then it might be possible to use the lowest 18 (most restrictive) DCGL. Note that if DCGLmin is the lowest of the DCGLs, then Equation (4-6) 19 applies, and DCGLmin may be applied to the total activity concentration rather than using the 20 unity rule.
C1        C2            C      (C1 +C2 ++C )
                                +        ++                                  1                (4-6)
DCGL1 DCGL2              DCGL          DCGLmin 21 The goal is then to demonstrate that the ratio of the total concentration of all radionuclides to 22 DCGLmin is less than 1, or alternatively that the total concentration of all radionuclides is less 23 than DCGLmin. Although this option may be considered, in many cases it will be too conservative 24 to be useful. Furthermore, the ease of detection must be taken into account during the DQO 25 process if use of the DCGLmin is being considered.
26 4.5.3.3 DCGLs for Multiple Radionuclides in Known Ratios (Surrogate Measurements) 27 For sites with multiple radionuclides, it may be possible to measure just one of the radionuclides 28 and still demonstrate compliance for all radionuclides present by using surrogate 29 measurements. If there is an established ratio among the concentrations of the radionuclides in 30 a survey unit, then the concentration of every radionuclide can be expressed in terms of any 31 one of them. The measured radionuclide is often called a surrogate radionuclide for the others.
32 In this case, the unity rule can be used to derive a new, modified DCGL for the surrogate 33 radionuclide, which accounts for the dose or risk contributions of the other radionuclides that are 34 not measured.
35 The fundamental aspect of the unity rule is that the sum of the ratios of the concentrations to the 36 DCGLs for each radionuclide should be less than or equal to one, as shown in Equation (4-7):
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Considerations for Planning Surveys                                                          MARSSIM C
1                                    (4-7)
DCGL
                                                =1 1 where 2
* C is the concentration of the th radionuclide.
3
* DCGL is the DCGL of the th radionuclide.
4 The terms in the denominator are the original, unmodified DCGLs for all the radionuclides in the 5 survey unit. However, when using a surrogate radionuclide, the design team needs to ensure 6 that the DCGL for the surrogate radionuclide is modified (DCGLS-mod) to account for the 7 presence of all the radionuclides. This is done by applying the unity rule as shown in 8 Equation (4-8:
Cs 1                                    (4-8)
DCGLS-mod 9 where 10
* Cs is the concentration of the surrogate radionuclide.
11
* DCGLS-mod is the modified DCGL for the surrogate radionuclide.
12 Here, DCGLS-mod is the DCGL for the surrogate radionuclide modified so that it represents all 13 radionuclides that are present in the survey unit. The DCGLS-mod is a variation of the unity rule 14 that uses established ratios as shown below in Equation (4-9):
1 DCGLS-mod =                                                                      (4-9) 1              2                     
                                                    +        +++            ++
DCGLS-unmod DCGL2                  DCGL        DCGL 15 where 16
* DCGLS-unmod is the DCGL of the surrogate radionuclide before modification.
17
* DCGL is the DCGL of the th radionuclide for  = 2,  .
18
* is the established ratio of the concentration of the th radionuclide to the concentration of 19    the surrogate radionuclide for  = 2,  .
20 DCGLS-mod is then used for survey design purposes described in Chapter 5. An example 21 calculation of a surrogate DCGL and additional discussion are shown in Section 4.12.2.1.
22 This scheme is applicable only when radionuclide-specific measurements of the surrogate 23 radionuclide are made. It is unlikely to apply in situations where the surrogate radionuclide NUREG-1575, Revision 2                              4-14                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                            Considerations for Planning Surveys 1 appears in background, as background variations would increase the uncertainty in the 2 calculation of the surrogate measurements to unacceptable levels.
3 When using surrogates, it is often difficult to establish a consistent ratio between two or more 4 radionuclides. Rather than follow prescriptive guidance on acceptable levels of variability for the 5 surrogate ratio, a more reasonable approach may be to review the data collected to establish 6 the ratio and to use the DQO process to select an appropriate ratio from that data. The DQO 7 process should be used to assess the feasibility of use of surrogates. The benefit of using the 8 surrogate approach is avoiding the need to perform costly wet chemistry analyses on each 9 sample. This benefit should be considered relative to the difficulty in establishing the surrogate 10 ratio, as well as the potential consequence of unnecessary investigations that result from 11 decision errors, which may arise from using a conservative surrogate ratio (i.e., determining 12 that the site is dirty when the site is clean). Selecting a conservative surrogate ratio ensures that 13 potential exposures from individual radionuclides are not underestimated. The surrogate method 14 can only be used with confidence when dealing with the same media in the same 15 surroundingsfor example, soil samples with similar physical and geological characteristics.
16 The planning team will need to consult with the regulatory agency for concurrence on the 17 approach used to determine the surrogate ratio.
18 The potential for shifts or variations in the radionuclide ratios means that the surrogate method 19 should be used with caution. Physical or chemical differences between the radionuclides may 20 produce different migration rates, causing the radionuclides to separate and changing the 21 radionuclide ratios. Remediation activities have a reasonable potential to alter the surrogate 22 ratio established prior to remediation. MARSSIM recommends that when the ratio is established 23 prior to remediation, additional post-remediation samples should be collected to ensure that the 24 data used to establish the ratio are still appropriate and representative of the existing site 25 condition. If these additional post-remediation samples are not consistent with the pre-26 remediation data, surrogate ratios should be re-established.
27 4.5.3.4 Gross Activity DCGLs for Multiple Radionuclides in Known Ratios 28 For situations where multiple radionuclides with their own DCGLs are present, a gross activity 29 DCGL can be developed. This approach enables field measurement of gross activity 30 (e.g., Bq/m2), rather than determination of individual radionuclide activity, for comparison to the 31 DCGL. The gross activity DCGL for surfaces with multiple radionuclides is calculated as follows:
32 1. Determine the relative fraction,  of the total activity contributed by each of the 33    radionuclides present for  = 1,  .
34 2. Obtain the DCGL for each th radionuclide present for  = 1,  .
35 3. Substitute the values  and DCGL in the following equation (Equation (4-10)) for  = 1,  .
1 DCGLgross =
1        2                                    (4-10)
                                              +          ++            ++
DCGL1 DCGL2              DCGL        DCGL 36 This process can be used to calculate a gross activity DCGL to be used as a DCGLW or a 37 DCGLEMC. See Appendix O.4 for the derivation. The example in Section 4.12.2.3 illustrates the 38 calculation of a gross activity DCGL.
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Considerations for Planning Surveys                                                        MARSSIM 1 Just as in the case of surrogate radionuclides, note that Equation (4-10) might not work for 2 sites having unknown or highly variable relative fractions of radionuclides throughout the site. In 3 these situations, the best approach may be to select the most conservative surface DCGL from 4 the mixture of radionuclides present (Section 4.5.3.2) or the unity rule (Section 4.5.3.5). If the 5 radionuclide with the most restrictive DCGL cannot be measured or is hard to detect with field 6 instruments, the DQOs must be revisited to determine the best approach. If the mixture contains 7 radionuclides that cannot be measured using field survey equipment, laboratory analyses of 8 surface materials may be necessary. Check with the regulator whether the use of a gross 9 activity DCGL is appropriate for the site.
10 4.5.3.5 DCGLs for Multiple Radionuclides with Unrelated Concentrations 11 If the concentrations of the different radionuclides appear to be unrelated in the survey unit, the 12 surrogate approach cannot be used. There is little choice but to measure the concentration of 13 each radionuclide and use the unity rule. The alternative would involve performing gross 14 measurements (e.g. alpha or beta) and applying the most restrictive DCGLW to all radionuclides.
15 Recall from Section 4.4 that the fundamental release criterion is that the sum of all the radiation 16 dose from all the residual radionuclides in a survey unit must be less than or equal to the dose 17 or risk criteria. In terms of DCGLs, the unity rule states that for a survey unit to meet the release 18 criteria, the sum of the ratios of the concentrations of each radionuclide to their respective 19 DCGLs must be less than or equal to one, as shown in Equation (4-11):
C1        C2              C                  C
                                  +          ++            +++                1          (4-11)
DCGL1 DCGL2              DCGL              DCGL 20 where 21
* C is the concentration of the th radionuclide for  = 1,  .
22
* DCGL is the DCGL of the th radionuclide for  = 1,  .
23 By using the unity rule in this manner, the design team creates an effective DCGL of 1. Note 24 that the DCGL is no longer expressed as a concentration; it is a unitless sum of fractions. To 25 apply the unity rule, the design team must calculate the sum of the ratios (SOR) or weighted 26 sum () of the ratios in the survey unit for each quantity measured at a given location, as 27 illustrated in Equation (4-12) and Example 4.12.4.
C1          C2              C              C
                            =          +        ++              ++                        (4-12)
DCGL1      DCGL2          DCGL              DCGL 28 where 29
* Ci is the concentration in the sample of the th radionuclide for  = 1,  .
30
* DCGL is the DCGL of the th radionuclide for  = 1,  .
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MARSSIM                                                            Considerations for Planning Surveys 1 In a given sample, the concentration of each radionuclide is divided by its DCGL 2 (normalization). This weighted sum, , and its standard deviation,    (), will be used in the 3 statistical tests to determine whether a survey unit can be released. The standard deviation in 4 the weighted sum is calculated as shown in Equation (4-13):
2          2              2                2 (C1 )      (C2 )        (C )        (C )
() =        +        ++          ++                      (4-13)
DCGL1      DCGL2          DCGL          DCGL 5 where 6 *    ( ) is the estimate of uncertainty in the concentration in the sample of the th radionuclide 7      for  = 1,  .
8
* DCGL is the DCGL of the th radionuclide for  = 1,  .
9 Note that if there is a fixed ratio between the concentrations of some radionuclides but not 10 others, a combination of the methods in Sections 4.5.3.4 and 4.5.3.5 may be used. The 11 appropriate value of the DCGL with the concentration of the measured surrogate radionuclide 12 should replace the corresponding terms in Equations (4-12) and (4-13). Example 4.12.4 13 illustrates the calculation of the weighted sum and its associated uncertainty for two 14 radionuclides.
15 During the planning stage, data from characterization, scoping, or other surveys can be used to 16 estimate the values of  and () in the survey unit to determine the number of samples 17 needed for the statistical tests.
18 Although this chapter does not discuss interpreting the data from an FSS (Chapter 8), a note on 19 how  is used can be helpful at this point. If the sum of the normalized concentrations is below 20 1.0 for every sample in a survey unit, compliance has been demonstrated. If a survey unit has 21 several individual locations where  exceeds 1, this does not mean that the survey unit fails to 22 meet the release criteria. If any individual  exceeds 1, then, as for the case for a single 23 radionuclide, an appropriate statistical test and the elevated measurement comparison test must 24 be performed.
25 4.5.3.6 The Use of External Radiation Measurements as a Surrogate 26 In lieu of using measurements of radionuclide concentrations to determine compliance with 27 release criteria, the DQO process can be used to determine if in situ measurements of external 28 radiation levels (e.g., exposure rates) can be used, particularly for radionuclides that deliver the 29 majority of their dose through the direct radiation pathway. This approach can be desirable 30 because external radiation measurements are generally easier to make and less expensive than 31 measuring radionuclide concentrations.
32 This method requires that a consistent ratio for the surrogate and unmeasured radionuclides be 33 established. The appropriate exposure rate DCGL could also account for radionuclides that do 34 not deliver the majority of their dose through the direct radiation pathway. This is accomplished 35 by determining the fraction of the total activity represented by radionuclides that do deliver the 36 majority of their dose through the direct radiation pathway and weighting the exposure rate limit May 2020                                            4-17                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Considerations for Planning Surveys                                                              MARSSIM 1 by this fraction (see surrogate discussion above). Note that the previously mentioned 2 considerations for establishing consistent ratios also apply to this surrogate approach. The 3 regulatory agency should be consulted before using this surrogate approach.
4 4.5.3.7 Small Areas of Elevated Activity 5 The concept of the elevated measurement comparison and DCGLEMC for small areas of elevated 6 activity was introduced in Section 4.5.2. The DCGLEMC accounts for the smaller area of 7 elevated residual radioactive material and is equal to or greater than the DCGLW. Recall that the 8 development of regulatory requirements leading to the establishment of a DCGLEMC is beyond 9 the scope of MARSSIM and is determined strictly through the requirements of regulatory 10 agencies. Therefore, it is important to work with the applicable regulatory agency to determine 11 whether requirements for establishing a DCGLEMC should be consistent with the approach 12 presented in MARSSIM or those in regulatory documents.
13 All the methods used to modify individual DCGLs to account for multiple radionuclides can be 14 used to modify the DCGLEMC. When the ratios between the radionuclides is unknown, the unity 15 rule inequality for the EMC is as shown below in Equation (4-14):
C1              C2                C              C
                                  +                ++              ++                1              (4-14)
DCGLEMC,1 DCGLEMC,2                DCGLEMC,        DCGLEMC, 16 In Equation (4-14), C is concentration of the th radionuclide for  = 1,  , and DCGLEMC, is 17 the DCGLEMC for th radionuclide for  = 1,  .
18 The use of Equation (4-14) may not be appropriate for scanning. For scanning, minimum 19 detectable concentration (MDC) considerations are a little more nuanced than for discrete 20 sampling. For example, when scanning for areas with potentially elevated concentrations of 21 residual radioactive material, the scan MDC should be below the DCGLpreferably at a fraction 22 (approximately 50 percent) of the DCGL. In a Class 1 survey unit, the scan MDC should be less 23 than the DCGLEMC. Additional information is provided in Sections 5.3.5.1 and 5.3.5.2. The 24 radionuclide yielding the lowest detector response may or may not have the most restrictive 25 DCGL.
26 As illustrated in Equation (4-15), to use the surrogate (known ratios) method for the elevated 27 measurement comparison, the DCGLEMC for the surrogate radionuclide is replaced by 1
DCGLEMC,S-mod =
1                  2                                      (4-15)
                                                +            ++                ++
DCGLEMC,S-unmod DCGLEMC,2                DCGLEMC,      DCGLEMC, 28 where 29
* DCGLEMC,S-unmod is the unmodified DCGLEMC for the first radionuclide.
30
* is the concentration ratio of the th radionuclide to the first radionuclide for  = 2,  .
31
* DCGLEMC, is the DCGLEMC for the th radionuclide for  = 2,  .
32 When dealing with discrete radioactive particles (hot particles), the MARSSIM EMC process is 33 not valid when the instrumentation dose-to-rate conversion factor modeling assumes a point NUREG-1575, Revision 2                                4-18                                        May 2020 DRAFT FOR PUBLIC COMMENT                                                      DO NOT CITE OR QUOTE
 
MARSSIM                                                          Considerations for Planning Surveys 1 source as opposed to an area source or plane source. This violates the assumption inherent 2 in the dose or risk model of an activity concentration averaged over some definable area. The 3 FSS planning team should use the DQO process to address discrete radioactive particles, if 4 there is a reasonable potential for them to be present. See Section 4.12.8 for more information 5 on release criteria for discrete radioactive particles.
6 4.5.3.8 A Note on Serial Radioactive Decay 7 For decay series (e.g., thorium and uranium) whose radionuclides emit alpha, beta, and gamma 8 radiation, compliance with building surface activity DCGLs may be demonstrated by assessing 9 alpha, beta, or gamma radiations. However, relying on the use of alpha surface measurements 10 often proves problematic because of the highly variable level of alpha attenuation by rough, 11 porous, and dusty surfaces. Beta measurements typically provide a more accurate assessment 12 of thorium and uranium on most building surfaces because surface conditions cause 13 significantly less attenuation of beta particles than alpha particles. Beta measurements, 14 therefore, may provide a more accurate determination of surface activity than alpha 15 measurements. The presence of gamma-emitting radionuclides can introduce uncertainty into 16 the beta measurements, and field measurement techniques need to be used to account for the 17 gamma interference at each beta measurement location.
18 The relationship of beta and alpha emissions from decay chains or various enrichments of 19 uranium should be considered when determining the surface activity for comparison with the 20 DCGL values. When the initial member of a decay chain has a long half-life, the concentration 21 of radioactive material associated with the subsequent members of the series will increase at a 22 rate determined by the individual half-lives until all members of the decay chain are present at 23 activity levels equal to the activity of the parent. This condition is known as secular equilibrium.
24 Section 4.12.2.1 provides an example of the calculation of beta activity DCGLW for thorium-232 25 in equilibrium with its decay products.
26 4.5.4    Investigation Levels 27 The survey design should include the development of investigation levels during the DQO 28 process for the FSS. A measurement result is compared to an investigation level to indicate 29 when additional action might be necessary (e.g., a measurement that exceeds the DCGLW in a 30 Class 2 area). Investigation levels can be radionuclide-specific levels of radioactive material or 31 an instrument response (e.g., counts per minute). Additional discussions of investigation levels 32 are in Section 5.3.8.
33 4.5.5    Conclusions 34 The foregoing discussion of DCGLs highlights the following:
35
* Measurements can be made for specific radionuclides, typically through gamma 36      spectrometry or radiochemical analyses.
37
* The FSS design team should be familiar with the operational DCGLs and their applications.
38
* Gross activity measurementstypically gross alpha or beta concentrationscan be made, 39      especially on surfaces.
40
* Measurement of surrogate quantities can be used based on known relationships among the 41      various radionuclides.
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Considerations for Planning Surveys                                                      MARSSIM 1
* The use of surrogates or ratios determined from data collected before the FSS must be 2    approved by the appropriate regulatory authorities, and if remediation or other activities 3    occur which could affect the ratios, additional support for the assumed ratios or revisions to 4    the ratios is needed.
5
* The unity rule can be used to determine the DCGLs for use in the design of the FSS when 6    multiple radionuclides/sources are present.
7
* If DCGLs are modified for use of surrogates, that modification will affect instrument 8    selection.
9 The choice of how the DCGLs are applied and measured affects the statistical methods, 10 background reference unit selection, and other design features of a survey. For example, 11 MARSSIM recommends using the Wilcoxon Rank Sum (WRS) test if the radionuclides are 12 present in the background or if gross activity measurements are made (see Section 8.2.3).
13 4.6    Area and Site Considerations 14 4.6.1  Area Classification 15 All areas of a site will not have the same potential for residual radioactive material and, 16 accordingly, will not need the same level of survey coverage to demonstrate compliance with 17 the established release criteria. The process will be more efficient if the survey is designed so 18 that areas with higher potential for residual radioactive material (based in part on results of the 19 HSA in Chapter 3) will receive a higher degree of survey effort. The following is a discussion of 20 site area classifications.
21 Non-impacted areas: Areas that have no reasonable potential for residual radioactive material 22 and do not need any level of survey coverage. Those areas have no radiological impact from 23 site operations and are typically identified during the HSA (Chapter 3). Background reference 24 areas are normally selected from non-impacted areas (Section 4.6.3).
25 Impacted areas: Areas that have some potential for containing residual radioactive material.
26 They can be classified into three classes:
27
* Class 1 areas: Areas that have, or had prior to remediation, a potential for residual 28    radioactive material above the DCGLW (based on site operating history) or known residual 29    radioactive material (based on previous radiological surveys). Examples of Class 1 areas 30    include 31    o  site areas previously subjected to remedial actions 32    o  locations where leaks or spills are known to have occurred 33    o  former burial or disposal sites 34    o  waste storage sites 35    o  areas with residual radioactive material in discrete solid pieces of material having high 36        specific activity 37    Note that areas containing residual radioactive material in excess of the DCGLW prior to 38    remediation should be classified as Class 1 areas. Justification is not required for a Class 1 NUREG-1575, Revision 2                          4-20                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                        Considerations for Planning Surveys 1      designation, unlike a Class 2 or Class 3 designation. The less restrictive the classification, 2      the greater the justification required.
3
* Class 2 areas: Areas that have, or had prior to remediation, a potential for residual 4      radioactive material or known residual radioactive material but are not expected to exceed 5      the DCGLW. To justify a Class 2 designation, the existing data (from the HSA, scoping 6      surveys, or characterization surveys) should provide a high degree of confidence that no 7      individual measurement would exceed the DCGLW. Other justifications may be appropriate 8      based on the outcome of the DQO process. Examples of areas that might be classified as 9      Class 2 for the FSS include 10      o  locations where radioactive materials were present in an unsealed form 11      o  residual radioactive material potentially along transport routes 12      o  areas downwind from stack release points 13      o  upper walls, roof support frameworks, and ceilings of some buildings or rooms subjected 14          to airborne radioactive material 15      o  areas where low concentrations of radioactive materials were handled 16      o  areas on the perimeter of former buffer or radiological control areas 17
* Class 3 areas: Any impacted areas that are not expected to contain any residual radioactive 18      material or are expected to contain levels of residual radioactive material at a small fraction 19      of the DCGLW, based on site operating history and previous radiological surveys. To justify a 20      Class 3 designation, the existing data (from the HSA, scoping surveys, or characterization 21      surveys) should provide a high degree of confidence either that there is no residual 22      radioactive material or that any levels of residual radioactive material are a small fraction of 23      the DCGLW. Other justifications for an areas classification may be appropriate based on the 24      outcome of the DQO process. Examples of areas that might be classified as Class 3 25      include 26      o  buffer zones around Class 1 or Class 2 areas 27      o  areas with very low potential for residual radioactive material but insufficient information 28          to justify a non-impacted classification 29 Classification is a critical step in the survey design process, as well as for the FSS (see 30 Table 2.2). Class 1 areas have the greatest potential for residual radioactive material and, 31 therefore, receive the highest degree of survey effort, followed by Class 2 and then Class 3 32 areas. All areas should be considered Class 1 areas unless some basis for classification as 33 Class 2 or Class 3 is provided.
34 The criteria used for designating areas as Class 1, 2, or 3 should be described in the FSS plan.
35 Compliance with the classification criteria should be demonstrated in the FSS report. A thorough 36 analysis of HSA findings (Chapter 3) and the results of scoping and characterization surveys 37 provide the basis for an areas classification. As a survey progresses, reevaluation of this 38 classification may be necessary based on newly acquired survey data. For example, if residual 39 radioactive material at concentrations that are a substantial fraction of the DCGLW is identified in 40 a Class 3 area, an investigation and reevaluation of that area should be performed to determine 41 if the Class 3 area classification is appropriate. Typically, the investigation will result in part or all May 2020                                          4-21                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Considerations for Planning Surveys                                                          MARSSIM 1 of the area being reclassified as Class 1 or Class 2. If survey results identify residual radioactive 2 material in a Class 2 area exceeding the DCGL or suggest that there may be a reasonable 3 potential that residual radioactive material is present in excess of the DCGL, an investigation 4 should be initiated to determine whether all or part of the area should be reclassified as Class 1.
5 More information on investigations and reclassifications is provided in Section 5.3.8.
6 4.6.2    Identification of Survey Units 7 A survey unit is a physical area consisting of structures or land areas of specified size and 8 shape for which a separate decision will be made whether that survey unit exceeds the release 9 criteria. This decision is made as a result of the FSS. Therefore, the survey unit is the primary 10 entity for demonstrating compliance with the release criteria.
11 To facilitate survey design and ensure that the number of survey data points for a specific site 12 are relatively uniformly distributed among areas of similar potential for residual radioactive 13 material, the site is divided into survey units that share a common history or other 14 characteristics or are naturally distinguishable from other portions of the site. A site may be 15 divided into survey units at any time before the FSS. Areas that have been classified can be one 16 survey unit or multiple survey units. For example, HSA or scoping survey results may provide 17 sufficient justification for partitioning the site into Class 1, 2, or 3 areas. Note, however, that 18 dividing the site into survey units is critical only for the FSS; scoping, characterization, and RAS 19 surveys may be performed without dividing the site into survey units.
20 A survey unit cannot include areas that have different classifications. A survey units 21 characteristics should be consistent with exposure pathway modeling that is used to convert 22 dose or risk into radionuclide concentrations. For indoor areas classified as Class 1, each room 23 may be designated as a survey unit. Indoor areas may also be subdivided into several survey 24 units of different classification, such as separating floors and lower walls from upper walls and 25 ceilings (and other upper horizontal surfaces) or subdividing a large warehouse based on floor 26 area.
27 Survey units should be limited in size based on classification, exposure pathway modeling 28 assumptions, and site-specific conditions. The suggested areas for survey units are provided in 29 Table 4.1.
30 Table 4.1: Suggested Area for Survey Units Suggested Area for Survey Units Structures (Floors, Walls, Classification              and Ceilings)                      Land Areas Class 1                          Up to 100 m2                    Up to 2,000 m2 Class 2                        Up to 1,000 m2                  Up to 10,000 m2 Class 3                            No Limit                          No Limit 31 Abbreviation: m2 = square meters 32 The limitation on survey unit size ensures that the density of the measurements/samples is 33 commensurate with the potential of residual radioactive materials in excess of the DCGLW. The NUREG-1575, Revision 2                              4-22                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                        Considerations for Planning Surveys 1 rationale for selecting a larger survey unit area should be developed using the DQO process 2 (Section 2.3) and fully documented.
3 Special considerations may be necessary for survey units with structure surface areas up to 4 10 m2 or land areas up to 100 m2. In this case, the number of data points obtained from the 5 statistical tests is unnecessarily large and not appropriate for smaller survey unit areas. Instead, 6 some specified level of survey effort should be determined based on the DQO process and with 7 the concurrence of the regulatory agency. For such small survey units, scan-only surveys or in 8 situ measurement may be more appropriate. The data generated from these smaller survey 9 units should be obtained based on judgment, rather than on systematic or random design, and 10 compared individually to the DCGLs.
11 One example special case for FSSs occurs at UMTRCA sites at which the radioactive materials 12 are from the processing of uranium or thorium ores for their source material content. See 13 Section 4.12.9 and Appendix O.6 for more details for UMTRCA sites.
14 4.6.3    Selection of Background Reference Areas 15 Certain radionuclides may also occur at significant levels as part of background in the media of 16 interest (e.g., soil, building material). Examples include members of the naturally occurring 17 uranium, thorium, and actinium series; potassium-40 (40K); carbon-14 (14C); and tritium (3H).
18 137 Cs and other radionuclides are also present in background as a result of fallout (Wallo et al.,
19 1994). Establishing a distribution of background concentrations is necessary to identify and 20 evaluate contributions attributable to site operations. Determining background levels for 21 comparison with the conditions determined in specific survey units entails conducting surveys in 22 one or more reference areas to define the background radiological conditions of the site.
23 NUREG-1505 (NRC 1998a) provides additional information on background reference areas.
24 The recommended site background reference area should have similar physical, chemical, 25 geological, radiological, and biological characteristics as the survey unit being evaluated.
26 Background reference areas should be selected from non-impacted areas, but they are not 27 limited to natural areas undisturbed by human activities. In some situations, a reference area 28 may be contiguous to the survey unit being evaluated, as long as the reference area does not 29 have any residual radioactive material resulting from site activities. For example, background 30 measurements may be taken from core samples of a building or structure surface or pavement.
31 This option should be discussed with the regulatory agency during survey planning. Reference 32 areas should not be part of the survey unit being evaluated.
33 Reference areas provide a location for background measurements that are used for 34 comparisons with survey unit data. The radioactive material present in a reference area would 35 ideally be the same as in the survey unit, had the survey unit never been affected by site 36 operations. If a site includes physical, chemical, geological, radiological, or biological variability 37 that is not represented by a single reference background area, selecting more than one 38 reference area may be necessary. Additionally, the concentration of some radionuclides may 39 vary over short (hours to days), medium (months or years), or long (centuries) time frames.
40 NUREG-1501 (NRC 1994a) provides more detailed information about sources of temporal 41 variability and methods to account for this variability.
42 It may be difficult to find a reference area within a residential or industrial complex for 43 comparison to a survey unit if the radionuclides of potential concern are naturally occurring.
44 Background may vary greatly due to different construction activities that have occurred at the 45 site. Examples of construction activities that change background include May 2020                                        4-23                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Considerations for Planning Surveys                                                        MARSSIM 1
* leveling 2
* excavating 3
* adding fill dirt 4
* importing rocks or gravel to stabilize soil or underlay asphalt 5
* manufacturing asphalt with different matrix rock 6
* using different pours of asphalt or concrete in a single survey unit; layering asphalt over 7    concrete 8
* layering different thicknesses of asphalt, concrete, rock, or gravel 9
* covering or burying old features, such as railroad beds or building footings 10 Background variability may also increase due to the concentration of fallout in low areas of 11 parking lots or under downspouts, where runoff water collects and evaporates. Variations in 12 background of a factor of five or more can occur in the space of a few meters.
13 There are a number of possible actions to address these concerns. NUREG-1505 (NRC 1998a) 14 provides a methodology for considering variability in reference area concentrations. Reviewing 15 and reassessing the selection of reference areas may also be necessary. Selecting different 16 reference areas to represent individual survey units is another possibility. More attention may 17 also be needed in selecting survey units and their boundaries with respect to different areas of 18 potential or actual background variability. More detailed scoping or characterization surveys 19 may be needed to better understand background variability. Using radionuclide-specific 20 measurement techniques instead of gross radioactive material measurement techniques may 21 also be necessary. If a background reference area that satisfies the above recommendations is 22 not available, consultation with the regulatory agency is recommended. Alternate approaches 23 may include using published studies of radionuclide distributions. However, published reports 24 may not truly reflect the conditions at the site.
25 Verifying that a background reference area is appropriate for a survey can be accomplished 26 using the techniques described or referenced in Chapter 8. Verification provides assurance that 27 assumptions used to design the survey are appropriate and defensible. This approach can also 28 prevent decision errors that may result from selecting an inappropriate background reference 29 area.
30 If the radionuclides of interest do not occur in background, or the background levels are known 31 to be a small fraction of the DCGLW (e.g., < 10 percent), the survey unit radiological conditions 32 may be compared directly to the specified DCGLW, and reference area background surveys are 33 not necessary. If the background is not well defined at a site and the decision maker is willing to 34 accept the increased probability of incorrectly failing to release a survey unit (Type II error), the 35 reference area measurements can be eliminated and the Sign test performed as described in 36 Section 8.3.
37 4.7    Statistical Considerations 38 The primary practical objective of an FSS survey is to answer the question, Can this survey unit 39 be released to the satisfaction of the regulator? In other words, the design team needs to be 40 able to confidently demonstrate compliance (or non-compliance) with the dose- or risk-based 41 release criteria expressed as a measurable quantity (DCGL). This need for a demonstrable, 42 quantitative confidence necessitates planning for statistical hypothesis testing.
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MARSSIM                                                                    Considerations for Planning Surveys 1 The statistical concepts used in MARSSIM were introduced in Section 2.5. This chapter 2 reinforces and builds on those concepts with respect to the design of an FSS. The MARSSIM 3 user should be familiar with the statistical discussions throughout Chapters 2, 5, and 8 and 4 Appendices D and I. Consultations with statisticians can be very valuable for surveys that rely 5 on statistical methods for their design and assessment of the collected data.
6 4.7.1    Basic Terms 7 Before designing an FSS, the planning team should be familiar with the following statistical 8 terms:
9
* sample 4 mean 10
* sample standard deviation 11
* sample median 12
* parametric and nonparametric tests 13      o    Sign test 14      o    Wilcoxon Rank Sum 5 (WRS) test 15      o    Students t test 16
* Type I and Type II errors 17
* statistical power 18
* lower boundary of the gray region (LBGR) 19
* upper boundary of the gray region (UBGR) 20
* relative shift ()
21
* null and alternative hypotheses 22 The MARSSIM user will encounter these and other statistical terms many times in this 23 document and while designing, performing, and assessing the results of an FSS. The use of 24 these terms will be kept to a minimum in this chapter, but this in no way diminishes their 25 importance. For this chapter, statistical terms will be defined when they are introduced.
26 4.7.2    Recommended Statistical Tests 27 How well a statistical test meets its objective depends on the difference between the 28 assumptions used to develop the test and the actual conditions being measured. Parametric 29 tests, such as the Students t test, rely upon the results fitting some known distribution, like a 4 The term sample here is a statistical term and should not be confused with laboratory samples. For the calculation of basic statistical quantities above, data may consist of scan data, direct measurement data, or laboratory sample data. See also the glossary definition of sample.
5 This test is also called the Mann-Whitney U test, Mann-Whitney-Wilcoxon test, or Wilcoxon-Mann-Whitney test.
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Considerations for Planning Surveys                                                          MARSSIM 1 normal distribution. Nonparametric statistics are recommended in MARSSIM because they are 2 based on less restrictive assumptions than parametric tests. MARSSIM recommends the use of 3 the WRS test if the radionuclides of concern are present in the background or if gross activity 4 measurements are made. If the radionuclides of concern are not present in the background or 5 present only to a slight degree, then the Sign test is recommended.
6 4.7.3    Considerations on the Choice of a Statistical Test 7 The choice of a statistical test should be part of the DQO process during the design phase of 8 the FSS. The choice of the statistical test is influenced by how the DCGLs are expressed (gross 9 activity, radionuclide-specific, sum or ratios [unity rule]), the distribution of residual radioactive 10 material in the survey unit (relatively uniform vs. small areas of elevated activity), number of 11 reference units needed, etc. Concurrently, the number of samples needed depends on the 12 DCGL, the standard deviation of the residual radioactive material in both the survey and 13 reference units, the desired confidence in the conclusions (Type I and Type II errors), and the 14 statistical test under consideration (see Sections 5.3.3 and 5.3.4 for details, and see example 15 calculations in Sections 4.12.3 and 4.12.4). Ensuring a reasonable level of confidence that any 16 areas of elevated activity are detected might require additional samples.
17 Once the FSS is completed, the assumptions used to select the statistical test are examined to 18 determine whether the conditions are met for the test. As part of the DQO process, the design 19 team should plan for the possibility that the initial assumptions were not correct.
20 4.7.4    Deviations from MARSSIM Statistical Test Recommendations 21 The guidance and recommendations in MARSSIM are meant to be a set of practices generally 22 acceptable for use in designing an FSS. However, the flexibility of the DQO process allows for 23 the use of more cost-effective methods, if they are acceptable to the regulator. An example is 24 presented in Section 4.12.7.
25 4.7.5    An Important Statistical Note 26 For FSSs, the parameter of interest is the mean concentration of residual radioactive material in 27 a survey unit. The nonparametric statistical tests recommended in MARSSIM are tests of the 28 median value. For data that are from a skewed right distribution, the mean could significantly 29 exceed the median. Therefore, the team planning the FSS should include a comparison step in 30 the survey to ensure that mean is less than the DCGLW. See Section 8.2.2.
31 4.8    Measurements 32 Based on the potential radionuclides of interest, their associated radiations, how the DCGLs are 33 expressed, the types of media (e.g., soil, structure surfaces), and number of measurements to 34 be evaluated, the detection capabilities of various measurement methods (which consist of a 35 combination of a measurement technique and instrument) must be determined and 36 documented. Note that measurements includes both direct (field) measurements and 37 laboratory analyses.
38 4.8.1    Quality Control and Quality Assurance 39 For both field measurements (Chapter 6) and laboratory analyses (Chapter 7), the FSS design 40 team must plan to collect data to evaluate the performance of measurement and analytical 41 methods (including data collection). These data are called measurement and instrument 42 performance indicators. The DQO and MQO processes are used to determine which indicators NUREG-1575, Revision 2                          4-26                                          May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                        Considerations for Planning Surveys 1 are important and included in the QAPP. Examples of measurement and instrument 2 performance indicators are shown below:
3
* Instrument background readings: Background readings before and after a series of 4    measurements are used as part of the process to ensure that an instrument was functioning 5    properly.
6
* Instrument response checks: Checking the instrument response with the same source in the 7    same geometry over the course of surveying can help ensure that the instrument was 8    working properly during the survey.
9
* Field blanks: These are samples prepared in the field using certified clean sand, soil, or 10    other media and sent to the laboratory for analysis. Field blanks are used to assess 11    contamination associated with sampling and laboratory procedures.
12
* Performance evaluation samples: These are used to assess the overall bias and errors in 13    the laboratorys analytical processes.
14 4.8.2  Measurement Quality Objectives 15 Although specifically for laboratory analyses, the performance characteristics discussed in the 16 Multi-Agency Radiological Laboratory Analytical Protocols Manual (MARLAP) (NRC 2004) 17 should be considered when establishing Measurement Quality Objectives (MQOs). This list is 18 not intended to be exhaustive:
19
* the methods uncertainty at a specified concentration, usually at the UBGR (expressed as a 20    standard deviation) 21
* the methods detection capability (expressed as the minimum detectable concentration, or 22    MDC) 23
* the methods quantification capability (expressed as the minimum quantifiable concentration, 24    or MQC) 25
* the methods range, which defines the methods ability to measure the radionuclide of 26    concern over some specified range of concentration 27
* the methods specificity, which refers to the ability of the method to measure the 28    radionuclide of concern in the presence of interferences 29
* the methods ruggedness, which refers to the relative stability of method performance for 30    small variations in method parameter values 31 Project-specific method performance characteristics should be developed as necessary and 32 may or may not include the characteristics listed here. When lists of performance characteristics 33 that affect measurability have been identified, the planning team should develop MQOs 34 describing the project-specific objectives for potential measurement techniques. Potential 35 measurement techniques should then be evaluated against the MQOs to determine whether 36 they are capable of meeting the objectives for measurability.
37 The International Organization for Standardization Guide to the Expression of Uncertainty in 38 Measurement (ISO 1993), National Institute of Standards and Technology Technical Note 1297 39 (NIST 1994), MARLAP (NRC 2004), Multi-Agency Radiation Survey and Assessment of May 2020                                        4-27                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Considerations for Planning Surveys                                                      MARSSIM 1 Materials and Equipment Manual (MARSAME) (NRC 2009), and Chapter 6 of this manual 2 provide information on determining measurement uncertainty. Chapter 6 of this manual and 3 NRC report NUREG-1507 (NRC 1997a) discuss the concept of detection capabilities and 4 provide guidance on determining detection capabilities and selecting appropriate measurement 5 methods. Although MARSAME and MARLAP include the concept of quantification capability, 6 MARSSIM takes a different approach by incorporating requirements for quantification capability 7 into detection capability with the requirement that the MDC be less than the UBGR and by 8 recommending that the MDC be less than 50 percent of the UBGR (See Chapter 6). Chapter 6 9 also discusses instruments and survey techniques for scans and direct measurements, and 10 Chapter 7 provides information on sampling and laboratory analysis. Appendix H describes 11 typical field and laboratory equipment, plus associated cost and instrument capabilities.
12 4.8.3    Selecting a Measurement Technique 13 Instruments should be identified for each of the three types of measurement techniques planned 14 for the FSS: (1) scanning, (2) direct, and (3) laboratory measurements. Scanning and direct 15 measurements are referred to as field measurements. In some cases, the same instrument or 16 type of instrument may be used for performing several measurement techniques. For example, 17 a gas proportional counter can be used for surface scanning measurements and laboratory 18 measurements of smear samples. Once the instruments are selected, appropriate 19 measurement techniques and standard operating procedures (SOPs) should be developed and 20 documented. The measurement techniques describe how the instrument will be used to perform 21 the required measurements.
22 4.8.3.1 Scanning Measurements 23 Scanning is an in situ measurement technique performed by moving a portable radiation 24 detector at a specified speed and distance next to a surface to detect radiation. Scanning 25 measurements are generally used to locate areas that exceed investigation levels and areas of 26 elevated activity that might be missed (e.g., measurements made with a systematic grid). In 27 general, MARSSIM does not recommend scan-only FSSs. However, through the DQO 28 process and consultation with the regulator, an FSS based on scanning measurements alone 29 might be allowed. Items that should be kept in mind while investigating a scan-only survey are 30
* data and location logging 31
* reproducibility of the measurements (e.g., fixing a detector at a constant distance from a 32      surface) 33
* MDCs 34
* scanning speed and operator training 35
* data integrity and security 36
* selecting an appropriately sized area for elevated measurement comparison calculations 37 Additional information can be found in Chapter 6.
38 4.8.3.2 Direct Measurements 39 A direct measurement is an in situ measurement of radioactive material obtained by placing the 40 detector near the surface or media being surveyed for a prescribed amount of time. An NUREG-1575, Revision 2                          4-28                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                      Considerations for Planning Surveys 1 indication of the resulting concentration of radioactive material is read out directly. Making direct 2 measurements is analogous to collecting samples, and the results are often treated in a similar 3 manner. Direct measurement of alpha, beta, and gamma radiation for an FSS requires that 4 instruments and techniques be used that meet the DQOs and MQOs (e.g., MDC). When 5 selecting instruments and techniques, the design team needs to consider 6
* type and amounts of radionuclides potentially present 7
* required detection limits 8
* distance from the surface being monitored and field of view 9
* type of measurementrate or scaler (integrated) (e.g., counts in 5 minutes) 10
* duration of integrated counts 11
* radiation background (including interferences from nearby radiation sources) 12 All direct measurements and their locations should be recorded. Additional information can be 13 found in Chapter 6.
14 4.8.3.3 Laboratory Measurements 15 When planning for collecting samples as part of an FSS, the design team should use the DQO 16 process to determine the need for sample collection and laboratory analyses. All laboratories 17 under consideration to analyze samples should have written procedures that document their 18 analytical capabilities for the radionuclides of concern and a QA/QC program that documents 19 adherence to established criteria. The survey design team should also consider any appropriate 20 laboratory accreditation. Accreditation, QA/QC, and other appropriate documentation should be 21 available for review by the survey design team (with appropriate restrictions for proprietary or 22 other controlled information). Once a qualified laboratory has been chosen, the design team 23 should involve the laboratory early in the design process and maintain communication 24 throughout execution and data evaluation and interpretation. Chapter 7 contains more 25 information on the sampling and preparation for laboratory measurements.
26 Additionally, MARLAP (NRC 2004) contains extensive information for the planning, 27 implementation, and assessment of projects that require laboratory analysis of radionuclides.
28 Like MARSSIM, MARLAP aims to provide a flexible approach to ensure that the radioanalytical 29 data are of the right quality and appropriate for the needs of the user.
30 Some items that should be considered when planning for laboratory analyses include the 31 following:
32
* sample media 33
* number of samples 34
* type and number of QC samples 35
* amount of material needed by the laboratory 36
* analytical bias and precision 37
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Considerations for Planning Surveys                                                      MARSSIM 1
* costs 2
* required turnaround time 3
* sample preservation and shipping requirements 4
* measurement documentation requirements 5
* sample tracking needs (e.g., chain of custody requirements) 6 4.8.3.4 Selecting a Radioanalytical Laboratory 7 It is advisable to select a radiochemical laboratory as early as possible in the survey planning 8 process so that it may be consulted on the analytical methodology and the sampling activities.
9 Federal procurement procedures may require additional considerations beyond the method 10 described here. The procurement of laboratory services usually starts with the development of a 11 request for proposal that includes a statement of work describing the analytical services to be 12 procured. The careful preparation of the statement of work is essential to the selection of a 13 laboratory capable of performing the required services in a technically competent and timely 14 manner.
15 Six criteria that should be considered are:
16
* well-documented procedures, instrumentation, and trained personnel to perform the 17      necessary analyses 18
* surveyors who are experienced in performing the same or similar analyses 19
* satisfactory performance evaluation results from formal monitoring or accreditation programs 20
* adequate capacity to perform all analyses within the desired timeframe 21
* internal QC program 22
* protocols for method performance documentation, sample tracking and security, and 23      documentation of results 24 The design team should review that laboratorys documentation concerning MDC calculations, 25 reporting procedures, calibrations, QA/QC, and accreditation to ensure that the FSS DQOs will 26 be met. More details can be found in Section 7.4.
27 When samples are collected for laboratory analyses, communications between the project 28 manager, field personnel, and laboratory personnel are vital to a successfully executed FSS.
29 The survey design team should strive to establish communications with the laboratory early in 30 the design process; when this is not possible, a radiochemist or health physicist with 31 radiochemical training should be consulted. Additional information on laboratory 32 communications is in Section 7.3.
33 4.8.4    Selection of Instruments for Field Measurements 34 4.8.4.1 Reliability and Robustness 35 Choose reliable instruments that are suited to the physical and environmental conditions at the 36 site and capable of meeting the MQOs. The MQOs should include the measurement method NUREG-1575, Revision 2                          4-30                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                          Considerations for Planning Surveys 1 uncertainty, which is typically established at the UBGR (usually the DCGLW). The required 2 measurement method uncertainty is perhaps the most important MQO to be established during 3 the planning process. Determining a realistic value for the measurement method uncertainty for 4 field measurements is a challenging calculation, typically requiring the use of specialized 5 software. However, ensuring that the measurement method uncertainty meets the requirement 6 set for it at the UBGR will ensure that the measurement method can reliably perform 7 measurements at the most critical concentration level for the survey.
8 4.8.4.2 Detection Capability 9 The detection capability (sensitivity) or the ability to detect radiation or radioactive material with 10 some quantifiable level of confidence is a critical factor in the design of an FSS. This capability 11 is most often referred to as the MDC for direct measurements, or the scan MDC for scanning 12 measurements. The formal MARSSIM definition of the MDC is the a priori activity concentration 13 that a specific instrument and technique that has a specified probability (typically 95 percent) of 14 producing a net count (or count rate) above the critical level. Informally, the MDC is the 15 concentration of radioactive material that can be reliably detected; if radioactive material is 16 present at the MDC with a specified probability of 95 percent, then the measurement process 17 will determine its presence 95 percent of the time. The MDC is a factor of both the 18 instrumentation and the technique or procedure being used. For scanning, human factors also 19 need to be taken into account. Details on how to calculate MDCs are given in Section 6.3. The 20 design team should be aware that there are other methods to calculate MDCs (especially for 21 direct and laboratory measurements) discussed in the scientific literature. The DQO process 22 should be used to determine which method best suits the needs of the FSS. This method and 23 results should be approved by the appropriate regulatory agency.
24 Having low MDCs is valuable when designing the FSS. If measured values are less than the 25 MDC, then the values can be quite variable and lead to high values for the standard deviation 26 () of the measured values in the survey unit or reference area. High values for  can be 27 accommodated in the statistical tests described in Chapter 8 for the FSS, but a large number of 28 measurements are needed to account for the variability.
29 Early in the project, low MDCs help in the identification of areas that can be classified as non-30 impacted or Class 3 areas. These decisions are usually based on fewer numbers of samples, 31 and each measurement is evaluated individually. Using an optimistically low estimation of the 32 MDC (see Section 2.3.5) for these surveys may result in the misclassification of a survey unit 33 and cleaning up an area with no residual radioactive material or, alternatively, performing an 34 FSS in an area with residual radioactive material. Selecting a measurement technique with a 35 well-defined MDC or a conservative estimate of the MDC ensures the usefulness of the data for 36 making decisions for planning the FSS. For these reasons, MARSSIM recommends that a 37 realistic or conservative estimate of the MDC be used instead of an optimistic estimate.
38 4.8.4.3 Dynamic Range 39 The expected concentration range for a radionuclide of concern can be an important factor in 40 the overall measurement method performance. Most radiation measurement techniques are 41 capable of measuring over a wide range of radionuclide concentrations. However, if the 42 expected concentration range is large, the range should be identified as an important 43 measurement method performance characteristic, and an MQO should be developed. The MQO 44 for the acceptable range should be a conservative estimate. This will help prevent the selection 45 of measurement techniques that cannot accommodate the actual concentration range.
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Considerations for Planning Surveys                                                                  MARSSIM 1 4.8.4.4 Calibration 2 Calibration refers to the determination and adjustment of the instrument response in a particular 3 radiation field of known intensity. Proper calibration procedures are essential to providing 4 confidence in measurements made to demonstrate compliance with release criteria. The FSS 5 design team should review and understand Section 6.6.4.
6 The instrument should be calibrated for the radiations and energies of interest at the site 7 (Section 6.6.4). Instrument calibrations should be traceable to an accepted standards 8 organization, such as the National Institute of Standards and Technology (NIST). 6 Operational 9 checks of instrument performance should be conducted routinely and frequently to ensure that 10 the instrument response is maintained within acceptable ranges and that any changes in 11 instrument background are not attributable to radioactive contamination of the detector.
12 Considerations for the use and calibration of instruments include 13
* the radiation type for which the instrument is designed 14
* the radiation energies within the range of energies for which the instrument is designed 15
* the environmental conditions for which the instrument is designed 16
* the influencing factors, such as magnetic and electrostatic fields, for which the instrument is 17    designed 18
* the orientation of the instrument, such that geotropic (gravity) effects are not a concern 19
* the manner the instrument is used, such that it will not be subject to mechanical or thermal 20    stress beyond that for which it is designed 21 As a minimum, each measurement system (detector/readout combination) should be calibrated 22 annually, and the response of the detector to a check source should be established following 23 calibration (ANSI 2013). Instruments may require more frequent calibration if recommended by 24 the manufacturer. Recalibration of field instruments is also required if an instrument fails a 25 performance check or if it has undergone repair or any modification that could affect its 26 response. The system should be calibrated to minimize potential errors during data transmission 27 and retransmission. The user may decide to perform calibrations following industry-recognized 28 procedures (ANSI 1997, NCRP 1978, NCRP 1985, NCRP 1991, ISO 1988, HPS 1994a, HPS 29 1994b), or the user can choose to obtain calibration by an outside service, such as a major 30 instrument manufacturer or a health physics services organization. Calibrations should include 31 devices used to determine the position or location of samples or measurements, as 32 recommended by the manufacturer.
33 Additional technical details about instrument efficiencies and example calculations are 34 contained in Section 4.12.5.
35 4.8.4.5 Specificity 36 Specificity is the ability of the measurement method to measure the radionuclide of concern in 37 the presence of interferences. To determine whether specificity is an important measurement 6 The NIST policy on traceability can be found here: https://www.nist.gov/calibrations/traceability.
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MARSSIM                                                        Considerations for Planning Surveys 1 method performance characteristic, the planning team will need information about expected 2 concentration ranges for the radionuclides of concern and other chemical and radionuclide 3 constituents, along with chemical and physical attributes of the soil or surface being measured.
4 The importance of specificity depends on 5
* the chemical and physical characteristics of the soil or surface 6
* the chemical and physical characteristics of the residual radioactive material 7
* the expected concentration range for the radionuclides of concern 8 If potential interferences are identified (e.g., inherent radioactive material, similar radiations), an 9 MQO should be established for specificity.
10 4.8.4.6 Instrumentation Examples 11 Table 4.2 presents a list of common radionuclides along with recommended instruments for 12 field measurement methods that have proven effective based on past survey experience in the 13 decommissioning industry. This table provides a general indication of the detection capability of 14 commercially available instruments for field measurements. As such, Table 4.2 may be used to 15 provide an initial evaluation of instrument capabilities for some common radionuclides at the 16 example DCGLs listed in the table. For example, consider a surface with 241Am. Table 4.2 17 indicates that 241Am is detectable at the example DCGLs and that viable direct measurement 18 instruments include gas-flow proportional (alpha mode) and alpha scintillation detectors.
19 Many radiation detection instruments can be used for both direct and scanning measurements.
20 The example DCGLs in Table 4.2 are given for direct measurements only. Issues of 21 detectability (MDC) for scanning are more complicated than for direct measurements and 22 depend on things such as human response, height above the surface, and scanning speed.
23 Table 4.2 should not be interpreted as providing specific values for an instruments detection 24 capability, which is discussed in Section 6.7. In addition, NRC draft report NUREG-1506 (NRC 25 1995) and NUREG-1507 (NRC 1997a) provide further information on factors that may affect 26 survey instrumentation selection.
27 4.8.5    Selection of Sample Collection Methods 28 Sample characteristicssuch as sample depth, volume, area, moisture level, and composition, 29 as well as sample preparation techniques that may alter the sampleare important planning 30 considerations for DQOs. Sample preparation may include, but is not limited to, removing 31 extraneous material, homogenizing, splitting, drying, compositing, and doing final preparations 32 of samples. Dose or risk pathway modeling should be representative of actual survey 33 conditions, to the extent practical, and modeling limitations should be well documented and 34 assessed. The sampling method should then consider assumptions made in the dose or risk 35 pathway modeling used to determine radionuclide DCGLs. For example, the actual depth and 36 area of residual radioactivity in the survey unit should be reflected in the modeling, and 37 sampling should be compatible with how the source was represented in the modeling. If a direct 38 measurement or scanning technique is used, it should also consider the compatibility of the 39 technique with the assumptions made in the dose or risk pathway modeling.
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1    Table 4.2: Examples of Field Measurement Instruments Considerations for Planning Surveys Structure Surfaces                      Land Areas                                        Example Instruments Example                            Example NUREG-1575, Revision 2 Nuclide        DCGLa (Bq/m2) Detectable            DCGLa (Bq/kg) Detectable              Surface Activity  Soil Activity              Exposure Rate 3H                                        No                                  No                      NDb              ND                        ND 2.0x108                            4.1x103 14C                                      Yes                                No                                        ND                        ND 6.2x106                            4.4x102                                GP 54Mn                                      Yes                                Yes 5.4x104                            5.6x102                              GP, GM          S, IS                  PIC, S, IS 55Fe                                      No                                  Noc                      ND 7.5x106                            3.7x105                                                ND (IS)                    ND(IS) 60Co                                      Yes                1.4x102        Yes 1.2x104                                                                  GP, GM          S, IS                  PIC, S, IS DRAFT FOR PUBLIC COMMENT 63Ni                                      Yes                                No                                        ND                        ND 3.0x106                            7.8x104                                GP 90Sr                                      Yes                                Noc                                                                  ND 1.5x104                            6.3x101                              GP, GM      ND (GM, GP) 99Tc                                      Yes                                No                                        ND                        ND 2.2x106                            7.0x102                              GP, GM 137Cs                                    Yes                                Yes 4.7x104                            4.1x102                              GP, GM          S, IS                  PIC, S, IS 152Eu                                    Yes                                Yes 3.2x102                              GP, GM          S, IS                  PIC, S, IS 226Ra (C)d                              Yes                                Yes 2.6x101                              GP, S          S, IS                  PIC, S, IS 232Th (C)d                              Yes                                Yes 4.1x101                            GP, S, GP        S, IS                  PIC, S, IS 238U (C)                                Yes                                Yes 1.9x101                          GP, S, GP, IS S, IS, GP                PIC, S, IS 239Pu                                    Yes                                Noc                                                                  ND 8.5x101                                GP,S          ND (IS) 241Am                                    Yes                                Yes 7.8x101                              GP, S          S, IS                  PIC, S, IS 2        Abbreviations: Bq = becquerels; m2 = square meters; kg = kilograms; GP = gas-flow proportional counter ( mode); GM = Geiger-Mueller survey meter; GP =
3 4-34 gas-flow proportional counter ( mode); PIC = pressurized ionization chamber; S = alpha scintillation survey meter; S = gamma scintillation (gross); IS = in situ 4        gamma spectrometry.
5        a    Example DCGLs are provided only for discussion and are based on values given in NRC Report NUREG-1757 (Rev. 2), Volume 1, Tables B.1 and B.2 (NRC May 2020 6            2006). Example DCGLs should not be used in place of approved DCGLs.
7        b    ND = Not detectable.
8        c    Possibly detectable at limits for areas of elevated activity.
9        d    For decay chains having two or more radionuclides of significant half-life that reach secular equilibrium, the notation (C) indicates the direct measurement 10 MARSSIM techniques assume the presence of decay products in the chain.
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MARSSIM                                                        Considerations for Planning Surveys 1 Conceptual models reflected in commonly used codes used to derive DCGLs should be 2 understood. For example, if surficial residual radioactive material exists at a thickness less than 3 15 cm (6 inches), commonly used codes either assume or allow the residual radioactive 4 material to be uniformly mixed throughout a larger thickness to simulate such processes as soil 5 mixing due to plowing. Yu et al. (1993) allows both the thickness of contamination and the 6 mixing depth to be specified. NRC (1992b) assumes the residual radioactivity is located in the 7 top 15 cm of soil. Similarly, models may be based on dry weight, which may necessitate either 8 drying samples or data transformation to account for dry weight. The DQOs and subsequent 9 direction to the laboratory for analysis might include removal of material not relevant for 10 characterizing the sample, such as pieces of glass, twigs, rocks, pebbles, or leaves. In all 11 cases, it is important to understand the modeling assumptions and how the data collected will 12 be compared to DCGLs derived from the modeling to ensure the fidelity of the statistical survey 13 results.
14 Both sample depth and area are considerations in determining appropriate sample volume, and 15 sample volume is a key consideration for determining the laboratory MDC. The depth should 16 also correlate with the conceptual model developed in Chapter 3 and upgraded throughout the 17 RSSI process. For example, if data collected during the HSA indicate that residual radioactive 18 material may exist to a certain depth, then samples should be deep enough to support the 19 survey objectives, such as for the scoping or characterization survey. Taking samples as a 20 function of depth might also be a survey design objective, such as for scoping, characterization, 21 or remediation support. Although some models and codes may allow for the input of (or can be 22 manipulated to consider) heterogeneous radionuclide distributions, other models and codes 23 may assume uniform residual radioactivity. In cases where the models are incapable of 24 representing the complexity of the sources, data may need to be processed for use in the 25 model. Impacts associated with the modeling simplifications should be well understood and 26 documented.
27 Additionally, the design team needs to consider sampling both data needs and data quality 28 indicators as determined from the DQO process. The design team should review the information 29 in Section 7.2 when designing the sampling portion of the FSS plan. The decision maker and 30 the survey planning team need to identify the data needs for the survey being performed, 31 including 32
* type of samples to be collected or measurements to be performed (Chapter 5) 33
* radionuclide(s) of interest (Section 4.3) 34
* number of samples to be collected (Sections 5.3.3-5.3.5) 35
* type and frequency of field QC samples to be collected (Section 4.9) 36
* amount of material to be collected for each sample (Sections 4.7.3 and 7.5) 37
* sampling locations and frequencies (Section 5.3.7) 38
* SOPs to be followed or developed 39
* measurement method uncertainty (Section 6.4) 40
* target detection capabilities for each radionuclide of interest (Section 6.3) 41
* cost of the methods being evaluated (cost per analysis and total cost) (Appendix H)
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Considerations for Planning Surveys                                                      MARSSIM 1
* necessary turnaround time 2
* sample preservation and shipping requirements (Section 7.6) 3
* specific background for each radionuclide of interest (Section 4.5) 4
* DCGL for each radionuclide of interest (Section 4.3) 5
* measurement documentation requirements (Section 5.3.11) 6
* sample tracking requirements (Section 7.8) 7 In addition to the above items, the design team needs to consider the following data quality 8 indicators:
9
* precision 10
* bias 11
* representativeness 12
* comparability 13
* completeness 14
* others as discussed in Section 7.2.2.6 15 See Section 7.2 for a detailed discussion of the DQOs and MQOs for sampling.
16 Under some circumstances, it might be useful to assess the radionuclide concentrations on 17 different size fractions to better assess transport processes assumed in some dose models.
18 Chapters 6 and 7 present more detail regarding the application of these survey planning 19 considerations.
20 4.8.6    Selection of Measurement Techniques 21 In practice, the DQO process is used to obtain a proper balance among the use of various 22 measurement techniques (scanning, direct, and laboratory). In general, there is an inverse 23 correlation between the cost of a specific measurement technique and the detection levels 24 being sought. Depending on the survey objectives, important considerations include survey 25 costs and choosing an appropriate measurement method.
26 A certain minimum number of direct measurements or samples may be needed to demonstrate 27 compliance with the release criteria based on certain statistical tests (see Section 5.3.2).
28 Alternatively, if there is sufficient detection capability and an acceptable level of measurement 29 method uncertainty, a scan-only survey technique can (with the proper application of the DQO 30 process and regulatory approval) be used to demonstrate compliance with the DCGLW. The 31 potential for areas of elevated residual radioactive material may also have to be considered for 32 designing scanning surveys, as the need to identify areas of elevated activity may affect the 33 number of measurements. Some measurements may provide information of a qualitative nature 34 to supplement other measurements. An example of such an application is in situ gamma 35 spectrometry to demonstrate the absence (or presence) of specific radionuclides.
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MARSSIM                                                        Considerations for Planning Surveys 1 Assuming the residual radioactive material can be detected, either directly or by measuring a 2 surrogate radionuclide in the mixture, the next decision point depends on whether the 3 radionuclide being measured is present in background. Gross measurement methods will likely 4 be more appropriate for measuring concentrations of radioactive materials on surfaces in 5 structures, scanning for locations of elevated activity, and determining exposure rates.
6 Radionuclide-specific measurement techniques, such as gamma spectrometry, provide a 7 marked increase in detection capability over gross measurements because of their ability to 8 screen out contributions from other sources. Figure 4.2 illustrates the sequence of steps in 9 determining the type of survey design neededthat is, whether field measurement techniques 10 can be applied at a particular site along with sampling or if a scan-only design is more 11 appropriate. The selection of appropriate instruments for scanning, direct measurement, and 12 sampling and analysis should be survey specific.
13 4.8.7  Data Conversion 14 Radiation survey data are usually obtained in units, such as the number of counts per unit time, 15 which have no intrinsic meaning relative to DCGLs. For comparison of survey data to DCGLs, 16 the survey data from field and laboratory measurements should be converted to DCGL units.
17 Alternatively, the DCGL can be converted into the same units used to record survey results.
18 Either method relies on understanding the instrument response (efficiency). The FSS design 19 team should use the DQO process to determine and document the proper methods used to 20 compare instrument results and DCGLs. Additional details are provided in Sections 4.12.6 and 21 6.7.
22 4.8.8  Additional Planning Considerations Related to Measurements 23 4.8.8.1 Selecting a Field Service Provider 24 The survey design team should start the process of selecting a service provider to perform field 25 data collection early in the planning process. Six criteria that should be considered are 26
* validated SOPs 27
* experience with similar data collection activities 28
* satisfactory performance evaluations or technical review results 29
* adequate capacity to perform the all the data collection activities 30
* internal QC program 31
* protocols for method performance documentation, sample tracking and security, and 32    documentation of results 33 More details can be found in Section 6.5.
34 4.8.8.2 Radon Measurements 35 In some cases, radon may be detected within structures that do not contain residual radioactive 36 material; conversely, some structures that contain residual radioactive material may not yield 37 detectable radon or thoron. Consult with your regulator for the applicability of radon or thoron 38 measurements as part of a site survey.
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Considerations for Planning Surveys                                              MARSSIM From Figure 4.1 Calculate Required MQOs (i.e., Detection Capabilities and Required Measurement Method Uncertainties)
Evaluate Measurement Methods Relative to Required MQOs Can Scanning                      Can Direct Measurements Achieve      No  Measurements Achieve                No Required MQOs?                  Required MQOs?
Yes                              Yes Design Survey Plan for Direct    Design Survey Plan for Design Survey Plan for Scan Measurement and/or                Sampling Survey and/or Sampling Sampling Select and Obtain Instruments Calibrate Instruments To Figure 4.1 1
2 Figure 4.2: Flow Diagram for Field Survey Design NUREG-1575, Revision 2                        4-38                                May 2020 DRAFT FOR PUBLIC COMMENT                                          DO NOT CITE OR QUOTE
 
MARSSIM                                                          Considerations for Planning Surveys 1 If radon is a concern for the FSS, the design team should work with the appropriate regulatory 2 agency to determine the applicability of radon or thoron measurements. Because of the 3 widespread nature of indoor air radon, many states have developed requirements for 4 certification/qualification of people who perform radon services. Therefore, as part of the 5 qualifications for the service provider, determine whether the measurement provider or the 6 laboratory analyzing the measurements is required to be certified by the state or locality where 7 the work is being performed. State radon contacts can be found at 8 https://www.epa.gov/radon/find-information-about-local-radon-zones-and-state-contact-9 information.
10 More details can be found in Section 6.8.
11 4.8.8.3 Specialized Equipment 12 The survey team must plan for using any specialized equipment other than radiation detectors 13 (e.g., global positioning systems [GPS], local microwave or sonar beacons and receivers, laser 14 positioning systems, etc.). Because these specialized systems are continuously being modified 15 and developed for site-specific applications, it is not possible to provide detailed descriptions of 16 every system. Section 6.9 provides examples of specialized equipment that have been applied 17 to radiation surveys and site investigations.
18 4.9    Site Preparation 19 Site preparation involves obtaining consent for performing the survey, establishing the property 20 boundaries, evaluating the physical characteristics of the site, accessing surfaces and land 21 areas of interest, and establishing a reference coordinate system. Site preparation may also 22 include removing equipment and materials that restrict access to surfaces. The presence of 23 furnishings or equipment will restrict access to building surfaces and add additional items that 24 the survey should address.
25 4.9.1    Consent for Survey 26 When facilities or sites are not owned by the organization performing the surveys, consent from 27 the site or equipment owner should be obtained before conducting the surveys. All appropriate 28 Federal, State, Tribal, and local officials, as well as the site owner and other affected parties, 29 should be notified of the survey schedule. Section 3.6 discusses consent for access, and 30 additional information based on the Comprehensive Environmental Response, Compensation, 31 and Liability Act is available from EPA (EPA 1987c).
32 4.9.2    Property Boundaries 33 Property boundaries may be determined from property survey maps furnished by the owners or 34 from plat maps obtained from city or county tax maps. Large-area properties and properties with 35 obscure boundaries or missing survey markers may require the services of a professional land 36 surveyor. A professional land surveyor can also tie a site radiological survey grid into the 37 existing land survey of the site or to an official State or municipal survey grid. Such a tie-in has 38 the advantage of making the radiological survey grid reproducible in the future.
39 If the radiological survey is only performed inside buildings, a tax map with the buildings 40 accurately located will usually suffice for site/building location designation.
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Considerations for Planning Surveys                                                        MARSSIM 1 4.9.3  Physical Characteristics of the Site 2 The physical characteristics of the site will have a significant impact on the complexity, 3 schedule, and cost of a survey. These characteristics include the number and size of structures, 4 type of building construction, wall and floor penetrations, pipes, building condition, total area, 5 topography, soil type, and ground cover. In particular, the accessibility of structures and land 6 areas (Section 4.9.4) has a significant impact on the survey effort. In some cases, survey 7 techniques (e.g., in situ gamma spectrometry or scanning surveys discussed in Chapter 6) can 8 preclude or reduce the need to gain physical access or use intrusive techniques. This should be 9 considered during survey planning.
10 4.9.3.1 Structures 11 Building design and condition will have a marked influence on the survey efforts. The time 12 involved in conducting a survey of building interior surfaces is essentially directly proportional to 13 the total surface area, recognizing that upper wall and ceiling areas require more time than floor 14 and lower wall surveys. For this reason, the degree of survey coverage decreases as the 15 potential for residual radioactive material decreases. Judgment measurements and sampling, 16 which are performed in addition to the measurements performed for certain survey designs, are 17 recommended in areas likely to have accumulated deposits of residual radioactive material. As 18 discussed in Section 8.5, judgment measurements and samples are compared directly to the 19 appropriate DCGL.
20 The condition of surfaces after remedial action may affect the survey process. Removing 21 radioactive material that has penetrated a surface usually involves removing the surface 22 material. As a result, the floors and walls of remediated facilities are frequently badly scarred or 23 broken up and are often very uneven. Such surfaces are more difficult to survey, because it is 24 not possible to maintain a fixed distance between the detector and the surface. In addition, 25 scabbled or porous surfaces may significantly attenuate radiationsparticularly alpha and low-26 energy beta particles. Use of monitoring equipment on wheels is precluded by rough surfaces, 27 and such surfaces also pose an increased risk of damage to fragile detector probe faces. These 28 factors should be considered during the calibration of survey instruments; NRC report NUREG-29 1507 (NRC 1997a) provides additional information on how to address these surface conditions.
30 The condition of the building should also be considered from a safety and health standpoint 31 before a survey is conducted. A structural assessment may be needed to determine whether the 32 structure is safe to enter.
33 Expansion joints, stress cracks, drains, and penetrations into floors and walls for piping, conduit, 34 anchor bolts, etc., are potential sites for accumulation of residual radioactive material and 35 pathways for migration into subfloor soil and hollow wall spaces. Drains, sewers, and septic 36 systems can contain residual radioactive material, and wall/floor interfaces are also likely 37 locations for residual radioactive material. Coring, drilling, or other such methods may be 38 necessary to gain access for surveying. Intrusive surveying may require permitting by local 39 regulatory authorities. Additionally, suspended ceilings may cover areas of potential residual 40 radioactive material, such as ventilation ducts and fixtures. There may be other materials 41 introduced that were not part of the original constructionsuch as floor tiles, partitions, 42 insulation, additional concrete slabs, and paintthat may cover residual radioactive material.
43 Exterior building surfaces will typically have a low potential for residual radioactive material; 44 however, there are several locations that should be considered during survey planning. If there 45 are roof exhausts or roof accesses that allow for radioactive material movement, or if the facility 46 is proximal to the air effluent discharge points, the possibility for residual radioactive material on NUREG-1575, Revision 2                          4-40                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                            Considerations for Planning Surveys 1 the roof should be considered. Because roofs are periodically resurfaced, radioactive material 2 may be trapped in roofing material, and sampling this material may be necessary. Such roof 3 drainage points as driplines along overhangs, downspouts, and gutters are also important 4 survey locations. Roofs may also accumulate radioactive material from fallout, or roof materials 5 may contain elevated levels of naturally occurring radioactive material (e.g., elevated uranium in 6 roof tar). Wall penetrations for process equipment, piping, and exhaust ventilation are potential 7 locations for exterior residual radioactive material. Window ledges and outside exits (doors, 8 doorways, landings, stairways, etc.) are also building exterior surfaces that should be 9 addressed.
10 4.9.3.2 Building Materials 11 In addition to radiological surveys of the building surfaces described in Section 4.8.3.1, it may 12 also be necessary to survey any building materials removed from the building as part of its 13 demolition, remediation, or renovation. Guidance for the design and implementation of 14 radiological surveys of these materials is provided in MARSAME (NRC 2009).
15 4.9.3.3 Land Areas 16 Depending on site processes and operating history, the radiological survey may include varying 17 portions of the land areas. Open land or paved areas with a potential for residual radioactive 18 material should include storage areas (e.g., equipment, product, waste, and raw material), liquid 19 waste collection lagoons and sumps, areas downwind (based on predominant wind directions 20 on an average annual basis, if possible) of stack release points, and surface drainage 21 pathways. Additionally, roadways and railways that may have been used for transport of 22 improperly contained radioactive materials could also have an accumulation of residual 23 radioactive material.
24 Building modifications should be reviewed to assess any expansions that might cover former 25 land disposal areas. Other land areassuch as wetlands, marshlands, or low-lying surface 26 areaswhere waste material was used as fill material need to be assessed for potential 27 residual radioactive material. In some instances, the waste material is covered with clean 28 backfill material to grade to ground surface. Archived aerial photos, historical maps, and 29 interviews can be used to assess the potential presence of such areas.
30 Buried piping, underground tanks, fill areas, sewers, spill areas, and septic leach fields that may 31 have received radioactive liquids are locations of possible residual radioactive material that may 32 necessitate sampling of subsurface soil (Section 7.5.3). Information regarding soil type 33 (e.g., clay, sand) may provide insight into the retention or migration characteristics of specific 34 radionuclides. The need for special sampling by coring or split-spoon equipment should be 35 anticipated for characterization surveys.
36 If radioactive waste has been removed, surveys of excavated areas will be necessary before 37 backfilling with clean fill. If the waste is to be left in place, subsurface sampling around the burial 38 site perimeter to assess the potential for future migration may be necessary.
39 Additionally, rivers, harbors, shorelines, and other outdoor areas with a potential for residual 40 radioactive material may require survey activities including environmental media (e.g., sediment 41 and biota) associated with these areas.
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Considerations for Planning Surveys                                                        MARSSIM 1 4.9.4    Clearing to Provide Access 2 In addition to the physical characteristics of the site, a major consideration is how to address 3 difficult-to-access areas that have a potential for residual radioactive material. Difficult-to-access 4 areas may need significant effort and resources to perform adequate surveys. This section 5 provides a description of common difficult-to-access areas that may have to be considered. The 6 level of effort expended to access such areas should be commensurate with the potential for 7 residual radioactive material. For example, the potential for the presence of residual radioactive 8 material behind walls should be established before significant effort is expended to remove 9 drywall.
10 4.9.4.1 Structures 11 When necessary, structures and indoor areas should be sufficiently cleared to permit 12 completion of the survey. Clearing includes providing access to interior surfaces (e.g., drains, 13 ducting, tanks, pits, ceiling areas, and equipment) by removing covers, disassembly, or other 14 means of producing adequate openings.
15 Such building features as ceiling height, construction materials, ducts, pipes, etc., will determine 16 the ease of accessibility of various surfaces. Scaffolding, cranes, lifts, or ladders may be 17 necessary to reach some surfaces, and dismantling portions of the building may be required.
18 The presence of furnishings and equipment will restrict access to building surfaces and add 19 additional items that the survey should address. Any remaining equipment indirectly involved in 20 the process may need to be dismantled to evaluate the radiological status, particularly of 21 difficult-to-access parts of the equipment. Removing or relocating certain furnishings, such as 22 laboratory benches and hoods, to obtain access to floors and walls may also be necessary. The 23 amount of effort and resources dedicated to such removal or relocation activities should be 24 commensurate with the potential for residual radioactive material. Where the potential is low, a 25 few spot-checks may be sufficient to provide confidence that covered areas are free of residual 26 radioactive material. In other cases, complete removal may be warranted. Guidance for the 27 survey and assessment of materials and equipment is included in the MARSAME Manual.
28 Piping, drains, sewers, sumps, tanks, and other components of liquid-handling systems present 29 special difficulties because of the difficulty in accessing interior surfaces. Process information, 30 operating history, and preliminary monitoring at available access points will assist in evaluating 31 the extent of sampling and measurements included in the survey. Some specialized survey 32 techniques for drains and sewers have been developed and are effective for the measurement 33 of some radionuclides.
34 If the building is constructed of porous materials (e.g., wood, concrete, masonry, etc.) and the 35 surfaces were not sealed, residual radioactive material may be found in the walls, floors, and 36 other surfaces. It may be necessary to obtain cores of these surfaces for laboratory analysis.
37 Another accessibility problem is the presence of residual radioactive material beneath tile or 38 other floor coverings. This often occurs because the covering was placed over surfaces 39 containing residual radioactive material, or the joints in tile were not sealed to prevent 40 penetration. The practice in some facilities has been to fix radioactive material (particularly 41 alpha emitters) by painting over the surface of the affected area. Thus, actions to obtain access 42 to surfaces, such as removing wall and floor coverings (including paint, wax, or other sealer) 43 and opening drains and ducts, may be necessary to enable representative measurements of the 44 residual radioactive material. This material may also require a radiation survey to ensure no NUREG-1575, Revision 2                            4-42                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                          Considerations for Planning Surveys 1 radioactive material was transferred during the removal process. If alpha radiation or very low 2 energy beta radiation is to be measured, the surface should be free of overlying material, such 3 as dust and water, which may significantly attenuate the radiations.
4 4.9.4.2 Land Areas 5 If ground cover needs to be removed or if other obstacles limit access by survey personnel or 6 necessary equipment, the time and expense of making land areas accessible should be 7 considered. In addition, contamination control procedures need to be developed to prevent the 8 spreading of radioactive material during ground cover removal or the use of heavy equipment.
9 Whenever possible, the property owner should perform the removal or relocation of equipment 10 and materials that require special precautions to prevent damage or maintain inventory 11 accountability. Clearing open land of brush and weeds will usually be performed by a 12 professional land-clearing organization under subcontract arrangements. However, survey 13 personnel may perform minor land-clearing activities as needed.
14 An important consideration prior to clearing is the possibility of bio-uptake of radionuclides in the 15 plant material to be cleared. Special precautions to avoid exposure of personnel involved in 16 clearing activities may be necessary. Radiological screening surveys should be performed to 17 ensure that cleared material or equipment does not contain residual radioactive material.
18 The extent of site clearing in specific areas depends primarily on the potential for residual 19 radioactive material to exist in those areas where 20
* The radiological history or results of previous surveys indicate a low potential for residual 21      radioactive material in an area; it may be sufficient to perform only minimum clearing to 22      establish a reference coordinate system.
23
* Residual radioactive material is known to exist, or a high potential for it necessitates 24      completely clearing an area to provide access to all surfaces.
25
* New findings as the survey progresses indicate that additional clearing is needed.
26 Open land areas may be cleared by heavy machinery (e.g., bulldozers, bushhogs, and 27 hydroaxes). However, care should be exercised to prevent relocation of surface radioactive 28 material or damage to such site features as drainage ditches, utilities, fences, and buildings.
29 Minor land clearing may be performed using manually operated equipment, such as brush 30 hooks, power saws, knives, and string trimmers. Brush and weeds should be cut to the 31 minimum practical height necessary to facilitate measurement and sampling activities 32 (approximately 15 cm). Care should be exercised to prevent unnecessary damage to or removal 33 of mature trees, shrubs, or historical or cultural resources.
34 Potential ecological or cultural damage that might result from an extensive survey should be 35 considered. If a survey is likely to result in significant or permanent damage to environmental or 36 cultural resources, appropriate environmental and cultural analyses should be conducted prior 37 to initiating the survey.
38 4.9.5    Reference Coordinate System 39 4.9.5.1 Establishment 40 Reference coordinate systems are established at the site to May 2020                                          4-43                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Considerations for Planning Surveys                                                      MARSSIM 1
* Facilitate the selection of measurement and sampling locations.
2
* Provide a mechanism for referencing a measurement to a specific location so that the same 3    survey point can be located again.
4 A survey reference coordinate system consists of a grid of intersecting lines referenced to a 5 fixed site location or benchmark. Typically, the lines are arranged in a perpendicular pattern, 6 dividing the survey location into squares or blocks of equal area; however, other types of 7 patterns (e.g., three-dimensional, polar) have been used.
8 The reference coordinate system used for a particular survey should provide a level of 9 reproducibility consistent with the objectives of the survey. For example, commercially available 10 single-frequency GPS devices can typically locate a position to within approximately 5 m, while 11 dual-frequency receivers and augmentation systems can provide real-time precision on the 12 order of a few centimeters. On the other hand, a metal bar can be driven into the ground to 13 provide a long-term reference point for establishing a local reference coordinate system. Some 14 States have official grid systems, and if such a system exists in a particular State, consideration 15 should be given to tying a site grid into the official State grid.
16 Reference coordinate system patterns on horizontal surfaces are usually identified numerically 17 on one axis and alphabetically on the other axis, or in distances in different compass directions 18 from the grid origin. Examples of structure interior and land area grids are shown in 19 Figures 4.3-4.5. Grids on vertical surfaces may include a third designator, indicating position 20 relative to floor or ground level. Overhead measurement and sampling locations (e.g., ceiling 21 and overhead beams) are referenced to corresponding floor grids.
22 For surveys of Class 1 and Class 2 areas, basic coordinate system patterns at 1-2 m intervals 23 on structure surfaces and at 10-20 m intervals of land areas may be sufficient for the purpose of 24 identifying FSS locations with a reasonable level of effort. Gridding of Class 3 areas may also 25 be necessary to facilitate referencing of survey locations to a common system or origin but, for 26 practical purposes, may typically be at larger intervals (e.g., 5-10 m for large structural surfaces 27 and 20-50 m for land areas). For the FSS, the required scanning percentages, number of 28 discrete survey locations for direct measurements, and number of sample locations will depend 29 on the classification of the survey unit (see Chapter 5).
30 Reference coordinate systems on structure surfaces are usually marked by chalk lines or paint 31 along the entire grid line or at line intersections. Land area reference coordinate systems are 32 usually marked by wooden or metal stakes driven into the surface at reference line 33 intersections. The selection of an appropriate marker depends on the characteristics and routine 34 uses of the surface. Where surfaces prevent installation of stakes, the reference line 35 intersection can be marked by painting.
36 Three basic coordinate systems are used for identifying points on a reference coordinate 37 system. The reference system shown in Figure 4.3 references grid locations using numbers on 38 the vertical axis and letters on the horizontal axis. The reference system shown in Figure 4.4 39 references distances from the (0,0) point using the compass directions N (north), S (south),
40 E (east), and W (west). The reference system shown in Figure 4.5 references distances along 41 and to the R (right) or L (left) of the baseline.
42 In addition, a less frequently used reference system is the polar coordinate system, which 43 measures distances along transects from a central point. Polar coordinate systems are 44 particularly useful for survey designs to evaluate effects of stack emissions, where it may be NUREG-1575, Revision 2                            4-44                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                        Considerations for Planning Surveys 1 desirable to have a higher density of samples collected near the stack and fewer samples with 2 increasing distance from the stack.
3 Figure 4.5 shows an example grid system for an outdoor land area. The first digit or set of digits 4 includes an L or R (separated from the first set by a comma) to indicate the distance from the 5 baseline in units (m) and the direction (left or right) from the baseline. The second digit or set of 6 digits refers to the perpendicular distance from the (0,0) point on the baseline and is measured 7 in hundreds of units. Point A in the example of a reference coordinate system for survey of site 8 grounds, Figure 4.5, is identified as (100R, 2+00) (i.e., 200 m from the baseline and 100 m to 9 the right of the baseline). Fractional distances between reference points are identified by adding 10 the distance beyond the reference point and are expressed in the same units used for the 11 reference coordinate system dimensions. Point B on Figure 4.5 is identified as (25R, 1+30).
12 Open land reference coordinate systems should be referenced to a location on an existing State 13 or local reference system or to a U.S. Geological Survey (USGS) benchmark. (This may require 14 the services of a professional land surveyor.) GPS is capable of locating reference points in 15 terms of latitude and longitude (Section 6.9.2 provides descriptions of positioning systems.)
16 Following the establishment of the reference coordinate system, a drawing is prepared by the 17 survey team or the land surveyor. This drawing indicates the reference lines, site boundaries, 18 and other pertinent site features and provides a legend showing the scale and a reference 19 compass direction.
20 4.9.5.2 Quality System Considerations 21 The concept of the quality system was introduced in Section 4.2.2. The process used to 22 develop the reference coordinate system should be recorded in the survey planning 23 documentation (e.g., the QAPP). Any deviations from the requirements developed during 24 planning should be documented when the reference coordinate system is established.
25 When the survey reference coordinate system is referenced to a fixed site location or 26 benchmark on a known geographic coordinate system (GCS) or projected coordinate system 27 (projection) (e.g., a State system), or the survey reference coordinate system itself uses a 28 known GCS or projection rather than one of the three basic coordinate systems described in 29 Section 4.9.5.1, then the following information should be provided about the actual GCS or 30 projection used:
31
* name 32
* units used (e.g., feet, meters, etc.)
33
* zone 34
* datum 35
* spheroid 36
* method used to determine/obtain the coordinates (e.g., GPS) 37
* estimates of the accuracy and precision of the coordinates 38
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Considerations for Planning Surveys                                                      MARSSIM 1 Ideally, this information should be provided in the spatial reference section of the metadata for 2 the GIS layer containing the data. If a GPS was used to obtain the coordinates, then information 3 should be included about the differential corrections made to the original GPS measurements.
4 It should be noted that the reference coordinate systems described in this section are intended 5 primarily for reference purposes and do not necessarily dictate the spacing or location of survey 6 measurements or samples. Establishment of a measurement grid to demonstrate compliance 7 with the DCGLs is discussed in Section 5.3.7 and Chapter 8.
8 9 Figure 4.3: Indoor Grid Layout with Alphanumeric Grid Block Designation: Walls and 10 Floors are Diagramed as Though They Lay Along the Same Horizontal Plane NUREG-1575, Revision 2                          4-46                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                Considerations for Planning Surveys 1
2 Figure 4.4: Example of a Grid System for Survey of Site Grounds Using Compass 3 Directions May 2020                                  4-47                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                      DO NOT CITE OR QUOTE
 
Considerations for Planning Surveys                                          MARSSIM 1
2 Figure 4.5: Example of a Grid System for Survey of Site Grounds Using Distances Left or 3 Right of the Baseline NUREG-1575, Revision 2                    4-48                                May 2020 DRAFT FOR PUBLIC COMMENT                                      DO NOT CITE OR QUOTE
 
MARSSIM                                                          Considerations for Planning Surveys 1 4.10 Health and Safety 2 Health and safety are emphasized as issues potentially affecting the implementation of 3 MARSSIM surveys. The focus of the health and safety program is minimizing environmental and 4 physical hazards (e.g., confined spaces, unstable surfaces, heat and cold stress) where these 5 issues may affect how a survey is designed and performed. Work areas and procedures that 6 present potential safety hazards must be identified and evaluated to warn personnel of potential 7 hazards. Personnel must be trained about potential physical and chemical safety hazards 8 (e.g., inhalation, adsorption, ingestion, injection/puncturing) and the potential for injury 9 (e.g., slips, trips, falls, burns). In addition, the presence or possibility of such environmental 10 hazards as poison ivy; ticks carrying Lyme disease; and poisonous snakes, spiders, rodents, or 11 insects should be noted. These hazards can affect the safety and health of the workers, as well 12 as the schedule for performing the survey. Some physical hazards require special procedures or 13 precautions. Steep slopes might require special gear for surveyors and instruments or might call 14 for dispensations from the regulatory agency to reduce or eliminate survey efforts in such areas.
15 The potential presence of unexploded ordnance (UXO) requires qualified explosive ordnance 16 disposal personnel to clear the survey unit of UXO and accompany survey personnel during the 17 survey.
18 A job safety analysis (JSA) should be performed prior to implementing a survey. The JSA offers 19 an organized approach to the task of locating problem areas for material handling safety (OSHA 20 2002). The JSA should be used to identify hazards and provide inputs for drafting a health and 21 safety plan (HASP). The HASP will address the potential hazards associated with survey 22 activities and should be prepared concurrently with the survey design. The HASP identifies 23 methods to minimize the threats posed by the potential hazards. The information in the HASP 24 may influence the selection of a measurement technique and disposition survey procedures.
25 Radiation work permits (RWPs) may be established to control access to radiologically controlled 26 areas. RWPs contain requirements from the JSA, such as dosimetry and personal protective 27 equipment (PPE), as well as survey maps illustrating predicted dose rates and related 28 radiological concerns (e.g., removable or airborne radioactive material). Hazard work permits 29 (HWPs) may be used in place of RWPs at sites with primarily physical or chemical hazards.
30 The JSA systematically carries out the basic strategy of accident prevention through the 31 recognition, evaluation, and control of hazards associated with a given job, as well as the 32 determination of the safest, most efficient method of performing that job. This process creates a 33 framework for deciding among engineering controls, administrative controls, and PPE for the 34 purpose of controlling or correcting unsafe conditions. Examples of these controls include 35
* engineering controls, which are physical changes in processes or machinery (e.g., installing 36    guards to restrict access to moving parts during operation), storage configuration 37    (e.g., using shelves in place of piles or stacks) 38
* administrative controls, which are changes in work practices and organization 39    (e.g., restricted areas where it is not safe to eat, drink, smoke, etc.), including the placement 40    of signs to warn personnel of hazards 41
* PPE, which are clothing or devices worn by employees to protect against hazards 42    (e.g., gloves, respirator, full-body suits) 43 Correction measures may incorporate principles of all of the controls listed above. The preferred 44 method of control is through engineering controls, followed by administrative controls, and then 45 PPE.
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Considerations for Planning Surveys                                                        MARSSIM 1 Proper handling procedures for hazardous substances are documented in site-specific health 2 and safety plans. Compliance with all control requirements is mandatory to maintain a safe 3 working environment. Personnel must regard control requirements as a framework to facilitate 4 health and safety, while still taking responsibility for their own well-being. Being wary of safety 5 hazards remains an individual responsibility, and personnel must be aware of their surroundings 6 at all times in work areas.
7 4.11 Documentation 8 Concurrently with the FSS design, the design team should begin to draft the FSS report. In 9 many cases before the FSS is started, the regulator will require a report documenting the 10 proposed sampling and surveying plan, including ancillary documentation such as the QAPP.
11 The FSS report should present a complete and unambiguous record of the radiological status of 12 the survey unit, relative to the established DCGLs. To the extent possible, this should be 13 self-contained and contain a minimum of information incorporated by reference. Reporting 14 requirements for the FSS should be developed during planning and clearly documented in the 15 QAPP. The text below describes some of the information needed for review of an FSS:
Example 1: Information Needed for an FSS Review A review by the U.S. Nuclear Regulatory Commission of the final status survey (FSS) documentation is undertaken to verify that the results of the FSS demonstrate that the site, area, or building meet the radiological criteria for license termination (NRC, 2006). The information needed by the NRC for a review is summarized below. For more details, see NRC (2006).
* an overview of the results of the FSS
* a summary of the derived concentration guideline levels
* a discussion of any differences from prior submissions
* a description of the method by which the number of samples was determined for each survey unit
* a summary of the values used to determine the number of samples and a justification for these values
* the results for each survey unit
* analytical methods used
* detection limits
* estimates of uncertainties or sample standard deviations
* a description of any changes in initial survey unit assumptions relative to the extent of residual radioactive material
* a description of how as low as reasonably achievable practices were employed to achieve final activity levels NUREG-1575, Revision 2                          4-50                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                            Considerations for Planning Surveys In addition to the items above, the design team should have the following information available (NRC, 2006):
* the results of previously conducted in-process inspections and confirmatory surveys
* the licensees quality assurance/quality control program
* confirmation that the changes to prior submissions are not significant and are technically correct
* issues (a) identified by intervenors and stakeholders and (b) raised in allegations to assure such issues have been satisfactorily resolved
* descriptions of the survey units to determine if any special survey situations are present
* results of elevated measurement comparisons
* results of the appropriate statistical tests (e.g., Wilcoxon Rank Sum and Sign tests) to confirm that results indicate compliance
* specific parts of the FSS and supporting data that affect the FSS but that were not available when the decommissioning or license termination plan was approved 1 4.12 Application of Survey Planning Concepts with Example Calculations 2 This section is intended to expand on the content presented in this chapter, provide a general 3 overview, and familiarize the MARSSIM user with the application of the concepts in 4 Sections 4.4 through 4.7 to planning FSSs. 7 Greater detail appears in the chapters that follow.
5 4.12.1 Scenario A or Scenario B?
6 Occasionally, the design team will need to determine the appropriate scenario for use in 7 statistical hypothesis testing as the basis for the FSS. Under Scenario A, it is assumed that the 8 concentration of residual radioactive material equals or exceeds the release criteria. For 9 Scenario B, it is assumed that the concentration of residual radioactive material meets the 10 release criteria (i.e., less than the action level [AL]). Historically, MARSSIM recommended the 11 use of Scenario A, which put the burden of proof that the survey unit met the release criteria on 12 the individuals designing the survey. In Scenario B, the burden of proof is no longer on the 13 individuals designing the survey and thus should be used with caution and only in those 14 situations where Scenario A is not an effective alternative.
15 The basic problem is one of being able to distinguish residual radioactive material from 16 background. If a radionuclide has a relatively small DCGLW and is present in the background 17 with a relatively large variation, then it requires a large number of measurements to determine if 18 the residual concentration exceeds the DCGLW. The choice of Scenario A or Scenario B should 19 be based on which null hypothesis is easier to live with if false (NRC 1998a). If the DCGLW is 20 large relative to the measurement or background variation, then Scenario A should be chosen 21 (NRC 1998a). This is likely the more common situation. Conversely, if the DCGLW is small 7 Appendix A contains a detailed example of MARSSIM applied to executing FSS for a single radionuclide. This example builds on examples in Chapters 5 and 8.
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Considerations for Planning Surveys                                                                MARSSIM 1 relative to the measurement or background variation, then Scenario B should be chosen 2 (NRC 1998a).
3 The MARSSIM user should review the information in Section 5.3.1 and NRC (1998a) for more 4 information on selecting the appropriate scenario. The remainder of the examples in this section 5 are based on Scenario A.
6 4.12.2 DCGL Calculations 7 4.12.2.1 Decay Series 8 In this example, the surface activity DCGLW for natural thorium (Th-nat) is 1,000 Bq/m2 9 (600 dpm/100 cm2), and all of its decay products are in secular equilibriumthat is, for each 10 disintegration of thorium-232 (232Th), a total of six alpha and four beta particles are emitted in 11 the thorium decay series. Note that in this example, the surface activity DCGLW of 1,000 Bq/m2 12 is assumed to apply to the total activity from all members of the decay chain. In this situation, 13 the corresponding alpha activity DCGLW should be adjusted to 600 Bq/m2 (360 dpm/100 cm2),
14 and the corresponding beta activity DCGLW to 400 Bq/m2 (240 dpm/100 cm2), in order to be 15 equivalent to 1,000 Bq/m2 of natural thorium surface activity. For a surface activity DCGLW of 16 1,000 Bq/m2, the beta activity DCGLW is calculated as shown in Equation (4-16):
DCGLW,  = DCGLW, Total  x (fraction of decays that emit s) 1,000 Bq of chain            4  Bq x
m2              Bq of 232Th    400  Bq
                                      =
10 Bq of chain
                                                                                  =                    (4-16) m2 232 1 Bq of Th 17 For this example, the beta activity DCGLW corresponding to the DCGLW for natural thorium is 18 400 beta particles/second/square meter.
19 To demonstrate compliance with the beta activity DCGLW for this example, measurements of 20 beta count rates must be converted to activity using a weighted beta efficiency that accounts for 21 the energy and yield of each beta particle. For decay chains that have not achieved secular 22 equilibrium, the relative activities between the different members of the decay chain can be 23 determined as previously discussed for surrogate ratios.
24 4.12.2.2 Surrogate DCGL 25 This example illustrates and discusses the application of the surrogate method.
26 Determining the Surrogate Ratio 27 Ten soil samples within the survey unit were collected and analyzed for 137Cs and 90Sr to 28 establish a surrogate ratio. The ratios of 90Sr to 137Cs were as follows: 6.6, 5.7, 4.2, 7.9, 3.0, 3.8, 29 4.1, 4.6, 2.4, and 3.3. An assessment of this example data set results in a mean 90Sr to 137Cs 30 surrogate ratio of 4.6, with a standard deviation of 1.7, as shown below using Equations 8.1 31 and 8.2:
6.6 + 5.7 +  + 2.4 + 3.3 32                              Mean =                                              = 4.6 10 (6.6  4.6)2 + (5.7  4.6)2 +  + (2.4  4.6)2 + (3.3  4.6)2 33                =                                                                          = 1.7 10  1 NUREG-1575, Revision 2                                    4-52                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                              DO NOT CITE OR QUOTE
 
MARSSIM                                                        Considerations for Planning Surveys 1 There are various approaches that may be used to develop a surrogate ratio from this data, but 2 each must consider the variability and level of uncertainty in the data. One may consider the 3 variability in the surrogate ratio by selecting the 95 percent upper confidence level (UCL) of the 4 surrogate ratio (to yield a conservative value of 90Sr from the measured 137Cs), which is 8.0 in 5 this case, as shown below using Equation 8.3:
6                                      UCL = 4.6 + 1.96 x 1.7 = 8.0 7 Similarly, one may select the most conservative value from the data set (in this case, 7.9).
8 At sites where surrogates are used, a correlation coefficient should be calculated to validate the 9 relationship between the radionuclides. In addition, the radioactive ingrowth and decay of 10 radionuclides should be evaluated. Surrogates are most appropriate for sites where the 11 radionuclides are contained in insoluble particulates. The sources of insoluble particulates 12 include the following:
13
* Sites processing minerals, such as monazite, thorite, thorianite, and zircon: The gamma 14    radiation from the decay products here are a useful surrogate for the decay chain, and the 15    insolubility of the minerals precludes changes in the ratios of the parent and progeny.
16
* Sites with residual radioactive material from corrosion products from nuclear reactors: In this 17    case, the gamma radiation from 60Co is typically used as a surrogate for other radionuclides, 18    including iron-59 (59Fe), iron-55 (55Fe), cobalt-57 (57Co), chromium (51Cr), manganese 19    (54Mn), nickel-57 (57Ni), and nickel-63 (63Ni). Note that at this kind of site, the shorter-lived 20    radionuclides will decay more rapidly than the 60Co, and appropriate decay corrections will 21    need to be evaluated.
22
* Sites with plutonium isotopes and americium-241 (241Am): At these sites, the gamma 23    radiation from 241Am is a useful surrogate for plutonium-249 (239Pu) and plutonium-240 24    (240Pu). Note that at this kind of site, plutonium-241 (241Pu) will continue to decay to 241Am; 25    therefore, the appropriate decay corrections will need to be made.
26
* Sites with thoriated metal (e.g., nickel, tungsten, or magnesium): The gamma radiation from 27    thorium progeny here can be used as a surrogate, but a thorough evaluation is required to 28    verify that sufficient time has passed to permit the thorium and its progeny to be near a state 29    of secular equilibrium.
30 Once an appropriate surrogate ratio is determined and approved by the appropriate regulatory 31 agency, the planning team needs to consider how compliance will be demonstrated using 32 surrogate measurements. That is, the planning team must modify the DCGL of the measured 33 radionuclide to account for the inferred radionuclide. This calculation is shown below.
34 Surrogate DCGL Calculation 35 The modified DCGL for 137Cs must be reduced using Equation (4-9):
1 36                                  DCGLCs-mod =
1      R
                                                              + Sr/Cs DCGLCs DCGLSr 37 where DCGLCs is the DCGL of 137Cs; DCGLSr is the DCGL of 90Sr, and RSr/Cs is the ratio of the 38 concentrations of 90Sr to 137Cs. Assuming that the DCGLSr is 150 Bq/kg, the DCGLCs is May 2020                                          4-53                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Considerations for Planning Surveys                                                      MARSSIM 1 100 Bq/kg, and the ratio of 90Sr to 137Cs is 8 (e.g., from a post-remediation characterization 2 survey), the modified DCGL for 137Cs (DCGLCs-mod ) can be calculated using Equation (4-9):
1 3                      DCGLCs-mod =                                    = 16 Bq kg-1 1              8
                                                    -1 +
100 Bq kg        150 Bq kg-1 4 The modified DCGL for 137Cs (DCGLCs-mod) is 16 Bq kg-1.
5 4.12.2.3 Gross Activity DCGL for Radionuclides in Known Ratios 6 Determining the Radionuclide Ratios 7 As with the surrogate ratio method, the determination of the relative ratios should be determined 8 through the DQO process and with regulatory approval. Care must be taken to ensure that 9 ratios are applicable to the FSS conditions (e.g., ratio measurements are made just before 10 starting the FSS).
11 General Gross Activity DCGL Calculation 12 For this example, assume that 40 percent of the total surface activity was contributed by a 13 radionuclide with a DCGL of 8,300 Bq/m2 (5000 dpm/100 cm2), 40 percent by a radionuclide 14 with a DCGL of 1,700 Bq/m2 (1000 dpm/100 cm2), and 20 percent by a radionuclide with a 15 DCGL of 830 Bq/m2 (500 dpm/100 cm2). Using Equation (4-10),
1 16                        DCGLgross =
1        2        3
                                                +            +
DCGL1 DCGL2 DCGL3 17 1
18                                  =
0.40              0.40          0.20 2 +              2 +
8,300 Bq/m        1,700 Bq/m      830 Bq/m2 19 20                                  = 1,900 Bq/m2 21 the gross activity DCGL is 1,900 Bq/m2 (1,100 dpm/100 cm2).
22        Note: If the relative amounts (ratios) were derived from data collected before 23        remediation, then the relative amounts need to be confirmed or verified after 24        remediation but before the FSS.
25 4.12.2.4 Unity Rule DCGL for Radionuclides with Unrelated Concentrations 26 For a given survey unit, data from previous surveys yield the radionuclide concentrations.
27
* Mean 60Co concentration = 41 +/- 32 (1) Bq/kg.
28
* Mean 137Cs concentration = 188 +/- 153 (1) Bq/kg.
29 The DCGLW values for 60Co and 137Cs are 130 Bq/kg (3.6 pCi/g) and 410 Bq/kg (11 pCi/g),
30 respectively. Since the concentrations of the two radionuclides appear to be unrelated in the 31 survey unit, the surrogate approach cannot be employed.
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MARSSIM                                                            Considerations for Planning Surveys 1 The weighted sum (calculated using Equation (4-12)) is CCo-60          CCs-137      41 Bqkg 188 Bqkg 2                    T=              +              =            +            = 0.77 DCGLCo-60 DCGLCs-137 130 Bqkg 410 Bqkg 3 The standard deviation of the weighted sum (calculated using Equation 4-13) is 2                2                2                2 4          (T)= (CCo-60 )  +  (CCs-137 )  = 32 Bqkg  + 153 Bqkg = 0.45 DCGLCo-60        DCGLCs-137          130 Bqkg    410 Bqkg 5 The weighted sum would be reported as 0.77 +/- 0.45 (1). This weighted sum and standard 6 deviation can be used to determine the number of samples required for FSS based on the 7 statistical tests chose by the design team. See the example in Section 4.12.4.
8 4.12.3 Required Number of Samples for a Single Radionuclide 9 See Sections 5.3.3 and 5.3.4 for detailed discussions on determining the required number of 10 data points for the WRS and Sign tests.
11 4.12.3.1 WRS Test 12 In this example the following data 8 were collected for the survey unit and reference area. Under 13 consideration are a single radionuclide that is present in the background and a single survey 14 unit. This process would be repeated for each survey unit and reference area combination.
15 Because the actual activity units are irrelevant to the example, they will be omitted.
16 Data from a post-remediation survey are shown in Table 4.3 below:
17 Table 4.3: Sample Data from a Post-Remediation Survey Reference Area              Survey Unit            Difference Mean =              38.8                    189.8                151.1 Median =              38.0                    188.0                150.0
              =              6.6                      8.1                  NA 18 The DCGL of concern is 160. The design team settled on alpha of 0.05 and beta of 0.10.
19 To determine the appropriate number of measurements, the relative shift must be calculated 20 using Equation (4-17):
DCGL  LBGR Relative Shift =                                                  (4-17) 21 22 The LBGR is often set at the expected median concentration of the radionuclide. However, in 23 our example the mean is higher than the median. Because it is conservative to set the LBGR at 8 This example is based on data presented in NRC (1998a).
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Considerations for Planning Surveys                                                                          MARSSIM 1 the higher value 9 (i.e., the expected mean) and to choose the larger value for  for the reference 2 area or survey unit, that is what the design team does using Equation (4-17):
160  151.1 3                                        Relative Shift =                      = 1.1 8.1 4 Referring to Table 5.2, we see that the recommended number of measurements (N/2) is 22 5 (given an alpha of 0.05 and beta of 0.10). 10 This is the number of samples that must be 6 collected in both the reference area and survey unit, for a total of 44 measurements. Also, this 7 number accounts for missing or unusable data. The simplest approach is to assign half of those 8 points to the survey unit and half to the reference area.
9 4.12.3.2 Sign Test 10 In this example, the following data were collected for the survey unit and reference area. Under 11 consideration are a single radionuclide that is not present in the background or present an 12 insignificant fraction of the DCGLW and a single survey unit. The activity levels are compared 13 directly to the DCGL. This process would be repeated for each survey unit. Because the actual 14 activity units are irrelevant to the example, they will be omitted.
15 Data from a post-remediation survey are shown in Table 4.4 below:
16 Table 4.4: Sample Data from a Post-Remediation Survey Survey Unit Mean =              10.9 Median =              11.5
              =              3.3 17 The DCGL of concern is 16. The design team settled on alpha of 0.05 and beta of 0.05.
18 To determine the appropriate number of measurements, the relative shift must be calculated 19 using Equation (4-17):
DCGL  LBGR 20                                        Relative Shift =
21 The LBGR is often set at the expected median concentration of the radionuclide. Because it is 22 conservative to set the LBGR at the higher of the mean or median, the median is used (see 23 Equation (4-17)):
16  11.5 24                                        Relative Shift =                    = 1.4 3.3 25 Referring to Table 5.2, we see that the required number of measurements (N) is 20 (given the 26 alpha of 0.05 and beta of 0.05). This number accounts for missing or unusable data.
9 Larger vales for the LBGR and  lead to a smaller relative shift that, in turn, leads to a larger number of required measurements.
10 Using the median value results in a relative shift of 1.2 and an N/2 value of 19.
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MARSSIM                                                                          Considerations for Planning Surveys 1 4.12.4 Required Number of Samples for the Multiple Radionuclides 2 See Sections 5.3.3-5.3.4 for detailed discussions on determining the required number of data 3 points for the WRS and Sign tests.
4 4.12.4.1 Applying the Unity Rule 5 A design team is tasked with classifying a survey unit according to the potential for 6 contamination and determining the appropriate number of soil samples to take during the FSS.
7 The contaminants are cobalt-60 (60Co) and cesium-137 (137Cs). The DCGLW values are 8
* DCGLW,Co-60: 130 Bq/kg (3.5 pCi/g) 9
* DCGLW,Cs-137: 410 Bq/kg (11 pCi/g) 10 During the DQO process and with approval of the regulator, the acceptable probability of a 11 Type I error 11 () is set to 0.05, and the acceptable probability of a Type II error 12 () set to 0.10.
12 Because compliance must be demonstrated for more than one radionuclide, and each 13 radionuclide will be measured separately, the unity rule will be used, wherein the concentration 14 of each contaminant is normalized to (divided by) its DCGLW. When this is done, the collective 15 concentration of the multiple radionuclides is expressed as the weighted sum of ratios (T) or 16 sum of the ratios (SOR). See Section 4.5.3.5 for details on the SOR.
17 The following data, obtained earlier during the characterization survey, are assumed to be 18 representative of the existing conditions in the survey unit. The data from the characterization 19 survey are shown in Table 4.5.
20 Sign test 21 Although 137Cs is in the background, it is present at such a low concentration 13 relative to the 22 DCGL that the planning team decides to swallow background and use the Sign test. 14 23 Classification and General Observations 24 Both the mean (0.78) and median 15 (0.66) of the SOR are less than 1. This indicates that the 25 survey unit might comply with the release criteria without further remediation. That the mean 26 and median differ indicates that the measurements might not be normally distributed. This 27 supports our decision to analyze the FSS data with a nonparametric test (Sign test).
28 That the value of the SORs for several samples (1, 4, 5, and 9) exceed 1 indicates that this 29 should be considered a Class 1 survey unit. Recall from the discussion of a Class 1 area that 11 This is the probability that the statistical test will indicate that the survey unit meets the release criteria when, in fact, it does not.
12 This is the probability that the statistical test will indicate that the survey unit does not meet the release criteria when, in fact, it does.
13 Cesium-137 appears in background soil at a concentration of about 37 Bq/kg (1 pCi/g).
14 The Sign test is a statistical test to demonstrate compliance with the release criteria when the radionuclide of concern is not present in background.
15 The median is the middle value of the data set when the number of data points is odd, and it is the average of the two middle values when the number of data points is even. Thus, 50 percent of the data points are above the median, and 50 percent are below the median.
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Considerations for Planning Surveys                                                                    MARSSIM 1 Table 4.5: Sample Results for Unity Rule Example Concentration Normalized Concentration Sample              (Bq/kg)                                                      Ta CCo-60        CCs-137        (C/DCGL)Co-60      (C/DCGL)Cs-137 1        104            308              0.80              0.74          1.54 2          33              78              0.25              0.19          0.45 3          30            185              0.23              0.45          0.69 4          41            322              0.32              0.79          1.11 5          78            525              0.60              1.28          1.89 6          26              70              0.20              0.17          0.38 7            4              44              0.03              0.11          0.14 8            0            -11              0.00              -0.03        -0.03 9          59            229              0.45              0.56          1.02 10          37            137              0.28              0.33          0.62 Mean          41            188              0.32              0.46          0.78 Median        35            161              0.27              0.39          0.66 Sigma (Bq/kg)                      Normalized Sigma Sample                                                                            Ta CCo-60        CCs-137        (/DCGL)Co-60      (/DCGL)Cs-137 N/A          32            162              0.25              0.39        N/A 2 Abbreviations: Bq = becquerel; kg = kilogram; DCGL = defined concentration guideline level; T = weighted sum of 3 ratios (see Equation 4-12).
4 a To be conservative, all the ratios in the table have been rounded up.
5 areas containing residual radioactive material in excess of the DCGLW prior to remediation 6 should be classified as Class 1 areas. (See Section 4.6.1.) In this example, the survey unit has 7 several individual locations where SOR exceeds 1, which is the unity rule DCGL. However, this 8 does not mean that the survey unit fails to meet the release criteria.
9 Determining the Appropriate Number of Systematic Samples 10 To determine the appropriate number of soil samples, we must calculate the relative shift using 11 Equation (4-17):
DCGL  LBGR 12                                          Relative Shift =
13 Because we have two radionuclides (60Co and 137Cs), the unity rule is used, wherein the 14 concentration of each radionuclide is divided by its DCGL. When this is done, the DCGL for the 15 combined radionuclides effectively becomes 1, as shown in Equation (4-18):
1  LBGR                                        (4-18)
Relative Shift =
16 The LBGR is often set at the expected median concentration of the contaminant. However, in 17 our example the mean is higher than the median. Because it is conservative to set the LBGR at 18 the higher value (i.e., the expected mean), that is what we will do.
19 Given the fact that we have multiple contaminants, we divide the expected mean concentration 20 of each radionuclide by its DCGL and use T or the SOR as our LBGR (Equation (4-12)):
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MARSSIM                                                          Considerations for Planning Surveys Expected Mean Concentration                  Expected Mean Concentration 1    LBGR =                                              +
DCGL                Co-60 DCGL                  Cs-137 41 Bq/kg    188 Bq/kg 2            =            +
130 Bq/kg 410 Bq/kg 3            = 0.32 + 0.46 4            = 0.78 5 Using Equation (4-18), the relative shift calculation then becomes 1  0.78 6                                        Relative Shift =
7 Using Equation (4-13), The combined sigma () for 60Co and 137Cs using data from Table 4.5 8 on previous page is 2                2 9                                    =                +
DCGL Co-60        DCGL Cs-137 10                                  = (0.25)2 + (0.39)2 11                                  = 0.47 12 The relative shift is then determined as follows, using Equation (4-18):
1  0.78 13                                    Relative Shift =            = 0.47 0.47 14 Note that the relative shift and sigma have the same value (0.47), which is a coincidence.
15 Referring to Table 5.3, we see that the recommended number of samples is somewhere 16 between 71 and 107 (given the alpha of 0.05 and beta of 0.10). When the relative shift falls 17 between the values on two lines on Table 5.3, the number of samples can be conservatively 18 estimated by using the number of samples corresponding to the smaller value of the relative 19 shift. For this example, the number of required samples would be 107.
20 4.12.5 Instrument Efficiencies 21 The instrument efficiency ( ) is defined as the ratio of the net count rate of the instrument to the 22 surface emission rate of a source for a specified geometry. The surface emission rate is defined 23 as the number of particles of a given type above a given energy emerging from the front face of 24 the source per unit time. The surface emission rate is the 2 particle fluence that embodies both 25 the absorption and scattering processes that effect the radiation emitted from the source. Thus, 26 the instrument efficiency is determined by the ratio of the net count rate and the surface 27 emission rate.
28 The source efficiency ( ) is defined as the ratio of the number of particles of a given type 29 emerging from the front face of a source to the number of particles of the same type created or 30 released within the source per unit time. The source efficiency takes into account the increased 31 particle emission due to backscatter effects, as well as the decreased particle emission due to 32 self-absorption losses. For an ideal source (i.e., no backscatter or self-absorption), the value of 33 the source efficiency is 0.5. Many real sources will exhibit values less than 0.5, although values 34 greater than 0.5 are possible, depending on the relative importance of the absorption and 35 backscatter processes.
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Considerations for Planning Surveys                                                                  MARSSIM 1 For surface activity measurements, the product of the instrument and surface efficiencies is the 2 total efficiency of the instrument ( ). The total efficiency is the net count rate of the instrument 3 divided by the total (4) emission rate in a specified geometry. It is usually the efficiency of 4 ultimate interest when planning FSSs.
5 4.12.5.1 Multiple Radionuclides 6 Whatever approach is used to assess multiple radionuclides, the FSS design team needs to 7 account for different instrument responses to the radionuclides of concern. It is important to use 8 an appropriately weighted total efficiency to convert from instrument counts to activity units. This 9 most frequently arises when measuring surface activity. When multiple radionuclides are being 10 measured with the same instrument, a weighted efficiency must be used. Starting with the unity 11 rule in its most general form (Equation (4-1)), the total number of counts is simply sum of the 12 counts from each radionuclide  present:
n Total Number of Counts = ATotal t =  Aj s,j i,j                    (4-19) j=1 13 where 14
* Total is the total activity of the  radionuclides.
15
* is the activity of the th radionuclide.
16 *    , is the source efficiency of the th radionuclide.
17 *    , is the instrument efficiency of the th radionuclide.
18 If the fraction  of each radionuclide in the mix is known, then, as shown in Equation (4-20),
ATotal  = ATotal  , ,                  (4-20)
                                                            =1 19 Dividing both sides by Total yields the total efficiency for the mixture, as shown in 20 Equation (4-21):
n
                                                      =  , ,                        (4-21) j=1 21 The example below illustrates the calculation of a weighted total efficiency for two radionuclides 22 with different instrument efficiencies.
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MARSSIM                                                                                Considerations for Planning Surveys 1 Consider a site contaminated with cesium-137 (137Cs) and strontium/yttrium-90 (90Sr/Y), with 2 137 Cs representing 60 percent of the total activity. Therefore, the relative fractions are 0.6 for 3 137 Cs and 0.4 for 90Sr/Y. The source efficiency for both 137Cs and 90Sr/Y is 0.5. The 4 corresponding instrument efficiencies for 137Cs and 90Sr/Y are determined to be 0.38 and 0.45, 5 respectively.
6 The total efficiency can be calculated using Equation (4-21):
7                                    = Cs ,Cs ,Cs + Sr/Y ,Sr/Y ,Sr/Y 8                                        = (0.6)(0.5)(0.38) + (0.4)(0.5)(0.45) 9                                        = 0.20 10 Alternatively, the total efficiencies for each radionuclide can be calculated by multiplying the 11 surface efficiency by the instrument efficiency, as shown in the equations below, modified from 12 Equation (4-21):
13                                  ,Cs = ,Cs x ,Cs = (0.5)(0.38) = 0.19 14                              ,Sr/Y = ,Sr/Y x ,Sr/Y = (0.5)(0.45) = 0.22 15 The weighted total efficiency can then be calculated as follows using equations modified from 16 Equation (4-21):
17                                          = Cs ,Cs + Sr/Y ,Sr/Y 18                                              = (0.6)(0.19) + (0.4)(0.22) 19                                              = 0.20 20 The weighted total efficiency is 0.20, or 20 percent.
21 When calculating the weighted total efficiency, one must account for the assumptions underlying 22 the corresponding DCGL, particularly the relative ratios of the radionuclides present. In this 23 case, the relative ratio of 137Cs and 90Sr/Y is needed to calculate the weighted total efficiency.
24 This can be important when dealing with the naturally occurring radionuclide chains (e.g., 226Ra 25 and progeny). The state of secular equilibrium (disequilibrium) would need to be accounted for 26 in determining the weighted total efficiency. An example of calculating the total weighted 27 efficiency for a mixture of radionuclides is shown in Section 4.12.6.
28 This weighted efficiency discussion addresses considerations for fractional activity. However, 29 more complex situations may be encountered, which must consider things such as radiation 30 emission intensities and branching ratios of decay chains. MARSAME and NUREG-1507 31 provide some additional examples of these more complex situations.
32 4.12.6 Data Conversion 33 This example illustrates the data conversion process along with another weighed total efficiency 34 calculation. Additional details are provided in Section 6.7.
35 A radionuclide laboratory is being decommissioned. Options are being considered for the FSS 36 of surfaces in the laboratory. The following radionuclide information is given in Table 4.6:
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Considerations for Planning Surveys                                                                  MARSSIM 1 Table 4.6: Sample Radionuclide Information DCGLW Radionuclide                                                      Relative Fraction Bq m-2            dpm (100 cm2)-1 14C                    5.77x106                3.46x106                    0.12 63Ni                  2.72x106                1.63x106                    0.18 99Tc                  1.95x106                1.17x106                    0.40 204Tl                  1.33x104                8.00x103                    0.02 90Sr/Y                1.30x104                7.78x103                    0.13 106Ru/Rh              3.98x104                2.39x104                    0.15 2 Abbreviations: DCGLW = derived concentration guideline level determined for a wide area; Bq = Becquerels; m =
3 meters; dpm = decays per minute; cm = centimeters.
4 Because the relative ratios are well known, were determined through the DQO process, and 5 were approved by the regulatory agency, gross beta activity measurements will be used to 6 determine compliance with the release criterion for this survey. The gross activity DCGLW can 7 be determined from Equation (4-10).
1 DCGLgross =
0.18          0.12          0.40          0.02          0.13        0.15
                                    +            +              +            +            +
2.72x106 5.77x106 1.95x106 1.33x104 1.30x104 3.98x104
    = 6.42 x104 Bq m-2 (3.85 x104 dpm (100 cm2)-1).
8 It has been decided to use a gas-flow proportional counter with a physical probe area of 9 126 cm2 (0.0126 m2) in  particle-only mode for the survey. The design team has determined 10 the following total efficiencies for the detector (Table 4.7):
11 Table 4.7: Sample Efficiencies for a Detector Source        Instrument            Total          Relative          Weighted Radionuclide        Efficiency      Efficiency        Efficiency        Fraction          Efficiency 14C                      0.25            0.16              0.04              0.12              0.0048 63Ni                    0.25            0.00              0.00              0.18              0.000 99Tc                    0.25            0.64              0.16              0.40              0.064 204Tl                    0.50            0.58              0.29              0.02              0.0058 90Sr/Y                  0.50            0.72              0.36              0.13              0.047 106Ru/Rh                0.50            1.10              0.55              0.15              0.082 Total =        1.00              0.20 12 In general, the output of the counter is a gross counting rate or integrated counts in a set 13 counting interval. The relationship between the counters output and surface activity (As) 14 concentration is given by Equation 6-19:
Cs t s 15                                                  As =
t xW 16 where Cs is the integrated net counts recorded by the instrument; t s is the time period over 17 which the counts were recorded;  is the total efficiency of the instrument in counts per 18 disintegration, effectively the product of the instrument efficiency ( ) and the source efficiency NUREG-1575, Revision 2                                4-62                                            May 2020 DRAFT FOR PUBLIC COMMENT                                                          DO NOT CITE OR QUOTE
 
MARSSIM                                                                Considerations for Planning Surveys 1 ( ); and  is the physical probe area. To account for background, Equation (4-22) (a slightly 2 modified form of Equation 6-20) is used:
Cs+bt s - Cb t b Cs t s      Rnet As =                      =          =                                  (4-22) t xW            t xW t xW 3
4 where Cb is the background counts 16 recorded by the instrument, t b is the time period over 5 which the background counts were recorded, 17 and Rnet is the net counting rate. The units for t s ,
6 t b, and W depend on the desired units for the FSS.
7 For this example, surface activity measurements are being made on drywall. Consider the 8 following data for one measurement location:
9
* Cb = 1,626 counts 10
* t b = 5 minutes 11
* Cs = 1,210 counts 12
* t s = 1 minute 13 The net counting rate is calculated using Equation (4-23):
Rnet = Cs+b ts - Cb tb                                    (4-23) 1,210 counts 1,626 counts 14                                          =                  -
1 minute        5 minutes 15                                                = (1,210 - 325.2) cpm 16                                                      = 884.8 cpm 17 The net counting rate can be converted to the surface activity concentration, as shown below, 18 using Equation (4-22):
Rnet 19                                                      As =
T xW 884.8 cpm 20                                                =
0.20 (c/d)x0.0126 m2 21                                                  = 3.51x105 dpm/m2 16 Background measurements should be made on uncontaminated material similar in composition to the material at the measurement location.
17 The sample and background counting intervals can be different, depending on the desired MDC. See Section 6.3 and the professional literature for more discussion.
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Considerations for Planning Surveys                                                        MARSSIM 1 In general, either SI (Bq/m2) or conventional (dpm/100 cm2) units are desired. For SI units, the 2 conversion is straightforward, because 60 dpm is equivalent to 1 Bq (see Equation (4-22)):
dpm          1 Bq 3                                  As = 3.51x 105                x m2    60 dpm 4                                                = 5.83x103 Bq/m2 5 The conversion to conventional units is shown below, using Equation (4-22):
5  dpm          0.01 m2 6                                  As = 3.51x10                  x m2    100 cm2 7                                            = 3.51x103 dpm/100 cm2 8 The FSS design team should determine the desired units during the planning phase. After the 9 desired units are chosen, the design team can create spreadsheets or other methods of 10 analyzing the raw counting data to streamline the process. Similarly, any action or investigation 11 levels chosen by the design team should be converted into the proper units. This process needs 12 to be performed for each field measurement instrument and technique.
13 For example, if it is determined that units of dpm/100 cm2 will be used, then the physical probe 14 area should be measured in cm2, and the following equation (Equation (4-24)) can be used for 15 each instrument used:
Cs t s - Cb t b          Rnet As =                      =                                      (4-24) t x W100        t x W100 16 17 where t s and t b are recorded in minutes (Rnet is expressed in cpm), and W is recorded in square 18 centimeters instead of square meters.
19 For this example, the equation is shown below (see Equation (4-22)):
884.8 cpm 20                                          As =
0.20 (c/d)x 126100 21                                            = 3.51x103 dpm/100 cm2 22 The result is the same as in the earlier example, as expected.
23 Additionally, action and investigation levels and the DCGL can be converted to detector outputs 24 to facilitate timely actions (i.e., expressing action levels in terms of net counting rate might allow 25 the field survey team to alert supervisors about measurements exceeding action levels in near-26 real time). In this case, the net counting rate corresponding to an action level can be expressed 27 by the following equation (Equation (4-25)):
RAL net = t x W x As AL (4-25)
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MARSSIM                                                        Considerations for Planning Surveys 1
2 Suppose the design team set an action level at 10 percent of the DCGLgross. The net counting 3 rate corresponding to this value is found as shown below, keeping in mind that 1 Bq is 4 equivalent to 1 disintegration per second (dps), using (Equation (4-25)):
3 5                  RAL                    2                  2 net = 0.20 x 0.0126 m x6.42x10 Bq/m  = 16.2 cps = 971 cpm 6 Thus, any net count exceeding about 970 counts per minute (cpm) would be flagged for 7 investigation. If background rates are relatively constant, an action level can be expressed as a 8 gross counting rate, as well.
9 4.12.7 Example of a Deviation from a Recommended Statistical Test 10 Consider the case of a survey unit that contains many different surfaces with potentially different 11 backgrounds (e.g., drywall panels, concrete floor, glass windows, metal doors, wood trim, and 12 plastic fixtures) and gross activity measurements are being considered. In this case, MARSSIM 13 recommends the use of the WRS test when gross activity measurements are used; however, 14 the use of the WRS test might require several survey and associated reference units, resulting 15 in an inordinately large number of measurements. Furthermore, it is not appropriate to make 16 each material a separate survey unit because the dose modeling is based on the dose from the 17 room as a whole and because a large number of survey units in a room would require an 18 inappropriate number of samples (NRC 2006). In this situation, the design team should use the 19 DQO process and determine the best approach.
20 Instead of attempting to use the WRS test and multiple reference units, the design team might 21 investigate the materials to determine if material-specific backgrounds are needed or whether 22 materials with similar background could be grouped and considered as a unit. If this is done, it 23 might be acceptable to perform a one-sample test (Sign test) on the difference between the 24 paired measurements from the survey unit and from the appropriate reference material 25 (NRC 2006). Chapter 2 of NUREG-1505 (NRC 1998a) contains details on this method.
26 In addition to the alternative statistical approach discussed above, the NRC (2006) discusses 27 two additional approaches to resolve this issue. First, if the materials in the survey unit have 28 substantially different backgrounds, then a reference unit containing a similar mix of material 29 might be used, and the WRS test can then be applied. Second, if the materials in the survey unit 30 have similar backgrounds, or if one material predominates, then a reference background from a 31 single material might suffice. See NRC (2006) for more details.
32 The design team should use the DQO process to investigate any deviations from usual methods 33 and get approval from the regulatory agency before executing the FSS.
34 4.12.8 Release Criteria for Discrete Radioactive Particles 35 With the installation in the mid- and late-1980s of very sensitive portal monitors, many nuclear 36 power plants detected residual radioactive material on individuals and their clothing, present as 37 smallusually microscopichighly radioactive particles having relatively high specific activity.
38 These particles became known as discrete radioactive particles and sometimes hot particles.
39 Discrete radioactive particles are small (usually on the order of millimeters or micrometers),
40 distinct, highly radioactive particles capable of delivering extremely high doses to a localized 41 area in a short period of time.
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Considerations for Planning Surveys                                                          MARSSIM 1 To prove compliance with requirements for discrete radioactive particles, some surveys have 2 used the MARSSIM EMC process (see Section 8.6.1); however, that process is not valid when 3 instrumentation dose-to-rate conversion factor modeling assumes a point source as opposed 4 to an area source or plane source. This violates the assumption inherent in the dose or risk 5 model of an activity concentration averaged over some definable area. Therefore, it is not 6 acceptable to use the MARSSIM EMC process when the distance to the detector is greater than 7 three times the longest dimension of the area of elevated activity, as represented by 8 Equation (4-26):
                                                    > 3                                          (4-26) 9 where  is the estimated longest dimension of the area of elevated activity, and  is the distance 10 to the detector.
11 To address discrete radioactive particles in surface soils or building surfaces 12
* Include discrete radioactive particles as a consideration during the DQO process for 13    MARSSIM surveys.
14
* When a regulatory agency sets requirements on the concentration of discrete radioactive 15    particles in a survey unit, use the DQO process to develop a survey to assess whether 16    requirements are met.
17
* When appropriate, apply ALARA by addressing discrete radioactive particles during the 18    RAS survey.
19
* If discrete radioactive particles do not contribute significantly to dose or risk at a site, it is a 20    reasonable assumption that they will not affect the outcome of a wide-area FSS. If an FSS 21    fails due to discrete radioactive particles, investigate the reasons for survey failure (see 22    Section 8.6.3).
23 4.12.9 Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA) Sites 24 At UMTRCA sites, the U.S. Environmental Protection Agencys Health and Environmental 25 Protection Standards for Uranium and Thorium Mill Tailings (in 40 CFR 192) are applicable.
26 However, the technical requirements in these standards are not always consistent with some of 27 the recommendations in MARSSIM. Specifically, the soil cleanup standards for 226Ra and 228Ra 28 are specified as averages over an area of 100 m2. (In the 40 CFR 192 rulemaking, an averaging 29 area of 100 m2 was used as a reasonable footprint for a home. One goal of the 40 CFR 192 30 standards was to protect future homes from indoor radon, and the specified averaging area was 31 a component implemented for the protection of health.) The rules at 40 CFR 192 do not 32 establish specific requirements for small areas of elevated radioactive material. At sites where 33 the uranium or thorium mill tailings standards are applicable, the following approach for FSSs is 34 acceptable:
35
* A survey unit of no greater than 100 m2 sections of land should be used, consistent with the 36    regulatory standards.
37
* The systematic sampling for performance of statistical tests, normally required under the 38    MARSSIM approach, is not required for each survey unit. Instead, compliance with the 39    standard can be demonstrated through the analysis of soil samples or composite soil 40    samples from each survey unit in conjunction with gamma radiation scanning or in situ NUREG-1575, Revision 2                            4-66                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                    Considerations for Planning Surveys 1    gamma radiation measurements of each survey unit. When appropriate, gamma radiation 2    scanning or in situ measurements correlated to soil sampling may be used in place of soil 3    sampling.
4
* Survey units may be classified, as appropriate, and the percentage of the survey unit that is 5    scanned may be adjusted accordingly for Class 1, Class 2, or Class 3 survey units.
6
* EMC criteria for small elevated areas of activity may be developed but are not required for 7    the purposes of MARSSIM.
8 These minor modifications to the standard MARSSIM radiological survey approach are 9 acceptable for those sites to which the UMTRCA standards are applicable.
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MARSSIM                                                                            Survey Planning and Design 1                            5 SURVEY PLANNING AND DESIGN 2 5.1    Introduction 3 This chapter is intended to assist the user in planning radiological surveys with a particular 4 emphasis on conducting a final status survey (FSS), with the ultimate objective being to 5 demonstrate compliance with the derived concentration guideline levels (DCGLs). 1 The survey 6 types that make up the Radiation Survey and Site Investigation (RSSI) process include scoping, 7 characterization, remedial action support (RAS), and FSSs; depending on the regulatory 8 framework, the process may also include confirmatory or independent verification surveys.
9 Although the scoping, characterization, and RAS surveys have multiple objectives, this manual 10 focuses on those aspects related to supporting the FSS and demonstrating compliance with 11 DCGLs. In general, each of these survey types expands upon the data collected during the 12 previous survey (e.g., the characterization survey is planned with information collected during 13 the scoping survey) up through the FSS. The conduct and extent of scoping and 14 characterization surveys will depend on the available information from the Historical Site 15 Assessment (HSA) and site-specific conditions. The purpose of the FSS is to demonstrate that 16 the release criteria established by the regulatory agency have not been exceeded. This final 17 release objective should be kept in mind throughout the design and planning phases for each of 18 the other survey types. For example, scoping surveys may be designed to meet the objectives 19 of the FSS such that the scoping survey report is also the FSS report. The survey and analytical 20 procedures referenced in this chapter are described in Chapters 6-7 and Appendix H. An 21 example of an FSS, as described in Section 5.3, appears in Appendix A. In addition, example 22 checklists are provided for each type of survey to assist the user in obtaining the necessary 23 information for planning an FSS.
24 Scoping surveysused to augment the HSA and provide input to future survey designsand 25 survey unit characterization and classification are described in Section 5.2.1. Section 5.2.2 26 describes characterization surveys performed to determine the following: nature and extent of 27 residual radioactive material; potential remediation alternatives and technologies; the inputs to 28 pathway analysis and dose or risk assessment models; occupational and public health and 29 safety impacts; and inputs to the FSS design. RAS surveys, performed to support remedial 30 activities, update estimates of site-specific parameters used in FSS planning, and determine 31 when a site or survey unit is ready for an FSS are described in Section 5.2.3. Section 5.3 32 covers FSSs, which are performed to demonstrate that a site or survey unit meets the residual 33 radioactive material release criteria.
34 A flowchart diagram illustrating the Survey Planning and Design Process, broken up by survey 35 type, is provided in Figures 5.1-5.3.
1 MARSSIM uses the word should as a recommendation, not as a requirement. Each recommendation in this manual is not intended to be taken literally and applied at every site. MARSSIMs survey planning documentation will address how to apply the process on a site-specific basis.
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Survey Planning and Design                                                                  MARSSIM From Figure 3.1              Survey Objectives
: 1. Perform a preliminary hazard assessment
: 2. Support classification of all or part of the site as a Class 3 area
: 3. Evaluate whether survey plan can be optimized for use in characterization or Design Scoping Survey          final status survey Plan Using            4. Provide input to the characterization DQO Process              survey design.
Perform Reassess DQOs Scoping Survey No Are the DQOs                Validate Data and Satisfied?                Assess Data Quality Is There Sufficient                                To Figure Yes          Information to Support    No/Unknown                    5.2 Classification as Class 3?
Document Findings Supporting Class 3 Classification To Figure 5.3 1
2 Figure 5.1: The Scoping Survey Portion of the Radiation Survey and Site Investigation 3 Process NUREG-1575, Revision 2                          5-2                                          May 2020 DRAFT FOR PUBLIC COMMENT                                          DO NOT CITE OR QUOTE
 
MARSSIM                                                                                                      Survey Planning and Design From Figure 5.1 Survey Objectives
: 1. Determine the nature and extent of the residual radioactive material Design                          2. Evaluate remedial alternatives and Reassess DQOs                                    Characterization                        technologies Survey Plan Using                      3. Evaluate whether survey plan can be DQO Process                            used as the final status survey No                                                                            4. Provide input to the final status survey design Perform Are the DQOs Characterization Satisfied?
Survey Yes Validate Data Classify Areas as                                  and Assess Class 1, Class 2,                                  Data Quality or Class 3 Determine Remedial Alternative and Site-Specific DCGLs Is Area Class 1 or Class 2?
No              Remediate the Area Yes Yes Perform Remedial Action Support Survey Is Area Remediation Required?
Does the Remedial Action Support Survey Indicate          Yes the Remediation is Complete?
No        Reassess Remedial Alternative and Site-No Specific DCGLs Is From                  To Figure Reassessment of Figure                    5.3 Yes              Remedial Alternative and Site-Specific DCGLs                              5.3*
Necessary?
* The point where survey units that fail to demonstrate compliance in the final status survey in Figure 5.3 re-enter the process 1
2 Figure 5.2: The Characterization and Remedial Action Support Survey Portions of the 3 Radiation Survey and Site Investigation Process May 2020                                                                  5-3                                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                                        DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                                            MARSSIM From Figure 5.1 and Figure 5.2                                Survey Objectives
: 1. Select/verify survey unit classification
: 2. Demonstrate that the potential dose or risk from residual radioactive material is below the release criteria for each survey unit Design Final Status Survey                      3. Demonstrate that the potential dose Plan Using DQO Process                            from residual elevated areas is below the release criteria for each survey unit Perform Final Status                Perform Final Status                    Perform Final Status Survey for Class 1                  Survey for Class 2                    Survey for Class 3 Survey Units                        Survey Units                            Survey Units Reassess DQOs Validate Data Are the DQOs                                                                  Perform Additional No                                                    and Assess Satisfied?                                                                        Surveys Data Quality Yes                                                                              No Do Final Status Survey Is Additional Results Contain Residual No                              Remediation Radioactive Material Required?
Less than DCGLs?
Yes Yes To Figure Document Results in the Final 5.2*
Status Survey Report
* Connects with the Remedial Action Support Survey portion of the process in Figure 5.2 1
2 Figure 5.3: The Final Status Survey Portion of the Radiation Survey and Site Investigation 3 Process NUREG-1575, Revision 2                                          5-4                                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                                        DO NOT CITE OR QUOTE
 
MARSSIM                                                                  Survey Planning and Design 1 5.2    Preliminary Surveys 2 5.2.1    Scoping Surveys 3 If the data collected during the HSA indicate that a site or area is impacted, a scoping survey 4 may be performed. The objective of this survey is to augment the HSA for sites with potential 5 residual radioactive material. Specific objectives may include 6
* performing a preliminary risk assessment and providing data to complete the site 7      prioritization scoring process for Comprehensive Environmental Response, Compensation, 8      and Liability Act (CERCLA) and Resource Conservation and Recovery Act (RCRA) sites 9      only (EPA 1992c) 10
* providing input to the characterization survey design, if necessary 11
* supporting the classification of all or part of the site as a Class 3 area for planning the FSS 12
* obtaining an estimate of the variability in the residual radioactive material concentration for 13      the site 14
* identifying non-impacted areas that may be appropriate for reference areas and estimating 15      the variability in radionuclide concentrations when the radionuclide of interest is present in 16      background 17 A scoping survey is not a requirement if HSA information meets the needs for designing 18 subsequent surveys, including the FSS. Alternatively, scoping surveys and characterization 19 surveys may be combined, if one survey can be designed to meet the requirements of both 20 survey types. See Section 5.2.2 for a description of characterization surveys.
21 Scoping survey information about the general radiation levels at the site, including gross levels 22 of residual radioactive material on building surfaces and in environmental media, is needed 23 when conducting a preliminary risk assessment (as noted above for CERCLA and RCRA sites).
24 If unexpected conditions are identified that prevent the completion of the survey, the Multi-25 Agency Radiation Survey and Site Investigation Manual (MARSSIM) user should contact the 26 regulatory agency for further guidance. Sites that meet the National Contingency Plan (NCP) 27 criteria for a removal should be referred to the Superfund Removal program (EPA 1988b).
28 If the HSA indicates that residual radioactive material above release levels is likely, a scoping 29 survey could be performed to provide initial estimates of the level of effort for remediation and 30 information for planning a more detailed survey, such as a characterization survey. Not all 31 radiological parameters need to be assessed when planning for additional characterization, 32 because total surface activity or limited sample collection may be sufficient to meet the 33 objectives of the scoping survey.
34 Once a review of pertinent site history indicates that an area is impacted, the minimum survey 35 coverage at the site will include a Class 3 area FSS before the sites being released. For 36 scoping surveys with this objective, identifying radiological decision levels is necessary for 37 selecting instruments and procedures with the necessary instrument capabilities to demonstrate 38 compliance with the release criteria. A methodology for planning, conducting, and documenting 39 scoping surveys is described in the following sections.
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Survey Planning and Design                                                                MARSSIM 1 5.2.1.1 Survey Design 2 Planning a scoping survey involves reviewing the HSA for a site (Chapter 3). This process 3 considers available information concerning locations of spills or other releases of radioactive 4 material. Reviewing the radioactive materials license or similar documentation provides 5 information on the identity, locations, and general quantities of radioactive material used at the 6 site. This information helps determine which areas are likely to contain residual radioactive 7 material and, thus, areas where scoping survey activities will be concentrated. The information 8 may also identify one or more non-impacted areas as potential reference areas when 9 radionuclides of concern are present in background (Section 4.5). Following the review of the 10 HSA, appropriate DCGLs for the site are selected. The DCGLs may be adjusted later if a 11 determination is made to use site-specific information to support the development of DCGLs.
12 If residual radioactive material is identified during the scoping survey, the area may be classified 13 as Class 1 or Class 2 for FSS planning (refer to Section 4.6.1 for information on initial 14 classification), and a characterization survey is subsequently performed. For scoping surveys 15 that are designed to provide input for characterization surveys, measurements and sampling 16 may not be as comprehensive or performed to the same level of sensitivity necessary for FSSs.
17 The design of the scoping survey should be based on specific Data Quality Objectives (DQOs).
18 See Section 2.3.1 and Appendix D for the information to be collected.
19 For scoping surveys that potentially serve to release the site or portions of the site from further 20 consideration, the scoping survey design for the Class 3 area should consist of sampling based 21 on the HSA data, and professional judgment and must be consistent with the requirements for 22 an FSS. If residual radioactive material is not identified, it may be appropriate to characterize 23 the area as non-impacted. Refer to Section 5.3 for a description of FSSs. However, collecting 24 additional information during subsequent surveys (e.g., characterization surveys) may be 25 necessary to make a final determination as to area classification.
26 5.2.1.2 Conducting Surveys 27 Scoping survey activities performed for preliminary risk assessment or to provide input for 28 additional characterization include a limited amount of surface scanning, surface activity 29 measurements, and sample collection (smears, soil, water, vegetation, paint, building materials, 30 subsurface materials). In this case, scans, direct measurements, and samples are used to 31 examine areas likely to contain residual radioactive material. These activities are conducted 32 based on HSA data, preliminary investigation surveys, and professional judgment.
33 Background activity and radiation levels for the area should be determined, including direct 34 radiation levels on building surfaces and radionuclide concentrations in media. Survey locations 35 should be referenced to grid coordinates, if appropriate, or fixed site features. This may be 36 accomplished by establishing a reference coordinate system in the event that residual 37 radioactive material is detected above the DCGLs (Section 4.8.5). Samples collected as part of 38 a scoping survey should be maintained under custody from collection through analysis and 39 reporting to ensure the integrity of the results. Sample tracking may include use of a chain of 40 custody, which is the unbroken trail of accountability that ensures the physical security of 41 samples, data, and records (Section 7.8).
42 Scoping surveys that are expected to be used as Class 3 area FSSs should be designed 43 following the procedure in Section 5.3. Scoping surveys should also include judgment 44 measurements and sampling in areas likely to have accumulated residual radioactive material 45 (Section 5.3.9). However, when performing a scoping survey as a Class 3 FSS, judgment NUREG-1575, Revision 2                            5-6                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                                Survey Planning and Design 1 samples should not be used as part of the statistical sampling population utilized to make a 2 release decision on a site or survey unit.
3 5.2.1.3 Evaluating Survey Results 4 Survey data are converted to the same units as the DCGLs (Section 6.6). Identification of 5 potential radionuclides of concern at the site is performed using direct measurements or 6 laboratory analysis of samples. The data are compared to the appropriate regulatory DCGLs.
7 For scoping survey activities that provide an initial assessment of the radiological hazards at the 8 site or input for additional characterization, the survey data are used to identify locations and the 9 general extent of residual radioactive material. Scoping surveys that are expected to be used as 10 Class 3 area FSSs should follow the methodology presented in Chapter 8 to determine whether 11 the release criteria have been exceeded.
12 5.2.1.4 Documentation 13 How the results of the scoping survey are documented depends on the specific objectives of the 14 survey. For scoping surveys that provide additional information for characterization surveys, the 15 documentation should provide general information on the radiological status of the site. Survey 16 results should include identification of the potential radionuclides of concern (including the 17 methods used for radionuclide identification), general extent of residual radioactive material 18 (e.g., activity levels, area, and depth), and possibly even relative ratios of radionuclides to 19 facilitate DCGL application. A narrative report or a report in the form of a letter may suffice for 20 scoping survey data that is used to provide input for characterization surveys. Sites being 21 released from further consideration should provide a level of documentation consistent with FSS 22 reports (Section 5.3.11). Example 1 includes an illustration of a scoping survey checklist, 23 including survey design, conduct of the survey, and evaluation of survey results.
Example 1: Example Scoping Survey Checklist Survey Design
_____ Enumerate Data Quality Objectives (DQOs) and Measurement Quality Objectives (MQOs). State the objectives of the survey; survey instrumentation capabilities should be appropriate for the specified survey objectives. Document survey requirements in a project-specific Quality Assurance Project Plan (QAPP).
_____ Review the Historical Site Assessment (HSA) for the following:
_____ Operational history (e.g., problems, spills, releases, or notices of violation) and available documentation (e.g., radioactive materials license)
_____ Other available resourcessite personnel, former workers, residents, etc.
_____ Types and quantities of materials that were handled and where radioactive materials were stored, handled, moved, relocated, and disposed
_____ Release and migration pathways May 2020                                          5-7                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                MARSSIM
_____ Areas that are potentially affected and likely to contain residual radioactive material (Note: Survey activities will be concentrated in these areas.)
_____ Types and quantities of materials likely to remain onsiteconsider radioactive decay
_____ Select derived concentration guideline levels (DCGLs) for the site based on the HSA review. (It may be necessary to assume appropriate regulatory DCGLs in order to permit selection of survey methods and instrumentation for the expected radioactive material and quantities.)
Conducting Surveys
_____ Follow the survey design documented in the QAPP. Record deviations from the stated objectives or documented standard operating procedures, and document additional observations made when conducting the survey.
_____ Select instrumentation based on the specific DQOs and MQOs of the survey.
Consider instrumentation capabilities for the expected residual radioactive material and quantities.
_____ Determine background activity and radiation levels for the area; include direct radiation levels on building surfaces, radionuclide concentrations in media, and exposure rates.
_____ Record measurement and sample locations referenced to grid coordinates or fixed site features.
_____ For scoping surveys that are conducted as Class 3 area final status surveys (FSSs),
follow FSS procedure.
_____ Conduct scoping survey, which involves judgment measurements and sampling based on HSA results:
_____ Perform investigatory surface scanning.
_____ Conduct limited surface activity measurements.
_____ Perform limited sample collection (smears, soil, water, vegetation, paint, building materials, subsurface materials).
_____ Maintain sample tracking.
Evaluating Survey Results
_____ Compare survey results with the DQOs and MQOs.
_____ Identify radionuclides of concern.
_____ Identify impacted areas and the general extent of residual radioactive material.
_____ Estimate the variability in the residual radioactive material levels for the site.
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MARSSIM                                                                Survey Planning and Design
_____ Adjust DCGLs based on survey findings (the DCGLs initially selected may not be appropriate for the site).
_____ Determine the need for additional action (e.g., none, remediate, more surveys)
_____ Prepare report for regulatory agency (determine if letter report is sufficient).
1 5.2.2  Characterization Surveys 2 Characterization surveys may be performed to satisfy a number of specific objectives. Examples 3 of characterization survey objectives include 4
* determining the nature and extent of residual radioactive material 5
* evaluating remediation alternatives (e.g., unrestricted use, restricted use, onsite disposal, 6    off-site disposal, etc.)
7
* input to pathway analysis/dose or risk assessment models for determining site-specific 8    DCGLs (becquerel [Bq]/kilogram [kg], Bq/square meter [m2])
9
* estimating the occupational and public health and safety impacts during decommissioning 10
* evaluating remediation technologies 11
* providing input to FSS design 12
* meeting Remedial Investigation/Feasibility Study (RI/FS) requirements (under a CERCLA 13    program) or RCRA Facility Investigation/Corrective Measures Study (RFI/CMS) 14    requirements (under an RCRA program).
15 A characterization survey is not a requirement if HSA and scoping survey information meets the 16 needs for designing subsequent surveys, including FSSs. Alternatively, scoping surveys and 17 characterization surveys may be combined if one survey can be designed to meet the 18 requirements of both survey types. The scope of this manual precludes detailed discussions of 19 characterization survey design for each of these objectives; therefore, the user should consult 20 other references for specific characterization survey objectives not covered. For example, the 21 Decommissioning Handbook (DOE 1994a) is a good reference for characterization objectives 22 that are concerned with evaluating remediation technologies or unrestricted/restricted use 23 alternatives. Other references (e.g., Abelquist 2014; EPA 1988b, 2006c; NRC 1994a) should be 24 consulted for planning decommissioning actions, including remediation techniques, projected 25 schedules, costs, waste volumes, and health and safety considerations during remedial action.
26 Also, the types of characterization data needed to support risk or dose modeling should be 27 determined from the specific modeling code documentation. This manual concentrates on 28 providing information for the FSS design, with limited coverage on determining the specific 29 nature and extent of residual radioactive material. The specific objectives for providing 30 information to the FSS design include 31
* estimating the projected radiological status at the time of the FSS, in terms of radionuclides 32    present, concentration ranges and variances, spatial distribution, etc.
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Survey Planning and Design                                                                  MARSSIM 1
* evaluating potential reference areas to be used for background measurements, if necessary 2
* reevaluating the initial classification of survey units 3
* selecting instrumentation based on the necessary Measurement Quality Objectives (MQOs) 4
* establishing acceptable Type I and Type II errors with the regulatory agency (Appendix D 5    provides information on establishing acceptable decision error rates.)
6 Many of these objectives are satisfied by determining the specific nature and extent of residual 7 radioactive material in structures, residues, and environmental media. Additional detail on the 8 performance of characterization surveys designed to determine the general extent of residual 9 radioactive material can be found in the U.S. Nuclear Regulatory Commissions (NRC's) 10 Consolidated Decommissioning Guidance (NUREG-1757) (NRC 2006), Performance and 11 Documentation of Radiological Surveys (HPS/ANSI 13.49-2001) (HPS 2001), Characterization 12 in Support of Decommissioning Using the Data Quality Objectives Process (HPS/ANSI N13.59) 13 (HPS 2008), and the U.S. Environmental Protection Agencys (EPAs) RI/FS guidance (EPA 14 1988b; EPA 1993b).
15 Results of the characterization survey should include 16
* the identification and distribution of residual radioactive material in buildings, structures, and 17    other site facilities 18
* the concentration and distribution of radionuclides of concern in surface and subsurface 19    soils 20
* the distribution and concentration of residual radioactive material in surface water, ground 21    water, and sediments 22
* the distribution and concentration of radionuclides of concern in other impacted media, such 23    as vegetation or paint 24 The characterization should include sufficient information on the physical characteristics of the 25 site, including surface features, meteorology and climatology, surface water hydrology, geology, 26 demography and land use, and hydrogeology. This survey should also address environmental 27 conditions that could affect the rate and direction of radionuclide transport in the environment, 28 depending on the extent of residual radioactive material identified above.
29 The following sections describe a method for planning, conducting, and documenting 30 characterization surveys. Alternative methodologies may also be acceptable to the regulatory 31 agencies.
32 5.2.2.1 Survey Design 33 The design of the site characterization survey is based on the specific DQOs for the information 34 to be collected, and it is planned using the HSA and scoping survey results. The DQO process 35 ensures that adequate data with sufficient quality are collected for the purpose of 36 characterization. The site characterization process typically begins with a review of the HSA, 37 which includes available information on site description, operational history, and the type and 38 extent of residual radioactive material (from the scoping survey, if performed). The site 39 description, or conceptual site model as first developed in Section 3.6.4, consists of the general 40 area, dimensions, and locations of affected areas on the site. A site map should show site NUREG-1575, Revision 2                            5-10                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                  Survey Planning and Design 1 boundaries, roads, hydrogeological features, major structures, and other features that could 2 affect decommissioning activities. When available, Global Positioning System (GPS) 3 coordinates should be recorded for major features.
4 The operational history includes records of site conditions before operational activities, 5 operational activities of the facility, effluents and on-site disposal, and significant incidents 6 including spills or other unusual occurrencesinvolving the spread of residual radioactive 7 material around the site and on areas previously released from radiological controls. This review 8 should include other available resources, such as site personnel, former workers, residents, etc.
9 Historic aerial photographs and site location maps may be particularly useful in identifying 10 potential areas of residual radioactive material.
11 The types and quantities of materials that were handled and the locations and disposition of 12 radioactive materials should be reviewed using available documentation (e.g., the radioactive 13 materials license). Release and migration pathways of radionuclides should be identified, as 14 well as areas that are potentially affected and are likely to contain residual radioactive material.
15 The types and quantities of materials likely to remain onsite, considering radioactive decay, 16 should be determined.
17 The characterization survey should clearly identify those portions of the site (e.g., soil, 18 structures, and water) that have been affected by site activities and potentially contain residual 19 radioactive material. The survey should also identify the portions of the site that have not been 20 affected by these activities. In some cases where no remediation is anticipated, results of the 21 characterization survey may indicate compliance with DCGLs established by the regulatory 22 agency. When planning for the potential use of characterization survey data as part of the FSS, 23 the characterization data must be of sufficient quality and quantity for that use (see 24 Section 5.3).
25 Several processes are likely to occur in conjunction with characterization. These include 26 considering and evaluating remediation alternatives and calculating site-specific DCGLs.
27 The survey should also provide information on variability in the radionuclide distribution in the 28 survey area. The radionuclide variability in each survey unit contributes to determining the 29 number of data points based on the statistical tests used during the FSS (Sections 5.3.3-5.3.4) 30 and the required scan coverage for Class 2 areas. Additionally, characterization data may be 31 used to justify reclassification for some survey units (e.g., from Class 1 to Class 2).
32 In some cases, judgment sampling is the most appropriate for meeting the data needs.
33 Judgment sampling includes measurements performed at locations selected using professional 34 judgment based on unusual appearance, location relative to known contaminated areas, high 35 potential for residual radioactive material, general supplemental information, etc. Examples of 36 situations in which judgment sampling may be the most appropriate include those where 37 residual radioactive material is isolated to locations that can be defined by individual 38 measurements, or in which biased results will provide the data from the areas of highest 39 suspected concentration of residual radioactive material. It should be understood, however, that 40 use of a judgment characterization survey will produce data that is considered biased and which 41 can generally only be used to draw conclusions about individual samples or specific locations 42 rather than provide quantifiable estimates about a larger aggregate population. As a result, May 2020                                          5-11                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                MARSSIM 1 averages of judgment samples (i.e., biased) should not be used to determine the mean 2 concentration of the residual radioactive material in the survey unit.
3 For those characterization survey objectives that require statistical evaluation of the data, the 4 sampling plan should be designed to produce unbiased data. Unbiased sampling makes use of 5 random sample selection, whereby each sample has an equal probability of being selected.
6 Unbiased data can be used to provide a measure of the population characteristics, such as the 7 average or mean radioactive material concentration and variance on that mean. One example of 8 when unbiased sample data may be required is the use of a data set in assessing compliance 9 with dose- or risk-based criteria. Most human health risk assessment protocols (e.g., EPA 10 1989d) require the computation of a mean and upper confidence limit (UCL) as the best 11 measure of residual radioactive material in identifying excess lifetime cancer risk or radiation 12 dose to a target population (EPA 2002b; 2006b).
13 The characterization survey may be used as an FSS for Class 3 areas under the following 14 conditions:
15
* The characterization survey was planned as an FSS.
16
* Site or survey unit conditions warrant the use of the characterization survey as the FSS.
17
* Only randomly selected samples are utilized as part of the statistical evaluation of the site or 18      survey unit. Any judgment samples collected may not be used as part of the statistical 19      sample count or as part of the statistical evaluation of results.
20 It may be also appropriate to combine the principles of judgment and unbiased sampling 21 strategies in designing a sample plan that provides the most representative data but also meets 22 all of the DQOs.
23 Note that because of site-specific characteristics of residual radioactive material, performing all 24 types of measurements described here may not be relevant at every site. For example, detailed 25 characterization data may not be needed for areas with residual radioactive material well above 26 the DCGLs that clearly require remediation. Judgment should be used in determining the types 27 of characterization information needed to provide an appropriate basis for remediation 28 decisions.
29 A number of software programs have been developed over the years to facilitate the design of 30 surveys, an example of which is Visual Sample Plan, developed by the Pacific Northwest 31 National Laboratory. These software programs can perform calculations to determine the 32 number of locations where measurements should be made or where samples should be 33 collected.
34 5.2.2.2 Conducting Surveys 35 Characterization survey activities often involve the detailed assessment of various types of 36 building and environmental media, including building surfaces, surface and subsurface soil, 37 surface water, and ground water. The HSA data should be used to identify the media onsite with 38 a potential for residual radioactive material (see Section 3.6.3). Identifying the media that may 39 contain residual radioactive material is useful for preliminary survey unit classification and for 40 planning subsequent survey activities. Selection of survey instrumentation and analytical 41 techniques are typically based on knowledge of the appropriate DCGLs, because remediation 42 decisions are made based on the level of the residual radioactive material as compared to the NUREG-1575, Revision 2                          5-12                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                                Survey Planning and Design 1 DCGL. Exposure rate measurements may be needed to assess occupational and public health 2 and safety.
3 Structure Surveys 4 Surveys of building surfaces and structures can include surface scanning, surface activity 5 measurements, exposure rate measurements, and sample collection (e.g., smears, subfloor 6 soil, water, paint, and building materials). Both field survey instrumentation (Chapter 6) and 7 analytical laboratory equipment and procedures (Chapter 7) are selected based on their 8 instrumentation capabilities for the expected residual radioactive material and their quantities.
9 Field and laboratory instruments are described in Appendix H.
10 Background activity and radiation levels for the area should be determined from appropriate 11 background reference areas. Background assessments include surface activity measurements 12 on building surfaces, exposure rates, and radionuclide concentrations in various media (refer to 13 Section 4.5). Building reference area measurements should be collected in non-impacted areas 14 within the same building, or in another similar building, provided that the reference area has 15 been constructed with materials of the same type and age. This ensures that the reference area 16 has the same inherent radioactive material and decay time, and therefore background 17 radioactivity, as the impacted area.
18 Measurement locations should be documented using reference system coordinates, if 19 appropriate, or fixed site features. A typical reference system spacing for building surfaces is 20 1 m. This is chosen to facilitate identifying survey locations and small areas of elevated activity.
21 Scans should be conducted in areas likely to contain residual radioactive material, based on the 22 results of the HSA and scoping survey.
23 Both systematic and judgment surface activity measurements are performed. Judgment direct 24 measurements are performed at locations of elevated direct radiation, as identified by surface 25 scans, to provide data on the upper ranges of residual radioactive material levels. Judgment 26 measurements may also be performed in sewers, air ducts, storage tanks, and septic systems 27 and on roofs of buildings, if necessary. Each surface activity measurement location should be 28 carefully recorded on the appropriate survey form.
29 Exposure rate measurements and media sampling are performed as necessary. For example, 30 subfloor soil samples may provide information on the horizontal and vertical extent of residual 31 radioactive material. Similarly, concrete core samples are necessary to evaluate the depth of 32 activated concrete in a reactor facility. Note that one type of radiological measurement may be 33 sufficient to determine the extent of residual radioactive material. For example, surface activity 34 measurements alone may be all that is needed to demonstrate that remediation of an area is 35 necessary; exposure rate measurements would add little to this determination.
36 Lastly, the measuring and sampling techniques should be commensurate with the intended use 37 of the data, as characterization survey data may be used to guide the FSS survey design or 38 supplement FSS data, provided that the data meet the selected DQOs and the FSS design 39 requirements.
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Survey Planning and Design                                                                MARSSIM 1 Land Area Surveys 2 Characterization surveys for surface and subsurface soils and media involve employing 3 techniques to determine the lateral and vertical extent and radionuclide concentrations in the 4 soil. This may be performed using either sampling and laboratory analyses or in situ gamma 5 spectrometry analyses, depending on the instrumentation capabilities of each methodology for 6 the expected radionuclides and concentrations. Note that in situ gamma spectrometry analyses 7 or any direct surface measurement cannot easily be used to determine distributions of 8 radionuclides as a function of depth. Sample collection followed by laboratory analysis 9 introduces several additional sources of uncertainty that need to be considered during survey 10 design. In many cases, a combination of direct measurements and samples is required to meet 11 the objectives of the survey.
12 Radionuclide concentrations in background soil samples should be determined for a sufficient 13 number of soil samples that are representative of the soil in terms of soil type, soil depth, etc. It 14 is important that the background samples be collected in non-impacted areas. Consideration 15 should be given to spatial variations in the background radionuclide concentrations as 16 discussed in Section 4.6 and NRC draft report NUREG-1501 (NRC 1994a).
17 Sample locations should be documented using GPS; reference system coordinates (see 18 Section 4.9.5), if appropriate; or fixed site features. A typical reference system spacing for open 19 land areas is 10 m (NRC 1992a). This spacing is somewhat arbitrary and is chosen to facilitate 20 determining survey unit locations and identifying areas of elevated concentrations of radioactive 21 material.
22 Surface scans for gamma activity should be conducted in areas likely to contain residual 23 radioactive material. Selection of instrumentation should be appropriate to detect the 24 radionuclide(s) of interest. Beta scans may be appropriate if the residual radioactive material is 25 near the surface and beta is the dominant radiation emitted from the residual radioactive 26 material. The detection capability and measurement uncertainty of the scanning technique 27 should be appropriate to meet the DQOs and MQOs.
28 Both systematic and judgment surface activity measurements are performed. Judgment direct 29 measurements are performed at locations of elevated direct radiation, as identified by surface 30 scans, to provide data on upper ranges of residual radioactive material levels. Judgment 31 measurements may also be performed in areas where radioactive materials might have 32 accrued, such as in swales, under downspouts, near access roads, etc., if necessary. Each 33 surface activity measurement location should be carefully recorded on the appropriate survey 34 form.
35 Both surface and subsurface soil and media samples may be necessary. Subsurface soil 36 samples should be collected where residual radioactive material is present on the surface and 37 where residual radioactive material is known or suspected in the subsurface. Boreholes should 38 be constructed to provide samples representing subsurface deposits.
39 Exposure rate measurements at 1 m (~3 feet) above the sampling location may also be 40 appropriate. Each surface and subsurface soil sampling and measurement location should be 41 carefully recorded.
42 Surface Water and Sediments 43 Surface water and sediment sampling may be necessary, depending on the potential for these 44 media to contain residual radioactive material, which depends on several factors, including the NUREG-1575, Revision 2                          5-14                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                  Survey Planning and Design 1 proximity of surface water bodies to the site, size of the drainage area, total annual rainfall, and 2 spatial and temporal variability in surface water flow rate and volume. Refer to Section 3.6.3.3 3 for further criteria to determine the necessity for surface water and sediment sampling.
4 Characterizing surface water involves techniques that determine the extent and distribution of 5 residual radioactive material. This may be performed by collecting grab samples of the surface 6 water in a well-mixed zone. At certain sites, it may be necessary to collect stratified water 7 samples to provide information on the vertical distribution of residual radioactive material.
8 Sediment sampling should also be performed to assess the relationship between the 9 composition of the suspended sediment and the bedload sediment fractions (i.e., suspended 10 sediments compared to deposited sediments). When judgment sampling is used to find 11 radionuclides in sediments, radioactive sediments are more likely to be accumulated on fine-12 grained deposits found in low-energy environments (e.g., deposited silt on inner curves of 13 streams).
14 Radionuclide concentrations in background water samples should be determined for a sufficient 15 number of water samples that are upstream of the site or in areas unaffected by site operations.
16 Consideration should be given to any spatial or temporal variations in the background 17 radionuclide concentrations.
18 Sampling locations should be documented using reference system coordinates, if appropriate, 19 or scale drawings of the surface water bodies. Effects of variability of surface water flow rate 20 should be considered. Surface scans for gamma activity may be conducted in areas likely to 21 contain residual radioactive material (e.g., along the banks) based on the results of the 22 document review or preliminary investigation surveys.
23 Surface water sampling should be performed in areas of runoff from active operations, at plant 24 outfall locations, upstream and downstream of the outfall, and any other areas likely to contain 25 residual radioactive material (see Section 3.6.3.3). Measurements of radionuclide 26 concentrations in water should include gross alpha and gross beta radioactivity concentration 27 assessments, as well as any necessary radionuclide-specific analyses. Non-radiological 28 parameterssuch as specific conductance, pH, and total organic carbonmay be used as 29 surrogate indicators of potential radioactive material, if a specific relationship exists between the 30 radionuclide concentration and the level of the indicator (e.g., if a linear relationship between pH 31 and the radionuclide concentration in water is found to exist, then the pH may be measured 32 such that the radionuclide concentration can be calculated based on the known relationship 33 rather than performing an expensive nuclide-specific analysis). The use of surrogate 34 measurements is discussed in Section 4.5.3.
35 Each surface water and sediment sampling location should be carefully recorded on the 36 appropriate survey form. Additionally, surface water flow models may be used to illustrate 37 radionuclide concentrations and migration rates.
38 Ground Water 39 Ground water sampling may be necessary, depending on the local geology, potential for 40 residual radioactive material in the subsurface, and the regulatory framework. Because different 41 agencies handle ground water compliance in different ways (e.g., EPAs Superfund program 42 and some States require compliance with maximum contaminant levels specified in the Safe 43 Drinking Water Act), the regulatory agency should be contacted if residual radioactive material May 2020                                        5-15                        NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                MARSSIM 1 in ground water is expected. The need for ground water sampling is described in 2 Section 3.6.3.4.
3 If residual radioactive material in ground water is identified, the regulatory agency should be 4 contacted at once, because (1) ground water release criteria and DCGLs should be established 5 by the appropriate agency (Section 4.5.2), and (2) the default DCGLs for soil may be 6 inappropriate, because they are usually based on ground water without any residual radioactive 7 material.
8 Characterization of residual radioactive material in ground water should determine the extent 9 and distribution of residual radioactive material, rates and direction of ground water migration, 10 and the assessment of potential effects of ground water withdrawal on the migration of residual 11 radioactive material in ground water. This may be performed by designing a suitable monitoring 12 well network. The actual number and location of monitoring wells depends on the size of the 13 affected area, the type and extent of the residual radioactive material, the hydrogeological 14 system, and the objectives of the monitoring program.
15 When ground water samples are taken, background radiation levels should be determined by 16 collecting samples from the same aquifer upgradient of the site and then analyzing them. Any 17 tidal effects and effects of additional wells in the upgradient zone on ground water flow should 18 be evaluated to aid in selecting the proper location of upgradient background samples. The 19 background samples should not be affected by site operations and should be representative of 20 the quality of the ground water that would exist if the site had not been affected by the residual 21 radioactive material. Consideration should be given to any spatial or temporal variations in the 22 background radionuclide concentrations.
23 Sampling locations should be referenced to grid coordinates, if appropriate, or to scale drawings 24 of the ground water monitoring wells. Construction specifications on the monitoring wells should 25 also be provided, including elevation, internal and external dimensions, types of casings, type of 26 screen and its location, borehole diameter, and other necessary information about the wells.
27 In addition to organic and inorganic constituents, ground water sampling and analyses should 28 include all significant radiological constituents. Measurements in potential sources of drinking 29 water should include gross alpha and gross beta assessments, as well as any other 30 radionuclide-specific analyses deemed appropriate based on the HSA. Non-radiological 31 parameterssuch as specific conductance, pH, and total organic carbonmay be used as 32 surrogate indicators of the potential presence of certain radionuclides, provided that a specific 33 relationship exists between the radionuclide concentration and the level of the indicator.
34 Each ground water monitoring well location should be carefully recorded on the appropriate 35 survey form. Additionally, radionuclide concentrations and sources should be plotted on a map 36 to illustrate the relationship among radionuclides, sources, hydrogeological features and 37 boundary conditions, and property boundaries (EPA 1993f).
38 Other Media 39 Air sampling may be necessary at some sites, depending on the local geology and the 40 radionuclides of potential concern. This may include collecting air samples or filtering the air to 41 collect resuspended particulates. Air sampling is often restricted to monitoring activities for 42 occupational and public health and safety, and it is not required to demonstrate compliance with 43 risk- or dose-based regulations. Section 3.6.3.5 describes examples of sites where air sampling 44 may provide information useful to designing an FSS. At some sites, radon measurements may NUREG-1575, Revision 2                            5-16                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                    Survey Planning and Design 1 be used to indicate the presence of radium, thorium, or uranium in the soil. Section 6.8 and 2 Appendix H provide information on this type of sampling.
3 In rare cases, vegetation samples may be collected as part of a characterization survey to 4 provide information in preparation for an FSS. Because most risk- and dose-based regulations 5 are concerned with potential future land use that may differ from the current land use, 6 vegetation samples are unsuitable for demonstrating compliance with regulations. There is a 7 relationship between radionuclide concentrations in plants and those in soil (the soil-to-plant 8 transfer factor is used in many models to develop DCGLs), and the plant concentration could be 9 used as a surrogate measurement of the soil concentration. In most cases, a measurement of 10 the soil itself as the parameter of interest is more appropriate and introduces less uncertainty in 11 the result.
12 5.2.2.3 Evaluating Survey Results 13 Survey data are converted to the same units as those in which DCGLs are expressed 14 (Section 6.7). Laboratory and in situ analyses are performed to identify potential residual 15 radioactive material at the site. Appropriate regulatory DCGLs for the site are selected, and the 16 data are then compared to the DCGLs. For characterization data that are used to supplement 17 FSS data, the statistical methodology in Chapter 8 should be followed to determine if a survey 18 unit satisfies the release criteria.
19 For characterization data that are used to help guide remediation efforts, the survey data are 20 used to identify locations and the general extent of residual radioactivity. The survey results are 21 first compared with DCGLs. Surfaces and environmental media are then differentiated as 22 exceeding DCGLs, not exceeding DCGLs, or not affected, depending on the measurement 23 results relative to the DCGL value. Direct measurements indicating areas of elevated activity are 24 further evaluated, and the need for additional measurements is determined.
25 5.2.2.4 Documentation 26 Documentation of the site characterization survey should provide a complete and unambiguous 27 record of the radiological status of the site. In addition, sufficient information to characterize the 28 extent of residual radioactive material, including all possible affected environmental media, 29 should be provided in the report. This report should also provide sufficient information to support 30 reasonable approaches or alternatives to site remediation. Example 2 includes an example of a 31 characterization survey checklist.
Example 2: Example Characterization Survey Checklist Survey Design
_____ Enumerate Data Quality Objectives (DQOs) and Measurement Quality Objectives (MQOs): State the objective of the survey; survey instrumentation capabilities should be appropriate for the specific survey objective.
_____ Review the Historical Site Assessment (HSA) and scoping survey results, if performed, for May 2020                                          5-17                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                              MARSSIM
_____ Operational history (e.g., any problems, spills, or releases) and available documentation (e.g., radioactive materials license).
_____ Other available resourcessite personnel, former workers, residents, etc.
_____ Types and quantities of materials that were handled and where radioactive materials were stored, handled, and disposed of.
_____ Release and migration pathways.
_____ Information on the potential for residual radioactive material that may be useful during area classification for final status survey (FSS) design. Note: Survey activities will be concentrated in Class 1 and Class 2 areas.
_____ Types and quantities of materials likely to remain onsiteconsider radioactive decay and ingrowth of decay products.
_____ Document the survey plan (e.g., Quality Assurance Project Plan, standard operating procedures, etc.)
Conducting Surveys
_____ Select instrumentation based on its capabilities for the expected residual radioactive material and quantities and knowledge of the appropriate derived concentration guideline levels (DCGLs).
_____ Define background locations and determine background activity and radiation levels for the area; include surface activity levels on building surfaces, radionuclide concentrations in environmental media, and exposure rates.
_____ Establish a reference coordinate system. Prepare scale drawings for surface water and ground water monitoring well locations.
_____ Perform thorough surface scans of all areas potentially containing residual radioactive material. Examples of indoor areas include expansion joints, stress cracks, penetrations into floors and walls for piping, conduits, anchor bolts, and wall/floor interfaces. Examples of outdoor areas include radioactive material storage areas, areas downwind of stack release points, dripline and downspout areas, surface drainage pathways, and roadways that may have been used for transport of radioactive materials.
_____ Perform systematic surface activity measurements.
_____ Perform systematic smear, surface and subsurface soil and media, sediment, surface water, and ground water sampling, if appropriate for the site.
_____ Perform judgment direct measurements and sampling of elevated areas to provide data on the upper ranges of levels of the concentration of radioactive material.
_____ Document survey and sampling locations.
_____ Maintain chain of custody of samples when necessary.
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MARSSIM                                                                  Survey Planning and Design Note: One category of radiological data (e.g., radionuclide concentration, direct radiation level, or surface radioactivity) may be sufficient to determine the extent of residual radioactive material; other measurements may not be necessary (e.g., removable surface radioactive material or exposure rate measurements).
Note: Measuring and sampling techniques should be commensurate with the intended use of the data, because characterization survey data may be used to supplement FSS data.
Evaluating Survey Results
_____ Compare survey results with DCGLs. Differentiate surfaces or areas as exceeding DCGLs, not exceeding DCGLs, or not affected.
_____ Evaluate all locations of elevated direct measurements, and determine the need for additional measurements or samples.
_____ Prepare site characterization survey report.
1 5.2.3    Remedial Action Support Surveys 2 RAS surveys are conducted to (1) support remediation activities, (2) determine when a site or 3 survey unit is ready for the FSS, and (3) provide updated estimates of site-specific parameters 4 to use for planning the FSS. This manual does not discuss the routine operational surveys 5 (e.g., air sampling, dose rate measurements, environmental sampling) conducted for health and 6 safety purposes to support remediation activities.
7 A RAS survey serves to monitor the effectiveness of remediation efforts to reduce residual 8 radioactive material to acceptable levels. The RAS survey also ensures that remediation is 9 targeted to only those areas requiring remediation, which in turn ensures a cost-effective 10 remediation. This type of survey guides the cleanup in a real-time mode. The RAS survey 11 typically relies on a simple radiological parameter, such as direct radiation near the surface, as 12 an indicator of effectiveness. The investigation level for the RAS survey (established as the 13 DCGL) is determined and used for immediate, in-field decisions (Section 5.3.8).
14 Such a survey is intended for expediency and cost-effectiveness and does not provide thorough 15 or accurate data describing the radiological status of the site. Note that this survey typically 16 does not provide information that can be used to demonstrate compliance with the DCGLs; 17 rather, it is an interim step in the compliance demonstration process. Areas that are determined 18 to likely satisfy the DCGLs on the basis of the RAS survey will then be surveyed in detail by the 19 FSS. Alternatively, the RAS survey can be designed to meet the objectives of an FSS as 20 described in Section 5.3.
21 Remedial activities result in changes to the distribution of residual radioactive material within a 22 survey unit. The site-specific parameters used during FSS planning (e.g., variability in the 23 radionuclide concentration within a survey unit or the probability of small areas of elevated 24 activity) will change during remediation. For most survey units, values for these parameters will 25 need to be re-established following remediation. Obtaining updated values for these critical 26 planning parameters should be considered when designing a RAS survey.
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Survey Planning and Design                                                                MARSSIM 1 5.2.3.1 Survey Design 2 The objective of the RAS survey is to determine whether remediation was adequate to remove 3 radioactive material to levels at or below the DCGL criteria. Although the presence of small 4 areas of elevated concentrations of radioactive material may satisfy the elevated measurement 5 criteria, it may be more efficient to design the RAS survey to identify residual radioactive 6 material at the radionuclide-specific release limit based on the spatial distribution of the 7 radionuclide within a survey unit (DCGLW) and to remediate small areas of elevated activity that 8 may potentially satisfy the release criteria. Survey instrumentation and techniques are therefore 9 selected based on the instrumentation capabilities for the known or suspected radionuclides and 10 DCGLs to be achieved.
11 There will be radionuclides and media that cannot be evaluated at the DCGLW using field 12 monitoring techniques. For these cases, it may be feasible to collect and analyze samples by 13 methods that are quicker and less costly than radionuclide-specific laboratory procedures. Field 14 laboratories and screening techniques may be acceptable alternatives to more expensive 15 analyses. Reviewing remediation plans may be required to get an indication of the location and 16 amount of residual radioactive material remaining following remediation.
17 5.2.3.2 Conducting Surveys 18 Field survey instruments and procedures are selected based on their ability to detect and 19 quantify the expected radionuclides. Survey methods typically include scans of surfaces 20 followed by direct measurements to identify residual radioactive material. The surface activity 21 levels are compared to the investigation levels, and a determination is made on the need for 22 further remediation efforts.
23 Survey activities for soil excavations include surface scans using field instrumentation sensitive 24 to beta and gamma activity. Because it can be difficult to correlate scanning results to 25 radionuclide concentrations in soil, judgment should be exercised carefully when using scan 26 results to guide the cleanup efforts. Field laboratories and screening techniques may provide a 27 better approach for determining whether further soil remediation is necessary.
28 5.2.3.3 Evaluating Survey Results 29 Survey data (e.g., surface activity levels and radionuclide concentrations in various media) are 30 converted to standard units and compared to the DCGLs (Section 6.7). If results of these 31 survey activities indicate that remediation has been successful in meeting the DCGLs, remedial 32 actions are ceased, and FSS activities are initiated. Alternatively, further remediation may be 33 needed if results indicate the presence of residual radioactive material in excess of the DCGLs.
34 DCGLs may be recalculated based on the results of the remediation process as the regulatory 35 program allows or permits.
36 5.2.3.4 Documentation 37 The RAS survey should guide the cleanup and alert those performing remedial activities that 38 (1) additional remediation is needed or (2) the site may be ready to initiate an FSS. Data that 39 indicate an area has been successfully remediated could be used to estimate the variance for 40 the survey units in that area. Information identifying areas of elevated activity that existed before 41 remediation may be useful for planning FSSs. Example 3 includes an example of a RAS survey 42 checklist, including survey design, conduct of surveys, and evaluation of survey results.
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MARSSIM                                                                Survey Planning and Design Example 3: Example Remedial Action Support Survey Checklist Survey Design
_____ Enumerate Data Quality Objectives and Measurement Quality Objectives: State the objectives of the survey; survey instrumentation capabilities should be appropriate for the specific survey objective.
_____ Document the survey plan (e.g., Quality Assurance Project Plan, standard operating procedures, etc.)
_____ Review the remediation plans.
_____ Determine applicability of monitoring surfaces/soils for the radionuclides of concern.
Note: RAS surveys may not be feasible for residual radioactive materials with very low-energy beta emitters or for soils or media containing pure alpha emitters.
_____ Select simple radiological parameters (e.g., surface activity) that can be used to make immediate in-field decisions on the effectiveness of the remedial action.
Conducting Surveys
_____ Select instrumentation based on its capabilities for measuring the expected radionuclides.
_____ Perform scanning and surface activity measurements near the surface being remediated.
_____ Survey soil excavations and perform field evaluation of samples (e.g., gamma spectrometry of undried/non-homogenized soil) as remedial actions progress.
Evaluating Survey Results
_____ Compare survey results with DCGLs using survey data as a field decision tool to guide the remedial actions in a real-time mode.
_____ Document survey results.
1 5.3    Final Status Surveys 2 An FSS is performed to demonstrate that residual radioactive material in each survey unit 3 satisfies the predetermined criteria for release for unrestricted use or, where appropriate, for use 4 with designated limitations. The survey provides data to demonstrate that all radiological 5 parameters do not exceed the established DCGLs. For these reasons, more detailed 6 information is provided for this category of survey. For the FSS, survey units represent the 7 fundamental elements for demonstrating that the property is less than the DCGLW by using a 8 combination of direct measurements or sampling and scanning (see Sections 5.3.3-5.3.5) or 9 by a scan-only survey of the property (if warranted by the scanning instrumentation detection 10 capability and measurement uncertainty; see Section 5.3.6). The percentage of the area May 2020                                        5-21                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                MARSSIM 1 scanned is dependent upon the classification of the property or survey units within the property 2 as well as the relative shift for the site. The documentation specified in the following sections 3 helps ensure a consistent approach among different organizations and regulatory agencies.
4 This allows for comparisons of survey results between sites or facilities.
5 The MARSSIM approach recognizes that alternative methods may be acceptable to different 6 regulatory agencies. Flow diagrams and a checklist to assist the user in planning a survey are 7 included in this section.
8 Figures 5.4-5.6 illustrate the process of designing an FSS. This process begins with 9 development of DQOs and MQOs. The first decision after developing the DQOs and MQOs is to 10 establish whether a scan-only or traditional MARSSIM approach (scanning with direct 11 measurements and/or samples) will be used. Based on these objectives and the known or 12 anticipated radiological conditions at the site, the numbers and locations of measurement and 13 sampling points used and amount of scanning to demonstrate compliance with the release 14 criteria are then determined. Finally, survey techniques appropriate to develop adequate data 15 (see Chapters 6 and 7) are selected and implemented.
16 The elements of an FSS discussed in Section 5.3 consist of the following subsections:
17
* selecting either Scenario A or Scenario B as a basis of the survey design (Section 5.3.1) 18
* determining the appropriate release criteria based on whether radionuclides of concern are 19      present in the background (Section 5.3.2) 20
* determining the appropriate number of data points for statistical tests when residual 21      radioactive materials are present in the background (Section 5.3.3) 22
* determining the appropriate number of data points for statistical tests when residual 23      radioactive materials are not present in the background (Section 5.3.4) 24
* establishing procedures for determining data points for small areas of elevated activity 25      (Section 5.3.5) 26
* determining the scan area (Section 5.3.6) 27
* determining the survey locations (Section 5.3.7) 28
* establishing the appropriate investigation level for a survey (Section 5.3.8) 29
* developing an integrated survey design (Section 5.3.9) 30
* evaluating the survey results (Section 5.3.10) 31
* documenting the results (Section 5.3.11) 32 Another important consideration during planning for an FSS is the performance of confirmatory 33 surveys. Planning for the FSS should include early discussions with the regulatory agency 34 concerning logistics for confirmatory or verification surveys. A confirmatory survey (also known 35 as an independent verification survey) may be performed by the regulatory agency or by an 36 independent third party (e.g., a party contracted by the regulatory agency) to provide data to 37 substantiate results of the FSS. Actual field measurements and sampling may be performed.
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MARSSIM                                                                                  Survey Planning and Design Select Appropriate Scenario Section 5.3.1 Enumerate DQOs & MQOs Sampling/Direct Surveys and Select Measurement              Scan-Only Surveys with Scanning Method Chapters 4, 6 & 7 Determine , , and /                                                          Determine , , and /
Sections 5.3.3 & 5.3.4                                                                    Section 5.3.6 Is Radionuclides(s)
Present in No                  Background?                  Yes Section 4.5 Obtain Number of Data Points for Obtain Number of Data Points for                  WRS Test, N/2, From Table 5.2 Sign Test, N, From Table 5.3                        for Each Survey Unit and Reference Area Section 5.3.4                                    Section 5.3.3 Identify Measurement Locations for Discrete Measurements                                      Determine Scan Area Section 5.3.7                                          Section 5.3.6 Figure 5.5 Identify Data Needs for                                    Determine Survey Location Assessment of Potential Areas of                                        for Scans Elevated Activity Section 5.3.7 Section 5.3.5 Figure 5.6 Determine Investigation Levels Section 5.3.8 Develop an Integrated Survey Design Section 5.3.9 1
2 Figure 5.4: Process for Designing an Integrated Survey Plan for a Final Status Survey May 2020                                                    5-23                            NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                  DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                                          MARSSIM WHAT IS THE Class 1                                                        Class 3 AREA CLASSIFICATION?
Section 4.6.1 Class 2 Determine Number of                        Determine Number of                        Determine Number of Data Points Needed                          Data Points Needed                        Data Points Needed Sections 5.3.3 & 5.3.4                    Sections 5.3.3 & 5.3.4                    Sections 5.3.3 & 5.3.4 Determine Spacing                          Determine Spacing                          Generate Sets of for Survey Unit                            for Survey Unit                          Random Values Equations 5.5 & 5.6                        Equations 5.5 & 5.6                      Appendix I Multiply Survey Unit Generate a Random                          Generate a Random                            Dimensions by Starting Point                              Starting Point                        Random Numbers to Determine Coordinates Appendix I                                Appendix I                                Section 5.3.7 Identify Data Point                        Identify Data Point Grid Locations                              Grid Locations Section 5.3.7                              Section 5.3.7 Where Conditions Prevent                    Where Conditions Prevent Survey of Identified Locations,              Survey of Identified Locations,            Continue Until the Necessary Supplement with Additional                  Supplement with Additional                Number of Data Points are Randomly Selected                            Randomly Selected                              Identified Locations                                    Locations 1
2 Figure 5.5: Process for Identifying Discrete Measurement Locations NUREG-1575, Revision 2                                        5-24                                                  May 2020 DRAFT FOR PUBLIC COMMENT                                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                                  Survey Planning and Design Establish DQOs for Areas with the Potential for Exceeding DCGLs and Acceptable Risk for Missing Such Areas Identify Number of Data Points, n, Needed Based on Statistical Tests          Sections 5.3.3 & 5.3.4 Calculate the Area, A, Bounded by Data Points, n                    Section 5.3.5.1 Determine Acceptable Concentrations in Various Individual Smaller Areas within      Section 5.3.5 Survey Unit Determine the Acceptable Concentration Section 5.3.5 Corresponding to the Calculated Area, A Determine the Required Scan MDC to Identify the Acceptable Concentration in an Area, A Evaluate MDCs of Measurement Techniques for Available Instrumentation Is the Scan MDC for No              Available Instrumentation Less          Yes Than the Required Scan MDC?
Calculate the Required                                                No Additional Sampling Grid Spacing and Number Section 5.3.5.2                                Points are Necessary for of Data Points    Examples 7 & 8                                Potential Elevated Areas 1
2 Figure 5.6: Identifying Data Needs for Assessment of Potential Areas of Elevated Activity 3 in Class 1 Survey Units May 2020                                        5-25                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                      MARSSIM 1 Independent confirmatory survey activities are usually limited in scope to spot-checking 2 conditions at selected locations, comparing findings with those of the FSS and performing 3 independent statistical evaluations of the data developed from the confirmatory survey and the 4 FSS. Another purpose of the confirmatory activities may be to identify any deficiencies in the 5 FSS documentation based on a thorough review of survey procedures and results. Finally, 6 reviewing the results of confirmatory surveys performed on other sites may provide insight into 7 possible survey deficiencies, which can then be corrected before the FSS is performed (Roberts 8 2008).
9 5.3.1    Selecting the Appropriate Scenario 10 The DQO process, as it is applied to FSSs, is described in more detail in Appendix D of this 11 manual and in EPA and NRC guidance documents (EPA 1987b, 1987c, 2006c; NRC 1998a). As 12 part of this process, the objective of the survey and the null and alternative hypotheses should 13 be clearly stated. The objective of FSSs is typically to demonstrate that residual radioactive 14 material levels meet the release criteria. One of two approaches is used to demonstrate that this 15 objective is met; the two approaches differ in the selection of the null hypothesis (i.e., what is 16 assumed to be the true state of nature), as summarized in Table 5.1.
17 Table 5.1: Null and Alternative Hypothesis for Scenarios A and B Scenario              Null Hypothesis ( )                Alternative Hypothesis ( )
A        The concentration of residual              The concentration of residual radioactive material is equal to or        radioactive material is less than the exceeds the release criteria.              release criteria.
B        The concentration of residual              The concentration of residual radioactive material is equal to or less  radioactive material exceeds the than the release criteria.                release criteria.
18 Historically, MARSSIM recommended the use of Scenario A, which put the burden of proof that 19 the survey unit met the release criteria on the individuals designing the survey. However, 20 Scenario A requires that survey designers choose a discrimination limit (DL), the lower bound of 21 the gray region (LBGR), at some radioactive material concentration less than the DCGL. This is 22 effectively impossible when the AL corresponding to the release criteria is zero residual 23 radioactive material or zero residual radioactive material above background. The only way to 24 design a survey for these kinds of release criteria is to establish a DL at some radioactive 25 material concentration greater than the AL.
26 In Scenario B, the burden of proof is no longer on the individuals designing the survey and, 27 thus, should be used with caution and only in those situations where Scenario A is not an 28 effective alternative. The consequence of inadequate power is an increased Type II decision 29 error () rate. For Scenario A, this means that a survey unit that does meet the release criteria 30 has a higher probability of being incorrectly determined not to meet the release criteria. For 31 Scenario B, this means that a survey unit that does not meet the release criteria has a higher 32 probability of being incorrectly determined to meet the release criteria. For this reason, 33 individuals designing a MARSSIM Survey using Scenario B should make conservative 34 assumptions for the estimate of the standard deviation () (see Section 5.3.3.2) so that even if 35 the variability in the survey unit is higher than expected, the power of the resulting survey 36 (1  ) (see Section 5.3.2) will still be sufficient to ensure that survey units with residual 37 radioactive material in excess of the AL will be discovered 1  percent of the time. As a result, 38 a retrospective power analysis needs to be performed following the completion of Scenario B NUREG-1575, Revision 2                              5-26                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                              Survey Planning and Design 1 MARSSIM surveys indicating that regulatory agency requirements on  at the DL were met. See 2 Chapter 8 and Appendix M for more information on performing a retrospective power analysis.
3 5.3.2  Application of Release Criteria 4 The statistical test used to evaluate data for FSSs where direct measurements or sampling and 5 analysis is performed depend on the scenario selected. For radionuclides that are present in 6 background, the Wilcoxon Rank Sum (WRS) test is typically used in Scenario A. In Scenario B 7 two nonparametric statistical tests are performed: the WRS test and the Quantile test. The WRS 8 and Quantile tests are both used because each test detects different residual radioactive 9 material patterns in the survey unit. When radionuclides of concern are not present in 10 background, the Sign test is used for both scenarios. For scan-only surveys, a comparison to an 11 upper confidence level (UCL) is performed. The Sign, WRS, UCL, and Quantile tests are 12 discussed in Chapter 8.
13 To determine data needs for these tests, the acceptable probability of making Type I decision 14 errors () and Type II decision errors () should be established (see Appendix D, Section 15 D.1.6). The acceptable decision error rates are defined at the LBGR and the DCGLW for 16 Scenario A and the action level (AL) and the DL for Scenario B. Acceptable decision error rates 17 are determined during survey planning using the DQO process.
18 The final step of the DQO process includes selecting a survey design that satisfies the DQOs.
19 For some sites or survey units, the information provided in this section may result in a survey 20 design that cannot be accomplished with the available resources. For these situations, the 21 planning team may be able to relax one or more of the constraints used to develop the survey 22 design as described in Appendix D. For example 23
* increasing the decision error rates, considering the risks associated with making an incorrect 24    decision 25
* increasing the width of the gray region, as long as the LBGR is not set lower than the 26    estimate of the residual radioactive material remaining in the survey unit in Scenario A 27
* changing the boundariesit may be possible to reduce measurement costs by changing or 28    eliminating survey units that may require different decisions 29 5.3.3  Determining Numbers of Data Points for Statistical Tests for Residual Radioactive 30        Material Present in Background 31 The comparison of measurements from the reference area and survey unit is made using the 32 WRS test, which is usually conducted for each survey unit. In addition, the Elevated 33 Measurement Comparison (EMC) may need to be performed against each measurement to 34 ensure that the measurement result does not exceed a specified investigation level. If any 35 measurement in the remediated survey unit exceeds the specified investigation level, then 36 additional investigation is recommended, at least locally, regardless of the outcome of the WRS 37 test.
38 The WRS test is most effective when residual radioactive material is uniformly present 39 throughout a survey unit. The test is designed to detect whether the median concentration 40 exceeds the DCGLW. The advantage of this nonparametric test is that it does not assume the May 2020                                        5-27                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                              DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                              MARSSIM 1 data are normally or log-normally distributed. The WRS test also allows for less than 2 measurements to be present in the reference area and the survey units. This test can generally 3 be used with up to 40 percent less than measurements in either the reference area or the 4 survey unit. However, the use of less than values in data reporting is not recommended (NRC 5 2004). Wherever possible, the actual result of a measurement, together with its uncertainty, 6 should be reported.
7 This section introduces several terms and statistical parameters that will be used to determine 8 the number of data points needed to apply the nonparametric tests. An example is provided 9 below to better illustrate the application of these statistical concepts.
10 5.3.3.1 Define the Gray Region 11 In Scenario A, the upper bound of the gray region (UBGR) is equal to the DCGLW. The gray 12 region is defined as the interval between the LBGR and the DCGLW (Figure 5.7). For 13 Scenario A, the LBGR is typically chosen to represent a conservative (slightly higher) estimate 14 of the mean concentration of residual radioactive material remaining in the survey unit at the 15 beginning of the FSS. If there is no information with which to estimate the residual radioactive 16 material concentration remaining, the LBGR may be initially set to equal one-half of the DCGLW.
LBGR                                                              DCGLW Concentration of Radioactive Material 17 18 Figure 5.7: Gray Region for Scenario A 19 In Scenario B, the UBGR is equal to the DL, and the LBGR is equal to the AL. The gray region 20 is defined as the interval between the AL and the DL (Figure 5.8). 2 The AL is the concentration 21 of radioactive material that causes a decision maker to choose one of the alternative actions, 22 such as releasing a survey unit or requiring additional investigation. The planning team also 23 chooses the DL. The DL is the concentration of radioactive material or level of radioactivity that 24 can be reliably distinguished from the action level by performing measurements with the devices 25 selected for the survey (i.e., direct measurements, scans, in situ measurements, samples with 26 laboratory analyses) and defines the rigor of the survey. It is determined through negotiations 27 with the regulator, and, in some cases, the DL will be set equal to a regulatory limit (e.g.,
28 10 CFR 36.57 and DOE 2011c). The DL and the AL should be reported in the same units. The 29 selection of the appropriate null hypothesis is further discussed in Chapter 8 and Appendix D.
2 This description of Scenario B is based on information contained in the Multi-Agency Radiation Survey and Assessment of Materials and Equipment (MARSAME) Manual and the Multi-Agency Radiation Laboratory Analytical Protocols and is fundamentally different from the description of Scenario B found in NUREG-1505 (NRC 1998a).
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MARSSIM                                                                      Survey Planning and Design AL                                                          DL Concentration of Radioactive Material 1
2 Figure 5.8: Gray Region for Scenario B 3 When Scenario B is being used, the variability in the data may be such that a decision may be 4 "too close to call" when the true but unknown value of the residual radioactivity concentration is 5 very near the DL. In this situation, consultation with the appropriate regulator may be required to 6 determine the AL and DL. As an example, the U.S. NRC discusses methods in NUREG-1505 7 (NRC 1998a), Chapter 13, to establish the gray region and a concentration level that is 8 considered indistinguishable from background when the WRS test is used 3.
9 5.3.3.2 Calculate the Relative Shift 10 The width of the gray region is a parameter that is essential for planning all statistical tests; it is 11 also referred to as the shift, . In Scenario A, the shift is the difference between the LBGR and 12 the DCGLW ( = DCGLW  LBGR). In Scenario B, the shift is the difference between the AL 13 and the DL ( = DL - AL). The absolute size of the shift is less important than the relative shift, 14 , where  is an estimate of the standard deviation of the measured values in the survey unit.
15 This estimate of  includes both the real spatial variability in the quantity being measured and 16 the uncertainty of the chosen measurement method. The relative shift is an expression of the 17 resolution of the measurements in units of measurement uncertainty.
18 The shift and the estimated standard deviation in the measurements of the radioactive material 19 in the survey unit ( ) and reference area ( ) are used to calculate the relative shift () (see 20 Appendix D, Section D.1.7.3). The standard deviations in the radionuclide level will likely be 21 available from previous systematic and non-judgment survey data (e.g., scoping or 22 characterization survey data for un-remediated survey units or RAS surveys for remediated 23 survey units). If they are not available, it may be necessary to (1) perform some limited 24 preliminary measurements (about 5-20) to estimate the distributions or (2) to make a 25 reasonable estimate based on available site knowledge. If the first approach above is used, the 26 scoping or characterization survey data or preliminary measurements used to estimate the 27 standard deviation should use the same technique as the FSS will. When preliminary data are 28 not obtained, it may be reasonable to assume a coefficient of variation (CV) on the order of 3 Chapter 8 in NUREG-1505 [NRC 1998] provides additional information on the WRS test.
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Survey Planning and Design                                                                    MARSSIM 1 30 percent, based on experience. The CV is a measure of the dispersion of the data and is 2 defined by the ratio of the standard deviation to the mean.
3 The value selected as an estimate of  for a survey unit may be based on data collected only 4 from within that survey unit or from data collected from a much larger area of the site. Note that 5 survey units are not finalized until the planning stage of the FSS. This means that there may be 6 some difficulty in determining which individual measurements from a preliminary survey may 7 later represent a particular survey unit. For many sites, the most practical solution is to estimate 8  for each area classification (i.e., Class 1, Class 2, and Class 3) for both interior and exterior 9 survey units. This will result in all exterior Class 3 survey units using the same estimate of , all 10 exterior Class 2 survey units using a second estimate for , and all exterior Class 1 survey units 11 using a third estimate for . If there are multiple types of surfaces within an area classification, 12 additional estimates of  may be required. For example, a Class 2 concrete floor may require a 13 different estimate of  than a Class 2 cinder block wall, or a Class 3 unpaved parking area may 14 require a different estimate of  than a Class 3 lawn. In addition, a separate estimate of 15 should be obtained for every reference area.
16 The importance of choosing appropriate values for  and  must be emphasized. If the value 17 is grossly underestimated, the number of data points will be too few to obtain the desired power 18 level for the test, and a resurvey may be recommended (see Chapter 8). If, on the other hand, 19 the value is overestimated, the number of data points determined will be unnecessarily large.
20 Values for the relative shift that are less than 1 will result in a large number of measurements 21 needed to demonstrate compliance. The number of data points will also increase as  becomes 22 smaller. Because the DCGL is fixed, this means that the LBGR also has a significant effect on 23 the estimated number of measurements needed to demonstrate compliance in Scenario A. The 24 DL selected during the DQO process will have a similar effect in Scenario B. When the 25 estimated standard deviations in the reference area and survey units are different, the larger 26 value should be used to calculate the relative shift (). There is little benefit, in terms of 27 reduced number of measurements, for relative shift values greater than 3. Because of this and 28 the large number of measurements resulting from relative shift values less than 1, in 29 Scenario A, the LBGR may be adjusted to ensure the relative shift is greater than 1, as long as 30 the LBGR is not set lower than the estimate of the residual radioactive material remaining in the 31 survey unit. For Scenario B, the planning team may wish to adjust the DL to achieve a similar 32 effect with approval from the regulator. However, it is extremely important that such adjustments 33 be supported by data. Additional considerations related to adjusting the relative shift are 34 provided in Appendix D, Section D.1.7.3.
35 In practice, the DQO process is used to obtain a proper balance among the use of various 36 measurement techniques. In general, there is an inverse correlation between the cost of a 37 specific measurement method and the detection levels being sought. Depending on the survey 38 objectives, there are many important considerations when selecting a measurement method 39 that will ultimately affect both the survey costs and the statistical power of the sampling design.
40 Statistical power is defined as the probability that a statistical test will correctly reject the null 41 hypothesis (i.e., under Scenario A, accepting that a site that meets the release criteria truly 42 does, and under Scenario B, accepting that a site that does not meet the release criteria truly 43 does not). A general example approach that might be undertaken for a Scenario A planning 44 session is discussed below.
45  is the total number of data points for each survey unit/reference area combination. The  data 46 points are divided between the survey unit, , and the reference area, . The simplest method NUREG-1575, Revision 2                            5-30                                        May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                                  Survey Planning and Design 1 for distributing the  data points is to assign half the data points to the survey unit and half to 2 the reference area, so  =  = /2. This means that /2 measurements are performed in 3 each survey unit, and /2 measurements are performed in each reference area. If more than 4 one survey unit is associated with a particular reference area, /2 measurements should be 5 performed in each survey unit, and /2 measurements should be performed in the reference 6 area.
7 Table 5.2 provides a list of the number of data points needed to demonstrate compliance using 8 the WRS test for selected values of , , and . The values listed in Table 5.2 represent the 9 number of measurements to be performed in each survey unit and in the corresponding 10 reference area. Example 4 illustrates the use of the WRS Test under Scenario A.
Example 4: Use of WRS Test under Scenario A A site has 14 survey units and 1 reference area in a building, and the same measurement method is used to perform measurements in each survey unit and the reference area. The radionuclide has a wide-area derived concentration guideline level of 400 becquerels/square meter (Bq/m2) (240 decays per minute [dpm]/100 square centimeters [cm2]). The radionuclide is present in background at a level of 100 +/- 15 Bq/m2 (1). The standard deviation of the radionuclide in the survey area is +/- 40 Bq/m2 (24 dpm/100 cm2), based on previous survey results for the same or similar radionuclide distribution. When the estimated standard deviation in the reference area and the survey units are different, the larger value, 40 Bq/m2 in this example, is used to calculate the relative shift. During the Data Quality Objective process, Scenario A is selected. The LBGR is selected to be 240 Bq/m2. This is based on a conservative estimate of the concentration of residual radioactive material in the survey unit.
Type I and Type II error values ( and ) of 0.05 are selected. Determine the number of data points to be obtained from the reference area and from each of the survey units for the statistical tests.
The value of the relative shift for the survey unit, , is (400  240)/40, or 4.0. The number of data points can be obtained directly from Table 5.2. For  = 0.05,  = 0.05, and  =
4.0, a value of 9 is obtained for /2. The table value has already been increased by 20 percent to account for missing or unusable data.
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12  Table 5.2: Values of / for Use with the Wilcoxon Rank Sum Test 4,5 Survey Planning and Design NUREG-1575, Revision 2 13                          = 0.01                          = 0.025                          = 0.05                            = 0.10                        = 0.25 0.01 0.025 0.05 0.10      0.25    0.01 0.025 0.05 0.10      0.25    0.01 0.025 0.05 0.10      0.25    0.01  0.025 0.05 0.10    0.25    0.01 0.025 0.05 0.10 0.25 0.1    5,452 4,627 3,972 3,278  2,268  4,627 3,870 3,273 2,646  1,748  3,972 3,273 2,726 2,157  1,355  3,278  2,646 2,157 1,655  964    2,268 1,748 1,355 964 459 0.2    1,370 1,163 998 824        570    1,163 973 823 665          440    998 823 685 542          341    824    665 542 416        243    570 440 341 243 116 0.3    614 521 448 370          256    521 436 369 298          197    448 369 307 243          153    370    298 243 187        109    256 197 153 109 52 DRAFT FOR PUBLIC COMMENT 0.4    350 297 255 211          146    297 248 210 170          112    255 210 175 139            87    211    170 139 106        62    146 112 87          62 30 0.5    227 193 166 137            95    193 162 137 111            73    166 137 114 90            57    137    111 90        69    41      95    73    57    41 20 0.6    161 137 117 97            67    137 114 97          78    52    117 97        81    64    40      97      78    64    49    29      67    52    40    29 14 0.7    121 103 88        73      51    103 86      73    59    39      88    73    61    48    30      73      59    48    37    22      51    39    30    22 11 0.8      95  81    69    57      40      81  68    57    46    31      69    57    48    38    24      57      46    38    29    17      40    31    24    17 8 0.9      77  66    56    47      32      66  55    46    38    25      56    46    39    31    20      47      38    31    24    14      32    25    20    14 7 1.0      64  55    47    39      27      55  46    39    32    21      47    39    32    26    16      39      32    26    20    12      27    21    16    12 6 1.1      55  47    40    33      23      47  39    33    27    18      40    33    28    22    14      33      27    22    17    10      23    18    14    10 5 1.2      48  41    35    29      20      41  34    29    24    16      35    29    24    19    12      29      24    19    15    9      20    16    12    9  4 1.3      43  36    31    26      18      36  30    26    21    14      31    26    22    17    11      26      21    17    13    8      18    14    11    8  4 1.4      38  32    28    23      16      32  27    23    19    13      28    23    19    15    10      23      19    15    12    7      16    13    10    7  4 1.5      35  30    25    21      15      30  25    21    17    11      25    21    18    14    9      21      17    14    11    7      15    11    9    7  3 1.6      32  27    23    19      14      27  23    19    16    11      23    19    16    13    8      19      16    13    10    6      14    11    8    6  3 5-32                      1.7      30  25    22    18      13      25  21    18    15    10      22    18    15    12    8      18      15    12    9    6      13    10    8    6  3 1.8      28  24    20    17      12      24  20    17    14      9      20    17    14    11    7      17      14    11    9    5      12    9      7    5  3 1.9      26  22    19    16      11      22  19    16    13      9      19    16    13    11    7      16      13    11    8    5      11    9      7    5  3 May 2020 2.0      25  21    18    15      11      21  18    15    12      8      18    15    13    10    7      15      12    10    8    5      11    8      7    5  3 2.25      22  19    16    14      10      19  16    14    11      8      16    14    11    9      6      14      11    9    7    4      10    8      6    4  2 2.5      21  18    15    13      9      18  15    13    10      7      15    13    11    9      6      13      10    9    7    4      9    7      6    4  2 2.75      20  17    15    12      9      17  14    12    10      7      15    12    10    8      5      12      10    8    6    4      9    7      5    4  2 3.0      19  16    14    12      8      16  14    12    10      6      14    12    10    8      5      12      10    8    6    4      8    6      5    4  2 DO NOT CITE OR QUOTE 3.5      18  16    13    11      8      16  13    11      9      6      13    11    9    8      5      11      9      8    6    4      8    6      5    4  2 4.0      18  15    13    11      8      15  13    11      9      6      13    11    9    7      5      11      9      7    6    4      8    6      5    4  2 MARSSIM 4  In Scenario B the sample size for the WRS test is also used for the Quantile test.
5 The      values were calculated using Equation O-1 and increased by 20 percent for the reasons discussed in Appendix O.
 
MARSSIM                                                                Survey Planning and Design 1 Example 5 illustrates the use of the WRS Test under Scenario B.
Example 5: Use of WRS Test under Scenario B A site has 14 survey units and 1 reference area in a building, and the same measurement method is used to perform measurements in each survey unit and the reference area. The radionuclide is present in background at a level of 100 +/- 15 becquerels/meter squared (Bq/m2) (1). The standard deviation of the radionuclide in the survey area is 40 Bq/m2, based on previous survey results for the same or similar radionuclide distribution. When the estimated standard deviation in the reference area and the survey units are different, the larger value, 40 Bq/m2 in this example, should be used to calculate the relative shift. During the Data Quality Objective process, Scenario B is selected because the release criterion for the site is no residual radioactive material above background. The discrimination limit is selected to be 220 Bq/m2 as a stakeholder agreed-upon starting point for developing an acceptable survey design, and Type I and Type II error values ( and ) of 0.05 are selected.
Determine the number of data points to be obtained from the reference area and from each of the survey units for the statistical tests.
The value of the relative shift for the reference area, , is (220  100)/40, or 3.0. The number of data points can be obtained directly from Table 5.2. For  = 0.05,  = 0.05, and
    = 3.0, a value of 10 is obtained for /2. The table value has already been increased by 20 percent to account for missing or unusable data.
2 5.3.4    Determining Numbers of Data Points for Statistical Tests for Residual Radioactive 3          Material Not Present in Background 4 For the situation where the residual radioactive material is not present in background or is 5 present at such a small fraction of the DCGLW as to be considered insignificant, a background 6 reference area is not necessary. Instead, the radionuclide levels are compared directly with the 7 DCGL value. The general approach closely parallels that used for the situation when the 8 radionuclide is present in background as described in Section 5.3.3. However, the statistical 9 tests differ slightly. The Sign test replaces the WRS test described above.
10 5.3.4.1 Define the Gray Region 11 In Scenario A, the UBGR is equal to the DCGLW (Figure 5.7). The LBGR is typically chosen to 12 represent a conservative (slightly higher) estimate of the residual radioactive material 13 concentration remaining in the survey unit at the beginning of the FSS. If there is no information 14 with which to estimate the residual radioactive material concentration remaining, the LBGR may 15 be initially set to equal one-half of the DCGLW. In Scenario B, the LBGR is equal to zero or the 16 DCGLW, and the UBGR is defined as the DL (Figure 5.8). The DL is a concentration or level of 17 radioactive material that can be reliably distinguished from the LBGR by performing 18 measurements with the devices selected for the survey. The DL defines the rigor of the survey 19 and is determined through negotiations with the regulator. The selection of the appropriate null 20 hypothesis is further discussed in Chapter 8 and Appendix D.
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Survey Planning and Design                                                                  MARSSIM 1 5.3.4.2 Calculate the Relative Shift 2 In Scenario A, the shift is the distance between the LBGR and the DCGLW ( = DCGLW 3  LBGR). In Scenario B, the shift is the distance between the AL and the DL ( = DL  AL).
4 The absolute size of the shift is less important than the relative shift, , where  is an 5 estimate of the variability in the survey unit. The value of  may be obtained from earlier 6 surveys, limited preliminary measurements, or a reasonable estimate. This estimate of 7  includes both the real spatial variability in the quantity being measured and the uncertainty of 8 the measurement method. The relative shift, , is an expression of the resolution of the 9 measurements in units of measurement uncertainty. Values of the relative shift that are less 10 than 1 will result in a large number of measurements needed to demonstrate compliance.
11 Section 5.3.3.2 provides more detail on the relative shift.
12 Table 5.3 provides a list of the number of data points used to demonstrate compliance using the 13 Sign test for selected values of , , and . The values listed in Table 5.3 represent the 14 number of measurements to be performed in each survey unit. These values were calculated 15 using Equation O-1 in Appendix O and increased by 20 percent to account for missing or 16 unusable data and uncertainty in the calculated value of . Example 6 illustrates the use of the 17 Sign Test under Scenario A.
Example 6: Use of Sign Test Under Scenario A A site has one survey unit. The wide-area derived concentration guideline level for the radionuclide of interest is 140 becquerels/kilogram (Bq/kg) (3.9 picocuries/gram [pCi/g]) in soil.
The radionuclide is not present in background; data from previous investigations indicate average residual radioactive material at the survey unit of 110 +/- 3.7 (1 ) Bq/kg (3.7 +/- 0.1 pCi/g). Using Scenario A, the lower bound of the gray region was selected to be 110 Bq/kg. A value of 0.05 is next selected for the probability of Type I decision errors (), and a value of 0.01 is selected for the probability of Type II decision errors () based on the survey objectives. Determine the number of data points to be obtained from the survey unit for the statistical tests.
The value of the relative shift, , is (140  110)/3.7, or 8.1. The number of data points can be obtained directly from Table 5.3. For  = 0.05,  = 0.01, and  > 3.0, a value of 20 is obtained for . The table value has already been increased by 20 percent to account for missing or unusable data and uncertainty in the calculated value of .
18 NUREG-1575, Revision 2                            5-34                                      May 2020 INTERNAL AGENCY REVIEW DRAFT                                              DO NOT CITE OR QUOTE
 
19      Table 5.3: Values of  for Use with the Sign Test 6 May 2020 MARSSIM
                                                  = 0.01                          = 0.025                          = 0.05                            = 0.10                    = 0.25
                                /
0.01 0.025 0.05 0.10      0.25    0.01 0.025 0.05 0.10      0.25    0.01 0.025 0.05 0.10      0.25    0.01  0.025 0.05 0.10 0.25 0.01 0.025 0.05 0.10 0.25 0.1    4,095 3,476 2,984 2,463  1,704  3,476 2,907 2,459 1,989  1,313  2,984 2,459 2,048 1,620  1,018  2,463  1,989 1,620 1,244 725 1,704 1,313 1,018 725 345 0.2    1,035 879 754 623          431    879 735 622 503          333    754 622 518 410          258    623    503 410 315 184 431 333 258 184 88 0.3      468 398 341 282          195    398 333 281 227          150    341 281 234 185          117    282    227 185 143 83 195 150 117 83                40 INTERNAL AGENCY REVIEW DRAFT 0.4      270 230 197 162          113    230 1921 162 131          87    197 162 136 107            68    162    131 107 82        48 113 87        68    48 23 0.5      178 152 130 107            75    152 126 107 87            58    130 107 89          71    45    107      87    71    54  33  75    58    45    33 16 0.6      129 110 94        77      54    110 92      77    63    42      94    77    65    52    33      77      63    52    40  23  54    42    33    23 11 0.7      99  83    72    59      41      83  70    59    48    33      72    59    50    40    26      59      48    40    30  18  41    33    26    18 9 0.8      80  68    58    48      34      68  57    48    39    26      58    48    40    32    21      48      39    32    24  15  34    26    21    15 8 0.9      66  57    48    40      28      57  47    40    33    22      48    40    34    27    17      40      33    27    21  12  28    22    17    12 6 1.0      57  48    41    34      24      48  40    34    28    18      41    34    29    23    15      34      28    23    18  11  24    18    15    11 5 1.1      50  42    36    30      21      42  35    30    24    17      36    30    26    21    14      30      24    21    16  10  21    17    14    10 5 1.2      45  38    33    27      20      38  32    27    22    15      33    27    23    18    12      27      22    18    15  9    20    15    12    9  5 1.3      41  35    30    26      17      35  29    24    21    14      30    24    21    17    11      26      21    17    14  8    17    14    11    8  4 1.4      38  33    28    23      16      33  27    23    18    12      28    23    20    16    10      23      18    16    12  8    16    12    10    8  4 5-35                1.5      35  30    27    22      15      30  26    22    17    12      27    22    18    15    10      22      17    15    11  8    15    12    10    8  4 1.6      34  29    24    21      15      29  24    21    17    11      24    21    17    14    9      21      17    14    11  6    15    11    9    6  4 1.7      33  28    24    20      14      28  23    20    16    11      24    20    17    14    9      20      16    14    10  6    14    11    9    6  4 NURGE-1575, Revision 2 1.8      32  27    23    20      14      27  22    20    16    11      23    20    16    12    9      20      16    12    10  6    14    11    9    6  4 Survey Planning and Design 1.9      30  26    22    18      14      26  22    18    15    10      22    18    16    12    9      18      15    12    10  6    14    10    9    6  4 2.0      29  26    22    18      12      26  21    18    15    10      22    18    15    12    8      18      15    12    10  6    12    10    8    6  3 2.5      28  23    21    17      12      23  20    17    14    10      21    17    15    11    8      17      14    11    9  5    12    10    8    5  3 3.0      27  23    20    17      12      23  20    17    14      9      20    17    14    11    8      17      14    11    9  5    12    9      8    5  3 DO NOT CITE OR QUOTE 20 6 The  values were calculated using Equation O-2 and increased by 20 percent for the reasons discussed in Appendix O.
 
Survey Planning and Design                                                                MARSSIM 1 5.3.5  Determining the Number of Discrete Data Points for Small Areas of Elevated 2        Activity 3 As described in Section 4.2.5, the treatment of elevated areas of radioactive material is 4 determined strictly through requirements of regulatory agencies and is beyond the scope of 5 MARSSIM. A technically sound approach should be used for the derivation of the DCGL for the 6 Elevated Measurement Comparison (DCGLEMC) values. The methodology presented in 7 MARSSIM of using the unity rule to consider the combined impact of each elevated area is one 8 conservative approach to assess areas of elevated radioactive materials. See Figure 5.6 for a 9 summary of data needs for areas of elevated activity.
10 The statistical tests described throughout Sections 5.3.3 and 5.3.4 (see also Chapter 8) 11 evaluate whether the residual radioactive material in an area exceeds the DCGLW for 12 radionuclide concentrations that are approximately uniform across the survey unit. In addition, 13 there should be a reasonable level of assurance that any small areas of elevated concentrations 14 of residual radioactive material that could be significant relative to the DCGLEMC are not missed 15 during the FSS. The statistical tests introduced in the previous sections may not successfully 16 detect small areas of elevated concentrations of radioactive material. Instead, systematic 17 measurements or samples are made at locations defined by a systematic grid, in conjunction 18 with surface scanning. These results are used to obtain adequate assurance that small areas of 19 elevated concentrations of radioactive material are below the DCGLEMC and the release criteria 20 are met. The procedure is applicable for all radionuclides, regardless of whether they are 21 present in background and is implemented for Class 1 survey units.
22 5.3.5.1 Determine if Additional Data Points are Needed 23 Identify the number of survey data points needed for the statistical tests discussed in 24 Sections 5.3.3 or 5.3.4 (the appropriate section is determined by whether the radionuclide is 25 present in background). These data points are then positioned throughout the survey unit by 26 randomly selecting a start point and establishing a systematic pattern. This systematic sampling 27 grid may be either triangular or rectangular. The triangular grid is generally more efficient for 28 locating small areas of elevated activity. Appendix D includes a brief discussion on the 29 efficiency of triangular and rectangular grids for locating areas of elevated activity. A more 30 detailed discussion is provided by EPA (EPA 1994b).
31 The number of calculated survey locations, n, and the total area of the survey unit, , are used 32 to determine the grid spacing, , of the systematic sampling pattern, using Equations 5-1 33 and 5-2.
(survey unit)
                                  =                    for a triangular grid                  (5-1) 0.866 (survey unit)
                                =                    for a rectangular grid                  (5-2)
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MARSSIM                                                                            Survey Planning and Design 1 The grid area that is bounded by these survey locations is given by Equations 5-3 and 5-4. The 2 risk of not sampling a circular areaequal to A (grid area)of elevated activity by use of a 3 random-start grid pattern is illustrated in Figure D.7 in Appendix D.
(grid area) = 0.866 2 for a triangular grid                            (5-3)
(grid area) = 2 for a rectangular grid                              (5-4) 4 The DCGLEMC that corresponds to this size of the area of elevated activity ( ) is obtained from 5 specific regulatory agency guidance. After using the grid area calculated in Equation 5-3 or 5-4 6 to determine the DCGLEMC for a specific radionuclide, the required minimum detectable 7 concentration (MDC) of the scan procedure needed to detect an area of elevated activity is 8 given by Equation 5-5.
Scan MDC (required) = DCGLEMC                                          (5-5) 9 The actual scan MDCs of scanning techniques are then determined for the available 10 instrumentation (see Sections 6.3.2 and 6.6). The actual scan MDC of the selected scanning 11 technique is compared to the required scan MDC. If the actual scan MDC is less than the 12 required scan MDC, no additional sampling points are necessary for assessment of small areas 13 of elevated activity. In other words, the scanning technique exhibits adequate detection 14 capability to detect small areas of elevated activity.
15 Revisions 0 and 1 of MARSSIM (published in 1998 and 2000, respectively) included the 16 calculation of an area factor 7 as an intermediate step in the determination of the required scan 17 MDC. The use of an area factor is not necessary if DCGLEMC is tabulated directly as a function 18 of the area of radioactive material. To simplify the determination of the required scan MDC, the 19 use of the area factor as an intermediate calculation is not included in this revision of 20 MARSSIM. The area factor can still be used if the ratio of the DCGLEMC to the DCGLW is known 21 and will produce the same results as the approach described in the current revision of 22 MARSSIM.
23 5.3.5.2 Calculate the Required Grid Spacing and Number of Data Points 24 If the actual scan MDC is greater than the required scan MDC (i.e., the available scan detection 25 capability is not sufficient to detect small areas of elevated activity), then it is necessary to 26 calculate the DCGLEMC that corresponds to the actual scan MDC using Equation 5-6.
DCGLEMC = Scan MDC (actual)                                            (5-6) 27 The size of the area of elevated activity ( ) that corresponds to this DCGLEMC is then obtained 28 from specific regulatory agency guidance. The required number of data points for assessing 7 The area factor,  , is defined as the ratio of the DCGL EMC to the DCGLW as a function of the grid area and relates the required scan MDC to the DCGLW using the equation: Scan MDC (required) =  x DCGLW .
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Survey Planning and Design                                                                                MARSSIM 1 small areas of elevated activity ( ) can then be determined by dividing the area of elevated 2 activity ( ) into the survey unit area using Equation 5-7.
A (survey unit)
                                                    =                                                        (5-7)
(grid unit) 3 The calculated number of measurement or sampling locations,  , is used to determine a 4 revised spacing,  , of the systematic pattern, using Equations 5-8 and 5-9.
(survey unit)
                                    =                        for a triangular grid                        (5-8) 0.866 (survey unit)
                                  =                        for a rectangular grid                        (5-9) 5 The distance between measurement/sampling locations should generally be rounded down to 6 the nearest distance that can be conveniently measured in the field. This value of  is then 7 used to determine the measurement locations as described in Section 5.3.7. The Sign, WRS, 8 and quantile tests are performed using the larger number of data points,  . Figure 5.6 9 provides a concise overview of the procedure used to identify data needs for the assessment of 10 small areas of elevated activity.
11 If residual radioactive material is found in an isolated area of elevated activity in addition to 12 residual radioactive material distributed relatively uniformly across the survey unit, the 13 information in Section 8.6.2 can be used to ensure that the total dose or risk does not exceed 14 the release criteria. If there is more than one area of elevated activity, a conservative method is 15 to include a separate term in the formula for each; however, this method may violate 16 assumptions used in the pathway modeling process if adjustments are not made to the 17 modeling. Specifically, if a receptor is assumed to be located directly above one area of 18 elevated activity for the full occupancy period, that same receptor cannot realistically also be 19 assumed to be located directly above a separate area of elevated activity for the full occupancy 20 period associated with the exposure scenario 8. As an alternative, the dose or risk due to the 21 actual residual radioactive material can be modeled if there is an appropriate exposure pathway 22 model available. Note that these considerations generally apply only to Class 1 survey units, 23 since areas of elevated activity should not exist in Class 2 or Class 3 survey units.
24 When the detection limit of the scanning technique is very large relative to the DCGLEMC, the 25 number of measurements estimated to demonstrate compliance using the statistical tests may 26 become unreasonably large. In this situation, evaluate the survey objectives and considerations.
27 These considerations may include the survey design and measurement methodology, exposure 8 By default, RESRAD assumes that the receptor spends 50 percent of the time indoors and 25 percent of his time outdoors; without further adjustment, and if two areas are considered, the receptor would spent 100 percent of the time indoors and another 50 percent of the time outdoors for a total time of 150 percent of what would typically be assumed for the exposure scenario.
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MARSSIM                                                                          Survey Planning and Design 1 pathway modeling assumptions and parameter values used to determine the DCGLs, HSA 2 conclusions concerning source terms and radionuclide distributions, and the results of scoping 3 and characterization surveys. In most cases, the result of this evaluation is not expected to 4 justify an unreasonably large number of measurements. Example 7 provides an example of 5 how to determine whether additional data points are required to ensure the actual scan MDC is 6 less than or equal to the required scan MDC.
Example 7: Example Determination Whether Additional Data Points Are Required A Class 1 land area survey unit of 1,500 square meters (m2) is potentially affected by residual radioactive material consisting of cobalt-60 (60Co). The wide-area derived concentration guideline level value for 60Co is 110 becquerels/kilogram (Bq/kg; 3 picocuries/gram [pCi/g]),
and the scan detection capability for this radionuclide has been determined to be 150 Bq/kg (4 pCi/g). The table below provides the derived concentration guideline level obtained using the Elevated Measurement Comparison for different grid areas:
Grid Area        DCGLEMC (m2)          (Bq/kg) 1        1,070 3          480 10            230 30            160 100            130 300            120 1,000            120 3,000            110 10,000            110 Abbreviations: m = meter; DCGLEMC = derived concentration guideline level obtained using the Elevated Minimum Comparison; Bq = becquerel; kg = kilogram.
Calculations indicate the number of data points needed for statistical testing is 27. The distance between measurement locations for this number of data points and the given land area is 8 m, as illustrated in the application of Equation 5-1:
(survey unit)      1,500 m2
                      =                  =                = 8.0 m for a triangular grid 0.866          0.866x27 The grid area encompassed by a triangular sampling pattern of 8 m is approximately 55.4 m2 as calculated using Equation 5-3:
(grid area) = 0.866 2 = 0.866 (8.0 m)2 = 55.4 m2 The DCGLEMC for a grid area of 55.4 m2 is determined by interpolation to be 150 Bq/kg:
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Survey Planning and Design                                                            MARSSIM 55.4 m2  30 m2 160 Bq/kg +                    (130 Bq/kg  160 Bq/kg) = 150 Bq/kg 100 m2  30 m2 The acceptable minimum detectable concentration (MDC) of the scan procedure needed to detect an area of elevated activity in a 55.4 m2 area is therefore given by Equation 5-5:
Scan MDC (required) = DCGLEMC = 150 Bq/kg Because the detection capability of the procedure to be used (150 Bq/kg) is equal to or less than the required Scan MDC, no additional data points are needed to demonstrate compliance with the elevated measurement comparison criteria.
1 Example 8 provides another example of how to determine if additional data points are required 2 to ensure the actual scan MDC is less than or equal to the required scan MDC, including how to 3 calculate the number of required data points when the actual scan MDC is greater than the 4 required scan MDC.
5 Example 8: Example Determination Whether Additional Data Points Are Required 6 A Class 1 land area survey unit of 1,500 square meters (m2) is potentially affected by residual 7 radioactive material consisting of 60Co. The wide-area derived concentration guideline level for 8 cobalt-60 (60Co) is 110 becquerels/kilogram (Bq/kg; 3 picocuries/gram [pCi/g]). The table below 9 provides the derived concentration guideline level obtained using the Elevated Measurement 10 Comparison for different grid areas:
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MARSSIM                                                                        Survey Planning and Design Grid Area        DCGLEMC (m2)            (Bq/kg) 1          1,070 3            480 10            230 30            160 100            130 300            120 1,000            120 3,000            110 10,000              110 Abbreviations: m = meter; DCGLEMC = derived concentration guideline level obtained using the Elevated Minimum Comparison; Bq = becquerel; kg = kilogram.
In contrast to Example 7, the scan detection capability for this radionuclide has been determined to be 170 Bq/kg (4.6 pCi/g). Calculations indicate the number of data points needed for statistical testing is 15. The distance between measurement locations for this number of data points and the given land area is 10 m, as illustrated in the application of Equation 5-1:
(survey unit)      1,500 m2
                  =                  =                = 10.7 m for a triangular grid 0.866          0.866x15 The grid area encompassed by a triangular sampling pattern of 10 m is approximately 86.6 m2, as calculated using Equation 5-3:
(grid area) = 0.866 2 = 0.866 (10.7 m)2 = 99.1 m2 The DCGLEMC for a grid area of 99.1 m2 is determined by interpolation to be 130 Bq/kg:
99.1 m2  30 m2 160 Bq/kg +                      (130 Bq/kg  160 Bq/kg) = 130 Bq/kg 100 m2  30 m2 The required scan minimum detectable concentration (MDC) for that grid area is therefore also 130 Bq/kg:
Scan MDC (required) = DCGLEMC = 130 Bqkg Because the actual scan MDC of the procedure to be used (170 Bq/kg) is greater than the required scan MDC, the data points obtained for the statistical testing may not be sufficient to demonstrate compliance using the elevated measurement comparison. The grid area corresponding to a DCGLEMC of 170 Bq/kg is determined by interpolation to be 27 m2:
170 Bq/kg  160 Bq/kg 30 m2 +                              10 m2  30 m2  = 27 m2 230 Bq/kg  160 Bq/kg May 2020                                            5-41                          NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                          DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                    MARSSIM The number of samples required to account for areas of elevated activity ( ) is calculated using Equation 5-7:
A (survey unit)      1,500 m2
                            =                    =          = 56 measurements (grid unit)    27 m2 The triangular grid spacing required to account for areas of elevated activity ( ) is calculated using Equation 5-8:
(survey unit)          1500 m2
                  =                      =              = 5.5 m for a triangular grid 0.866          0.866 x 56 The number of data points required increased from 15 to 56, and the grid spacing decreased from 10.7 m to 5.5 m.
1 5.3.6  Determining the Scan Area 2 The use of direct measurements or sampling in combination with separate scans of the area is 3 necessary when the scanning instrument and technique have sufficient detection capability to 4 identify areas of elevated concentrations of radioactive material, but insufficient detection 5 capability to quantify the average concentration of radioactive material in the survey unit. In 6 instances where the measurement method has sufficient detection capability to meet the MQOs 7 to both quantify the average concentration of radioactive material in the survey unit and identify 8 areas of elevated concentrations of radioactive material, a scan-only survey can be considered.
9 Similar in principle to a scan-only survey is a series of direct measurements that have the 10 detection capability to meet the MQOs to both quantify the average concentration of radioactive 11 material in the survey unit and identify areas of elevated concentrations of radioactive material.
12 5.3.6.1  Scan-Only Surveys 13 During scan-only surveys, a large number of discrete scan measurements are taken and 14 analyzed; this approach is greatly facilitated by the use of scan systems that automatically 15 record scan measurements and location. These systems typically utilize GPS or other position 16 determinations in conjunction with radiological measurements, with both the radiological and 17 locational data being automatically recorded. These techniques permit the convenient 18 accumulation, storage, and display of hundreds or thousands of scan data points for a survey 19 unit.
20 Scan-only surveys will likely require site-specific validation samples to ensure that the method 21 can reliably detect concentrations at the DCGLW under the conditions expected at the site. This 22 validation can be accomplished at any point in the RSSI process (post-remediation, if 23 remediation is performed). Consult with your regulator for guidance on the level of effort needed 24 to validate scan-only surveys.
25 Scan-only surveys generally cover a much larger portion of the survey unit than traditional 26 discrete sampling or measurement. A similar concept is found in a series of direct NUREG-1575, Revision 2                                  5-42                                  May 2020 DRAFT FOR PUBLIC COMMENT                                                      DO NOT CITE OR QUOTE
 
MARSSIM                                                                              Survey Planning and Design 1 measurements, where the field of view of the direct measurements covers a statistically 2 significant portion of the survey unit (i.e., 10 percent or more). 9 3 However, a scan-only approach should be used only for circumstances where the measurement 4 method has sufficient detection capability to meet the MQOs to both quantify the average 5 concentration of radioactive material in the survey unit and identify areas of elevated 6 concentrations of radioactive material. To ensure that this is the case, the scan MDC (for the 7 scan system) should be less than 50 percent of the DCGLW. The scan-only methodology will 8 require validation, which likely requires collecting some percentage of samples for laboratory 9 analysis to compare with results from the same location. Other MQOs should be met as well, 10 including the MQO for measurement method uncertainty at the DCGLW.
11 In general, when utilizing a scan-only survey approach, the anticipated measurement method 12 uncertainty is expected to be higher than traditional scan and sampling procedures. Therefore, a 13 maximum scan coverage (e.g., 100 percent) should always be achieved in Class 1 areas when 14 utilizing this approach. The percentages of Class 2 or Class 3 areas that should be scanned is 15 10 percent or the result using Equation 5-10, whichever is larger:
(10  )
Scan Area =                      x 100%                                  (5-10) 10 16 Scanning a greater percentage than that calculated above is always acceptable. When 17 performing scan-only surveys, the following must be considered and addressed in survey plans:
18
* Perform quality control procedures, such as evaluating measurement method uncertainty by 19      performing replicate scans over a prescribed portion of the site and performing reference 20      standard checks at a prescribed frequency.
21
* Evaluate the extent to which alpha and beta radiation in the surface may impact scan-only 22      survey results.
23
* Determine the number and type of validation samples to establish a correlation between 24      scan-only and laboratory results.
25 5.3.6.2 Scanning and Sampling 26 When scanning is done in combination with direct measurements or sampling, the scanning 27 instrument and technique must have detection capabilities to meet the MQOs to identify areas 28 of elevated concentrations of radioactive material. This differs from the requirements for scan-29 only surveys that must have detection capabilities to both identify areas of elevated 30 concentrations of radioactive material and quantify the average concentration of radioactive 31 material in the survey unit.
9 In the Multi-Agency Radiation Survey and Assessment of Materials and Equipment (MARSAME) Manual, a direct measurement survey covering a statistically significant portion of the survey unit was referred to as an in situ survey type; in MARSSIM, this survey type is incorporated into scan-only surveys.
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Survey Planning and Design                                                                MARSSIM 1 The percentage of the area that needs to be scanned depends on the classification of the 2 survey unit. For Class 1 survey units, 100 percent of the area should be scanned. The 3 percentages of Class 2 or Class 3 areas are scanned according to Equation 5-10. Scanning a 4 greater percentage than that calculated above for Class 2 or Class 3 areas is always 5 acceptable.
6 The detection capability for scanning techniques used in Class 2 and Class 3 areas is not tied to 7 the area between measurement locations like they are in a Class 1 area (see Section 5.3.5).
8 The scanning techniques selected should represent the best reasonable effort based on the 9 survey objectives. Structure surfaces are generally scanned for alpha-, beta-, and gamma-10 emitting radionuclides. In contrast, scanning for alpha or beta emitters for land area survey units 11 is generally not considered effective because of problems with attenuation and media 12 interferences. If one can reasonably expect to find any residual radioactive material, it is prudent 13 to perform a judgment scanning survey.
14 5.3.7  Determining Survey Locations 15 Like the required scanning percentages, the determination of discrete survey locations for the 16 direct measurements or the collection of samples depends on the classification of the survey 17 unit. The method for determining survey locations for land areas and structure surfaces is 18 described below.
19 5.3.7.1 Survey Locations for Discrete Measurements and Samples 20 A scale drawing of the survey unit is prepared, along with the overlying planar reference 21 coordinate system or grid system. Any location within the survey area is thus identifiable by a 22 unique set of coordinates. The maximum length, X, and width, Y, dimensions of the survey unit 23 are then determined. Identifying and documenting a specific location for each measurement 24 performed is an important part of an FSS to ensure that measurements can be reproduced if 25 necessary. The reference coordinate system described in Section 4.9.5 provides a method for 26 relating measurements to a specific location within a survey unit. Systems utilizing GPS 27 technology and data logging software are widely available to identify and track survey 28 dimensions, sampling locations, and locations associated with specific scan results.
29 Land Areas 30 Measurements and samples in Class 3 survey units and reference areas are usually taken at 31 random locations. These locations are determined by generating sets of random numbers 32 (two values, representing the X axis and Y axis distances). Random numbers can be obtained 33 from mathematical tables, including Table I.11 in Appendix I, or generated by calculator or 34 computer. Sufficient sets of numbers will be needed to identify the total number of survey 35 locations established for the survey unit. Each set of random numbers is multiplied by the 36 appropriate survey unit dimension to provide coordinates, relative to the origin of the survey unit 37 reference grid pattern. Coordinates identified in this manner that do not fall within the survey unit 38 area or that cannot be surveyed because of site conditions are replaced with other survey points 39 determined in the same manner. Example 9 provides an example of a random sampling 40 pattern.
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MARSSIM                                                              Survey Planning and Design Example 9: Random Sampling Pattern In this example, eight data points were identified using the appropriate table (Table 5.2 or Table 5.3). The locations of these points were determined using the table of random numbers found in Appendix I, Table I.11.
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Survey Planning and Design                                                                MARSSIM 1 Class 2 areas are surveyed on a random-start systematic pattern. The number of calculated 2 survey locations, , based on the statistical tests, is used to determine the spacing, , of a 3 systematic pattern as specified in Equations 5-1 and 5-2.
4 After  is determined, a random start location is identified, as described previously, for a survey 5 pattern starting location. Beginning at the random start location, a row of points is identified 6 parallel to the X-axis at intervals of .
7 For a triangular grid, a second row of points is then developed, parallel to the first row, at a 8 distance of 0.866 x  from the first row. Survey points along that second row are midway (on the 9 X-axis) between the points on the first row. This process is repeated to identify a pattern of 10 survey locations throughout the affected survey unit. If identified points fall outside the survey 11 unit or at locations that cannot be surveyed, additional points are determined using the random 12 process described above until the desired total number of points is identified.
13 For Class 1 areas, a systematic pattern having dimensions determined in Section 5.3.6 is 14 installed on the survey unit. The starting point for this pattern is selected at random, as 15 described above for Class 2 areas. The same process as described above for Class 2 areas 16 applies to Class 1. Example 10 provides an illustration of a triangular systematic pattern in an 17 outdoor Class 2 survey unit.
Example 10: Illustration of a Triangular Systematic Pattern in an Outdoor Class 2 Survey Unit An example of a triangular survey pattern is shown below. In this example, the statistical test calculations estimate 20 samples (Table 5.3,  = 0.01,  = 0.05, / > 3.0). The random-start coordinates were 27E, 53N. The grid spacing () was calculated using Equation 5-3.
2 5,100 m
                                          =              = 17 m 0.866 x 20 Two points were identified on a row parallel to the X-axis, each 17 meters (m) from the starting point. The subsequent rows were positioned 0.866 x , or 15 m, from the initial row.
This random-start triangular sampling process resulted in 21 sampling locations, one of which was difficult to assess because of the building location, which yields the desired number of data points.
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MARSSIM                                                                  Survey Planning and Design 1 Structure Surfaces 2 All structure surfaces for a specific survey unit are included on a single reference grid system for 3 purposes of identifying survey locations. The same methods as described above for land areas 4 are then used to locate survey points for all classifications of areas.
5 In addition to the survey locations identified for statistical evaluations and elevated 6 measurement comparisons, data may be obtained from judgment locations that are selected 7 because of unusual appearance, location relative to areas affected by residual radioactive 8 material, high potential for residual radioactive material, general supplemental information, etc.
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Survey Planning and Design                                                                MARSSIM 1 Data points selected based on professional judgment are not included with the data points from 2 the random-start triangular grid for statistical evaluations; instead they are compared individually 3 with the established DCGLs and conditions. Measurement locations selected on the basis of 4 professional judgment cannot be considered representative of the survey unit, a necessary 5 condition if the statistical tests described in Chapter 8 are used.
6 5.3.7.2 Survey Locations for Scans 7 Like the determination of the location of discrete measurements or samples, the determination 8 of survey locations for scans depends on the classification of the survey unit.
9 Class 1 Areas 10 For Class 1 areas, scans are intended to detect small areas of elevated activity that are not 11 detected by the measurements using the systematic pattern (Section 5.3.5). This is the reason 12 for recommending 100 percent coverage for the scanning survey. One-hundred percent 13 coverage means that the entire accessible surface area of the survey unit is covered by the field 14 of view of the scanning instrument. If the field of view is 2 m wide, the survey instrument can be 15 moved along parallel paths 2 m apart to provide 100 percent coverage. If the field of view of the 16 detector is 5 centimeters (cm), the parallel paths should be 5 cm apart.
17 Class 2 Areas 18 Class 2 survey units have a lower probability for areas of elevated activity than Class 1 survey 19 units, but some portions of the survey unit may have a higher potential than others. Judgment 20 scanning surveys focus on the portions of the survey unit with the highest probability for areas 21 of elevated activity. If the entire survey unit has an equal probability for areas of elevated 22 activity, or the judgment scans dont cover at the required scanning percentage of the area, 23 systematic scans along transects of the survey unit or scanning surveys of randomly selected 24 grid blocks are performed.
25 Class 3 Areas 26 Class 3 areas may be uniformly scanned for radiation emitted from the radionuclides of interest, 27 or the scanning may be performed in areas with the greatest potential for residual radioactive 28 material (e.g., corners, ditches, and drains) based on professional judgment and the objectives 29 of the survey. Such recommendations are typically provided by a health physics professional 30 with radiation survey experience. This provides a qualitative level of confidence that no areas of 31 elevated activity were missed by the random measurements or that there were no errors made 32 in the classification of the area. In some cases, a combination of these approaches may be the 33 most appropriate.
34 5.3.8    Determining Investigation Levels 35 An important aspect of the FSS is the design and implementation of investigation levels.
36 Investigation levels are radionuclide-specific levels of radioactive material used to indicate when 37 additional investigations may be necessary. Investigation levels also serve as a quality control 38 check to determine when a measurement process begins to get out of control. For example, a 39 measurement that exceeds the investigation level may indicate that the survey unit has been NUREG-1575, Revision 2                            5-48                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                            Survey Planning and Design 1 improperly classified (see Section 4.6), or it may indicate a failing instrument. Typically, 2 investigation levels are set as part of the DQO process.
3 When an investigation level is exceeded, the first step is to confirm that the initial measurement 4 or sample actually exceeds the particular investigation level. This may involve taking further 5 measurements to determine that the area and level of the elevated residual radioactive material 6 are such that the resulting dose or risk meets the release criteria. Rather thanor in addition 7 totaking further measurements, the investigation may involve assessing the adequacy of the 8 exposure pathway model used to obtain the DCGLs and area factors, as well as the consistency 9 of the results obtained with the HSA and the scoping, characterization, and RAS surveys.
10 Depending on the results of the investigation actions, the survey unit may require 11 reclassification, remediation, or resurvey. Table 5.4 illustrates an example of how investigation 12 levels can be developed.
13 Table 5.4: Example FSS Investigation Levels Survey Unit            Flag Direct Measurement or                Flag Scanning Measurement Result Classification            Sample Result When                                      When Class 1                                                          > DCGLEMC for the area bounded by four
                        > DCGLEMC or                                  adjacent systematic grid measurement points to determine the DCGLEMC (when
                        > DCGLW and > a statistical                  a traditional MARSSIM approach is parameter-based value                        utilized), or for the area bounded by an acceptable elevated area size (when a scan-only approach is utilized)
Class 2            > DCGLW                                      > DCGLW or > scan MDC Class 3            > fraction of DCGLW                          > DCGLW or > scan MDC 14 Abbreviations: DCGLEMC is the derived concentration guideline level (DCGL) determined with the Elevated 15 Measurement Compairson; DCGLW is the wide-area DCGL.
16 When determining an investigation level using a statistical-based parameter (e.g., standard 17 deviation) one should consider survey objectives, underlying radionuclide distributions, and an 18 understanding of corresponding types (e.g., normal, lognormal, non-parametric), descriptors 19 (e.g., standard deviation, mean, median), population stratifications (i.e., subgroups), and other 20 prior survey and historical information. For example, a level might be arbitrarily established at 21 the mean + 3s, where s is the standard deviation of the survey unit, assuming a normal 22 distribution. A higher value might be used if locating discrete sources of higher activity was a 23 primary survey objective. By the time the FSS is conducted, survey units should be defined.
24 Estimates of the mean, variance, and standard deviation of the radionuclide activity levels within 25 the survey units should also be available.
26 For a Class 1 survey unit, measurements above the DCGLW are not necessarily unexpected.
27 However, a measurement above the DCGLW at one of the discrete measurement locations 28 might be considered unusual if it were much higher than all of the other discrete measurements.
29 Thus, any discrete measurement that is both above the DCGLW and above the statistical-based 30 parameter for the measurements should be investigated further. Any measurement, either at a 31 discrete location or from a scan that is above the DCGLEMC should also be flagged for further 32 investigation. When a traditional MARSSIM approach (scanning with direct measurements 33 and/or samples) is utilized, the DCGLEMC should be established for the largest (worst case)
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Survey Planning and Design                                                                MARSSIM 1 potential elevated measurement area (the area bounded by four sampling grid measurement 2 points). This largest potential elevated area is also the survey unit area divided by the number of 3 measurements or samples (for the systematic sampling grid). When a scan-only approach is 4 utilized, it is important that an appropriate size for a potential elevated area and associated 5 DCGLEMC be established as a part of the DQO process and in agreement with the regulator.
6 In Class 2 or Class 3 areas, neither measurements above the DCGLW nor areas of elevated 7 activity are expected. Any measurement at a discrete location exceeding the DCGLW in these 8 areas should be flagged for further investigation. Because the survey design for Class 2 and 9 Class 3 survey units is not driven by the EMC, the scan MDC might exceed the DCGLW. In this 10 case, any indication of residual radioactive material during the scan would warrant further 11 investigation.
12 When it is not feasible to obtain a scan MDC below the DCGLW, the basis for using the 13 DCGLEMC or an investigation level above the DCGLW in Table 5.4 for Class 2 and Class 3 areas 14 may be necessary but should be justified in survey planning documents. For example, where 15 there is high uncertainty in the reported scan MDC, more conservative criteria would be 16 warranted.
17 Similarly, data quality assessment (DQA) for scanning may warrant a more conservative flag, as 18 would greater uncertainty from HSA or other surveys on the size of potential areas of elevated 19 activity. In some cases, it may even be necessary to agree in advance with the regulatory 20 agency on which site-specific investigation will be used if other than those presented in 21 Table 5.4.
22 Because there is a low expectation for residual radioactive material in a Class 3 area, it may be 23 prudent to investigate any measurement exceeding even a fraction of the DCGLW. The level 24 selected in these situations should be commensurate with the potential exposures at the site, 25 the radionuclides of concern, and the measurement and scanning methods chosen. This level 26 should be set using the DQO Process during the survey design phase of the Data Life Cycle. In 27 some cases, the user may also wish to follow this procedure for Class 2 and even Class 1 28 survey units.
29 5.3.9    Developing an Integrated Survey Strategy 30 The final step in survey design is to integrate the survey techniques (Chapter 6) with the 31 number of measurements and measurement spacing, with the amount of scanning determined 32 earlier in this chapter. This integration, along with the information provided in other portions of 33 this manual, produce an overall strategy for performing the survey. The survey design may 34 consist of scan-only, or a combination of scans with sampling or direct measurements.
35 Table 5.5 provides a summary of the recommended survey coverage for structures and land 36 areas. This survey coverage for different areas is the subject of this section.
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MARSSIM                                                                        Survey Planning and Design 1 Table 5.5: Recommended Survey Coverage for Structures and Land Areas Scanning and Direct Measurements and/or                  Scan-Only Survey Area                                Sampling Survey Classification                                    Direct Measurements              Scanning Scanning or Samples)
Class 1              100%                        Number of data points      100%
from statistical tests (Sections 5.3.3 and 5.3.4); additional measurements may be necessary for small areas of elevated activity (Section 5.3.5)
Class 2              10-100%                      Number of data points      10-100%
from statistical tests Systematic and Judgment (Sections 5.3.3 and              Systematic and Judgment 5.3.4)
                          "Scan Area"=                                            "Scan Area"=
(10  )                                              (10  )
x 100%                                                x 100%
10                                                      10 Class 3              Judgment                    Number of data points      "Scan Area"=
from statistical tests        (10  )
(Sections 5.3.3 and 5.3.4)                x 100%
10 Judgment 2 Abbreviation:  represents the relative shift.
3 For surveys in which discrete measurements or samples are taken, random measurement 4 patterns are generally used for Class 3 survey units to ensure that the measurements are 5 independent and support the assumptions of the statistical tests. Systematic grids are used for 6 Class 2 survey units because there is an increased probability of small areas of elevated 7 activity. The use of a systematic grid allows the decision maker to draw conclusions about the 8 size of the potential areas of elevated activity based on the area between measurement 9 locations. The random starting point of the grid provides an unbiased method for obtaining 10 measurement locations to be used in the statistical tests. Class 1 survey units have the highest 11 potential for small areas of elevated activity, so the areas between measurement locations 12 might need to be adjusted to ensure that these areas can be detected by scanning techniques.
13 MARSSIM allows the use of both sampling (where a sample is collected and sent to an 14 analytical laboratory, on-site or off-site) and direct measurements (fixed measurement taken in 15 the field by an in situ gamma spectroscopy or beta scintillation meter, for example.) It is 16 important to consider the required MQOs for the survey and ensure that the measurement 17 method chosen meets those criteria. Some direct measurement methods may not be 18 appropriate for some radionuclides in land areas.
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Survey Planning and Design                                                              MARSSIM 1 The objectives of the scanning surveys are different. Scanning is used to identify locations 2 within the survey unit that exceed the investigation level. These locations are marked and/or 3 receive additional investigations to determine the concentration, area, and extent of the residual 4 radioactive material.
5 Scanning measurements can also be used in place of the sampling or direct measurements 6 when the detection capability is sufficient and a large number of discrete scan measurements 7 are taken and analyzed; this approach is greatly facilitated by the use of scan systems that 8 automatically record scan measurements and location. These systems typically utilize GPS or 9 other position determinations in conjunction with radiological measurements, with both the 10 radiological and locational data being automatically recorded. These techniques permit the 11 convenient accumulation, storage, and display of hundreds or thousands of scan data points for 12 a survey unit. However, a scan-only approach should only be used for circumstances where the 13 scan MDC (for the scan system) is less than 50 percent of the DCGLW and other MQOs, such 14 as requirements for measurement method uncertainty, can be met. For scan-only surveys of 15 Class 2 or Class 3 survey units where the percentage of the area scanned is less than 16 100 percent, the survey must be designed so that average concentration of radioactive material 17 calculated from the survey data is an unbiased representative estimate of the true mean 18 concentration in the survey unit. In the event the scan-only survey option is feasible for a site or 19 survey unit, the sampling function of the FSS would not be applicable.
20 In addition to the building and land surface areas described above, there are numerous other 21 locations where measurements and/or sampling may be necessary independent from the FSS.
22 Examples include items of equipment and furnishings, building fixtures, drains, ducts, and 23 piping. Many of these items or locations have both internal and external surfaces with potential 24 residual radioactive material. An approach on conducting or evaluating these types of surveys is 25 contained in the Multi-Agency Radiation Survey and Assessment of Materials and Equipment 26 (MARSAME) Manual (NRC 2009), which is a supplement to MARSSIM. Subsurface 27 measurements or sampling may also be necessary.
28 Special situations may be evaluated by judgment sampling and measurements. Data from such 29 surveys should be compared directly with a limit developed for the specific situation and 30 approved by the regulator.
31 Quality control measurements are recommended for all surveys, as described in Sections 4.8, 32 6.2, and 7.2. Also, some regulatory programs require removable activity measurements 33 (e.g., DOE requirements in DOE Order 458.1 [DOE 2011c], 10 CFR 835). These additional 34 measurements should be considered during survey planning.
35 5.3.9.1 Class 1 Areas 36 For Class 1 areas, scanning surveys are designed to detect small areas of elevated activity 37 above the DCGLW that are not detected by the measurements using the systematic pattern 38 (Section 5.3.7). For this reason, the measurement locations and the number of measurements 39 may need to be adjusted based on the sensitivity of the scanning technique (Section 5.3.5.1).
40 This is also the reason for recommending 100 percent coverage for the scanning survey.
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MARSSIM                                                                  Survey Planning and Design 1 As discussed in Section 5.3.6.1, scanning techniques can be used in lieu of discrete samples or 2 direct measurements when the scan MDC is less than 50 percent of the DCGLW, and the scan 3 coverage is 100 percent. Note that, in a statistical sense, a scan of 100 percent of a survey unit 4 constitutes a sample of 100 percent of the survey unit. Other MQOs need to be met, as well, 5 including the MQO for required measurement method uncertainty.
6 Locations of direct radiation above an investigation level are identified and evaluated. Results of 7 initial and followup direct measurements and sampling at these locations are recorded and 8 documented in the FSS report. For structure surfaces, measurements of total and (when 9 applicable) removable radioactive material are performed at locations identified by scans and at 10 previously determined locations (Section 5.3.7). Soil sampling or direct measurements are 11 performed at locations identified by scans and at previously determined locations 12 (Section 5.3.7).
13 The development of direct measurement or sample investigation levels for Class 1 areas should 14 establish a course of action for individual measurements that exceed the investigation level.
15 Because measurements above the DCGLW are not necessarily unexpected in a Class 1 survey 16 unit, additional investigation levels may be established to identify discrete measurements that 17 are much higher than the other measurements. Any discrete measurement that both is above 18 the DCGLW and exceeds a statistical based parameter (e.g., three standard deviations above 19 the mean) should be investigated further (Section 5.3.8). Any measurement (direct 20 measurement, sample, or scan) that exceeds the DCGLEMC should be flagged for further 21 investigation.
22 The results of the investigation and any additional remediation that was performed should be 23 included in the FSS report. Data are reviewed as described in Section 8.2.2, additional data are 24 collected as necessary, and the final complete data set evaluated as described in Section 8.3 25 and Section 8.4.
26 5.3.9.2 Class 2 Areas 27 Scanning surveys in Class 2 areas are also primarily performed to find areas of elevated activity 28 not detected by the measurements using the systematic pattern. However, the number and 29 location of measurements are not adjusted based on sensitivity of the scanning technique, and 30 scanning is performed in portions of the survey unit. The level of scanning effort should be 31 proportional to the potential for finding areas of elevated activity based on the conceptual site 32 model developed and refined from Section 3.6.4. In other words, the farther the expected 33 residual radioactive material in the survey unit is from the DCGLW in units of uncertainty (the 34 larger the ), the less scanning is needed. Surface scans are performed over 10-100 percent 35 of structure surfaces or open land surfaces, as calculated in Equation 5-10. A larger portion of 36 the survey unit would be scanned in Class 2 survey units that have residual radioactive material 37 close to the release criteria, but for survey units that are closer to background scanning, a 38 smaller portion of the survey unit may be appropriate.
39 As discussed in Section 5.3.6.1, scanning techniques for Class 2 survey units might be used in 40 lieu of discrete samples or direct measurements when the scan MDC is less than 50 percent of 41 the DCGLW and the scan coverage is between 10 and 100 percent. Note that, in a statistical 42 sense, a scan of 10-100 percent of a survey unit constitutes a sample of 10-100 percent of the May 2020                                        5-53                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Survey Planning and Design                                                                  MARSSIM 1 survey unit. Other MQOs need to be met, as well, including the MQO for required measurement 2 method uncertainty. The area scanned should be selected in an unbiased manner.
3 Locations of scanning survey results greater than the investigation level are identified and 4 investigated. If small areas of elevated activity are confirmed by this investigation, all or part of 5 the survey unit should be reclassified as Class 1 and the survey strategy for that survey unit 6 redesigned accordingly. Investigation levels for Class 2 areas should establish levels for 7 investigation of individual measurements close to but less than the DCGLW. Investigation levels 8 for Class 2 areas should also establish a course of action for individual measurements that 9 exceed or approach the DCGLW. The results of the investigation of the positive measurements 10 and basis for reclassifying all or part of the survey unit as Class 1 should be included in the FSS 11 report.
12 The results of the investigation should be included in the FSS report. Data are reviewed as 13 described in Section 8.2.2, additional data are collected as necessary, and the final complete 14 data set evaluated as described in Section 8.3 and Section 8.4.
15 5.3.9.3 Class 3 Areas 16 Class 3 areas have the lowest potential for areas of elevated activity. Locations exceeding the 17 scanning survey investigation level should be flagged for further investigation. If the presence of 18 residual radioactive material occurring at concentrations greater than a small fraction of the 19 DCGLW is identified, reevaluation of the classification of the survey unit should be performed.
20 As discussed in Section 5.3.6.1, scanning techniques for Class 3 survey units can be used in 21 lieu of sampling and statistical testing when the scan MDC is less than 50 percent of the 22 DCGLW. Other MQOs need to be met, as well, including the MQO for required measurement 23 method uncertainty.
24 Sampling or direct measurements are performed at randomly selected locations 25 (Section 5.3.7). Survey results are tested for compliance with DCGLs, and additional data are 26 collected and tested as necessary. For structure surfaces, measurements of total and (when 27 applicable) removable radioactive material are performed at the locations identified by the scans 28 and at the randomly selected locations that are chosen in accordance with Section 5.3.7.
29 Investigation levels for Class 3 areas should be established to identify areas of elevated activity 30 that may indicate the presence of residual radioactive material. Because there is a low 31 expectation for residual radioactive material in a Class 3 area, it may be prudent to investigate 32 any measurement exceeding even a fraction of the DCGLW. The investigation level selected will 33 depend on the site, the radionuclides of concern, and the measurement and scanning methods 34 chosen. This level should be commensurate with the potential exposures and should be 35 determined using the DQO Process during survey planning. In some cases, the user may wish 36 to follow this procedure for Class 2 survey units.
37 The data are tested relative to the preestablished criteria. If additional data are needed, they 38 should be collected and evaluated as part of the entire data set. Identification of residual 39 radioactive material suggests that the area may be incorrectly classified. If so, a reevaluation of NUREG-1575, Revision 2                            5-54                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                                Survey Planning and Design 1 the Class 3 area classification should be performed and, if appropriate, all or part of the survey 2 unit should be resurveyed as a Class 1 or Class 2 area.
3 The results of the investigation of the measurements that exceed the investigation level and the 4 basis for reclassifying all or part of the survey unit as Class 1 or Class 2 should be included in 5 the FSS report.
6 As discussed in Section 5.3.8, investigation levels are determined and used to indicate when 7 additional investigations may be necessary or when a measurement process begins to get out 8 of control. The results of all investigations should be documented in the FSS report, including 9 the results of scan surveys that may have potentially identified areas of elevated direct radiation.
10 5.3.10 Evaluating Survey Results 11 Chapter 8 describes detailed procedures for evaluating survey results. After data are converted 12 to the same units as the DCGL, the process of comparing the results to the DCGLs and 13 objectives begins. Individual measurements and sample concentrations are first compared to 14 DCGL levels for evidence of small areas of elevated activity and not to determine if 15 reclassification is necessary. Additional data or additional remediation and resurveying may be 16 necessary. Data are then evaluated using statistical methods to determine if they exceed the 17 release criteria. If the release criteria have been exceeded or if results indicate the need for 18 additional data points, appropriate further actions will be determined by the site management 19 and the regulatory agency. The scope of further actions should be agreed upon and developed 20 as part of the DQO Process before the survey begins (Appendix D). Finally, the results of the 21 survey are compared with the DQOs established during the planning phase of the project. Note 22 that DQOs may identify a need for a report of the evaluation of removable radioactive material 23 resulting from the analysis of smears. These results may be used to satisfy regulatory 24 requirements or to evaluate the need for additional ALARA procedures.
25 5.3.11 Documentation 26 Documentation of the FSS should provide a complete and unambiguous record of the 27 radiological status of the survey unit relative to the established DCGLs. In addition, sufficient 28 data and information should be provided to enable an independent re-creation and evaluation at 29 some future time. Much of the information in the FSS report will be available from other site 30 remediation documents; however, to the extent practicable, this report should be a stand-alone 31 document with minimum information incorporated by reference. The report should be 32 independently reviewed (see Section 8.7) and should be approved by a designated person (or 33 persons) who are capable of evaluating all aspects of the report before release, publication, or 34 distribution. Example 11 includes an example of a final status survey checklist, including survey 35 preparations, survey design, conduct of surveys, and evaluation of survey results.
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Survey Planning and Design                                                              MARSSIM Example 11: Example Final Status Survey Checklist Survey Preparations
_____ Ensure that residual radioactive material limits have been determined for the radionuclides present at the site, typically performed during earlier surveys associated with the release process.
_____ Identify the radionuclides of concern. Determine whether the radionuclides of concern exist in background.
_____ Segregate the site into Class 1, Class 2, and Class 3 areas, based on the presence of potential residual radioactive material.
_____ Identify the survey units.
_____ Select representative reference (background) areas for both indoor and outdoor survey areas. Reference areas are selected from non-impacted areas and
_____ are free of residual radioactive material from site operations
_____ exhibit similar physical, chemical, and biological characteristics of the survey area
_____ have similar construction, but have no history of radioactive operations
_____ Select measurement method, based on the required Measurement Quality Objectives (MQOs).
_____ Determine minimum detectable concentrations (MDCs; select instrumentation based on the radionuclides present) and match between instrumentation and derived concentration guideline levels (DCGLs)the selected instruments should be capable of detecting the radionuclides of concern at less than 50 percent of the DCGLs.
_____ Determine measurement method uncertainty and compared to required measurement method uncertainty.
_____ Determine ruggedness, specificity, and range and compare to requirements.
_____ Prepare the area if necessaryclear and provide access to areas to be surveyed.
_____ Establish reference coordinate systems (as appropriate).
Survey Design
_____ Enumerate Data Quality Objectives (DQOs) and MQOs: State the objective of the survey, state the null and alternative hypotheses, specify the acceptable decision NUREG-1575, Revision 2                        5-56                                    May 2020 DRAFT FOR PUBLIC COMMENT                                              DO NOT CITE OR QUOTE
 
MARSSIM                                                            Survey Planning and Design error rates (Type I [] and Type II []) and requirements for MDC, measurement method uncertainty, ruggedness, specificity, and range.
_____ Specify sample collection and analysis procedures.
_____ Determine numbers of data points for statistical tests, depending on whether the radionuclide is present in background. Alternatively, design a scan-only survey using automated equipment recording both data and location.
_____ Specify the number of samples/measurements to be obtained, if applicable.
_____ Evaluate the power of the statistical tests to determine whether the number of samples is appropriate.
_____ Ensure that the sample size is sufficient for detecting areas of elevated activity.
_____ Add additional samples/measurements for quality control and to allow for possible loss.
_____ Establish the percentage of the survey unit to be surveyed by scanning.
_____ Specify sampling locations, if appropriate.
_____ Specify areas and percentage of areas subject to scanning survey.
_____ Provide information on the survey measurement method.
_____ Specify methods of data reduction and comparison of survey units to reference areas.
_____ Provide quality control procedures and Quality Assurance Project Plan (QAPP) for ensuring validity of survey data:
_____ properly calibrated instrumentation
_____ necessary replicate, reference, and blank measurements
_____ comparison of field measurement results to laboratory sample analyses
_____ Document the survey plan (e.g., QAPP, standard operating procedures [SOPs], etc.)
Conducting Surveys
_____ Perform reference (background) area measurements and sampling.
_____ Conduct survey activities:
_____ Perform surface scans of the Class 1, Class 2, and Class 3 areas.
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Survey Planning and Design                                                          MARSSIM
_____ Conduct surface activity measurements and sampling at previously selected sampling locations, if applicable.
_____ Conduct additional direct measurements and sampling at locations based on professional judgment.
_____ Perform and document any necessary investigation activities, including survey unit reclassification, remediation, and resurvey.
_____ Document measurement and sample locations; provide information on measurement system MDC and measurement method uncertainty.
_____ Document any observations, abnormalities, and deviations from the QAPP or SOPs.
Evaluating Survey Results
_____ Review DQOs and MQOs.
_____ Perform data reduction on the survey results.
_____ Conduct a preliminary data review.
_____ Select the statistical test(s).
_____ Verify the assumptions of statistical tests.
_____ Compare survey results with regulatory DCGLs:
_____ Conduct an elevated measurement comparison, if appropriate.
_____ Determine the area-weighted average, if appropriate.
_____ Conduct Wilcoxon Rank Sum or Sign tests, if appropriate.
_____ Conduct quantile test or retrospective power analysis, if appropriate.
_____ Conduct Upper Level Comparison, if appropriate.
_____ Prepare FSS report.
_____ Obtain an independent review of the report.
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MARSSIM                                                    Field Measurement Methods and Instrumentation 1      6 FIELD MEASUREMENT METHODS AND INSTRUMENTATION 2 6.1    Introduction 3 Measurement is used in the Multi-Agency Radiation Survey and Investigation Manual 4 (MARSSIM) to mean (1) the act of using a detector to determine the level or quantity of 5 radioactive material on a surface or in a sample of material removed from a medium being 6 evaluated, or (2) the quantity obtained by the act of measuring. 1 Three methods are available 7 for collecting radiation data while performing a survey: direct measurements, scanning, and 8 sampling. This chapter discusses direct measurement methods, scanning, and instrumentation.
9 The collection and analysis of media samples are presented in Chapter 7. Information on the 10 operation and use of individual field and laboratory instruments is provided in Appendix H.
11 Total surface activities, removable surface activities, and radionuclide concentrations in various 12 environmental media are the radiological parameters typically determined using field 13 measurements and laboratory analyses. Certain radionuclides or radionuclide mixtures may 14 necessitate the measurement of alpha, beta, and gamma radiations. In addition to assessing 15 each survey unit as a whole, any small areas of elevated activity should be identified to the 16 extent practicable and their extent and activities determined. Due to numerous detector 17 requirements, multiple measurement methods (survey technique and instrument combination) 18 may be needed to adequately measure all of the parameters required to satisfy the release 19 criteria or meet all the objectives of a survey.
20 Selecting an appropriate measurement method requires evaluation of both Data Quality 21 Objectives (DQOs) and Measurement Quality Objectives (MQOs). Instruments should be stable 22 and reliable under the environmental and physical conditions where they are used, and their 23 physical characteristics (size and weight) should be compatible with the intended application.
24 Numerous commercial firms offer a wide variety of instruments appropriate for the radiation 25 measurements described in this manual. These firms can provide thorough information 26 regarding capabilities, operating characteristics, limitations, etc., of specific equipment.
27 If the available field measurement methods do not achieve the MQOs, laboratory methods 28 discussed in Chapter 7 are typically used. There are certain radionuclides that are difficult to 29 measure at some derived concentration guideline levels (DCGLs) typically encountered in situ 30 using current state-of-the-art instrumentation and techniques because of the types, energies, 31 and abundances of their radiations. Examples of such radionuclides include such very low-32 energy, pure beta emitters as tritium (3H) and nickel-63 (63Ni) and low-energy photon emitters as 33 iron-55 (55Fe) and iodine-125 (125I). Pure alpha emitters dispersed in soil or covered with some 34 absorbing layer may not be measurable, because alpha radiation will not penetrate through the 35 media or covering to reach the detector. A common example of such a condition would be 36 thorium-230 (230Th) surface contamination covered by paint, dust, oil, or moisture. The 37 U.S. Nuclear Regulatory Commission (NRC) report NUREG-1507 (NRC 1997a) provides 38 information on the extent to which these surface conditions may affect detection capability. In 1 MARSSIM uses the word should as a recommendation, not as a requirement. Each recommendation in this manual is not intended to be taken literally and applied at every site. MARSSIMs survey planning documentation will address how to apply the process on a site-specific basis.
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Field Measurement Methods and Instrumentation                                          MARSSIM 1 such circumstances, the survey design will usually rely on sampling and laboratory analysis to 2 measure residual activity levels. Appendix E provides information on using a ranked set 3 sampling procedure to reduce sampling requirements for hard-to-detect radionuclides.
4 Section 6.2 includes a discussion of DQOs and MQOs. Two important MQOs, detection 5 capability and measurement uncertainty, are covered in more detail in Sections 6.3 and 6.4, 6 respectively. Section 6.5 discusses the selection of a service provider to perform field data 7 collection activities. The selection of a measurement method is discussed in Section 6.6.
8 Section 6.7 includes information on the data conversion needed to make comparisons with the 9 applicable DCGLs. Radon measurements are covered in Section 6.8. Section 6.9 includes 10 information about special equipment.
11 6.2  Data Quality Objectives 12 The third step of the DQO Process (EPA 2006c) involves identifying the data needs for a 13 survey. One decision that can be made at this step is the selection of field measurement 14 methods that meet the MQOs or determining that sample collection and subsequent laboratory 15 analysis is required.
16 6.2.1  Identifying Data Needs for Field Measurement Methods 17 The decision maker and the survey planning team need to identify the data needs for the survey 18 being performed, including the following:
19
* type of measurements to be performed (Chapter 5) 20
* radionuclide(s) of interest (Section 4.5) 21
* number of direct measurements to be performed (Sections 5.3.3-5.3.4) 22
* area of survey coverage for surface scans based on survey unit classification 23    (Section 5.3.6) 24
* type and frequency of field QC measurements to be performed (Section 4.8) 25
* standard operating procedures (SOPs) to be followed or developed (Chapter 6) 26
* measurement method uncertainties (Section 6.4) 27
* detection capabilities for each radionuclide of interest (Section 6.3) 28
* cost of the measurement methods being evaluated (both cost per measurement and total 29    cost) (Appendix H) 30
* necessary turnaround time (a potential health and safety concern for situations involving 31    excavations) 32
* specific background for the radionuclide(s) of interest (Section 4.5)
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MARSSIM                                          Field Measurement Methods and Instrumentation 1
* DCGL for each radionuclide of interest (Section 4.10) 2
* measurement documentation requirements 3
* measurement tracking requirements 4 Some of this information will be supplied by subsequent steps in the DQO process, and several 5 iterations of the process may be needed to identify all of the data needs. Consulting with a 6 health physicist or radiochemist may be necessary to properly evaluate the information before 7 deciding between field measurement methods or sampling followed by laboratory analytical 8 methods to perform the survey. Many surveys will involve a combination of field measurements 9 and sampling methods to demonstrate compliance with the release criteria.
10 6.2.2  Measurement Performance Indicators 11 Measurement performance indicators are used to evaluate the performance of the 12 measurement method. These indicators describe how the measurement method is performing 13 to ensure the survey results are of sufficient quality to meet the survey objectives.
14 6.2.2.1 Background Measurements/Blanks 15 Background measurements are direct measurements or scans of materials with little or no 16 radioactive material, other than that present in the natural background of the material; or the 17 response of the instrument to ambient radiation when the instrument is moved away from the 18 surface being surveyed. These measurements are performed to determine whether the 19 measurement process introduces any increase in instrument signal rate that could impact the 20 measurement method detection capability. Background measurements should be representative 21 of all measurements performed using a specific measurement method (i.e., combination of 22 instrumentation and measurement technique). When practical, the background measurements 23 should consist of the same or equivalent material(s) as the area being surveyed.
24 Background measurements typically are performed before and after a series of measurements 25 to demonstrate the measurement method was performing adequately throughout the survey. At 26 a minimum, background measurements should be performed at the beginning and end of each 27 shift. When large quantities of data are collected (e.g., scanning measurements) or there is an 28 increased potential for radionuclide contamination of the instrument (e.g., removable or airborne 29 radionuclides), background measurements may be performed more frequently. In general, 30 background measurements should be performed before too many measurements have been 31 performed such that it is not practical to repeat those measurements if a problem is identified.
32 A sudden change in the measured background indicates a condition requiring immediate 33 attention. Sudden changes can be caused by the introduction of a radionuclide, a change in 34 ambient background, instrument instability, or contamination of the detector. Gradual changes in 35 the measured background indicate a need to inspect all survey areas for sources of radioactive 36 material. Gradual buildup of removable radionuclides over time or instrument drift and 37 deterioration can result in slowly increasing background measurements. High variability in 38 background measurements can result from instrument instability or improper classification May 2020                                        6-3                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                              MARSSIM 1 (i.e., high-activity and low-activity areas combined into a single survey unit). It is important to 2 correct any problems with blanks to ensure that the detection capability (see Section 6.3) is not 3 compromised.
4 If smears or swipes, described in more detail in Section 6.6.1.4, are used to estimate the 5 amount of removable radioactive material on the surface, measurement of an unused smear, or 6 blank, provides a background measurement of the instrument used to test the smears 7 6.2.2.2 Replicate Measurements 8 Replicate measurements are two or more measurements performed at the same location or on 9 the same sample that are performed primarily to provide an estimate of the random uncertainty 10 for the measurement method. The reproducibility of measurement results should be evaluated 11 by replicates to establish this component of measurement uncertainty (see Section 6.4).
12 Replicates typically are performed at specified intervals during a survey (e.g., 5 percent of all 13 measurements or once per day) and should be employed to evaluate each batch of data used 14 to support a decision (e.g., one replicate per survey unit). For scan-only surveys, where 15 decisions are made based on logged and geolocated measurements, typically 5 percent of all 16 measurements are replicated (e.g., 5 percent of the scanned area is scanned twice).
17 Estimates of random uncertainty exhibit a range of values and depend in part on the surface 18 being measured and the activity level. Small changes in the random uncertainty are expected, 19 and the acceptable range of variability should be established before initiating data collection 20 activities. The main causes for high random uncertainty include problems with repeating 21 measurements on irregular surfaces, the surface being measured, counting statistics when the 22 activity levels are low, and instrument contamination.
23 6.2.2.3 Spikes and Standards 24 Spikes and standards are materials with known composition and amounts of radioactive 25 material; they are used to evaluate bias in the measurement method and typically performed 26 periodically during a survey (e.g., 5 percent of all measurements or once per day). When spikes 27 and standards are available, they should be used to evaluate each batch of data used to 28 support a release decision (i.e., at least one spike or standard per survey unit).
29 Tracking results of measurements with known activity can provide an indication of the 30 magnitude of the systematic uncertainty or drift of the measurement system. In general, activity 31 levels near the DCGLs (or discrimination limits in Scenario B) will provide adequate information 32 on the performance of the measurement system.
33 6.2.3    Instrument Performance Indicators 34 Evaluating instrument performance indicators provides information on the operation of the 35 instruments and how they are performing.
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MARSSIM                                              Field Measurement Methods and Instrumentation 1 6.2.3.1 Performance Tests 2 Performance tests should be carried out periodically and after any maintenance to ensure that 3 the instruments continue to meet performance requirements for measurements. An example of 4 a performance test is a test for response time. Performance requirements should be met as 5 specified in the applicable sections of the American National Standards Institute (ANSI) 6 publications ANSI N323AB (ANSI 2013), ANSI N42.17A (ANSI 2004), and ANSI N42.17C (ANSI 7 1990). These tests may be conducted as part of the calibration procedure.
8 6.2.3.2 Functional Tests 9 Functional tests should be performed before initial use of an instrument and after periods when 10 the instrument was stored for a relatively long time or transported over a long distance. These 11 functional tests should include 12
* general condition 13
* battery condition 14
* verification of current calibration (i.e., check to see that the date due for calibration has not 15      passed) 16
* source and background response checks (and other tests as applicable to the instrument) 17
* constancy check 18 The effects of environmental conditions (temperature, humidity, etc.) and interfering radiation on 19 an instrument should be established before use. The performance of functional tests should be 20 appropriately documented. This may be as simple as a checklist on a survey sheet, or it may 21 include more detailed statistical evaluation, such as a chi-square test (Gilbert 1987).
22 6.2.3.3 Instrument Background 23 All radiation detection instruments have a background response, even in the absence of a 24 sample or radiation source. Inappropriate background correction will result in measurement 25 error and increase the uncertainty of data interpretation.
26 6.2.3.4 Efficiency Calibrations 27 Knowing the detector efficiency is critical for converting the instrument response to activity (see 28 MARSSIM Section 6.7, Multi-Agency Radiation Survey and Assessment of Materials and 29 Equipment [MARSAME] Section 7.8.2.2, and Multi-Agency Radiological Laboratory Analytical 30 Protocols [MARLAP] Chapter 16). Routine performance checks may be used to demonstrate 31 that the systems operational parameters are within acceptable limits, and these measurements 32 typically are included in the assessment of systematic uncertainty. The systems operational 33 parameters may be tracked using control charts.
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Field Measurement Methods and Instrumentation                                              MARSSIM 1 6.2.3.5 Energy Calibrations (Spectrometry Systems) 2 Spectrometry systems identify radionuclides based on the energy of the detected radiations. A 3 correct energy calibration is critical to accurately identify radionuclides. An incorrect energy 4 calibration may result in misidentification of peaks or failure to identify radionuclides present.
5 6.2.3.6 Peak Resolution and Tailing (Spectrometry Systems) 6 The shape of the full energy peak is important for identifying radionuclides and quantifying their 7 activity with spectrometry systems. Poor peak resolution and peak tailing may result in larger 8 measurement uncertainty or in failure to identify the presence of peaks based on shape.
9 Consistent problems with peak resolution indicate the presence of an analytical bias.
10 6.2.3.7 Voltage Plateaus (Proportional Counters, Geiger-Mueller Detectors) 11 The accuracy of results using a proportional counter or Geiger-Mueller (GM) detector can be 12 affected if the system is not operated with its detectors high voltage adjusted such that it is on a 13 stable portion of the operating plateau.
14 6.2.3.8 Self-Absorption, Backscatter, and Crosstalk 15 Alpha and beta measurement results can be affected through self-absorption and backscatter.
16 Measurement systems using an electronic discriminator (e.g., gas flow proportional detectors) 17 that simultaneously detect alpha and beta particles can be affected by crosstalk 18 (i.e., identification of alpha particles as beta particles and vice versa). Accurate differentiation 19 between alpha and beta activity depends on the assessment and maintenance of information on 20 self-absorption and crosstalk.
21 6.3    Detection Capability 22 The detection capability (sometimes referred to as sensitivity) of a measurement system refers 23 to a radiation level or quantity of radioactive material that can be measured or detected with 24 some known or estimated level of confidence. This quantity is a factor of both the 25 instrumentation and the technique or procedure being used.
26 The primary parameters that affect a measurement systems detection capability are the 27 background count rate, the instruments detection efficiency, and the counting time interval.
28 When making field measurements, the detection capability will usually be less than what can be 29 achieved in a laboratory due to increased background and, often, significantly lower detection 30 efficiency. It is often impossible to guarantee that pure alpha emitters can be detected in situ, 31 because the weathering of aged surfaces will often completely absorb the alpha emissions.
32 NUREG-1507 (NRC 1997a) contains data on many of the parameters that affect detection 33 efficiencies in situ, such as absorption, surface smoothness, and particulate radiation energy.
34 6.3.1    Detection Capability for Direct Measurements 35 Prior to performing field measurements using scalers, an investigator must evaluate the 36 detection capability of the equipment proposed for use to ensure that levels below the DCGL 37 can be detected. After a direct measurement has been made, it is then necessary to determine NUREG-1575, Revision 2                            6-6                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                    Field Measurement Methods and Instrumentation 1 whether the result can be distinguished from the instrument background response of the 2 measurement system. The terms that are used in this manual to define detection capability for 3 fixed point counts and sample analyses are 4
* Critical level: The critical level ( ) is the level at which there is a statistical probability (with a 5      predetermined confidence) of correctly identifying a measurement as greater than 6      background.
7
* Detection limit: The detection limit ( ) is the net response level that can be expected to be 8      seen with a detector with a fixed level of confidence.
9
* Minimum detectable concentration: The minimum detectable concentration (MDC) is the a 10      priori activity concentration that a specific instrument and technique that has a specified 11      probability (typically 95 percent) of producing a net count (or count rate) above the critical 12      level. When stating the detection limit of an instrument, this value should be used. The MDC 13      is the detection limit multiplied by an appropriate conversion factor to give units of activity.
14 The following discussion provides an overview of the derivation contained in the well-known 15 publication by Currie (1968) followed by a description of how the resulting formulas should be 16 used. Publications by Currie (1968) and Altshuler and Pasternack (1963) provide details of the 17 derivations involved. The two parameters of interest for a detector system with a background 18 response greater than zero are 19 1. The critical level is the lower bound on the 95 percent detection interval defined for  and is 20      the level at which there is a 5 percent chance of calling a background value greater than 21      background. This value should be used when counting samples or making direct radiation 22      measurements. Any response above this level should be considered as above background 23      (i.e., a net positive result). This will ensure 95 percent detection capability for  .
24 2. The detection limit is the net response level, in counts, that can be expected to be seen with 25      a detector with a fixed level of confidence, which is assumed to be 95 percent.
26 Assuming that a system has a background response, and that random uncertainties and 27 systematic uncertainties are accounted for separately, these parameters can be calculated 28 using Poisson statistics. For these calculations, two types of decision errors should be 29 considered. A Type I error occurs when a detector response is considered to be above 30 background when, in fact, only background radiation is present. A Type II error occurs when a 31 detector response is considered to be background when, in fact, radiation is present at levels 32 above background. The probability of a Type I error is referred to as  (alpha) and is associated 33 with  ; the probability of a Type II error is referred to as  (beta) and is associated with  .
34 Figure 6.1 graphically illustrates the relationship of these terms with respect to each other and 35 to a normal background distribution. 2 2 Note that the values of  and  chosen here are for the detection hypothesis test and are always chosen to be 5%
for comparability purposes. These  and  values are separate and distinct from the values of  and  chosen by the planning team for use in designing site surveys.
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Field Measurement Methods and Instrumentation                                                        MARSSIM Probability (Normalized) 2 =
2 =  +
0 Net Counts B = Background Counts (mean)
                                    = Critical Level (net counts above background)
                                    = Detection Limit (net counts above background)
                                    = Probability of Type I Error
                                    = Probability of Type II Error 1
2    Figure 6.1: Graphically Represented Probabilities for Type I and Type II Errors in 3    Detection Capability for Instrumentation with a Background Response 4    If  and  are assumed to be equal, the variance (2) of all measurement values is assumed to 5    be equal to the values themselves. If the background of the detection system is not well known, 6    then the critical level and the detection limit can be calculated by using the following formulas:
                                                                    = 2                              (6-1)
                                                                =  2 = 22                          (6-2) 7    where  is the critical level (counts),  is the detection limit (counts),  is the Poisson 8    probability sum for  and  (assuming  and  are equal), and  is the number of background 9    counts that are expected to occur while performing an actual measurement.
10  The curve to the left in Figure 6.1 is the background distribution. The result is a Poisson 11  distribution with a mean equal to the number of background counts, , and a variance,  2 , equal 12  to . Note that the distribution accounts only for the expected statistical variation due to the 13  stochastic nature of radioactive decay. Currie assumed paired blanks when deriving the above 14  stated relationships (Currie 1968), which is interpreted to mean that the sample and background 15  count times are the same.
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MARSSIM                                            Field Measurement Methods and Instrumentation 1 If values of 0.05 for both  and  are selected as acceptable, then  = 1.645 (from Appendix I, 2 Table I.1), and Equations 6-1 and 6-2 can be written as
                                                  = 2.33                                    (6-3)
                                              = 3 + 4.65                                    (6-4) 3          Note: In Curries derivation, the constant factor of 3 in the  formula was stated 4          as being 2.71, but since that time it has been shown (Brodsky 1992) and 5          generally accepted that a constant of 3 is more appropriate. If the sample count 6          times and background count times are different, a slightly different formulation is 7          used.
8 The MDC value should be used when stating the detection capability of an instrument. Again, 9 this value is used before any measurements are made and is used to estimate the level of 10 activity that can be detected using a given measurement method.
11 For an integrated measurement over a preset time, the MDC can be obtained from 12 Equation 6-4 by multiplying by the factor . This factor is used to convert from counts to 13 concentration, as shown in Equation 6-5:
MDC =  x 3+4.65                                  (6-5) 14 The total detection efficiency and other constants or factors represented by the variable  are 15 usually not truly constants, as shown in Equation 6-5. It is likely that at least one of these 16 factors will have a certain amount of variability associated with it, which may or may not be 17 significant. These varying factors are gathered together into the single constant, , by which the 18 net count result will be multiplied when converting the final data. If  varies significantly between 19 measurements, then it might be best to select a value, , from the observed distribution of 20 values that represents a conservative estimate. For example, a value of  might be selected to 21 ensure that at least 95 percent of the possible values of  are less than the chosen value, .
22 The MDC calculated in this way helps assure that the survey results will meet the DQOs. This 23 approach for including uncertainties into the MDC calculation is recommended in both 24 NUREG/CR-4007 (NRC 1984) and Appendix A to ANSI N13.30 (ANSI 1996). Underestimating 25 an MDC can have adverse consequences, especially if activity is later detected at a level above 26 the stated MDC.
27 From a conservative point of view, it is better to overestimate the MDC for a measurement 28 method. Therefore, when calculating MDC and  values, a measurement system background 29 value should be selected that represents the high end of what is expected for a particular 30 measurement method. For direct measurements, probes will be moved from point to point; as a 31 result, it is expected that the background will most likely vary significantly because of variations 32 in background, source materials, and changes in geometry and shielding. Ideally, the MDC 33 values should be calculated for each type of area, but it may be more economical to simply 34 select a background value from the highest distribution expected and use this for all May 2020                                            6-9                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                              MARSSIM 1 calculations. For the same reasons, realistic values of detection efficiencies and other process 2 parameters should be used when possible and should be reflective of the actual conditions, as 3 adopting an overly conservative MDC may sometimes lead to difficulties in implementation. To a 4 great degree, the selection of these parameters will be based on judgment and will require 5 evaluation of site-specific conditions. Example 1 illustrates the calculation of an MDC in 6 becquerels per square meter (Bq/m2) for an instrument with a 15 cm2 probe area when the 7 measurement and background counting times are each 1 minute.
Example 1: Calculation of a Minimum Detectable Concentration (MDC)
This example illustrates the calculation of an MDC in becquerels per square meter (Bq/m2) for an instrument with a 15 square centimeter (cm2) probe area when the measurement and background counting times are each 1 minute. Note that the count rate is reported in units of disintegrations per minute (dpm). The background counts, , is 40 counts.
If the total efficiency of the probe is 20 percent, then 1 count will be recorded during a 1-minute timeframe for every 5 dpm. The concentration  =
5 dpm        Bq        1      10,000 cm2
                        =                                          = 55.6 Bqm2 count 60 dpm 15 cm2                  m2 The MDC is calculated using Equation 6-5:
MDC = 55.6 Bqm2  x 3+4.6540 = 1,800 Bq/m21,100 dpm/100 cm2 The critical level,  , for this example is calculated from Equation 6-3:
                                        = 2.33 = 2.3340 = 15 counts Given the above scenario, if a person asked what level of residual radioactive material could be detected 95 percent of the time using this method, the answer would be 1,800 Bq/m2 (1,100 dpm/100 cm2). When performing measurements using this method, any count yielding greater than 55 total counts, or greater than 15 net counts (55 - 40 = 15) during a period of 1 minute, would be regarded as greater than background.
8 MDC values for other counting conditions may be derived from Equation 6-5, depending on the 9 detector and radionuclides of concern. For example, it may be required to determine what level 10 of residual radioactive material, distributed over 100 square centimeters (cm2), can be detected 11 with a 500 cm2 probe or what level of residual radioactive material can be detected with any 12 probe when the area is smaller than the probe active area. Table 6.1 lists several common field 13 survey detectors with estimates of MDC values for uranium-238 (238U) on a smooth, flat plane.
14 As such, these represent minimum MDC values and may not be applicable at all sites.
15 Appropriate site-specific MDC values should be determined using the DQO Process.
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MARSSIM                                                  Field Measurement Methods and Instrumentation 1 6.3.2      Detection Capability for Scans 2 Unless data logging is employed, the ability to identify a small area of elevated levels of 3 radioactive material during surface scanning is dependent upon the surveyors skill in 4 recognizing an increase in the output of an instrument. For notation purposes, the term 5 detection capability (sometimes referred to as scanning sensitivity) is used throughout this 6 section to describe the ability of a surveyor to detect a pre-determined level of residual 7 radioactive material with a detector. The greater the detection capability, the lower the level of 8 residual radioactive material that can be detected. Table 6.1 provides examples of a set of 9 detection capabilities.
10 Table 6.1: Examples of Estimated Detection Capabilities for Alpha and Beta Survey 11 Equipment (Static 1-Minute Counts for 238U Calculated Using Equations 6-3, 6-4, and 6-5)
Approximate Detection Capability Probe Detector            Area      Background          Efficiency                                MDC (cm2)          (cpm)        (cpm/dpm)          (counts)        (counts)    (Bq/m2)a Alpha 50              1              0.15                2              7            150 proportional Alpha 100              1              0.15                2              7            83 proportional Alpha 600              5              0.15                5            13            25 proportional Alpha 50              1              0.15                2              7            150 scintillation Beta 100            300              0.20              40            83            700 proportional Beta 600            1,500              0.20              90            183            250 proportional Beta 15              40              0.20              15            32          1,800 GM pancake 12 Abbreviations: cm = centimeter; cpm = counts per minute; dpm = decays per minute;  = critical level;  = detection 13 limit; Bq = becquerels; m = meters; GM = Geiger-Mueller.
14 a Assumes that the size of the area of radioactive material is at least as large as the probe area.
15 Many of the radiological instruments and monitoring techniques typically used for occupational 16 health physics activities may not provide the detection capabilities necessary to demonstrate 17 compliance with the DCGLs. The detection capability for a given application can be improved 18 (i.e., lower the MDC) by (1) selecting an instrument with a higher detection efficiency or a lower 19 background, (2) decreasing the scanning speed, or (3) increasing the size of the effective probe 20 area without significantly increasing the background response.
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Field Measurement Methods and Instrumentation                                              MARSSIM 1 Scanning is usually performed during radiological surveys to identify the presence of any areas 2 of elevated activity. The probability of detecting residual radioactive material in the field not only 3 depends on the detection capability of the survey instrumentation when used in the scanning 4 mode of operation, but also is affected by the surveyors ability (i.e., human factors). The 5 surveyor must make a decision whether the signals represent only the background activity or 6 residual radioactive material in excess of background. Lower levels of residual radioactive 7 material can be detected by increasing the detection capability (i.e., detection of residual 8 radioactive material is inversely proportional to the detection capability). Accounting for these 9 human factors represents a significant change from the methods of estimating detection 10 capabilities for scans used in the past.
11 An empirical method for evaluating the detection capability for surveys is by actual 12 experimentation or, as it is certainly feasible, by simulating an experimental setup using 13 computer software. The following steps provide a simple example of how one can perform this 14 empirical evaluation:
15 1. A desired radionuclide activity level is selected.
16 2. The response of the detector to be used is determined for the selected radionuclide activity 17    level.
18 3. A test source is constructed that will give a detector count rate equivalent to the detector 19    response, determined in Step 2. The count rate is equivalent to what would be expected 20    from the detector when placed on an actual area with residual radioactive material equal in 21    value to that selected in Step 1.
22 4. The detector of choice is then moved over the source at different scan rates until an 23    acceptable speed is determined.
24 The most useful aspect of this approach is that the source can then be used to show surveyors 25 what level of residual radioactive material is expected to be targeted with the scan. They, in 26 turn, can gain experience with what the expected response of the detector will be and how fast 27 they can survey and still feel confident about detecting the target residual radioactive material 28 level. The person responsible for the survey can then use this information when developing a 29 fixed point measurement and sampling plan.
30 The remainder of this section provides the reader with information regarding the underlying 31 processes involved when performing scanning surveys for alpha-, beta-, and gamma-emitting 32 radionuclides. The purpose is to provide relevant information that can be used for estimating 33 realistic detection capabilities for scans.
34 6.3.2.1 Scanning for Beta and Gamma Emitters 35 The scan MDC depends on several factors:
36
* the intrinsic characteristics of the detector (efficiency, physical probe area, etc.)
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MARSSIM                                              Field Measurement Methods and Instrumentation 1
* the nature (type and energy of emissions) and relative distribution of residual radioactive 2      material (point versus distributed source and depth of residual radioactive material) 3
* scan rate 4
* other characteristics of the surveyor 5 Some factors may affect the surveyors performance (e.g., fatigue, noise, level of training, 6 experience) and the surveys a priori expectation of the likelihood of residual radioactive 7 material present. For example, if the surveyor believes that the potential for residual radioactive 8 material is very low, as in a Class 3 area, a relatively large signal may be required for the 9 surveyor to conclude that residual radioactive material is present.
10 Signal Detection Theory 11 Personnel conducting radiological surveys for residual radioactive material at sites must 12 interpret the audible output of a portable survey instrument to determine when the signal 13 (clicks) exceeds the background level by a margin sufficient to conclude that residual 14 radioactive material is present. It is difficult to detect low levels of residual radioactive material, 15 because both the signal and the background vary widely. Signal detection theory provides a 16 framework for the task of deciding whether the audible output of the survey meter during 17 scanning is due to background or signal plus background levels. An index of sensitivity () that 18 represents the distance between the means of the background and background plus signal 19 (refer to Figure 6.1 for determining  ), in units of their common standard deviation can be 20 calculated for various decision errors (correct detection and false positive rate).
21 As an example, for a correct detection rate of 95 percent (complement of a false negative rate of 22 5 percent) and a false positive rate of 5 percent,  is 3.28 (similar to the static MDC for the 23 same decision error rates). The index of sensitivity is independent of human factors; therefore, 24 the ability of an ideal observer (theoretical construct) may be used to determine the minimum 25 that can be achieved for particular decision errors. The ideal observer makes optimal use of the 26 available information to maximize the percent correct responses, providing an effective upper 27 bound against which to compare actual surveyors. Table 6.2 lists selected values of .
28 Two Stages of Scanning 29 The framework for determining the scan MDC is based on the premise that there are two stages 30 of scanning. That is, surveyors do not make decisions based on a single indication; rather, upon 31 noting an increased number of counts, they pause briefly and then decide whether to move on 32 or take further measurements. Thus, scanning consists of two components: continuous 33 monitoring and stationary sampling. In the first component, characterized by continuous 34 movement of the probe, the surveyor has only a brief look at potential sources, determined by 35 the scan speed. The surveyors willingness to decide that a signal is present at this stage is 36 likely to be liberal, in that the surveyor should respond positively on scant evidence, because 37 the only cost of a false positive is a little time. The second component occurs only after a 38 positive response was made at the first stage. This response is marked by the surveyor 39 interrupting his or her scanning and holding the probe stationary for a period of time while May 2020                                            6-13                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                              MARSSIM 1 comparing the instrument output signal during that time to the background counting rate. Owing 2 to the longer observation interval, detection capability is relatively high. For this decision, the 3 criterion should be stricter, as the cost of a yes decision is to spend considerably more time 4 Table 6.2: Index of Sensitivity () Values for Selected True Positive and False Positive 5 Proportions True Positive Proportion False Positive Proportion 0.60      0.65      0.70      0.75      0.80    0.85      0.90      0.95 0.05          1.90      2.02      2.16      2.32      2.48    2.68      2.92      3.28 0.10          1.54      1.66      1.80      1.96      2.12    2.32      2.56      2.92 0.15          1.30      1.42      1.56      1.72      1.88    2.08      2.32      2.68 0.20          1.10      1.22      1.36      1.52      1.68    1.88      2.12      2.48 0.25          0.93      1.06      1.20      1.35      1.52    1.72      1.96      2.32 0.30          0.78      0.91      1.05      1.20      1.36    1.56      1.80      2.16 0.35          0.64      0.77      0.91      1.06      1.22    1.42      1.66      2.02 0.40          0.51      0.64      0.78      0.93      1.10    1.30      1.54      1.90 0.45          0.38      0.52      0.66      0.80      0.97    1.17      1.41      1.77 0.50          0.26      0.38      0.52      0.68      0.84    1.04      1.28      1.64 0.55          0.12      0.26      0.40      0.54      0.71    0.91      1.15      1.51 0.60          0.00      0.13      0.27      0.42      0.58    0.82      1.02      1.38 6 taking a static measurement or a sample. Because scanning can be divided into two stages, it is 7 necessary to consider the surveys scan detection capability for each stage. Typically, the 8 minimum detectable count rate (MDCR) associated with the first scanning stage will be greater 9 due to the brief observation intervals of continuous monitoringprovided that the length of the 10 pause during the second stage is significantly longer. Typically, observation intervals during the 11 first stage are on the order of 1 or 2 seconds, while the second stage pause may be several 12 seconds longer. The greater value of MDCR from each of the scan stages is used to determine 13 the detection capability for the surveyor.
14 Determination of MDCR and Use of Surveyor Efficiency 15 The minimum detectable number of net source counts in the time interval is given by  .
16 Therefore, for an ideal observer, the number of source counts required for a specified level of 17 performance can be arrived at by multiplying the square root of the number of background 18 counts by the detectability value associated with the desired performance (as reflected in ) as 19 shown in Equation 6-6:
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                                                          =                              (6-6) 1 where the value of  is selected from Table 6.2 based on the required true positive and false 2 positive rates and  is the number of background counts in the interval. The MDCR can be 3 calculated using the Equation 6-7:
(6-7)
MDCR =
4 where  is the observation interval. Example 2 illustrates the calculation of the MDCR for a 5 probe with a background count rate of 1,500 counts per minute (cpm) for a 1-second interval.
Example 2: Calculation of the Minimum Detectable Count Rate for the First Stage of Scanning Estimate the minimum detectable count rate (MDCR) by scanning in an area with a background of 1,500 counts per minute (cpm). Note that the MDCR must be considered for both scan stages, and the more conservative value is selected as the minimum count rate that is detectable. It will be assumed that a typical source remains under the probe for 1 second (s) during the first stage, therefore, the average number of background counts in the observation interval is minute
                                = (1500 cpm)(1 s)                  = 25 counts 60 s where bi is the average number of background counts in an observation interval.
Furthermore, it can be assumed that at the first scanning stage, a high rate (e.g., 95 percent) of correct detections is required and that a correspondingly high rate of false positives (e.g.,
60 percent) will be tolerated. From Table 6.2, the value of , representing this performance goal is 1.38. The net source counts needed to support the specified level of performance (assuming an ideal observer) will be estimated by multiplying 5 (the square root of 25) by 1.38. Thus, the net source counts,  in interval  (in seconds), needed to yield better than 95 percent detections with about 60 percent false positives is given by Equation 6-6:
                                                = 1.38x25 = 6.9 The MDCR, in cpm, may be calculated using Equation 6-7:
6.9 counts      60 s MDCR =          =                          = 414 cpm 1s          minute where si is the minimum detectable number of net source counts and is over a time interval specified by ti. For this example, MDCR is equivalent to 414 cpm above a background of 1,500 cpm (1,914 cpm gross).
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Field Measurement Methods and Instrumentation                                                                MARSSIM 1 Example 3 illustrates the determination of the detection limit for the ideal observer (MDCR) at 2 the first scanning stage for various background levels for a true positive proportion of 95 percent 3 and false positive proportion of 60 percent.
Example 3: Determination of the Detection Limit for the Ideal Observer The table below provides the minimum detection count rate and detection limit for the ideal observer at the first scanning stage for various background levels, based on an index of sensitivity () of 1.38 for a true positive proportion of 95 percent, a false positive proportion of 60 percent, and a 2-second observation interval.
Detection Capability of the Ideal Observer for Various Background Levels Background            MDCR                Scan (cpm)          (net cpm)          Sensitivity (gross cpm)a 45                  50                  95 60                  60                120 260                120                380 300                130                430 350                140                490 400                150                550 1,000                240              1,240 3,000                410              3,410 4,000                480              4,480 Abbreviations: cpm = counts per minute; MDCR = minimum detectable count rate.
aThe detection capability of the ideal observer during the first scanning stage is based on an index of sensitivity (d') of 1.38 and a 2-second observational interval.
4 The minimum number of source counts required to support a given level of performance for the 5 final detection decision (second scan stage) can be estimated using the same method. As 6 explained earlier, the performance goal at this stage will be more demanding. Example 4 7 illustrates the calculation of the MDCR for the probe from Example 2 but with an interval of 8 4 seconds instead of 1 second.
Example 4: Calculation of the Minimum Detectable Count Rate for the Second Stage of Scanning The required rate of true positives remains high (e.g., 95 percent), but fewer false positives (e.g., 20 percent) can be tolerated, such that the index of sensitivity () (from Table 6.2) is now 2.48. One will assume that the surveyor typically stops the probe over a suspect location for about 4 seconds (s) before making a decision so that the average number of background counts in an observation interval is NUREG-1575, Revision 2                                    6-16                                              May 2020 DRAFT FOR PUBLIC COMMENT                                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                Field Measurement Methods and Instrumentation minute
                                = (1,500 cpm)(4 s)              = 100 counts 60 s where bi is the average number of background counts in an observation interval. Therefore, the minimum detectable number of net source counts,  , needed will be estimated by multiplying 10 (the square root of bi) by 2.48 (the  value) using Equation 6-6:
                                        =  = 2.48x100 = 24.8 The minimum detectable count rate (MDCR) is calculated using Equation 6-7:
24.8 counts      60 s MDCR =            =                        = 372 cpm 4s        minute where si is the minimum detectable number of net source counts and is over a time interval specified by ti. The MDCR is 372 counts per minute (cpm) net, or 1,872 cpm gross. The value associated with the first scanning stage (Example 2: 414 cpm net or 1,914 cpm gross) will typically be greater, owing to the relatively brief intervals assumed.
1 Laboratory studies using simulated sources and backgrounds were performed to assess the 2 abilities of surveyors under controlled conditions. The methodology and analysis of results for 3 these studies are described in NUREG-1507 (NRC 1997a). The surveyors actual performance 4 as compared with the ideal possible performance (using the ideal observer construct) provided 5 an indication of the efficiency of the surveyors. Based on the results of the confidence rating 6 experiment, this surveyor efficiency () was estimated to be between 0.5 and 0.75.
7 MARSSIM recommends assuming a surveyor efficiency value at the lower end of the observed 8 range (i.e., 0.5) when making MDC estimates. Thus, the required number of net source counts, 9 MDCRsurveyor, is determined by dividing the MDCR by the square root of , as in Equation 6-8:
MDCR                              (6-8)
MDCRsurveyor =
10 Example 5 shows the calculation of the surveyor MDCR for Example 1:
Example 5: Calculation of the Surveyor Minimum Detectable Count Rate for Example 1 Using the data from Example 1, the surveyor minimum detectable count rate (MDCR) is calculated using Equation 6-8:
MDCR      414 cpm MDCRsurveyor =            =            = 585 cpm 0.5 May 2020                                              6-17                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                      DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                          MARSSIM The surveyor MDCR is 585 counts per minute (cpm) net (2,085 cpm gross).
1 Scan MDCs for Structure Surfaces and Land Areas 2 The survey design for determining the number of data points for areas of elevated activity (see 3 Section 5.3.5) depends on the scan MDC for the selected instrumentation. In general, alpha or 4 beta scans are performed on structure surfaces to satisfy the elevated activity measurements 5 survey design, and gamma scans are performed for land areas. Because of low background 6 levels for alpha emitters, the approach described here is not generally applied to determining 7 scan MDCs for alpha emitters; rather, the reader is referred to Section 6.3.2.2 for an 8 appropriate method for determining alpha scan MDCs for building surfaces. In any case, the 9 data requirements for assessing potential elevated areas of direct radiation depend on the scan 10 MDC of the survey instrument (e.g., floor monitor, GM detector, sodium iodide [NaI] scintillation 11 detector).
12 Scan MDCs for Building/Structure Surfaces 13 The scan MDC is determined from the MDCR by applying conversion factors that account for 14 detector and surface characteristics and surveyor efficiency. As discussed above, the MDCR 15 accounts for the background level, performance criteria (d), and observation interval. The 16 observation interval during scanning is the actual time that the detector can respond to the 17 source of residual radioactive materialthis interval depends on the scan speed, detector size 18 in the direction of the scan, and area of elevated activity. Because the actual dimensions of 19 potential areas of elevated activity in the field cannot be known a priori, MARSSIM recommends 20 postulating a certain area (e.g., perhaps 50-200 cm2) and then selecting a scan rate that 21 provides a reasonable observation interval.
22 Finally, the scan MDC in units of decays per minute (dpm)/100 cm2 for structure surfaces may 23 be calculated using Equation 6-9:
MDCR Scan MDC =                                          (6-9) 100 24 where 25
* MDCR is the minimum detectable count rate 26
* is the instrument efficiency 27
* is the surface efficiency 28
* is the surveyor efficiency 29
* is the physical probe area in square centimeters 30
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MARSSIM                                              Field Measurement Methods and Instrumentation 1 Consideration may need to be given to the size of the detector probe relative to the size of the 2 postulated hot spot size. For example, a large area floor monitor with a probe area of 3 approximately 600 cm2 would fully cover the area of the postulated hot spot in the scenario 4 presented above (i.e., 50-200 cm2). In this situation, a probe area correction is likely not 5 appropriate. Example 6 illustrates the calculation of the scan MDC for the probe in Example 3 6 for technetium-99 (99Tc).
Example 6: Calculation of the Scan Minimum Detectable Concentration for the Probe in Example 3 As an example, the scan minimum detectable concentration (MDC) (in disintegrations per minute [dpm]/100 square centimeters [cm2]) for technetium-99 (99Tc) on a concrete surface may be determined for a background level of 300 counts per minute (cpm) and a 2-second observation interval using a hand-held gas proportional detector (126 cm2 probe area). For a specified level of performance at the first scanning stage of 95 percent true positive rate and 60 percent false positive rate (and assuming the second stage pause is long enough to ensure that the first stage is more limiting),  equals 1.38 (Table 6.2), and the minimum detectable count rate (MDCR) is 130 cpm (Example 3). Using a surveyor efficiency of 0.5, and assuming instrument and surface efficiencies of 0.36 and 0.54, respectively, the scan MDC is calculated using Equation 6-9:
MDCR                            130 cpm Scan MDC =                      =                                        = 750 dpm/100 cm2 126 cm 2 100  0.5 (0.36 x 0.54 cpm/dpm) 100 The scan MDC for 99Tc is 750 dpm/100 cm2.
7 Additional examples for calculating the scan MDC may be found in NUREG-1507 (NRC 1997a).
8 Scan MDCs for Land Areas 9 In addition to the MDCR and detector characteristics, the scan MDC for land areas is based on 10 the area of elevated activity, depth of contamination, and the radionuclide (i.e., energy and yield 11 of gamma emissions).
12 Thallium-infused NaI (NaI(Tl)) scintillation detectors are generally used for scanning land areas.
13 Typically, the detectors are placed just above the surveyed area. By hand, this can be done by 14 suspending the detector from the surveyors hand by a rope. By mechanical means, the 15 detector can be fixed from an automated device.
16 An overview of the approach used to determine scan MDCs for land areas follows. The NaI(Tl) 17 scintillation detector background level and scan rate (observation interval) are postulated, and 18 the MDCR for the ideal observer, for a given level of performance, is obtained. After a surveyor 19 efficiency is selected, the relationship between the surveyor MDCR (MDCRsurveyor) and the 20 radionuclide concentration in soil, in Bq/kilogram (kg) or picocuries/gram (pCi/g) is determined.
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Field Measurement Methods and Instrumentation                                              MARSSIM 1 This correlation requires two steps: First, the relationship between the detectors net count rate 2 to net exposure rate (cpm per microroentgens/hour [&#xb5;R/h]) is established, and second, the 3 relationship between the concentration of residual radioactive material and exposure rate is 4 determined.
5 For a particular gamma energy, the relationship of NaI(Tl) scintillation detector count rate and 6 exposure rate may be determined analytically (in cpm per &#xb5;R/h). The approach used to 7 determine the gamma fluence rate necessary to yield a fixed exposure rate (1 &#xb5;R/h)as a 8 function of gamma energyis provided in NUREG-1507 (NRC 1997a). The NaI(Tl) scintillation 9 detector response (in cpm) is related to the fluence rate at specific energies, considering the 10 detectors efficiency (probability of interaction) at each energy. From this, the NaI(Tl) detector 11 count rate versus exposure rates for varying gamma energies are determined. After the 12 relationship between the NaI(Tl) detector response and the exposure rate is established, the 13 MDCRsurveyor (in cpm) of the NaI(Tl) detector can be related to the minimum detectable exposure 14 rate (MDER) using Equation 6-10:
MDCRsurveyor MDER =                                                              (6-10)
Ratio of Count Rate to Exposure Rate 15 The MDER is used to determine the minimum detectable radionuclide concentration (i.e., the 16 scan MDC) by modeling a specified small area of elevated activity and then dividing the MDER 17 by the exposure rate conversion factor using Equation 6-11:
MDER Scan MDC =                                                            (6-11)
Exposure Rate Conversion Factor 18 Example 7 illustrates the calculation of the scan MDC for cesium-137 (137Cs) using a 38 19 millimeter (mm; 1.5 inch [in.]) by 32 mm (1.25 in.) NaI(Tl) scintillation detector.
Example 7: Calculation of a Scan Minimum Detectable Concentration for 137Cs Modeling (using MicroShield 5.05TM) of the small area of elevated activity (soil concentration) is used to determine the net exposure rate produced by a radionuclide concentration at a distance 10 centimeters (cm) above the source. This position is selected because it relates to the average height of the NaI(Tl) scintillation detector above the ground during scanning. The factors considered in the modeling include the following:
* radionuclide of interest (considering all gamma emitters for decay chains)
* expected concentration of the radionuclide of interest
* areal dimensions of the area of elevated activity
* depth of the area of elevated activity
* location of dose point (NaI(Tl) scintillation detector height above the surface)
* density and moisture content of soil Modeling analyses are conducted by selecting a radionuclide (or radioactive material decay series) and then varying the concentration of the radionuclide. The other factors are held NUREG-1575, Revision 2                            6-20                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                            Field Measurement Methods and Instrumentation constantthe areal dimension of a cylindrical area of elevated activity is 0.25 square meters (m2; radius of 28 cm), the depth of the area of elevated activity is 15 cm, the dose point is 10 cm above the surface, and the density of soil is 1.6 g/cm3. The soil was modeled as 50 percent aluminum and 50 percent carbon by weight. The objective is to determine the radionuclide concentration that is correlated to the minimum detectable net exposure rate.
The scan MDC for cesium-137 (137Cs) using a 38 millimeter (mm; 1.5 inch [in.]) by 32 mm (1.25 in.) NaI(Tl) scintillation detector is considered in detail. Assume that the background level is 4,000 counts per minute (cpm) and that the desired level of performance, 95 percent correct detections and 60 percent false positive rate, results in a  of 1.38. The scan rate of 0.5 m/second (s) provides an observation interval of 1 second (based on a diameter of about 56 cm for the area of elevated activity). The MDCRsurveyor may be calculated assuming a surveyor efficiency () of 0.5, as follows:
                        = (4,000 cpm)x(1 s)x(1 min60 s) = 66.7 counts MDCR =  x(60 s1 min) = (1.38)x 66.7 x(60 s1 min) = 680 cpm MDCR      680 cpm MDCRsurveyor =          =          = 960 cpm 0.5 The corresponding minimum detectable exposure rate (MDER) is determined for this detector and radionuclide. The manufacturer of this particular 38 mm (1.5 in.) by 32 mm (1.25 in.)
NaI(Tl) scintillation detector quotes a count rate to exposure rate ratio for 137Cs of 350 cpm per &#xb5;R/hour (h), which is equivalent to the Standard International System of Units of 1.36 cpm per picocoulomb (pC) per kilogram (kg) per hour (cpm/(pC/kg)/h). MDER can be calculated by dividing the MDCRsurveyor by the exposure rate ratio for 137Cs, as shown below:
960 cpm MDER =                            = 706 (pCi/kg)/h (2.74 R/h) 1.36 cpm/(pCi/kg)/h Both 137Cs and its short-lived progeny, 137mBa, are chosen from the MicroShield library. The source activity and other modeling parameters are entered into the modeling code. The source activity is selected based on an arbitrary concentration of 185 Bq/kg (5 picocuries
[pCi]/g). The modeling code performed the appropriate calculations and determined an exposure rate of 337 (pCi/kg)/h (1.307 R/h), which accounts for buildup.
Finally, the radionuclide concentrations of 137Cs and 137mBa (scan MDC) necessary to yield the minimum detectable exposure rate of 706 (pCi/kg)/h (2.74 &#xb5;R/h) may be calculated using the following formula:
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Field Measurement Methods and Instrumentation                                                MARSSIM 706 (pC/kg)/h scan MDC =                      = 390 Bq/kg 337 (pC/kg)/h 185 Bq/kg The scan MDC for 137Cs using a 38 mm (1.5 in.) by 32 mm (1.25 in.) NaI(Tl) scintillation detector, rounded to the appropriate number of significant digits, is 390 Bq/kg (11 pCi/g).
1 It must be emphasized that although a single scan MDC value can be calculated for a given 2 radionuclide, other scan MDC values may be equally justifiable, depending on the values 3 chosen for the various factors, including the MDCR (background level, acceptable performance 4 criteria, observation interval), surveyor efficiency, detector parameters, and the modeling 5 conditions of the residual radioactive material. It should also be noted that determination of the 6 scan MDC for radioactive materialssuch as uranium and thoriummust consider the gamma 7 radiation emitted from the entire decay series. NUREG-1507 (NRC 1997a) provides a detailed 8 example of how the scan MDC can be determined for enriched uranium.
9 Example 7 uses 137Cs as the radionuclide, which is the same radionuclide that is used to 10 calibrate the instrument. When doing gamma surveys for other radionuclides than 137Csthe 11 most common instrument calibration sourceinstruments may underestimate or overestimate 12 the source strength because of the different energies of the gamma rays that are emitted. This 13 uncertainty can be reduced or eliminated by cross calibrating the detector to energy 14 compensated detectors, such as pressurized ion chambers, or the instrument can be calibrated 15 to the specific radionuclide of concern.
16 Table 6.3 provides scan MDCs for common radionuclides and radioactive materials in soil. It is 17 important to note that the variables used in the above examples to determine the scan MDCs for 18 the 38 mm (1.5 in.) by 32 mm (1.25 in.) NaI(Tl) scintillation detector (i.e., the MDCRsurveyor 19 detector parameters (e.g., cpm per R/h), and the characteristics of the area of elevated 20 activity) have all been held constant to facilitate the calculation of scan MDCs provided in 21 Table 6.3. The benefit of this approach is that generally applicable scan MDCs are provided for 22 different radionuclides. Additionally, the relative detectability of different radionuclides is evident 23 because the only variable in Table 6.3 is the nature of the radionuclide.
24 As noted above, the scan MDCs calculated using the approach in this section are dependent on 25 several factors. One way to validate the appropriateness of the scan MDC is by tracking the 26 levels of residual radioactive material (both surface activity and soil concentrations) identified 27 during investigations performed as a result of scanning surveys. The measurements performed 28 during these investigations may provide an a posteriori estimate of the scan MDC that can be 29 used to validate the a priori scan MDC used to design the survey.
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MARSSIM                                                    Field Measurement Methods and Instrumentation 1 Table 6.3: NaI(Tl) Scintillation Detector Scan MDCs for Common Radionuclides and 2 Radioactive Materials 1.25 in. by 1.5 in. NaI      2 in. by 2 in. NaI Detectora Radionuclide/Radioactive                        Detectora Material                  Scan MDC          Weighted      Scan MDC          Weighted (Bq/kg)        cpm/&#xb5;R/h        (Bq/kg)        cpm/&#xb5;R/h 241Am                                              1,650            5,830          1,170            13,000 60Co                                                215              160            126              430 137Cs                                                385              350            237              900 230Th                                          111,000            4,300          78,400            9,580 226Ra (Individual radionuclide, in                        167              300            104              760 equilibrium with progeny) 232Th  decay series (Sum of all radionuclides in the                  1,050              340            677              830 thorium decay series)
Th-232 (Individual radionuclide, in 104              340          66.6              830 equilibrium with progeny in decay series)
Depleted Ub 2,980            1,680          2,070            3,790 (0.34% U-235)
U in natural isotopic abundanceb                  4,260            1,770          2,960            3,990 3% Enriched      Ub                              5,070            2,010          3,540            4,520 20% Enriched Ub                                    5,620            2,210          3,960            4,940 50% Enriched Ub                                    6,220            2,240          4,370            5,010 75% Enriched Ub                                    6,960            2,250          4,880            5,030 3 Abbreviations: in. = inch; MDC = minimum detectable concentration; Bq = becquerel; kg = kilogram; cpm = counts per 4 minute; R/h = microroentgens/hour.
5 a Refer to text for complete explanation of factors used to calculate scan MDCs. For example, the background level 6    for the 1.25 in. by 1.5 in. NaI detector was assumed to be 4,000 cpm, and 10,000 cpm for the 2 in. by 2 in. NaI 7    detector. The observation interval was 1 second, and the level of performance was selected to yield a performance 8    criteria (d) of 1.38.
9 b Scan MDC for uranium includes the sum of 238U, 235U, and 234U.
10 6.3.2.2 Scanning for Alpha Emitters 11 Scanning for alpha emitters differs significantly from scanning for beta and gamma emitters in 12 that the expected background response of most alpha detectors is very close to zero. The 13 following discussion covers scanning for alpha emitters and assumes that the surface being May 2020                                                  6-23                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                            DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                            MARSSIM 1 surveyed is similar in nature to the material on which the detector was calibrated. In this respect, 2 the approach is purely theoretical. Surveying surfaces that are dirty, non-planar, or weathered 3 can significantly affect the detection efficiency and therefore introduce bias to the expected 4 MDC for the scan. The use of reasonable detection efficiency values instead of optimistic values 5 is highly recommended. Appendix J contains a complete derivation of the alpha scanning 6 equations used in this section.
7 Because the time an area is under the probe varies and the background count rate of some 8 alpha instruments is less than 1 cpm, it is not practical to determine a fixed MDC for scanning.
9 Instead, it is more useful to determine the probability of detecting an area of residual radioactive 10 material at a predetermined DCGL for given scan rates.
11 For alpha survey instrumentation with backgrounds ranging from less than 1 to 3 cpm, a single 12 count provides a surveyor sufficient cause to stop and investigate further. Assuming this to be 13 true, the probability of detecting given levels of alpha-emitting radioactive materials on a surface 14 can be calculated by use of Poisson summation statistics.
15 Given a known scan rate and a DCGL for residual radioactive material on a surface, the 16 probability of detecting a single count while passing over the contaminated area is calculated 17 using Equation 6-12:
(  1) = 1    60                          (6-12) 18 where 19 *  (  1) is the probability of observing one or more counts 20
* is the activity in disintegrations per minute (dpm) 21
* is the detector efficiency (4) 22
* is width of the detector in the direction of the scan in centimeters 23
* is the scan speed in centimeters/second 24 Equation 6-12 may be solved for a minimum detectable alpha concentration by assessing 25 the probability of detection using Poisson summation statistics. Specifically, by defining a 26 certain probability of detection, the alpha scan minimum detectable activity (MDA) may be 27 estimated by solving Equation 6-12 for , as shown in Equation 6-13, where i is the 28 observation interval (in seconds) that can be calculated as  /  from Equation 6-12:
ln1  (  1) x (60/)
Alpha Scan MDA =                                                  (6-13) 29 The scan MDC calculation may be written to account for the probe area, as shown in 30 Equation 6-14:
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MARSSIM                                                Field Measurement Methods and Instrumentation ln1  (  1) x (60/)
Alpha Scan MDC =                                                                (6-14) x 100 1 where  is the physical probe area (cm2) and the Alpha Scan MDC is in units of dpm/100 cm2.
2            Note: This evaluation is shown for the situation where a surveyor is expected to 3            respond to one single count and would become more complex for 2 or more 4            counts. It is also necessary to define an acceptable probability of detection, 5            which should be considered during the DQO process and may require 6            consultation with the regulator.
7 After a count is recorded and the guideline level of residual radioactive material is present, the 8 surveyor should stop and wait until the probability of getting another count is at least 90 percent.
9 This time interval can be calculated by using Equation 6-15:
ln1  (  1) x 60 x 100                  13,800
                              =                                            =                              (6-15) x  x                      x  x 10 where 11
* is the time period for static count in seconds 12
* is the DCGL in dpm/100 cm2 13
* is the physical probe area (in cm2) 14
* is the detector efficiency (4) 15 Many portable proportional counters have background count rates on the order of 5-10 cpm, 16 and a single count should not cause a surveyor to investigate further. A counting period long 17 enough to establish that a single count indicates that an elevated level would be prohibitively 18 inefficient. For these types of instruments, the surveyor usually will need to get at least 2 counts 19 while passing over the source area before stopping for further investigation.
20 Assuming this to be a valid assumption, the probability of getting two or more counts can be 21 calculated using Equation 6-16:
(  2) = 1  ( = 0)  ( = 1)
( + )        ( +)
(6-16)
                                            = 1  1 +                      60 60 22 where (  2) is probability of getting 2 or more counts during the time interval t; ( = 0) is 23 the probability of not getting any counts during the time interval t; ( = 1) is the probability of May 2020                                              6-25                                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                                    DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                                      MARSSIM 1 getting exactly 1 count during the time interval ; and  is the background count rate (cpm). All 2 other variables are the same as in Equation 6-10.
3 Appendix J provides a complete derivation of Equations 6-12 through 6-16 and a detailed 4 discussion of the probability of detecting residual alpha-emitting radioactive material on surfaces 5 for several different variables. Several probability charts are included at the end of Appendix J 6 for common detector sizes. Table 6.4 provides estimates of the probability of detecting 7 300 dpm/100 cm2 for some commonly used alpha detectors.
8 Table 6.4: Probability of Detecting 300 dpm/100 cm2 of Alpha Activity While Scanning 9 with Alpha Detectors Using an Audible Output (Calculated Using Equation 6-16)
Detection        Probe Dimension                          Probability of Scan Rate Detector Type        Efficiency        in Direction of                            detecting (cm/s)
(cpm/dpm)            Scan (cm)                            300 dpm/100 cm2 Proportional              0.20                  5                    3                  80%
Proportional              0.15                  15                    5                  90%
Scintillation            0.15                  5                    3                  70%
Scintillation            0.15                  10                    3                  90%
10 Abbreviations: cpm = counts per minute; dpm = decays per minute; cm = centimeters; s = seconds.
11 6.4    Measurement Uncertainty 12 The quality of measurement data will be directly affected by the magnitude of the measurement 13 uncertainty associated with it. Some uncertainties, such as statistical counting uncertainties, can 14 be easily calculated from the count results using mathematical procedures. Evaluation of other 15 sources of uncertainty requires more effort and in some cases is not possible. For example, if 16 an alpha activity measurement is made on a porous concrete surface, the observed instrument 17 response when converted to units of activity will probably not exactly equal the true activity 18 under the probe. Variations in the absorption properties of the surface for particulate radiation 19 will vary from point to point and therefore will create some level of variation in the expected 20 detection efficiency. This variability in the expected detector efficiency results in uncertainty in 21 the final reported result.
22 The measurement uncertainty for every analytical result or series of results, such as for a 23 measurement system, should be reported. This uncertainty, although not directly used for 24 demonstrating compliance with the release criteria, is used for survey planning and data 25 assessment throughout the Radiation Survey and Site Investigation (RSSI) process. In addition, 26 the uncertainty is used for evaluating the performance of measurement systems using quality 27 control (QC) measurement results. QC measurement results provide an estimate of random and 28 systematic uncertainties associated with the measurement process. Uncertainty can also be 29 used for comparing individual measurements to the DCGL. This is especially important in the 30 early stages of remediation (i.e., scoping, characterization, remedial action support) when 31 decisions are made based on a limited number of measurements.
32 Finally, where controlling uncertainty is important, a required uncertainty can be specified or a 33 minimum quantifiable concentration (MQC) can be defined. The MQC could, for example, be NUREG-1575, Revision 2                              6-26                                          May 2020 DRAFT FOR PUBLIC COMMENT                                                        DO NOT CITE OR QUOTE
 
MARSSIM                                          Field Measurement Methods and Instrumentation 1 that concentration of residual radioactive material that can be quantified with an uncertainty no 2 greater than some limit (e.g., 10 percent) at some specified concentration (e.g., the DCGL).
3 For most sites, evaluations of uncertainty associated with field measurements are important 4 only for data being used as part of the final status survey (FSS) documentation. The FSS data, 5 which is used to document the final radiological status of a site, should state the uncertainties 6 associated with the measurements. Conversely, detailing the uncertainties associated with 7 measurements made during scoping or characterization surveys may or may not be of value, 8 depending on what the data will be used for, as defined by the DQOs. From a practical 9 standpoint, if the observed data are obviously greater than the DCGL and will be eventually 10 cleaned up, then the uncertainty may be relatively unimportant. Conversely, data collected 11 during early phases of a site investigation that may eventually be used to show that the area is 12 below the DCGL, and therefore does not require any cleanup action, will need the same 13 uncertainty evaluation as the FSS data. In summary, the level of effort needed to evaluate the 14 uncertainty should match the intended use of the data.
15 6.4.1    Systematic and Random Uncertainties 16 Measurement uncertainties are often broken into two subclasses: systematic uncertainty 17 (e.g., methodical) and random uncertainty (e.g., stochastic). Systematic uncertainties derive 18 from a lack of knowledge about the true distribution of values associated with a numerical 19 parameter and result in data that are consistently higher or lower than the true value. An 20 example of a systematic uncertainty would be the use of a fixed counting efficiency value 21 without knowledge of the frequency, even though it is known that the efficiency varies from 22 measurement to measurement. If the fixed counting efficiency value is higher than the true but 23 unknown efficiencyas would be the case for an unrealistically optimistic valuethen every 24 measurement result calculated using that efficiency would be biased low. Random uncertainties 25 refer to fluctuations associated with a known distribution of values. An example of a random 26 uncertainty would be a well-documented chemical separation efficiency that is known to 27 fluctuate with a regular pattern about a mean. A constant recovery value is used during 28 calculations, but the true value is known to fluctuate from sample to sample with a fixed and 29 known degree of variation.
30 To minimize the need for estimating potential sources of uncertainty, the sources of uncertainty 31 themselves should be reduced to a minimal level by using such practices as the following:
32
* The detector used should minimize the potential uncertainty. For example, when making 33    field surface activity measurements for 238U on concrete, a beta detectorsuch as a thin-34    window GM pancake probemay provide better quality data than an alpha detector, 35    depending on the circumstances. Less random uncertainty would be expected between 36    measurements with a beta detector, such as a pancake probe, because beta emissions 37    from the uranium will be affected much less by thin, absorbent layers than the alpha 38    emissions will.
39
* Calibration factors should accurately reflect the efficiency of the detector used on the 40    surface material being measured for the radionuclide or mixture of radionuclides of concern May 2020                                        6-27                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                              MARSSIM 1    (see Section 6.6.4). For most field measurements, variations in the counting efficiency on 2    different types of materials will introduce the largest amount of uncertainty in the final result.
3
* Uncertainties should be reduced or eliminated by using standardized measurement 4    protocols (e.g., SOPs) when possible. Special effort should be made to reduce or eliminate 5    systematic uncertainties, or uncertainties that are the same for every measurement simply 6    due to an error in the process. If the systematic uncertainties are reduced to a negligible 7    level, then the random uncertainties, or those uncertainties that occur on a somewhat 8    statistical basis, can be dealt with more easily.
9
* Instrument operators should be trained and experienced with the instruments used to 10    perform the measurements.
11
* Quality assurance/quality control (QA/QC) should be conducted.
12 Uncertainties that cannot be eliminated need to be evaluated such that the effect can be 13 understood and properly propagated into the final data and uncertainty estimates. As previously 14 stated, nonstatistical uncertainties should be minimized as much as possible using good work 15 practices.
16 Overall random uncertainty can be evaluated using the methods described in the following 17 sections:
18
* Section 6.4.2 describes a method for calculating random counting uncertainty.
19
* Section 6.4.3 discusses how to combine this counting uncertainty with other uncertainties from the 20    measurement process using uncertainty propagation.
21 Systematic uncertainty is derived from calibration errors, incorrect yields and efficiencies, 22 nonrepresentative survey designs, and blunders. It is difficultand sometimes impossibleto 23 evaluate the systematic uncertainty for a measurement process, but bounds should always be 24 estimated and made small compared to the random uncertainty, if possible. If no other 25 information on systematic uncertainty is available, Currie (NRC 1984) recommends using 26 16 percent as an estimate for systematic uncertainties (1 percent for blanks, 5 percent for 27 baseline, and 10 percent for calibration factors).
28 6.4.2    Statistical Counting Uncertainty 29 When performing an analysis with a radiation detector, the result will have an uncertainty 30 associated with it because of the statistical nature of radioactive decay. To calculate the total 31 uncertainty associated with the counting process, both the background measurement 32 uncertainty and the sample measurement uncertainty must be accounted for. The standard 33 deviation of the net count rate, or the statistical counting uncertainty, can be calculated using 34 Equation 6-17:
                                                      +
                                              =  2 + 2                                      (6-17)
                                                      +
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MARSSIM                                                        Field Measurement Methods and Instrumentation 1 where 2
* is the standard deviation of the net count rate result 3 *  + is the number of gross counts (sample) 4 *  + is the gross count time 5
* is the number of background counts 6
* is the background count time 7 6.4.3      Uncertainty Propagation 8 Most measurement data will be converted to different units or otherwise included in a calculation 9 to determine a final result. The standard deviation associated with the final result, or the total 10 uncertainty, can then be calculated. Assuming the individual uncertainties are relatively small, 11 symmetric about zero, and independent of one another, then the total uncertainty for the final 12 calculated result can be determined by solving the following partial differential equation:
2 2          2 2              2 2
                                    =        1 +        2 +  +                      (6-18) 1            2 13 where  = (1 , 2 ,  ) is a formula that defines the calculation of a final result as a function of 14 the collected data. All variables in this equation (i.e., 1 , 2 ,  ) are assumed to have a 15 measurement uncertainty associated with them and do not include numerical constants. is 16 the standard deviation, or uncertainty, associated with the final result, and 1 , 2 ,  are the 17 standard deviations, or uncertainties, associated with the parameters 1 , 2 ,  , respectively.
18 Equation 6-18, generally known as the error propagation formula, can be solved to determine 19 the standard deviation of a final result from calculations involving measurement data and their 20 associated uncertainties. The solutions for common calculations along with their uncertainty 21 propagation formulas are included in Table 6.5.
22            Note: In the above examples, 1 and 2 are measurement values with associated 23            standard deviations, or uncertainties, equal to 1 and 2 , respectively. The 24            symbol  is used to represent a numerical constant which has no associated 25            uncertainty. The symbol  is used to denote the standard deviation, or 26            uncertainty, of the final calculated value, .
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Field Measurement Methods and Instrumentation                                                        MARSSIM 1 Table 6.5: Common Uncertainty Propagation Equations Data Calculation                        Uncertainty Propagation
                        = 1 + 2 or  = 1  2                      = 21 + 22 1 2      2
                        = 1 /2 or  = 1 x 2                =          +  2 1        2
            = 1 where  is a positive constant                            = 1 1
            = 1 / where  is a positive constant                            =
2 6.4.4    Reporting Confidence Intervals 3 Throughout Section 6.4, the term measurement uncertainty is used interchangeably with the 4 term standard deviation. In this respect, the uncertainty is qualified as numerically identical to 5 the standard deviation associated with a normally distributed range of values. When reporting a 6 confidence interval for a value, one provides the range of values that represent a predetermined 7 level of confidence (i.e., 95 percent). To make this calculation, the final standard deviationor 8 total uncertainty  , as shown in Equation 6-18is multiplied by a constant factor k, 9 representing the area under a normal curve as a function of the standard deviation. The values 10 of k representing various intervals about a mean of normal distributions as a function of the 11 standard deviation are given in Table 6.6. The following example illustrates the use of this factor 12 in context with the propagation and reporting of uncertainty values. Example 8 demonstrates 13 the calculation of the activity of a sample, along with its associated activity.
14 Table 6.6: Areas Under Various Intervals About the Mean of a Normal Distribution Interval                      Area Under the
(&#xb5; +/- )
A Interval
            &#xb5; +/- 0.674 A
0.500
              &#xb5; +/- 1.00 A
0.683
              &#xb5; +/- 1.65 A
0.900
              &#xb5; +/- 1.96 A
0.950
              &#xb5; +/- 2.00 A
0.954
              &#xb5; +/- 2.58 A
0.990
              &#xb5; +/- 3.00 A
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MARSSIM                                              Field Measurement Methods and Instrumentation 1
Example 8: Uncertainty Propagation and Confidence Interval A measurement process with a zero background yields a count result of 28 +/- 5 counts in 5 minutes, where the +/- 5 counts represents one standard deviation about a mean value of 28 counts. The detection efficiency is 0.1 +/- 0.01 counts per disintegration, again representing one standard deviation about the mean.
Calculate the activity of the sample, in decays per minute (dpm), total measurement uncertainty, and the 95 percent confidence interval for the result.
The total number of disintegrations is 1              28 counts
                          =      =                            = 280 disintegrations 2    0.1 countsdisintegration Using the equation for error propagation for division, total uncertainty is 1 2    2 2 5 2 0.01 2
                  =  +  = 280  +                    = 57 disintegrations 1        2            28    0.1 The activity will then be 280/5 minutes = 56 dpm and the total uncertainty will be 57 &#xf7; 5 minutes = 11 dpm. (Because the count time is considered to have trivial variance, this is assumed to be a constant.)
Referring to Table 6.6, a k value of +/- 1.96 represents a confidence interval equal to 95 percent about the mean of a normal distribution. Therefore, the 95 percent confidence interval would be 1.96 x 11 dpm = 22 dpm. The final result would be that a 95 percent confidence interval for mean activity is 56 +/- 22 dpm at a coverage factor of k equal to 1.96.
2 6.5    Select a Service Provider to Perform Field Data Collection Activities 3 Often, one of the first steps in designing a survey is to select a service provider to perform field 4 data collection activities. MARSSIM recommends that this selection take place early in the 5 planning process so that the service provider can provide information during survey planning 6 and participate in the design of the survey. Service providers may include in-house experts in 7 field measurements and sample collection, health physics companies, or environmental 8 engineering firms, among others. See Section 6.8 and Appendix H for important information 9 concerning radon service providers.
10 Potential service providers should be evaluated to determine their ability to perform the 11 necessary analyses. Consideration should be given to using a field survey company that is 12 separate from the remediation company to preclude questions of independence and conflict of May 2020                                            6-31                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                              MARSSIM 1 interest. For large or complex sites, this evaluation may take the form of a pre-award audit. The 2 results of this audit provide a written record of the decision to use a specific service provider.
3 For less complex sites or facilities, a review of the potential service providers qualifications is 4 sufficient for the evaluation.
5 Six criteria should be reviewed during this evaluation:
6
* Does the service provider possess the validated SOPs, appropriate instrumentation, and 7    trained personnel necessary to perform the field data collection activities, including 8    radon/thoron measurements? Field data collection activities (e.g., scanning surveys, direct 9    measurements, and sample collection) are defined by the data needs identified by the DQO 10    process.
11
* Is the service provider experienced in performing the same or similar data collection 12    activities?
13
* Does the service provider have satisfactory performance evaluation or technical review 14    results? The service provider should be able to provide a summary of QA audits and QC 15    measurement results to demonstrate proficiency. Equipment calibrations should be 16    performed using National Institute of Standards and Technology (NIST) traceable reference 17    radionuclide standards whenever possible.
18
* Is there adequate capacity to perform all field data collection activities within the desired 19    timeframe? This criterion considers the number of trained personnel and quantity of 20    calibrated equipment available to perform the specified tasks.
21
* Does the service provider conduct an internal QC review of all generated data that is 22    independent of the data generators?
23
* Are there adequate protocols for method performance documentation, sample tracking and 24    security (if necessary), and documentation of results?
25 Chapter 10 of MARLAP provides additional guidance related to field and sampling issues that 26 affect laboratory measurements (NRC 2004). Potential service providers should have an active 27 and fully documented quality system in place. The quality management system is typically 28 documented in one or more documents such as a Quality Management Plan (QMP) or Quality 29 Assurance Manual (QAM). This system should enable compliance with the objectives 30 determined by the DQO process in Section 2.3 (see also EPA 2006c). The elements of a 31 quality management system are discussed in Appendix D and EPA QA/G-5 (EPA 2002a).
32 6.6    Select a Measurement Method 33 The combination of a measurement technique with instrumentation, or measurement method, is 34 selected to implement a radiological survey design based on the ability to meet the MQOs (see 35 Section 6.1). Note that measurement techniques are separate from survey designs. A realistic 36 determination of the measurement method uncertainty is critical to demonstrating a method 37 meets the MQOs. Other considerations when selecting a measurement method include NUREG-1575, Revision 2                          6-32                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                          Field Measurement Methods and Instrumentation 1
* health and safety concerns (Section 4.10) 2
* required detection capability (Section 6.3) 3
* required measurement method uncertainty and/or required measurement quantifiability 4      (Section 6.4) 5
* DQOs for the project 6 Measurement techniques are discussed in Section 6.6.1. Instrumentation includes a 7 combination of a radiation detector (Section 6.6.2) and a display (Section 6.6.3). Evaluation of 8 a measurement method and comparison to MQOs also requires an understanding of the 9 instrument calibration (Section 6.6.4). Instrumentation for performing radiological 10 measurements is varied and constantly being improved. Section 6.6.5 provides an overview of 11 some commonly used types of instruments and how they might be applied to FSSs. The 12 purpose of the discussions on instrumentation is not to provide an exhaustive list of acceptable 13 instruments, but to provide examples of how instrumentation and measurement techniques can 14 be combined to meet the survey objectives. Additional information on instrumentation is found in 15 Appendix H.
16 Section 6.6.6 provides information on selecting a combination of measurement technique and 17 instrumentation to provide a measurement method. It is necessary that the selected 18 measurement method meet the MQOs established during survey design. Selecting 19 instrumentation can be an iterative process. Certain MQOs (e.g., MDC, required measurement 20 method uncertainty) may not be attainable with some measurement methods. In some cases, 21 selection of a different instrument may be all that is necessary, and in other cases a different 22 measurement technique or an entirely different measurement method will need to be 23 considered. Finally, in cases where the MQOs cannot be met with any available measurement 24 methods, consult with the regulator for acceptable options.
25 6.6.1    Select a Measurement Technique 26 A measurement technique describes how a measurement is performed. The detector can be 27 moved relative to the surface being measured (i.e., scanning), used to perform static 28 measurements at a specified location in the survey unit (i.e., in situ or direct measurements), or 29 some representative portion of the survey unit taken to a different location for analysis 30 (i.e., sampling). These three measurement techniques are described in Section 6.6.1.1, 31 Section 6.6.1.2, and Section 6.6.1.3, respectively. Smears are a type of sampling, where a 32 portion of the removable radioactive material is collected from the surface being investigated 33 (Section 6.6.1.4).
34 6.6.1.1 Scanning Techniques 35 Scanning techniques generally consist of moving portable radiation detectors at a specified 36 distance relative to the physical surface of a survey unit at some specified speed to meet the 37 MQOs. Scanning is used in surveys to locate radiation anomalies by searching for variations in 38 readings, indicating gross activity levels that may require further investigation or action.
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Field Measurement Methods and Instrumentation                                            MARSSIM 1 Scanning techniques can more readily provide thorough coverage of a given survey unit and are 2 often relatively quick and inexpensive to perform.
3 Scanning techniques can be used alone to demonstrate that concentrations of radioactive 4 material do not exceed release criteria. These surveys are referred to as scan-only surveys and 5 are discussed in detail in Section 5.3.6.1. Important considerations include that the scan MDC 6 and measurement method uncertainty are sufficient to meet MQOs to both quantify the average 7 concentration of the radioactive material and to identify areas of elevated activity. Scanning 8 equipment coupled with GPS or other locational data is strongly recommended for scan-only 9 surveys.
10 Maintaining the specified distance and speed during scanning can be difficult, especially with 11 hand-held instruments and irregularly shaped surfaces. Variations in source-to-detector 12 distance and scan speed can result in increased total measurement method uncertainty.
13 Determining a calibration function for situations other than surficial radionuclides uniformly 14 distributed on a plane can be complicated and may also contribute to the total measurement 15 method uncertainty.
16 6.6.1.2 Direct Measurements 17 Direct measurements, also referred to as in situ measurements, are taken by placing the 18 instrument in a fixed position at a specified distance from the surface of a given survey unit and 19 taking a discrete measurement for a pre-determined time interval. Direct measurements may be 20 combined with scanning measurements in a FSS design. In situ measurements are used 21 generally to provide an estimate of the average radionuclide concentration or level of activity 22 over a certain area or volume defined by the calibration function. In situ techniques are not 23 typically used to identify or quantify small areas or volumes of elevated radionuclide 24 concentration or activity.
25 Determining a calibration function and the associated MDA/MDC can be complicated and may 26 contribute to the total measurement method uncertainty, especially for situations other than 27 radionuclides uniformly distributed on a plane or through a regularly shaped volume (e.g., a disk 28 or cylinder).
29 However, in applicable situations and at the concurrence of the regulator, direct measurements 30 may be substituted for laboratory analysis. For example, all or a fraction of the systematic soil 31 samples may be measured in situ rather than traditional laboratory analysis.
32 6.6.1.3 Sampling 33 Sampling consists of removing a representative portion of the survey unit for separate 34 laboratory analysis. This measurement method generally has greater detection capability and 35 less measurement uncertainty than techniques that may be implemented as scanning or direct 36 measurements. Sampling is discussed in more detail in Chapter 7.
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MARSSIM                                          Field Measurement Methods and Instrumentation 1 6.6.1.4 Smears 2 Smears, sometimes referred to as smear tests, swipes, or wipes, are used to provide an 3 estimate of removable radioactive material on the surface. Smears are a type of sample where 4 a filter paper or other substance is used to wipe a specified area of a surface. The filter paper or 5 other substance is then tested for the presence of removable radioactive material. The amount 6 of removable radioactive material transferred to the smear will depend on a number of factors, 7 including the type of swipe or smear material, the method used, the physical and chemical 8 nature of the surface being tested, the surface roughness, and the physical and chemical nature 9 of the radioactive material. These factors result in the need to establish a removal factor that will 10 be subject to some uncertainty. For this reason, although smears with detectable radioactive 11 material provide a qualitative indication of removable radioactive material, caution should be 12 exercised when using any quantitative results from smears. EPA 600/R-11/122 (EPA 2011) 13 provides more detailed guidance on the use of smears.
14 6.6.2    Select InstrumentationRadiation Detectors 15 The particular capabilities of a radiation detector will establish its potential applications in 16 conducting a specific type of survey. Radiation detectors can be divided into four general 17 classes based on the detector material or the application: (1) gas-filled detectors, (2) scintillation 18 detectors, (3) solid-state detectors, and (4) passive integrating detectors. See Appendix H for 19 more information on the detectors discussed in this section.
20 6.6.2.1 Gas-Filled Detectors 21 Radiation interacts with the fill gas, producing ion-pairs that are collected by charged electrodes.
22 Commonly used gas-filled detectors are categorized as ionization, proportional, or GM, referring 23 to the region of gas amplification in which they are operated. The fill gas varies, but the most 24 common are 25
* air 26
* argon with a small amount of methane (usually 10 percent methane by mass, referred to as 27      P-10 gas) 28
* neon or helium with a small amount of a halogen (e.g., chlorine or bromine) added as a 29      quenching agent 30 6.6.2.2 Scintillation Detectors 31 Radiation interacts with a solid or liquid medium, causing electronic transitions to excited states 32 in a luminescent material. The excited states decay rapidly, emitting photons that, in turn, are 33 captured by a photomultiplier tube. The ensuing electrical signal is proportional to the scintillator 34 light output, which, under the right conditions, is proportional to the energy loss that produced 35 the scintillation. The most common scintillator materials are NaI(Tl), silver-activated zinc sulfide 36 (ZnS(Ag)), cadmium telluride (CdTe), thallium-activated cesium iodide (CsI(Tl)), and plastic May 2020                                        6-35                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                              MARSSIM 1 organic scintillators. The most traditional radiation survey instruments are the NaI(Tl) detector 2 used for gamma surveys and the ZnS(Ag) detector for alpha surveys.
3 6.6.2.3 Solid-State Detectors 4 Radiation interacting with a semiconductor material creates electron-hole pairs that are 5 collected by a charged electrode. The design and operating conditions of a specific solid-state 6 detector determines the types of radiations (alpha, beta, or gamma) that can be measured, the 7 detection limit of the measurements, and the ability of the detector to resolve the energies of the 8 interacting radiations. The common semiconductor materials in use are germanium, silicon, and 9 cadmium zinc telluride (CZT), which are available in both n and p types in various 10 configurations.
11 Spectrometric techniques using these detectors provide a marked increase in energy resolution 12 in many situations. When a particular radionuclide contributes only a fraction of the total particle 13 fluence, photon fluence, or both from all sources (natural or manmade background), gross 14 measurements are inadequate and nuclide-specific measurements are necessary.
15 Spectrometry provides the means to discriminate among various radionuclides based on 16 characteristic energies. Direct gamma spectrometry is particularly effective in field 17 measurements, because the penetrating nature of the radiation allows one to see beyond 18 immediate radioactive materials on the surface. The availability of large, high-efficiency 19 germanium detectors permits measurement of low-abundance gamma emitters, such as 238U.
20 6.6.2.4 Passive Integrating Detectors 21 An additional class of instruments consists of passive, integrating detectors and associated 22 reading/analyzing instruments. The integrated ionization is read using a laboratory or hand-held 23 reader. This class includes thermoluminescent dosimeters (TLDs), optically stimulated 24 luminescence (OSL) dosimeters, and electret ion chambers (EICs). Because these detectors 25 are passive and can be exposed for relatively long periods of time, they can provide better 26 sensitivity for measuring low activity levels, such as free release limits, or for ongoing 27 surveillance. The ability to read and present data onsite is a useful feature, and such systems 28 are comparable to direct reading instruments.
29 The scintillation materials in Section 6.6.2.2 are selected for their prompt fluorescence 30 characteristics. In another class of inorganic crystals, called TLDs, the crystal material and 31 impurities are chosen so that the free electrons and holes created following the absorption of 32 energy from the radiation are trapped by impurities in the crystalline lattice, thus locking the 33 excitation energy in the crystal. Such materials are used as passive, integrating detectors. After 34 removal from the exposure area, the TLDs are heated in a reader, which measures the total 35 amount of light produced when the energy is released. The total amount of light is proportional 36 to the number of trapped, excited electrons, which, in turn, is proportional to the amount of 37 energy absorbed from the radiation. The intensity of the light emitted from the 38 thermoluminescent crystals is thus directly proportional to the radiation dose. TLDs come in a 39 large number of materials, the most common of which are lithium fluoride (LiF), manganese-40 activated calcium fluoride (CaF2:Mn), dysprosium-activated calcium fluoride (CaF2:Dy),
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MARSSIM                                            Field Measurement Methods and Instrumentation 1 manganese-activated calcium sulfate (CaSO4:Mn), dysprosium-activated calcium sulfate 2 (CaSO4:Dy), and carbon-activated aluminum oxide (Al2O3:C).
3 OSL dosimeters are similar in principle to TLDs but use light instead of heat to release the free 4 electrons and holes trapped when radiation is absorbed. Advantages of OSL dosimeters over 5 TLDs include lower limits of detection and the fact that OSL dosimeters can be read multiple 6 times and can be reread later, if necessary.
7 The EIC consists of a very stable electret (a charged Teflon disk) mounted inside a small 8 chamber made of electrically charged plastic. The ions produced inside this air-filled chamber 9 are collected onto the electret, causing a reduction of its surface charge. The reduction in 10 charge is a function of the total ionization during a specific monitoring period and the specific 11 chamber volume. This change in voltage is measured with a surface potential voltmeter.
12 6.6.3  Display and Recording Equipment 13 Radiation detectors are connected to electronic devices to (1) provide a source of power for 14 detector operation and (2) enable measurement of the quantity or quality of the radiation 15 interactions that are occurring in the detector. The quality of the radiation interaction refers to 16 the amount of energy transferred to the detector. In many cases, radiation interacts with other 17 material (e.g., air) before interacting with the detector or only partially interacts with the detector 18 (e.g., Compton scattering or pair production for photons). Because the energy recorded by the 19 detector is affected, there is an increased probability of incorrectly identifying the radionuclide.
20 The most common recording or display device used for portable radiation measurement 21 systems is a ratemeter. This device provides a display on either an analog meter representing 22 the number of events occurring over some time period (e.g., cpm), or, in the case of digital 23 ratemeters, on a digital display. The number of events can also be accumulated over a preset 24 time period using a digital scaling device. The resulting information from a scaling device is the 25 total number of events that occurred over a fixed period of time, where a ratemeter display 26 varies with time and represents a short-term average of the event rate. Determining the average 27 level on a ratemeter will require judgment by the user, especially when a low frequency of 28 events results in significant variations in the meter reading. The use of a ratemeter, although 29 acceptable for certain scanning applications, is discouraged for performing fixed measurements 30 (e.g., gross alpha/beta.)
31 Pulse height analyzers are specialized electronic devices designed to measure and record the 32 number of pulses or events that occur at different pulse height levels at specific energies. These 33 types of devices are used with detectors that produce output pulses proportional in height to the 34 energy deposited within them by the interacting radiation. They can be used to record only 35 those events occurring in a detector within a single band of energy or can simultaneously record 36 the events in multiple energy ranges. In the former case, the equipment is known as a single-37 channel analyzer; the latter application is referred to as a multichannel analyzer. Both types of 38 analyzers can quantify specific radionuclides.
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Field Measurement Methods and Instrumentation                                              MARSSIM 1 6.6.4    Instrument Calibration 2 Calibration refers to the determination and adjustment of the instrument response in a particular 3 radiation field of known intensity. Proper calibration procedures are an essential requisite toward 4 providing confidence in measurements made to demonstrate compliance with remediation 5 criteria. Certain factors, such as energy dependence and environmental conditions, require 6 consideration in the calibration process, depending on the conditions of use of the instrument in 7 the field. Considerations for the use and calibration of instruments include 8
* the radiation type for which the instrument is designed 9
* the radiation energies within the range of energies for which the instrument is designed 10
* the environmental conditions for which the instrument is designed 11
* the influencing factors, such as magnetic and electrostatic fields, for which the instrument is 12      designed 13
* the orientation of the instrument, such that geotropic (gravity) effects are not a concern 14
* the manner the instrument is used, such that it will not be subject to mechanical or thermal 15      stress beyond that for which it is designed 16 Routine calibration commonly involves the use of one or more sources of a specific radiation 17 type and energy and of sufficient activity to provide adequate field intensities for calibration on 18 all ranges of concern.
19 Actual field conditions under which the radiation detection instrument will be used may differ 20 significantly from those present during routine calibration. Factors that may affect calibration 21 validity include 22
* The energies of radioactive sources used for routine calibration may differ significantly from 23      those of radionuclides in the field.
24
* The source-detector geometry (e.g., point source or large area distributed source) used for 25      routine calibration may be different than that found in the field.
26
* The source-to-detector distance typically used for routine calibration may not always be 27      achievable in the field.
28
* The condition and composition of the surface being monitored (e.g., sealed concrete, 29      scabbled concrete, carbon steel, stainless steel, and wood) and the presence of overlaying 30      material (e.g., water, dust, oil, paint) may result in a decreased instrument response relative 31      to that observed during routine calibration.
32 If the actual field conditions differ significantly from the calibration assumptions, a special 33 calibration for specific field conditions may be required. Such an extensive calibration need only 34 be done once to determine the effects of the range of field conditions that may be encountered NUREG-1575, Revision 2                              6-38                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                            Field Measurement Methods and Instrumentation 1 at the site. If responses under routine calibration conditions and proposed use conditions are 2 significantly different, a correction factor or chart should be supplied with the instrument for use 3 under the proposed conditions.
4 As a minimum, each measurement system (detector/readout combination) should be calibrated 5 annually and response checked with a source following calibration (ANSI 2013). Instruments 6 may require more frequent calibration, if recommended by the manufacturer. Re-calibration of 7 field instruments is also required if an instrument fails a performance check or if it has 8 undergone repair or any modification that could affect its response. The system should be 9 calibrated to minimize potential errors during data transmission and re-transmission. The user 10 may decide to perform calibrations following industry recognized procedures (ANSI 1997, NCRP 11 1978, NCRP 1985, NCRP 1991, ISO 1988, HPS 1994a, HPS 1994b), or the user can choose to 12 obtain calibration by an outside service, such as a major instrument manufacturer or a health 13 physics services organization.
14 Calibration sources should be traceable to NIST. Where NIST-traceable standards are not 15 available, standards obtained from an industry-recognized organization (e.g., the New 16 Brunswick Laboratory for various uranium, thorium, and plutonium standards) may be used.
17 Calibration of instruments for measurement of residual radioactive material on surfaces should 18 be performed such that a direct instrument response can be accurately converted to the 4 19 (total) emission rate from the source. An accurate determination of activity from a measurement 20 of count rate above a surface in most cases is an extremely complex task because of the need 21 to determine appropriate characteristics of the source, including decay scheme, geometry, 22 energy, scatter, and self-absorption. Proper calibration ensures that systematic errors in 23 measurements are controlled to help ensure that the MQO for measurement method uncertainty 24 is met.
25 The variables that affect instrument response should be understood. Therefore, the calibration 26 should account for the following factors (where necessary):
27
* Calibrations for point and large area source geometries may differ, and both may be 28      necessary if areas of activity smaller than the probe area and regions of activity larger than 29      the probe area are present.
30
* Calibration should either be performed with the radionuclide of concern or with appropriate 31      correction factors developed for the radionuclide(s) present based on calibrations with 32      nuclides emitting radiations similar to the radionuclide of concern.
33
* For portable instrumentation, calibrations should account for the substrate of concern 34      (i.e., concrete, steel) or appropriate correction factors developed for the substrates relative 35      to the actual calibration standard substrate. This is especially important for beta emitters 36      because backscatter is significant and varies with the composition of the substrate.
37      Conversion factors developed during the calibration process should be for the same 38      counting geometry to be used during the actual use of the detector.
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Field Measurement Methods and Instrumentation                                              MARSSIM 1 For building surface DCGLs, the level of residual radioactive material is typically expressed in 2 terms of the activity per unit area, normally Bq/m2 or dpm per 100 cm2. In many facilities, 3 residual radioactive material on the surface is assessed by converting the instrument response 4 (in cpm) to surface activity using the overall total efficiency. The total efficiency may be 5 considered to represent the product of two factors: the instrument (detector) efficiency and the 6 source efficiency. Use of the total efficiency is not a problem, provided that the calibration 7 source exhibits characteristics similar to the residual radioactive material on the surface 8 (i.e., radiation energy, backscatter effects, source geometry, self-absorption). In practice, this is 9 rarely the case; more likely, instrument efficiencies are determined with a clean, stainless steel 10 source, and then those efficiencies are used to determine the level of residual radioactive 11 material on a dust-covered concrete surface. By separating the efficiency into two components, 12 the surveyor has greater ability to consider the actual characteristics of the residual radioactive 13 material on the surface.
14 The instrument efficiency is defined as the ratio of the net count rate of the instrument to the 15 surface emission rate of a source for a specified geometry. The surface emission rate is defined 16 as the number of particles of a given type above a given energy emerging from the front face of 17 the source per unit time. The surface emission rate is the 2 particle fluence that embodies both 18 the absorption and scattering processes that effect the radiation emitted from the source. Thus, 19 the instrument efficiency is determined by the ratio of the net count rate and the surface 20 emission rate.
21 The instrument efficiency is determined during calibration by obtaining a static count with the 22 detector over a calibration source that has a traceable activity or surface emission rate. In many 23 cases, a source emission rate is measured by the manufacturer and certified as NIST traceable.
24 The source activity is then calculated from the surface emission rate based on assumed 25 backscatter and self-absorption properties of the source. The maximum value of instrument 26 efficiency is 1.
27 The source efficiency is defined as the ratio of the number of particles of a given type emerging 28 from the front face of a source to the number of particles of the same type created or released 29 within the source per unit time. The source efficiency takes into account the increased particle 30 emission due to backscatter effects, as well as the decreased particle emission due to self-31 absorption losses. For an ideal source (i.e., no backscatter or self-absorption), the value of the 32 source efficiency is 0.5. Many real sources will exhibit values less than 0.5, although values 33 greater than 0.5 are possible, depending on the relative importance of the absorption and 34 backscatter processes.
35 Source efficiencies may be determined experimentally. Alternatively, ISO-7503-1 (ISO 1988) 36 makes recommendations for default source efficiencies. A source efficiency of 0.5 is 37 recommended for beta emitters with maximum energies above 0.4 megaelectronvolts (MeV).
38 Alpha emitters and beta emitters with maximum beta energies between 0.15 and 0.4 MeV have 39 a recommended source efficiency of 0.25. Source efficiencies for some common surface 40 materials and overlaying material are provided in NUREG-1507 (NRC 1997a).
41 Instrument efficiency may be affected by detector-related factors, such as detector size (probe 42 surface area); window density thickness; geotropism; instrument response time; counting time NUREG-1575, Revision 2                          6-40                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                          Field Measurement Methods and Instrumentation 1 (in static mode); scan rate (in scan mode); and ambient conditions, such as temperature, 2 pressure, and humidity. Instrument efficiency also depends on solid angle effects, which include 3 source-to-detector distance and source geometry.
4 Source efficiency may be affected by source-related factors, such as the type of radiation and 5 its energy, source uniformity, surface roughness and coverings, and surface composition 6 (e.g., wood, metal, concrete).
7 The calibration of gamma detectors for the measurement of photon radiation fields should also 8 provide reasonable assurance of acceptable accuracy in field measurements. Use of these 9 instruments for demonstration of compliance with DCGLs is complicated by the fact that most 10 DCGLs produce exposure rates of at most a few &#xb5;R/h. Several of the portable survey 11 instruments currently available in the United States for exposure rate measurements of ~1 &#xb5;R/h 12 (often referred to as micro-R meters) have full scale intensities of ~3-5 &#xb5;R/h on the first range.
13 This is below the ambient background for most low radiation areas and most calibration 14 laboratories. A typical background exposure rate of 10 mR/h gives a background dose rate of 15 100 millirem/year (mrem/y) Even on the second range, the ambient background in the 16 calibration laboratory is normally a significant part of the range and must be taken into 17 consideration during calibration. The instruments commonly are not energy-compensated and 18 are very sensitive to the scattered radiation that may be produced by the walls and floor of the 19 room or additional shielding required to lower the ambient background.
20 Low-intensity sources and large distances between the source and detector can be used for 21 low-level calibrations if the appropriate precautions are taken. Field characterization of low-level 22 sources with traceable transfer standards can be difficult because of the poor signal-to-noise 23 ratio. To achieve adequate detector signal, the distance between the detector and the source 24 generally will be as small as possible while still maintaining good geometry (5-7 detector 25 diameters).
26 Corrections for scatter can be made using a shadow-shield technique in which a shield of 27 sufficient density and thickness is placed about midway between the source and the detector to 28 eliminate virtually all the primary radiation. The dimensions of the shield should be the minimum 29 required to reduce the primary radiation intensity at the detector location to less than 2 percent 30 of its unshielded value. The change in reading caused by the shields removal is attributed to 31 the primary field from the source at the detector position.
32 In some instruments that produce pulses (GM counters or scintillation counters), the detector 33 can be separated electronically from the readout electronics, and the detector output can be 34 simulated with a suitable pulser. Caution must be exercised to ensure that either the high 35 voltage is properly blocked or that the pulser is designed for this application. If this can be 36 accomplished, the instrument can first be calibrated on a higher range that is not affected by the 37 ambient background and in a geometry where scatter is not a problem and, after disconnecting 38 the detector, to provide the pulse-rate from the pulser, which will give the same instrument 39 response. The pulse rate can then be related to field strength and reduced to give readings on 40 lower ranges (with the detector disconnected) even below the ambient background. This May 2020                                        6-41                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                              MARSSIM 1 technique does not take into account any inherent detector background independent of the 2 external background.
3 Ionization chambers are commonly used to measure radiation fields at very low levels. To 4 obtain the sensitivity necessary to measure these radiation levels, the instruments are 5 frequently very large and often pressurized. These instruments have some of the same 6 calibration problems as the more portable micro-R meters described above. The same 7 precautions (shadow shield) must be taken to separate the response of the instrument to the 8 source and to scattered radiation. Generally, it is not possible to substitute an electronic pulser 9 for the radiation field in these instruments.
10 For energy-dependent gamma scintillation instruments, such as NaI(Tl) detectors, calibration for 11 the gamma energy spectrum at a specific site may be accomplished by comparing the 12 instrument response to that of a pressurized ionization chamber, or equivalent detector, at 13 different locations on the site. Multiple radionuclides with various photon energies may also be 14 used to calibrate the system for the specific energy of interest.
15 In the interval between calibrations, the instrument should receive a daily performance check 16 when in use. In some cases, a performance check following use may also provide valuable 17 information. This calibration check is merely intended to establish whether the instrument is 18 operating within certain specified, rather large, uncertainty limits. The initial performance check 19 should be conducted following the calibration by placing the source in a fixed, reproducible 20 location and recording the instrument reading. The source should be identified along with the 21 instrument, and the same check source should be used daily in the same fashion to 22 demonstrate the instruments operability when the instrument is in use. Location and other 23 specific conditions should be recorded as well (e.g., indoor, outdoor, inside trailer, inside 24 vehicle, on the roof, etc.). For analog readout (count rate) instruments, a variation of 25 +/- 20 percent is usually considered acceptable. Optionally, instruments that integrate events and 26 display the total on a digital readout typically provide an acceptable average response range of 27 2 or 3 standard deviations. This is achieved by performing a series of repetitive measurements 28 (10 or more is suggested) of background and check source response and determining the 29 average and standard deviation of those measurements. From a practical standpoint, a 30 maximum deviation of +/- 20 percent is usually adequate when compared with other uncertainties 31 associated with the use of the equipment. The amount of uncertainty allowed in the response 32 checks should be consistent with the level of uncertainty allowed in the final data. Ultimately the 33 decision maker determines what level of uncertainty is acceptable.
34 Instrument response, including both the background and check source response of the 35 instrument, should be tested and recorded at a frequency that ensures the data collected with 36 the equipment is reliable. For most portable radiation survey equipment, MARSSIM 37 recommends that a response check be performed at least twice daily when in usetypically 38 before beginning the days measurements and again following the conclusion of measurements 39 on that same day. Additional checks can be performed if warranted by the instrument and the 40 conditions under which it is used. If the instrument response does not fall within the established 41 range, the instrument is removed from use until the reason for the deviation can be resolved 42 and acceptable response again demonstrated. If the instrument fails the post-survey source 43 check, all data collected during that time period with the instrument must be carefully reviewed NUREG-1575, Revision 2                            6-42                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                            Field Measurement Methods and Instrumentation 1 and possibly adjusted or discarded, depending on the cause of the failure. Ultimately, the 2 frequency of response checks must be balanced with the stability of the equipment being used 3 under field conditions and the quantity of data being collected. For example, if the instrument 4 experiences a sudden failure during the days work due to physical harm, such as a punctured 5 probe, then the data collected up until that point is probably acceptable even though a post-use 6 performance check cannot be performed. If no obvious failure occurred but the instrument failed 7 the post-use response check, then the data collected with that instrument since the last 8 response check should be viewed with great skepticism and possibly re-collected or randomly 9 checked with a different instrument. Additional corrective action alternatives are presented in 10 Appendix D. If recalibration is necessary, acceptable response ranges must be reestablished 11 and documented.
12 Record requirements vary considerably and depend heavily on the needs of the user. Even 13 though Federal and State regulatory agencies all specify requirements, the following records 14 should be considered a minimum:
15
* laboratory quality control 16    o  records documenting the traceability of radiological standards 17    o  records documenting the traceability of electronic test equipment 18
* record-keeping of instrument calibration files 19    o  date the instrument was received in the calibration laboratory 20    o  initial condition of the instrument, including mechanical condition (e.g., loose or broken 21        parts, dents, punctures), electrical condition (e.g., switches, meter movement, batteries),
22        and radiological condition (i.e., presence or absence of contamination) 23    o  calibrators records, including training records and signature on calibration records 24    o  calibration data, including model and serial number of instrument, date of calibration, 25        recommended recalibration date, identification of source(s) used, NIST certificate or 26        standard certificate from the industry-recognized organization (certificate must include 27        the standard expiration date), as found calibration results, and final calibration results 28        as returned for use 29 In addition, records of instrument problems, failures, and maintenance can be included and are 30 useful in assessing performance and identifying possible needs for altered calibration 31 frequencies for some instruments. Calibration records should be maintained at the facility where 32 the instruments are used as permanent records and should be available either as hard copies or 33 in safe computer storage.
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Field Measurement Methods and Instrumentation                                            MARSSIM 1 6.6.5  Select Instrumentation TypeRadiation Survey Equipment 2 This section briefly describes the typical types of instrumentation that may be used to conduct 3 radiological surveys. More detailed information relevant to each type of instrument and 4 measurement method is provided in Appendix H.
5 6.6.5.1 Hand-Held Instruments 6 Hand-held instruments typically are composed of a detection probe (utilizing a single detector) 7 and an electronic instrument to provide power to the detector and to interpret data from the 8 detector to provide a measurement display. They may be used to perform scanning surveys or 9 direct measurements. Hand-held measurements also allow the user the flexibility to constantly 10 vary the source-to-detector geometry for obtaining data from difficult-to-measure areas.
11 6.6.5.2 Large Area Detectors 12 Although hand-held instruments are very useful for making direct measurements and scanning 13 small and/or difficult-to-measure areas, large area detectors provide advantages when the 14 survey unit includes large, easily accessible areas. These detectors may consist of either a 15 single large detector or an array of detectors. Unlike most hand-held detectors, which can only 16 measure the concentration in a small areatypically about 100 cm2some detectors can 17 measure the concentration in a much larger area. When used in combination with data logging 18 and positioning systems, large-area detectors can be used in place of direct measurements and 19 scanning, if the systems can meet the required MQOs.
20 6.6.5.3 In situ Gamma Spectroscopy 21 Some in situ gamma spectroscopy (ISGS) systems consist of a small hand-held unit that 22 incorporates the detector and counting electronics into a single package. Other ISGS systems 23 consist of a semiconductor detector, a cryostat, a multichannel analyzer electronics package 24 that provides amplification and analysis of the energy pulse heights, and a computer system for 25 data collection and analysis. ISGS systems typically are applied to perform direct 26 measurements, but they may be incorporated into innovative detection equipment setups to 27 perform scanning surveys.
28 6.6.5.4 Laboratory Analysis 29 Laboratory analysis consists of analyzing a portion or sample of the surface soil or building 30 surface. The laboratory will generally have recommendations or requirements concerning the 31 amount and types of samples needed for the analysis of radionuclides or radiations.
32 Communications should be established between the field team collecting the samples and the 33 laboratory analyzing the samples. More information on sampling is provided in Section 7.5.
34 Laboratory analyses can be developed for any radionuclide with any material, given sufficient 35 resources. Laboratory analyses typically require more time to complete than field analyses. The 36 laboratory may be located onsite or offsite. The quality of laboratory data typically is greater 37 than data collected in the field, because the laboratory is better able to control sources of 38 measurement method uncertainty. The planning team should consider the resources available 39 for laboratory analysis (e.g., time, money), the sample collection requirements or NUREG-1575, Revision 2                          6-44                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                          Field Measurement Methods and Instrumentation 1 recommendations, and the requirements for data quality (e.g., MDC, required measurement 2 method uncertainty) during discussions with the laboratory.
3 6.6.6    Select a Measurement Method 4 Table 6.7 illustrates the potential applications for combinations of the instrument and 5 measurement techniques discussed in Sections 6.6.1 and 6.6.5, respectively. Sampling 6 followed by laboratory analysis is not included in these tables but is considered GOOD for all 7 applications. Please note the following qualifiers:
8
* GOOD: The measurement technique is well-suited for performing this application.
9
* FAIR: The measurement technique can adequately perform this application.
10
* POOR: The measurement technique is poorly suited for performing this application.
11
* NA: The measurement technique cannot perform this application.
12
* Few: A relatively small number, usually three or less.
13
* Many: A relatively large number, usually more than three.
14 Table 6.8 illustrates that most measurement techniques can be applied to almost any sample 15 and type of radioactive material. The quantity of samples to be surveyed becomes a major 16 factor for the selection of measurement instruments and techniques described in this chapter.
17 Facilities that conduct routine surveys may benefit financially from investing in measurement 18 instruments and techniques that require less manual labor to conduct disposition surveys. Use 19 of such automated systems will also reduce the potential for ergonomic injuries and attendant 20 costs associated with routine, repetitive surveys performed using hand-held instruments.
21 Hand-held surveying remains the more economical choice for a small area, but as the area 22 increases, the cost of an automated system becomes an increasingly worthwhile investment to 23 reduce manual labor costs associated with surveying. Note that alpha radiation has no survey 24 design options that are described as GOOD in Table 6.7. The planning team should revisit 25 earlier DQO selections to see if a different approach is more acceptable.
26 Each type of measurement technique has associated advantages and disadvantages, some of 27 which are summarized in Table 6.8. All the measurement techniques described in this table 28 include source-to-detector geometry and sampling variability as common disadvantages.
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Field Measurement Methods and Instrumentation                                            MARSSIM 1 Table 6.7: Potential Applications for Instrumentation and Measurement Technique 2 Combinations Hand-Held      In Situ Gamma Radiation Type Instruments      Spectroscopy Direct Measurements Alpha              FAIR              NA Beta              GOOD                NA Photon            GOOD              GOOD Neutron            GOOD                NA Scanning Surveys Alpha              POOR                NA Beta              GOOD                NA Photon            GOOD              GOOD Neutron              FAIR              NA 3 6.7    Data Conversion 4 This section describes methods for converting survey data to appropriate units for comparison 5 to radiological criteria. As stated in Chapter 4, conditions applicable to satisfying 6 decommissioning requirements include determining that any residual radioactive material will 7 not result in individuals being exposed to unacceptable levels of radiation or radioactive 8 materials.
9 Radiation survey data are usually obtained in units that have no intrinsic meaning relative to 10 DCGLs, such as the number of counts per unit time. For comparison of survey data to DCGLs, 11 the survey data from field and laboratory measurements should be converted to DCGL units.
12 Alternatively, the DCGL can be converted into the same units used to record survey results.
13 6.7.1    Surface Activity 14 When measuring surface activity, it is important to account for the physical surface area 15 assessed by the detector to make probe area corrections and report data in the proper units 16 (i.e., Bq/m2, dpm/100 cm2). This is termed the physical probe area. A common misuse is to 17 make probe area corrections using the effective probe area, which accounts for the amount of 18 the physical probe area covered by a protective screen. Figure 6.2 illustrates the difference 19 between the physical and effective probe areas. The physical probe area is used because the 20 reduced detector response due to the screen is accounted for during instrument calibration as 21 long as the screen is in place during calibration.
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MARSSIM                                  Field Measurement Methods and Instrumentation 1
2 Table 6.8: Advantages and Disadvantages of Instrumentation and Measurement 3 Technique Combinations Measurement Instrument                              Advantages                  Disadvantages Technique Hand-Held Instruments Direct
* Generally allows
* Requires a relatively flexibility in media to    large amount of manual be measured.                labor as a surveying
* Detection equipment          technique; may make is usually portable.        surveying large areas labor-intensive.
* Detectors are available to efficiently
* Detector windows may measure alpha, beta,        be fragile.
gamma, x-ray, and
* Most do not provide neutron radiation.          nuclide identification.
* Measurement equipment is relatively low cost.
* May provide a good option for small areas.
Hand-Held Instruments Scanning
* Generally allows
* Requires a relatively flexibility in media to    large amount of manual be measured.                labor as a surveying
* Detection equipment          technique; may make is usually portable.        surveying large areas labor-intensive.
* Detectors are available to efficiently
* Detector windows may measure beta,              be fragile.
gamma, x-ray, and
* Most do not provide neutron radiation.          nuclide identification.
* Measurement
* Incorporates more equipment is                potential sources of relatively low cost.        uncertainty than most
* May provide a good          instrument and option for small            measurement technique areas.                      combinations.
* Potential ergonomic injuries and attendant costs associated with repetitive surveys.
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Field Measurement Methods and Instrumentation                                      MARSSIM Measurement Instrument                              Advantages              Disadvantages Technique Hand-Held Instruments Smear
* Only measurement
* Instrument background technique for            may not be sufficiently assessing removable      low.
radioactive material.
* Detectors with a
* Removable                counting sensitive radioactive material    region larger than the can be transferred      smear surface area may and assessed in a        require counting low background          adjustments to account counting area.          for inherent backgrounds associated with other media located under the detector sensitive region.
* The results are not always reproducible and may not be considered quantitative.
ISGS                  Direct
* Provides quantitative
* Instrumentation may be measurements with        expensive and difficult flexible calibration. to set up and maintain.
* Generally requires a
* May require liquid moderate amount of      nitrogen supply (with labor.                  ISGS semiconductor
* May be cost-effective    systems).
for measuring large
* Size of detection areas.                  equipment may
* Good peak resolution    discourage portability.
with high purity
* Poor peak resolution germanium                with NaI(Tl) detectors.
detectors.
ISGS                  Scanning
* Provides quantitative
* Instrumentation may be measurements with        expensive and difficult flexible calibration. to set up and maintain.
* Generally requires a
* May require liquid moderate amount of      nitrogen supply (with labor.                  ISGS semiconductor
* May be cost-effective    systems).
for measuring large
* Size of detection areas.                  equipment may discourage portability.
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MARSSIM                                              Field Measurement Methods and Instrumentation Measurement Instrument                                        Advantages                Disadvantages Technique Laboratory Analysis          Sampling
* Generally provides
* Most costly and time-the lowest MDCs and        consuming measurement                measurement method                    technique.
uncertainties, even
* May incur increased for difficult-to-          overhead costs while measure                    personnel are waiting radionuclides.            for analytical results.
* Allows positive
* Great care must be identification of          taken to ensure samples radionuclides without      are representative.
gammas.
* Detector windows may be fragile.
Laboratory Analysis          Smear
* Only measurement
* Instrument background technique for              may not be sufficiently assessing removable        low.
radioactive material.
* Detectors with a
* Removable                  counting sensitive radioactive material      region larger than the can be transferred        smear surface area may and assessed in a          require counting low background            adjustments to account counting area.            for inherent backgrounds associated with other media located under the detectors sensitive region.
* The results are not always reproducible and may not be considered quantitative.
1 Abbreviation: ISGS = in situ gamma spectrometer; MDC = minimum detectable concentration.
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Field Measurement Methods and Instrumentation                                                MARSSIM 1
2 Figure 6.2: The Physical Probe Area of a Detector: Gas Flow Proportional Detector with 3 Physical Probe Area of 126 cm2 4 The conversion of instrument display in counts to surface activity units of Bq/m2 is obtained 5 using Equation 6-19:
                                                    =                                            (6-19) x 6 where  is the integrated counts recorded by the instrument,  is the time period over which 7 the counts were recorded in seconds,  is the total efficiency of the instrument in counts per 8 disintegration, effectively the product of the instrument efficiency ( ) and the source efficiency 9 ( ), and  is the physical probe area in square meters (m2).To convert instrument counts to 10 conventional surface activity units of decays per minute per 100 cm2, Equation 6-19 can be 11 modified as shown in Equation 6-20:
                                              =                                                  (6-20) x ( 100) 12 where  is recorded in minutes instead of seconds, and  is recorded in square centimeters 13 instead of square meters.
14 Most instruments have background counts associated with the operation of the instrument. A 15 correction for instrument background can be included in the data conversion calculation, as 16 shown in Equation 6-21:
                                              =                                                (6-21) x NUREG-1575, Revision 2                                  6-50                                May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                  Field Measurement Methods and Instrumentation 1 where  is the background counts recorded by the instrument, and  is the time period over 2 which the background counts were recorded in seconds. Note that the instrument background is 3 not the same as the measurements in the background reference area used to perform the 4 statistical tests described in Chapter 8. Equation 6-17 can be modified to provide conventional 5 surface activity units of decays per minute per 100 cm2, as shown in Equation 6-22:
                                              =                                                (6-22) x ( 100) 6 where  and  are recorded in minutes instead of seconds, and  is recorded in square 7 centimeters instead of square meters.
8 The presence of multiple radionuclides at a site requires additional considerations for 9 demonstrating compliance with a dose- or risk-based requirement. As demonstrated in 10 Section 4.5.3, a gross activity DCGL should be determined. Example 9 illustrates the 11 calculation of a weighted efficiency for a gross activity DCGL.
Example 9: Calculation of a Weighted Efficiency for a Gross Activity Derived Concentration Guideline Level Consider a site contaminated with cesium-137 (137Cs) and strontium/yttrium-90 (90Sr/Y), with 137 Cs representing 60 percent of the total activity. The relative fractions are 0.6 for 137Cs and 0.4 for 90Sr/Y. If the derived concentration guideline level (DCGL) for 137Cs is 8,300 becquerels per square meter (Bq/m2; 5,000 decays per minute [dpm]/100 square centimeters
[cm2]) and the DCGL for 90Sr/Y is 12,000 Bq/m2 (7,200 dpm/100 cm2), the gross activity DCGL is calculated using Equation 4-10, as shown below:
1                                1 DCGLGross Activity =                              =
Cs            Sr/Y              0.6        0.4
                                                  +                                +
DCGLCs DCGLSr/Y 8,300 Bq/m2 12,000 Bq/m2
                                    = 9,500 Bq/m2 (5,700 dpm/100 cm )
2 Note that because the half-lives of 137Cs and 90Sr are approximately the same, the relative fractions of the two radionuclides will not change because both decay at the same rate. For other radionuclides, the relative fractions will change over time from the decay of one radionuclide relative to the other.
It is important to use an appropriately weighted total efficiency to convert from instrument counts to surface activity units using Equations 6-19 through 6-22. In this example, the individual efficiencies for 137Cs and 90Sr/Y should first be independently evaluated. The maximum energies for beta particles for 137Cs and 90Sr/Y are 0.51 MeV and 2.28 MeV, respectively. The corresponding instrument efficiencies for 137Cs and 90Sr/Y are determined to be 0.38 and 0.45, respectively. The surface efficiency of both nuclides is estimated to be 0.5.
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Field Measurement Methods and Instrumentation                                                      MARSSIM The total efficiencies are calculated by multiplying the surface efficiency by the instrument efficiency, as shown below (see Section 4.12.5.1 for further explanation):
                                        ,Cs = ,Cs x ,Cs = (0.5)(0.38) = 0.19
                                  ,Sr/Y = ,Sr/Y x ,Sr/Y = (0.5)(0.45) = 0.22 The overall efficiency is then determined by weighting each individual radionuclide efficiency by the relative fraction of each radionuclide (Equation 4-21):
                        = Cs ,Cs + Sr/Y ,Sr/Y = (0.6)(0.19)+(0.4)(0.22) = 0.20 The overall efficiency is 0.20 (20 percent).
1 6.7.2    Soil Radionuclide Concentration and Exposure Rates 2 Analytical procedures, such as alpha and gamma spectrometry, are typically used to determine 3 the radionuclide concentration in soil in units of Bq/kg. Net counts are converted to soil DCGL 4 units by dividing by the time, detector or counter efficiency, mass or volume of the sample, and 5 by the fractional recovery or yield of the chemistry procedure (if applicable). Refer to Chapter 7 6 for examples of analytical procedures.
7 Instruments, such as a pressurized ionization chamber (PIC) or micro-R meter are used to 8 measure exposure rate. Typically, exposure rates are read directly in millisieverts per hour 9 (mSv/h) (Standard International System of Units) or microroentgens (&#xb5;R) per hour. A gamma 10 scintillation detector (e.g., NaI(Tl)) provides data in cpm, and conversion to mSv/h is 11 accomplished by using site-specific calibration factors developed for the specific instrument 12 (Section 6.6.4).
13 In situ gamma spectrometry data may require special analysis routines before the spectral data 14 can be converted to soil concentration units or exposure rates. Commercially available 15 measurement systems may use proprietary methods to convert instrument counts to the 16 reported units. Although it is not always necessary to understand the conversion calculations, 17 any deviations from assumptions included in the conversion must be accounted for in the 18 estimate of total measurement uncertainty (Section 6.4). Consult the manufacturer to ensure 19 the total measurement uncertainty is determined correctly.
20 6.8    Radon Measurements 21 There are three radon isotopes in nature: 222Rn (radon) in the 238U decay chain, 220Rn (thoron) in 22 the 232Th decay chain, and 219Rn (actinon) in the 235U decay chain. 219Rn is the least abundant of 23 these three isotopes, and because of its short half-life of 4 seconds, it has the least probability 24 of emanating into the atmosphere before decaying. 220Rn, with a 55-second half-life, is 25 somewhat more mobile. 222Rn, with a 3.8-day half-life, is capable of migrating through soil or 26 building material and reaching the atmosphere. Therefore, in most situations, 222Rn should be 27 the predominant airborne radon isotope. In other instances, thorium-containing building material NUREG-1575, Revision 2                                          6-52                              May 2020 DRAFT FOR PUBLIC COMMENT                                                              DO NOT CITE OR QUOTE
 
MARSSIM                                          Field Measurement Methods and Instrumentation 1 or interior building structures where processed thorium ore is present can result in thorons 2 becoming the predominant airborne radon isotope.
3 In some cases, radon may be detected within structures that do not contain residual radioactive 4 material, and conversely, some structures that contain residual radioactive material may not 5 yield detectable radon or thoron. Consult with your regulator for the applicability of radon or 6 thoron measurements as part of a site survey.
7 Because of the widespread nature of indoor air radon, many states have developed 8 requirements for certification/qualification of people who perform radon services. Therefore, as 9 part of the qualifications for the service provider, determine whether the measurement provider 10 or the laboratory analyzing the measurements is required to be certified by the state or locality 11 where the work is being performed. State radon contacts can be found at 12 https://www.epa.gov/radon/find-information-about-local-radon-zones-and-state-contact-13 information.
14 Many techniques have been developed over the years for measuring radon (Jenkins 1986) and 15 radon progeny in air. In addition, considerable attention is given by the U.S. Environmental 16 Protection Agency to the measurement of radon and radon progeny in homes (EPA 1992e).
17 Radon and radon progeny emit alpha and beta particles and gamma rays. Therefore, numerous 18 techniques can and have been developed for measuring these radionuclides based on detecting 19 alpha particles, beta particles, or gamma rays, independently or in some combination. This 20 section contains an overview of information dealing with the measurement of radon and radon 21 progeny. The information is focused on the measurement of 222Rn; however, the information 22 may be adapted for the measurement of 219Rn and 220Rn. There are commercial options for 23 measurements of 220Rn, but options for 219Rn are limited. More consideration should be given to 24 the two latter radon isotopes because of their short half-lives, which may prevent the shipment 25 of the sample for off-site laboratory analyses, depending on the sampling and measurement 26 methods.
27 Radon concentrations within a fixed structure can vary significantly from one section of the 28 building to another and can fluctuate over time. If a home has a basement, for instance, it is 29 usually expected that a higher radon concentration will be found there. Radon primarily enters 30 buildings that are at negative pressure with respect to the soil. A small increase in the relative 31 pressure between the soil and the inside of a structure can cause a significant increase in the 32 amount of radon entering the building from the soil. Many factors play a role in these variations, 33 but from a practical standpoint it is only necessary to recognize that fluctuations are expected 34 and that they should be accounted for. Long-term measurement periods (91 days or greater) 35 are required to determine a mean concentration inside a structure; however, a mean may not be 36 necessary to determine if a risk-reduction strategy is required. It may also not be necessary if 37 radon is being used as an indicator of nearby residual radioactive material.
38 Two analytical end points are of interest when performing radon measurements. The first and 39 most commonly used is radon concentration, which is stated in terms of activity per unit volume, 40 in Bq/m3 or picocuries per liter (pCi/L). Although this terminology is consistent with most Federal 41 requirements, it only implies the potential dose equivalent associated with radon. The second May 2020                                        6-53                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                                          MARSSIM 1 analytical end point is the potential alpha energy concentration (PAEC) (or equilibrium 2 equivalent concentration) of the radon progeny. Radon progeny usually attach very quickly to 3 charged aerosols in the air following creation. The fraction that remains unattached is usually 4 quite small (i.e., 5-10 percent). Because most aerosol particles carry an electrical charge and 5 are relatively massive ( 0.1 &#xb5;m), they are capable of attaching to the surfaces of the lung.
6 Essentially all dose or risk from radon is associated with alpha decays from radon progeny 7 deposited in the respiratory system. If an investigator is interested in accurately determining the 8 potential dose or risk associated with radon in the air of a room, the radon progeny 9 concentration must be known. It should be noted, however, that various processes remove 10 radon progeny from a room. If the radon is removed or prevented from entering, there will be no 11 risk from decay products.
12 Radon progeny concentrations are usually reported in units of working levels, where one 13 working level is equal to the potential alpha energy associated with the radon progeny in secular 14 equilibrium with 100 pCi/L of radon. One working level is equivalent to 1.3 x 105 MeV/L of 15 potential alpha energy. Given a known breathing rate and lung attachment probability, the 16 expected mean lung dose from exposure to a known working level of radon progeny can be 17 calculated.
18 Radon progeny are not usually found in secular equilibrium with radon indoors because of the 19 plating out of the charged aerosols onto walls, furniture, etc. The ratio of 222Rn progeny activity 20 to 222Rn activity usually ranges from 0.2 to as high as 0.8 indoors (NCRP 1988). If only the 222Rn 21 concentration is measured and it is not practical to measure the progeny concentrations, then 22 general practice is to assume a progeny to 222Rn equilibrium ratio for indoor areas. The 23 appropriate regulatory agency should be consulted to determine the appropriate equilibrium 24 factor. This allows one to estimate the expected dose or risk associated with a given radon 25 concentration.
26 In general, the following generic guidelines should be followed when performing radon 27 measurements during site investigations:
28
* The radon measurement method used should be well understood, documented, and carried 29    out in compliance with certification requirements as applicable. Measurements in buildings 30    should conform to current radon standards of practice as required by the regulator. 3 31
* Long-term measurements should be considered where short-term (screening) tests are 32    close to guidance levels.
33
* In nonresidential buildings, such as schools and commercial buildings, the impact of the 34    heating, ventilation, and air conditioning system on radon entry should be considered, 35    because radon levels may change significantly between occupied and non-occupied 36    periods.
37
* The impact of variable environmental conditions (e.g., humidity, temperature, dust loading, 38    and atmospheric pressure) on the measurement process should be accounted for when 3 Contact the American Association of Radon Scientists and Technologists for the current radon standards of practice.
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MARSSIM                                          Field Measurement Methods and Instrumentation 1      necessary. Consideration should be given to effects on both the air collection process and 2      the counting system.
3
* The background response of the detection system should be accounted for.
4
* If measuring the potential alpha energy concentration directly is impractical to measure the 5      potential alpha energy concentration directly, then the progeny activities can be estimated 6      by assuming a specific equilibrium with radon. The concentrations of the radon progeny are 7      then estimated by applying an equilibrium factor to the measured radon concentration. The 8      appropriate regulatory agency should be consulted to determine the appropriate equilibrium 9      factor.
10 For a general overview, a list of common radiation detectors with their usual applications during 11 radon surveys is provided in Table 6.9. Descriptions and costs for specific equipment used for 12 the measurement of radon are contained in Appendix H.
13 The following provides a general overview of radon sampling and measurement concepts. The 14 intent of this section is to provide an overview of common methods and terminology.
15 6.8.1    Direct Radon Measurements 16 Direct radon measurements are performed by gathering radon into a chamber and measuring 17 the ionizations produced. A variety of methods have been developed, each making use of the 18 same fundamental mechanics but employing different measurement processes. The first step is 19 to get the radon into a chamber without collecting any radon progeny from the ambient air. A 20 filter is normally used to capture charged aerosols while allowing the radon gas to pass through.
21 Most passive monitors rely on diffusion of the ambient radon in the air into the chamber to 22 establish an equilibrium between the concentrations of radon in the air and in the chamber.
23 Active monitors use some type of air pump system for the air exchange method.
24 Once inside the chamber, the radon decays by alpha emission to form 218Po, which usually 25 takes on a positive charge within thousandths of a second following formation. Some monitor 26 types collect these ionic molecules and subsequently measure the alpha particles emitted by 27 the radon progeny. Other monitor types, such as the electret ion chamber, measure the 28 ionization produced by the decay of radon and progeny in the air within the chamber by directly 29 collecting the ions produced inside the chamber. The electrets are influenced by the ambient 30 gamma radiation level; therefore, correction factors based on the gamma radiation level must be 31 established to adjust the radon results. Simple systems measure the cumulative radon during 32 the exposure period based on the total alpha decays that occur. More complicated systems 33 measure the individual pulse height distributions of the alpha and/or beta radiation emissions 34 and derive the radon plus progeny isotopic concentration in the air volume.
35 Care must be taken to accurately calibrate a system and to understand the effects of humidity, 36 temperature, dust loading, air currents, and atmospheric pressure on the system. These 37 conditions create a small adverse effect on some systems and a large influence on others.
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Field Measurement Methods and Instrumentation                                          MARSSIM 1 Table 6.9: Radiation Detectors with Applications to Radon Surveys Category    Measures    System      Description    Application  Time          Remarks Integrating/  222Rn      Activated    Activated      Measure radon 2-7 days  LLD is 0.007-Averaging                charcoal    charcoal is    concentration          0.04 Bq/L (0.2-Methods                  adsorption  opened to the in indoor air.            1.0 pCi/L).
ambient air, then gamma                              Must wait 3 hours after counted on a                            deployment ends to gamma                                  begin analysis.
scintillator or in a liquid                            Not a true integrating scintillation                          device.
counter.
Must be returned to the laboratory promptly.
222Rn      Electret ion This is a      Measure radon 2-7 days Must correct reading chamber      charged        concentration for short for gamma 220Rn                  plastic vessel in air.        term      background that can be                            concentration. Electret Radon Flux              opened for air                91-365 is sensitive to to pass                      days for extremes of through.                      long      temperature and Voltage drop                  term      humidity.
is then measured.                              Reader is sensitive to temperature changes.
LLD is 0.007-0.02 Bq/L (0.2-0.5 pCi/L).
Alpha track  A small piece Measure radon 91-365      LLD is 0.04 Bq/L-d detection    of special      concentration days      (1 pCi/L-d).
plastic or film in air.
inside a small                          Typical deployment is container.                              a minimum of 90 days.
Damage tracks from alpha particles are chemically etched and tracks counted.
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MARSSIM                                        Field Measurement Methods and Instrumentation Category    Measures    System      Description      Application      Time          Remarks 222Rn    Filter/      Air pump and      Measure          1 day -  LLD is 0.0002 Working Progeny  detector unit filtration unit  progeny          a few    Level for a week-long with TLD          concentration    weeks    measurement.
220Rn                  chips or          in air.
Progeny                nuclear track detectors.
Continuous  222Rn    Ionization    Measure          Measure radon Minutes      LLD is 150 Bq/m3 Monitors              chambers,    radon            concentration to a few    (4 pCi/L) in 220Rn    scintillation concentrations    in air; sniffer days    10 minutes.
detectors,    and log results  to locate radon solid state  on real-time      entry points in detectors    basis. May        building.
provide spectral data, depending on device.
Radon        222Rn    Continuous    Air pump and Measurement            1 day-  LLD is 20 nJ/m3 (0.001 Progeny      Decay    radon        solid-state      of PAEC. Can      1 week Working Level).
Measurements Products  progeny      detector.        calculate        grab monitors                        equilibrium.      samples 220Rn                                                      for some Decay                                                      models Products Short-Term  222Rn    Large-area    A canister        Short-term        24 hours The LLD is 0.007 Radon Flux            activated    containing        radon flux                Bq/m2/s (0.2 pCi/m2 s).
Measurements          charcoal      activated        measurements.
collector    charcoal is twisted into the surface and left for 24 hours.
Electret Ion  Ion Chamber      Short term        8 - 24  Gamma correction for Chamber      has filtered      radon flux        hours    background required.
outlets to        measurements.
prevent                                      LLD is 0.08 pCi/m2 s saturation.
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Field Measurement Methods and Instrumentation                                                          MARSSIM 1 Abbreviations: Bq = becquerels; L = liters; pCi = picocuries; d = day; LLD = lower limit of detection; 2 TLD = thermoluminescent dosimeter; m = meter; PAEC = potential alpha energy concentration; nJ = nanoJoules; 3 s = second.
4 6.8.1.1 Integrating/Averaging Methods 5 With integrating methods, measurements are made over a period of days, weeks, or months, 6 and the device is subsequently read by an appropriate device for the detector media used. The 7 most common detectors used are activated charcoal adsorbers (good for up to 1 week), EICs 8 (good for days to weeks), and alpha track plastics (good for weeks to months). Short-term 9 fluctuations are averaged out, thus making the measurement representative of average 10 concentration. Results in the form of an average value provide no way to determine the 11 fluctuations of the radon concentration over the measurement interval. Successive short-term 12 measurements can be used in place of single long-term measurements to gain better insight 13 into the seasonal dependence of the radon concentration. Continuous measurements can be 14 used to get better insight into the time dependence of the radon concentration, which can be of 15 particular importance in large buildings. Because charcoal allows continual adsorption and 16 desorption of radon, the method does not give a true integrated measurement over the 17 exposure time. Use of a diffusion barrier over the charcoal reduces the effects of drafts and high 18 humidity.
19 6.8.1.2 Continuous Monitors 20 Devices that measure direct radon concentrations over successive time increments are 21 generally called continuous radon monitors. These systems are more complex than integrating 22 devices, in that they measure the radon concentration and log the results to a data recording 23 device on a real-time basis. The monitor must take a reading at least once per hour to be 24 considered a continuous monitor. Continuous radon measurement devices normally allow the 25 noble gas radon to pass through a filter into a detection chamber where the radon decays and 26 the radon or the resulting progeny are measured. Common detectors used for real time 27 measurements are ion chambers, solid state surface barrier detectors, and ZnS(Ag) scintillation 28 detectors.
29 A principle of operation for monitors equipped with solid state detectors is an electrostatic 30 collection of alpha emitters with spectral analysis. The electric field within the sample cell drives 31 the positively charged ion to the detector where it attaches. The detector converts alpha 32 radiation directly to an electrical signal proportional in strength to the energy of alpha particle.
33 This makes it possible to tell which radionuclide produced the radiation; therefore, one can 34 distinguish 222Rn from 220Rn. If operated in air with a relatively high radon concentration, these 35 monitors need to be purged with filtered, fresh dry air with a normal radon concentration before 36 taking the next series of measurements. Continuous methods offer the advantage of providing 37 successive, short-term results over long periods of time. This allows the investigator not only to 38 determine the average radon concentration, but also to analyze the fluctuations in the values 39 over time. More complicated systems are available that measure the relative humidity and 40 temperature at the measurement location and log the values along with the radon NUREG-1575, Revision 2                                    6-58                                        May 2020 DRAFT FOR PUBLIC COMMENT                                                              DO NOT CITE OR QUOTE
 
MARSSIM                                                  Field Measurement Methods and Instrumentation 1 concentrations to the data logging device. This allows the investigator to make adjustments, if 2 necessary, to the resulting data before reporting the results. 4 3 6.8.2    Radon Progeny Measurements 4 Radon progeny measurements are usually performed by collecting aerosols onto filter paper 5 and subsequently counting the filter for attached progeny. Some systems pump air through a 6 filter and then automatically count the filter for alpha or beta emissions. An equivalent but more 7 labor-intensive method is to collect a sample using an air sampling pump and then count the 8 filter in standalone alpha or beta counting systems. The measurement system may make use of 9 any number of different techniques, ranging from full alpha and beta spectrometric analysis of 10 the filters to simply counting the filter for total alpha and or beta emissions.
11 When performing total (gross) counting analyses, the assumption is usually made that the only 12 radioisotopes in the air are due to 222Rn and its progeny. This uncertainty, which is usually very 13 small, can be essentially eliminated when performing manual sampling and analysis by 14 performing a followup measurement of the filter after the radon progeny have decayed to a 15 negligible level. This value can then be used as a background value for the air. Of course, such 16 a simple approach is applicable only when 222Rn is the isotope of concern. For 219Rn or 220Rn, 17 other methods would have to be used.
18 Time is a significant element in radon progeny measurements. Given any initial equilibrium 19 condition for the progeny isotopes, an investigator must be able to correlate the sampling and 20 measurement technique back to the true concentration values. When collecting radon progeny, 21 the buildup of total activity on the filter increases asymptotically until the activity on the filter 22 becomes constant (after approximately 3 hours of sampling). At this point, the decay rate of the 23 progeny atoms on the filter is equal to the collection rate of progeny atoms. This is an important 24 parameter to consider when designing a radon and progeny sampling procedure. Depending on 25 sensitivity requirements, collection times can be as short as 5 minutes (Maiello 2010). Although 26 it is possible to sample for other time periods, the equations developed for the three major 222Rn 27 progeny concentrations are valid for sampling times of 5 minutes only. Samples should be 28 shipped and analyzed as expeditiously as possible after sampling is concluded.
29 Note that the number of charged aerosol particles in the air can affect the results for radon 30 progeny measurements. If the number of particles is few, as is possible when humidity is low 31 and a room is very clean, then most of the progeny will not be attached and can plate out on 32 room surfaces before reaching the sample filter.
4 Depending on the device, these measurements would indicate unexpected disruptions when the device is used for radon testing. The theory is that opening windows or moving the device would cause a noticeable disruption in the measurement.
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Field Measurement Methods and Instrumentation                                            MARSSIM 1 6.8.3  Radon Flux Measurements 2 Sometimes it is desirable to characterize the source of radon in terms of the rate at which radon 3 is emanating from a surfacethat is, soil, uranium mill tailings, or concrete. One method used 4 for measuring radon flux is briefly described here.
5 The measurement of radon flux can be achieved by adsorption onto charcoal using a variety of 6 methods, such as a charcoal canister or a large-area collector (e.g., 25 cm polyvinyl chloride 7 [PVC] end cap). The collector is deployed by sealing the collection device onto the surface of 8 the material to be measured. After 24 hours of exposure, the activated charcoal is removed and 9 transferred to plastic containers. The amount of radon adsorbed on the activated charcoal is 10 determined by gamma spectroscopy. Because the area of the surface is well defined and the 11 deployment period is known, the radon flux (in units of Bq/m2-s or pCi/m2-s) can be calculated.
12 This method is reliable for measuring radon flux in normal environmental situations. However, 13 care should be taken if an extremely large source of radon is measured with this method. The 14 collection time should be chosen carefully to avoid saturating the canister with radon. If 15 saturation is approached, the charcoal loses its ability to absorb radon, and the collection rate 16 decreases. Even transporting and handling of a canister that is saturated with radon can be a 17 problem because of the dose rate from the gamma rays being emitted. One would rarely 18 encounter a source of radon that is so large that this would become a problem; however, the 19 potential for it should be recognized. Charcoal also can become saturated with water, which will 20 affect the absorption of radon. This can occur in areas with high humidity.
21 An alternative method for making passive radon flux measurements has been developed 22 recently using EICs. EIC technology has been widely used for indoor radon measurements. The 23 passive EIC procedure is similar to the procedures used with large-area activated charcoal 24 canisters. To provide the data for the background corrections, an additional EIC monitor is 25 located side-by-side on a radon-impermeable membrane. These data are used to calculate the 26 net radon flux. The Florida State Bureau of Radiation Protection has compared the results from 27 measurements of several phosphogypsum flux beds using the charcoal canisters and EICs and 28 has shown that the two methods give comparable results. The passive method seems to have 29 overcome some of the limitations encountered in the use of charcoal. The measurement periods 30 can be extended from hours to several days to obtain a better average, if needed. EIC flux 31 measurements are not affected by such environmental conditions as temperature, humidity, and 32 air flow. The measured detection capabilities are comparable to the charcoal method, but 33 unlike charcoalEICs do not become saturated by humidity. Intermediate readings can be 34 made if needed. In view of the low cost of the EIC reading and analysis equipment, the cost per 35 measurement can be as much as 50 percent lower than the charcoal method, with additional 36 savings in time. There are handling and storage requirements associated with these methods 37 and detectors. For more information, refer to the manufacturer and Appendix H.
38 6.9    Special Equipment 39 Various specialized systems have been developed that can be used during the performance of 40 RSSIs. These range from specially designed quick radiation scanning systems to commercial 41 global positioning systems (GPSs). The equipment may be designed to detect radiation directly, NUREG-1575, Revision 2                        6-60                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                            Field Measurement Methods and Instrumentation 1 detect and locate materials associated with the residual radioactive material (e.g., metal 2 containers), or locate the position where a particular measurement is performed. Because these 3 specialized systems are continuously being modified and developed for site-specific 4 applications, it is not possible to provide detailed descriptions of every system. The following 5 sections provide examples of specialized equipment that have been applied to radiation surveys 6 and site investigations.
7 6.9.1  Local Microwave and Sonar Positioning Systems 8 Local microwave or sonar beacons and receivers may provide useful location data in small 9 areas and tree-covered locales. With a number of fixed beacons in place, a roving unit can be 10 oriented and provide location data with similar accuracy and precision as the differential GPS 11 (DGPS). If the beacons are located at known points, the resulting positions can be determined 12 using simple calculations based on the known reference locations of the beacons.
13 The logistics of deploying the necessary number of beacons properly and the short range of the 14 signals are the major limitations of the system. In addition, multipathing of signals within wooded 15 areas or interior areas can cause jumps in the positioning data. These systems have 16 applicability both indoors and outdoors but require setting up a site-specific system that may 17 require adjustment for different locations (e.g., each room in a building).
18 6.9.2  Laser Positioning Systems 19 Laser positioning systems are becoming more popular for monitoring positions in three 20 dimensions. The newest systems use reflectorless electronic distance measurement to measure 21 the distance to an object without actually accessing the object. Laser systems use the principles 22 of phase shift and pulse (or time of flight) or a hybrid combination to measure distance. This 23 allows mapping of distant or inaccessible objects in hazardous areas. Using a reflector, or 24 retroprism, to identify the location of a surveyor or detector allows the system to track the 25 location of individual measurements. Laser systems are accurate to within a few millimeters at 26 distances up to 1,000 m. Laser systems require a clear line of sight between the object and the 27 laser. Systems with multiple lasers at different locations can be used to minimize issues with 28 line-of-sight interference.
29 6.9.3  Mobile Systems with Integrated Positioning Systems 30 In recent years, the advent of new technologies has introduced mobile sensor systems for 31 acquiring data that include fully integrated positioning systems. Portable and vehicle-based 32 versions of these systems record survey data while moving over surfaces to be surveyed and 33 simultaneously recording the location data from a roving DGPS receiver, local microwave/sonar 34 receiver, or special retroprism for a laser system. All measurement data are automatically stored 35 and processed with the measurement location for later posting (see Section 8.2.2.2 for a 36 discussion of posting plots) or for mapping the results using a geographic information system.
37 These systems are designed with a variety of detectors for different applications. For example, 38 alpha or beta detectors have been mounted on a robot at a fixed distance over a smooth 39 surface. The robot moves at a predetermined speed over the surface to provide scanning 40 results and records individual direct measurements at predetermined intervals. This type of May 2020                                          6-61                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Field Measurement Methods and Instrumentation                                            MARSSIM 1 system not only provides the necessary measurement data, but also reduces the uncertainty 2 associated with human factors. Other systems are equipped with several types of radiation 3 detectors, magnetometers, electromagnetic sensors, or various combinations of multiple 4 sensors. The limitations of each system should be evaluated on a site-specific basis to 5 determine if the positioning system, the detector, the transport system, or some combination 6 based on site-specific characteristics will represent the limits of the system.
7 6.9.4    Radar, Magnetometer, and Electromagnetic Sensors 8 The number of sensors and sensor systems applicable to the detection and location of buried 9 waste have increased in use and reliability in recent years. These systems are typically 10 applicable to scoping and characterization surveys where the identification of residual 11 radioactive materials in the subsurface is a primary concern. However, the results of these 12 surveys may be used during FSS planning to demonstrate that subsurface materials are not a 13 concern for a particular site or survey unit. Some of the major technologies are briefly described 14 in the following sections.
15 6.9.4.1 Ground Penetrating Radar 16 For most sites, ground-penetrating radar (GPR) is the only instrument capable of collecting 17 images of buried objects in situ, as compared to magnetometers (Section 6.9.3.2) and 18 electromagnetic sensors (Section 6.9.3.3), which detect the strength of signals as measured at 19 the ground surface. Additionally, GPR is unique in its ability to detect both metallic and 20 nonmetallic (e.g., plastic, glass) containers. GPR techniques are being studied to monitor the 21 performance and stability of soil covers at uranium mill tailings sites and other land disposal 22 sites with earthen covers (Necsoiu and Walter 2015).
23 Subsurface radar detection systems have been the focus of study for locating and identifying 24 buried or submerged objects that otherwise could not be detected. There are two major 25 categories of radar signals: (1) time domain and (2) frequency domain. Time-domain radar uses 26 short impulses of radar-frequency energy directed into the ground being investigated.
27 Reflections of this energy, based on changes in dielectric properties, are then received by the 28 radar. Frequency-domain radar, on the other hand, uses a continuous transmission, where the 29 frequency of the transmission can be varied either stepwise or continuously. The changes in the 30 frequency characteristics due to effects from the ground are recorded. Signal processing, in 31 both cases, converts this signal to represent the location of radar reflectors against the travel 32 time of the return signal. Greater travel time corresponds to a greater distance beneath the 33 surface.
34 Examples of existing GPR technologies currently being applied to subsurface investigations 35 include the following:
36
* narrow-band radar 37
* ultra-wideband radar 38
* synthetic aperture radar NUREG-1575, Revision 2                          6-62                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                            Field Measurement Methods and Instrumentation 1
* frequency modulated continuous radar 2
* polarized radar waves 3 The major limitation to GPR is the difficulty in interpreting the data, which is often provided in the 4 form of hazy, waterfall-patterned data images requiring an experienced professional to 5 interpret. Also, GPR can vary depending on the soil typehighly conductive clay soils often 6 absorb a large amount of the radar energy and may even reflect the energy. GPR can be 7 deployed using ground-based or airborne systems.
8 6.9.4.2 Magnetometers 9 Although soil affected by residual radioactive material and most radioactive waste possess no 10 ferromagnetic properties, the containers commonly used to hold radioactive waste (e.g., 55-11 gallon drums) are made from steel. These containers possess significant magnetic 12 susceptibility, making the containers detectable using magnetometry.
13 Magnetometers sense the pervasive magnetic field of the Earth. This field, when encountering 14 an object with magnetic susceptibility, induces a secondary magnetic field in that object. This 15 secondary field creates an increase or decrease in Earths ambient magnetic field.
16 Magnetometers measure these changes in the expected strength of the ambient magnetic field.
17 Some magnetometers, called vector magnetometers, can sense both the direction and the 18 magnitude of these changes. However, for subsurface investigations only the magnitude of the 19 changes is used.
20 The ambient magnetic field on Earth averages 55,000 gamma in strength. The variations 21 caused by the secondary magnetic fields typically range from 10-1,000 gamma and average 22 around 100 gamma. Most magnetometers currently in use have a detection capability in the 23 0.1-0.01 gamma range and can detect these secondary fields.
24 An alternate magnetometer survey can be performed using two magnetometers in a 25 gradiometric configuration. This means that the first magnetometer is placed at the ground 26 surface, and the second is mounted approximately 0.5 m above the first. Data are recorded 27 from both sensors and compared. When the readings from both detectors are nearly the same, 28 it implies that there is no significant disturbance in the Earths ambient magnetic field or that 29 such disturbances are broad and far away from the gradiometer. When a secondary magnetic 30 field is induced in an object, it affects one sensor more strongly than the other, producing a 31 difference in the readings from the two magnetometers. This approach is similar to the use of a 32 guard detector in anti-coincidence mode in a low-background gas-flow proportional counter in a 33 laboratory (see Appendix H for a description of gas-flow proportional counters). The 34 gradiometric configuration filters out the Earths ambient magnetic field, large-scale variations, 35 and objects located far from the sensor to measure the effects of nearby objects, all without 36 additional data processing. Fifty-five-gallon drums buried 5-7 meters below the surface may be 37 detectable using a magnetometer. At many sites, multiple drums have been buried in trenches 38 or pits, and detection is straightforward. A single operator carrying a magnetometer with the 39 necessary electronics in a backpack can cover large areas in a relatively small amount of time.
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Field Measurement Methods and Instrumentation                                              MARSSIM 1 The limitations on the system are related to the size of the objects and their depth below the 2 surface. Objects that are too small or buried too deep will not provide a secondary magnetic 3 field that can be detected at the ground surface.
4 6.9.4.3 Electromagnetic Sensors 5 Electromagnetic sensors emit an electromagnetic wave, in either a pulsed or continuous wave 6 mode, and then receive the result of that transmission. The result of the transmission is two 7 signals: quadrature and in-phase. As the wave passes through some material other than air, it is 8 slowed down by a resistive medium or sped up by a conductor through dielectric effects. This 9 produces the quadrature signal. If the electromagnetic wave encounters a highly conductive 10 object, it induces a magnetic field in the object. This induced electromagnetic field returns to the 11 sensor as a reflection of the original electromagnetic wave and forms the in-phase signal.
12 The in-phase signal is indicative of the presence, size, and conductivity of nearby objects 13 (e.g., 55-gallon drums), and the quadrature signal is a measure of the dielectric properties of the 14 nearby objects, such as soil. This means that electromagnetic sensors can detect all metallic 15 objects (including steel, brass, and aluminum), such as the metal in waste containers, and 16 sample the soil for changes in properties, such as those caused by leaks of contents.
17 Depths of interest are largely determined by the spacing between the coil used to transmit the 18 primary electromagnetic wave and the receiver used to receive that transmission. The rule of 19 thumb is that the depth of interest is on the order of the distance between the transmitter and 20 the receiver. A system designed with the transmitter and receiver placed tens of meters apart 21 can detect signals from tens of meters below the surface. A system with the transmitter and 22 receiver collocated can detect signals only from depths on the order of the size of the coil, which 23 is typically about 1 m. The limitations of electromagnetic sensors include a lack of clearly 24 defined signals and decreasing resolution of the signal as the distance below the surface 25 increases.
26 6.9.5    Aerial Radiological Surveys 27 Low-altitude aerial radiological surveys are designed to encompass large areas and may be 28 useful in 29
* providing data to assist in the identification of residual radioactive materials and their 30      corresponding concentrations and spatial distributions 31
* characterizing the nature, extent and impact of the residual radioactive materials 32 The detection capability and data processing procedures provide total area coverage and a 33 detailed definition of the extent of gamma-producing isotopes for a specific area. The gamma 34 radiation spectral data are processed to provide a qualitative and quantitative analysis of the 35 radionuclides in the survey area. Flyover surveys establish a grid pattern (e.g., east-west) of 36 parallel lines approximately 60-150 m (200-500 feet) above the ground surface.
37 The survey consists of airborne measurements of natural and manmade gamma radiation from 38 the terrain surface. These measurements allow the determination of terrestrial spatial NUREG-1575, Revision 2                            6-64                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                        Field Measurement Methods and Instrumentation 1 distribution of isotopic concentrations and equivalent gamma exposure rates (e.g., 60Co, 234mPa, 2 and 137Cs). The results are reported as isopleths or data points for the isotopes and are usually 3 superimposed on scale maps of the area.
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MARSSIM                                          Sampling and Preparation for Laboratory Measurements 1            7 SAMPLING AND PREPARATION FOR LABORATORY 2                                                MEASUREMENTS 3 7.1    Introduction 4 The Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) provides three 5 methods for collecting radiation data while performing a survey: direct measurement, scanning, 6 and sampling. 1 A direct measurement is a radioactivity measurement obtained by placing the 7 detector near the surface or media being surveyed for a prescribed amount of time. An 8 indication of the resulting concentration of radioactive material is read out directly. Scanning is 9 an evaluation technique performed by moving a portable radiation detection instrument at a 10 constant speed and distance relative to the surface to detect radiation. These measurement 11 techniques are discussed in Chapter 6. The third method of obtaining radiation data involves 12 collecting a portion of a larger quantity of media for sample analysis using instrumentation in the 13 field or in a laboratory (NRC 2004).
14 Chapter 7 discusses issues involved in collecting and preparing samples for analysis. This 15 information will assist in communications with the laboratory during survey planning.
16 Samples should be collected and analyzed by qualified individuals using the appropriate 17 equipment and procedures. This manual assumes that the samples taken during the survey will 18 be submitted to a qualified laboratory for analysis. The laboratory should have written 19 procedures that document its analytical capabilities for the radionuclides of interest and a quality 20 assurance/quality control (QA/QC) program that documents the compliance of the analytical 21 process with established criteria. The method used to assay the radionuclides of concern should 22 be recognized as a factor affecting analysis time.
23 Commonly used radiation detection and measuring equipment for radiological survey field 24 applications is described in Chapter 6 and Appendix H. Many of these equipment types may 25 also be used for laboratory analyses, usually under more controlled conditions that provide for 26 lower detection limits and measurement method uncertainties and greater abilities to identify 27 and quantify between radionuclides. Laboratory methods often involve combinations of both 28 chemical and physical preparation and instrument techniques to quantify the low levels 29 expected in the samples. This chapter provides guidance to assist the MARSSIM user in 30 selecting appropriate procedures for collecting and handling samples for laboratory analysis.
31 More detailed information is available in documents listed in the reference section of this 32 manual.
33 The development of data quality objectives (DQOs) and measurement quality objectives 34 (MQOs) to define the data needs for a survey is described in Section 7.2. This includes making 35 decisions regarding the need to collect samples, the appropriate sampling methods, and QC 36 measurements implemented as part of the survey process. Section 7.3 describes 1 MARSSIM uses the word should as a recommendation, not as a requirement. Each recommendation in this manual is not intended to be taken literally and applied at every site. MARSSIMs survey planning documentation will address how to apply the process on a site-specific basis.
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Sampling and Preparation for Laboratory Measurements                                    MARSSIM 1 communication with laboratory personnel during survey planning, before and during sample 2 collection, and during and after sample analysis. Collaborative communication with the 3 laboratory is an important aspect of the sampling and analysis process that helps ensure that 4 survey DQOs are met.
5 The selection of radiochemical laboratories based on their capability to meet technical, 6 reporting, and other contractual requirements is described in Section 7.4. Section 7.5 covers 7 sample collection considerations to enhance the representativeness of the sample, and the 8 establishment of field sample preparation and preservation criteria is included in Section 7.6.
9 Section 7.7 describes the selection of appropriate analytical methods to ensure that the 10 residual radionuclideseither as individual radionuclides or as a total amount of radioactivity as 11 identified in the DQOs and MQOscan be detected at appropriate levels of sensitivity and that 12 requirements for measurement uncertainties are met. Sample tracking from field activities 13 through laboratory analysis and reporting is covered in Section 7.8. Section 7.9 covers the 14 packaging and shipping of samples containing radioactive material to minimize radiation 15 exposure to the general public and meet applicable Federal and international requirements.
16 7.2    Data Quality Objectives and Measurement Quality Objectives 17 The survey design is developed and documented using the DQO process (see Appendix D).
18 The third step of the DQO process involves identifying the data needs for a survey. One 19 decision that can be made at this step is the selection of either a scan-only survey, direct 20 measurements in conjunction with scanning for performing a survey, or sampling and laboratory 21 analysis in conjunction with scanning as the appropriate data collection strategy for the survey.
22 This chapter addresses the sampling and laboratory analysis of samples.
23 Because DQOs apply to both sampling and analytical activities, what are needed from an 24 analytical perspective are performance objectives specifically for the analytical process of a 25 project. Chapter 3 of the Multi-Agency Radiological Laboratory Analytical Protocols (MARLAP; 26 NRC 2004) refers to these performance objectives as MQOs. An MQO is a quantitative or 27 qualitative statement of a performance objective or requirement for a performance characteristic 28 of a particular method. The MQOs can be viewed as the analytical portion of the overall project 29 DQOs. In a performance-based approach, the MQOs are used initially for the selection and 30 evaluation of analytical methods and protocols and are subsequently used for the ongoing and 31 final evaluation of the analytical data.
32 7.2.1    Identifying Data Needs 33 The decision maker and the survey planning team need to identify the data needs for the survey 34 being performed, including the following:
35
* type of samples to be collected or measurements to be performed (Chapter 5) 36
* radionuclide(s) of interest (Section 4.3) 37
* number of samples to be collected (Sections 5.3.3-5.3.5) 38
* type and frequency of field QC samples to be collected (Section 4.9)
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MARSSIM                                  Sampling and Preparation for Laboratory Measurements 1
* amount of material to be collected for each sample (Section 4.7.3 and Section 7.5) 2
* sampling locations and frequencies (Section 5.3.7) 3
* standard operating procedures (SOPs) to be followed or developed 4
* measurement method uncertainty (Section 6.4) 5
* target detection capabilities for each radionuclide of interest (Section 6.3) 6
* cost of the methods being evaluated (cost per analysis as well as total cost) (Appendix H) 7
* necessary turnaround time 8
* sample preservation and shipping requirements (Section 7.6) 9
* specific background for each radionuclide of interest (Section 4.5) 10
* derived concentration guideline level (DCGL) for each radionuclide of interest (Section 4.3) 11
* measurement documentation requirements (Section 5.3.11) 12
* sample tracking requirements (Section 7.8) 13 Some of this information will be supplied by subsequent steps in the DQO process, and several 14 iterations of the process may be needed to identify all of the data needs. Consulting with a 15 radiochemist or health physicist may be necessary to properly evaluate the information before 16 deciding what combination of scan-only, direct measurements and scanning, or sampling 17 methods and scanning will be required to meet the DQOs. Surveys might require data from all 18 three collection methods (i.e., sample analysis, direct measurements, and scans) to 19 demonstrate compliance with the applicable regulations and DQOs for the project.
20 7.2.2  Data Quality Indicators 21 Precision, bias, representativeness, comparability, and completeness are some of the historical 22 data quality indicators (DQIs) recommended for quantifying the amount of error in survey data 23 (EPA 2002a). The first two of these DQIs represent different aspects of the measurement 24 method uncertainty (Section 6.4), with precision representing that portion of the measurement 25 method uncertainty due to random uncertainty and bias representing that portion of the 26 measurement method uncertainty due to systematic uncertainty. Together, these DQIs should 27 be considered when selecting a measurement technique (i.e., scanning, direct measurement, or 28 sampling) or an analytical technique (e.g., radionuclide-specific analytical procedure). In some 29 instances, the DQI requirements will help in the selection of an analytical technique. In other 30 cases, the analytical requirements will assist in the selection of appropriate levels for the DQIs.
31 7.2.2.1 Precision 32 Precision is a measure of agreement among replicate measurements of the same property 33 under prescribed similar conditions (ASQC 1995). Precision is determined quantitatively based 34 on the results of replicate measurements (equations are provided in EPA 1990). The number of May 2020                                        7-3                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Sampling and Preparation for Laboratory Measurements                                                      MARSSIM 1 replicate analyses needed to determine a specified level of precision for a project is discussed 2 in Section 4.9. Several types of replicate analyses are available to determine the level of 3 precision, and these replicates are typically distinguished by the point in the sample collection 4 and analysis process where the sample is divided. Determining precision by replicating 5 measurements with results at or near the detection limit of the measurement system is not 6 recommended, because the measurement uncertainty is usually greater than the desired level 7 of precision.
8
* Field replicates 2 are two or more separate samples collected at the same point in time and 9    space (EPA 2002b). These samples, also known as collocated samples, are collected 10    adjacent to the routine field sample to determine local variability of the radionuclide 11    concentration. Typically, including for MARSSIM collection, field replicates are collected 12    about 0.5-3 feet away from the selected sample location. Analytical results from field 13    replicates can be used to assess site variation, but only in the immediate sampling area.
14    Field replicates should not be used to assess variability across a site and are not 15    recommended for assessing error (EPA 1995). Field replicates can be non-blind, single-16    blind, or double-blind.
17
* Field splits are two or more representative portions taken from a single, usually 18    homogenized, sample collected in the field (EPA 2002b). These portions are divided into 19    separate containers and treated as separate samples throughout the remaining sample 20    handling and analytical processes and are used to assess error associated with sample 21    heterogeneity, sample methodology, and analytical procedures. Field splits are used when 22    determining total error for critical samples with residual radioactive material concentrations 23    near the action level. A minimum of eight field split samples is recommended for valid 24    statistical analysis (EPA 1995). Counting multiple split samples of a homogenized field 25    sample will decrease the uncertainty of the sample, because the sample count times can be 26    combined to derive the overall count time for the sample. In some cases, homogenization 27    may not be possible (e.g., discrete [small] radioactive particles). Field split samples can be 28    non-blind, single-blind, or double-blind and are recommended for determining the level of 29    precision for a radiation survey or site investigation.
30
* An analytical laboratory replicate is two or more representative aliquots (portions of a 31    homogeneous sample, removed for the purpose of analysis or other chemical treatment) 32    whose independent measurements are used to determine the precision of laboratory 33    preparation and analytical procedures (NRC 2004). It is used to determine method 34    precision, but because it is a non-blind sample (i.e., known to the analyst), it can be used by 35    the analyst only as an internal control tool and not as an unbiased estimate of analytical 36    precision (EPA 1990).
37
* A laboratory instrument replicate is the repeated measurement of a sample that has been 38    prepared for counting (i.e., laboratory sample preparation and radiochemical procedures 39    have been completed). It is used to determine precision for the instrument (repeated 40    measurements of the same sample using same instrument) and the instrument calibration 2 The term field replicates is used in some documents to refer to what this guidance calls field splits.
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MARSSIM                                  Sampling and Preparation for Laboratory Measurements 1    (repeated measurements of the same sample using different instruments, such as two 2    different germanium detectors with multichannel analyzers). A laboratory instrument 3    replicate is generally performed as part of the laboratory QC program and is a non-blind 4    sample. It is typically used as an internal control tool and not as an unbiased estimate of 5    analytical precision.
6 7.2.2.2 Bias 7 Bias is the systematic or persistent distortion of a measurement process that causes error in 8 one direction (ASQC 1995). Bias is determined quantitatively based on the analysis of samples 9 with a known concentration. There are several types of samples with known concentrations. QC 10 samples used to determine bias should be included as early in the analytical process as 11 possible.
12
* Reference materials are one or more materials or substances with property values that are 13    sufficiently homogeneous and well established to be used for the calibration of an 14    apparatus, the assessment of a measurement method, or for assigning values to materials 15    (ISO 2008). A certified reference material is one for which each certified property value is 16    accompanied by an uncertainty at a stated level of confidence. Radioactive reference 17    materials may be available for certain radionuclides (e.g., uranium) in soil, but reference 18    building materials may not be available. Because reference materials are prepared and 19    homogenized as part of the certification process, they are rarely available as double-blind 20    samples. When appropriate reference materials are available (i.e., proper matrix, proper 21    radionuclide, and proper concentration range), they are recommended for use in 22    determining the overall bias for a measurement system.
23
* Performance evaluation (PE) samples are used to evaluate the overall bias of the analytical 24    laboratory and detect any error in the analytical method used. These samples are usually 25    prepared by a third party, using a quantity of analyte(s) known to the preparer but unknown 26    to the laboratory, and always undergo certification analysis. The analyte(s) used to prepare 27    the PE sample is the same as the analyte(s) of interest. Laboratory procedural error is 28    evaluated by the percentage of analyte identified in the PE sample (EPA 1995). PE samples 29    are recommended for use in determining overall bias for a measurement system when 30    appropriate reference materials are not available. PE samples are equivalent to matrix 31    spikes prepared by a third party that undergo certification analysis and can be non-blind, 32    single-blind, or double-blind.
33
* Matrix spike samples are environmental samples that are spiked in the laboratory with a 34    known concentration of a target analyte(s) to verify percent recoveries. They are used 35    primarily to check sample matrix interferences but can also be used to monitor laboratory 36    performance. However, a data set of at least three or more results is necessary to 37    distinguish between laboratory performance and matrix interference (EPA 1995). Matrix 38    spike samples are often replicated to monitor method performance and evaluate error due to 39    laboratory bias and precision (when four or more pairs are analyzed). These replicates are 40    often collectively referred to as a matrix spike/matrix spike duplicate (MS/MSD).
41 Several additional terms are applied to samples prepared by adding a known amount of the 42 radionuclide of interest to the sample. The majority of these samples are designed to isolate May 2020                                          7-5                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Sampling and Preparation for Laboratory Measurements                                                    MARSSIM 1 individual sources of bias within a measurement system by preparing pre- and post-operation 2 spikes. For example, the bias from the digestion phase of the measurement system can be 3 determined by comparing the result from a pre-digest spike to the result from a post-digest 4 spike.
5 Several types of samples are used to estimate bias caused by contamination during the sample 6 collection or analytical process:
7
* Background samples are collected from a non-impacted area with similar characteristics 8      (either onsite or offsite) where there is little or no chance of migration of the radionuclides of 9      concern (EPA 1995). Background samples are collected from the background reference 10      area (Section 4.5), to determine the natural composition and variability of the soil (especially 11      important in areas with high concentrations of naturally occurring radionuclides). They 12      provide a basis for comparison of radionuclide concentration levels with samples collected 13      from the survey unit when the statistical tests described in Chapter 8 are performed.
14
* Field blanks are samples prepared in the field using certified clean sand, soil, or water and 15      then submitted to the laboratory for analysis (EPA 1995). A field blank is used to evaluate 16      contamination error associated with sampling methodology and laboratory procedures. It 17      also provides information about contaminants that may be introduced during sample 18      collection, storage, and transport. Field blanks are recommended for determining bias 19      resulting from contamination for a radiation survey or site investigation.
20
* Method blanks are analytical control samples used to demonstrate that reported analytical 21      results are not the result of laboratory contamination (ATSDR 2005). A method blank 22      contains distilled or deionized water and reagents and is carried through the entire analytical 23      procedure (laboratory sample preparation, digestion, and analysis).3 24 7.2.2.3 Representativeness 25 Representativeness is a measure of the degree to which data accurately and precisely 26 represent a characteristic of a population parameter at a sampling point (ASQC 1995).
27 Representativeness is a qualitative term that is reflected in the survey design through the 28 selection of a measurement technique (e.g., direct measurement or sampling) and the size of a 29 sample collected for analysis.
30 Sample collection and analysis is typically less representative of true radionuclide 31 concentrations at a specific measurement location than performing a direct measurement. This 32 is caused by the additional steps required in collecting and analyzing samples, such as sample 33 collection, field sample preparation, laboratory sample preparation, and radiochemical analysis.
34 However, direct measurement techniques with acceptable detection limits are not always 35 available. When sampling is required as part of a survey design, it is critical that the sample 36 collection procedures consider representativeness. The location of the sample is determined as 37 described in Section 5.3.7, but the size and content of the sample are usually determined as 3 The method blank is also referred to as a reagent blank. The method blank is generally used as an internal control tool by the laboratory because it is a non-blind sample.
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MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1 the sample is collected. Sample size and content are discussed in Section 4.7.3 and 2 Section 7.5. Sample collection procedures also need to consider the development of the 3 DCGLs when determining the representativeness of the samples.
4 7.2.2.4 Comparability 5 Comparability is a qualitative term that expresses the confidence that two data sets can 6 contribute to a common analysis and interpolation. Generally, comparability is provided by using 7 the same measurement system for all analyses of a specific radionuclide. In many cases, 8 equivalent procedures used within a measurement system are acceptable. For example, using a 9 liquid-liquid extraction purification step to determine the concentration of plutonium-238 (238Pu) 10 using alpha spectrometry may be equivalent to using an ion-exchange column purification step.
11 However, using a gross alpha measurement made with a gas proportional counting system 12 would not be considered equivalent. Comparability is usually not an issue except in cases 13 where historical data have been collected and are being compared to current analytical results 14 or when multiple laboratories are used to provide results as part of a single survey design and 15 the analytical methods have not been clearly communicated to the laboratories.
16 7.2.2.5 Completeness 17 Completeness is a measure of the amount of valid data obtained from the measurement 18 system, expressed as a percentage of the number of valid measurements that should have 19 been collected. Valid data is all data that are usable for an intended purpose, including data with 20 no validation qualifiers and data found to be estimated that are justifiable for use. For example, 21 data below the DCGL determined using the Wilcoxon Rank Sum test (DCGLW) that are 22 estimated with high bias would be considered usable data. Completeness is of greater concern 23 for laboratory analyses than for direct measurements, because the consequence of having 24 incomplete data often requires the collection of additional samples. Direct measurements can 25 usually be repeated easily. The collection of additional samples generally requires a 26 remobilization of sample collection personnel, which can be expensive. Conditions at the site 27 may have changed, making it difficult or impossible to collect representative and comparable 28 samples without repeating the entire survey. On the other hand, if it is simply an analytical 29 problem and sufficient samples were originally collected, the analysis can be repeated using 30 archived sample material. Samples collected on a grid to locate areas of elevated activity are 31 also a concern for completeness. If one sample analysis result is not valid, the survey design 32 may not be able to detect areas of elevated activity near or at the missing sample location.
33 7.2.2.6 Other Data Quality Indicators 34 Several additional data quality indicators that influence the final status survey (FSS) design are 35 identified as DQOs and MQOs in Section 2.3.1. Many of these (e.g., selection and classification 36 of survey units, decision error rates, variability in the contaminant concentration, lower bound of 37 the gray region) are used to determine the number of measurements and are discussed in detail 38 in Section 5.3. The required detection capability (Section 6.3) and measurement method 39 uncertainties (Section 6.4) are directly related to the selection of a measurement method and a 40 radionuclide-specific analytical technique.
41 Cost, time, best available technology, or other constraints may create situations where the 42 required detection capabilities or measurement method uncertainties are deemed impracticable.
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Sampling and Preparation for Laboratory Measurements                                      MARSSIM 1 Under these circumstances, different values may be acceptable. Although laboratories will state 2 detection limits, these are usually based on ideal or optimistic situations and may not be 3 achievable under actual measurement conditions. Detection limits and measurement method 4 uncertainties are subject to variation from sample to sample, instrument to instrument, and 5 procedure to procedure, depending on sample size, geometry, background, instrument 6 efficiency, chemical recovery, abundance of the radiations being measured, counting time, self-7 absorption in the prepared sample, and interferences from radionuclides or other materials 8 present in the sample.
9 7.3    Communications with the Laboratory 10 Laboratory analyses of samples are generally performed by personnel not directly involved in 11 the collection of the samples being analyzed. Samples are typically collected by one group 12 working in the field and analyzed by a second group located in a laboratory. This separation of 13 tasks can potentially lead to problems based on the lack of communication between the two 14 groups. For this reason, communications between the project manager, field personnel, and 15 laboratory personnel are vital to ensuring the success of a project. The MARLAP manual 16 (NRC 2004), Section 11.2.1 provides more information on communications with a laboratory.
17 7.3.1  Communications During Survey Planning 18 The radioanalytical laboratory is a valuable resource during survey planning. Information on 19 available analytical techniques, measurement method uncertainty, method detection capability, 20 required measurement uncertainties, analytical costs, and turnaround times can easily be 21 provided by the laboratory. All this information is used to make the decision to perform direct 22 measurements or collect samples for laboratory measurements. Additional information, such as 23 required sample size/volume, type of sample container, preservative requirements, and shipping 24 requirementsincluding the laboratorys availability for receipt of samples on weekends or 25 holidayscan be obtained and factored into the survey plan.
26 Involving the radioanalytical laboratory during survey planning also provides the laboratory with 27 site-specific information about the project. Information on the radionuclides of interest, possible 28 chemical and physical form of the residual radioactive material, and mechanism for release of 29 the residual radioactive material to the environment is used to modify or develop the analytical 30 method for site-specific conditions, if required. The laboratory should also be provided with the 31 site-specific action levels (i.e., DCGLs, investigation levels) early in the survey planning 32 process.
33 In some cases, it is not practical to select a radioanalytical laboratory early in the survey 34 process to participate in the survey planning activities. For example, Federal procurement 35 procedures require that a statement of work (SOW) identifying the tasks to be performed by the 36 laboratory be developed before selecting a laboratory. Unfortunately, the details of the tasks for 37 the laboratory to perform are developed during survey planning. This means that the information 38 provided by the laboratory and used during survey planning will be obtained from another 39 source, usually a radiochemist or health physicist trained in radiochemistry. The uncertainty 40 associated with this information and subsequent decisions made based on this information 41 increases. This may lead to increased costs caused by specifying an unnecessarily expensive 42 analytical method in the SOW, repeated sampling and analysis of samples that did not meet the NUREG-1575, Revision 2                            7-8                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1 required detection capabilities, or measurement method uncertainties because the specified 2 analytical method was not sufficient. In addition, unnecessary or inappropriate analytical 3 methods may be selected by the laboratory because site-specific information concerning the 4 samples was not provided.
5 The laboratory should be consulted when planning the schedule for the survey to ensure that 6 the expected turnaround times can be met based on the projected laboratory workload.
7 7.3.2  Communications Before and During Sample Collection 8 In most situations, the sample collection and shipping containers are supplied by the laboratory; 9 therefore, the laboratory should be notified well in advance of the sampling trip so that these 10 items will be available to the sampling team during the survey.
11 The main purpose of communications with the laboratory during sample collection is to inform 12 the laboratory of modifications to the survey design specified in the planning documents 13 (e.g., Quality Assurance Project Plan [QAPP] and SOPs). The laboratory should have a copy of 14 the survey design in its possession before samples being collected.
15 Modifications to the survey design are often minor deviations from the SOPs caused by site-16 specific conditions and usually affect a small number of samples. For example, a rock 17 outcropping covered by a thin layer of soil may restrict the depth of the surface soil sample to 18 5 centimeters (cm; 2 inches [in.]) instead of the 10 cm (4 in.) specified in the SOP. If the mass of 19 the samples collected from this area of the site is one-half the expected sample mass, the 20 laboratory needs to be informed of this deviation from the SOP. Also, the laboratory should be 21 notified of the proper sample handling requirements (i.e., inform the laboratory of the proper 22 handling of gravel in the samples, as some residual radioactive material could be present in the 23 form of small gravel). Finally, the laboratory should be notified of the approximate activity 24 concentrations to be expected in samples to ensure that the laboratory is licensed and equipped 25 to handle samples with elevated activity concentrations.
26 In other situations, there may be an extensive modification to the number or types of samples 27 collected at the site that will affect the analytical methods, detection capabilities, required 28 measurement uncertainties, analytical costs, or even the assumptions used to develop the 29 DCGL. For example, a large portion of the site may have been converted to a parking lot. A 30 large pile of material that may represent the former surface soil will be sampled, as well as soil 31 collected from beneath the parking lot surface. The number of samples to be analyzed has 32 doubled compared to the original SOW.
33 If the expected timing of receipt of samples at the laboratory changes because of sample 34 collection schedule deviations, the laboratory should be notified. Most laboratories require prior 35 notification for samples to be received on weekends.
36 7.3.3  Communications During Sample Analysis 37 The laboratory should communicate with the project manager and field personnel during sample 38 analysis. The laboratory should provide a list of missing or damaged samples as soon as 39 practical after the samples are received. This allows the project manager to determine if 40 resampling is required to replace the missing or damaged samples. The project manager may May 2020                                            7-9                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Sampling and Preparation for Laboratory Measurements                                      MARSSIM 1 also request notification from the laboratory when samples are damaged or lost, or if any 2 security seals are missing or broken. Preliminary reports of analytical results may be useful to 3 help direct sampling activities and provide early indications of whether the survey objectives 4 defined by the DQOs and MQOs are being met. However, if preliminary results have not been 5 verified or validated, their usefulness is limited.
6 7.3.4    Communications Following Sample Analysis 7 Following sample analysis, the laboratory will provide documentation of the analytical results as 8 specified in the survey design, which should include the measurement result, measurement 9 uncertainty, minimum detectable activity, and quality control and chain-of-custody (COC) 10 documentation. Laboratory personnel should be available to assist with interpretation, data 11 verification, and data validation.
12 7.4    Selecting a Radioanalytical Laboratory 13 After the decision to perform sampling activities is made, the next step is to select the analytical 14 methods and determine the data needs for these methods. It is advisable to select a 15 radiochemical laboratory as early as possible in the survey planning process so it may be 16 consulted on the analytical methodology and the sampling activities. The laboratory provides 17 information on personnel, capabilities, and current workload that are necessary inputs to the 18 decision-making process. In addition, mobile laboratories can provide on-site analytical 19 capability. Obtaining laboratory or other services may involve a specific procurement process.
20 Federal procurement procedures may require additional considerations beyond the method 21 described here.
22 The procurement of laboratory services usually starts with the development of a request for 23 proposal (RFP) that includes an SOW describing the analytical services to be procured. Careful 24 preparation of the SOW is essential to the selection of a laboratory capable of performing the 25 required services in a technically competent and timely manner.
26 The technical proposals received in response to the procurement RFP must be reviewed by 27 personnel familiar with radioanalytical laboratory operations to select the most qualified offeror.
28 For complicated sites with a large number of laboratory analyses, it is recommended that a 29 portion of this evaluation take the form of a pre-award audit. The provision for this audit must be 30 in the RFP. The results of this audit provide a written record of the decision to use a specific 31 laboratory. Smaller sites or facilities may decide that a review of the laboratorys qualifications is 32 sufficient for the evaluation.
33 Six criteria should be reviewed during this evaluation:
34
* Does the laboratory possess the appropriate well-documented procedures, instrumentation, 35      and trained personnel to perform the necessary analyses? Necessary analyses are defined 36      by the data needs (radionuclide(s) of interest, required measurement uncertainties, and 37      target detection limits) identified by the DQO process.
38
* Is the laboratory experienced in performing similar analyses?
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MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1
* Does the laboratory have satisfactory performance evaluation results from formal monitoring 2    or accreditation programs? The laboratory should be able to provide a summary of QA 3    audits and proof of participation in interlaboratory cross-check programs. Equipment 4    calibrations should be performed using National Institute of Standards and Technology 5    (NIST)-traceable reference radionuclide standards whenever possible.
6
* Is there an adequate capacity to perform all analyses within the desired timeframe? This 7    criterion considers whether the laboratory possesses a radioactive materials-handling 8    license or permit for the samples to be analyzed. Very large survey designs may indicate 9    that more than one analytical laboratory is necessary to meet the survey objectives. If 10    several laboratories are performing analyses as part of the survey, the analytical methods 11    used to perform the analyses should be similar to ensure comparability of results (see 12    Appendix D).
13
* Does the laboratory provide an internal QC review of all generated data that is independent 14    of the data generators?
15
* Are there adequate protocols for method performance documentation and sample security?
16 Providers of radioanalytical services should have an active and fully documented QA program in 17 place, typically via one or more documents, such as a Quality Management Plan, Quality 18 Assurance Manual, or QAPP. This program should comply with the objectives determined by 19 the DQO process in Section 2.3.
20 Requirements for the QA program (e.g. QAPP), COC requirements, and the numbers of 21 samples to be analyzed should be specified, communicated to the laboratory in writing, and 22 agreed upon. The Sampling and Analysis Plan (SAP), analytical procedures, and the 23 documentation and reporting requirements should also be specified, communicated to the 24 laboratory in writing, and agreed upon. The laboratorys accreditation, if required, should be 25 confirmed by contacting the organization that provided the certification. These topics are 26 discussed in detail in the following sections of this chapter. Additional guidance on obtaining 27 laboratory services can be found in Chapter 5 of the MARLAP manual (NRC 2004).
28 7.5    Sampling 29 This section provides guidance on developing appropriate sample collection procedures for 30 surveys designed to demonstrate compliance with a dose- or risk-based regulation. Sample 31 collection procedures are concerned mainly with ensuring that collected samples are 32 representative of the sample media, are large enough to provide sufficient material to achieve 33 the desired detection limit and required measurement uncertainties, and are consistent with 34 assumptions used to develop the conceptual site model and the DCGLs. Additional 35 considerations for sample collection activities are discussed in Section 4.7.3.
36 Commingled chemical and radioactive waste at a site can influence sample handling and 37 laboratory requirements. Also, the external exposure rates or radioactivity concentration of a 38 specific sample may limit the time that workers will be permitted to remain in intimate contact 39 with the samples or may dictate that smaller samples be taken and special holding areas be 40 provided for collected samples before shipment. These special handling considerations may 41 conflict with the size specifications for the analytical method, normal sampling procedures, or May 2020                                        7-11                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Sampling and Preparation for Laboratory Measurements                                      MARSSIM 1 equipment. There is a potential for biasing sampling programs by selecting samples that can be 2 safely handled or legally shipped to support laboratories, which could be a concern for scoping, 3 characterization, and Radiation Survey and Site Investigation (RSSI) samples.
4 7.5.1    Surface Soil 5 The purpose of surface soil sampling is to collect samples that accurately and precisely 6 represent the radionuclides and their concentrations at the location being sampled. To do this 7 and plan for sampling, a decision must be made as to the survey design. The selection of a 8 survey design is based on the Historical Site Assessment, results from preliminary surveys 9 (i.e., scoping characterization, remedial action support), and the objectives of the survey 10 developed using the DQO process. The selection between judgment, random, and systematic 11 survey designs is discussed in Section 5.3.
12 7.5.1.1 Sample Volume 13 The volume of soil collected should be specified in the sample collection procedure. In general, 14 large volumes of soil are more representative than small volumes of soil. In addition, large 15 samples provide sufficient material to ensure that required detection limits can be achieved and 16 that sample reanalysis can be done if there is a problem. However, large samples may cause 17 problems with shipping, storage, and disposal. All of these issues should be discussed with the 18 sample collection team and the analytical laboratory during development of sample collection 19 procedures. In general, surface soil samples range in size from 100 grams up to several 20 kilograms.
21 The sample collection procedure should also make clear if it is more important to meet the 22 volume requirement of the survey design or the surface area the sample represents. Constant 23 volume is related to comparability of the results, while surface area is more closely related to the 24 representativeness of the results. Maintaining a constant surface area and depth for samples 25 collected for a particular survey can eliminate problems associated with different depth profiles.
26 The actual surface area included as part of the sample may be important for estimating the 27 probability of locating areas of elevated concentration.
28 7.5.1.2 Sample Content 29 The material present in the field at the sample location may or may not provide a representative 30 sample. Vegetative cover, soil particle size distribution, inaccessibility, and lack of sample 31 material are examples of problems that may be identified during sample collection. All 32 deviations from the survey design as documented in the SOPs should be recorded as part of 33 the field sample documentation.
34 Sample content is generally defined by the assumptions used to develop the conceptual site 35 model and the DCGLs. A typical agricultural scenario assumes that the top few centimeters of 36 soil are available for resuspension in air; that the top 15 cm (6 in.) are homogenized by 37 agricultural activities (e.g., plowing); that roots can extend down several meters to obtain water 38 and nutrients, depending on the plant; and that external exposure is based on an assumed 39 thickness of contaminated soil (usually at the surface). Depending on the dominant exposure 40 pathways for each radionuclide, this can result in a complicated set of instructions for collecting 41 representative samples. This situation can be further complicated by the fact that the site is not NUREG-1575, Revision 2                            7-12                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1 currently being used for agricultural purposes. For this situation, it is necessary to look at the 2 analytical results from the preliminary surveys (i.e., scoping, characterization, remedial action 3 support) to determine the expected depth of residual radioactive material.
4 In most situations the vegetative cover is not considered part of the surface soil sample and is 5 removed in the field. It is important that the sample collection procedure clearly indicate what is 6 and what is not considered part of the sample.
7 7.5.1.3 Sampling Equipment 8 The selection of proper sampling equipment is important to ensure that samples are collected in 9 a reproducible manner and to minimize the potential for cross-contamination. Sampling 10 equipment generally consists of a tool to collect the sample and a container to place the 11 collected sample in. Sample tracking begins as soon as the sample is collected, so it may be 12 necessary to consider security of collected samples required by the objectives of the survey.
13 Sampling tools are selected based on the type of soil, sample depth, number of samples 14 required, and training of available personnel. The selection of a sampling tool may also be 15 based on the expected use of the results. For example, if a soil sample is collected to verify the 16 depth profile used to develop the calibration for in situ gamma spectrometry, it is important to 17 preserve the soil core. Table 7.1 lists several examples of tools used for collecting soil samples, 18 situations where they are applicable, and some advantages and disadvantages involved in their 19 use.
20 Samples collected below the surface are useful in establishing the extent of residual radioactive 21 material in the vertical profile. Understanding the extent of residual radioactive material below 22 the surface can be helpful in determining remediation alternatives and release criteria. Sample 23 containers are generally not a major concern for collecting surface soil samples. Polyethylene 24 bottles with screw caps and wide mouths are recommended and should be new or clean, dry, 25 and checked for residual radioactive material before reuse. Polyethylene bags are acceptable, 26 especially with heavy gauge plastic to avoid sample spillage from tears in the bags. These 27 containers are fairly economical, provide easy access for adding and removing samples, and 28 resist chemicals, breaking, and temperature extremes. Glass containers are also acceptable, 29 but they are fragile and tend to break during shipment. Metal containers are sometimes used, 30 but sealing the container can present a problem, and corrosion can be an issue if the samples 31 are stored for a significant length of time.
32 Table 7.1: Soil Sampling Equipment 4 Disadvantages/
Equipment      Application              Advantages Considerations Scoop,          Soft surface
* Inexpensive
* Trowels with painted surfaces Trowel, or      soil                                                  should be avoided.
Post-Hole Digger 4 Reproduced and adapted from EPA 1995.
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Sampling and Preparation for Laboratory Measurements                                              MARSSIM Disadvantages/
Equipment          Application                  Advantages Considerations
* Easy to use and decontaminate Bulb Planter      Soft Soil, 0-
* Easy to use
* Limited depth capability 15 cm (0-6 in.)
* Uniform diameter and sample
* Can be difficult to volume                          decontaminate
* Preserves soil core Soil Coring        Soft soil, 0-60
* Relatively easy to use
* Limited depth capability Device            cm (0-24 in.)
* Preserves soil core
* Can be difficult to decontaminate Thin-Wall          Soft soil, 0-
* Easy to use
* Can be difficult to remove Tube              3m                                                    cores Sampler            (0-10 ft)
* Preserves soil core
* Easy to decontaminate Split Spoon        Soil, to
* Excellent depth range
* Often used in conjunction Sampler            bedrock                                                with drill rig for obtaining
* Preserves soil core            deep cores
* Useful for hard soils Shelby Tube        Soft soil, to
* Excellent depth range
* May be used in conjunction Sampler            bedrock                                                with drill rig for obtaining
* Preserves soil core            deep cores
* Tube may be used for shipping core to lab Bucket            Soft soil,
* Easy to use
* May disrupt and mix soil Auger              7.5 cm-3 m                                            horizons greater than 15 cm (3 in.-10 ft)
* Good depth range
* Uniform diameter and sample volume Hand-              Soil, 15 cm-
* Good depth range
* Destroys soil core Operated          4.5 m Power Auger        (6 in.-5 ft)
* Generally used in conjunction
* Requires two or more with bucket auger              operators
* Can be difficult to decontaminate 1 Abbreviations: cm = centimeters; in. = inches; m = meters; ft = feet.
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MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1 7.5.2  Building Surfaces 2 Because building surfaces tend to be relatively smooth, and the radioactive material is assumed 3 to be on or near the surface, direct measurements are typically used to provide information on 4 residual radioactive material concentrations. Sometimes, however, it is necessary to collect 5 actual samples of the building material surface for analysis in a laboratory.
6 7.5.2.1 Sample Volume 7 The sample volume collected from building surfaces is usually a less significant DQO concern 8 than the area from which the sample was collected. This is because building surface DCGLs are 9 usually expressed in terms of activity per unit area. It is still necessary to consider the sample 10 volume to account for sample matrix effects that may reduce the chemical recovery, which in 11 turn affects the detection limit.
12 7.5.2.2 Sample Content 13 If residual radioactive material is covered by paint or some other treatment, the underlying 14 surface and the coating itself may contain residual radioactive material. If the residual 15 radioactive material is a pure alpha or low-energy beta emitter, measurements at the surface 16 will probably not be representative of the actual residual activity level. In this case, the surface 17 layer is removed from the known area, such as by using a commercial stripping agent or by 18 physically abrading the surface. The removed coating material is analyzed for activity content 19 and the level converted to appropriate units (i.e., becquerels/square meter [Bq/m2], decays per 20 minute [dpm]/100 cm2) for comparison with surface activity DCGLs. Direct measurements can 21 be performed on the underlying surface after removal of the coating.
22 Residual radioactive material may be incorporated into building materials, such as pieces of 23 concrete or other unusual matrices. Developing SOPs for collecting these types of samples may 24 involve consultation with the analytical laboratory to help ensure that the objectives of the 25 survey are achieved.
26 The thickness of the layer of building surface to be removed as a sample should be consistent 27 with the development of the conceptual site model and the DCGLs. For most sites, the surface 28 layer will only be the first few millimeters of the material being sampled.
29 7.5.2.3 Sampling Equipment 30 Tools used to provide samples of building surfaces depend on the material to be sampled.
31 Concrete may require chisels, hammers, drills, or other tools specifically designed to remove a 32 thin layer of the surface. Wood surfaces may require using a sander or a saw to collect a 33 sample. Paint may be chemically or physically stripped from the surface.
34 Sample containers for these samples are generally the same as those recommended for soil 35 samples. If chemicals are used to strip paint or other surface materials, the chemical resistance 36 of the container should be considered.
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Sampling and Preparation for Laboratory Measurements                                        MARSSIM 1 7.5.3    Other Media 2 Surface soil and building surfaces are the media addressed in MARSSIM during the FSS 3 design. Other media may be involved and may have been remediated. Data collection activities 4 during preliminary surveys (i.e., scoping, characterization, remedial action support) may involve 5 collecting samples of other media to support the FSS design. Examples of other media that may 6 be sampled include 7
* subsurface soil 8
* ground water 9
* surface water 10
* sediments 11
* sewers and septic systems 12
* flora and fauna (plants and animals) 13
* airborne particulates 14
* air (gas) 15 7.6    Field Sample Preparation and Preservation 16 Proper sample preparation and preservation are essential parts of any radioactive material 17 sampling program. The sampling objectives should be specified before sampling activities 18 begin. Precise records of sample collection and handling are necessary to ensure that data 19 obtained from different locations or time frames are correctly compared.
20 The appropriateness of sample preparation techniques is a function of the analysis to be 21 performed (EPA 1992a, 1992b). Field sample preparation procedures are a function of the 22 specified analysis and the objectives of the survey. It is essential that these objectives be clearly 23 established and agreed on in the early stages of survey planning (see Section 2.3).
24 7.6.1    Surface Soil 25 Soil and sediment samples, in most protocols, require no field preparation and are not 26 preserved. In some protocols (e.g., if the sample will be analyzed for both volatile organics and 27 radionuclides), cooling of soil samples to 4 degrees Celsius is required during shipping and 28 storage of soil samples.
29 When replicate samples are prepared in the field, it is necessary to homogenize the sample 30 before separation into replicates. There are standard procedures for homogenizing soil in the 31 laboratory (ASTM 2010), but the equipment required for these procedures may not be available 32 in the field. Simple field techniques, such as cone and quarter, or using a riffle splitter to divide 33 the sample may be appropriate if the sample can be dried (ASTM 2003, EPA 1995). If the 34 sample contains significant amounts of residual water (e.g., forms clumps of soil) and there are 35 no facilities for drying the sample, it is recommended that the homogenization and separation NUREG-1575, Revision 2                          7-16                                        May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1 into replicates be performed in a laboratory. It is preferable to use non-blind replicates where the 2 same laboratory prepares and analyzes the replicates rather than use poorly homogenized or 3 heterogeneous samples to prepare replicate samples.
4 7.6.2  Building Surfaces 5 Field preparation and preservation of building and associated materials, including smear 6 samples, is not generally required. Homogenization of samples to prepare replicates is the 7 same for building surface material and soil.
8 7.6.3  Other Media 9 Other media may have significant requirements related to field sample preparation and 10 preservation. For example, water samples may need filtering and acidification. Storage at 11 reduced temperatures (i.e., cooling or freezing) to reduce biological activity may be necessary 12 for some samples. Adding chemical preservatives for specific radionuclides or media may also 13 be required. Guidance on sample preparation and preservation in matrices not discussed above 14 can be found in Chapter 10 of MARLAP.
15 7.7    Analytical Procedures 16 The selection of the appropriate radioanalytical methods is normally made before the 17 procurement of analytical services and is included in the SOW of the request for proposal. The 18 SOW may dictate the use of specific methods or be performance based. Unless there is a 19 regulatory requirement, such as conformance to the EPA drinking water methods (EPA 1980b),
20 the specification of performance-based methodology is encouraged. One reason for this is that 21 a laboratory will usually perform better using the methods it routinely employs, rather than other 22 methods with which it has less experience. The laboratory is also likely to have historical data 23 on performance for methods routinely used by that laboratory. However, the methods employed 24 in a laboratory should be derived from a reliable source.
25 This section briefly describes specific equipment and procedures to be used once the sample is 26 prepared for analysis. The results of these analyses (i.e., the concentrations of radioactive 27 material found in these samples) are the values used to determine the level of residual 28 radioactive material at a site. In a decommissioning effort, the DCGLs are expressed in terms of 29 the concentrations of certain radionuclides. It is of vital importance, therefore, that the analyses 30 be accurate, of adequate sensitivity, and have adequate minimum measurement uncertainties 31 for the radionuclides of concern. The selection of analytical procedures should be coordinated 32 with the laboratory and specified in the survey plan.
33 Analytical methods should be adequate to meet the data needs identified in the DQO process.
34 Consultation with the laboratory performing the analysis is recommended before selecting a 35 course of action. MARSSIM is not intended to limit the selection of analytical procedures; rather, 36 all applicable methods should be reviewed to provide results that meet the objectives of the 37 survey. The decision maker and survey planning team should decide whether routine methods 38 will be used at the site or if non-routine methods may be acceptable.
39
* Routine analytical methods are documented with information on minimum performance 40      characteristics, such as detection limit, minimum measurement uncertainty, precision and May 2020                                        7-17                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Sampling and Preparation for Laboratory Measurements                                  MARSSIM 1    accuracy, and useful range of radionuclide concentrations and sample sizes. Routine 2    methods may be issued by a recognized organization (e.g., Federal or State agency, 3    professional organization), published in a refereed journal, or developed by an individual 4    laboratory. The following are examples of sources for routine methods:
5    o    Methods of Air Sampling and Analysis (Lodge 1988) 6    o    Annual Book of ASTM Standards, Water and Environmental technology. Volume 11.05, 7          Environmental Assessment, Risk Management and Corrective Action (ASTM 2012) 8    o    Standard Methods for the Examination of Water and Wastewater (APHA 2012) 9    o    Environmental Measurements Laboratory Procedures Manual (DOE 1997) 10    o    Inventory of Radiological Methodologies for Sites Contaminated With Radioactive 11          Materials (EPA 2006d) 12    o    Radiochemistry Procedures Manual (EPA 1984) 13    o    ANSI-AARST Radon Protocols/Standards 14            MAH-2014, Protocol for Conducting Measurements of Radon and Radon Decay 15              Products in Homes (AARST 2014a) 16            MAMF-2017, Protocol for Conducting Measurements of Radon and Radon Decay 17              Products in Multifamily Buildings (AARST 2017) 18            MALB-2014, Protocol for Conducting Measurements of Radon and Radon Decay 19              Products in Schools and Large Buildings (AARST 2014b) 20            MS-PC-2015, Performance Specifications for Instrumentation Systems Designed to 21              Measure Radon Gas in Air (AARST 2015) 22            MS-QA-2019, Radon Measurement Systems Quality Assurance (AARST 2019) 23
* Non-routine methods address situations with unusual or problematic matrices; low detection 24    limits; or new parameters, procedures or techniques. Non-routine methods include 25    adjustments to routine methods, new techniques published in refereed literature, and 26    development of new methods.
27 References that provide information on radiochemical methodology and should be considered in 28 the methods review and selection process are available from such organizations as 29
* National Council on Radiation Protection and Measurements 30
* American Society of Testing and Materials 31
* American National Standards Institute 32
* Radiological and Environmental Sciences Laboratory, Idaho Falls, Idaho (operated by the 33    U.S. Department of Energy)
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MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1
* National Urban Security Technology Laboratory, New York City, NY (operated by the 2    U.S. Department of Homeland Security) 3 Equipment vendor literature, catalogs, and instrument manuals are often a source of useful 4 information on the characteristics of radiation detection equipment. Table 7.2 provides a 5 summary of common laboratory methods with estimated detection limits.
6 Analytical procedures in the laboratory consist of several parts that are assembled to produce 7 an SOP for a specific project or sample type. These procedures may include all or only some of 8 the following elements:
9
* laboratory sample preparation 10
* sample dissolution 11
* sample purification 12
* preparation for counting 13
* counting 14
* data reduction 15 7.7.1    Photon-Emitting Radionuclides 16 There is minimal special sample preparation required for counting samples using a germanium 17 detector or a sodium iodide (NaI) detector beyond placing the sample in a known geometry for 18 which the detector has been calibrated. The procedures to be followed to process a raw soil 19 sample to obtain a representative subsample for analysis depend, to some extent, upon the size 20 of the sample, the amount of processing already undertaken in the field, andmost important 21 the radionuclide of interest (NRC 2004). The samples can be measured as they arrive at the 22 laboratory, or the sample can be dried, ground to a uniform particle size, and mixed to provide a 23 more homogeneous sample if required by the SOPs. Guidance on the preparation of samples, 24 including soil samples, can be found in Chapter 12 of MARLAP (NRC 2004).
25 The samples are typically counted using a germanium detector with a multichannel analyzer or 26 a NaI detector with a multichannel analyzer. Germanium detectors have better resolution and 27 can identify peaks (and the associated radionuclides) at lower concentrations. NaI detectors 28 often have a higher efficiency and are significantly less expensive than germanium detectors.
29 Low-energy photons (i.e., x-rays and gamma rays below 50 kilo-electron volts) can be 30 measured using specially designed detectors with an entrance window made from a very light 31 metal, typically beryllium. Descriptions of germanium and NaI detectors are provided in 32 Appendix H.
33 Data reduction is usually the critical step in measuring photon-emitting radionuclides. Often 34 several hundred individual gamma ray energies are detected within a single sample. Computer 35 software is usually used to identify energy peaks and associate these peaks with their 36 respective radionuclides. The software is also used to correct for the efficiency of the detector 37 and the geometry of the sample and to provide results in terms of concentrations with the May 2020                                        7-19                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
1    Table 7.2: Typical Measurement Sensitivities for Laboratory Radiometric Procedures NUREG-1575, Revision 2 Sampling and Preparation for Laboratory Measurements Sample            Radionuclides or                                                                                          Approximate Detection Procedure Type            Radiation Measured                                                                                              Capability Gross alpha                          Gas-flow proportional counter; 5 min count                            0.08 Bq (5 dpm)
Alpha scintillation detector with scaler; 5 min count                  0.33 Bq (20 dpm)
Smears Gross beta                            Gas-flow proportional counter; 5 min count                            0.17 Bq (10 dpm)
(Filter DRAFT FOR PUBLIC COMMENT End window GM with scaler; 5 min count (unshielded detector)          1.33 Bq (80 dpm)
Paper)
Low energy beta                      Liquid scintillation spectrometer; 5 min count                        0.50 Bq (30 dpm)
(3H, 14C, 63Ni) 137Cs, 60Co, 226Ra (214Bi)a,          Germanium detector (25% relative efficiency) with multichannel        0.04-0.1 Bq/g 232Th (228Ac), 235U                  analyzer; pulse height analyzer; 500 g sample; 15 min analysis        (1-3 pCi/g)
Soil 234, 235, 238U; 238, 239, 240Pu;      Alpha spectroscopy with multichannel analyzerpyrosulfate              0.004-0.02 Bq/g Sediment 227, 228, 230, 232Th;  other alpha  fusion and solvent extraction; surface barrier detector; pulse        (0.10.5 pCi/g) emitters                              height analyzer; 1 g sample; 16 h count Gross alpha                          Gas-flow proportional counter; 100 ml sample, 200 min count            0.04 Bq/L (1 pCi/L)
Gross beta                            Gas-flow proportional counter; 100 ml sample, 200 min count            0.04 Bq/L (1 pCi/L) 7-20                              137Cs, 60Co, 226Ra (214Bi),          Germanium detector (25% relative efficiency) with multichannel        0.4 Bq/L (10 pCi/L) 232Th (228Ac), 235U                  analyzer; pulse height analyzer; 3.5 L sample, 16 h count Water 234, 235, 238U; 238, 239, 240Pu;      Alpha spectroscopy with multichannel analyzersolvent                  0.004-0.02 Bq/L 227, 228, 230, 232Th;  other alpha  extraction; surface barrier detector; pulse height analyzer;          (0.1-0.5 pCi/L) emitters                              100 ml sample, 30 min count May 2020 3H                                    Liquid scintillation spectrometry; 5 ml sample, 30 min count          10 Bq/L (300 pCi/L) 2    Abbreviations: min = minute; Bq = becquerel; dpm = disintegrations per minute; GM = Geiger-Mueller; g = grams; h = hour; pCi = picocuries; ml = milliliters; L =
3    liters 4    a Indicates that a member of the decay series is measured to determine activity level of the parent radionuclide of primary interest.
DO NOT CITE OR QUOTE 5
MARSSIM
 
MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1 associated uncertainty. It is important that the software be either a well-documented commercial 2 package or thoroughly evaluated and documented before use.
3 7.7.2    Beta-Emitting Radionuclides 4 Laboratory sample preparation is an important step in the analysis of surface soil and other solid 5 samples for beta-emitting radionuclides. The laboratory will typically have a sample preparation 6 procedure that involves drying the sample and grinding the soil so that all particles are smaller 7 than a specified size to provide a homogeneous sample. A small portion of the homogenized 8 sample is usually all that is required for the individual analysis.
9 Once the sample has been prepared, a small portion is dissolved, fused, or leached to provide a 10 clear solution containing the radionuclide of interest. The only way to ensure that the sample is 11 solubilized is to completely dissolve the sample. However, this can be an expensive and time-12 consuming step in the analysis. In some cases, leaching with strong acids can consistently 13 provide greater than 80 percent recovery of the radionuclide of interest (NCRP 1976) and may 14 be acceptable for certain applications. After dissolution, the sample is purified using a variety of 15 chemical reactions to remove bulk chemical and radionuclide impurities. The objective is to 16 provide a chemically and radiologically pure sample for measurement. Examples of purification 17 techniques include precipitation, liquid-liquid extraction, ion-exchange chromatography, 18 distillation, and electrodeposition. Gross beta measurements may also be performed on material 19 that has not been purified.
20 After the sample is purified, it is prepared for counting. Beta-emitting radionuclides are usually 21 prepared for a specific type of counter in a specified geometry. Some samples can be 22 precipitated and collected on a filter in a circular geometry to provide a homogeneous sample.
23 Other samples can be converted to the appropriate chemical form and diluted to a specified 24 volume in preparation for counting.
25 Measurements of some samples may be performed using a gas-flow proportional counter.
26 Because total beta activity is measured, it is important that the purification step be performed to 27 remove any interfering radionuclides. Other samples can be added to a liquid scintillation 28 cocktail and counted using a liquid scintillation spectrometer. Liquid scintillation spectrometers 29 can be used for low-energy beta-emitting radionuclides, such as 3H and 63Ni. Proper 30 applications can decrease lower limits of detection for all nuclides; however, typical applications 31 in many labs limit the minimum detectable activity to those that are higher than standard gas 32 proportional counting. Gas-flow proportional counters have a very low background. Appendix H 33 provides a description of both the gas-flow proportional counter and the liquid scintillation 34 spectrometer.
35 7.7.3    Alpha-Emitting Radionuclides 36 Laboratory sample preparation for alpha-emitting radionuclides is similar to that for beta-emitting 37 radionuclides. Sample dissolution and purification tasks are also similar to those performed for 38 beta-emitting radionuclides.
39 Because of the limited penetrating power of alpha particles, the preparation for counting is often 40 a critical step. Gross alpha measurements can be made using small sample sizes with a gas-41 flow proportional counter, but self-absorption of the alpha particles results in a relatively high 42 detection limit for this technique. Liquid scintillation spectrometers can also be used to measure 43 alpha-emitting radionuclides, but the resolution limits the usefulness of this technique. Most 44 alpha-emitting radionuclides are measured in a vacuum (to limit absorption by air) using alpha May 2020                                          7-21                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
Sampling and Preparation for Laboratory Measurements                                      MARSSIM 1 spectroscopy. This method requires that the sample be prepared as a virtually weightless mount 2 in a specific geometry. Electrodeposition is the traditional method for preparing samples for 3 counting. This technique provides the highest resolution, but it requires a significant amount of 4 training and expertise on the part of the analyst to produce a high-quality sample. Precipitation 5 of the radionuclide of interest on the surface of a substrate is often used to prepare samples for 6 alpha spectroscopy. While this technique generally produces a spectrum with lower resolution, 7 the preparation time is relatively short compared to electrodeposition, and personnel can be 8 trained to prepare acceptable samples relatively quickly.
9 Alpha-emitting radionuclides are typically measured using alpha spectroscopy. The data 10 reduction requirements for alpha spectroscopy are greater than those for beta-emitting 11 radionuclides and similar to those for photon-emitting radionuclides. Alpha spectroscopy 12 produces a spectrum of alpha particles detected at different energies, but because the sample 13 is purified before counting, all of the alpha particles come from radionuclides of a single 14 element. This simplifies the process of associating each peak with a specific radionuclide, but 15 the lower resolution associated with alpha spectroscopy increases the difficulty of identifying the 16 peaks. Although commercial software packages are available for interpreting alpha 17 spectroscopy results, an experienced operator is required to ensure that the software is working 18 properly.
19 7.8    Sample Tracking 20 Sample tracking refers to the identification of samples, their location, and the individuals 21 responsible for their custody and transfer of the custody. This process covers the entire process 22 from collection of the samples and remains intact through the analysis and final holding or 23 disposal. It begins with the taking of a sample where its identification and designation of the 24 sample are critical to being able to relate the analytical result to a site location.
25 Tracking samples from collection to receipt at the analytical laboratory is normally done through 26 a COC process and documented on a COC or tracking record. The purpose of the COC record 27 is to ensure the security and legal defensibility of the sample throughout the process. When 28 samples are received by the laboratory, internal tracking and COC procedures should be in 29 place. These procedures should be documented through SOPs that ensure integrity of the 30 samples. Documentation of changes in the custody of a sample is important. This is especially 31 true for samples that may be used as evidence to establish compliance with release criteria. In 32 such cases, there should be sufficient evidence to demonstrate that the integrity of the sample 33 is not compromised from the time it is collected to the time it is analyzed. During this time, the 34 sample should either be under the positive control of a responsible individual or secured and 35 protected from any activity that could change the true value of the results or the nature of the 36 sample. When this degree of sample handling or custody is necessary, written procedures 37 should be developed for field operations and for interfacing between the field operations and the 38 analytical laboratory. This ensures that a clear transfer of the custodial responsibility is well-39 documented and that no questions exist as to who is responsible for the sample at any time.
40 7.8.1    Field Tracking Considerations 41 Suggestions for field sample tracking are given below:
42
* Field personnel are responsible for maintaining field logbooks with adequate information to 43      relate the sample identifier (sample number) to its location and for recording other 44      information necessary to adequately interpret results of sample analytical data. Logbooks NUREG-1575, Revision 2                          7-22                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                  Sampling and Preparation for Laboratory Measurements 1    may use electronic records, provided information is stored in manner that is tamper-proof 2    and retrievable if electronic media fail.
3
* The sample collector is responsible for the care and custody of the samples until they are 4    properly transferred or dispatched. This means that samples are in their possession, under 5    constant observation, or secured. Samples may be secured in a sealed container, locked 6    vehicle, locked room, etc.
7
* Sample labels should be completed for each sample using waterproof ink or in a tamper-8    proof and recoverable electronic medium.
9
* The survey manager or designee determines whether or not proper custody procedures 10    were followed during the field work and decides if additional sampling is indicated.
11
* If photographs are included as part of the sampling documentation, the name of the 12    photographer, date, time, site location, and site description should be entered sequentially in 13    a logbook as the photos are taken. After the photographs are printed, the prints should be 14    serially numbered. Alternatively, the information can be filed in a tamper-proof electronic 15    form or database.
16 7.8.2    Transfer of Custody 17 Suggestions for transferring sample custody are given below:
18
* All samples leaving the site should be accompanied by a COC record. This record should be 19    standardized and document sample custody transfer from the sampler, often through 20    another person, to the laboratory. The sample collector is responsible for initiating the 21    tracking record. The record should include a list, containing sample designation (number), of 22    the samples in the shipping container and the analysis requested for each sample.
23
* Shipping containers should be sealed and include a tamper-indicating seal that will indicate 24    if the container seal has been disturbed. The method of shipment, courier name, or other 25    pertinent information should be listed in the COC record.
26
* The original COC record should accompany the samples. A copy of the record should be 27    retained by the individual or organization relinquishing the samples. If a sample is to be split 28    and distributed to more than one analytical laboratory, multiple forms will be needed to 29    accompany sample sets.
30
* Discuss the custody objectives with the shipper to ensure that the objectives are met. For 31    example, if the samples are sent by mail and the originator of the sample requires a record 32    that the shipment was delivered, the package should be registered with return receipt 33    requested. If, on the other hand, the objective is to simply provide a written record of the 34    shipment, a certificate of mailing may be a less expensive and appropriate alternative.
35
* The individual receiving the samples should sign, date, and note the time of receipt on the 36    record. The condition of the container and the tamper-indicating seal should be documented 37    on the COC. Any problems with the individual samples, such as a broken container, should 38    be noted on the record.
39
* COC procedures may utilize tamper-proof electronic media, as appropriate.
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Sampling and Preparation for Laboratory Measurements                                      MARSSIM 1 7.8.3    Radiochemical Holding Times 2 In some circumstances, sample holding times are particularly important. For example, liquid 3 samples are usually analyzed as quickly as possible. This would also be true for short half-lived 4 radionuclides. Minimizing the holding times in these situations can reduce the measurement 5 uncertainties and lower the minimum detectable concentrations.
6 For this reason, the SOW should contain the requirements for radiological holding and sample 7 turnaround times. It is important that the laboratory review the specifications for radionuclides 8 that have short half-lives (less than 30 days), because the method proposed by the laboratory 9 may depend on the required radiological holding time. For very short-lived radionuclides, it is 10 crucial to analyze the samples within the first two half-lives to meet the MQOs conveniently.
11 Additionally, samples requiring parent decay or progeny ingrowth should be held for sufficient 12 time before counting. Limits for minimum ingrowth and maximum or minimum decay times 13 should be established for all analytical methods where they are pertinent. For ingrowth, the 14 limits should reflect the minimum time required to ensure that the radionuclides of interest have 15 accumulated sufficiently to not adversely affect the detection limit or uncertainty (e.g., holding 16 samples for 226Ra analysis to permit ingrowth of 222Rn). Alternatively, requirements for holding 17 times may be set to ensure that interfering radionuclides have a chance to decay sufficiently 18 Conversely, the time for radioactive decay of the radionuclides of interest should be limited such 19 that the decay factor does not elevate the minimum detectible concentration or adversely affect 20 the measurement uncertainty (NRC 2004).
21 7.8.4    Laboratory Tracking 22 When the samples are received by the laboratory, they are prepared for radiochemical 23 analyses, which includes dividing the sample into aliquots. The tracking and COC 24 documentation within the laboratory become somewhat complicated because several portions 25 of the original sample may exist in the laboratory at a given time. The term tracking refers to 26 an accountability process that meets generally acceptable laboratory practices as described by 27 accrediting bodies but is less stringent than a formal COC process. Similar to the COC process, 28 tracking also develops a record of all individuals responsible for the custody and transfer of 29 samples. The use of a computer-based laboratory information management system can greatly 30 assist in tracking samples and fractions through the analytical system.
31 The minimal laboratory tracking process consists of the following:
32
* transfer of custody on receipt of the samples (original COC form is retained by the laboratory 33      and submitted with the data package for the samples) 34
* documentation of sample storage (location and amount) 35
* documentation of removal and return of sample aliquots (amount, date and time, person 36      removing or returning, and reason for removal) 37
* transfer of the samples and residues to the receiving authority (usually the site from which 38      they were taken) 39
* tamper-proof electronic systems acceptable for laboratory tracking 40 The procedure for accomplishing the above varies from laboratory to laboratory, but the exact 41 details of performing the operations of sample tracking should be contained in an SOP.
NUREG-1575, Revision 2                          7-24                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                      Sampling and Preparation for Laboratory Measurements 1 7.9    Packaging and Transporting Samples 2 All samples being shipped for radiochemical analysis should be properly packaged and labeled 3 before transport offsite or within the site. The primary concern is the possibility of spills, leaks, or 4 breakage of the sample containers. In addition to resulting in the loss of samples and cross-5 contamination, the possible release of hazardous material poses a threat to the safety of 6 persons handling and transporting the package.
7 Suggestions for packaging and shipping radioactive environmental samples are listed below:
8
* Review NRC requirements (10 CFR Part 71) and U.S. Department of Transportation (DOT) 9    requirements (49 CFR Parts 171-177) for packaging and shipping radioactive 10    environmental samples.
11
* Visually inspect each sample container for indication of leaks or defects in the sample 12    container.
13    o    Liquid samples should be shipped in plastic containers, if possible, and the caps on the 14          containers should be secured with tape. One exception to the use of plastic bottles is 15          samples collected for 3H analyses, which may require glass containers.
16      o    Heavy plastic bags with sealable tops can be used to contain solid samples (e.g., soil, 17          sediment, air filters). The zipper lock should be secured with tape. Heavy plastic lawn 18          bags can be used to contain vegetation samples. The tops should be closed with a tie 19          that is covered by tape to prevent it from loosening and slipping off.
20
* Wipe individual sample containers with a damp cloth or paper towel to remove any exterior 21      contamination. The outer surfaces of containers holding samples collected in an area 22      containing residual radioactive material should be surveyed with one or more hand-held 23      instruments appropriate for the suspected type of radioactive material.
24
* If glass sample containers are used, place sample containers inside individual plastic bags 25      and seal to contain the sample in case of breakage.
26
* Use packing material (e.g., paper, Styrofoam', bubble wrap) to immobilize and isolate each 27      sample container and buffer hard knocks on the outer container during shipping. This is 28      especially important in cold weather, when plastic containers may become brittle and water 29      samples may freeze.
30
* When liquid samples are shipped, include a sufficient quantity of an absorbent material 31      (e.g., vermiculite) to absorb all liquid packed in the shipping container in case of breakage.
32      This absorbent material also may suffice as the packing material.
33
* Include the original signed and dated COC form, identifying each sample in the package. It 34      is good practice to place the COC form in a plastic bag to prevent it from becoming wet or 35      contaminated in case of a spill during shipment. If possible, avoid having multiple packages 36      of samples covered by a single COC form.
37
* Seal closed the package and apply COC tape in such a manner that it must be torn (broken) 38      to open the package. The tape should carry the signature of the sender, and the date and 39      time, so that it cannot be removed and replaced undetected.
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Sampling and Preparation for Laboratory Measurements                                      MARSSIM 1
* Ice chests constructed of metal or hard plastic make excellent shipping containers for 2      radioactive environmental samples.
3
* Regulations may require specific labeling and markings on the external surface of each 4      shipping container and may also require handling instructions and precautions be attached 5      to the shipping container. Some information should be included on the package even if not 6      required by the regulations, such as the senders and receivers (consignee and consignor) 7      names, addresses, and telephone numbers. When required by shipping regulation, proper 8      handling instructions and precautions should be clearly marked on shipping containers.
9
* Shipments with dry ice or other hazardous packaging material are subject to requirements 10      pertaining to the packaging, apart from the radioactive or hazardous contents.
11 If samples are sent offsite for analysis, the shipper is responsible for complying with all 12 applicable Federal, State, and local regulations. Applicable Federal regulations are briefly 13 addressed below. Any State or local regulation will very likely reflect a Federal regulation.
14 7.9.1    U.S. Nuclear Regulatory Commission Regulations 15 NRC regulations for packaging, preparation, and shipment of licensed material are contained in 16 10 CFR Part 71: Packaging and Transportation of Radioactive Materials.
17
* Samples containing low levels of radioactive material are exempted as set forth in &sect;&sect; 71.10.
18
* Low Specific Activity material (LSA) is defined in &sect;&sect; 71.4: Definitions. Samples classified 19      as LSA need only meet the requirements of the DOT, discussed below, and the 20      requirements of &sect;&sect; 71.88: Air transport of plutonium. Most environmental samples either 21      will fall into this category or will be exempt of any DOT regulations.
22 7.9.2    U.S. Department of Transportation Regulations 23 The DOT provides regulations governing the transport of hazardous materials under the 24 Hazardous Materials Transportation Act of 1975 (88 Stat. 2156, Public Law 93-633). Applicable 25 requirements of the regulations are found in 49 CFR Parts 171-177. Shippers of samples 26 containing radioactive material should be aware of the current rules in the following areas:
27
* Accident reporting: 49 CFR 171 28
* Marking and labeling packages for shipment: 49 CFR 172 29
* Packaging: 49 CFR 173 30
* Placarding a package: 49 CFR 172 31
* Registration of shipper/carrier: 49 CFR 107 32
* Shipper required training: 49 CFR 172 33
* Shipping papers and emergency information: 49 CFR 172 34
* Transport by air: 49 CFR 175 35
* Transport by rail: 49 CFR 174 NUREG-1575, Revision 2                            7-26                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                    Sampling and Preparation for Laboratory Measurements 1
* Transport by vessel: 49 CFR 176 2
* Transport on public highway: 49 CFR 177 3 7.9.3  U.S. Postal Service Regulations 4 Any package containing radioactive materials may not be mailed if it is required to bear the 5 DOTs Radioactive White-1 (49 CFR 172.436), Radioactive Yellow-II (49 CFR 172.438), or 6 Radioactive Yellow-III (49 CFR 172.440) label, or if it contains quantities of radioactive material 7 in excess of those authorized in Publication 6, Radioactive Material, of the U.S. Postal Service.
8 7.9.4  International Atomic Energy Agency Regulations 9 In the event that samples or other radioactive materials, such as calibration sources, are 10 shipped outside the boundaries of the United States, the shipment of those materials must 11 comply with the International Atomic Energy Agency Regulations for the Safe Transport of 12 Radioactive Material (IAEA 2005). The areas addressed in the Regulations include 13
* activity limits and material restrictions 14
* requirements and controls for transport 15
* radioactive material package and packaging requirements 16
* test procedures 17
* administrative controls and requirements May 2020                                        7-27                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                              Interpretation of Survey Results 1                    8 INTERPRETATION OF SURVEY RESULTS 2 8.1    Introduction 3 This chapter discusses the interpretation of survey results, primarily those of the final status 4 survey (FSS). Interpreting a surveys results is most straightforward when measurement data 5 are entirely higher or lower than the wide-area derived concentration guideline level (DCGLW).
6 In such cases, the decision that a survey unit meets or exceeds the release criteria requires little 7 in terms of data analysis. However, formal statistical tests provide a valuable tool when a survey 8 units measurements are neither clearly above nor exclusively below the DCGLW. Nevertheless, 9 the survey design always makes use of the statistical tests to help ensure that the number of 10 sampling points and the measurement detectability and uncertainty are adequate, but not 11 excessive, for the decision to be made. Although most statistical analysis is completed using 12 statistical software packages, this chapter provides an explanation to facilitate the readers 13 understanding of the mechanics behind the calculations of these statistical tests.
14 Section 8.2 discusses the assessment of data quality. The remainder of Chapter 8 deals with 15 application of the statistical tests used in the decision-making process and the evaluation of the 16 test results. In addition, an example checklist is provided to assist the user in obtaining the 17 necessary information for interpreting the results of an FSS. Section 8.3 discusses the 18 application of the Sign test to survey data involving radionuclides that are not in the background.
19 Section 8.4 discusses the application of the Wilcoxon Rank Sum (WRS) test to survey data 20 involving radionuclides that are in the background and, for Scenario B, the application of the 21 quantile test when the null hypothesis is not rejected. Comparisons of scan-only results to an 22 upper confidence limit are discussed in Section 8.5. Section 8.6 discusses the results, 23 including the elevated measurement comparison (EMC), and interpretation of the statistical 24 tests. Section 8.7 discusses the documentation requirements.
25 8.2    Data Quality Assessment 26 Data Quality Assessment (DQA) is a scientific and statistical evaluation that determines whether 27 the data are of the right type, quality, and quantity to support their intended use. An overview of 28 the DQA process is presented in Section 2.3 and Appendix D. The DQA process has five 29 steps:
30
* Review the Data Quality Objectives (DQOs), Measurement Quality Objectives (MQOs) and 31      Survey Design (Section 8.2.1) 32
* Conduct a Preliminary Data Review (Section 8.2.2) 33
* Select the Statistical Test (Section 8.2.3) 34
* Verify the Assumptions of the Statistical Test (Section 8.2.4) 35
* Draw Conclusions from the Data (Section 8.2.5)
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Interpretation of Survey Results                                                        MARSSIM 1 The effort applied to DQA should be consistent with the graded approach used to develop the 2 survey design. More information on DQA can be found in Data Quality Assessment: A Users 3 Guide (EPA QA/G-9R, EPA 2006a) and Data Quality Assessment: Statistical Tools for 4 Practitioners (EPA QA/G-9S, EPA 2006b).
5 Data should be verified and validated as described in the Quality Assurance Project Plan 6 (QAPP). Guidance on data verification and validation can be found in Appendix D and Multi-7 Agency Radiation Laboratory Analytical Protocols (MARLAP) (NRC 2004) Chapter 8. Guidance 8 on developing a QAPP is available in EPA QA/G-5 (EPA 2002a) and MARLAP Chapter 4.
9 8.2.1    Review the Data Quality Objectives, Measurement Quality Objectives, and Survey 10          Design 11 The first step in the DQA evaluation is a review of the DQO outputs to ensure that they are still 12 applicable. The review of the DQOs and survey design should also include the MQOs 13 (e.g., measurement uncertainty, detectability). For example, if the data suggest the survey unit 14 was misclassified as Class 3 instead of Class 1 (i.e., because measurement results above the 15 DCGLW were obtained), then the original DQOs should be redeveloped for the correct 16 classification; or, for example, if the data show the measurement uncertainty exceeds the 17 estimate used to design the survey, the DQOs and MQOs should be revisited.
18 The survey design and data collection documentation should be reviewed for consistency with 19 the DQOs. For example, the review should check that the calculated  number of samples was 20 taken in the correct locations and that the samples were analyzed using measurement systems 21 with required detection capability and uncertainty. Example checklists for different types of 22 surveys are given in Chapter 5.
23 Determining that the survey design provides adequate power is important to decision making, 24 particularly in cases where the average levels of residual radioactive material are near the 25 DCGLW. This can be done both prospectively during survey design to test the efficacy of a 26 proposed design and retrospectively during interpretation of survey results to determine that the 27 objectives of the design are met. The procedure for generating power curves for specific tests is 28 discussed in Appendix M. Note that the accuracy of a prospective power curve depends on 29 having good estimates of the data variability, , and the number of measurements. After the 30 data are analyzed, a sample estimate of the data variability, namely the sample standard 31 deviation () and the actual number of valid measurements will be known. While the Type I ()
32 decision error rate will always be achieved, the consequence of inadequate power is an 33 increased Type II ( or false negative) decision error rate.
34
* For Scenario A, this means that a survey unit that actually meets the release criteria has a 35    higher probability of being incorrectly deemed not to meet the release criteria.
36
* For Scenario B, this means that a survey unit that does not meet the release criteria has a 37    higher probability of being incorrectly deemed to meet the release criteria.
38 Regulators are primarily concerned with errors that result from determining that a survey unit 39 meets the release criteria when it does not. This incorrect decision is a Type I error under 40 Scenario A and a Type II error under Scenario B. Site owners are also concerned with errors NUREG-1575, Revision 2                          8-2                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                                          Interpretation of Survey Results 1 that result from determining that a survey unit does not meet the release criteria when it does.
2 This incorrect decision is a Type II error under Scenario A and a Type I error under Scenario B.
3 8.2.2    Conduct a Preliminary Data Review 4 To learn about the structure and quality of the dataidentifying patterns, relationships, or 5 potential anomaliesit is recommended that the quality assurance (QA) and quality control 6 (QC) reports be reviewed and that basic statistical quantities be calculated and graphs of the 7 data, or populations estimators, be prepared so that objective evidence is provided to support 8 conclusions about the data set.
9 8.2.2.1 Data Evaluation and Conversion 10 Radiological survey data are usually obtained in units that have no intrinsic meaning relative to 11 DCGLs, such as the number of counts per unit time. For comparison of survey data to DCGLs, 12 the survey data from field and laboratory measurements are converted to DCGL units. Further 13 information on instrument calibration and data conversion is given in Section 6.7.
14 Basic statistical quantities that should be calculated for the sample data set are the 15
* sample mean 16
* sample standard deviation 17
* sample median 1 18 Other statistical quantities that may be calculated are 19
* the standard error for the mean 20
* the highest measurement 21
* the lowest measurement 22 The sample mean,  , can be calculated using Equation 8-1:
1                                                    (8-1)
                                                        = 
                                                                  =1 1 The term sample here is a statistical term and should not be confused with laboratory samples. For the calculation of basic statistical quantities above, data may consist of scan data, direct measurement data, or laboratory sample data. See also the glossary definition of sample.
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Interpretation of Survey Results                                                              MARSSIM 1 where  is the number of samples, and  are the results of the individual samples. The sample 2 standard deviation, , can be calculated using Equation 8-2:
1
                                                =        (  )2                      (8-2) 1
                                                              =1 3 The median is the middle value of the data set when the number of data points is odd and is the 4 average of the two middle values when the number of data points is even. Thus, 50 percent of 5 the data points are above the median, and 50 percent are below the median. Example 1 6 illustrates how to calculate the sample standard deviation.
Example 1: Calculate the Sample Standard Deviation Suppose the following 20 concentration values are from a survey unit:
90.7, 83.5, 86.4, 88.5, 84.4, 74.2, 84.1, 87.6, 78.2, 77.6, 86.4, 76.3, 86.5, 77.4, 90.3, 90.1, 79.1, 92.4, 75.5, 80.5.
First, the sample mean of the data should be calculated:
1
                                = 
                                        =1 1
                                    = (90.7 + 83.5 + 86.4 +  + 92.4 + 75.5 +80.5)
                                    = 83.5 The sample mean is 83.5. The sample standard deviation should also be calculated:
1
                  =        (  )2 1
                                =1 1
                    =      [(90.7 - 83.5)2 +(83.5 - 83.5)2 ++(75.5 - 83.5)2+(80.5 - 83.5)2 ]
20-1
                    = 5.7 The sample standard deviation is 5.7.
7 For Scenario A, the mean concentration of the survey unit should always be compared to the 8 DCGLW. A mean survey unit concentration less than the DCGLW is a necessary, but not 9 sufficient, requirement for the release of the survey unit if the radionuclide is not present in the 10 background. Where remediation is inadequate, this comparison may readily reveal that a survey NUREG-1575, Revision 2                                  8-4                                  May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                                        Interpretation of Survey Results 1 unit contains excess residual radioactive materialeven before applying statistical tests. For 2 example, if the sample mean of the data exceeds the DCGLW and the radionuclide of interest 3 does not appear in background, then the survey unit clearly does not meet the release criteria.
4 On the other hand, if every measurement in the survey unit is below the DCGLW, the survey unit 5 clearly meets the release criteria. 2 6 The value of the sample standard deviation is especially important. If the standard deviation is 7 too large compared to that assumed during the survey design, this may indicate that an 8 insufficient number of samples were collected to achieve the desired power of the statistical 9 test. Again, inadequate power can lead to unnecessary remediation for Scenario A (of particular 10 interest to the regulated) or inadequate remediation for Scenario B (of particular interest to the 11 regulator).
12 Large differences between the mean and the median would be an indication of skewness in the 13 data. This would also be evident in a histogram of the data. Example 2 illustrates a comparison 14 of the sample mean and median.
Example 2: Comparison of the Sample Mean and the Median Using the data from the earlier example, take the 20 concentration values from the survey unit:
90.7, 83.5, 86.4, 88.5, 84.4, 74.2, 84.1, 87.6, 78.2, 77.6, 86.4, 76.3, 86.5, 77.4, 90.3, 90.1, 79.1, 92.4, 75.5, 80.5.
Sort and rank the data from lowest to highest:
1          2            3        4          5        6          7          8            9          10 74.2        75.5        76.3      77.4      77.6      78.2      79.1        80.5        83.5        84.1 11          12          13        14          15        16        17          18          19          20 84.4        86.4        86.4      86.5      87.6      88.5      90.1        90.3        90.7        92.4 For the example data above, the median is 84.25 (i.e., (84.1 + 84.4)/2). The difference between the median and the mean (i.e., 84.25 - 83.5 = 0.75) is a small fraction of the sample standard deviation (i.e., 5.7). Thus, in this instance, the mean and median would not be considered significantly different.
15 Examining the minimum, maximum, and range of the data may provide additional useful 16 information. The maximum is the value of the largest observed sample, the minimum is the 2 It can be verified that if every measurement is below the DCGLW, the conclusion from the statistical tests will always be that the survey unit does not exceed the release criteria.
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Interpretation of Survey Results                                                          MARSSIM 1 value of the smallest observed sample, and the range is the difference between the maximum 2 and minimum. When there are 30 or fewer data points, values of the range much larger than 3 about 4 to 5 standard deviations would be unusual. For larger data sets, the range might be 4 wider. Example 3 illustrates how to determine the sample range.
Example 3: Determination of the Sample Range The minimum in the previous example is 74.2 and the maximum is 92.4, so the range is 18.2 (92.4 - 74.2 = 18.2). Dividing the range by the standard deviation indicates how many standard deviations wide the sample data represent:
18.2
                                                      = 3.2 5.7 This is only 3.2 standard deviations. Thus, the range is not unusually large.
5 8.2.2.2 Graphical Data Review 6 At a minimum, a graphical data review should consist of a posting plot and a histogram.
7 Quantile plots are also useful diagnostic tools, particularly in the two-sample case, to compare 8 the survey unit and reference area in cases where the radionuclide is present in the background 9 or measurements are not radionuclide specific. Quantile plots are discussed in Appendix L, 10 Section L.2.
11 A posting plot is simply a map of the survey unit with the data values entered at the 12 measurement locations. This potentially reveals heterogeneities in the data, especially possible 13 areas of elevated residual radioactive material. Even in a reference area, a posting plot can 14 reveal spatial trends in background data that might affect the results of the statistical tests used 15 when the radionuclide is present in the background or measurements are not radionuclide 16 specific.
17 If the data given in the examples above were obtained using a triangular grid in a rectangular 18 survey unit, the posting plot might resemble the display in Figure 8.1. Figures 8.1a and 8.1c 19 show no unusual patterns in the data, whereas Figures 8.1b and 8.1d show the exact same 20 values (and therefore the same mean) but with a different distribution of residual radioactive 21 material. Figures 8.1b and 8.1d also reveal an obvious trend toward smaller values as one 22 moves from left to right across the survey unit, which can be discerned only if spatial information 23 is available and analyzed. The graphical display of data in a posting plot is beneficial to better 24 understanding the distribution of residual radioactive material at a site.
25 If the posting plot reveals systematic spatial trends in the survey unit, the cause of the trends 26 would need to be investigated. In some cases, such trends could be due to residual radioactive 27 material, but they may also be due to inhomogeneities in the survey unit background. Other 28 diagnostic tools for examining spatial data trends may be found in EPA Guidance Document 29 QA/G-9S (EPA 2006b). The use of geostatistical tools to evaluate spatial data trends may also 30 be useful in some cases (EPA 1989b).
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MARSSIM                                                          Interpretation of Survey Results (a)                                            (b)
(c)                                            (d) 1 Figure 8.1: Examples of Posting Plots 2 Geographic information system (GIS) tools can also be used to help with creation of conceptual 3 models (e.g., provide spatial context and a better understanding of site features that may control 4 or enhance radionuclide transport in the environment). Figures created with GIS tools can also 5 assist with identifying relatively homogeneous areas of residual radioactivity for delineation of 6 survey units. Examples of features that can be captured on a figure using GIS tools include the 7 following:
8
* study area and property boundary 9
* buildings where residual radioactivity may be present 10
* roads 11
* surface water features (streams, ponds, runoff basins, ditches, culverts)
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Interpretation of Survey Results                                                                        MARSSIM 1
* underground features (underground storage tanks, piping) 2
* topography, surface geology, and outcrop locations 3
* hydrostratigraphic surfaces and isopach maps 4
* water table and potentiometric surfaces 5
* sampling locations 6
* monitoring well locations 7
* contaminant distributions 8 For example, Figure 8.2a shows a map that includes the location of two hypothetical tanks.
9 Leaks are known to have occurred near the tanks. GIS information on the location of important 10 features and topography of surficial (or subsurface) structures can be used to identify areas 11 where residual radioactivity may be present and more likely to have been transported 12 (e.g., surface water runoff direction). GIS information and geostatistical tools can be helpful in 13 designing survey plans and identifying areas most likely to be above risk-based thresholds. For 14 example, the geostatistical tools available in such codes as Visual Sample Plan and Spatial 15 Analysis and Decision Assistance (SADA) can be used to analyze data and extrapolate data in 16 areas where no data are available. Figure 8.2 illustrates the use of SADA (Version 5) in 17 creating a three-dimensional visualization of the volume of soil most likely to be affected based 18 on sampling results and use of geostatistical tools available in the code. Figure 8.2b illustrates 19 how geostatistical tools can help interpolate and extrapolate data to determine the probability of 20 exceeding a threshold following characterization.
21 A frequency plot (or a histogram) is a useful tool for examining the general shape of a data 22 distribution. This plot is a bar chart of the number of data points within a certain range of values.
23 A frequency plot of the example data from Figure 8.1 is shown in Figure 8.3. A simple method 24 for generating a rough frequency plot is the stem-and-leaf display discussed in Appendix L, 25 Section L.1. The frequency plot may reveal any obvious departures from symmetry, such as 26 skewness or bimodality (two peaks), in the data distributions for the survey unit or reference 27 area. The presence of two peaks in the survey unit frequency plot may indicate the existence of 28 isolated areas of residual radioactive material, which may need to be further investigated as part 29 of the EMC tests.
30 The presence of two peaks in the background reference area or survey unit frequency plot may 31 also indicate a mixture of background concentration distributions due to different soil types, 32 construction materials, etc., or it could indicate the presence of residual radioactivity in the 33 background reference area. 3 The greater variability in the data due to the presence of such a 34 mixture will reduce the power of the statistical tests to detect an adequately remediated survey 35 unit that meets the release criteria for Scenario A or to detect a survey unit that does not meet 3 In some cases, it may be necessary to perform additional investigation to determine if background reference areas were properly classified as non-impacted.
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MARSSIM                                                            Interpretation of Survey Results 1 the release criteria for Scenario B. These situations should be avoided whenever possible by 2 carefully matching the background reference areas to the survey units and choosing more 3 homogeneous survey units, as discussed in more detail in Appendix D. If relatively 4 homogenous survey units cannot be identified, consistent with the underlying assumptions in 5 the DCGLW derivation, then other approaches may need to be taken to evaluate the 6 acceptability of the survey units for release (e.g., increased focus on evaluation of the risk of 7 elevated areas). Consult with your regulator for highly heterogeneous survey units.
(a) 8 Figure 8.2: Sample GIS Visualization, Modified from Figures 3.4 and 7.8 in NUREG/CR-9 7021 (NRC 2012).
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Interpretation of Survey Results                                                      MARSSIM All Data 4
3 Frequency 2
1 0
76  78  80  82          84    86  88  90      92 h i (a)
(b) 1  Figure 8.3: Example of a Frequency Plot (a) and Other Statistical Information Output from 2  Visual Sample Plan v. 7 (b)
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MARSSIM                                                              Interpretation of Survey Results 1 Caution should be exercised when developing frequency plots (commonly referred to as 2 histograms). The shape of a histogram can depend on the choice of the bin widths and ranges.
3 If bins are too wide, features of the underlying distribution within the bin width may be missed. If 4 bins are too narrow, the bin-to-bin variability can be mistaken as a feature of the underlying 5 distribution. Additional caution should be exercised when interpreting histograms for small data 6 sets where smaller features, such as a second smaller peak, may not be observed.
7 Skewness or other asymmetry can impact the accuracy of the statistical tests. When the 8 underlying data distribution is highly skewed, it is often because there are a few elevated areas.
9 Because the Elevated Measurement Comparison derived concentration guideline level 10 (DCGLEMC) is specifically used to evaluate the acceptability of elevated areas (i.e., the ability of 11 a site with elevated areas of residual radioactivity material above the DCGLW to meet release 12 criteria), the limitations associated with use of statistical tests based on the median or mean for 13 nonhomogeneous residual radioactivity are mitigated. In cases where highly heterogeneous 14 residual radioactive material is present, care should be taken to ensure that the lateral extent of 15 the elevated area is delineated and a DCGLEMC is calculated consistent with the actual size of 16 the elevated area. When a number of elevated areas are present, techniques can be used to 17 evaluate the cumulative risk of the elevated areas dependent on the distribution of the elevated 18 areas in the survey unit.
19 8.2.2.3 Draw Conclusions from the Preliminary Data Review 20 In some instances, a preliminary review of the data may be sufficient to draw conclusions without 21 performing the statistical tests described in Section 8.2.3. For example, under Scenario A, the 22 sample mean of the survey unit data can be compared to the reference area sample mean and 23 the DCGLW to get a preliminary indication of the survey unit status. If the difference of the survey 24 unit sample mean and the reference area sample mean is greater than DCGLW, then the survey 25 unit cannot be released. Alternatively, significantly higher concentrations in the reference area 26 compared to the survey unit may be an indicator that the reference area is not appropriate for the 27 survey unit and warrants further investigation 28 Tables 8.3-8.5 describe examples of other circumstances leading to specific conclusions based 29 on a simple examination of the data without the need to perform certain statistical tests.
30 8.2.3    Select the Statistical Test 31 An overview of the statistical considerations important for FSSs appears in Section 2.5 and 32 Appendix D. The parameter of interest is the mean concentration in the survey unit. The 33 nonparametric tests recommended in this manual, in their most general form, are tests of the 34 median. For data that are from a skewed distribution, the mean could be significantly larger than 35 the median. Therefore, the mean should be compared to the DCGLW to ensure that the mean is 36 less than the DCGLW, as indicated in Section 8.2.2.3. If the data are highly skewed because of 37 the presence of elevated areas, the EMC test helps ensure that the site is acceptable for release.
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Interpretation of Survey Results                                                          MARSSIM 1 If one assumes that the data are from a symmetric distribution where the median and the mean 2 are effectively equal, these statistical evaluations are also tests of the mean. If the assumption 3 of symmetry is violated, then nonparametric tests of the median approximately test the mean.
4 Computer simulations (Hardin and Gilbert, 1993) have shown that the approximation is a good 5 onethat is, the correct decision will be made about whether the mean concentration exceeds 6 the DCGLW, even when the data come from a skewed distribution. In this regard, Hardin and 7 Gilbert found the nonparametric tests to be correct more often than the commonly used 8 Students t test. The robust performance of the Sign and WRS tests over a wide range of 9 conditions is the reason that they are recommended in this manual.
10 When a given set of assumptions is true, a parametric test designed for exactly that set of 11 conditions will have the highest power. For example, if the data are from a normal distribution, 12 the Students t test will have higher power than the nonparametric tests. It should be noted that 13 for large enough sample sizes (e.g., large number of measurements), the Students t test is not 14 a great deal more powerful than the nonparametric tests. On the other hand, when the 15 assumption of normality is violated, the nonparametric tests can be much more powerful than 16 the t test. Therefore, any statistical test may be used, provided that the data are consistent with 17 the assumptions underlying their use. When these assumptions are violated, the prudent 18 approach is to use the nonparametric tests, which generally involve fewer assumptions than 19 their parametric equivalents.
20 The Sign test, described in Section 5.3.4, is typically used when the radionuclide is not present 21 in background and radionuclide-specific measurements are made. The Sign test may also be 22 used if the radionuclide is present in the background at such a small fraction of the DCGLW 23 value as to be considered insignificant. In this case, background concentrations of the 24 radionuclide are included with the residual radioactive material (i.e., the entire amount is 25 attributed to facility operations). Thus, the total concentration of the radionuclide is compared to 26 the release criteria. This option should be used only if one expects that ignoring the background 27 concentration will not affect the outcome of the statistical tests. The advantage of ignoring a 28 small background contribution is that no reference area is needed. This can simplify the FSS 29 considerably. Some alternative statistical tests to the Sign test are described in Chapter 14 of 30 NUREG-1505, A Nonparametric Statistical Methodology for the Design and Analysis of Final 31 Status Decommissioning Surveys (NRC 1998a) and in Chapter 2.
32 The Sign test (Section 8.3.1) evaluates whether the median of the data is above or below the 33 DCGLW. If the data distribution is symmetric, the median is equal to the mean. In cases where 34 the data are severely skewed, the mean may be above the DCGLW, while the median is below 35 the DCGLW. In such cases, the survey unit does not meet the release criteria regardless of the 36 result of the statistical tests. On the other hand, if the largest measurement is below the DCGLW, 37 the Sign test will always show that the survey unit meets the release criteria.
38 For FSSs, the WRS test discussed in Section 5.3.3 can be used when the radionuclide of 39 concern appears in background or if measurements used are not radionuclide-specific. The 40 WRS test (Section 8.4.1) assumes the reference area and survey unit data distributions are 41 similar except for a possible shift in the medians. When the data are severely skewed, the value 42 for the mean difference may be above the DCGLW, while the median difference is below the 43 DCGLW. In such cases, the survey unit does not meet the release criteria regardless of the NUREG-1575, Revision 2                            8-12                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                    Interpretation of Survey Results 1 result of the statistical test. On the other hand, if the difference between the largest survey unit 2 measurement and the smallest reference area measurement is less than the DCGLW, the WRS 3 test will always show that the survey unit meets the release criteria.
4 The use of paired observations for survey units with different backgrounds and some alternative 5 statistical tests to the WRS test are described in Chapters 12 and 14, respectively, of NUREG-6 1505, A Nonparametric Statistical Methodology for the Design and Analysis of Final Status 7 Decommissioning Surveys (NRC 1998a). If Scenario B was selected during the DQO process, 8 the quantile test is performed to test for skewness when the WRS test does not reject the null 9 hypothesis.
10 If individual scan-only survey results are recorded, a nonparametric confidence interval can be 11 used to evaluate the results of the FSS. Similarly, a confidence interval can be used to evaluate 12 a series of in situ measurements with overlapping fields of view. A one-tailed version of 13 Chebyshevs inequality or software (e.g., EPAs ProUCL software) can be used to evaluate the 14 probability of exceeding the upper bound of the grey region (UBGR) using an upper confidence 15 limit (UCL). The use of a UCL applies to both Scenario A (where the UBGR equals the DCGLW) 16 and Scenario B (where the UBGR equals the discrimination limit [DL]). Table 8.1 provides a 17 summary of the statistical tests and evaluation methods discussed in this chapter.
18 Table 8.1: Summary of Statistical Tests and Evaluation Methods Statistical Test or Applicability Evaluation Method Sign Test
* Radionuclide not in background and nuclide-specific (see Section 8.3 and Table 8.3)        measurements
* Scenario A or B WRS Test
* Radionuclide in background or non-nuclide specific (see Section 8.4 and Table 8.4)        measurements
* Scenario A or B Quantile Test
* Test for non-uniform distribution of radioactive material (see Section 8.4)
* Combined with WRS Test
* Scenario B only Comparison to UCL
* Scan-only surveys or in situ surveys (see Section 8.5 and Table 8.5)
* Scenario A or B 19 Abbreviations: WRS test = Wilcoxon Rank Sum test; UCL = upper confidence limit.
20 8.2.4    Verify the Assumptions of the Statistical Tests 21 An evaluation to determine that the data are consistent with the underlying assumptions made 22 for the statistical procedures helps to validate the use of a test. One may also determine that 23 certain departures from these assumptions are acceptable when given the actual data and other 24 information about the study.
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Interpretation of Survey Results                                                          MARSSIM 1 For surveys consisting of a combination of scanning with samples or direct measurements, the 2 nonparametric tests described in this chapter assume that the data from the reference area or 3 survey unit consist of independent samples from each distribution. Spatial dependencies that 4 potentially affect the assumptions can be assessed using posting plots (Section 8.2.2.2). More 5 sophisticated tools for determining the extent of spatial dependencies are also available 6 (e.g., EPA QA/G-9S, EPA 2006b). These methods tend to be complex and are best used with 7 guidance from a professional statistician.
8 Asymmetry in the data can be diagnosed with a stem-and-leaf display, a histogram, or a 9 quantile plot.
10 One of the primary advantages of the nonparametric tests is that they involve fewer 11 assumptions about the data than their parametric counterparts. If parametric tests are used, 12 (e.g., Students t test), then any additional assumptions made in using them should be verified 13 (e.g., testing for normality). These issues are discussed in detail in EPA QA/G-9S (EPA 2006b).
14 One of the more important assumptions made in the survey designs described in 15 Sections 5.3.3 and 5.3.4 is that the sample sizes determined for the tests are sufficient to 16 achieve the DQOs set for the Type I and Type II error rates. Verification of the power of the 17 tests (1  ) correctly determines a site that does not meet the release criterion is not released 18 under Scenario B, regardless of what the test determined, which may be of particular interest to 19 the regulator and is, therefore, required for surveys conducted under Scenario B. For Scenario 20 A, verification of the power of the tests to correctly release a site that meets the release criteria, 21 regardless of what the test determined, may be of particular interest to the site owner/operator.
22 Methods for assessing the power are discussed in Appendix M.
23 For these reasons, it is better to plan the surveys cautiously, including 24
* overestimating the potential data variability 25
* taking more than the minimum number of measurements 26
* overestimating minimum detectable concentrations (MDCs) and measurement method 27    uncertainties 28 If one is unable to show that the DQOs and MQOs were met with reasonable assurance, a 29 resurvey may be needed. Examples of assumptions and possible methods for their assessment 30 are summarized in Table 8.2.
31 For scan-only surveys where data are compared to a UCL, Chebyshevs inequality should be 32 used with caution when there are very few points in the data set. Section 6.7 provides 33 information on converting the instrument reading to the appropriate units for reporting the UCL.
34 This is because the population mean and standard deviation in the Chebyshev formula are 35 being estimated by the sample mean and sample standard deviation. In a small data set from a 36 highly skewed distribution, the sample mean and sample standard deviation may be 37 underestimated if the high concentration but low probability portion of the distribution is not 38 captured in the sample data set.
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MARSSIM                                                                    Interpretation of Survey Results 1 Table 8.2: Methods for Checking the Assumptions of Statistical Tests Assumption                      Diagnostic Spatial Independence          Posting Plot Symmetry                      Histogram, Quantile Plot Data Variance                  Sample Standard Deviation Adequate Power                Retrospective Power Chart 2 8.2.5    Draw Conclusions from the Data 3 The types of measurements that can be made in a survey unit are direct measurements, 4 laboratory samples, and scans.
5 Specific details for conducting the statistical tests are given in Section 8.3 (Sign test),
6 Section 8.4 (WRS test and quantile test), and Section 8.5 (upper confidence limit test). When 7 the data clearly show that a survey unit meets or exceeds the release criteria, the result is often 8 obvious without performing the formal statistical analysis. The data still need to meet the 9 assumptions for the statistical tests, (e.g., ensuring adequate power in Scenario B.) Tables 8.3-10 8.5 display various survey results and their conclusions.
11 Table 8.3: Summary of Statistical Tests for Radionuclide Not in Background and 12 Radionuclide-Specific Measurement Survey Result                                              Conclusion Scenario A All measurements are less than DCGLW.                        Survey unit meets release criteria.
Sample mean is greater than DCGLW.                            Survey unit does not meet release criteria.
Any measurement is greater than DCGLW, and the                Conduct Sign test and EMC.
sample mean is less than DCGLW.
Scenario B Sample mean is less than the AL.                              Survey unit meets release criteria.
All measurements are greater than AL.                        Survey unit does not meet release criteria.
Any measurement is greater than the AL, and the              Conduct Sign test and EMC.
sample mean is greater than AL.
13 Abbreviations: DCGLW = wide-area derived concentration guideline level; EMC = elevated measurement comparison; 14 AL = action level.
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Interpretation of Survey Results                                                                          MARSSIM 1 Table 8.4: Summary of Statistical Tests for Radionuclide in Background or Radionuclide 2 Non-Specific (Gross) Measurements Survey Result                                                Conclusion Scenario A Difference between largest survey unit measurement                Survey unit meets release criteria.
and smallest reference area measurement is less than the DCGLW.
Difference between survey unit sample mean and                    Survey unit does not meet release criteria.
reference area sample mean is greater than the DCGLW.
Difference between any survey unit measurement and                Conduct WRS test and EMC.
any reference area measurement is greater than DCGLW, and the difference between survey unit sample mean and reference area sample mean is less than the DCGLW.
Scenario B Difference between survey unit sample mean and                    Conduct quantile test.
reference area sample mean is less than the AL.
Difference between smallest survey unit measurement                Survey unit does not meet release criteria.
and largest reference area measurement is greater than the AL.
Difference between any survey unit measurement and                Conduct WRS test, quantile test, and EMC.
any reference area measurement is less than the AL, and the difference between survey unit sample mean and reference area sample mean is greater than AL.
3 Abbreviations: DCGLW = wide-area derived concentration guideline level; WRS test = Wilcoxon Rank Sum test; 4 EMC = elevated measurement comparison; AL = action level.
5 6 If applicable release criteria for elevated measurements exist, then both the measurements at 7 discrete locations and the scans are also subject to the EMC. The result of comparing individual 8 measurements to DCGLEMC is not conclusive as to whether the survey unit meets or exceeds 9 the release criteria, but it is a flag or trigger for further investigation. The investigation may 10 involve taking further measurements to determine that the area and level of the elevated 11 residual radioactive material are such that the resulting dose or risk meets the release criteria. 4 12 The investigation should also provide adequate assurance, using the DQO process, that there 4  Rather than, or in addition to, taking further measurements, the investigation may involve assessing the adequacy of the exposure pathway model used to obtain the DCGLs and the consistency of the results obtained with the Historical Site Assessment and the scoping, characterization, and remedial action support surveys.
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MARSSIM                                                                        Interpretation of Survey Results 1 Table 8.5: Summary of Results for Scan-Only Surveys Survey Resulta                                                Conclusion Scenario A UCL is less than DCGLW.                                          Survey unit meets average release criteria; conduct the EMC.
UCL is greater than DCGLW.                                      Survey unit does not meet release criteria.
Scenario B UCL is less than DL.                                            Survey unit meets average release criteria; conduct the EMC.
UCL is greater than DL.                                          Survey unit does not meet release criteria.
2 Abbreviations: UCL = upper confidence limit; DCGLW = wide-area derived concentration guideline level; EMC =
3 elevated measurement comparison; DL = discrimination limit.
4 a See Section 8.5 for additional details on calculating the UCL.
5 are no undiscovered areas of elevated residual radioactive material in the survey unit that might otherwise result in a 6 dose or risk exceeding the release criteria when considered in conjunction with the dose or risk posed by the 7 remainder of the survey unit. In some cases, this may lead to reclassifying all or part of a survey 8 unit unless the results of the investigation indicate that reclassification is not necessary. The 9 investigation level appropriate for each class of survey unit and type of measurement is shown 10 in Table 5.4 and is described in Section 5.3.8. Example 4 provides background information 11 that will be used in Examples 5-8.
Example 4: Illustrative Examples Background Information This example provides the background for Examples 5-8.
To illustrate the data interpretation process, consider an example facility with 14 survey units consisting of interior concrete surfaces, one interior survey unit with drywall surfaces, and two outdoor surface soil survey units. The radionuclide of concern is cobalt-60 (60Co). The interior surfaces were measured with a gas-flow proportional counter (see Appendix H) with an active surface area of 100 square centimeters (cm2) to determine gross beta activity.
Because these measurements are not radionuclide-specific, appropriate reference areas were chosen for comparison. The exterior surface soil was measured with a germanium spectrometer to provide radionuclide-specific results. A reference area is not needed because 60 Co does not have a significant background in soil.
The exterior surface soil Class 3 survey unit incorporates areas that are not expected to contain residual radioactive material. The exterior surface soil Class 2 survey unit is similar to the Class 3 survey unit but is expected to contain concentrations of residual radioactive material below the wide-area derived concentration guideline level (DCGLW). The Class 1 May 2020                                                  8-17                          NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                            DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                                          MARSSIM interior concrete survey units are expected to contain small areas of elevated activity that may or may not exceed the DCGLW. The Class 2 interior drywall survey unit is similar to the Class 1 interior concrete survey unit, but the drywall is expected to have a lower background, less measurement variability, and a more uniform distribution of radioactive material. The Class 2 survey unit is not expected to contain areas of residual radioactive material above the DCGLW. The survey design parameters and DQOs developed for these survey units under Scenario A are summarized in Table 8.6.
Table 8.7 provides survey design parameters and DQOs developed for two survey units under Scenario B where the lower bound of the gray region is zero or indistinguishable from background for a radionuclide that is in the natural background.
1 Table 8.6: Final Status Survey Parameters for Example Survey Units for Scenario A Estimated Standard Survey                        DQO Type                          LBGR        DCGLW    a        Deviation, b          Test/Section Unit Survey    Reference Exterior      Class 2    0.025    0.025    128 Bq/kg      140 Bq/kg    4.0 Bq/kg N/A              Sign/
Surface                                                                                              Example 5 Soil Exterior      Class 3    0.025    0.01    128 Bq/kg      140 Bq/kg    4.0 Bq/kg N/A              Sign/
Surface                                                                                              Example 6 Soil Interior      Class 1      0.05    0.05    3,000 dpm/ 5,000 dpm/ 625 dpm/ 220 dpm/                  WRS/
Concrete                                    100 cm2        100 cm2      100 cm2 100 cm2            Appendix A Interior      Class 2    0.025    0.05    3,000 dpm/ 5,000 dpm/ 200 dpm/ 200 dpm/                  WRS/
Drywall                                    100 cm2        100 cm2      100 cm2 100 cm2            Example 7 2 Abbreviations: DQO = data quality objective; LBGR = lower bound of the gray region; DCGLW = derived concentration 3 guideline level using the Wilcoxon Rank Sum test;  = standard deviation;  = Type I decision error;  = Type II 4 decision error; Bq = becquerel; kg = kilogram; dpm = disintegrations per minute; cm = centimeter.
5 a DCGL is given in units of becquerels per kilogram or disintegrations per minute per 100 square centimeters.
W 6 b Estimated standard deviation from scoping, characterization, and Remedial Action Support surveys 7 8.3    Radionuclide Not Present in Background 8 The statistical test discussed in this section is used to compare each survey unit directly with the 9 applicable release criteria. A reference area is not included because the measurement 10 technique is radionuclide-specific and the radionuclide of concern is not present in background 11 (see Section 8.2.3). In this case, the concentrations of residual radioactive material are 12 compared directly with the DCGLW. The method in this section should be used only if the 13 radionuclide is not present in background or is present at such a small fraction of the DCGLW 14 value as to be considered insignificant. In addition, the Sign test is applicable only if 15 radionuclide-specific measurements are made to determine the concentrations. Otherwise, the 16 method in Section 8.4 is recommended.
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MARSSIM                                                                        Interpretation of Survey Results 1 Table 8.7: Final Status Survey Parameters for Example Survey Units for Scenario B Estimated Standard DQO                                                                  Test/
Survey Unit          Type                              AL          DL a        Deviation, b Section Survey      Reference Exterior Surface Class 1          0.05    0.05    0 Bq/kg      12 Bq/kg  6 Bq/kg      6 Bq/kg        WRS Soil Exterior Surface Class 3          0.05    0.01    0 Bq/kg      12 Bq/kg  6 Bq/kg      6 Bq/kg        WRS Soilc 2 Abbreviations: DQO = data quality objective; DL = discrimination limit;  = standard deviation;  = Type I decision 3 error;  = Type II decision error; Bq = becquerel; kg = kilogram; WRS = Wilcoxon Rank Sum.
4 a AL is zero.
5 b Estimated standard deviation from scoping, characterization, and Remedial Action Support surveys.
6 c This survey unit is not worked out in further examples.
7 Reference area samples are not needed when there is sufficient information to indicate that 8 there is essentially no background concentration for the radionuclide being considered. With 9 only a single set of survey unit samples, the statistical test used here is the Sign test. See 10 Section 5.3.4 for further information appropriate to following the example and discussion 11 presented here.
12 8.3.1      Sign Test 13 The Sign test is designed to detect failure of the survey unit to meet release criteria if the 14 radioactive material is distributed across that survey unit. Although the parameter of interest is 15 usually the mean concentration of residual radioactive material in the survey unit, the median is 16 used in the Sign test as an estimate of the mean. This test does not assume that the data follow 17 any particular distribution, such as normal or lognormal.
18 In Scenario A, the hypothesis tested by the Sign test is as follows:
19            Null Hypothesis 20            0 : The median concentration of residual radioactive material in the survey unit is 21            greater than or equal to the DCGLW.
22            Versus 23            Alternative Hypothesis 24            1 : The median concentration of residual radioactive material in the survey unit is 25            less than the DCGLW; also defined as  .
26 The null hypothesis is assumed to be true unless the statistical test indicates that it should be 27 rejected in favor of the alternative. For Scenario A, the null hypothesis states that the probability May 2020                                                  8-19                        NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                            DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                          MARSSIM 1 of a measurement less than the DCGLW is less than one-half, i.e., the 50th percentile (or 2 median) is greater than the DCGLW.
3 Because the Sign test uses the median instead of the mean, the null hypothesis in Scenario A 4 may be rejected if the median concentration is less than the DCGLW, even if the mean 5 concentration is greater than or equal to the DCGLW. If the mean concentration is greater than 6 or equal to the DCGLW, the survey unit does not meet the release criteria (see Table 8.3) 7 Furthermore, in addition to the Sign test, the DCGLEMC (see Section 5.3.5) is compared to each 8 measurement to ensure none exceeds the DCGLEMC. If a measurement exceeds the DCGLEMC, 9 then additional investigation is recommended, at least locally, to determine the actual areal 10 extent of the elevated concentration.
11 In Scenario B, the hypothesis tested by the Sign test is as follows:
12        Null Hypothesis 13        0 : The median concentration of residual radioactive material in the survey unit is 14        less than or equal to the AL.
15        Versus 16        Alternative Hypothesis 17        1 : The median concentration of residual radioactive material in the survey unit is 18        greater than the AL.
19 Again, the null hypothesis is assumed to be true unless the statistical test indicates that it should 20 be rejected in favor of the alternative. For Scenario B, the null hypothesis states that the 21 probability of a measurement greater than the AL is less than one-half (i.e., the 50th percentile 22 [or median] is less than the AL).
23 When using the Sign test for both Scenario A and B, it is necessary to show that there are a 24 sufficient number of measurements or samples with concentrations below the DCGLW or AL, 25 respectively. Under Scenario A, when there are too many measurements or samples with 26 concentrations above the DCGLW, we fail to reject the null hypothesis that the survey unit does 27 not meet the release criteria. Under Scenario B, when there are too many measurements or 28 samples with concentrations above the lower bound of the gray region (LBGR), we reject the 29 null hypothesis that the survey unit does meet the release criteria.
30 When the values of  and  are selected in the DQO process, an important difference between 31 Scenario A and Scenario B should be considered. For a fixed value of , a lower value for  is 32 more protective in Scenario A, but is less protective in Scenario B. In both scenarios, a lower 33 value for  requires a higher degree of evidence before the null hypothesis is rejected. In 34 Scenario A, the null hypothesis is that the survey unit exceeds the release criteria, and a lower 35 value for  makes it more difficult to reject this hypothesis. In Scenario B, the null hypothesis is 36 that the survey unit meets the release criteria, and a lower value of  makes it more difficult to 37 reject this hypothesis.
38 Note that some individual survey unit measurements may exceed the DCGLW even when the 39 survey unit as a whole meets the release criteria. In fact, a survey unit sample mean that is NUREG-1575, Revision 2                            8-20                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                                Interpretation of Survey Results 1 close to the DCGLW might have almost half of its individual measurements greater than the 2 DCGLW. Such a survey unit may still not exceed the release criteria. The risk associated with 3 any areas above the DCGL is evaluated by developing a DCGLEMC based on dose or risk 4 modeling. The DCGLEMC is higher than the DCGLW and consider the size of the elevated area.
5 As long as the concentration in the elevated areas are less than the DCGLEMC, the site can be 6 released. See Section 8.6.1 for additional details.
7 The assumption is that the survey unit measurements are independent random samples from a 8 symmetric distribution. If the distribution of measurements is symmetric, the median and the 9 mean are the same. If the distribution of measurements is highly skewed, then the efficacy of 10 the statistical tests is reduced because of the underlying homogeneity assumptions inherent in 11 the decision criteria (i.e., DCGL calculations).
12 The hypothesis specifies release criteria in terms of a DCGLW. The test should have sufficient 13 power (1 - , as specified in the DQOs) to detect concentrations of residual radioactive material 14 at the LBGR, which is less than the DCGLW. If  is the standard deviation of the measurements 15 in the survey unit, then the relative shift (the width of the gray region, which is calculated by 16 DCGLW-LBGR, divided by the standard deviation []) reflects the difference between the 17 average concentration of radioactive material and the DCGL relative to measurement variability.
18 The procedure for determining  is given in Section 5.3.3.2.
19 As stated above, the null hypothesis for Scenario B is that the median concentration of residual 20 radioactive material in the survey unit is less than the LBGR (or AL). To use the Sign test with 21 Scenario B, the concentration of radioactive material in background should be zero or 22 insignificant compared to the LBGR (or AL). In some cases, the LBGR (or AL) may be set equal 23 to zero (e.g., release criteria require that concentrations be indistinguishable from background 24 and the radionuclide is not present in background). In this case, results should be scattered 25 about zero; therefore, if there are too many results with concentrations greater than zero, the 26 null hypothesis should be rejected. Results less than zero are both possible and likely when the 27 concentrations are truly equal to zero and measurements are subject to some random 28 component of measurement method uncertainty.
29 In this case, the number of positive and negative results are expected to be the same, and the 30 average of all the results is expected to be zero. When analyzing samples where the 31 concentration is very small, the data analysis should be reviewed carefully, because even 32 relatively small systematic errors can result in relatively large differences in the number of 33 positive and negative results.
34 Some laboratories report results below the lower limit of detection as < LLD or below the 35 minimum detectable activity as < MDA. Under Scenario A, the use for the Sign test of such 36 results is usually not problematic, because the DL is required to be less than the DCGLW, and 37 any values less than the DL will also be less than the DCGLW. However, under Scenario B, in 38 which the DL is greater than the AL, it is difficult to determine if the concentrations reported as May 2020                                          8-21                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                            MARSSIM 1 < LLD or < MDA are greater than or less than the AL. For this reason, the Sign test should be 2 used only for Scenario B when actual concentrations, no matter how small, are reported.
3 8.3.2  Applying the Sign Test 4 The Sign test is applied as outlined in the following five steps, and further illustrated by 5 Examples 5 and 6. Separate instructions are given for Scenarios A and B.
6        Scenario A 7        1. List the survey unit measurements:  ,  = 1, 2, 3,  , .
8        2. Subtract each measurement,  , from the DCGLW to obtain the differences:  =
9            DCGLW  ,  = 1, 2, 3,  , .
10        3. Discard each difference that is exactly zero and reduce the sample size, , by the 11            number of such measurements exactly equal to the DCGLW.
12        4. Count the number of positive differences. The result is the test statistic S+. (Note that 13            a positive difference corresponds to a measurement below the DCGLW and 14            contributes evidence that the survey unit meets the release criteria).
15        5. Large values of S+ indicate that the null hypothesis is false. The value of S+ is 16            compared to the critical values in Table I.4. If S+ is greater than the critical value, k, 17            in that table, the null hypothesis is rejected.
18        Scenario B 19        1. List the survey unit measurements:  ,  = 1, 2, 3,  , .
20        2. Subtract the AL from each measurement,  , to obtain the differences:  =  AL, 21              = 1, 2, 3,  , .
22        3. Discard each difference that is exactly zero and reduce the sample size, , by the 23            number of such measurements exactly equal to the AL.
24        4. Count the number of positive differences. The result is the test statistic S+. (Note that 25            a positive difference corresponds to a measurement above the AL and contributes 26            evidence that the survey unit does not meet the release criteria.)
27        5. Large values of S+ indicate that the null hypothesis is false. The value of S+ is 28            compared to the critical values in Table I.4. If S+ is greater than the critical value, k, 29            in that table, the null hypothesis is rejected.
30 Passing a survey unit without making a single calculation may seem an unconventional 31 approach. However, the key is in the survey design, which is intended to ensure enough 32 measurements are made to satisfy the DQOs. As in the previous example, after the data are 33 collected, the conclusions and power of the test can be checked by constructing a retrospective 34 power curve as outlined in Appendix M.
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MARSSIM                                                                Interpretation of Survey Results 1 In addition to checking the power of the statistical test, it is also important to ensure that the 2 uncertainty of the measurements met the MQOs for required measurement uncertainty. One 3 final consideration remains regarding the survey unit classification: Was any definite amount of 4 residual radioactive material found in the survey unit? This will depend on the MDC of the 5 measurement method. Generally, the MDC is at least three or four times the estimated 6 measurement standard deviation. For example, in Table 8.9, the largest observation, 7 9.3 becquerels/kilogram (Bq/kg; 0.25 picocuries/gram [pCi/g]), is less than three times the 8 estimated measurement standard deviation of 3.8 Bq/kg (0.10 pCi/g). Thus, it is unlikely that 9 any of the measurements could be considered indicative of positive residual radioactive 10 material. This means that the Class 3 survey unit classification was appropriate. Examples 5 11 and 6 illustrate how to use the Sign test on Class 2 and 3 exterior soil units.
Example 5: Sign Test for a Class 2 Exterior Soil Survey Unit Refer back to Example 4 for background information. For the Class 2 Exterior Soil survey unit, the Sign test is appropriate, because the radionuclide of concern does not appear in background and radionuclide-specific measurements were made. Scenario A is selected.
Table 8.6 shows that the DQOs for this survey unit include  = 0.025 and  = 0.025. The DCGLW is 140 becquerels/kilogram (Bq/kg; 3.8 picocuries/gram [pCi/g]), and the LBGR was selected to be 128 Bq/kg (3.5 pCi/g). The estimated standard deviation of the measurements is  = 4.0 Bqkg (0.11 pCig). The relative shift was calculated to be 3.0, as shown below:
DCGLW  LBGR 140 Bq/kg  128 Bq/kg
                              =                    =                              = 3.0 4.0 Bq/kg Table 5.3 indicates the number of measurements estimated for the Sign Test, , is 20
( = 0.025,  = 0.025, and  = 3). (Table I.2 in Appendix I also lists the number of measurements estimated for the Sign test.) This survey unit is Class 2, so the 20 measurements needed were made on a random-start triangular grid. When laying out the grid, 22 measurement locations were identified.
The 22 measurements taken on the exterior lawn Class 2 survey unit are shown in the first column of Table 8.8. The mean of these data is 129 Bq/kg (3.5 pCi/g), and the standard deviation is 11 Bq/kg (0.30 pCi/g). Since the number of measurements is even, the median of the data is the average of the two middle values (126+128)/2 = 127 Bq/kg (3.4 pCi/g). A quantile plot of the data is shown in Appendix L, Figure L.3.
Five measurements exceed the DCGLW value of 140 Bq/kg: 142, 143, 145, 148, and 148.
However, none exceed the mean of the data plus three standard deviations:
129+(3x11) = 162 Bqkg (4.3 pCig). Thus, these values appear to reflect the overall variability of the concentration measurements rather than to indicate an area of elevated activityprovided that these measurements were scattered through the survey unit.
However, if a posting plot demonstrates that the locations of these measurements are May 2020                                        8-23                        NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                        MARSSIM grouped together, then that portion of the survey unit containing these locations merits further investigation.
The middle column of Table 8.8 contains the differences, DCGLW - Data, and the last column contains the signs of the differences. The bottom row shows the number of measurements with positive differences, which is the test statistic S+. In this case, S+ = 17.
The value of S+ is compared to the appropriate critical value in Table I.4. In this case, for
    = 22 and  = 0.025, the critical value is 16. Because S+ = 17 exceeds this value, the null hypothesis that the survey unit exceeds the release criteria is rejected.
1 Table 8.8: Example Sign Analysis: Class 2 Exterior Soil Survey Unit Data          DCGLW  Data Sign (Bq/kg)              (Bq/kg) 121                  19            +
143                  -3            -
145                  -5            -
112                  28            +
125                  15            +
132                    8            +
122                  18            +
114                  26            +
123                  17            +
148                  -8            -
115                  25            +
113                  27            +
126                  14            +
134                    6            +
148                  -8            -
130                  10            +
119                  21            +
136                    4            +
128                  12            +
125                  15            +
142                  -2            -
129                  11            +
Number of positive differences S+ = 17 2
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MARSSIM                                                                Interpretation of Survey Results Example 6: Sign Test for a Class 3 Exterior Soil Survey Unit Refer back to Example 4 for background information. For the Class 3 exterior soil survey unit, the Sign test is again appropriate, because the radionuclide of concern does not appear in background and radionuclide-specific measurements were made. Scenario A is selected.
Table 8.6 shows that the DQOs for this survey unit include  = 0.025 and  = 0.01. The DCGLW is 140 becquerels/kilogram (Bq/kg; 3.8 picocuries/gram [pCi/g]), and the LBGR was selected to be 128 Bq/kg (3.5 pCi/g). The estimated standard deviation of the measurements is  = 4.0 Bqkg (0.11 pCig). The relative shift was calculated to be 3.0, as shown below:
DCGLW  LBGR 140 Bq/kg  128 Bq/kg
                              =                      =                            = 3.0 4.0 Bq/kg Table 5.3 indicates that the sample size estimated for the Sign test, , is 23 ( = 0.025,
    = 0.01, and  = 3). This survey unit is Class 3, so the measurements were made at random locations within the survey unit. The 23 measurements taken on the exterior lawn are shown in the first column of Table 8.9. The mean of these data is 2.1 Bq/kg (0.057 pCi/g),
and the standard deviation is 3.3 Bq/kg (0.089 pCi/g). None of the data exceed 2.1 Bqkg +(3x3.3) Bqkg = 12.0 Bqkg (0.32 pCig). Because  is odd, the median is the middle (12th-highest) value, namely 2.6 Bq/kg (0.070 pCi/g).
An initial review of the data reveals that every data point is below the DCGLW, so the survey unit meets the release criteria specified in Table 8.3. For purely illustrative purposes, the Sign test analysis is performed. The middle column of Table 8.9 contains the quantity DCGLW - Data. Because every data point is below the DCGLW, the sign of DCGLW - Data is always positive. The number of positive differences is equal to the number of measurements,
    , and so the Sign test statistic S+ is 23. The null hypothesis will always be rejected at the maximum value of S+ (which in this case is 23) and the survey unit passes. Thus, the application of the Sign test in such cases requires no calculations and one need not consult a table for a critical value. If the survey is properly designed, the critical value must always be less than .
Notice that some of these measurements are negative (-0.37 in cell A6). This might occur if an analysis background (e.g., the Compton continuum under a spectrum peak) is subtracted to obtain the net concentration value. The data analysis is both easier and more accurate when numerical values are reported as obtained rather than reporting the results as less than or not detected.
1 If one determines that residual radioactive material is definitely present, this would indicate that 2 the survey unit was initially misclassified. Ordinarily, MARSSIM recommends a resurvey using a 3 Class 1 or Class 2 design. In some cases, the original survey may have met the requirements May 2020                                          8-25                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                        MARSSIM 1 for the Class 1 or 2 design. Section 8.6.3 includes additional discussion on the misclassification 2 of survey units.
3 For example, if one determines that the survey unit is a Class 2, a resurvey might be avoided if 4 the survey unit does not exceed the maximum size recommended for such a classification. In 5 this case, the only difference in survey design would be whether the measurements were 6 obtained on a random or on a triangular grid. Provided that the initial surveys scanning 7 methodology has sufficient detection capability to detect areas at the DCGLW, versus the higher 8 DCGLEMC, the scan would be able to compensate for differences in the survey grid sample 9 locations, and those differences alone would not affect the outcome of the statistical analysis.
10 Therefore, if the above conditions were met, a resurvey might not be necessary.
11 Table 8.9: Sign Test Example Data for Class 3 Exterior Survey Unit A                B            C Sample Data          DCGLW-Data Number                                        Sign (Bq/kg)            (Bq/kg) 1          3.0              137.0          +
2          3.0              137.0          +
3          1.9              138.1          +
4          0.37              139.6          +
5        -0.37              140.4          +
6          6.3              133.7          +
7          -3.7              143.7          +
8          2.6              137.4          +
9          3.0              137.0          +
10          -4.1              144.1          +
11          3.0              137.0          +
12          3.7              136.3          +
13          2.6              137.4          +
14          4.4              135.6          +
15          -3.3              143.3          +
16          2.1              137.9          +
17          6.3              133.7          +
18          4.4              135.6          +
19        -0.37              140.4          +
20          4.1              135.9          +
21          -1.1              141.1          +
22          1.1              138.9          +
23          9.3              130.7          +
Number of positive differences S+ =  23 NUREG-1575, Revision 2                          8-26                                    May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                                Interpretation of Survey Results 1 8.4    Radionuclide Present in Background 2 The statistical tests discussed in this section will be used to compare each survey unit with an 3 appropriately chosen, site-specific reference area. Each reference area should be selected on 4 the basis of its similarity to the survey unit, as discussed in Section 4.6.3.
5 8.4.1    Wilcoxon Rank Sum Test and Quantile Test 6 In Scenario A, the comparison of measurements from the reference area and survey unit is 7 made using the WRS test. In Scenario B, in addition to the WRS test, the quantile test should be 8 used to further evaluate survey units when the WRS test fails to reject the null hypothesis. The 9 recommended tests should be conducted for each survey unit. In addition, the EMC is 10 performed against each measurement to ensure that it does not exceed a specified 11 investigation level (e.g., DCGLEMC for Class 1 survey units). If any measurement in the 12 remediated survey unit exceeds the specified investigation level, then additional investigation is 13 recommended, at least locally, regardless of the outcome of the WRS test.
14 The WRS test is most effective when residual radioactive material is uniformly present 15 throughout a survey unit. For Scenario A, the test is designed to detect whether this residual 16 radioactive material exceeds the DCGLW. For Scenario B, it is designed to detect whether this 17 residual radioactive material exceeds the AL.
18 The advantage of the nonparametric WRS test is that it does not assume that the data are 19 normally or lognormally distributed. The WRS test also allows less than measurements to be 20 present in the reference area and the survey units. The WRS test can generally be used with up 21 to 40 percent less than measurements in either the reference area or the survey unit.
22 However, the use of less than values in data reporting is not recommended, as discussed in 23 Sections 2.3.5 and 8.3. When possible, report the actual result of a measurement together with 24 its uncertainty.
25 The quantile test is a statistical test for non-uniformity in the distribution of the residual 26 radioactive material. The quantile test was developed to detect differences between the survey 27 unit and the reference area that consist of a shift to higher values in only a fraction of the survey 28 unit. The quantile test is performed only when Scenario B is used and only if the null hypothesis 29 is not rejected for the WRS test. Using the quantile test in tandem with the WRS test results in 30 higher power to identify survey units that do not meet the release criteria than either test by itself.
31 Using the quantile test in tandem with the WRS test also results in higher probability of Type I 32 errors when the true concentration is equal to the AL. The probability of making a Type I error 33 on at least one of the two tests is approximately  =  +  where  and  are the values 34 of alpha selected for the quantile and WRS tests, respectively. For this reason, when the 35 quantile test is performed in tandem with the WRS test  and  should both be set equal to 36  2 so that when the true concentration is equal to the AL, the probability of a Type I error of 37 the two tests in tandem is approximately .
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Interpretation of Survey Results                                                          MARSSIM 1 In Scenario A, the hypothesis tested by the WRS test is as follows:
2          Null Hypothesis 3          0 : The median concentration of residual radioactive material in the survey unit 4          exceeds that in the reference area by more than the DCGLW.
5          Versus 6          Alternative Hypothesis 7          1 : The median concentration of residual radioactive material in the survey unit 8          exceeds that in the reference area by less than the DCGLW.
9 In Scenario B, the hypothesis tested by the WRS test is as follows:
10          Null Hypothesis 11          0 : The median concentration of residual radioactive material in the survey unit 12          exceeds that in the reference area by less than the AL.
13          Versus 14          Alternative Hypothesis 15          1 : The median concentration of residual radioactive material in the survey unit exceeds 16          that in the reference area by more than the AL.
17 Scenario B is used when the goal of remediation is that residual radioactive material in the survey 18 unit be indistinguishable from background activity levels in the reference area (e.g., AL = 0) or 19 when the AL is below some discrimination level.
20 When the values of  and  are selected in the DQO process, an important difference between 21 Scenario A and Scenario B should be considered. For a fixed value of , a lower value for  is 22 more protective in Scenario A, and a lower value for  is less protective in Scenario B. In both 23 scenarios, a lower value for  requires a higher degree of evidence before the null hypothesis is 24 rejected. In Scenario A, the null hypothesis is that the survey unit exceeds the release criteria, 25 and a lower value for  makes it more difficult to reject this hypothesis. In Scenario B, the null 26 hypothesis is that the survey unit meets the release criteria, and a lower value of  makes it 27 more difficult to reject this hypothesis. An illustration of this effect is shown in Example 8 28 presented in Section 8.4.3.
29 In both scenarios, the null hypothesis is assumed to be true unless the statistical test indicates 30 that it should be rejected in favor of the alternative. One assumes that any difference between 31 the reference area and survey unit concentration distributions is due to a shift in the survey unit 32 concentrations to higher values (i.e., due to the presence of residual radioactive material in 33 addition to background). Note that some or all of the survey unit measurements may be larger 34 than some reference area measurements while still meeting the release criteria. Indeed, some 35 survey unit measurements may exceed some reference area measurements by more than the 36 DCGLW. The result of the hypothesis test determines whether the survey unit as a whole is 37 deemed to meet the release criteria. The EMC is used to screen individual measurements.
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MARSSIM                                                                        Interpretation of Survey Results 1 Two assumptions underlie this test: (1) Samples from the reference area and survey unit are 2 independent, identically distributed random samples, and (2) each measurement is independent 3 of every other measurement, regardless of the set of samples from which it came.
4 8.4.2    Applying the Wilcoxon Rank Sum Test 5 The WRS test is applied as outlined in the following six steps and further illustrated by the examples 6 in Section 8.4.3 and Appendix A. Separate instructions are provided for Scenarios A and B.
7          Scenario A 8          1. Obtain the adjusted reference area measurements,  , by adding the DCGLW to each 9              reference area measurement,  .  =  + DCGLW . The  adjusted reference 10              sample measurements,  , from the reference area and the  sample measurements, 11                , from the survey unit are pooled and ranked in order of increasing size from 1 to ,
12              where  =  + .
13          2. If several measurements are tied (i.e., have the same value), all are assigned the 14              average rank of that group of tied measurements.
15          3. If there are t less than values, all are given the average of the ranks from 1 to t.
16              Therefore, they are all assigned the rank ( + 1)(2) = ( + 1)2, which is the 17              average of the first t integers. If there is more than one detection limit, all observations 18              below the largest detection limit should be treated as less than values. 5 19          4. Sum the ranks of the adjusted measurements from the reference area,  . Note that 20              because the sum of the first  integers is ( + 1)2, one can equivalently sum the 21              ranks of the measurements from the survey unit,  , and compute  =
22              ( + 1)2  .
23          5. Compare  with the critical value given in Table I.5 for the appropriate values of ,
24              , and . If  is greater than the tabulated value, reject the hypothesis that the 25              survey unit exceeds the release criteria.
26          Scenario B 27          1. Obtain the adjusted survey unit measurements,  , by subtracting the AL from each 28              survey unit measurement,  .  =  AL.
5 If more than 40 percent of the data from either the reference area or survey unit are less than, the WRS test cannot be used. Such a large proportion of non-detects suggest that the DQO process be revisited for this survey to determine if the survey unit was properly classified or the appropriate measurement method was used. As stated previously, the use of less than values in data reporting is not recommended. Wherever possible, the actual result of a measurement, together with its uncertainty, should be reported.
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Interpretation of Survey Results                                                            MARSSIM 1        2. The  adjusted sample measurements,  , from the survey unit and the  reference 2            measurements,  , from the reference area are pooled and ranked in order of 3            increasing size from 1 to , where  =  + . (Note: When using Table I.5 for 4            Scenario B, the roles of  and  are reversed.)
5        3. If several measurements are tied (i.e., have the same value), all are assigned the 6            average rank of that group of tied measurements.
7        4. If there are t less than values, they are all given the average of the ranks from 1 to 8            t. Therefore, all are assigned the rank ( + 1)(2) = ( + 1)2, which is the 9            average of the first t integers. If there is more than one detection limit, all 10            observations below the largest detection limit should be treated as less than values.
11        5. Sum the ranks of the adjusted measurements from the survey unit,  . Note that 12            because the sum of the first  integers is ( + 1)2, one can equivalently sum the 13            ranks of the measurements from the reference area,  , and compute  =
14            ( + 1)2  .
15        6. Compare  with the critical value given in Table I.5 for the appropriate values of ,
16            , and . (Because the quantile test is used in addition to the WRS test,  2 should 17            be used rather than .) If  is greater than the tabulated value, reject the null 18            hypothesis that the survey unit does not exceed the release criteria.
19 Example 7 illustrates the WRS test in practice for a Class 2 interior drywall survey unit.
Example 7: Wilcoxon Rank Sum Test Example: Class 2 Interior Drywall Survey Unit Refer to Example 4 for background information. In this example, the gas-flow proportional counter measures gross beta activity (see Appendix H), and the measurements are not radionuclide-specific. The Wilcoxon Rank Sum (WRS) test is appropriate for the Class 2 interior drywall survey unit because background contributes to gross beta activity even though the radionuclide of interest does not appear in background. Scenario A is selected because the derived concentration guideline level using the WRS test (DCGLW) is higher than the discrimination limit. As a result, the quantile test will not be needed for this example.
Table 8.6 shows that the data quality objectives (DQOs) for this survey unit include  = 0.025 and  = 0.05. The DCGLW is 8,300 becquerels/square meter (Bq/m2; 5,000 decays per minute [dpm]/100 square centimeters [cm2]) and the lower bound of the gray region (LBGR) was selected to be 5,000 Bqm2 3,000 dpm/100 cm2 . The estimated standard deviation, ,
of the measurements is about 830 Bq/m2 (500 dpm/100 cm2). The relative shift was calculated to be 4.0, as shown below:
DCGLW - LBGR 8,300 Bqm2 - 5,000 Bqm2
                            =                    =                                = 4.0 830 Bqm2 NUREG-1575, Revision 2                            8-30                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                              Interpretation of Survey Results In Table 5.2, one finds that the number of measurements estimated for the WRS test is 11 in each survey unit and 11 in each reference area ( = 0.025,  = 0.05, and  = 4).
(Table I.3 in Appendix I also lists the number of measurements estimated for the WRS test.)
Table 8.10 lists the data obtained from the gas-flow proportional counter in units of counts per minute (cpm). A reading of 160 cpm with this instrument corresponds to the DCGLW of 8,300 Bq/m2 (5,000 dpm/100 cm2). Column A lists the measurement results as they were obtained. The sample mean and sample standard deviation of the reference area measurements are 44 and 4.4 cpm, respectively. The sample mean and sample standard deviation of the survey unit measurements are 98 and 5.3 cpm, respectively. In column B, the code R denotes a reference area measurement, and S denotes a survey unit measurement. Column C contains the Adjusted Data. The Adjusted Data are obtained by adding the DCGLW to the reference area measurements (see Section 8.4.2, Step 1). The ranks of the adjusted data appear in Column D. They range from 1 to 22, because there is a total of 11+11 measurements (see Section 8.4.2, Step 2).
Note that two cases of measurements tied with the same value, at 104 and 205. Each tied measurement is always assigned the average of the ranks. Therefore, both measurements at 104 are assigned rank (9 + 10)/2 = 9.5 (see Section 8.4.2, Step 3). Also note that the sum of all of the ranks is still 22(22 + 1)/2 = 253. Checking this value with the formula in Step 5 of Section 8.4.2 is recommended to guard against errors in the rankings.
Column E contains only the ranks belonging to the reference area measurements. The total is 187. This is compared with the entry for the critical value of 156 in Table I.5 for  = 0.025, with  = 11 and  = 11. Because the sum of the reference area ranks is greater than the critical value, the null hypothesis (i.e., that the mean survey unit concentration exceeds the DCGLW) is rejected.
If some of the values of the survey unit had been higher and had ranked above some of the reference unit samples, then the sum of the reference values would have been lower (because the survey values are not counted and would have displaced downward reference values). This then moves the sum closer to the critical value. If enough survey sample ranks had displaced reference rankings, then the sum would have been below the critical value and the null hypothesis would be accepted.
1 Table 8.10: WRS Test for Class 2 Interior Drywall Survey Unit in Example 7 A              B              C        D            E Sample Data (cpm)      Unit or Area    Adjusted    Ranks    Reference Number Data                Area Ranks 1            49              R            209        22          22 2            35              R            195        12          12 3            45              R            205        17.5        17.5 4            45              R            205        17.5        17.5 May 2020                                            8-31                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                              MARSSIM A                B                C        D            E Sample Data (cpm)    Unit or Area        Adjusted  Ranks      Reference Number Data              Area Ranks 5          41                R              201        14          14 6          44                R              204        16          16 7          48                R              208        21          21 8          37                R              197        13          13 9          46                R              206        19          19 10          42                R              202        15          15 11          47                R              207        20          20 12          104                S              104      9.5          0 13          94                S                94        4          0 14          98                S                98        6          0 15          99                S                99        7          0 16          90                S                90        1          0 17          104                S              104      9.5          0 18          95                S                95        5          0 19          105                S              105        11          0 20          93                S                93        3          0 21          101                S              101        8          0 22          92                S                92        2          0 Sum =                        253        187 1 Abbreviation: cpm = counts per minute.
2 8.4.3  Applying the Quantile TestUsed Only in Scenario B 3 The quantile test was developed to detect differences between the survey unit and the 4 reference area that consist of a shift to higher values in only a fraction of the survey units. It 5 should be noted that, in general, this shift is not necessarily the same as the shift used for the 6 WRS test. The quantile test is better at detecting situations in which only a portion of the survey 7 unit contains excess residual radioactive material. The WRS test is better at detecting situations 8 in which any excess residual radioactive material is uniform across the entire survey unit. The 9 quantile test is used only in Scenario B. The quantile test is performed after the WRS test, if the 10 null hypothesis for the WRS test has not been rejected. Using the quantile test in tandem with 11 the WRS test in Scenario B results in higher power to detect survey units that have not been 12 adequately remediated than either test has by itself.
13 The quantile test is outlined in the six steps below:
14 1. Calculate  . ( =  2).
15 2. Obtain the adjusted survey unit measurements,  , by subtracting the AL from each survey 16    unit measurement,  :  =  AL. If the DCGLW is equal to zero, then this step is not 17    necessary.
18 3. The  adjusted survey unit measurements,  , and the  reference area measurements,  ,
19    are pooled and ranked in order of increasing size from 1 to , where  =  + .
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MARSSIM                                                                Interpretation of Survey Results 1 4. If several measurements are tied (i.e., have the same value), all are assigned the mean rank 2      of that group of tied measurements.
3 5. Look up the values for r and k in Tables I.7-I.10 to be based on the number of measurements 4      in the survey unit (), the number of measurements in the reference area (), and  . The 5      operational decision described in the next step is made using the values for r and k.
6 6. If k or more of the r largest measurements in the combined ranked data set are from the 7      survey unit, the null hypothesis is rejected.
8 Examples 8-10 illustrate how certain tests can be used under a variety of testing scenarios.
Example 8: Class 2 Interior Survey Example Under Scenario B Using Wilcoxon Rank Sum and Quantile Tests Refer to Example 4 for background information. The data for an example Wilcoxon Rank Sum (WRS) test using Scenario B are shown in Column A of Table 8.11. In Column B, the label R is inserted to denote a reference area measurement, and the label S to denote a survey unit measurement. Column C contains the adjusted data obtained by subtracting the lower bound of the gray region (LBGR) of 142 counts per minute (cpm) from just the survey unit measurements (the reference area measurements are not adjusted). The ranks of the adjusted data in Column C are listed in Column D. The ranks range from 1 to 24, because there are 12 + 12 = 24 measurements. The sum of all the ranks is ( + 1)/2 = (24x25)/2 =
300. Column E contains only the ranks belonging to the adjusted survey unit measurements.
The sum of the ranks of the adjusted survey unit data is 194.5. From Table I.5, for  = 0.025 and  =  = 12, the critical value is 184. Because the sum of the adjusted survey unit ranks, 194.5, is greater than the critical value, 184, the null hypothesis that the survey unit concentrations do not exceed the LBGR is rejected (i.e., the site is determined to be dirty). In Scenario B, the true concentration of radioactive material in the survey unit is judged to be in excess of 142 cpm above the background.
For the quantile test, Table I.8 provides the critical value, , of the largest r measurements for different values of , the number of measurements from the survey unit, and , the number of measurements from the reference area. The same rankings in Column D of Table 8.11 for the WRS test can be used for the quantile test. If  or more of the r largest measurements in the combined ranked data set are from the survey unit, the null hypothesis is rejected. For a survey unit that has failed the WRS test, as was the case in this example, it is not usually necessary to also perform the quantile test. However, the quantile test is presented for illustrative purposes.
In Table 8.11, Columns F and G show the sorted ranks of the adjusted data and the location associated with each rank (i.e., R for reference area and S for survey unit). In Table I.8, the closest entry to  =  = 12 is for  =  = 10. The values of r = 7, k = 6 and  = 0.029 are found. Thus, the null hypothesis is rejected if six of the seven largest adjusted measurements May 2020                                          8-33                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                                      MARSSIM come from the survey unit. From Table 8.11, we find that only five of the seven largest adjusted measurements come from the survey unit, so the null hypothesis is not rejected based on the quantile test. The values of  and  that were used are close to, but not equal to, the actual values so the  value will be different from that listed in the table. It is prudent to check a few other entries in Table I.8 that are near the actual sample size. Additionally, Chapter 7 in NUREG-1505 (NRC 1998a) provides equations to calculate exact and approximate values of the alpha error for the quantile test as a function of , , k, and r.
1 Table 8.11: WRS and Quantile Test Under Scenario B for Class 2 Interior Drywall Survey 2 Unit in Example 8 A            B          C            D          E            F            G Location Sample Data                  Adjusted                  Survey      Sorted      Associated Number                      Area                  Ranks (cpm)                      Data                  Unit Ranks    Ranks      with Sorted Ranksa 1          47            R          47          18                        1            R 2          28            R          28            1                        2            R 3          36            R          36            6                        3            R 4          37            R          37            7                      4.5            R 5          39            R          39          9.5                      4.5            S 6          45            R          45          13                        6            R 7          43            R          43          11                        7            R 8          34            R          34            3                        8            S 9          32            R          32            2                      9.5            R 10          35            R          35          4.5                      9.5            R 11          39            R          39          9.5                      11            R 12          51            R          51          21                      13            R 13        209            S          67          24          24          13            S 14        197            S          55          23          23          13            S 15        188            S          46          16          16          16            S 16        191            S          49          19          19          16            S 17        193            S          51          21          21          16            S 18        187            S          45          13          13          18            R 19        188            S          46          16          16          19            S 20        180            S          38            8            8          21            R 21        193            S          51          21          21          21            S 22        188            S          46          16          16          21            S 23        187            S          45          13          13          23            S 24        177            S          35          4.5          4.5          24            S Sum =        300        194.5 3 a Measurements from the reference area and the survey unit are denoted by R and S, respectively. The adjusted data 4 and data columns are identical when AL= 0.
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MARSSIM                                                              Interpretation of Survey Results Example 9: Example Using NUREG-1505 Kruskall-Wallis Test to Determine Whether Appropriate to Consider Variability from Background under Scenario B NUREG-1505 (NRC 1998a) provides guidance on methods used to demonstrate indistinguishability from background when Scenario B is deemed appropriate to use (e.g., when the DCGL is close to background considering variability). A difficulty arises in the ability to release a site when variations in mean background among the potential reference areas become comparable in magnitude to the width of the gray region. Because any difference in radioactivity between the reference area and survey unit is assumed to be due to residual radioactivity, and it is not possible to determine if the difference is actually due to differences in background concentrations between the two areas, tests are available to determine the significance of background variability and how this variability can be considered in the statistical tests used to help determine if the site is clean.
The parametric F-test (assumes a normal distribution) and nonparametric Kruskall-Wallis test (does not make an assumption regarding the underlying distribution) can be used to determine if variability between the means of potential reference areas is statistically significant. See data in Table 8.12 used to determine ranks of reference area measurements used to perform the Kruskall-Wallis test. NUREG-1505 Equation 13-3 is used to calculate a Kruskal-Wallis statistic:
12          2
                                  =                3 ( + 1)
( + 1)     
                                                    =1 where N is the total number of measurements in all the reference areas i=1 to k reference areas;  is the number of measurements in a given reference area; and  is the sum of the ranks of the measurements in a given reference area.
The test statistic of 14.0 is compared to the critical values provided in NUREG-1505 Table 13.1. In the example, the Kruskall Wallis statistic of 14.0 is above the critical threshold for 4 - 1=3 reference areas that range from 11.3 for an  value of 0.01 to 4.6 for an  value of 0.2. Therefore, the null hypothesis that the variability in the reference area means is zero can be rejected with high confidence (i.e., the null hypothesis is rejected even for very small  or false positive error rates). Although the Kruskall-Wallis test (or F-test) is used to determine if it is appropriate to consider reference area variability in applying Scenario B, NUREG-1505 also indicates that background variability could be given the benefit of the doubt, in which case the Kruskal-Wallis test (or F-test) need not be conducted.
If it is determined that the variability between reference means should be considered, NUREG-1505 Equation 13-13 can be used to calculate the variance,          2 , which can be used to determine the lower bound of the gray region (LBGR, or action level [AL]) for Scenario B.
NUREG-1505 provides an example where the mean square between reference areas,  2 ,
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Interpretation of Survey Results                                                                        MARSSIM and mean square within reference areas,  2 , calculated manually using Equation 13-13 or output from ANOVA testing can be used to compute            2 = ( 2  2 )0 , where 0 is equal to the number of measurements per reference area when the number of measurements in each reference area is the same (or see Equation 13-13 in NUREG-1505 when the number of measurements in the reference areas are not the same). Using the ANOVA output in Table 8.13, 2  2 6.52  0.97 2 =
                                                      =            = 0.55 0          10 As part of the data quality objective process, an agreed-upon value for the LBGR as a multiple of can be selected (e.g., NUREG-1505 states that 3            is a reasonable default [or in the example 55 x 3 = 0.74 x 3 = 2.22 for the LBGR]). Note that the difference in means between reference areas 2 and 4 in Table 13.2 is 1.82, which is similar to the LBGR calculated based on 3 . NUREG-1505, Table 13.5 also provides information on the power of the F-test, which is used to approximate the power of the Kruskal-Wallis test, to help determine the number of references areas and the number of measurements that should be taken in each reference area to perform the Kruskal-Wallis test and to estimate                . In all cases, the regulatory authority should be consulted to determine the acceptability of using Scenario B, as well as determining appropriate values for the test parameters.
1 Table 8.12: Calculation of    for Example 9 Measurements                    Measurement Ranks              Measurements Squared Sample Area  Area Area        Area      Area Area Area Area              Area Area Area Area Number 1      2      3        4          1    2      3        4          1          2      3      4 1      0.27  1.04  2.45      3.77          6    13    27      39      0.07        1.08  6.00 14.21 2      1.87  0.39  0.34      2.63        20    9      8      31      3.50        0.15  0.12    6.92 3      0.97  2.07  3.06      4.05        10    23    37      40      0.94        4.28  9.36 16.40 4      1.01  0.57  2.83      1.72        11    2    35      19      1.02        0.32  8.01    2.96 5      2.08  1.97  1.09      1.50        24    21    14      17      4.33        3.88  1.19    2.25 6      1.62  0.22  0.26      2.47        18    3      5      29      2.62        0.05  0.07    6.10 7      0.30  1.39  2.80      1.42          7    15    34      16      0.09        1.93  7.84    2.02 8      1.98  0.05  2.77      2.47        22    4    33      28      3.92        0.00  7.67    6.10 9      2.18  0.75  2.42      2.76        25    1    26      32      4.75        0.56  5.86    7.62 10      1.02  2.50  2.86      3.35        12    30    36      38      1.04        6.25  8.18 11.22 Sum        13.30  7.87 20.88      26.14                                  22.28 18.50 54.30 75.80 Average    1.33  0.79  2.09      2.61 Average 1.77  0.62  4.36      6.83 Squared 2 Table 8.13: Analysis of Variance for Example 9 Data Source of              Sum of            Degrees of        Mean        F Statistic Variation              Squares            Freedom        Square Between Groups          19.56                    3          6.52            6.69 Within Groups          35.08                  36          0.97 NUREG-1575, Revision 2                                8-36                                              May 2020 DRAFT FOR PUBLIC COMMENT                                                          DO NOT CITE OR QUOTE
 
MARSSIM                                                              Interpretation of Survey Results Source of              Sum of        Degrees of      Mean      F Statistic Variation              Squares        Freedom        Square Total                    54.65            39 1
Example 10: Class 1 Interior Concrete Survey Unit As in the previous example, the gas-flow proportional counter measures gross beta activity (see Appendix H) and the measurements are not radionuclide-specific. The nonparametric statistical test for when the radionuclide is present in background is appropriate for the Class 1 interior concrete survey unit because gross beta activity contributes to the overall background, even though the specific radionuclide of interest does not appear in background.
Appendix A provides a detailed description of the calculations for the Class 1 interior concrete survey unit.
2 8.4.4  Multiple Radionuclides 3 The use of the unity rule when there is more than one radionuclide to be considered is 4 discussed in Section 4.4. An example application of the use of the unity rule appears in 5 Examples 11 and 12.
Example 11: Application of WRS Test to Multiple Radionuclides Consider a site with both cobalt-60 (60Co) and cesium-137 (137Cs) contamination. 137Cs appears in background from fallout at a typical concentration of about 37 becquerels/kilogram (Bq/kg; 1 picocurie/gram [pCi/g]). Assume that the DCGLW for 60Co is 74 Bq/kg (2 pCi/g) and for 137Cs is 52 Bq/kg (1.4 pCi/g). In disturbed areas, the background concentration of 137Cs can vary considerably. An estimated spatial standard deviation of 19 Bq/kg (0.5 pCi/g) for 137 Cs will be assumed. During remediation, it was found that the concentrations of the two radionuclides were not well correlated in the survey unit. 60Co concentrations were more variable than the 137Cs concentrations, and 26 Bq/kg (0.7 pCi/g) is estimated for its standard deviation. Measurement errors for both 60Co and 137Cs using gamma spectrometry will be small compared to this. For the comparison to the release criteria, the weighted sum of the concentrations of these radionuclides is computed from 60                  137 Co concentration      Cs concentration
                              =    60
                                                      +      137 Co DCGL                Cs DCGL 60                    137 Co concentration      Cs concentration
                                =                    +
74 Bq/kg                52 Bq/kg May 2020                                        8-37                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                        MARSSIM The variance of the weighted sum, assuming that the 60Co and 137Cs concentrations are spatially unrelated, is 2                            2 60                          137 Co concentration          Cs concentration 2 () =        60
                                                        +        137 Co DCGL                      Cs DCGL 26 Bq/kg 2    19 Bq/kg 2
                              =            +          = 0.26 74 Bq/kg      52 Bq/kg Thus,  = 0.5. The wide-area derived concentration guideline level (DCGLW) for the weighted sum is 1. The null hypothesis for Scenario A is that the survey unit exceeds the release criterion. During the data quality objective process, the lower bound of the gray region (LBGR) was set at 0.5 for the weighted sum, so that  = DCGLW - LBGR =1.0 -0.5 = 0.5, and
  / = 0.5/0.5 = 1.0. The acceptable error rates chosen were  =  = 0.05. To achieve this, 32 samples each are required in the survey unit and the reference area.
The weighted sums are computed for each measurement location in both the reference area and the survey unit. The WRS test is then performed on the weighted sum. The calculations for this example are shown in Table 8.14. The DCGLW for the unity rule (i.e., 1.0) is added to the weighted sum for each location in the reference area. The ranks of the combined survey unit and adjusted reference area weighted sums are then computed. The sum of the ranks of the adjusted reference area weighted sums is then compared to the critical value for  =
    = 32,  = 0.05, which is 1,162 (see formula following Table I.5). In Table 8.14, the sum of the ranks of the adjusted reference area weighted sums is 1,281. This exceeds the critical value, so the null hypothesis is rejected. In Scenario A, this means the survey unit meets the release criteria. The difference between the mean of the weighted sums in the survey unit and the reference area is 1.86 - 1.16 = 0.7. Thus, the estimated dose or risk due to residual radioactive material in the survey unit is approximately equal to 70 percent of the release criterion.
1 Example 12: Use of ProUCL for the WRS Test for Multiple Radionuclides As Table 8.14 does for Example 11, Table 8.15 provides sample results for a survey unit with residual radioactive material that includes cobalt-60 (60Co) and cesium-137 (137Cs).
Because 137Cs from fallout is found in the background, samples were also collected and analyzed from a reference area. The wide-area derived concentration guideline levels (DCGLW) for 137Cs and 60Co are 1.4 and 2.0 Bq/kg, respectively. The unity rule is used to determine if the survey unit meets the release criteria. Scenario A was selected. To perform the WRS test, ProUCL, Version 5.0 was used. ProUCL is a freeware statistical software program, provided by the U.S. Environmental Protection Agency.
The data can be entered by hand or copied and pasted from another software program.
Descriptions can be provided for the column headers by right-clicking the column header and selecting Header Name. For this example, the columns were named Reference and NUREG-1575, Revision 2                            8-38                                  May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                              Interpretation of Survey Results Survey Unit. Figure 8.4 shows the initial program inputs of the weighted sums of the reference area and survey unit with their column headings.
To perform the WRS test, the two-sample Wilcoxon-Mann-Whitney test was selected. The Wilcoxon-Mann-Whitney test is a nonparametric of the same hypothesis as the WRS test.
The two tests use a different test statistic and critical value, but both tests will provide the same conclusion. The test can be selected by first choosing Two Sample from the Hypothesis Testing menu, and then selecting Wilcoxon-Mann-Whitney.
Variables are selected by clicking on the variable name in the list of variables, and then clicking the corresponding >> button. The Reference Area results are selected as the Background/Ambient variable, and the Survey Unit results are selected as the Area of Concern/Site variable, as shown in Figure 8.5.
Clicking the Options in the dialog window shown in Figure 8.5, generates another dialog window. This window allows the user to specify the Confidence Coefficient. The confidence coefficient is equal to (1  ) . For this example, the Confidence Coefficient of 95 percent is selected, corresponding to  = 0.05. The dialog window also allows the user to specify the form of the hypothesis. For this example, Form 2 is selected, and the value of 1 is entered for the Substantial Difference. When using Form 2, the unadjusted reference area results should be used instead of the adjusted reference area results.
Clicking the OK button shown in Figure 8.6 saves the changes and closes the dialog window. Clicking the OK button shown in Figure 8.5 closes that dialog window and generates the output sheet shown in Figure 8.7. As shown near the bottom of Figure 8.7, the null hypothesis is rejected, and the survey unit is demonstrated to pass the statistical test.
The elevated measurement comparison would still need to be performed before deciding that the survey unit has met the release criteria.
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Interpretation of Survey Results                                                MARSSIM 1 Table 8.14: Example 11 WRS Test for Two Radionuclides Sample Reference Area        Survey Unit          Weighted Sum            Ranks Number      137 Cs  60 Co  137 Cs    60 Co      Ref    Survey  Adj Ref Survey Adj Ref 1        2.00      0    1.12      0.06    1.43    0.83    2.43      1      56 2        1.23      0    1.66      1.99    0.88    2.18    1.88    43      21 3        0.99      0    3.02      0.56    0.71    2.44    1.71    57      14 4        1.98      0    2.47      0.26    1.41    1.89    2.41    23      55 5        1.78      0    2.08      0.21    1.27    1.59    2.27      9      50 6        1.93      0    2.96      0.00    1.38    2.11    2.38    37      54 7        1.73      0    2.05      0.20    1.23    1.56    2.23      7      46 8        1.83      0    2.41      0.00    1.30    1.72    2.30    16      52 9        1.27      0    1.74      0.00    0.91    1.24    1.91      2      24 10        0.74      0    2.65      0.16    0.53    1.97    1.53    27        6 11        1.17      0    1.92      0.63    0.83    1.68    1.83    13      18 12        1.51      0    1.91      0.69    1.08    1.71    2.08    15      32 13        2.25      0    3.06      0.13    1.61    2.25    2.61    47      63 14        1.36      0    2.18      0.98    0.97    2.05    1.97    30      28 15        2.05      0    2.08      1.26    1.46    2.12    2.46    39      58 16        1.61      0    2.30      1.16    1.15    2.22    2.15    45      41 17        1.29      0    2.20      0.00    0.92    1.57    1.92      8      25 18        1.55      0    3.11      0.50    1.11    2.47    2.11    59      35 19        1.82      0    2.31      0.00    1.30    1.65    2.30    11      51 20        1.17      0    2.82      0.41    0.84    2.22    1.84    44      19 21        1.76      0    1.81      1.18    1.26    1.88    2.26    22      48 22        2.21      0    2.71      0.17    1.58    2.02    2.58    29      62 23        2.35      0    1.89      0.00    1.68    1.35    2.68      3      64 24        1.51      0    2.12      0.34    1.08    1.68    2.08    12      33 25        0.66      0    2.59      0.14    0.47    1.92    1.47    26        5 26        1.56      0    1.75      0.71    1.12    1.60    2.12    10      38 27        1.93      0    2.35      0.85    1.38    2.10    2.38    34      53 28        2.15      0    2.28      0.87    1.54    2.06    2.54    31      61 29        2.07      0    2.56      0.56    1.48    2.11    2.48    36      60 30        1.77      0    2.50      0.00    1.27    1.78    2.27    17      49 31        1.19      0    1.79      0.30    0.85    1.43    1.85      4      20 32        1.57      0    2.55      0.70    1.12    2.17    2.12    42      40 Avg        1.62      0    2.28      0.47    1.16    1.86    2.16  sum =    sum =
Std Dev      0.43      0    0.46      0.48    0.31    0.36    0.31    799      1281 NUREG-1575, Revision 2                      8-40                                May 2020 DRAFT FOR PUBLIC COMMENT                                          DO NOT CITE OR QUOTE
 
MARSSIM                                                  Interpretation of Survey Results 1 Table 8.15: Example 12 WRS Test for Two Radionuclides Reference Area                                                      Adjusted Sample                          Survey Unit (Bq/kg) Reference      Survey Results (Bq/kg)                                                    Reference Number                                              Area ( )  Unit ( )
137 Cs      60 Co    137 Cs      60 Co                                Area ( )
1        2.00      0.00      1.12        0.06    1.429          0.830        2.429 2        1.23      0.00      1.66        1.99    0.879          2.181        1.879 3        0.99      0.00      3.02        0.56    0.707          2.437        1.707 4        1.98      0.00      2.47        0.26    1.414          1.894        2.414 5        1.78      0.00      2.08        0.21    1.271          1.591        2.271 6        1.93      0.00      2.96        0.00    1.379          2.114        2.379 7        1.73      0.00      2.05        0.20    1.236          1.564        2.236 8        1.83      0.00      2.41        0.00    1.307          1.721        2.307 9        1.27      0.00      1.74        0.00    0.907          1.243        1.907 10        0.74      0.00      2.65        0.16    0.529          1.973        1.529 11        1.17      0.00      1.92        0.63    0.836          1.686        1.836 12        1.51      0.00      1.91        0.69    1.079          1.709        2.079 13        2.25      0.00      3.06        0.13    1.607          2.251        2.607 14        1.36      0.00      2.18        0.98    0.971          2.047        1.971 15        2.05      0.00      2.08        1.26    1.464          2.116        2.464 16        1.61      0.00      2.30        1.16    1.150          2.223        2.150 17        1.29      0.00      2.20        0.00    0.921          1.571        1.921 18        1.55      0.00      3.11        0.50    1.107          2.471        2.107 19        1.82      0.00      2.31        0.00    1.300          1.650        2.300 20        1.17      0.00      2.82        0.41    0.836          2.219        1.836 21        1.76      0.00      1.81        1.18    1.257          1.883        2.257 22        2.21      0.00      2.71        0.17    1.579          2.021        2.579 23        2.35      0.00      1.89        0.00    1.679          1.350        2.679 24        1.51      0.00      2.12        0.34    1.079          1.684        2.079 25        0.66      0.00      2.59        0.14    0.471          1.920        1.471 26        1.56      0.00      1.75        0.71    1.114          1.605        2.114 27        1.93      0.00      2.35        0.85    1.379          2.104        2.379 28        2.15      0.00      2.28        0.87    1.536          2.064        2.536 29        2.07      0.00      2.56        0.56    1.479          2.109        2.479 30        1.77      0.00      2.50        0.00    1.264          1.786        2.264 31        1.19      0.00      1.79        0.30    0.850          1.429        1.850 32        1.57      0.00      2.55        0.70    1.121          2.171        2.121 2
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Interpretation of Survey Results                                            MARSSIM 1
2 Figure 8.4: ProUCL Worksheet for Example 12 3
4 Figure 8.5: ProUCL Select Variables Window for Hypothesis Testing for Example 12 NUREG-1575, Revision 2                  8-42                                May 2020 DRAFT FOR PUBLIC COMMENT                                    DO NOT CITE OR QUOTE
 
MARSSIM                                                  Interpretation of Survey Results 1
2 Figure 8.6: ProUCL Hypothesis Testing Options Window for Example 12 May 2020                                8-43                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                      DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                        MARSSIM 1
2 Figure 8.7: ProUCL Output for Example 12 3 8.5    Scan-Only Surveys 4 The use of the UCL can apply to both Scenario A and B for scan-only surveys where individual 5 results are recorded. When release decisions are made about the estimated mean of a sampled 6 population, the assessment of the survey results is accomplished by comparing a UCL for the 7 mean to the DCGLW or DL for Scenarios A and B, respectively.
8 If individual scan-only survey results are recorded, a nonparametric confidence interval can be 9 used to evaluate the results of the release survey. Similarly, a confidence interval can be used 10 to evaluate a series of direct measurements with overlapping fields of view. A one-tailed version 11 of Chebyshevs inequality or software (e.g., EPAs ProUCL software) can be used to evaluate 12 the probability of exceeding the UBGR (i.e., using a UCL). The use of a UCL applies to both 13 Scenario A (where the UBGR equals the DCGLW) and Scenario B (where the UBGR equals the 14 DL).
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MARSSIM                                                                Interpretation of Survey Results 1 Chebyshevs inequality calculates the probability that the absolute value of the difference of the 2 true but unknown mean of the population and a random number from the data set is at least a 3 specified value. That is, given a specified positive number (), a mean (), and a random 4 number from the data set (), then the probability that [  ] is greater than or equal to  is 5 equal to . In addition, a one-tailed version of the inequality can be used to calculate a UCL for 6 a data set that is independent of the data distribution (i.e., there is no requirement to verify the 7 data are from a normal, lognormal, or any other specified kind of distribution) by letting the 8 inequality equal the UCL. The UCL can be calculated using Equation 8-3:
2  2                                  (8-3 UCL =  +
9 The comparison to the UCL is described in the following steps:
10      1. Calculate the mean () and standard deviation () of the number of results () in the 11          data set.
12      2. For Scenario A, retrieve the Type I error rate () used to design the survey. For 13          Scenario B, substitute the Type II error rate () used to design the survey for  in 14          Equation 8-3.
15      3. Using Chebyshevs inequality, calculate the maximum UCL using Equation 8-3.
16 If the maximum UCL is less than the UBGR, the survey demonstrates compliance with the 17 disposition criterion (i.e., reject the null hypothesis for Scenario A or fail to reject the null 18 hypothesis for Scenario B).
19 Chebyshevs inequality must be used with caution when there are very few points in the data 20 set. This is because the population mean and standard deviation in the Chebyshev formula are 21 being estimated by the sample mean and sample standard deviation. In a small data set from a 22 highly skewed distribution, the sample mean and sample standard deviation may be 23 underestimated if the high concentration but low probability portion of the distribution is not 24 captured in the sample data set.
25 8.6    Evaluate the Results: The Decision 26 When the data and the results of the tests have been obtained, the specific steps required to 27 achieve survey unit release depend on the procedures instituted by the governing regulatory 28 agencies and site-specific ALARA 6 considerations. The following suggested considerations are 6 as low as reasonably achievable May 2020                                          8-45                      NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                            MARSSIM 1 for the interpretation of the test results with respect to the release limit established for the site or 2 survey unit. Note that the tests need not be performed in any particular order.
3 8.6.1    Elevated Measurement Comparison 4 If applicable release criteria for elevated measurements exist, then the EMC consists of 5 comparing each measurement from the survey unit with the investigation levels discussed in 6 Section 5.3.8. The EMC is performed both for measurements obtained on the systematic 7 sampling grid and for locations flagged by scanning measurements. Any measurement from the 8 survey unit that is equal to or greater than an investigation level indicates an area of relatively 9 high concentrations that should be investigated, regardless of the outcome of the nonparametric 10 statistical tests.
11 Under Scenario A, the statistical tests may reject the null hypothesis when only a very few high 12 measurements are obtained in the survey unit, regardless of how high the measurements are.
13 In a similar manner, under Scenario B, the statistical tests might not reject the null hypothesis 14 when only a few high measurements are obtained in the survey unit. The use of the quantile test 15 and the EMC against the investigation levels may be viewed as assurance that unusually large 16 measurements will receive proper attention regardless of the outcome of those tests and that 17 any area having the potential for significant dose or risk contributions will be identified. The EMC 18 is intended to flag potential failures in the remediation process. This should not be considered 19 the primary means to identify whether a survey unit meets the release criteria.
20 Note that the DCGLEMC is an a priori limit, established both by the DCGLW and by the survey 21 design (i.e., grid spacing and scanning MDC). The true extent of an area of elevated activity can 22 be determined only after performing the survey and taking additional measurements. Upon the 23 completion of further investigation, the a posteriori limit can be established. The area of elevated 24 activity is generally bordered by concentration measurements below the DCGLW. An individual 25 elevated measurement on a systematic grid could conceivably represent an area four times as 26 large as the systematic grid area used to define the DCGLEMC. This is the area bounded by the 27 nearest neighbors of the elevated measurement location. The results of the investigation should 28 show that the appropriate DCGLEMC is not exceeded. If measurements above the stated 29 scanning MDC are found by sampling or by direct measurements at locations that were not 30 flagged during the scanning survey, then this may indicate the scanning method does not meet 31 the DQOs.
32 The preceding discussion primarily concerns Class 1 survey units. Measurements exceeding 33 the DCGLW in Class 2 or Class 3 areas may indicate survey unit misclassification. Scanning 34 coverage for Class 2 and Class 3 survey units is less stringent than for Class 1. If the 35 investigation levels of Section 5.3.8 are exceeded, an investigation should (1) ensure that the 36 area of elevated activity discovered meets the release criteria, and (2) provide reasonable 37 assurance that other undiscovered areas of elevated activity do not exist. If further investigation 38 determines that the survey unit was misclassified with regard to potential for residual radioactive 39 material, then a resurvey using the method appropriate for the new survey unit classification is 40 appropriate.
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MARSSIM                                                                Interpretation of Survey Results 1 8.6.2    Interpretation of Statistical Test Results 2 The result of the statistical test is the decision to reject or not to reject the null hypothesis.
3 Provided that the results of investigations triggered by the EMC were resolved, a rejection of the 4 null hypothesis leads to the decision that the survey unit meets the release criteria in 5 Scenario A. In Scenario B, failure to reject the null hypothesis in both the WRS and quantile 6 tests leads to the decision that the survey unit meets the release criteria, provided that EMC 7 results are acceptable. However, estimating the mean concentration of residual radioactive 8 material in the survey unit may also be necessary so that dose or risk calculations can be made.
9 This estimate is designated by . The mean concentration is generally the best estimator for .
10 However, only the unbiased measurements from the statistically designed survey should be 11 used in the calculation of .
12 If residual radioactive material is found in an isolated area of elevated activityin addition to 13 residual radioactive material distributed relatively uniformly across the survey unitthe unity 14 rule (Section 4.4) can be used to ensure that the total dose is within the release criteria, as 15 shown in Equation 8-4:
(mean concentration in elevated area  )
                                  +                                                1                (8-4)
DCGLW                        DCGLEMC 16 If there is more than one elevated area, a separate term could be included in Equation 8-4 for 17 each area. The use of the unity rule for more than one elevated area may imply that a person is 18 centered on each area of elevated radioactive material and exposed simultaneously. This is an 19 impossible situation and represents a very cautious exposure scenario. If there are multiple 20 elevated areas, then alternative approaches may be considered:
21 1. The MARSSIM user could determine the elevated area (primary area) that contributes the 22      most to the total dose or risk. As shown by Abelquist (2008), the doses from elevated areas 23      other than the primary area can be very small and might be negligible.
24 2. The dose or risk due to the actual residual radioactive material distribution could be 25      calculated if an appropriate exposure pathway model is available.
26 Other approaches for handling elevated concentrations of radioactive material may be utilized 27 and should be coordinated with the regulator.
28 The MARSSIM user should consult with the responsible regulatory agency for guidance on an 29 acceptable approach to address the dose or risk from elevated areas of residual radioactive 30 material. Note that these approaches generally apply only to Class 1 survey units, because 31 areas of elevated activity above the DCGLW should not exist in Class 2 or Class 3 survey units.
32 A retrospective power analysis for the test will often be useful, especially when the null 33 hypothesis is not rejected (see Appendix M). When the null hypothesis is not rejected, it may 34 be because it is true, or it may be because the test did not have sufficient power to detect that it May 2020                                          8-47                        NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                                    DO NOT CITE OR QUOTE
 
Interpretation of Survey Results                                                            MARSSIM 1 is not true. The power of the test will be primarily affected by changes in the actual number of 2 measurements obtained and their standard deviation. An effective survey design will slightly 3 overestimate both the number of measurements and the standard deviation to ensure adequate 4 power. This ensures that a survey unit is not subjected to additional remediation simply because 5 the FSS is not sensitive enough to detect that residual radioactive material is below the DCGLW.
6 When the null hypothesis is rejected in Scenario A, the power of the test becomes a somewhat 7 moot question. Nonetheless, even in this case, a retrospective power curve can be a useful 8 diagnostic tool and an aid to designing future surveys and for other survey units at the site.
9 When the null hypothesis is accepted in Scenario B, the power of the test is of particular 10 importance. If an insufficient number of samples are collected, the null hypothesis that the 11 survey unit meets the release criteria may be accepted simply because of the lack of sufficient 12 power to detect residual radioactive material in the survey unit above the release criteria. If the 13 retrospective power analysis reveals a lack of sufficient power, it may be necessary to revisit the 14 DQO process with the updated estimate of .
15 8.6.3    If the Survey Unit Fails 16 The systematic planning process included in MARSSIM should include planning for possible 17 survey unit failure. Early discussions with appropriate regulatory personnel about what actions 18 can and should be taken if the survey unit fails may prevent long delays later in the project.
19 However, if the survey unit fails in a way that is not anticipated, agreed upon actions may not be 20 applicable, and discussions will need to take place to address the unanticipated results.
21 The information provided in MARSSIM is fairly explicit concerning the steps that should be 22 taken to show that a survey unit meets the release criteria. Less has been said about the 23 procedures that should be used if the survey unit fails at any point. This is primarily because 24 there are many different ways that a survey unit may fail the FSS. The mean concentration of 25 residual radioactive material may not pass the nonparametric statistical tests. Further 26 investigation following the elevated measurement comparison may show a large enough area 27 with a concentration too high to meet the release criteria. Investigation levels may have caused 28 locations to be flagged during scanning that indicate unexpected levels of residual radioactive 29 material for the survey unit classification. Site-specific information is needed to fully evaluate all 30 of the possible reasons for failures, their causes, and their remedies.
31 When a survey unit fails to demonstrate compliance with the release criteria, the first step is to 32 review and confirm the data that led to the decision. Once this is done, the DQO process 33 (Appendix D) can be used to identify and evaluate potential solutions to the problem. The 34 concentration of residual radioactive material in the survey unit should be determined to help 35 define the problem. Once the problem has been stated, the decision concerning the survey unit 36 should be developed into a decision rule. Next, determine the additional data, if any, that are 37 needed to document that the survey unit demonstrates compliance with the release criteria.
38 Alternatives to resolving the decision statement should be developed for each survey unit that 39 fails the tests. These alternatives are evaluated against the DQOs, and a survey design that 40 meets the objectives of the project is selected. Example 13 discusses a Class 2 survey unit with 41 measurements exceeding the DCGLW.
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MARSSIM                                                              Interpretation of Survey Results Example 13: Class 2 Survey Unit with Measurements Exceeding the DCGLW A Class 2 survey unit passes the nonparametric statistical tests but has several measurements on the sampling grid that exceed the derived concentration guideline level determined using the Wilcoxon Rank Sum test (DCGLW). This is unexpected in a Class 2 area, so these measurements are flagged for further investigation. Additional sampling confirms several areas where the concentration exceeds the DCGLW. This indicates that the survey unit was misclassified. However, the scanning technique that was used was sufficient to detect concentrations of residual radioactive material at the derived concentration guideline level determined using the elevated measurement comparison (DCGLEMC) calculated for the sample grid. No areas exceeding the DCGLEMC were found. Thus, the only difference between the performed final status survey (FSS) and the required FSS for a Class 1 area is that the scanning may not have covered 100 percent of the survey unit area. In this case, one might simply increase the scan coverage to 100 percent. Reasons the survey unit was misclassified should be noted. If no areas exceeding the DCGLEMC are found, the survey unit essentially demonstrates compliance with the release criteria as a Class 1 survey unit.
If a Class 2 survey unit has been misclassified as a Class 1 survey unit, the size of the survey unit should be considered to determine if the survey unit should be divided into two or more smaller survey units, based on the recommended survey sizes in Table 4.1 and the concentration of radioactive material in different areas of the survey unit. If the scanning technique was not sufficiently sensitive, it may be possible to reclassify as Class 1 only that portion of the survey unit containing the higher measurements. This portion would be resampled at the higher measurement density required for a Class 1 survey unit, with the rest of the survey unit remaining as Class 2.
1 Example 14 discusses a Class 1 survey unit with elevated areas.
Example 14: Class 1 Survey Unit with Elevated Areas Consider a Class 1 Survey unit that passes the nonparametric statistical tests and contains some areas that were flagged for investigation during scanning. Further investigation, sampling, and analysis indicate one area is truly elevated. This area has a concentration that exceeds the derived concentration guideline level determined using the Wilcoxon Rank Sum test by a factor greater than the area factor calculated for its actual size. This area is then remediated. Remediation control sampling shows that the residual radioactive material was removed, and no other areas were affected by residual radioactive material. In this case, one may simply document the original final status survey (FSS), the fact that remediation was performed, the results of the remedial action support survey, and the additional remediation data. In some cases, additional FSS data may not be needed to meet the release criteria.
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Interpretation of Survey Results                                                          MARSSIM 1 Example 15 discusses a Class 1 survey unit that fails the statistical test.
Example 15: Class 1 Survey Unit Fails the Statistical Test Consider a Class 1 area that fails the nonparametric statistical tests. Confirmatory data indicate that the mean concentration in the survey unit exceeds the derived concentration guideline level determined using the Wilcoxon Rank Sum test over a majority of its area. This indicates remediation of the entire survey unit is necessary, followed by another final status survey (FSS). Reasons for performing an FSS in a survey unit with significant amounts of residual radioactive material should be noted.
2 Examples 13-15 are meant to illustrate the actions that may be necessary to secure the 3 release of a survey unit that has failed to meet the release criteria. The DQO process should be 4 revisited to plan how to attain the original objective, which is to safely release the survey unit by 5 showing that it meets the release criteria. Whatever data are necessary to meet this objective 6 will be in addition to the FSS data already in hand.
7 8.6.4    Removable Radioactive Material 8 Some regulatory agencies may require that smear samples be taken at indoor grid locations as 9 an indication of removable surface activity. In addition, the percentage of removable activity 10 assumed in the dose modeling can have a large impact on estimated doses. As such, it might 11 be necessary to confirm this assumption regarding the amount of removable contamination.
12 However, measurements of smears are very difficult to interpret quantitatively. In general, the 13 results of smear samples should be used for determining compliance with requirements that 14 specifically require a smear measurement. In addition, they may be used as a diagnostic tool to 15 determine whether further investigation is necessary.
16 8.7    Documentation 17 Documentation of the FSS should provide a complete and unambiguous record of the 18 radiological status of the survey unit relative to the established DCGLs. In addition, sufficient 19 data and information should be provided to enable an independent evaluation of the results of 20 the surveyincluding repeating, when possible, measurements at some future time. The 21 documentation should comply with all applicable regulatory requirements. Additional information 22 on documentation is provided in Chapter 3, Chapter 5, and Appendix D.
23 Much of the information in the final status report will be available from other decommissioning 24 documents. However, to the extent practicable, this report should be a stand-alone document 25 with minimum information incorporated by reference. This document should describe the 26 instrumentation or analytical methods applied, how the data were converted to DCGL units, the 27 process of comparing the results to the DCGLs, and the process of determining that the DQOs 28 were met.
29 The results of actions taken as a consequence of individual measurements or sample 30 concentrations in excess of the investigation levels should be reported with any additional data, NUREG-1575, Revision 2                            8-50                                      May 2020 DRAFT FOR PUBLIC COMMENT                                                  DO NOT CITE OR QUOTE
 
MARSSIM                                                              Interpretation of Survey Results 1 remediation, or resurveys performed to demonstrate that issues concerning potential areas of 2 elevated activity were resolved. The results of the data evaluation using statistical methods to 3 determine whether release criteria were satisfied should be described. If criteria were not met, 4 or if results indicate a need for additional data, appropriate further actions should be determined 5 by the site management in consultation with the responsible regulatory agency. Example 16 6 provides an example of a data interpretation checklist.
Example 16: Example Data Interpretation Checklist Convert Data to Standard Units
_____ Structure activity should be in becquerels/square meter (Bq/m2) (decays per minute
[dpm]/100 square centimeters [cm2]).
_____ Solid media (soil, building surfaces, etc.) activity should be in in Bq/kilogram (kg)
(picocuries/gram [pCi/g]).
Evaluate Elevated Measurements
_____ Identify elevated data.
_____ Compare data with derived elevated area criteria.
_____ Determine need to remediate and/or reinvestigate elevated condition.
_____ Compare data with survey unit classification criteria.
_____ Determine need to investigate and/or reclassify.
Assess Survey Data
_____ Review data quality objectives (DQOs), measurement quality objectives (MQOs), and survey design.
_____ Verify that data of adequate quantity and quality were obtained.
_____ Perform preliminary assessments (graphical methods) for unusual or suspicious trends or resultsinvestigate further as appropriate.
Perform Statistical Tests
_____ Select appropriate tests for the radionuclide.
_____ Conduct tests.
_____ Compare test results against hypotheses.
_____ Confirm power level of tests.
Compare Results to Guidelines
_____ Determine mean or median concentrations.
_____ Confirm that residual activity satisfies guidelines.
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Interpretation of Survey Results                                            MARSSIM Compare Results with DQOs and Measurement Quality Objectives (MQOs)
_____ Determine whether all DQOs and MQOs are satisfied.
_____ Explain/describe deviations from design-basis DQOs/MQOs.
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MARSSIM                                                                              References REFERENCES, U.S. CODE, AND FEDERAL LAWS General References 42 FR 60956, EPA, Persons Exposed to Transuranium Elements in the Environment, Federal Register, Vol. 42, No. 230, November 30, 1977, pp. 60956-60959.
46 FR 52601, NRC, Disposal or On-site Storage of Thorium or Uranium Wastes from Past Operations, Federal Register, Vol. 46, No. 205, October 23, 1981, pp. 52061-52063.
55 FR 51532, EPA, Hazard Ranking System; Final Rule (46 CFR Part 300), Federal Register, Vol. 5, No. 241, December 14, 1990, pp. 51532-51667.
57 FR 13389, NRC, Action Plan to Ensure Timely Cleanup of Site Decommissioning Management Plan Sites (10 CFR Part 30)," Federal Register, Vol. 57, No. 74, April 16, 1992, pp. 13389-13392.
57 FR 6136, NRC, Order Establishing Criteria and Schedule for Decommissioning the Bloomberg Site (10 CFR Part 30), Federal Register, Vol. 57, No. 34, February 20, 1992, pp. 6136-6143.
American Association of Radon Scientists and Technologists (AARST), Protocol for Conducting Measurements of Radon and Radon Decay Products in Homes, AARST, Fletcher, NC, 2014a (MAH-2014).
AARST, Protocol for Conducting Measurements of Radon and Radon Decay Products in Schools and Large Buildings, AARST, Fletcher, NC, 2014b (MALB-2014).
AARST, Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air, AARST, Fletcher, NC, 2015 (MS-PC-2015).
AARST, Protocol for Conducting Measurements of Radon and Radon Decay Products in Multifamily Buildings, AARST, Fletcher, NC, 2017 (MAMF-2017).
AARST, Radon Measurement Systems Quality Assurance, AARST, Fletcher, NC, 2019 (MS-QA-2019).
Abelquist, E., Dose Modeling and Statistical Assessment of Hot Spots for Decommissioning Applications, Ph.D. Dissertation, University of Tennessee, Knoxville, TN, 2008.
Abelquist, E., Decommissioning Health Physics, A Handbook for MARSSIM Users, Taylor &
Francis Group, New York, NY, 2010.
Abelquist, E., Decommissioning Health Physics, A Handbook for MARSSIM Users, Second Edition, Taylor and Francis Group, Boca Raton, FL, 2014.
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References                                                                              MARSSIM Adams, T.L., Jr., Entry and Continued Access Under CERCLA, Memorandum to Regional Administrators I-X and Regional Counsels I-X from Assistant Administrator, Office of Environment and Compliance Monitoring, EPA, June 5, 1987, PB91-138867.
Altshuler, B. and B. Pasternak, Statistical Measures of the Lower Limit of Detection of a Radioactivity Counter, Health Physics, 9:293-298, 1963.
Ames, L.L. and D. Rai, Radionuclide Interactions with Soil and Rock Media, Office of Radiation Programs, EPA, Las Vegas, NV,1978 (EPA 520/78-007A).
Angus, J.E., Bootstrap One-Sided Confidence Intervals for the Log-Normal Mean, The Statistician, 43(3): 395-401, 1994.
ANS (American Nuclear Society), Mobile In Situ Gamma-Ray Spectroscopy System, Transactions of the American Nuclear Society, 70:47, 1994a.
ANS, Large Area Proportional Counter for In Situ Transuranic Measurements, Transactions of the American Nuclear Society, 70:47, 1994b.
ANSI (American National Standards Institute), American National Standard Performance Specifications for Health Physics Instrumentation - Portable Instrumentation for Use in Extreme Environmental Conditions, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, March 28, 1990 (ANSI N42.17C).
ANSI, American National Calibration and Usage of Thallium-Activated Sodium Iodide Detector Systems for Assay of Radionuclides, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, January 26, 1995 (ANSI N42.12-1994).
ANSI, Performance Criteria for Radiobioassay, American National Standards Institute, Washington, DC, May 1, 1996 (ANSI/HPS N13.30).
ANSI, Radiation Protection Instrumentation Test and Calibration - Portable Survey Instruments, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, December 31, 1997 (N323A-1997).
ANSI, Institute of Electrical and Electronics Engineers, Inc. Standard Test Procedures and Bases for Geiger Mueller Counters, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, June 4, 1999 (IEEE 309-1999/ANSI N42.3-1999).
ANSI, American National Standard Performance Specifications for Health Physics InstrumentationPortable Instrumentation for Use in Normal Environmental Conditions, IEEE, Piscataway, NJ, April 29, 2004 (N42.17A-2003).
ANSI, American National Standard for Radiation Instrumentation Test and Calibration, Portable Survey Instruments, IEEE, New York, NY, 2013 (N323AB-2013.)
ANSI, American National Standard Performance Criteria for Handheld Instruments for the Detection and Identification of Radionuclides, IEEE, New York, NY, August 24, 2016 (N42.34-2015).APHA (American Public Health Association), Standard Methods for the NUREG-1575, Revision 2                          Ref-2                                  May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                                              References Examination of Water and Wastewater, 22nd Edition, APHA, Washington, DC, 2012.ASME (American Society of Mechanical Engineers), Quality Assurance Program Requirements for Nuclear Facilities, NQA-1, ASME, New York, NY, 1989.
ASQC (American Society for Quality Control), Specifications and Guidelines for Quality Systems for Environmental Data Collection and Environmental Technology Programs, ANSI/ASQ E4-1994, ASQC, Milwaukee, WI, 1995.
ASTM (American Society of Testing and Materials,) Standard Guide for Conducting Ruggedness Tests, ASTM E1169-2002, ASTM, West Conshohocken, PA, 2002.
ASTM Standard Practice for Reducing Samples of Aggregate to Testing Size, ASTM C702-98, ASTM, West Conshohocken, PA, 2003.
ASTM, Standard Practice for Soil Sample Preparation for the Determination of Radionuclides, ASTM C999-90 (2010) e1, ASTM, West Conshohocken, PA, 2010.
ASTM, Annual Book of ASTM Standards, Water and Environmental Technology, Volume 11.05, Environmental Assessment; Hazardous Substances and Oil Spill Responses; Waste Management; Environmental Risk Assessment, ASTM, West Conshohocken, PA, 2012.
ATSDR (Agency for Toxic Substances and Disease Registry), Public Health Assessment Guidance Manual (Update), ATSDR, Atlanta, GA, 2005.
Bailey, E.N., Lessons Learned from Independent Verification Activities (DCN 0476-TR-02-0)
Oak Ridge Institute of Science and Education, Oak Ridge, TN, 2008.
Bernabee, R., D. Percival, and D. Martin, Fractionation of Radionuclides in Liquid Samples from Nuclear Power Facilities, Health Physics, 39:57-67, 1980.
Berven, B.A., W.D. Cottrell, R.W. Leggett, C.A. Little, T.E. Myrick, W.A. Goldsmith, and F.F.
Haywood, Generic Radiological Characterization Protocol for Surveys Conducted for DOE Remedial Action Programs, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, 1986, Report No. ORNL/TM-7850 (DE86-011747).
Berven, B.A., W.D. Cottrell, R.W. Leggett, C.A. Little, T.E. Myrick, W.A. Goldsmith, and F.F.
Haywood. Procedures Manual for the ORNL Radiological Survey Activities (RASA)
Program, Oak Ridge National Laboratory, Oak Ridge, TN, 1987, Report No. ORNL/TM-8600 (DE87-009089).
Bickel P.J. and K.A. Doksum, Mathematical Statistics: Basic Ideas and Selected Topics, Holden-Day, San Francisco, CA, 1977.
Box, G.P., and G.C. Tiao, Bayesian Inference in Statistical Analysis, John Wiley and Sons, Inc.,
Hoboken, NJ, 2011.
Brodsky, A., Exact Calculation of Probabilities of False Positives and False Negatives for Low Background Counting, Health Physics, 63(2):198-204, 1992.
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References                                                                              MARSSIM Chen, L., Testing the Mean of Skewed Distributions, Journal of the American Statistical Association, 90: 767, 1995.
Chen, Z., Z. Bai, and B. Sinha, Ranked Set Sampling: Theory and Applications. Series: Lecture Notes in Statistics, Vol. 176, Springer-Verlag, New York, NY, 2004.
Cheng, J.-J., B. Kassas, C. Yu, D. LePoire, J. Arnish, E.S. Dovel, S.Y. Cehn, A.W. Williams, A.
Wallo, and H. Petersen. RESRAD-RECYCLE: A Computer Model for Analyzing the Radiological Doses and Risks Resulting from the Recycling of Radioactive Scrap Metal and the Reuse of Surface-Contaminated Material and Equipment, ANL/EAD-3, Argonne National Laboratory, Argonne, IL, 2000.
Committee on the Biological Effects of Ionizing Radiations (BEIR), National Research Council, Health Effects of Exposure to Low Levels of Ionizing Radiation: BEIR V, National Academies Press, Washington, DC, 1990.
Conover, W.J., Practical Nonparametric Statistics, Second Edition, John Wiley & Sons, New York, NY, 1980.
Currie, L.A., Limits for Qualitative Detection and Quantitative Determination, Analytical Chemistry, 40(3):586-693, 1968.
Davidson, J.R., ELIPGRID-PC: Upgraded Version, Oak Ridge National Laboratory, Oak Ridge, TN, 1995 (ORNL/TM-13103).
Dawson, J., 2011, Public Comment, MARSSIM Workgroup Meeting, Washington, D.C., May 2011.
DeGroot, M.H., Optimal Statistical Decisions, John Wiley & Sons, Inc., Hoboken, New Jersey, 2005.
DoD (Department of Defense), Environment, Safety, and Occupational Health, DoD Directive 4715.1E, DoD, Washington, DC, 2005.
DoD, Environmental Compliance at Installations Outside the United States, DoD Instruction 4715.05, Incorporating Change 2 DoD, Washington, DC, 2018.
DoD, Integrated Recycling and Solid Waste Management, DoD Instruction 4715.23, DoD, Washington, DC, 2016.
DoD, Occupational Medical Examinations and Surveillance Manual, Incorporating Change 3, DoD 6055.05-M, DoD, Washington, DC, 2018.
DoD, Quality Program Requirements, Military Specification MIL-Q-9858A, Washington, DC, 1963.
Department of the Air Force, Environmental Baseline Surveys in Real Estate Transactions, AFI 32-7066, Air Force, Washington, DC, 2015.
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MARSSIM                                                                            References Department of the Air Force, The Environmental Restoration Program, Incorporating Change 1, AFI 32-7020, Air Force, Washington, DC, 2016.
Department of the Air Force, Radioactive Materials (RAM) Management, AFMAN 40-201, Air Force, Washington, DC, 2019.
Department of the Army, Handling, Storage and Disposal of Army Aircraft Components Containing Radioactive Materials, TB 43-0108, Army, Washington, DC, 1979.
Department of the Army, Occupational and Environmental Health: Control of Health Hazards from Protective Material Used in Self-Luminous Devices, TB MED 522, Army, Washington, DC, 1980.
Department of the Army, Control of Hazards to Health from Ionizing Radiation Used by the Army Medical Department, TB MED 525, Army, Washington, DC, 1988a.
Department of the Army, Handling and Disposal of Unwanted Radioactive Material, TM 3-261, Army, Washington, DC, 1988b.
Department of the Army, Identification of U.S. Army Communications-Electronics Command Managed Radioactive Items in the Army Supply System, TB 43-0122, Army, Washington, DC, 1989a.
Department of the Army, Transportability Guidance for Safe Transport of Radioactive Materials, TM 55-315, Army, Washington, DC, 1989b.
Department of the Army, Safety and Hazard Warnings for Operation and Maintenance of TACOM Equipment, TB 43-0216, Army, Washington, DC, 1990.Department of the Army, USAEHA Environmental Sampling Guide, Technical Guide No. 155, U.S. Army Environmental Hygiene Agency, Aberdeen Proving Ground, MD, 1993.
Department of the Army, Identification of Radioactive Items in the Army, TB 43-0116, Army, Washington, DC, 1998.
Department of the Army, Management of Equipment Contaminated with Depleted Uranium or Radioactive Commodities, AR 700-48, Army, Washington, DC, 2002a.
Department of the Army, Occupational and Environmental Health: Management and Control of Diagnostic, Therapeutic, and Medical Research X-Ray Systems and Facilities, TB MED 521, Army, Washington, DC, 2002b.
Department of the Army, Instructions for Safe Handling, Maintenance, Storage and Transportation of Radioactive Items under License 12-00722-06, TB 43-0197, Army, Washington, DC, 2006.
Department of the Army, Environmental Protection and Enhancement, AR 200-1, Army, Washington, DC, 2007a.
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References                                                                          MARSSIM Department of the Army, Health Hazard Assessment Program in Support of the Army Acquisition Process, AR 40-10, Army, Washington, DC, 2007b.
Department of the Army, Preventive Medicine, AR 40-5, Army, Washington, DC, 2007c.
Department of the Army, Occupational Dosimetry and Dose Recording for Exposure to Ionizing Radiation, DA PAM 385-25, Army, Washington, DC, 2012.
Department of the Army, Army Test, Measurement, and Diagnostic Equipment, AR 750-43, Army, Washington, DC, 2014.
Department of the Army, The Army Radiation Safety Program, DA PAM 385-24, Army, Washington, DC, 2015.
Department of the Army, The Army Safety Program, AR 385-10, Army, Washington, DC, 2017.
Department of the Army, Calibration and Repair Requirements for the Maintenance of Army Materiel, TB 43-180, Army, Washington, DC, 2018.
Department of the Navy, Initial Management of Irradiated or Radioactively Contaminated Personnel, BUMEDINST 6470.10B, Navy, Washington, DC 2003.
Department of the Navy, Radiological Affairs Support Program, NAVSEA 5100-18B, Navy, Washington, DC, 2007.
Department of the Navy, Navy Radiation Safety Committee, OPNAVINST 6470.3, Navy, Washington, DC, 2015.
Department of the Navy, Radiation Health Protection Manual, Incorporating Change 1, NAVMED P-5055, Navy, Washington, DC, 2018a.
Department of the Navy, Radioactive Commodities in the Department of Defense Supply System, NAVSUPINST 4000.34C, Navy, Washington, DC, 2018b.
DOE (Department of Energy), Radiological and Environmental Sciences Laboratory Procedures, Analytical Chemistry Branch Procedures Manual, DOE/IDO-12096, DOE, Idaho Operations Office, Idaho Falls, ID, 1982.
DOE, Formerly Utilized Sites Remedial Action Program, Verification and Certification Protocol Supplement No. 2 to the FUSRAP Summary Protocol, Revision 1, Division of Facility and Site Decommissioning Projects, Office of Nuclear Energy, DOE, Washington, DC, 1985.
DOE, Formerly Utilized Sites Remedial Action Program, Designation/Elimination Protocol Supplement No. 1 to the FUSRAP Summary Protocol, DOE, Division of Facility and Site Decommissioning Projects, Office of Nuclear Energy, Washington, DC, 1986a.
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MARSSIM                                                                            References DOE, Formerly Utilized Sites Remedial Action Program, Summary Protocol, Identification Characterization Designation - Remedial Action - Certification, DOE, Division of Facility and Site Decommissioning Projects, Office of Nuclear Energy, Washington, DC, 1986b.
DOE, The Environmental Survey Manual, Appendix A - Criteria for Data Evaluation, DOE/EH-0053, DOE, Office of Environmental Audit, Washington, DC, 1987 (DE88-000254).
DOE, Environmental Protection, Safety, and Health Protection Information Reporting Requirements, DOE Order 5484.1, Change 7, Washington, DC, 1990.
DOE, Hanford Past-Practice Strategy, DOE/RL-91-40, Washington, DC, 1991.
DOE, Environmental Implementation Guide for Radiological Survey Procedures Manual, DOE Report for Comment, Martin Marietta Energy Systems, Oak Ridge National Laboratory, Oak Ridge, TN, 1992.
DOE, Decommissioning Handbook, DOE/EM-0142P, DOE, Washington, DC, 1994a (DE94-008981).
DOE, DOE Methods for Evaluating Environmental and Waste Management Samples, DOE/EM-0089T, Rev. 2, Prepared for the U.S. Department of Energy by Pacific Northwest Laboratory, Richland, WA, 1994b.
DOE, Statistical and Cost-Benefit Enhancements to the DQO Process for Characterization Decisions, DOE/EM-0316, DOE, Washington, DC, 1996.
DOE, The Procedures Manual of the Environmental Measurements Laboratory, Volume I, 28th Edition, HASL-300, Environmental Measurements Laboratory, DOE, New York, NY, 1997 (DE91-010178).
DOE, Radioactive Waste Management, DOE O 435.1, DOE, Washington, DC 1999.
DOE, Adaptive Sampling and Analysis Programs (ASAPs), DOE/EM-0592, DOE, Washington, DC 2001.
DOE, Use of Institutional Controls, DOE P 454.1, DOE, Washington, DC 2003.
DOE, Institutional Controls Implementation Guide for Use with DOE P 454.1, Use of Institutional Controls, DOE G 454.1-1, DOE, Washington, DC 2005.
DOE, Derived Concentration Technical Standard, DOE-STD-1196-2011, DOE, Washington, DC 2011a.
DOE, Quality Assurance, DOE O 414.1D, DOE, Washington, DC, 2011b.
DOE, Radiation Protection of the Public and the Environment, DOE O 458.1, DOE, Washington, DC, 2011c.
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References                                                                          MARSSIM DOE, Optimizing Radiation Protection of the Public and the Environment for use with DOE O 458.1, ALARA Requirements, DOE HDBK-1215-2014, DOE, Washington, DC 2014.
DOE, Environmental Radiological Effluent Monitoring and Environmental Surveillance, DOE-HDBK-1216-2015, DOE, Washington, DC 2015.
DOE, A Graded Approach for Evaluating Radiation Doses to Aquatic and Terrestrial Biota, DOE STD-1153-2019, DOE, Washington, DC 2019.
DOE, EPA (U.S. Environmental Protection Agency), and DOD, Guidance on Accelerating CERCLA Environmental Restoration at Federal Facilities, Memorandum from S.A.
Herman, E.P. Laws, T.P. Grumbly, and S.W. Goodman to Addresses, Washington, DC, August 22, 1994 Egan, J.P., Signal Detection Theory and ROC Analysis, Academic Press, Inc., New York, NY, 1975.
Eisenbud, M., Environmental Radioactivity, 3rd Ed., Academic Press, Inc., New York, NY. 1987.
EPA, Methods for Chemical Analysis of Water and Wastes (Revised), Office of Technology Transfer, EPA, Washington, DC, 1974 (EPA 625/6-74-003).
EPA, Development and Application of a Risk Assessment Method for Radioactive Waste Management, Office of Radiation Programs, EPA, Washington DC, 1978 (EPA 520/6-78-007).
EPA, Radiochemical Analytical Procedures for Analysis of Environmental Samples, Office of Radiation and Indoor Air, EPA, Las Vegas, NV, 1979 (EMSL-LV-0539-17).
EPA, Interim Guidelines and Specifications for Preparing Quality Assurance Project Plans, Office of Monitoring Systems and Quality Assurance, EPA, Washington, DC, 1980a (QAMS-005/80).
EPA, Prescribed Procedures for Measurement of Radioactivity in Drinking Water, Environmental Monitoring and Support Laboratory, EPA, Cincinnati, OH, 1980b (EPA-600/4-80-032, PB80-224744).
EPA, Samplers and Sampling Procedures for Hazardous Waste Streams, Municipal Environmental Research Laboratory, EPA, Cincinnati, OH, 1980c (EPA-600/2-80-018, PB80-135353).
EPA, Upgrading Environmental Radiation Data, Health Physics Society Committee Report HPSR-1, Office of Radiation Programs, EPA, Washington, DC, 1980d (EPA 520/1        012, PB81-100364).
EPA, Handbook for Sampling and Sample Preservation of Water and Wastewater, Environmental Monitoring and Support Laboratory, Cincinnati, OH, 1982 (EPA 600/4        029, PB83-124503).
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MARSSIM                                                                              References EPA, Interim Guidelines and Specifications for Preparing Quality Assurance Project Plans, Office of Monitoring Systems and Quality Assurance, EPA, Washington, DC, 1983 (EPA-600/4-83-004, PB83-170514).
EPA, Eastern Environmental Radiation Facility: Radiochemical Procedures Manual, Office of Radiation Programs, Eastern Environmental Radiation Facility, EPA, Montgomery, AL, 1984a (EPA 520/5-84-006, PB84-215581).
EPA, Soil Sampling Quality Assurance Users Guide, Environmental Monitoring Systems Laboratory, EPA, Las Vegas, NV, 1984b (EPA 600/4-84-0043, PB84-198621).
EPA, Preliminary Assessment Petition, Office of Emergency and Remedial Response, EPA, Washington, DC, 1986, Publication 9200.5-301FS.
EPA, A Compendium of Superfund Field Operations Methods, Office of Emergency and Remedial Response, EPA, Washington, DC, 1987a (EPA 540/P-87-001, PB88-181557).
EPA, Data Quality Objectives for Remedial Response Activities-Development Process, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1987b (EPA/540/G-87/003, OSWER Directive 9355.07B, PB88-131370).
EPA, Data Quality Objectives for Remedial Response Activities-Example Scenario: RI/FS Activities at a Site with Contaminated Soils and Groundwater, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1987c (EPA/540/G-87/004, OSWER Directive 9355.07B, PB88-131388).
EPA, Field Screening Methods Catalog - Users Guide, Office of Emergency and Remedial Response, EPA, Washington, DC, 1988a (EPA 540/2-88-005, PB89-134159).
EPA, Guidance for Conducting Remedial Investigations and Feasibility Studies Under CERCLA: Interim Final, Office of Emergency and Remedial Response, EPA, Washington, DC, 1988b (EPA/540/G-89/004, OSWER Directive 9355.3-01, PB 89-184626).
EPA, Background Information Document: Procedures Approved for Demonstrating Compliance with 40 CFR Part 61, Subpart I, Office of Radiation Programs, EPA, Washington, DC, 1989a (EPA/520/1-89-001).
EPA, Methods for Evaluating the Attainment of Cleanup Standards, Volume 1: Soils and Solid Media, Office of Policy, Planning, and Evaluation, EPA, Washington, DC, 1989b (EPA-230/02-89-042, PB89-234959).
EPA, Procedures for Completion and Deletion of National Priorities List Sites and (Update):
Final Report, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1989c (OSWER Directive 9320.2-03B, (PB90-274556).
EPA, Risk Assessment Guidance for Superfund- Part A, EPA, Washington, DC, 1989d (EPA/540/1-89/002).
May 2020                                      Ref-9                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
References                                                                          MARSSIM EPA, A Rationale for the Assessment of Errors in the Sampling of Soils, Environmental Monitoring Systems Laboratory, EPA, Las Vegas, NV, 1990 (EPA 600/4-90/013).
EPA, Compendium of ERT Ground Water Sampling Procedures, Office of Emergency and Remedial Response, EPA, Washington, DC, 1991a (EPA 540/P-91-007, PB91-921275/CCE).
EPA, Compendium of ERT Soil Sampling and Surface Geophysics Procedures, Office of Emergency and Remedial Response, EPA, Washington, DC, 1991b (EPA 540/P-91-006, PB91-921273/CCE).
EPA, Compendium of ERT Surface Water and Sediment Sampling Procedures, Office of Emergency and Remedial Response, EPA, Washington, DC, 1991c (EPA 540/P-91-005, PB91-921274/CCE).
EPA, Description and Sampling of Contaminated Soils, Office of Research and Development, EPA, Washington, DC, 1991d (EPA 625/12-91-002).
EPA, Guidance for Performing Preliminary Assessments under CERCLA, Office of Emergency and Remedial Response, EPA, Washington, DC, 1991e (EPA/540/G-91/013, PB92-963303).
EPA, Risk Assessment Guidance for Superfund. Volume 1, Human Health Evaluation Manual -
Part B, Development of Risk Based Preliminary Remediation Goals, Interim Report, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1991f (EPA/540/R-92/003, OSWER 9285.7-01B, PB92-963333).
EPA, Site Assessment Information Directory, Office of Emergency and Remedial Response, EPA, Washington, DC, 1991g.
EPA, Guidance for Data Usability in Risk Assessment, Part A, Office of Emergency and Remedial Response, EPA, Washington, DC, 1992a (OSWER Directive 9285.7-09A, PB92-963356).
EPA, Guidance for Data Usability in Risk Assessment, Part B, Office of Emergency and Remedial Response, EPA, Washington, DC, 1992b (OSWER Directive 9285.7-09B, PB92-963362).
EPA, Guidance for Performing Site Inspections Under CERCLA, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1992c (EPA/540-R-92-021).
EPA, Guidance on Implementation of the Superfund Accelerated Cleanup Model (SACM) under CERCLA and the NCP, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1992d (OSWER Directive 9203.1-03).
EPA, Indoor Radon and Radon Decay Product Measurement Device Protocols, Office of Air and Radiation, EPA, Washington, DC, 1992e (EPA 402-R-92-004).
NUREG-1575, Revision 2                      Ref-10                                  May 2020 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
MARSSIM                                                                            References EPA, RCRA Groundwater Monitoring: Draft Technical Guidance, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1992f (EPA/530-R-93-001, PB93-139350).
EPA, Supplemental Guidance to RAGS: Calculating the Concentration Term, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1992g (Publication 9285.7-081, PB92-963373).
EPA, The Hazard Ranking System Guidance Manual; Interim Final, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1992h (NTIS PB92-963377, EPA 9345.1-07).
EPA, Description and Sampling of Contaminated Soils: A Field Pocket Guide, Center for Environmental Research Information, EPA, Cincinnati, OH, 1993a (EPA/625/12-91/00).
EPA, Integrating Removal and Remedial Site Assessment Investigations, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1993b (OSWER Directive 9345.1-16FS, PB93-963341).
EPA, Protocols for Radon and Radon Decay Product Measurements in Homes, Office of Air and Radiation, EPA, Washington, DC, 1993c (EPA 402-R-93-003).
EPA, Quality Assurance for Superfund Environmental Data Collection Activities, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1993d (Publication 9200.2-16FS).
EPA, Subsurface Characterization and Monitoring Techniques: A Desk Reference Guide, Volume 1, Office of Research and Development, EPA, Washington, DC, 1993f (EPA/625/R-93/003A, PB94-136272).
EPA, Methods for Monitoring Pump-and-Treat Performance, Office of Research and Development, EPA, Washington, DC, 1994a (EPA/600/R-94/123).
EPA, Statistical Methods for Evaluating the Attainment of Cleanup Standards, Volume 3:
Reference Based Standards for Soils and Solid Media, Office of Policy, Planning, and Evaluation, EPA, Washington, DC, 1994b (EPA 230-R-94-004, PB94-176831).
EPA, Superfund Program Representative Sampling Guidance, Interim Final, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1995 (OSWER Directive 9360.4-10, EPA 540/R-95/14).
EPA, Soil Screening Guidance: Technical Background Document, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1996a (EPA/540/R-95/128, PB96-963502).
EPA, Soil Screening Guidance: Users Guide, Office of Emergency and Remedial Response, EPA, Washington, DC, 1996b (EPA/540/R-96/018).
May 2020                                    Ref-11                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
References                                                                            MARSSIM EPA, Superfund Removal Procedures, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 1996c (OSWER Directive 9360.3-04).
EPA, Understanding Variation in Partition Coefficient, Kd, Values, Volume I - Kd Model, Measurement Methods, and Application of Chemical Reaction Codes, Office of Radiation and Indoor Air, EPA, Washington, DC, 1999a (EPA 402-R-99-004A).
EPA, Understanding Variation in Partition Coefficient, Kd, Values Volume II - Geochemistry and Available Kd Values for Selected Inorganic Contaminants, Office of Radiation and Indoor Air, EPA, Washington, DC, 1999b (EPA 402-R-99-004B).
EPA, Soil Screening Guidance for Radionuclides: Technical Background Document, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 2000a (EPA/540/R        006, PB2000-96330).
EPA, Soil Screening Guidance for Radionuclides: Users Guide, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 2000b (EPA/540/R-00-007, PB2000-963307).
EPA, Decision Error Feasibility Trials Software (DEFT)-Users Guide, Office of Environmental Information, EPA, Washington, DC, 2001a (EPA/240/B-01/007, EPA QA/G-4D).
EPA, EPA Requirements for Quality Assurance Project Plans, Office of Environmental Information, EPA, Washington, DC, 2001b (EPA/240/B-01/003, EPA QA/R-5).
EPA, EPA Guidance for Quality Assurance Project Plans (Final), Office of Research and Development, EPA, Washington, DC, 2002a (EPA QA/G-5).
EPA, Guidance for the Data Verification and Data Validation, Office of Environmental Information, EPA, Washington, DC, 2002b (EPA/240/R-02/004, EPA QA/G-8).
EPA, Supplemental Guidance for Developing Soil Screening Levels for Superfund Sites, Office of Solid Waste and Emergency Response, EPA, Washington, DC, 2002c (OSWER 9355.4-24).
EPA, Understanding Variation in Partition Coefficient, Kd, Values Volume III - Review of Geochemistry and Available Kd Values for Americium, Arsenic, Curium, Iodine, Neptunium, Radium, and Technetium, Office of Radiation and Indoor Air, EPA, Washington, DC, 2004 (EPA 402-R-99-004C).
EPA, Intergovernmental Data Quality Task Force, Uniform Federal Policy for Implementing Environmental Quality Systems - Evaluating, Assessing, and Documenting Environmental Data Collection/Use and Technology Programs (Final), Office of Solid Waste and Emergency Response, EPA, Washington, DC, 2005a (EPA-505-F-03-00).
EPA, Intergovernmental Data Quality Task Force, Uniform Federal Policy for Quality Assurance Project Plans - Evaluating, Assessing, and Documenting Environmental Data Collection and Use Programs - Part 1: UFP-QAPP Manual (Final), Office of Solid Waste and Emergency Response, EPA, Washington, DC, 2005b (EPA-505-B-04-900A).
NUREG-1575, Revision 2                        Ref-12                                  May 2020 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
MARSSIM                                                                              References EPA, Intergovernmental Data Quality Task Force, Uniform Federal Policy for Quality Assurance Project Plans - Evaluating, Assessing, and Documenting Environmental Data Collection and Use Programs - Part 2B: Quality Assurance/Quality Control Compendium: Minimum QA/QC Activities (Final), Office of Solid Waste and Emergency Response, EPA, Washington, DC, 2005c (EPA-505-B-04-900B).
EPA, Intergovernmental Data Quality Task Force, Workbook for Uniform Federal Policy for Quality Assurance Project Plans - Evaluating, Assessing, and Documenting Environmental Data Collection and Use Programs - Part 2A: UFP-QAPP Workbook (Final), Office of Solid Waste and Emergency Response, EPA, Washington, DC, 2005d (EPA-505-B-04-900B).
EPA, Use of Dynamic Work Strategies Under a Triad Approach for Site Assessment and CleanupTechnology Bulletin, Office of Solid Waste and Emergency, EPA, Washington, DC, 2005e (EPA 542-F-05-008).
EPA, Data Quality Assessment: A Reviewers Guide, Office of Environmental Information, EPA, Washington, DC, 2006a (EPA QA/G-9R, EPA/240/B-06/002).
EPA, Data Quality Assessment: Statistical Methods for Practitioners, Office of Environmental Information, EPA, Washington, DC, 2006b (EPA QA/G-9S, EPA/240/B-06/003).
EPA, Guidance for Systematic Planning Using the Data Quality Objectives Process, Office of Environmental Information, EPA, Washington, DC, 2006c (EPA/240/B-06/001, EPA QA/G-4).
EPA, Inventory of Radiological Methodologies for Sites Contaminated with Radioactive Materials, Office of Radiation and Indoor Air, EPA, Washington, DC, 2006d (EPA/402-r-06-007).
EPA, Guidance for Preparing Standard Operating Procedures (SOPs), Office of Environmental Information, EPA, Washington, DC, 2007 (EPA QA/G-6, EPA/600/B-07/001).
EPA, Management and Interpretation of Data Under a Triad ApproachTechnology Bulletin, Office of Solid Waste and Emergency, EPA, Washington, DC, 2007b (EPA 542-F        001).
EPA, Best Management Practices: Use of Systematic Project Planning Under a Triad Approach for Site Assessment and Cleanup, Office of Solid Waste and Emergency, EPA, Washington, DC, 2010 (EPA 542-F-10-010).
EPA, A Performance-Based Approach to the Use of Swipe Samples in Response to a Nuclear or Radiological Incident, Office of Research and Development, EPA, Washington, DC, 2011 (EPA 600/R-11/122).
EPA and Ad Hoc Industrial Excess Landfill Panel of the Science Advisory Board (SAB), An SAB Report: Review of EPAs Approach to Screening for Radioactive Waste Materials at May 2020                                      Ref-13                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
References                                                                            MARSSIM a Superfund Site in Uniontown, Ohio, Scientific Advisory Board, EPA, Washington, DC, 1994 (EPA-SAB-EC-94-010).
Friedman, G.M. and J.L. Sanders, Principles of Sedimentology, John Wiley and Sons, New York, NY, 1978.
Fritzsche, A.E., An Aerial Radiological Survey of the White Creek Floodplain, Oak Ridge Reservation, Oak Ridge, Tennessee, Remote Sensing Laboratory, EG&G/EM, Las Vegas, NV, 1987 (EGG-10282-1136).
GAO (General Accounting Office), Integrated Site Assessments May Expedite Cleanups, GAO, Washington, DC, 1997 (GAO/RCED-97-181).
George, A.C., Passive, Integrated Measurement of Indoor Radon Using Activated Carbon, Health Physics, 46:867, 1984.
George Air Force Base, CA, 91(b) Radioactive Material (RAM), available at www.georgeafb.info/91b-radioactive-material/, accessed November 18, 2019.
Gilbert, R.O., Statistical Methods for Environmental Pollution Monitoring, Van Nostrand Reinhold, New York, NY, 1987.
Hall, P. and E. Mammen, On General Resampling Algorithms and Their Performance in Distribution Estimation, The Annals of Statistics, 22(4): 2011-2030, 1994.
Hardin, J.W. and R.O. Gilbert, Comparing Statistical Tests for Detecting Soil Contamination Greater Than Background, Pacific Northwest Laboratory, Richland, WA, 1993 (PNL-8989).
Harnett, D.L., Introduction to Statistical Methods, 2nd Ed., Addison-Wesley, Reading, MA, 1975.
Hill, R.L., R.L. Aaberg, D.A. Baker, and W.E. Kennedy, Jr. Radiation Dose Assessments to Support Evaluations of Radiological Control Levels for Recycling or Reuse of Materials and Equipment, PNL-8724, Pacific Northwest Laboratory, Hanford, WA, 1995.
Hollander, M., Nonparametric Statistical Methods, 3rd Edition, John Wiley & Sons, Inc.,
Hoboken, New Jersey, 2014.
Hora, S.C. and R.L. Iman, Expert Opinion in Risk Analysis: The NUREG-1150 Methodology, Nuclear Science and Engineering, 102(4):323-331, 1989.
HPS (Health Physics Society), Criteria for Accreditation of Calibration Laboratories by the Health Physics Society, HPS, McLean, VA, 1994a.
HPS, Program Handbook for the Accreditation of Calibration Laboratories by the Health Physics Society, HPS, McLean, VA, 1994b.
HPS, Performance and Documentation of Radiological Surveys, ANSI/HPS N13.49, HPS, McLean, VA, 2001.
NUREG-1575, Revision 2                        Ref-14                                  May 2020 DRAFT FOR PUBLIC COMMENT                                                DO NOT CITE OR QUOTE
 
MARSSIM                                                                              References HPS, Characterization in Support of Decommissioning Using the Data Quality Objectives Process, ANSI/HPS N13.59, HPS, McLean, VA, 2008.
IAEA (International Atomic Energy Agency), Handbook on Calibration of Radiation Protection Monitoring Instruments, Technical Report Series 133, IAEA, Vienna, Austria, 1971.
IAEA, Regulations for the Safe Transport of Radioactive Material, Technical Report Series 1, IAEA, Vienna, Austria, 2005.
Interagency Steering Committee on Radiation Standards, RESRAD-BIOTA: A Tool for Implementing a Graded Approach to Biota Dose Evaluation, ISCORS Technical Report 2004-02, DOE/EH-0676, ISCORS, Washington, DC 2004.
ISO (International Organization for Standardization), Quality Management and Quality Assurance Standards - Guidelines for Selection and Use. American Society for Quality Control, Milwaukee, WI, 1987a (ISO 9000-1).
ISO, Quality Management and Quality System Elements - Guidelines, American Society for Quality Control, Milwaukee, WI, 1987b (ISO 9004-1).
ISO, Quality Systems  Model for Quality Assurance in Design/Development, Production, Installation and Servicing, American Society for Quality Control, Milwaukee, WI, 1987c (ISO 9001-1).
ISO, Quality Systems  Model for Quality Assurance in Final Inspection and Test, American Society for Quality Control, Milwaukee, WI, 1987d (ISO 9003).
ISO, Quality Systems  Model for Quality Assurance in Production and Installation, and Servicing, American Society for Quality Control, Milwaukee, WI, 1987e (ISO 9002).
ISO, Evaluation of Surface Contamination  Part 1: Beta-Emitters (Maximum Beta Energy Greater Than 0,15 MeV) and Alpha-Emitters, ISO-7503-1 (1st Edition) ISO, Geneva, Switzerland, 1988.
ISO, Guide to the Expression of Uncertainty in Measurement, ISO, Geneva, Switzerland, 1993.
ISO, International Vocabulary of Basic and General Terms in Metrology, 3rd Edition, ISO, Geneva, Switzerland, 2008.
Jenkins, P.H., Radon Measurement Methods: An Overview, Proceedings of Health Physics Society Meeting, 29 June 1986, Pittsburgh, PA, Monsanto Research Corporation, Miamisburg, OH, 1986, p. 38 (CONF-8606139-5).
Kamboj, S., E. Gnanapragasam, and C. Yu. Users Guide for RESRAD-ONSITE Code, ANL/EVS/TM-18/1, Argonne National Laboratory, Argonne, IL, 2018.
Kume, H. and K.G.K. Kykai, Statistical Methods for Quality Improvement, The Association of Overseas Technical Scholarship, Tokyo, Japan, 1985.
May 2020                                      Ref-15                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                              DO NOT CITE OR QUOTE
 
References                                                                              MARSSIM Lodge, J.P., Jr., ed., Methods of Air Sampling and Analysis, 3rd Edition, American Chemical Society, American Institute of Chemical Engineers, American Public Works Association, American Society of Mechanical Engineers, Association of Official Analytical Chemists, Air and Waste Management Association, Health Physics Society, Instrument Society of America, CRC Press, Inc., Boca Raton, FL, 1988.
Macmillan, N.A. and C.D. Creelman, Detection Theory: A Users Guide, Cambridge University Press, Cambridge, England, 1991.
Maiello, M.L. and M.D. Hoover, Radioactive Air Sampling Methods, CRC Press, Boca Raton, FL, 2010.
McAninch, J.E., T.F. Hamilton, T.A. Brown, T.J. Jokela, J.P. Knezovich, T.J. Ognibene, I.D.
Proctor, M.L. Roberts, E. Sideras-Haddad, J.R. Southon, J.S. Vogol, Plutonium Measurements by Accelerator Mass Spectrometry at LLNL, Lawrence Livermore National Laboratory, Livermore, CA, 1999.
Miller, K.M., P. Shebell, and G.A. Klemic, In Situ Gamma-Ray Spectrometry for the Measurement of Uranium in Surface Soils, Health Physics, 67:140-150, 1994.
Mood, A.M., F.A. Graybill, and D.C. Boes, Introduction to the Theory of Statistics, 3rd Edition, McGraw Hill, Boston, MA, 1974.
Myrick, T.E., B.A. Berven, and F.F. Haywood, State Background Radiation Levels: Results of Measurements Taken During 1975-1979, Oak Ridge National Laboratory, Oak Ridge, TN, 1981 (ORNL/TM-7343).
NCRP (National Council on Radiation Protection and Measurements), Environmental Radiation Measurements, NCRP, Bethesda, MD, 1976 (NCRP Report No. 50).
NCRP, Instrumentation and Monitoring Methods for Radiation Protection, NCRP, Bethesda, MD, 1978 (NCRP Report 57).
NCRP, A Handbook of Radioactivity Measurement Procedures, 2nd Ed., NCRP, Bethesda, MD, 1985 (NCRP Report 58d).
NCRP, Exposure of the Population in the United States and Canada from Natural Radiation, NCRP, Bethesda, MD, 1987 (NCRP Report 94).
NCRP, Measurement of Radon and Radon Daughters in Air, NCRP, Bethesda, MD, 1988 (NCRP Report 97).
NCRP, Calibration of Survey Instruments used in Radiation Protection for the Assessment of Ionizing Radiation Fields and Radioactive Surface Contamination, NCRP, Bethesda, MD, 1991 (NCRP Report 112).
Necsoiu, M. and G.R. Walter, Detection of Uranium Mill Tailings Settlement Using Satellite-based Radar Interferometry, Engineering Geology, 197:267-277, 2015.
NUREG-1575, Revision 2                        Ref-16                                  May 2020 DRAFT FOR PUBLIC COMMENT                                              DO NOT CITE OR QUOTE
 
MARSSIM                                                                                References National Institute of Standards and Technology (NIST), Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results, NIST Technical Note 1297, NIST, Gaithersburg, MD, 1994.
NIST, NIST Policy of Metrological Traceability, https://www.nist.gov/calibrations/traceability, NIST, Gaithersburg, MD, published September 4, 2019, accessed March 31, 2020.
NRC (U.S. Nuclear Regulatory Commission), Termination of Operating Licenses for Nuclear Reactors, Regulatory Guide 1.86, NRC, Washington, DC, 1974.
NRC, Programs for Monitoring Radioactivity in the Environs of Nuclear Power Plants, NRC Regulatory Guide 4.1, Rev. 1, NRC, Washington, DC, 1975.
NRC, Quality Assurance for Radiological Monitoring Programs (Normal Operations) - Effluent Streams and the Environment, Regulatory Guide 4.15, NRC, Washington, DC, 1979.
NRC, Radiological Effluent and Environmental Monitoring at Uranium Mills, NRC Regulatory Guide 4.14, Revision 1, NRC, Washington, DC, 1980.
NRC, Letter to Stanford University, NRC, Office of Nuclear Reactor Regulation, Washington, DC, 1982, NRC Docket No. 50-401.
NRC, Lower Limit of Detection: Definition and Elaboration of a Proposed Position for Radiological Effluent and Environmental Measurements, NRC, Washington DC, 1984 (NUREG/CR-4007).
NRC, Severe Accident Risks: An Assessment for Five U.S. Nuclear Power Plants, NUREG-1150, Volume 1, Office of Nuclear Regulatory Research, NRC, Washington, DC, 1990.
NRC, Quality Assurance Guidance for a Low-Level Radioactive Waste Disposal Facility, NUREG-1293, Revision 1, NRC, Washington, DC, 1991.
NRC, Manual for Conducting Radiological Surveys in Support of License Termination, NUREG/CR-5849, Draft Report for Comment, NRC, Washington, DC and Oak Ridge Associated Universities, Oak Ridge, TN, 1992a.
NRC, Residual Radioactive Contamination from Decommissioning, NUREG/CR-5512, Final Report, NRC, Washington, DC and Pacific Northwest Laboratory, Richland, WA, 1992b.
NRC, Background as a Residual Radioactivity Criterion for Decommissioning, Draft Report, NUREG-1501, Office of Nuclear Regulatory Research, NRC, Washington, DC, 1994a.
NRC, Draft Branch Technical Position on Site Characterization for Decommissioning, NRC, Washington, DC, 1994b.
NRC, Working Draft Regulatory Guide on Release Criteria for Decommissioning: NRC Staffs Draft for Comment, NUREG-1500, Office of Nuclear Regulatory Research, NRC, Washington, DC, 1994c.
May 2020                                    Ref-17                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                              DO NOT CITE OR QUOTE
 
References                                                                        MARSSIM NRC, Proposed Methodologies for Measuring Low Levels of Residual Radioactivity for Decommissioning (Draft Report for Comment), NUREG-1506, NRC, Washington, DC, 1995.
NRC, Minimum Detectable Concentrations with Typical Radiation Survey Instruments for Various Contaminants and Field Conditions (Final), NUREG/CR-1507, NRC, Washington, DC, 1997a.
NRC, NMSS Handbook for Decommissioning Fuel Cycle and Materials Licensees, NUREG/BR-0241, NRC, Washington, DC, 1997b.
NRC, A Proposed Nonparametric Statistical Methodology for the Design and Analysis of Final Status Decommissioning Surveys (Revision 1, Final), NUREG-1505, NRC, Washington, DC, 1998a.
NRC, Multi-Agency Radiological Survey and Site Investigation Manual, NUREG-1575, EPA-402-R-97-016, DOE/EH-0624, NRC, Washington, DC, 1998b.
NRC, Development of Probabilistic RESRAD 6.0 and RESRAD-BUILD 3.0 Computer Codes, NUREG/CR-6697, ANL/EAD/TM-98, NRC, Washington, DC, 2000a.
NRC, Multi-Agency Radiological Survey and Site Investigation Manual, NUREG-1575, Rev. 1, EPA-402-R-97-016, Rev. 1, DOE/EH-0624, Rev. 1, NRC, Washington, DC, 2000b.
NRC, Probabilistic Modules for the RESRAD and RESRAD-BUILD Computer Codes User Guide, NUREG/CR-6692, ANL/EAD/TM-91, NRC, Washington, DC, 2000c.
NRC, Multi-Agency Radiological Laboratory Analytical Protocols Manual, NUREG-1576, EPA 402-B-04-001A, PB2004-105421, NRC, Washington, DC, 2004.
NRC, Consolidated Decommissioning Guidance, Volume I: Decommissioning Process for Materials Licensees, Revision 2, Volume 1, NUREG-1757, NRC, Washington, DC, 2006.
NRC, Inspection Manual, Chapter 2602, Decommissioning Oversight and Inspection Program for Fuel Cycle Facilities and Materials Licensees, NRC, Washington, DC, 2008.
NRC, Multi-Agency Radiation Survey and Assessment of Materials and Equipment Manual, Supplement 1, NUREG-1575, EPA 402-R-09-002, DOE DOE/HS-0004, NRC, Washington, DC, 2009.
NRC, A Subsurface Decision Model for Supporting Environmental Compliance, NUREG/CR-7021, NRC, Washington, DC, 2012.
NRC, Users Guide for RESRAD/OFFSITE, NUREG/CR-7189, ANL/EVS/TM-14/2, NRC, Washington, DC, 2018.
Occupational Safety and Health Administration (OSHA), Job Hazard Analysis, OSHA 3071, OSHA, Washington, DC, 2002.
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MARSSIM                                                                              References Perdue, P.A., R.W. Leggett, and F.F. Haywood, A Technique for Evaluating Airborne Concentrations of Daughters of Radon Isotopes, T.F. Gesell and W.M. Lowder, eds.,
Third International Symposium on the Natural Radiation Environment, 23-28 April 1978, in Natural Radiation Environment III, Houston, TX, Technical Information Center, U.S, Department of Energy, Springfield, VA, 1978, pp. 347-356 (CONF-780422).
Peter Gray & Associates (PGA), The NORM Report, Peter Gray and Associates, Tulsa, OK, Fall 1999/Winter 2000, pp. 1-10.
Roberts, S., Independent Verification Objectives and Recent Lessons Learned, Oak Ridge Associated Universities, Oak Ridge, TN, 2008.
-panl, P. and D. Smith, Accuracy and Precision of Flowing Afterglow Mass Spectrometry for the Determination of the Deuterium Abundance in the Headspace of Aqueous Liquids and Exhaled Breath Water, Rapid Communications in Mass Spectrometry, 15:867-872, 2001.
-panl, P. and D. Smith, Flowing Afterglow Mass Spectrometry (FA-MS) for the Determination of the Deuterium Abundance in Breath Water Vapour and Aqueous Liquid Headspace, A. Amann and D. Smith, eds., Breath Analysis for Clinical Diagnosis and Therapeutic Monitoring, World Scientific Publishing, Singapore, 2005, pp. 439-455.
Taylor, J.K., Quality Assurance of Chemical Measurements, Lewis Publishers, Inc., Chelsea, MI, 1987.
van der Leeden, F., F.L. Troise, and D.K. Todd, The Water Encyclopedia, 2nd Edition, Lewis Publishers, Chelsea, MI, 1990.
Vitkus, T.J., Technical Bases and Guidance for the Use of Composite Soil Sampling for Demonstrating Compliance with Radiological Release Criteria, Oak Ridge Institute for Science and Education, Oak Ridge, TN, 2012.
Wallo III, A., M. Moscovitch, J.E. Rodgers, D. Duffey, and C. Soares, Investigations of Natural Variations of Cesium-137 Concentrations in Residential Soil, The Health Physics Society 39th Annual Meeting, June 26-30, 1994, San Francisco, CA, Health Physics Society (HPS), McLean, VA, 1994 (TPM-E4).
Walpole, R.E. and R.H. Myers, Probability and Statistics for Engineers and Scientists, 3rd Edition, MacMillan Publishing Company, New York, NY, 1985.
Wang, Y.-Y., B.M. Biwer, and C. Yu. A Compilation of Radionuclide Transfer Factors for Plant, Meat, Milk, and Aquatic Food Pathways and the Suggested Default Values for the RESRAD Code, ANL/EAIS/TM-103, Argonne National Laboratory, Argonne, IL, 1993.Yu, C., A.J. Zielen, J.-J. Cheng, Y.C. Yuan, L.G. Jones, D.J. LePoire, Y.Y. Wang, C.O. Loureiro, E. Gnanapragasam, E. Faillace, A. Wallo III, W.A. Williams, and H.
Peterson, Manual for Implementing Residual Radioactive Material Guidelines Using RESRAD, Version 5.0, DE94-015594, ANL/EAD/LD-2, Argonne National Laboratory, Argonne, IL, 1993.
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References                                                                              MARSSIM Yu, C., A.J. Zielen, J.-J. Cheng, D.J. LePoire, E. Gnanapragasam, S. Kamboj, J. Arnish, A.
Wallo III, W.A. Williams, and H. Peterson. Users Manual for RESRAD, Version 7.2, ANL/EAD-4, Argonne National Laboratory, Argonne, IL, 2001.
Yu, C., D.J. LePoire, J.-J. Cheng, E. Gnanapragasam, S. Kamboj, J. Arnish, B.M. Biwer, A.J.
Zielen, W.A. Williams, A. Wallo III, and H.T. Peterson, Jr. Users Manual for RESRAD-BUILD, Version 3, ANL/EAD/03-1, Argonne National Laboratory, Argonne, IL, 2003.
Yu, C., E. Gnanapragasam, B.M. Biwer, S. Kamboj, J.-J. Cheng, T. Klett, D. LePoire, A.J.
Zielen, S.Y. Chen, W.A. Williams, A. Wallo, S. Domotor, T. Mo, and A. Schwartzman.
Users Manual for RESRAD-OFFSITE, Version 2, ANL/EVS/TM/07-1, DOE/HS-0005, NUREG/CR-6937, Argonne National Laboratory, Argonne, IL, 2007.
Yu, C., S. Kamboj, C. Wang, and J.-J. Data Collection Handbook to Support Modeling Impacts of Radioactive Material in Soil and Building Structures, ANL/EVS/TM-14/4, Argonne National Laboratory, Argonne, IL, 2015.
U.S. Code of Federal Regulations U.S. Code of Federal Regulations, Nuclear Regulatory Commission, (10 CFR, Chapter 1),
U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Standards for Protection Against Radiation, (10 CFR Part 20), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Standards for Protection Against Radiation - Subpart A General Provisions: Purpose, (10 CFR 20.1001), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Dose limits for Individual Members of the Public - Subpart DOccupational Dose Limits: Dose Limits for Individual Members of the Public, (10 CFR 20.1301), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Method for Obtaining Approval of Proposed Disposal Procedures, (10 CFR 20.2002), U.S. Nuclear Regulatory Commission,1995.
U.S. Code of Federal Regulations, Rules of General Applicability to Domestic Licensing of Byproducts and Material, (10 CFR Part 30), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Licenses: Expiration and Termination of Licenses and Decommissioning of Sites and Separate Buildings or Outdoor Areas, (10 CFR 30.36),
U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Radiation Surveys, (10 CFR Part 36.57), U.S Nuclear Regulatory Commission, 1993.
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MARSSIM                                                                              References U.S. Code of Federal Regulations, Domestic Licensing of Source Material, (10 CFR Part 40),
U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Licenses: Expiration and Termination of Licenses and Decommissioning of Sites and Separate Buildings or Outdoor Areas, (10 CFR 40.42),
U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Domestic Licensing of Source Material: Effluent Monitoring Reporting Requirements, (10 CFR 40.65), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Criteria Relating to the Operation of Uranium Mills and the Disposition of Tailings or Wastes Produced by the Extraction or Concentration of Source Material from Ores Processed Primarily for Their Source Material Content, (10 CFR Part 40, Appendix A), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Domestic Licensing of Production and Utilization Facilities, (10 CFR Part 50), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Numerical Guides for Design Objectives and Limiting Conditions for Operations to Meet the Criterion As Low as is Reasonably Achievable for Radioactive Material in Light-Water-Cooled Nuclear Power Reactor Effluents, (10 CFR Part 50, Appendix I), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Domestic Licensing of Production and Utilization Facilities:
US/IAEA Safeguards Agreement: Application for Termination of License, (10 CFR 50.82), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Domestic Licensing of Special Nuclear Material, (10 CFR Part 70), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Licenses: Expiration and Termination of Licenses and Decommissioning of Sites and Separate Buildings or Outdoor Areas, (10 CFR 70.38),
U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Special Nuclear Material Control, Records, Reports and Inspections: Effluent Monitoring Reporting Requirements, (10 CFR 70.59), U.S.
Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Packaging and Transportation of Radioactive Material, (10 CFR Part 71), U.S. Nuclear Regulatory Commission, 1996.
U.S. Code of Federal Regulations, Packaging and Transportation of Radioactive Material -
Subpart AGeneral Provisions: Definitions, (10 CFR 71.4), U.S. Nuclear Regulatory Commission, 1996.
U.S. Code of Federal Regulations, Packaging and Transportation of Radioactive Material -
Subpart BExemptions: Exemption for Low-level Materials, (10 CFR 71.10), U.S.
Nuclear Regulatory Commission, 1996.
May 2020                                    Ref-21                    NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
References                                                                          MARSSIM U.S. Code of Federal Regulations, Packaging and Transportation of Radioactive Material -
Subpart FOperating Controls and Procedures: Air Transport of Plutonium, (10 CFR 71.88), U.S. Nuclear Regulatory Commission, 1996.
U.S. Code of Federal Regulations, Licensing Requirements for the Independent Storage of Spent Nuclear Fuel and High-level Radioactive Waste - Subpart CIssuance and Conditions of License: Expiration and Termination of Licenses and Decommissioning of Sites and Separate Buildings or Outdoor Areas, (10 CFR 72.54), U.S. Nuclear Regulatory Commission, 1995.
U.S. Code of Federal Regulations, Nuclear Safety Management, (10 CFR Part 830), U.S.
Department of Energy, as amended, 2001.
U.S. Code of Federal Regulations, Occupational Radiation Protection, (10 CFR Part 835), U.S.
Department of Energy, 1993.
U.S. Code of Federal Regulations, Worker Safety and Health Program, (10 CFR Part 851),
U.S. Department of Energy, 2006.
U.S. Code of Federal Regulations, National Emission Standards for Hazardous Air Pollutants, (40 CFR Part 61), U.S. Environmental Protection Agency, as amended, 1973.
U.S. Code of Federal Regulations, National Primary Drinking Water Regulations, (40 CFR Part 141), U.S. Environmental Protection Agency, 1994.
U.S. Code of Federal Regulations, "Environmental Radiation Protection Standards for Nuclear Power Operations, (40 CFR Part 190), U.S. Environmental Protection Agency, 1995.
U.S. Code of Federal Regulations, Environmental Radiation Protection Standards for Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive Wastes, (40 CFR Part 191), U.S. Environmental Protection Agency, as amended, 1993.U.S. Code of Federal Regulations, Health and Environmental Protection Standards for Uranium and Thorium Mill Tailings, (40 CFR Part 192), U.S.
Environmental Protection Agency, as amended, 1995.
U.S. Code of Federal Regulations, Hazard Ranking System, (40 CFR Part 300), U.S.
Environmental Protection Agency, 1990.
U.S. Code of Federal Regulations, Registration of Shipper/Carrier - Subpart GRegistration of Persons Who Offer or Transport Hazardous Materials, (40 CFR Part 300), U.S.
Environmental Protection Agency, 1990.
U.S. Code of Federal Regulations, Hazardous Materials Program Procedures, (49 CFR Part 107), U.S. Department of Transportation, 2015.
U.S. Code of Federal Regulations, Accident Reporting, (49 CFR Part 171), U.S. Department of Transportation, 1996.
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MARSSIM                                                                            References U.S. Code of Federal Regulations, Marking and Labeling Packages for Shipment, (49 CFR Part 172), U.S. Department of Transportation, 1996.
U.S. Code of Federal Regulations, Packaging, (49 CFR Part 173), U.S. Department of Transportation, 1996.
U.S. Code of Federal Regulations, Transport by Rail, (49 CFR Part 174), U.S. Department of Transportation, 1996.
U.S. Code of Federal Regulations, Transport by Air, (49 CFR Part 175), U.S. Department of Transportation, 1996.
U.S. Code of Federal Regulations, Transport by Vessel, (49 CFR Part 176), U.S. Department of Transportation, 1996.
U.S. Code of Federal Regulations, Transport on Public Highway, (49 CFR Part 177), U.S.
Department of Transportation, 1996.
U.S. Federal Law (Acts and Executive Orders)
Administrative Procedures Act of 1946, 5 U.S.C. &sect;551 et seq.
Atomic Energy Act (AEA) of 1954, as amended, 42 U.S.C. &sect;&sect; 2011-2296 Clean Air Act (CAA) of 1990, as amended, 42 U.S.C. &sect;&sect; 7401-7671 Clean Water Act (CWA) of 1972, as amended, 33 U.S.C. &sect; 1251 et seq.
Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) of 1980, as amended, 42 U.S.C. &sect;&sect; 9601-9675 Department of Energy Organization Act of 1977, Public Law 95-91,91 Stat. 565 Energy Policy Act of 1992, 16 U.S.C. &sect; 2601 et seq. and 42 U.S.C. &sect;13201 et seq.
Energy Policy Act of 2005, 16 U.S.C. &sect; 2601 et seq. and 42 U.S.C. &sect;13201 et seq.
Energy Reorganization Act of 1974, as amended, 42 U.S.C. &sect; 5801 et seq.
Executive Order 10831, Establishing the Federal Radiation Council Executive Order 12088, Federal Compliance with Pollution Control Standards Executive Order 12580, Superfund Implementation Federal Facilities Compliance Act of 1992, Public Law 102-386 Hazardous Materials Transportation Act of 1975, Public Law 93-633 May 2020                                    Ref-23                  NUREG-1575, Revision 2 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE
 
References                                                                        MARSSIM Indoor Radon Abatement Act (IRAA) of 1988 15 &sect; U.S.C. 2601 &sect;&sect; 301-311 Low-Level Radioactive Waste Policy Act (LLRWPA) of 1980, as amended, 42 U.S.C. &sect; 2021b National Environmental Policy Act of 1970, 42 U.S.C. &sect; 4321 et seq.
Nuclear Non-Proliferation Act of 1978, as amended, 22 U.S.C. &sect; 3201 et seq.
Nuclear Waste Policy Act (NWPA) of 1982, as amended, 42 U.S.C. &sect; 10101 Omnibus Diplomatic Security and Antiterrorism Act of 1986, 22 U.S.C. 4852 Price-Anderson Amendments Act of 1988, Public Law 100-408, 102 Stat. 1066 Public Health Service Act, as amended, 42 U.S.C &sect; 241 et seq.
Reorganization Plan No. 3 of 1970, 35 Fed. Reg. 15623 (October 6, 1970)
Resource Conservation and Recovery Act (RCRA) of 1976, 42 U.S.C. &sect;&sect; 6901-6992k Safe Drinking Water Act (SDWA) of 1974, as amended, 42 U.S.C. &sect; 300f et seq.
Solar, Wind, Waste, and Geothermal Power Production Incentives Act of 1990, Pub. L. 101-575, 104 Stat. 2834 Toxic Substances Control Act (TSCA) of 1976, 15 U.S.C. &sect;&sect; 2601-2692 Uranium Mill Tailings Radiation Control Act (UMTRCA) of 1978, as amended, 42 U.S.C. &sect; 2022 Waste Isolation Pilot Plant Land Withdrawal Act of 1992, Public Law No: 102-579 West Valley Demonstration Project Act of 1980, Pub. L. No. 96-368, Stat. 2443 NUREG-1575, Revision 2                      Ref-24                              May 2020 DRAFT FOR PUBLIC COMMENT                                            DO NOT CITE OR QUOTE}}

Revision as of 11:37, 29 November 2024

NUREG-1575, Rev. 2, Multi-Agency Radiation Survey and Site Investigation Manual (Marssim), Draft for Public Comment
ML21008A573
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Issue date: 05/31/2020
From:
Office of Nuclear Regulatory Research
To:
Mark Fuhrmann
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References
DOE/AU-0002, EPA-402-P-20-001 NUREG-1575, Rev. 2
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