ML20248H732

Proceedings of the Workshop on Review of Dose Modeling Methods for Demonstration of Compliance with the Radiological Criteria for License Termination

ML20248H732
Person / Time
Issue date:	05/31/1998
From:	Thomas Nicholson, Jack Parrott NRC OFFICE OF NUCLEAR MATERIAL SAFETY & SAFEGUARDS (NMSS), NRC OFFICE OF NUCLEAR REGULATORY RESEARCH (RES)
To:
References
NUREG-CP-0163, NUREG-CP-163, NUDOCS 9806080229
Download: ML20248H732 (123)

Text

NUREG/CP-0163 i

Proceedings of the Workshop on  !

Review of Dose Modeling Methods for Demonstration of i Compliance With the Radiological Criteria for License Termination l Held at NRC Headquarters Auditorium  !

Rockville. Maryland, USA 1 i

l November 13-14,1997

. icholson, USNRC/RES )

J.D. Panott, USNRC/NMSS l

Sponsored by j Office of Nuclear Regulatory Research Offict of Nuclear Material Safety and Safeguards {c) /

U.S. Nuclear Regulatory Commission l l

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NUREG/CP-0163 1

l Proceedings of the Workshop on Review of Dose Modeling Methods for Demonstration of Compliance With the Radiological Criteria for License Termination Held at NRC Headquarters Auditorium Rockville, Maryland, USA November 13-14,1997 Manuscript Completed: April 1998 Date Published:May 1998 Edited by T.J.Nicholson USNRC/RES J.D. Parrou, USNRC/NMSS Sponsored by Office of Nuclear Regulatory Research Office of Nuclear Material Safety and Safeguards U.S. Nuclear Regulatory Commission Wcshington, DC 20555-0001

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NUREG4CP-0163 has been reproduced from the best available copy.

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l ABSTRACT The public " Workshop on Review of Dose Modeling Methods for Demonstration of Compliance with the Radiological Criteria for License Termination" was held at the NRC Headquaners Auditorium, Rockville, Maryland, on November 13-14,1997. The workshop was one in a series to suppon NRC staff development of guici.:nce for implemendng the final rule on " Radiological Criteria for License Termination." The workshep topics included discussion of: dose models used for decommissioning reviews; identification of criteria for evaluating the acceptability of dose models; and selection of parameter values for demonstrating compliance with the final rule.

The 2-day public workshop wasjointly organized by RES and NMSS staffresponsible for reviewing dose modeling methods used in decommissioning reviews. The workshop was noticed in the Federal Register (62 FR 51706). The workshop presenters included: NMSS and RES staff, who discussed both dose modeling needs for licensing reviews, and development of guidance related to dose modeling and parameter selection needs; DOE national laboratory scientists, who provided responses to earlier NRC staff-developed questions and discussed their various Federally-sponsored dose models (i.e., DandD, RESRAD, and MEPAS codes); and an EPA l

scientist, who presented details on the EPA dose assessment model (i.e., PRESTO code). The workshop was formatted to provide opponunities for the attendees to observe computer demonstrations of the dose codes presented. More than 120 workshop attendees from NRC Headquarters and the Regions, Agreement States; as well as industry representatives and l consultants; scientists from EPA, DOD, DNFSB, DOE, and the national laboratories; and interested members of the public participated. A complete transcript of the workshop, including viewgraphs and attendance lists, is available in the NRC Public Document Room. This NUREG/CP documents the formal presentations made during the workshop, and provides a preface outlining the workshop's focus, objectives, background, topics and questions provided to the invited speakers, and those raised during the panel discussion. NUREG/CP-0163 also provides technical bases supporting the development of decommissioning guidance.

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TABLE OF CONTENTS Abstract......................................................................................................................................iii Preface......................................................................................................................................vii Foreword.................................................................................................................................xiii Dose Modeling Needs for Licensing Reviews by D. Fauver and J. Parrott, NRC/NM S S ................................................................... 1 Development of Guidance Related to Dose Modeling and Parameter Selection Needs by C. Daily, T. J. Nicholson and F. Cardile, NRC/RES .......................................... .. 5 Use of DandD for Dose Assessment Under NRC's

. Radiological Criteria for License Termination Rule by D. P. Gallegos, T. J. Brown, and P. A. Davis, SNL ....... ...................................... 13 RESRAD Model Presentation by C. Yu, D.- Faillace, S.Y. Chen, ANL, A. Wallo, W. Williams, H. Peterson and S. Domotor, DOE ................................................... 29 Response to Nuclear Regulatory Commission's Ten l Questions Penaining to Site-Specific Models for Use in the License Termination Rule: Multimedia Environmental Pollutant Assessment System (MEPAS) by J.W. Buck, D. Strenge, B. Hoopes, J. Mcdonald, l ' K. Castleton, M. Pelton, G. Gelston, and R. Taira, PNNL ...................................... 63 Framework for Risk Analysis in Multimedia i Environmental Systems (FRAMES)

L by G. Whelan, J. Buck, K. Castleton, B. Hoopes, M. Pelton, J. Mcdonald, G. Gelston, and R. Taira, PNNL ..................................... 77 Overviewof PRESTOModel

by C . Y. H ung, U.S . E PA . . ... . . . . .. . . . . .. .. .. . . ... . . . . . . .. . . . . . . . . . .. ... .... . .. . . .. . . . . . . . . . . . . . . . . . .. . . . . . .. . . 93 v NUREG/CP-0163 l

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PREFACE A public workshop, noticed in the Federal Register (62 FR 51706), was held at the U.S. Nuclear Regulatory Commission (NRC) Headquarters Auditorium, Rockville, Maryland. The workshop objectives were to: (1) provide the NRC staff and the public with an overview of currently available Federally-sponsored dose models appropriate for decommissioning dose assessments; and (2) discuss NRC staff-developed questions related to model and parameter selection criteria for evaluating the acceptability of the models and parameters for demonstrating compliance with the final rule on " Radiological Criteria for License Termination" (62 FR 39058). This workshop was one in a series designed to support NRC staff efforts in developing guidance for implementing the final rule on " Radiological Criteria for License Termination." The guidance will identify criteria for evaluating the acceptability of dose models and parameter values to demonstrate compliance with the final mle.

In support of this effort, NRC st..ff from the Offices of Nuclear Regulatory Research (RES) and Nuclear Material Safety and Safeguards (NMSS) jointly organized the 2-day public workshop on review of dose modeling methods. The workshop presenters (see " Agenda") included: NMSS and RES staff who discussed both dose modeling needs for licensing reviews, and development of guidance related to dose modeling and parameter selection needs; U.S. Department of Energy (DOE) national laboratory scientists who developed the Federally-sponsored dose models, and provided responses to earlier NRC staff-developed questions through presentations and discussions of their dose code (i.e., DandD, RESRAD, and MEPAS codes); and a U.S.

Environmental Protection Agency (EPA) scientist who presented details on their dose assessment model (i.e., PRESTO code).

During the lunch hour and afternoon break on the first day of the workshop, computer demonstrations of the dose codes were provided to the attendees. More than 120 workshop attendees from NRC Headquarters and the Regions, Agreement States; as well as, industry representatives and consultants; scientists fron' EPA, U.S. Department of Defense (DOD),

Defense Nuclear Facilities Safety Board (DNE , DOE and national laboratory; and interested members of the public participated. An official uanscript of the workshop, including a listing of attendees, was placed in the NRC Public Document Room.

This NUREG/CP reports on the workshop proceedings in a more formal manner than the official transcripts by providing documentation of the technical papers presented. The technical papers, prepared by the invited speakers and their colleagues, after the meeting, address, in part, questions raised during their presentations, and in the panel discussions at the conclusion of the I

workshop. The NUREG/CP is also designed to provide technical bases and discussions to l support development cf the decommissioning guidance.

The NRC staff considered a range of dose models that may be appropriate for use in site-specific dose assessments for specific pathways. The goal of the workshop was to provide an overview of the dose models currently available for NRC staff to consider, when developing regulatory guidance for selecting dose models to be used in demonstrating compliance with the final rule on vii NUREG/CP-0163

" Radiological Criteria for License Termination." Additionally, the workshap provided an open forum to discuss: the capabilities, experiences and appropriateness of each dose model presented; information and methods available for selecting site-specific parameter values; and ideas for

! developing a minimum list of technical issues that need to be addressed and satisfied in an NRC licensee's request to use a site-specific screening and/or site-specific modeling dose code which go beyond the default screening model (i.e., DandD code). The workshop was not meant to discuss comparisons between the dose codes, nor to critically compare the dose models, but rather to simply allow the developer of each Federally-sponsored code to respond to NRC staff questions.

A series of questions were developed by a team of RES and NMSS staff to explore how appropriate the identified Federally-sponsored dose models are NRC staff needs. These questions were reviewed by NRC management and sent to the in ited speakers. The speakers were requested to address the following questions in their presentations (and later in their technical papers, which are published in this NUREG/CP):

1. Please describe the history of the analytical method's development (e.g., Who developed it? For what purpose was it developed? Who were the sponsors? Is there documentation on the code such as a " users' manual?").

2. What transport mechanisms, scena;ios, and exposure pathways are considered?

3. How are parameter values determined for input?

(Can uncertainties.s be incorporated into the parameter distributions and the subsequent dose calculations?)

4. What radionuclides and chemicals that can affect radionuclides transport are considered?

(Is decay and in-growth considered? to what extent?)

5. What are the time and spatial geometry limitations inherent in the analytical method?

6. To what extent can alternative remedial actions be assessed and compared (e.g.,

comparison of concentrations, doses, and costs)?

7. To what extent has the dose model been tested and included in bench-marking studies?

8. To what extent can the analytical method handle complex:

(a) source tenn characterization; (b) multiple source terms; (c) hydrologic and hydrogeologic conditions; (d) exposure pathway combinations; (e) remedial methods linked to cost and monitoring programs; and (f) ALARA considerations?

9. Does the dose model include software graphical output for portraying dose versus time for various exposure pathways and specified radionuclides and total effective dose equivalents (TEDE), including uncertainties?

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10. Can the analytical method consider various restrictions on land use and site boundaries in calculating concentrations and/or doses, and in determining monitoring strategies?

The workshop followed the following agenda:

AGENDA November 13 1:00 p.m. Welcome and Introductions - Joseph Murphy, Director, Division of Regulatory Applications, Ofice ofNuclear Regulatory Research (RES)/NRC 1:15 Meeting Objectives and Review of Agenda - Cheryl Trottier, Chief Radiation Protection andHealth Efects Branch, RES/NRC \

1:30 Dose Modeling Needs for Licensing Reviews - David Fauver, Of] ice ofNuclear Material Safety and Safeguards (NMSS)/NRC 2:00 Development of Gujdance Related to Dose Modeling and Parameter Selection Needs - Chris Daily,RES/NRC 2:45 BREAK 3:00 D&D Code - Theresa Brown, Sandia NationalLaboratories (SNL) 4:00 RESRAD Code - Drs. Charlie Yu and Ernesto Faillace, Argonne NationalLaboratory (ANL), & Andrew Wallo, DOE 5:00 ADJOURN l November 14 l 9:00 a.m. Review Agenda and Announcements - Thomas Nicholson, RES/NRC i

9:15 MEPAS Code - Drs. John Buck & Gene Whelan, Pacific Northwest NationalLaboratory(PNNL) 10:15 BREAK 10:30 PRESTO Code - Dr. Cheng Hung, U.S. Environmental Protection Agency (EPA) 11:30 LUNCH 1:00 p.m. Panel Discussion on the Strategy for Moving from the NRC Baseline Screening Model - Jack Parrott, NMSS/NRC, Panel Moderator Panel: Theresa Brown,SNL Charlie Yu, ANL l John Buck, PNNL Gene Whelan, PNNL  ;

! Cheng Hung, EPA Chris Daily, RES/NRC '

i David Fauver,NMSS/NRC Mark Thaggard,NMSS/NRC l 2:30 BREAK l 2:45 Resume Panel Discussion 4:45 Closing Remarks ' - John W.N. Hickey, Chief Low-Level Waste and Decommissioning Projects Branch, NMSS/NRC ,

5:00 ADJOURN l

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An important component of the workshop was a panel discussion. The panel was comprised of the invited speakers plus NMSS staff working on decommissioning reviews (see panel members listed above, in the " Agenda"). The panel discussion objective was to provide NRC staff with technical information to consider during the development of guidance on site-specific modeling.

The panel discussion, moderated by Jack Parrott, NMSS, was structured to: (1) provide both a review of the previous NRC staff presentations on the baseline screening model, and a summary of NRC stafflicensing needs; (2) engage the panelists in a second series of questions prepared by the NRC staff and transmitted to them prior to the workshop (see below); and (3) open the discussion, on development of dose modeling guidance, to all workshop attendees.

Technical considerations provided to the panelists prior to the workshop included the following information and questions:

"The guidance being developed by the NRC will recommend the critical modeling components that should be evaluated when moving from the DandD screening model, and default parameters, to site-specific modeling and parameters. The goal of the guidance is to ensure that NRC licensing decisions involving site-specific modeling are consistent, and to allow for a seamless transition from screening to site-specific modeling. This would include the underlying assumptions and justification required to support the site-specific analysis. The NRC is seeking recommendations for criteria which can be used for the acceptability of codes proposed for demonstrating compliance with the license tennination rule on a site-specific basis.

Questions to the panel:

1. What would be the strategy for moving from the NRC baseline screening model to your model, using site-specific information?

In responding, please describe what suggestions you would give to the users of your code that would help them justify moving from the NRC baseline screening model to:

. alternative parameter values,

. alternative mathematical formulations,

. attemative conceptual models (i.e. changing, adding, or deleting pathways).

Please also describe how the user of your code could maintain the concept of the critical group when moving to your code.

2. What information can you provide to the potential users of your software so that it meets basic software QA requirements, and so that modifications to the software are controlled?

3. With regard to software QA procedures, what information can you provide to potential users so that your code can be used with confidence to demonstrate compliance with regulatory requirements?"

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Specific answers to these questions and others posed during the panel discussion are provided in the official workshop transcripts (available in the NRC Public Document Room). The panelists responses were also incorporated into each speaker's technical paper. These technical papers are presented in this NUREG/CP.

ThomasJ. Nicholson,Co-Editor Jack D. Parrott, Co-Editor WasteManagement Branch Low-Level Waste & Decommissioning Project Branch Division ofRegulatory Applications Division of WasteManagement Office ofNuclear Regulatory Research Office ofNuclear MaterialSafety andSafeguards t

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FOREWORD This technical proceedings report, NUREG/CP-0163, was prepared by the NRC staff, using formal technical papers prepared by the invited workshop speakers. The workshop objectives were to both provide the NRC staff and the public with an overview of currently available Federally-sponsored dose models appropriate for decommissioning assessments, and to discuss NRC staff-developed questions related to model and parameter selection criteria, for evaluating the acceptability of the models and parameters for demonstrating compliance with the final rule on " Radiological Criteria for License Termination" (62 FR 39058). This NUREG/CP reports on the public workshop proceedings in a more formal manner than do the official transcripts, which are available in the NRC Public Document Room, by providing documentation of the technical papers presented. The technical papers were prepared by the invited speakers and their colleagues after the workshop. These papers address, in part, questions raised during both; the invited speakers' presentations, and the panel discussion held at the conclusion of the workshop.

NUREG/CP-0163 also provides technical bases supporting the development of decommissioning guidance.

NUREG/CP-0163 is not a substitute for NRC regulations, and compliance is not required. The approaches and/or methods described in this NUREG/CP are provided for information only.

Publication of this report does not necessarily constitute NRC approval nor agreement with the information contained herein. Use of product or trade names is for identification purposes only and does not constitute endorsement by NRC or the invited speakers whose papers are presented.

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DOSE MODELING FOR THE LICENSE TERMINATION RUI E David N. Fauver and Jack D. Parrott Division of Waste Management Office of Nuclear Material Safety and Safeguards U.S. Nuclear Regulatory Commission Washington, DC 20555 INTRODUCTION The U.S. Nuclear Regulatory Commission's new rule on radiological criteria for license termination consists of dose-based decommissioning limits, prudently conservative screening criteria, and a flexible approach to site-specific dose modeling. The staffis continuing to develop guidance for the use of dose modeling to demonstrate compliance with this new rule. A description of the dose modeling aspects of the new rule and an update on the development of guidance to implement the dose modeling will be presented here.

DECOMMISSIONING OPTIONS IN THE LICENSE TERMINATION RULE The new rule allows a licensee to select which decommissioning option is best for its site, through the implementation of an unrestric*ed- or a restricted-use requirement. The basic terms of the new rule are that: (1) The unrestricted-use dose limit is 25 mrem /yr; (2) The restricted-use dose limits are 25 mrem /yr, with restrictions in place, and 100 mrem /yr assuming failure of restrictions; (3) There is a second restricted-use option, with dose limits of 25 mrem /yr, with restrictions in place, and 500 mrem /yr, assuming failure ofrestrictions, that contains more demanding requirements for implementing and maintaining the site restrictions.

THE LICENSE TERMINATION PROCESS From a licensing perspective, the license termination process starts with comparison of site-l 1 NUREG/CP-0163 t

r specific measurements with screening criteria. Screening criteria are essentially preapproved decommissioning limits, analogous to what are referenced now in the Site Decommissioning i

Management Plan action plan. The screening criteria will be radionuclides concentration limits in soil or activity per unit area limits on building surfaces. Essentially, the screening criteria will be an unrestricted use limit that is prudently conservative. Most NRC licensees, including sealed source users, radiographer, and users of short-lived isotopes, should be able to meet the limits in the screening criteria without further analysis to satisfy decommissioning requirements. More complex sites containing uranium or thorium, or significant levels ofloose byproduct material contamination, will probably not meet the screening criteria.

One goal of the guidance for the license termination rule is to develop screening criteria that are conservative but not overly conservative, or bounding. The parameters being put into the screening criteria model are being reviewed closely. It is not intended that the screening criteria model will be applied to the maximally exposed individual, but, rather, to the critical group, as defined in the new rule.

If the site-specific measurements are above the screening criteria, the staff anticipates that licensees will perform site-specific dose assessments. Although site-specific dose assessments may not be necessary for most NRC licensees, the majority of the people attending this ,

workshop are associated with complex sites that will require site-specific dose assessments.  ;

FLEXIBLE SITE-SPECIFIC DOSE MODELING .

The default parameters and scenarios that staffis establishing in the guidance will be used as baseline screening values, to begin the dose assessment process. However, the licensee may l

want to do site-specific modeling because, for example, the assumption of the presence of an onsite pond for fish consumption in the baseline scenario may not be appropriate because the site is in the desert. Or some other site-specific situation may exist where the licensee believes that it is justified to modify some of the defaults in the baseline scenario or parameters. The staff NUREG/CP-0163 2

believes that the most efficient way to get through the dose assessment process is to start with the assumptions in the screening scenario and then to reassess, if appropriate, and explain the reasons for the deviations from the baseline screening scenario. This is as opposed to starting the process from the site-specific situation by developing a set of parameters and scenarios from scratch, without considering the baseline situation.

The development of site-specific parameters and pathways that are not related to the baseline scenarios and parameters will raise many questions during the review, such as why the licensee is making certain assumptions in the model or why certain pathways are not included. Therefore, the stafTbelieves that the dose assessment process needs to start with the baseline screening scenario and parameters and then, if needed, tojustify changes to the pathways, to deal with the site-specific situations.

Site-specific modeling applies to both unrestricted and restricted use. After the preliminary evaluations, the licensee may fmd that, regardless of how much site-specific information is gathered, unrestricted use is not going to be a viable option because of the radionuclides concentrations present and the cost to remediate to an unrestricted-use level. In that case, a licensee may want to go to a restricted-use release. .

There are two aspects of site-specific modeling to consider in a restricted-use situation. First, the licensee models the site with the assumption that the restrictions are in place. For example, if a licensee were to opt for onsite disposal, with 4 feet of cover, there would be a site-specific assessment for that configuration. That assumes that institutional controls will be maintained l such that there will not be intrusion into the disposal. In that case certain pathways, such as a resident farmer consuming food grown onsite and breathing soil resuspended from the surface, may not be significant pathways whereas groundwater may be an important pathway. There is also the second requirement of a 100 mrem / year (or 500 mrem /yr) limit on dose for unrestricted use. This scenario would assume that there is intrusion into the disposal after a failure of institutional controls. In that case, the licensee will have to do site-specific dose assessment for 3 NUREG/CP-0163

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the unrestricted-use situation.

One could envision a situation where some other land use besides the baseline resident farmer scenario could bejustified without restriction. However, staff has not fully developed which scenarios other than the resident farmer would be appropriate for the unrestricted-use situation.

That is an issue that the staff will be working on over the next several months.

GUIDANCE DEVELOPMENT CHALLENGES From a licensing perspective, reasonableness and efficiency need to be considered in the development of the dose modeling guidance. This will help the licensees comply with the regulation and, of course, help the staff do its job reviewing the dose modeling submittals. One of the challenges for staffis to develop, in a guidance document, NRC review criteria, for dose modeling, that will reasonably accept some site-specific parameters and site-specific situations, while also assuring the public that, over a 1000-year period, doses to the critical group will not likely exceed a certain level. If the guidance is developed correctly by the staff and followed closely by the licensees, there will be an efficiency in the dose modeling and review process.

Therefore, NRC is being very careful in the process of developing this guidance, so that a reasonable review process will result.

There are other challenges with the development of this guidance. There is a optimization dynamic between the flexibility of the guidance and the level of effort (and therefore cost) of review for the regulator. The staffis aware of this dynamic and is trying to balance these two competing goals.

That's a brief overview of how dose modeling fits into the process of determining compliance with the dose criteria in the rule and staffs development of the guidance for the dose modeling.

Staffis looking forward to this workshop arid will use the information and comments presented here to help us refine and develop an efficient licensing process.

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DEVELOPMENT OF GUIDANCE RELATED TO DOSE MODELING AND PARAMETER SELECTION NEEDSI Christine Daily, Thomas J. Nicholson and Frank Cardile Division of Regulatory Analysis Office of Nuclear Regulatory Research U.S. Nuclear Regulatory Commission Washington, DC 20555 Abstract NRC staff and contractors are developing guidance on dose modeling and parameter selection needs to suppott implementation of the decommissioning rule. An overview is provided on the decision methodology and imbedded decision framework being developed by the NRC staff and contractors for implementing the decommissioning rule. Information is provided on how dose models may be used in the context of the proposed methodology for decommissioning assessments. Informatic,a and methods being developed for selecting default parameters or replacing default parameters in the DandD code are also presented.

Introduction NRC staff and contractors are developing guidance related to decommissioning assessments including a decision methodology and framework for selecting and using dose models to demonstrate compliance with the final rule on " Radiological Criteria for License Termination" (62 FR 39058)(USNRC,1997b). Additional background information on the license termination rule and its technical aspects are provided in the Generic Environmental Impact Statement (USNRC,1997a). This paper provides information on the decision methodology, decision framework, modeling hierarchy, and parameter analysis process being developed as specific regulatory guidance documents in support of the license termination rule.

Work in Progress and Completed l

Specific products being developed or complend for providing guidance on implemen+1ng the decommissioning rule include:

1. An outline of the decision methodology for selecting and using dose models in the process of decommissioning sites including infonnation on screening approaches which 8

The information presented in this paper represents proposed draft guidance as of November,1997. It is intended as a discussion ofinformation under development and does not represent the final staffposition on guidance for license termination.

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l will be presented in draft NUREG-1549;

2. The DandD software developed by Sandia National Laboratory (see Gallegos and others, 1998 in this NUREG/CP) which is being further refined and tested;

3. A method for selecting default parameters to use within DandD in screening;

4. A method for replacing default parameters in DandD which is also included in draft NUREG-1549; i

5. Detailed documentation of scenarios, calculations, parameter distributions, and default l l

parameter selection as presented in Volume 1 of NUREG/CR-5512 (Kennedy and others, 1992); ,

6. User's manual for the DandD software (NUREG/CR-5512, Volume 2) including (

information about the differences between the calculations listed in NUREG/CR-5512, Volume 1 and those in the updated DandD software; and

7. Documentation of prameter distributions that are used for developing default parameter values and the integrated process used for selecting the default values.

Since no model can work for all situations, the NRC staff also needs:

1. A method for evaluating dose assessments developed using other models (e.g., RESRAD and MEPAS);

2. Quality assurance and documentation criteria for evaluating dose assessments; and

3. Minimum criteria for parameter value selection for other models.

Decision Methodology i

Figure 1 provides a simplified logic chart of the decision methodology being developed by the NRC staff and contractors. The diagram outlines the iterative approach for decision making, and provides a framework for progressing through the decommissioning process. For simple situations, licensees would progress from box 1 to box 7. This approach would be appropriate for using the DandD code with all of the default values, where a calculated dose ofless than 25 mrem can be demonstrated. For such simple cases where the 25 mrem criteria is met, the process is relatively straightforward.

For more complicated cases where the initial pass through the decision methodology does not result in a calculated dose less than 25 mrem, the licensee would better define their situation by proceeding with an evaluation of decommissioning options such as additional site characterization, remediation, and/or restricted use (see box 8 in Figure 1). The process is designed to direct the analyst to consider options prior to making a decision as to restricted versus unrestricted release, and to utilize the most efficient path to decommissioning the site.

The decision methodology (to be presented in draft NUREG-1549) is an iterative process grounded in the real world. The methodology is not a simple pass / fail initial test in that if a licensee cannot demonstrate that the dose is below 25 mrem on the first pass, it does not mean they have failed the process, rather, it means that they are early in the process, and more analysis NUREG/CP-0163 6

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O ScenarioDefrutoni PathwayldentWication I

ReviseModelAssumptions, System ParameterValues,& Pathways Conceptualization andEvaluateResults V

$ Dose Assessment U

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Remedation,and Released? [^ D0 RestricteduseOptions

/ yes ( O Select N Analyze Optiorisinterms ofCost Preferred andLikelihood ofSuccess Op6on O. ALARA ReWremerts Ucense M LicenseTe SueRelease ationand l

Figure 1. Logic diagram for the Decision Methodology.

needs to be performed. An underlying concept in this decision process is that as more site information is gathered, the uncertainty in the dose assessment is reduced, and the calculated dose should also decrease. The assumption is that initially in the screening process licensees do not have much detail on the site, and therefore the assessment should be relatively conservative.

As application of the methodology progresses to utilize more site-specific infonnation, the dose l assessment becomes more realistic, and the calculated dose should decrease. Developing such a l methodology allows for better optimization of decommissioning activities, balancing of costs

) and actions, and an efficien: framework for moving through the decommissioning process.

The decision methodology provides a simple path for those sites which do not warrant a great 7 NUREG/CP-0163 f

deal of analytical complexity. In addition, the methodology allows for the introduction of needed information in a gradual and more efficient manner. Being an interactive process, the methodology facilitates constructive dialogue among the regulators, stakeholder and licensees at appropriate points and in a realistic manner. The methodology provides a transparent and open approach for conducting and evaluating dose assessments for decommissioning resiews.

Purpose of the Screening Model Approach The purpose of having a screening model is to have a baseline to begin the evaluation process.

The first component is default screening using generic models. These default screening models are generic in nature so that the vast majority of sites will be covered. This simplified initial screening approach is warranted because it is easy to use and is cost effective since generic default parameters are used rather than site-specific data. It is also efficient for both the licensee and NRC staff reviewers since sites that pass the screening criteria do not need to collect and submit a lot of site-specific information. If this screening approach with generic defaults is used, there is a high assurance that the site actually meets the criteria and release of the license is appropriate.

The next phase is screening with site-specific data. The generic paramet rs and pathways are adjusted to be more site-specific. These adjustments may include modifications to, or elimination of whole pathways, and modification of specific parameters depending upon the site-specific information. The licensee can use inexpensive techniques to gather additional data. For example, additional infonnation can come from low cost access to regional data such as soil types, depth to ground water, and parameter distributions from the_U.S. Geological Survey or Agricultural Research Service. This relatively inexpensive regional data can help to reduce uncertainties in the parameters used in the model. The approach is based on prioritizing data

. collection, so that the most useful and inexpensive site-specific data is obtained first. For the first iterations though the decision methodology, any revised parameters should fall within the specific ranges associated with the generic default parameter distributions, otherwise additional uncertainty analysis may be required.

Modeling Hierarchy A modeling hierarchy is embedded within the decision methodology. The hierarchy involves a range of modeling, from simple generic anslysis to complex site-specific models.

1. Default Screening The first level of analysis is default screening using generic models in which the NUREG/CR-5512 approach applies. NUREG/CR-5512 and accompanying information provides default scenarios, parameters and pathways to be considered. The only information needed is the site-specific source term.

NUREG/CP-0163 8

2. Site-Specific Screening The next level of analysis is site-specific screening using generic models in which pathways have been varied or eliminated, and cenain default parameters may be replaced with site-specific values. Again, the NUREG/CR-5512 approach applies, but a range of site-specific information may be incorporated.

3. Site-Specific Modeling The final and most complex level of analysis is site-specific nodeling. This modeling approach allows for site-specific models, alternative scenarios, and any vthe pathways or parameters that may be appropriate to the site and the site-specific source term. While it is expected that the NUREG/CR-5512 approach may not be appropriate for all sites and pathways, ponions of the approach may be useful for specific locations and/or pathways for sites that use more complex modeling. In developing a site-specific model, one approach may be to use the relevant aspects of the NUREG/CR-5512 model, and replace only those pathways and parameters where more realistic analysis is needed to demonstrate compliance with the dose criterion. For example, only the ground-water pathway may need to be modeled in greater detail while the remaining pathways are modeled using the methodology as described in NUREG/CR-5512. For site-specific modeling, the licensee must propose a calculational approach for NRC approval. This approach should include an evaluation of uncenainty. NRC staffis in the process of developing additional information for site-specific modeling, including guidance on what kind of information would need to be provided and how it is to be organized. This methodology and guidance will be provided in the final NUREG-1549 and Regulatory Guide DG-4006 (USNRC, 1998).

Technical Basis Documents The NRC staff and contractors are developing the technical bases and their documentation to suppon the decision methodology including models, scenario identification, parameter distributions, and default parameter selection. The following documents have either been issued, or are under development:

1. NUREG-1549 contains decision methods for dose assessment;

2. NUREG/CR-5512 Volume 1 documents the scenarios and calculations;

3. NUREG/CR-5512 Volume 2 will provide a user guide for the DandD software, and information on modifications made to the models and parameters outlined in Volume 1; i

{ 4. NUREG/CR-5512 Volume 3 will provide details on the parameter distributions, the selection methodology for developing default parameters, and the generic uncertainty analysis that is the technical basis for the selection of those default parameters.

9 NUREG/CP-0163

Parameter Analysis The parameter analysis process is designed to evaluate how the model and parameters work together for estimating the dose from residual radioactivity at the site. The underlying basis of the approach is that as the licensee proceeds from screening using default parameter values to site-specific modeling, the estimated dose should decrease. Uncertainty should be reduced by using site-specific information and data. It is assumed that the licensee can obtain a better (more realistic) estimate of the dose using site-specific models and data, and such an estimate will generally be lower than that calculated using generic models and parameters in the default screening approach. The additional resources required to obtain the more realistic dose estimate need only be expended if necessary to demonstrate compliance with the dose criterion or to support a more detailed evaluation of decommissioning options.

The parameter analysis process vas developed to determine if the combination of assumptions and input data lead to results that tre consistent with the intended use of the code. When moving from defaults to site-specific data, or modifying pathways, new information should generally not result in an increase in the calculated dose. The technical approach identifies default parameter sets that limit the probability that the site-specific maximum total effective dose equivalent (TEDE) would exceed the default analysis maximum TEDE. For example, if all defaults are used, the calculated dose should be higher than the dose that would be calculated if any or all of the parameters were changed or pathways were modified. The process should provide assurance that even if the maximum TEDE calculated in the site-specific model exceeds the maximum TEDE determined by the default analysis, the difference would be small.

One objective in conducting this parameter analysis is to support a finding that the final defadt ~

parameters are prudently, but not excessively, conservative. The analysis is also attempting to ,

quantify what prudently conservative means. For exampb, in assessing residential and building scenarios, the NRC staffis determining the range and distribution for default parameters, and is performing analyses for all radionuclides and all pathways. The parameter analysis will assist in defining the default parameter values, valid parameter ranges, and combinations for replacement parameters. The analysis will also assist in determining when uncertainty assessments are needed.

Another important question to be addressed in the parameter analysis is: Given multiple valid sets of default parameter values, how can the default parameter set be chosen? One approach being pursued is to choose a parameter set where parameter values are least extreme within the .;

i criteria of selecting prudent, rather than maximum conservative values, and where all parameters within the set are as equally. conservative as possible and meet an objective, reproducible criterion.

Method for Replacing Default Parameters for DandD l The proposed method for replacing default panuneter values with site-specific information and/or NUREG/CP-0163 10 l

l l

data for the DandD code will be documented in Volume 3 of NUREG/CR-5512 and NUREG-l 1549. The technical basis for identifying the default parameters presently used will be discussed in Volume 3 of NUREG/CR-5512. The process for modifying parameters, eliminating pathways, and eventually moving to other models will be discussed in NUREG-1549. The proposed method will support the decision framework approach of reducing uncertainty by applying additional data. The initial approach will allow limited substitutions, and modifications within certain limits. The licensee cau proceed up to full site-specific uncertainty analysis.

References:

Kennedy, W.E., and D.L. Strenge, " Residual Radioactive Contamination From Decommissioning, " NUREG/CR-5512, Volume 1, U.S. Nuclear Regulatory Commission, Washington, DC, October 1992.

USNRC, " Generic Environmental Impact Statement in Support of Rulemaking on Radiological Criteria for License Tennination of NRC-Licensed Nuclear Facilities," NUREG-1496, Volumes 1-3, U.S. Nuclear Regulatory Commission, Washington, DC, July 1997a.

USNRC,10 CFR 20, et al., " Radiological Criteria for License Termination; Final Rule, and i Radiological Criteria for License Termination: Uranium Recovery Facilities; Proposed Rule,"

Federal Register, Vol. 62, No. 139, Monday, July 21,1997b, pp. 39058-39095.

USNRC, " Decision Methods for Dose Assessments to Comply with Radiological Criteria for License Termination," Draft NUREG-1549, U.S. Nuclear Regulatory Commissinn, Washington, I DC, February 1998 (available in electronic form only at http://techconf.llnl. gov /radcri/ java.html).

USNRC, " Demonstrating Compliance with Radiological Criteria for License Termination,"

Regulatory Guide DG-4006, U.S. Nuclear Regulatory Commission, Washington, DC, February i 1998 (available in electronic form only at http://techconf.llnl. gov /raderi/ java.html).

L 11 NUREG/CP-0163

Use of DandD for Dose Assessment Under NRC's Radiological Criteria for License Termination Rule David P. Gallegos, Theresa J. Brown, and Paul A. Davis Environmental Risk and Decision Analysis Department Sandia NationalLaboratories Albuquerque, NM 87185-1345 Christine Daily Radiation Protection and Health Effects Branch, Office of Nuclear Regulatory Research U.S. Nuclear Regulatory Commission Washington, DC 20555 ABSTRACT:

The Decontamination and Decommissioning (DandD) software package has been developed by Sandia National Laboratories for the Nuclear Regulatory Commission (NRC) specifically for the purpose of providing a user-friendly analytical tool to address the dose criteria contained in NRC's Radiological Criteria for License Termination rule (10 CFR Part 20 Subpart E; NRC, 1997). Specifically, DandD embodies the NRC's screening methodology to allow licensees to convert residual radioactivity contamination levels at their site to annual dose, in a manner I consistent with both 10 CFR Part 20 and the cormsponding implementation guidance developed by NRC. The screening methodology employs reasonably conservative scenarios, fate and transport models, and default parameter values that have been developed to allow the NRC to quantitatively estimate the risk of releasing a site given only information about the level of contamination. Therefore, a licensee has the option of specifying only the level of contamination and running the code with the default parameter values, or in the case where site specific information is available to alter the appropriate parameter values and then calculate dose. DandD can evaluate dose for four diffemnt scenarios: residential, buikling occupancy, building mnovation, or drinkmg water. The semening methodology and DandD are part of a larger decision framework that allows and encourages licensees to optimize decision on choice of alternative actions at their site, including collection of additional data and information. This decision framework is integrated into and documented in NRC's technical guidance for decommissioning.

l l

1 INTRODUCTION DandD is intended to be implemented within the structure of NRC's decommissioning decision j framework (to be documented in NUREG-1549'). This framework is described in Section 2 of l this document. This framework allows for NRC control of the risk of releasing sites erroneously, l

' - Methods for Dose Assessment to Comply With Radiological Cnteria for License Termination." NUREG-1549, U.S.

Nuclear Regulatory Commission, Washington, DC (in preparation).

13 NUREG/CP-0163

while at the same time not being overly restrictive in their requirements for site remediation.

Licensees wouki be allowed to define the most cost-effective decommissioning and license termination strategy by evaluating alternative actions at their site, including possible reductions in uncenainty that would reduce overall mmediation costs. Because of the nature of the DandD models and default parameter values, the NRC would not expect licensees to define concentration clean-up levels based on preliminary DandD dose tabulations that fail to meet 10 CFR Part 20 dose criteria; instead, licensees would be encouraged to evaluate the cost of added information and the value it adds in better defining remedial actions.

In general, the objective of the software, Decontamination and Decommissioning (DandD), is to provide a user-friendly and somewhat automated interface to the Nuclear Regulatory Commission's (NRC) dose assessment and screening methodology for site assessment against the Radiological Criteria for License Termmation Rule in 10 CFR Pan 20 Subpart E [NRC,1997].

DandD assists NRC licensees who have requested termmation of their license and who, in some cases, must decontaminate lands and structures as part of the decommissioning process. The software does this by providing a tool that allows licensees to translate residual radioactive contammation levels at their site into total effective dose equivalect (TEDE) by analyzing and modeling the set of NRC-prescribed scenarios of future land-use. DandD contains models of the 7ansport and exposure pathways associated with each of the scenarios, requiring only information m source concentration from the user. The user may, if they choose, supply site-specific aformation on other parameters (e.g., physical properties of the site) if available and defensible.

Specifically, DandD is the software impkmentation of NRC's screening methodology transport and exposure models for assessing human heakh and safety against the dose requirements set forth in 10 CFR Part 20 Subpart E [NRC,1997]. For this discussion, screening refers to the release of a site where little or no site-specific information is known or used, other than level of contamination. To provide useful and defensible screening level cakulations, the NRC has developed reasonably conservative scenarios, pathway models, and parameter values, and has implemented these in DandD. " Reasonably conservative" implies that the calculated doses are more likely to be overestimates of the actual dose rather than accurate estimates or underestimates, but at the same time are not necessarily worst case estimates. As a resuh, the scenarios and models implemented in DandD are relatively simple. To p;rform these screening calculations, the DandD software automates the scenarios, models, mathematical formulations, and assumptions documented in NUREG/CR-5512, Volume 1 [ Kennedy and Strenge,1992] and Volume 2. The generic modeling approach defines radiation exposure scenarios to address residual radioactive contamination inside buildings, in soils and in ground water. For buiklings, two scenarios are presented. The scenarios relate either volume or surface contamination levels to estimates of the annual TEDE received during each year of exposure with the conditions defined in the scenarios.

For the simplest level of analysis (previously referred to as Level I screening), the user is required to provide a mmanum amount of site-specific information. In general, only m ' formation about source concentration is rerluired for their site for this level of analysis. This level of analysis has

• Residual Radmeetive Contamination From D~== Wing. User's Manual. NUREGCR-5512. Volume 2. U.S.

Nuclear Regulatory Commission. Washington, DC (in preparauon)

NUREG/CP-0163 14

effectively been automated in DandD, and therefore provides certain licensees with a simple and cost-effective method to demonstrate compliance. This level of analysis uses deterministic values for all model parameters. At the final release of DandD Version 1.0, the default parameter values will have been defined through e systematic process of assessing the variability of each parameter and then defining default values that produce generic dose estimates that are unlikely to be exceeded at any real site. The derivation sad final values of the defauk parameter values for DandD Version 1.0 will be discussed in NUREG/CR-5512, Volume 3' (i.e., default parameter values in NUREG/CR-5512, Volume I will not be used).

If a licensee has site-specific information for certain parameters, they may choose to replace the defauh parameter values with alternative values, and employ the defauh transport and exposure models. This level of analysis, which can easily be conducted with DendD, was previously referred to as level 2 screening. Licensees are not required to conduct the "Ievel 1" screening calculations prior to proposing changes to parameter values.

As discussed above, the defauh parameter values for the NUREG/CR-5512 modeling (which are implemented in DandD) are based on probability distributions representing the variability across the country for physical parameters, and within the screening group for behavioral and metabolic parameters. As a consequence, the licensee would likely need little supporting information to defend significant changes to the parameter values. This approach of moving away from the

" reasonably conservative" values used in the NUREG/CR-5512 modeling could be used by all sites until the point that funber reduction in simulated dose wouki require model changes. This would necessarily require the licensee to step away from using DandD. For example, those models might be muhi-dimensional flow, transpon or exposure models. At that point, new model parameter values would have to be developed and supported by the licensee.

DandD produces reports in NRC-defined and accepted text and graphics formats that will allow the NRC to efficiently assess compliance with the 10 CFR Pan 20 dose criteria and to determme if more detailed modeling should be required.

2 USE OF DandD WITHIN THE NRC D&D DECISION FRAMEWORK A logical, consistent decision process is viewed as a useful tool that will support licensee plannmg of decommissioning activities and NRC review oflicense termination requests. To suppon this process, a decision methodology has been developed to suppon implementation of the dose assessment requirements in 10 CFR Part 20 Subpart E (see Figure 1). The decision process encourages an assessment of the entire range of dose modeling options from which a licensee may choose, from changing a single parameter to changing mukiple parameters and modifying pathways or models.

l 3

Residual Radioactive Contamination From Decommissioning. Parameter Analysis. NUREGCR-5512. Volume 3. U.S.

Nuclear Regulatory Commission, Washington, DC (inr y..&m) 15 NUREG/CP-0163

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Figure 1 - NRC f+-- "-t dec. don fra.nework As discussed above, generic exposure scenarios and pathways have been defined based on the NUREG/CR-5512 methodology [ Kennedy and Strenge,1992] and can be used by licensees who are applying the default scenarios and parameters using the DandD software. The default screening scenarios and pathways provide the licensee with a simple method of demonstrating compliance using little site-specific information. The generic models and default parameters are intended to estimate a reasonably conservative value of the dose that the average member of the critical group could receive. The default parameters were developed probabilistically to control time risk associated with releasing a site based on source terin data alone. Figure 2 illustrates where portions of the framework have been predefined for the " Level 1" screening analyses.

Figure 2 also illustrates where DandD can be used to execute certain steps in the process. These will be discussed under each step below.

For licensees with more complex decomnussioning situations, the decision process supports the modification of model parameters to allow site specific factors to be taken into account while still using the default models. This allows a licensee to use site-specific values in place of some or all of the default parameters. Thus, the new dose estimates will have a high likelihood of being lower than the previous estimates, but should still have a high likelihood of being lower than the actual NUREG/CP-0163 16

g Aashnneson of Erkiang Dans Pre defined for DandD U Level 1 Analysis O Scener6o Denniton/ l Pupuny Manuncadon j

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dose for a particular site based on the use of the default models. The site specific data are used to support modifying or eliminating a particular scenario or pathway, or to demonstrate that a parameter or group of parameters can be better repmsented by site specific values. Alternative exposure scenarios may be appropriate based on site-specific factors that affect the likelihood and extent of potential future exposure to residual radioactivity.

Step 1: The first step of the decision process involves gathering and evaluating existing data and information. Licensees must provide information regarding the types and amounts of radioactive material they possessed on their site. The licensee may start the process with other defensible site-specific information (e.g., physical properties of the site), and can input this infonnation into the DandD code, either through modifications to default parameter values or through elimination l ofpathways.

1 Step 2: The second step in the decision process involves defm' ing the scenarios and pathways that am important for the site dose assessment. For a generic application, this step has already been completed by the NRC, based on the generic scenarios and pathways for screening that have been 17 NUREG/CP-0163

defined and described in NUREG/CR-5512, Volume 1 [ Kennedy and Strenge,1992).

These generic scenarios and pathways have been implemented in the DandD code. The four exposure scenarios are:

o residential, e building occupancy, o building renovation, and e drinking water.

In the NUREG/CR-5512 methodology, and in DandD, the exposure pathways for the building scenarios are external exposure, inhalation exposure, and secondary ingestion. The residential scenario considers external exposure, mhalation, and the following ingestion pathways: drinkmg water, food grown from irrigation water, land-based food, soil, and fish. The types of land-based food considered for the residential scenario are leafy vegetables, other vegetables, fruit, grain, beef, pouhry, milk, and eggs. Three types of animal feeds are considered: forage, stored grain, and stored hay. The drinkmg water and residential scenarios use a simple three-box water-use model to account for radionuclides decay, progeny ingrowth, and environmental transport. 'Ihe three boxes (or layers) in the water-use model are the surface soil, unsaturated soil, and the aquifer.

i Step 3: This step involves system conceptnahration, which includes conceptual and mathematical model development and assessment of parameter uncertainty. For a generic application, this step has already been completed by NRC (i.e., the models described in NUREG/CR-5512, Volume 1).

In addition, these models and the defauh parameter values have been automated and implemented in the DandD software. For more complex sites, licensees may use site-specific conceptual and mathematical models.

l Step 4: This step involves the dose assessment for the site, which means running the DandD or l other appropriate models with the applicable site-specific source term. l The framework is designed such ths.t the level of complexity and rigor of analysis conducted for a j given site should be commensurate with the level of risk that the site poses. Although all sites are  !

expected to step through Steps 1 through 7, the amount of work that goes into each of these steps - l should be based on the expected levels of contamination and the health risks they pose. For  ;

example, a site with a scaled source would obviously not be expected to conduct calculations (if any) that are the same complexity as a site with extensive soil and groundwater contamination. l l

Step 5: The fifth step is the first major decision point in the methodology, and involves answering the question of whether the dose assessment results are less than the dose critenon of 25 mrem /yr in 10 CFR Part 20, Subpart E. DandD provides graphical and text output of TEDE to evaluate l the resuhs of the analysis. In addition, the user can view the dose history for any radionuclides, for ;

all radionuclides, and for any path within a given scenario.

l NUREG/CP-0163 18 I

)

IF THE RESULT IN STEP 5 IS THAT THE CALCUIATED DOSE IS LESS THAN OR EQUAL TO 25 mremly, THEN:

( Step 6: If the result in Step 5 is that the 25 mrem /y criterion has been met, the licensee can proceed to satisfy any remammg ALARA requirements. Conducting ALARA analyses and j evaluating if the doses are ALARA are beyond the scope of the DandD software.

Step 7: In this step the final documentation is compkted, including documenting any survey results used to calculate the source tenn and the results of the dose cMeulations. DandD provides a written report in a format that is acceptable for NRC's review and evaluation of the site's j ability to meet the dose criteria in 10 CFR Part 20. I l

IF THE RESULTIN STEP 5 IS THAT THE CALCULATED DOSE IS GREATER THAN 25 mremly, THEN:

l Step 8: The purpose of this step is to define options for proceedmg with the license termmation process. Note that the framework would not recommend that a licensee define concentration ckan up goals after the initial iteration of simple dose cakulations until other options have been evaluated that could reduce the cakulated doses and the cost of remediation, if it is necessary at j all. There are basically three options that the licensee couki apply either alone or in combination:

! Option 1 - Activities that reduce uncertainty (information/ data collection), Option 2 - Activities that reduce contamination (remediation), and Option 3 - Activities that reduce exposure (land-use restrictions).

I Only a limited number of sites will need to perform complex dose assessment and options  !

analyses, with most sites performing an options analysis that is relatively simple and straightforward. For example, a site with a small, contamed source of contammation that is i obviously simpk to remove wouki not perform extensive analyses on large suites of alternative data collection and remediation options. The same may be true for certain compkx sites, where the configuration of the contamination, site conditions, or regulatory requirements cause the options for proceeding forward to be relatively limited and straightforward. The sites which will i

benefit the most from this options analysis are those with complex contamination situations where l this process can be used to analyze a variety of simple and compkx options and define the most effective and cost-efficient decontamination and decomrmssioning strategy.

The first option, activities that reduce uncertainty, begins by looking at the default parameter

values in the NUREG/CR-5512 model and what they represent. The default parameter values for

the NUREG/CR-5512 modeling (that have been implemented in DandD) are being developed based on probability distributions representing the expected variability across the country. A probabilistic parameter analysis is being performed to select a set of default parameters that meet the NRC's requirements to control the risk associated with releasing a site based only on source term information. The risk is controlled by NRC sekcting screening parameters that, as a set and within the context of the specified model, provide a specified kvel of confklence that the dose estimate will go down as more site specific information is used in modeling. In addition, the parameters are selected in a manner that controls the amount by which the dose could exceed the 19 NUREG/CP-0163 l

screening dose. The parameter analysis also provided information regarding the valid ranges for site specific parameter changes that a license could propose without an additional uncenainty analysis. As a consequence, the licensee needs less supporting information to defend changes to the parameter values that are within the limits specified in the parameter analysis. This is important in evaluating the relative worth of collecting additional data on these parameters under Step 9.

The second option listed above is based on actual reduction of the quantity of residual radioactivity remaining on the site. Information that may be useful for evaluating this option is contained in the final environmental impact statement for 10 CFR Part 20, Subpart E (NUREG-14%) and DG-4006. If the third option, reduction of exposure, is pursued, the licensee is required by 10 CFR Part 20, Subpart E, to demonstrate that unrestricted release is not ALARA.

This is discussed in Regulatory Guide DG-4006.

DandD can be used to a cenain extent under Step 8 to identify certain options by evaluating the consequences of possible reductions in uncertainty or possible reductions in contamination.

Step 9: This step involves the analysis of options, primarily in terms of cost and the likelihood of success. To evaluate the likelihood of success, an analysis of the potential outcome (consequence analysis) will need to be performed for each of the options identified in Step 8. The consequence analysis should be no more complex than necessary to support a reasonable and cost-effective evaluation of the options. The cost and time required to complete each option must be estimated, and the analysis should also address the uncertainty associated with each potential cutcome. The desired endpoint is a determination of the likelihood or probability that carrying out a given option will resuk in meeting the criteria of 10 CFR Part 20, Subpart E.

'Ihe result of the activities performed under Step 9 is a logically organized list of options, and the corresponding cost, likelihood of site release (probability of success), and other imponant considerations given that the option is pursued. In some cases, the decision regarding the preferied option will be obvious; for example, a low cost of success and failure, high probability of success option will generally be selected over a high cost, low probability of success option, assuming the regulatory requirements are equal. However, the preferred option will not always be obvious, and additional analysis may be required for sites attempting to balance complex issues. At this point in the decision process, the idea is not to permanently eliminate options from further consideration, but rather to select the optimum approach under the current state of knowledge.

. This step in the decision framework should support an evaluation of the cost and time impacts of both success and failure. Generally, low cost / high likelihood of success options, or combinations of options, are preferred. This step should also include ALARA considerations (see DG-4006), in terms of cost / benefit calculations as well as qualitative considerations. With regard to costs, the licensee should consider that if the option (s) selected are successful, the license will be released and further costs will be minimiwA. However, if the selected option (s) are unsuccessful, it may be necessary to perform additional characterization or remediation, or there may need to be an evaluation of restricted use (with its associated costs).

NUREG/CP-0163 20

Generally, Step 9 is outside tle scope of DandD.

Step 10: Once the various options have been evaluated, the pmferred option can be selected.

This step is outside the scope of DandD.

[ Step 13: For those ram situations where the licensee is unable to meet the criteria of 10 CFR Part 20, Subpart E, it may be necessary to maintain the license. Consequently, this step does not represent a permanent resolution, but an interim action until the problem can be resolved.]

Step 11: Under this step, the preferred option is implemented. For example, if additional site characterization was the selected option, this is the step where the data collection would be performed. This Step is outside the scope of DandD.

Step 12: Once the preferred option has been implemented, the model assumptions, parameter values, and pathways (as appropriate) are revised. Within DandD, this may mean a change in a deterrr_inistic parameter value (default or otherwise), or an elimination of a pathway through the appropriate parameter changes. If a specific scenario can be defensibly ruled out, then it is simply not analyzed in DandD. To support a future request for license termination, any site survey results, parameter data, or laboratory tests should be carefully documented.

Step 4: The revised source term and parameter values are used in the next iteration of the dose assessment. Depending on the application, the licensee can leave the original default model assumptions and pathways unchanged, and continue to use the DandD software. Note that in other more complicated situations a licensee might seek to modify these assumptions and pathways or apply different models (and hence different codes / software).

Step 5: The revised dose assessment is performed to detennine if the calculated dose meets the requirements in 10 CFR Part 20, Subpart E.

IF THE CALCULATED DOSE IS STILL GREATER THAN 25 miemly, THE I2CENSEE PROCEEDS ONCE AGAIN TO STEP 8.

If the calculated dose is less than or equal to 25 mrem /y, the licensee can proceed with license termination as described in DG-4004.

3 WORKSHOP QUESTIONS This section addresses the specific questions posed prior to and during the " Workshop on Review of Dose Modeling Methods for Demonstration of Compliance with the Radiological Criteria for License Termination."

21 NUREG/CP-0163

3.1 Question 1 Please describe the history of the analytical method's development (e.g., who developed it)? For what purpose was it developed? Who were the sponsors? Is there documentation on the code such as a " Users' Manual"?)

The Decontamination and Decommissioning (DandD) software package has been developed by Sacdia National Laboratories for the Nuclear Regulatory Commission (NRC) specifically for the purpose of providing a user-friendly analytical tool to address the technical dose criteria contained in NRC's Radiological Criteria for License Termination rule (10 CFR Pan 20 Subpart E; NRC, 1997). Specifically, DandD embodies the NRC's screening methodology to allow licensees to convert residual radioactivity contamination levels at their site to annual dose, in a way consistent with both 10 CFR Part 20 and the corresponding implementation guidance developed by NRC.

The computational and analytical portion of DandD implements the scenarios and models found in NUREG/CR-5512, Volume 1 [ Kennedy and Strenge,1992). The final Users' Manual for DandD 2

is i i preparation and should be completed in 1998 ,

3.2 Question 2 What transport mechanisms, scenarios, and exposure pathmiys are considered?

Within DandD, the transport mechanisms, scenarios, and exposure pathways have been defined by the NRC, based on the generic scenarios and pathways for screening that have been developed arxi described in NUREG/CR-5512, Volume 1 [ Kennedy and Strenge,1992).

The four generic exposure scenanos implemented in DandD are:

• residential, e building occupancy, e building renovation, and e drmking water.

In the NUREG/CR-5512 methodology, and in DandD, the exposure pathways for the building scenarios are external exposure, inhalation exposure, arxi secondary ingestion. The residential scenario considers external exposure, inhalation, and the following ingestion pathways: drmkmg water, food grown from irrigation water, land-based food, soil, and fish. The types ofland-based food considered for the residential scenario are leafy vegetables, other vegetables, fruit, grain, beef, pouhry, milk, and eggs. Three types of animal feeds are considered: forage, stored grain, and stored hay. The drinking water arxi residential scenanos use a simple three-box water-use model to account for radionuclides decay, progeny ingrowth, and environmental transport. The three boxes (or layers) in the water-use model are the surface soil, unsaturated soil, and the aquifer.

Because of concerns about potential ground-water contammation from residual radioactive l contamination in soil, a generic water-use model was developed to permit evaluation of the annual TEDE for drinking water from wells (drmkmg water scenario). The generic water-use model was NUREG/CP-0163 22

also used in the evaluation of multiple pathways associated with contaminated soil. The generic treatment of potentially complex ground-water systems provides a conservative analysis that may only suggest when additional site data and more sophisticated modeling are warranted.

3.3 Question 3 How are parameter values determinedfor input? (Can uncertainties be incorporated into the parameter distributions and the subsequent dose calculations?)

The defauk parameter values for the NUREG/CR-5512 modeling (implemented in DandD) are being developed based on a probabilistic analysis using input parameter distributions representing the expected variability across the country. A probabilistic parameter analysis was performed to select a set of default parameters that meet the NRC's requirements to control the risk associated with releasing a site based only on source term information. Risk is defined as the risk that a site will be released when it exceeds the dose criterion. The risk is controlled by selecting screening parameters that, as a set and within the context of the specified model, provide a specified level of confidence in the dose estimate and control the amount by which the dose could exceed the criterion. The parameter analysis also provided infonnation regarding the valid ranges for site specific parameter changes that a license could propose without an additional uncertainty analysis.

For the screening calculations that use the defauh parameter values, it is important to note that uncenainty has implicitly and quantitatively been incorporated in the analysis because of the nature of the process used to define the defauhs. For user supplied changes to the defauh parameter values, DandD restricts the range of possible values that can be input. The NRC and SNL are presently conducting analyses to evaluate the uncenainty in output when alternative parameter values ait used. In addition, the NRC will provide guance for altering parameter values and accounting for uncertainty.

l 3.4 Question 4 What radionuclides and chemicals which can affect radionuclides transport are considered? (Is decay andin-growth considered? To what extent?)

DandD includes all 224 NRC-listed radior;uclides and automatically.models chain decay and ingrowth of daughters. The code gives the user options on how to report doses from progeny including reponing implicit progeny doses separate from the parent or reponing implicit progeny doses as pan of the parent doses. The code does not model the fate and transport of hazardous chemicals.

3.5 Question 5 What are the time and spatial geometry limitations inherent in the analytical method?

Certain analytical practical limits have been incorporated in the DandD code to constrain the evaluation period. For the residential scenario, although the regulatory time period is 10' years, 23 NUREG/CP-0163 t

the maxunum analysis time is 10' years. For the building occupancy scenario, akhough the typical analysis period is I to 70 years, the analytical maxunum in the code is again 10' years.

In terms of spatial considerations, the system geometry is defined by NUREG/CR-5512 transport process models (see Kennedy and Strenge,1992]. In general, the user cannot modify system  ;

geortetry in DandD, although pathways may be eliminated through modifications in parameter values. In addition, for the residential scenario, the user may specify the number of different layers in the unsaturated zone. Spatial geometry is not considered in many cases due to the nature of the models.

3.6 Question 6 To what extent can alternative remedial actions be assessed and compared (e.g., con;parison of concentrations, doses, and costs)?

Muhiple executions of DanJD can be used to compare ahernative parameter values and the corresponding concentration levels to provide the necessary resuhing doses that would resuk in compliance with 10 CFR Part 20. These analyses are contingent upon the model assumptions inherent in DandD. Based on these resuking proposed cleanup levels, estimates can be developed outside of DandD for the cost to collect the necessary data and the costs of remediation.

However, because of the nature of the DandD models and defauk parameter values, the NRC wouki not expect concentration clean-up levels to be defined based on preliminary DandD dose calculations that fail to meet 10 CFR Part 20 dose criteria; rather, the cost of added information and the value it adds in better defining remedial actions should be provided.

DandD is intended to be implemented within the structure of NRC's decommissioning decision framework (documented in NUREG-1549'). This framework is described in Section 2.0. This process has been defined to allow the NRC to control the risk of releasing sites erroneously, while at the same time not being overly restrictive in the requirements for site remediation. This would allow licensees to define the most cost-effective decommissioning and license termmation strategy by evaluating ahernative actions at their site, including possible reductions in uncertainty that would reduce overall remediation costs.

3.7 Question 7 To what extent has the dose model been tested and included in bench marking studies?

Final functional testing of the DandD software is currently in process. Testing and documentation are expected to be completed by March,1998. Extensive testing of baseline models was completed in 1994. A beta test of the software was conducted and completed in 1996.

Documentation of the resuhs of this beta test is expected to be published in early 1998. Extensive testing of the user interface has been completed and will be documented in the final test report. A model comparison is planned for 1998, where the DandD model assumptions will be compared against other dose code model assumptions. DandD has not been included in any formal bench marking studies.

NUREG/CP-0163 '24 J

3.s Question s To what extent can the analytical method handle complex: (a) source tenn characterization; (b) multiple source tenns; (c) hydrologic and hydrogeologic co utitions; (d) exposure pathway combinations; (e) remedial methods linked to cost and monitoring progmms; and (f) ALARA considerations.

3.8.1 Source Term Characterization The source tenn in DandD is treated through detenninistic input of radionuclides source concentrations (activity / area or activity / volume). It is expected that the he wouW conduct an evaluation of the source outside of DandD to define the detenninistic input value for input into the code. DandD then assumes a homogeneous source concentration across the entire area or volume of the appropriate scenario. The NRC has developed guidance (DG-4006) for h=:s i to define source concentrations for use in DandD.

3.8.2 Multiple Source Terms Multiple source terms wouM be h-IIM in DandD in one of two ways. In the first, ddierent sources may be superimposed and equivalent source concentrations defined. DandD wouM then evaluate the composite effect of all the sources. In the second approach, ddferent sources could be evaluated within DandD independently. Total dose may be denved from the sum of the independent analyses or this infonnation may be used to guide options identification for data collection or remediation. Because of the nature of the transport and exposure models in DandD, multiple sources cannot be treated as spatially distributed.

3.8.3 Hydrologic and Hydrogeologic Conditions The site hydrologic and hydrogeologic conditions in DandD are based on the transport models in NUREG/CR-5512, Volume 1. Certain hydrogeologic conditions may be ahemd by changes in parameter values; however, ahernative models are not possible in DandD, except through elimination of scenarios, pathways, and assumptions by changes in parameter values. Increased complexity in hydrologic and hydrogeologic conditions is expected to be handled by following the D&D Decision framework and identifying where increased complexity is supportable with site-specific information and where it is necessary and appropriate.

l As an ahernative, DandD does allow the user to import concentrations in the groundwater that have been derived from another model In this case, the user wouM conduct flow and transport calculations outside of DandD, and derive from these calculations, a representative groundwater concentration that is then read into DandD. The pathway transport calculations in DandD then proceed as before.

l 25 NUREG/CP-0163 )

3.8.4 Exposum Pathway Combinations Mukiple simultaneous pathways are automatically handled in DandD (see Sections 2 and 3.8.2).

'Ihe source is pamtioned among the different pathways based on the process models and parameter values. DandD reports doses from all pathways and radionuclides combined, dose from each radmnuclide, and dose from each pathway. Pathways may be eliminated in DandD by defining appropriate parameter values.

3.8.5 Remedial Methods IJaked to Cost and Monitoring Programs Remedial methods hnked to cost and monitoring programs are outside the scope of DandD; however, it is expected that these wouM be treated through implementation of the NRC Decision Framework 3.8.6 ALARA Based on the ALARA analysis requirements AM in DG-4006, DandD is capable of conducting the individual dose portion of the analysis. Cost modeling wouM be conducted outside of DandD.

3.9 Question 9 Does the dose model include software graphical output for ponraying dose versus time for wrious exposure pathways and specified radionuclides and total effective dose equivalents including uncenainties?

DandD provides the following output, in both graphical and text formats:

• TEDE vs. time for each isotope e TEDE vs. time for each pathway e calculation of time and magnirude of maximum TEDE o simultaneous display of all or any TEDE vs. time curves The software allows the user to aher the graphical output if desired. There is no explicit treatment or display of uncertainty within DandD, except in the process that has been used to derive defauk parameter values, where uncertainty has been explicitly treated.

3.10 Question 10 Can the analytical method consider various restrictions on land use and site boundaries in calculating concentrations and/or doses, and in determining monitoring strategies?

DandD can be used to conduct dose calculations during the period when site land-use restrictions fail, in which the compliance assessment wouM be against restricted relea.se dose criteria defined in 10 CFR Part 20.1403. In this case, the user wouM likely be assuming that the NRC default scenarios were operable. DandD can also be used to conduct dose calculation during the period NUREG/CP-0163 26

when restrictions are in place by eliminating or altering pathways appropriately. As with any other code, this would be acceptable if the model assumptions in DandD are appropriate and defensible. In the case of determining monitoring strategies, the DandD output can be used to quickly define important pathways and nuclides that contribute most to dose.

REFERENCES Kennedy, W.E., Jr., and Strenge, D.L (1992), Residual Radioactive Contamination From Decommissioning, Technical Basis for Translating Contammation levels to Annual Total Effective Dose Equivalent, NUREG/CR-5512, Vol 1, PNL-7994, U.S. Nuclear Regulatory Comnussion, Washington, DC.

NRC (U.S. Nuclear Regulatory Commission) (1997a), Radiological Criteria for License Termmation; Final Rule, Federal Register: July 21,1997, Volume 62, Number 139, pp.

39057-39092.

27 NUREG/CP-0163 1

l

' U.S. NUCLEAR REGULATORY COMMISSION DOSE MODELING WORKSHOP, NOV.13-14,1997, RESRAD MODEL PRESENTATION C. Yu, E. Faillace, and S.Y. Chen A. Wallo III, W.A. Williams, H. Peterson, and S. Domotor Argonne National Laboratory U.S. Department of Energy Argonne,IL 60439 Washington, D.C. 20585 ABSTRACT:

RESRAD was one of the multimedia models selected by the U.S. Nuclear Regulatory Commission (NRC) to include in its workshop on radiation dose modeling and demonstration of compliance with the radiological criteria for license termination.This paper is a summary of the presentation made at the workshop and focuses on the 10 questions the NRC distributed to all participants prior to the workshop. The code selection criteria, which were solicited by the NRC, for demonstrating compliance with the license termination mle are also included. Among the RESRAD family of codes, RESRAD and RESRAD-BUILD are designed for evaluating radiological contamination in soils and in buildings. Many documents have been published to suppon the use of these codes. This paper focuses on these two codes. The pathways considered, the databases and parameters used, quality control and quality assurance, benchmarking, verification and validation of these codes, and capabilities as well as limitations of these codes I

are discussed in detail.

1 INTRODUCTION j

On November 13-14,1997, the U.S. Nuclear Regulatory Commission (NRC) conducted a workshop on radiation dose modeling and demonstration of compliance with the radiological criteria for license termination. The RESRAD model, developed at Argonne National Laboratory (ANL) for the U.S. Department of Energy (DOE), was one of the models the NRC selected to include in the workshop. The RESRAD model and code are used to derive site-specific guidelines for allowable residual concentrations of radionuclides in soil and to calculate doses, risks, and guideline values (Yu et al.1993b). Argonne's presentation focused on the 10 questions the NRC distributed to all panicipants prior to the workshop. The NRC also asked participants to suggest criteria for selecting code for demonstrating compliance with the license termination rule. On the basis of its experience in developing and using computer models for l decontamination and decommissioning, Argonne recommended the following criteria for '

selecting computer code for demonstrating compliance with the license termination rule:

i a

Code should have a users' manual and other supponing materials document-ing its methodology and databases / parameters.

29 NUREG/CP-0163

• Code should be benchmarked, verified, and undergo quality assurance (QA) and quality control (QC) procedures.

• Code should be easy to use and the results reproducible.

• Code should have a state-of-science dose conversion factors (DCFs) database and transfer factors database.

- Code should be able to evaluate both soil and building contamination.

- Code should address both volume and surface contamination with varying thiclaiesses and areas, with or without cover.

• Code should address time-dependent processes such as ingrowth and decay, in both the source and during transport in the environment.

• Code should address radionuclides-dependent processes such as leaching, transfer, and migration (retardation).

• Code should support estimations of both individual dose and average collective dose and risk.

• Code should include, or allow users to construct, all potential exposure scenarios.

• Code should have the capability to accommodate modification of parameters as well as selection / suppression of pathways.

• Code should be able to perform sensitivity analysis and probabilistic uncertainty analysis.

• Code should have specific models for special radionuclides (e.g., tritium, carbon-14, and radon-222 and radon-220) that behave differently in the environment and in buildings.

• Code should have a sufficient radionuclides database, and it should be easy to add radionuclides if needed (under QA/QC conditions).

NUREG/CP-0163 30

2 ARGONNE'S RESPONSES TO NRC QUESTIONS The following sections present the questions asked by the NRC regarding the RESRAD code and Argonne's responses.

2.1 Question One

1. Please describe the history of the analytical method's development (e.g., who developed it? For what purpose was it developed? Who were the sponsors? Is there documentation on the code such as a " users' manual"?).

Development of the RESRAD model and code was initiated in the early 1980s. The code has evolved into its present form as a result of extensive reviews, application experience, and scientific development. The model and code were developed as integral parts of DOE guidelines for control of residual radioactive material issued as interim guidance in 1984-85; incorporated into the DOE public and environmental radiation protection directive, Order DOE 5400.5 in 1990; and proposed as part of Title 10, Pan 834 of the Code of Federal Regulations (10 CFR 834)in 1993.

During 1983 and 1984, DOE conducted workshops to support the development of its guidelines for controlling residual radioactive material. The workshops were attended by ,

representatives from DOE (Offices of the Secretary, Nuclear Energy, Defense Programs, Energy Research, General Counsel and Environment and Policy and DOE field offices); the national laboratories (Argonne,IAs Alamos, Oak Ridge, and Pacific Northwest); industry (The Aerospace Corp.; Bechtel National, Inc.; Bendix Field Engineering; EG&G; Jacobs Engineering; and UNC Nuclear Industries); the U.S. Environmental Protection Agency (EPA); and the NRC. These.

workshops resulted in the development of draft interim guidelines issued for review and comment in 1984. The interim guidelines contained generic soil concentration criteria (based on models that were predecessors of RESRAD) that were to be the maximum concentration levels that could not be exceeded and that would be subjected to the ALARA (as low as reasonably l achievable) process to determine how far below the criteria authorized limits for a cleanup should be set. The generic soil concentration criteria approach was generally found to be l

unacceptable because of its inflexibility and because it was difficult to address ALARA requirements without specifically estimating like doses to populations associated with alternative ,

i cleanup limits. Current DOE requirements and the RESRAD model and code were developed on the basis of experience associated with early effects.

DOE used input from field and program elements attempting to apply the interim guidelines to determine that a standardized dose /ALARA-based approach would be the most I flexible and cost-effective way to establish protective authorized limits for the release of DOE real propeny. Initially, DOE guidelines simply required that authorized limits for the release of property be developed to be as low as is reasonably achievable below the 100 mrem per year 31 NUREG/CP-0163

primary dose limit. Later guidance recommended the use of a dose constraint of about one quarter of the primary dose limit as the cap for the ALARA analysis to ensure that multiple sources would not result in public exposures exceeding the "all sources" primary dose limit.

The RESRAD code was developed for use in conducting dose assessments and supponing ALARA process analyses necessary to meet DOE requirements. The initial criteria used by DOE to develop the RESRAD model and code were as follows:

• The model

- must be sufficiently flexible to handle multiple radionuclides, all significant pathways, numerous land uses, and various spatial configurations and other site-specific considerations.

- should be based on the best peer-reviewed science available.

- should be able to handle special radionuclides such as tritium, carbon-14, and radon.

• The code implementing the model should mn on computer systems readily available to DOE and DOE contractors.

be user friendly.

be validated and verified.

be fully documented.

permit sensitivity analyses for various parameters.

output dose estimates or soil guidelines.

provide graphical output as a function of time, pathway, and radionuclides.

default parameters should be selected so as not to underestimate potential doses should they be used for screening assessments in lieu of site-specific factors; guidance, however, should encourage site-specific analysis and discourage the use ofdefault parameters.

NUREG/CP-0163 32

Subsequently, the following criteria for code were added, on the basis of user input and DOE needs.

should estimate both risks and doses.

should be capable of uncertainty analyses, graphical output dose distribu-tions, and deterministic values.

should be capable of evaluating indoor building contamination in addition to outdoor soil contamination.

Several national laboratories and DOE program offices were involved in the initial development of the code. Argonne spearheaded the development effort, and DOE was the sole sponsor of the project.

RESRAD is designed for evaluating sites that contain residual radioactive material. It can be used to derive contaminated site cleanup criteria and for site screening and pre- and postremediation dose / risk assessment. It is designed with user-friendliness and flexibility in mind. Initially, the RESRAD code was developed on the IBM main frame computer and was i later converted to a PC code. After several years of testing and evaluation, the first version of the l RESRAD PC code was published in June 1989, along with a users' manual (Gilbert et al.,1989) that documents the methodology used in the code and the DOE guidelines for residual ,

radioactive material. These guidelines were revised, and in 1990, they were issued as part of {

DOE Order 5400.5. On the basis ofinput from DOE and non-DOE users, including the NRC and j the EPA, the code and model were updated and several supporting documents were prepared to aid in the use of the RESRAD code. These include the RESRAD Data Collection Handbook (Yu et al.,1993a), Compilation of Radionuclides Transfer Factors (Wang et al.,1993), RESRAD Sensitivity Analysis (Cheng et al.,1991), RESRAD Benchmarking Against Six Radiation Exposure Pathway Afodels (Faillacc et al.,1994), and Verification of RESRAD (Halliburton, 1994). The RESRAD code is continually maintained and updated under control of a DOE-approved QA plan. An updated users' manual (Yu et al.,1993b) was published in September 1993; a new update of the manual is planned for 1998. j i

RESRAD is designed for evaluating soil contamination. Another code, RESRAD-BUILD is designed for evaluating indoor building contamination. The RESRAD-BUILD code was also developed by Argonne for DOE. A users' manual (Yu et al.,1994) was published in November 1994, and a draft RESRAD-BUILD Data Collection Handbook is under development.

l In addition to the RESRAD and RESRAD-BUILD codes, ANL developed several codes  ;

6 m the RESRAD series for DOE. These codes are shown in Figure 1. RESRAD-CHEM includes special models for volatile corapounds and dermal absorption pathways. RESRAD-BASELINE was developed to perform baseline risk assessments in accordance with EPA human health risk 33 NUREG/CP-0163

RESRAD. i  :

PROBABHlS11C +

suEssungo y 3CEjh + add'n RESRAD. , *e' RESRAD-BASEI M .,f,,e *RisaAD Fammy er cedes

,,s,Ao. , .

1,. ,,s %

RECYCLE y ECoRISK pg RESRAD BUILD I ,.Ji  %

Figure 1. The RESRAD Family of Codes assessment guidelines. The RESRAD-BASELINE database contains both radionuclides and chemicals. RESRAD-RECYCLE estimates radiation doses to various receptors resulting from the recycle and/or reuse of radioactively contaminated materials / equipment. RESRAD-ECORISK estimates the risk to ecological receptors from contaminant exposure. The RESRAD-Probabilistic code was developed to quantify uncertainties associated with predicted doses and risks. The probabilistic code has been incorporated into the RESRAD, RESRAD-BUILD, and RESRAD-RECYCLE codes.

2.2 Question 2

2. What transport mechanisms, scenarios, and exposure pathways are considered?

2.2.1 RESRAD In the RESRAD code, the initial source of contamination is assumed to be radionuclides in soil; however, measured concentrations of radionuclides in a downgradient well or pond can also be entered. The code will calculate (predict) contaminant concentrations in various media and pathways.

Up to nine exposure pathways can be modeled in RESRAD: direct exposure to external radiation from contamir.ated soil material; internal dose from inhalation of airborne radionuclides, including radon progeny; and internal dose from ingestion of plant foods grown in the contaminated soil and irrigated with contaminated water, meat and milk from livestock fed with contaminated fodder and water, drinking water from a contaminated well or pond, fish (and other aquatic organisms) from a contaminated pond, and contaminated soil. These pathways and i

l NUREG/CP-0163 34

w w l

the transpon among environmental media are shown in Figure 2. The transport mechanisms considered in the RESRAD code are listed in Table 1.

l The code may be used to analyze doses to on-site individuals under current or plausible l future land uses of the site. The default land use scenario in RESRAD assumes an on-site

! subsistence farmer with all exposure pathways active. By suppressing selected pathways and modifying applicable intake or occupancy parameter values, the user may simulate any number l of potential scenarios such as (but not limited to) recreational, industrial, and residential. Two l scenarios that may be modeled in RESRAD are shown in Figures 3 and 4. Doses to off-site l individuals may be modeled by following the recommendations in the users' manual. These l models are being incorporated in a version of the code that will calculate off-s e doses and risks l directly.

l In most cases, the code should be applied to chronic exposure scenarios with durations of one year or more, panicularly for those scenarios with food pathways. However, the code may also be used to assess shon-term exposures from extemal gamma, inhalation, soil, and water ingestion pathways.

1

% '"% '% OL E 3 :r Ie  ;

= -

m y@ %e i, " ^

Riig P .E:

jg iw

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~ =  ::_

E _ _ i( -  !=-

=

# e-  :{ s _=

. = i{e -

~

a r- sn_ l 3; &- I 25 .

Figure 2. Graphical Representation of Pathways C nsidered in RESRAD l

i 35 NUREG/CP-0163 i

i

--____-.____------J

Table 1. Transport Mechanisms Considered in RESRAD Transport Mechanism Media Affected Exposure Pathways Leaching Soil + water All pathways Advection W ater Water-dependent pathways Mixing with uncontaminated Soil Water-independent pathways soil Erosion (source loss only) Soil + water / air All pathways Resuspension Soil + air Inhalation of particulate; ingestion of plant, meat, and milk Diffusion Soil + air Inhalation of radon Off-gassing Soil 4 air C-14 pathways Evapotranspiration Soil + air Tritium pathway Bioaccumulation Water + aquatic Ingestion of aquatic organisms organisms Root uptake Soil + plant Ingestion of plant, meat, milk Foliar deposition Air + plant Ingestion of plant, meat, milk Irrigation Water 4 plant Ingestion of plant, meat, milk Photosynthesis Air + plant C-14 pathways Electromagnetic (gamma, Soil + human Extemal x-ray) and charged particle (beta) transport inhalation Air + human Inhalation of particulate, radon,

CO2, HTO Ingestion Soii+ livestock Meat, Milk Water + livestock Meat, Milk Plant + livestock water + Meat, milk human Water Soil + human Soil Plant + human Plant Meat + human Meat Milk + human Milk Aquatic organisms Aquatic organisms 4 human Dermal Absorption Air 4 human Tritium pathway NUREG/CP-0163 36

j bh .2 mmser 3I EEEPR"" "

v: . ntomenamentt-- 1 gam:o m ,1v., . , - c o irsns-A/4 \#gve.

" $64:m 6+r.- 3 m W M:a;, so,,,,

p!Mit MbiNi@cypM;;!resounsmuner rmpuermi:;mu%9lu!: uv-Figure 3. Schematic Representation of Exposure Pathways in a TypicalIndustrial Use Scenario

-~

iiiid!!!!@!iN$ilMi!ili!!!$ienisubdirWGi@UOlj@ ifs .Wi!iDN& 'n 's Figure 4. Schematic Representation of Exposure Pathways in a Typical Subsistence Farming Scenario 2.2.2 RESRAD BUILD In RESRAD-BUILD, an individual may be exposed to a source through up to seven exposure pathways, as shown in Figure 5 and listed below:

External exposure directly from the source, External exposure due to air submersion, External exposure to materials deposited on the floor, Inhalation of airborne radioactive particulate.

Inhalation of aerosol indoor radon progeny (in the case of radon predecessors),

37 NUREG/CP-0163

Eamwn Inhalation 7 g External Gamma 7 Ingestion >

f =

< e y ,

a _s:-

S S Figure 5. Graphical Representation of Pathways Considered in RESRAD BUILD

- Inadvertent ingestion of radioactive material directly from the source, and

- Inadvertent ingestion of radioactive materials deposited on the surfaces of the building compartments.

Contaminants may move from the source to the receptor by the various transport mechanisms outlined in Table 2.

RESRAD-BUILD may be used to assess a number of different exposure scenarios related to building activities. The code may be used as a scoping tool in preparation for decontamination activities and estimates both individual and collective doses to cleanup workers. It can be used to derive cleanup criteria under occupancy or renovation scenarios. Finally, it can be used as a tool for ALARA, by assessing the dose impact of the no-action alternative versus different remedial activities.

2.3 Question 3

3. How are parameter values determined for input? (Can uncertainties be incorporated into parameter distributions and the subsequent dose calculations?)

NUREG/CP-0163 38

Table 2. Transport Mechanisms Considered in RESRAD-BUILD Transport Mechanism Media Affected Exposure Pathways Erosion / air release fraction Source + air All pathways (volume source only)

Removable fraction / Source 9 air All pathways lifetime / air release fraction (all other source types)

Diffusion (volume source only) Source 9 air Inhalation of radon, tritium Radon release fraction (all other Source 9 air Inhalation of radon source types)

Plate-out Free state 9 surfaces Inhalation of radon Attachment Free state + particulate Inhalation of radon Decay with recoil Surfaces + free state Inhalation of radon Particulate 4 free state Electromagnetic (gamma, x-ray) Source 9 human Extemal and charged particle (beta) Surface + human Extemal transport Ventilation Air All air-dependent pathways Deposition Air 9 surfaces All air-dependent pathways Resuspension Surfaces + air All air-dependent pathways Inhalation Air 4 human Inhalation of particulate, tritiated water vapor, and radon Ingestion Source 9 human Direct ingestion Surfaces + human Indirect ingestion Dermal absorption Air 9 human Tritium  ;

2.3.1 RESRAD 1

The database included in the RESRAD code consists of two categories of parameters:

contaminant-specific and site- or scenario-specific.

The first category includes parameters that are not modified frequently, but may be l changed and saved in a user-specific data file. These data include decay and ingrowth functions,  !

DCFs, cancer risk slope factors, and biological transfer factors (plant / soil, meat / fodder, j milk / fodder, fish / water, other aquatic organisms / water). The defaults for these parameters are conservative and are derived from federal guidance reports (Eckerman, et. al.,1988; Eckerman and Ryman,1993; EPA,1994) or literature searches (Wang et al.,1993). Figure 6 shows a typical RESRAD screen for these parameters. Data are available for 84 radionuclides with half-lives greater than or equal to one month.1 Some radionuclides were added at the request of the NRC.

1 The user may select from two sets of radionuchde databases based on a half-life cutoff. The default database is for 67 radionuclides with half-lives greater than six months. .

39 NUREG/CP-0163

3 A M "l*ti - -.-- -

. .:=.---==-a.-=- - ~ ~ -

= -

. .:= == -

4. * " '

~

".*"f*

m

-. . T g . ".*.""."., *

• T*.

E31C3

~'~~ " " " " . " " "_. _. " " . . .

• '3';"~"

. g y""""'"g". ..sM,

., i i p::;r -1 1

-.- [;$

".=.

• ,=.:

.- mr.~ -  ::::, s1

{ ll""- g ll"'""4:" O b-1 Figure 6. Typical RESRAD Dose Factor Library Screen For those radionuclides with short-lived decay products, the latter are assumed to be in secular equilibrium with their parent and are accounted for implicitly in the dose or slope factors of the parent.

For the second category of parameters, RESRAD provides a default set of more than 150 parameters representative of national averages or reasonable maximum values for a subsistence farming scenario. Any of these parameters may be modified te reflect site-specific conditions and are grouped as follows (examples are shown in parentheses):

• Physical parameters (size, depth, density, porosity, diffusion coefficient)

• Hydrological parameters (hydraulic conductivity, gradient, soil b parameter, water table depth)

. Geochemical parameters (distribution coefficient, leach rate, solubility)

• Meteorological parameters (precipitation, evapotranspiration, erosion, runoff, mass loading)

. Usage and consumption parameters (inhalation, irrigation, ingestion, occupancy)

The Data Collection Handbook (Yu et al.,1993a) and the Compilation of Parameter Distribution (Yu et al.,1997) provide guidance on selecting site- and scenario-specific input values. RESRAD reduces the amount of parameter data input required from the user by only allowing access to those parameters used to calculate doses from a particular pathway. For NUREG/CP-0163 40

i example, if the food ingestion pathways are suppressed, the consumption rates for plants, meat, l milk, or fish are rendered inaccessible (see Figure 7).

Two tools are provided to account for variability and uncertainty in parameter values.

Both the sensitivity analysis and uncertainty analysis tools may be used by the licensee to establish priorities for gathering input data; they may also be used by the regulator to determine the parameters thut should receive attention.

RESRAD uses graphic output to illustrate the effects of variability in a single parameter on the response (e.g., dose as a function of time). The sensitivity analysis feature allows the user to enter a factor that will be used to multiply and divide the base parameter value (Figure 8).

Sensitivity analysis can be performed on almost all input parameters, with up to five parameters per run. The code then graphically calculates the sensitivity of the result due to the variation of each parameter's values and holds all other parameters at their base value (Figure 9).

The uncertainty analysis feature (Figure 10) allows the user to assign one of five distribution types (normal, lognormal, uniform, loguniform, and triangular), along with the associated statistical parameters for the distribution (e.g., mean, standard deviation, minimum, maximum), to two or more parameters. The user may also correlate two or more dependent parameters. The code then samples these distributions and performs a user-selected number of runs. The results (dose / risk as a function of time) are presented both stati stically (minimum, maximum, average, standard deviations) and graphically in Figures 11 and 12.

g. ..

7 ,_ ,

I "IGid Par 8 meters I g _MIT'M

._.. Alth W.'44Bils lmMEl_h___

_.g . _ _ -

j ,

= : ~ ~' qq 7 0'.;t~"~' 22 u-C Z:".' ~~ u. L.'." ,,.

. . ,-,, .m

- . - rm -

3*[  !"~~""""

. 1  :

?.~: '.'."L'""

. rx--d

-- - gm - ,

e I we I - 1 __*==' j Figure 7. Typical RESRAD Site-Specific Parameter Input Screen j 41 NUREG/CP-0163 l

____.___________j

_ . .__. ._ m.r.i

-s . - - -

ry m sr u m wi- w. l

._ -______ei-. 1 is .--""=""""""]

-I

-a Stana.d g g g: -e == - I5 een OW E sais.ep ed. g{

• a s asa.g.s r 4 m - - el: -=~

- - . - o

,'. F~".*. " _

m - mi - _-. _

_ j m - - - - - -  :-- , - {

m -- m L- ,' c-m - - m' __ - ,

= -

Sepe. F 8' 3

- . . - ,_ oi.

Si 54> , ". ;

- IwI g5,,, g

' ' ' ~

{

Figure 8. Typical RESRAD Sensitivity Analysis Input Screen to L. Eum=

itim Od M l

'E c-

oon:v =... w . . u ,

f.e stmaale ! gg

1. " " ' I ii} I j {, ji l l i

.i

es i ni

-: i

.I o ii ao i m i. c !/ii sii F" m i i,i i ei' .ii  ;

l 1tt ) i /j I l l l pg . ,

ni i i yI! ,! i i;>

g m ,,

i t il i  ! /. I 6 y r--

I

=r~g T. -

a i/ .i; t.

i i <

i F'7

• i i i, i W;6

,i i i .i . _

1 to 100 1000 v

Figure 9. Typical RESRAD Sensitivity Analysis Graphicsl Output Screen l

NUP.EG/CP-0163 42

r. . _ - - . - - . _,.r.,

~ -v -

osu mnw,'arge.

,n.n.... i-__-_m w

i-

- - ~ . - .. .,

l wm *"

i e ~'. m -

- - i .mi .o a i 5ll:::l- - [T L

1. 'b~ re-l $-~$ -lh' ?

\

, .Ii f

--i Et am w A  ; ma - . i

- Y_P , "O i ~. r

__ t-W"""

r

- lJh'.'""'243."=M

'~

a.~ ~ ' t* ~ = = .

j [ __,,

l Figure 10. Typical RESRAD Uncertainty Analysis l

Input Screen  !

l l

l I

Dose for AN Rathonuc: ides l i., ,

i 16' _

94, Mammum

+ 1 Stand. Dev Mean 1 Stand. Dev.

M'"'*"*

. 10 l s.

4 4-1 10 100 1000 year Figure 11. Typical RESRAD Uncertainty Analysis Graphical Output Screen - Statistical Distribution of Results 43 NUREG/CP-0163 I

Probabildy for All Radiornelides 8

++v T l

o.. -

] o.. -

l o.v j o.s -

g o.s .

(o3 1

j o.,f a.,

"o , . . . ,o ,, ,. ,. ,.

1 mreaWr Figure 12. Typical RESRAD Uncertainty Analysis Graphical Output Screen - Cumulative Probability Distribution of Results 2.3.2 RESRAD-BUILD The contaminant-specific database for RESRAD-BUILD is consistent with the RESRAD database, with the exception of the transfer factor library, which is not required in performing dose assessments for building scenarios.

Over 40 site- and scenario-specific parameters are used in RESRAD-BUILD. These can be grouped as follows (with examples in parentheses):

= femporal parameters (total time, indoor fraction, receptor time fraction),

=

Spatial parameters (source and receptor coordinates, number of rooms),

• Air flow parameters (air exchange rates, room dimensions, deposition velocity, resuspension rate),

= Shielding parameters (thickness, density, material, orientation),

= Source characteristics (radionuclides concentration, source type, dimensions, direction, removal rate, air release fraction, radon parameters, and tritium parameters), and

=

Receptor characteristics (inhalation and ingestion rates).

NUREG/CP-0163 44

The defaults included in RESRAD-BUILD are based on a generic occupancy scenario.

Because of high variability in building properties, sources, receptors, and scenarios that can be modeled, most default values should be replaced with site- and scenario-specific values. A data collection handbook is being prepared to assist users in gathering the required input data.

RESRAD-BUILD does not have a sensitivity analysis feature; it does, however, have the same uncertainty analysis feature as the RESRAD code.

Figure 13 shows a typical parameter input screen from the RESRAD-BUILD code.

2.4 Question 4

4. What radionuclides and chemicals which can affect radionuclides transport are considered? (Is decay and in-growth considered? To what extent?)

2.4.1 RESRAD The RESRAD database includes 84 principal radionuclides and 52 associated radio-nuclides in the decay chains (i.e., a total of 136 radionuclides). RESRAD does not perform dose or risk calculations for hazardous chemicals. This task is performed by other codes in the RESRAD family, that is the RESRAD-CHEM and RESRAD-BASELINE codes. The RESRAD-CHEM code performs transport and exposure calculations consistent with those performed by the RESRAD code (see response to Question 1). A total of 151 inorganic and organic compounds are included in the RESRAD-CHEM and RESRAD-BASELINE codes.

7 .

v=== we m j U"* y--===] -

.a nas g--)

9 ?.". '."."" T l '~$,,,

- @ l @'a uL i

• n c-- ___ - I- G 2%W  : l l l,L,'$.n.

M 5'

.. i i

-.: tu, .,

r , .

4

=:- . - c- e.i

==

Y"'"7 ' .

y-1 t: : TFW j Figure 13. Typical RESRAD. BUILD Site. Specific Parameter Input Screen 45 NUREG/CP-0163

The chemical form of the radionuclides is considered in the DCFs for radionuclides taken up internally. For ingestion, the user may select the DCF for one or more gastrointestinal (GI) tract fractions; for inhalation; the user may select the DCF for one or more inhalation classes.

RESRAD defaults are for the most conservative DCFs, where more than one GI fraction or inhalation class is available. Short-lived radionuclides (i.e., those with half-lives less than one month or six months, depending on the user-selected cutoff) are considered to be in secular equilibrium with their parents. Thus, their DCFs and slope factors are added to the DCF and slope factor of the parent. An exception to this are radon isotopes and their short-lived progeny, for which ingrowth is tracked explicitly.

Special methodologies have been developed that take into account the different chemical forms and transport of tritium (as tritiated water and water vapor) and carbon-14 (as organic carbon and carbon dioxide)in the environment (Figure 14).

Longer-lived progeny for all radionuclides are tracked separately from their parents. his is particularly important in groundwater transport where different distribution coefficients may be assigned to the decay products. This allows the user to account for the different chemistries of the decay products during transport from the contaminated zone through the unsaturated zone and into the saturated zone. The distribution coefficient (Kd) for each long-lived radionuclides within each zone may be different and will depend on the chemical form of the radionuclides and the soil properties. These Kds may be entered directly by the user, or the code may be used to estimate these values using four separate methodologies (Figure 15): (1) input of radionuclides concentrations in a downgradient well and time since material placement, (2) direct input of the leach rate from the contaminated zone, (3) input of a solubility limit, and (4) correlation with the soil / plant transfer factor. It is quite possible, with the above methodology, to simulate the more rapid transport of a soluble decay product, which may arrive at the exposure point ahead of its slower moving insoluble parent.

em b

i oir,ct entn.2 -

4 ,. . .

, n 2 .~ > . , \

hi4 -

, (> k N,

[*L*1 '"*" '

> 2io a < , . .

~ rm MTamL w

~

> > >,a w , , . ..~.._,

>s

noot uotaas " " * * " " ' ' ' ' ' ' " " ' ' ' ' ' ' " '

~

j -

i Figure 14. Special Models for Tritium and Carbon 14 in RESRAD NUREG/CP-0163 46

1 i

...,_= _ _

ow s-ma.n wzum .ri

--=u j

3: =.3 _

c 1-.

M_l~_

_.w_ _-a

{::::

ne _e.J  :

mm

= - ~ =l._

_l ~*'y m

m -

7_,. - , _  ; _ ,I

~yQ **~ ". ;"~ a ,

t =. Ea-

- a-temass aan. [%rse7 w gg v.ea==a.e .a. O s,.~j ry]

Figure 15. Typical RESRAD Distribution Coefficient Parameter Input Screen The user may also account for the chemical form of the radionuclides by adjusting the biological transfer factors. These factors are used to estimate the transport of radionuclides from soil to plants, fodder to meat or milk, and water to aquatic organisms.

2.4.2 RESRAD-BUILD As with RESRAD, RESRAD-BUILD applies only to radionuclides and not chemical contaminants. There is no biological transport of radionuclides. The chemical form of the radionuclides is accounted for implicitly in the DCFs used, as well by using special models for the diffusion of radon and tritium. Radionuclides decay is considered for all radionuclides, and ingrowth is accounted for explicitly when decay products have half-lives greater than the cutoff.

2.5 Question 5

i. What are the time and spatial geometry limitations inherent in the analytical method?

l l

2.5.1 RESRAD RESRAD calculates annual doses, soil guidelines, radionuclides concentrations, and lifetimes risks as a function of time. The user may enter up to nine times (time zero is always calculated). Any time horizon up to 100,000 years may be selected (the default is 1,000 years),

but the uncertainty in the results will increase with increasing time. The code will also estimate 47 NUREG/CP-0163

the time at which the peak dose occurs for each radionuclides and for all radionuclides summed.

With few exceptions, RESRAD should be applied to chronic exposure scenarios (i.e., over one or more years of exposure) rather than short-term exposure conditions. For exposure durations greater than one year, RESRAD performs a time-integration of excess cancer risks that takes into I

account changes in the radionuclides concentrations in all media as a function of time.

RESRAD has few spatial constraints. The methodology requires the input of homogeneous layers (one optional cover layer, one contaminated zone, one to five optional unsaturated zones, and one optional saturated zone). The code provides graphical feedback on the thickness of the layers entered by the user (Figure 16). Nonhomogeneous (or multiple) contaminated layers may be simulated in separate mns, each with a distinct homogeneous contaminated layer, and the resulting doses may be summed. The code can also be used to perform hot spot analysis to assess doses from small subareas of contamination. No constraints are placed on the area or thickness of any layer.

In most cases, the receptor is assumed to be on-site (outdoors and/or indoors, one meter above the soil surface) and may obtain water from a well or pond located in the middle of the site (mass-balance model) or at the downgradient edge of the site (nondispersion model). For the external gamma pathway, the default source area is conservatively assumed to be circular, with the individual located above the center. However, the user may select a noncircular area, with the receptor located anywhere, including off-site locations (Figure 17). The manual contains the methodology, implemented in a version of the code cunently undergoing testing and evaluation, to estimate doses to off-site receptors from airborne and groundwater transport.

Sod Stiet. Pasameten -

E U

, , CONT AMINAT ED l i i .I I I l i l i i il 1 t l i ,

y l / .

N UNSATURATED (31 / '- < - /- ' ^ ^ ' / ' -- E -

khY$khhk.hhkh - -

.f UNSATURATED 5lo n < -< c o < .' /

"o^ E' sATURATgD E

Figure 16. Typical RESRAD Soil Strata Parameter Screen NUREG/CP-0163 48

1 l

l

- _ _ _ _ I l -._.n._

t i *w n.-r -

l cn - ,m:_- w -%.m. em _,,m j

.m. .,

O_ WI M -c_

:r r s  :

B%

i

! h'  :

l

, h,jW rr.-,i .- . ,

, i l 1 --

l '- :: s -- R U l l  :::: E ::.T=  %: ~!'.*."'.~A-

=. H

~O$*

I Figure 17. Typical RESRAD Shape Factor Parameter Input Screen l 2.5.2 RESRAD-BUILD Similar to RESRAD, RESRAD-BUILD calculates doses as a function of time; the user can input up to nine times. There is no limitation on the maximum time, but as a practical matter, the user should limit the calculations to the anticipated maximum lifetime of the building. By allowing future times to be investigated, it is possible to investigate the effects of source removal l

processes coupled with radionuclides decay and ingrowth.

The RESRAD-BUILD code is very flexible regarding spatial definitions of problems. By entering source and receptor locations in a Cartesian coordinate system, the user may place up to 10 sources and 10 receptors at any point within this coordinate system. However, receptors may not be co-located with sources or placed at locations that intersect source planes or axes. For the external gamma model, a shield of varying thickness, density, and material type may be specified for each source-receptor location pair (up to 100 shields). For the air pathways, one, two, or up to three rooms may be defined, each with unique dimensions and air exchange propenies (Figure 18). Rooms must be adjacent to one another. Air is allowed to flow between adjacent rooms and may be exchanged with outside air; direct air flow between nonadjacent rooms, however, is not allowed. In a two- or three-room scenario, rooms may be configured horizontally or vertically (or mixed), with or without a basement. Receptors and sources may be placed anywhere within a room, or even outside the building, if only the external gamma pathway is of concern.

I 49 NUREG/CP-0163

y

• )'..l.

5

^

u ny ,

]!gV '

Figure 18. Schematic Representation of the RESRAD-BUILD Three-Room Model Four source types may be specified, each with their own spatial definitions (Figure 19). A point source is simply defined by its coordinate location. A line source is defined by its length, its coordinate location at the center of the line, and a direction parallel to one of the three coordinate axes. A surface source is modeled as a disk and is defined by its area, its coordinate location at the center of the area, and a direction that is normal to the surface and parallel to one of the three coordinate axes. A volume source is modeled as a cylinder with up to five layers, one of which contains the contamination. Each layer can be defined with a unique thickness, density, erosion rate, porosity, and radon transport properties. The other dimensional definitions are the same as for a surface source. Two or more sources may be co-located. For example, a wall that is both volumetrically and superficially contaminated may be simulated by placing a volume source and a surface source at the same location; a hot spot may be simulated by placing a point source anywhere along the surface or inside the volume.

Receptors may be defined as points that represent the location at which the dose rate is measured. By entering different locations and time fractions at each location, a scenario may be set up to calculate collective doses to more than one individual, the ' total dose to a single individual at multiple locations, or any combination. Two receptor-source orientations, rotational and anterior-posterior, may be simulated. The latter is used when the receptor faces the source and results in slightly higher direct gamma doses than the former.

2.6 Question 6

6. To what extent can alternative remedial actions be assessed and compared (e.g., comparison ofconcentrations, doses, and costs)?

NUREG/CP-0163 50

z

'olume or Area S Y une (1,1,0) oint

X (0,0,0)

Figure 19. RESRAD-BUILD Source Types and Geometry Definitions 2.ti.1 RESRAD The RESRAD code provides output in the form of doses, risks, cleanup guidelines, and contaminant concentrations. Multiple mns of the code, as well as the sensitivity and uncertainty analysis tools discussed in the response to Question 3 may be used to assess the effects of altemative remedial actions. An example may be a sensitivity analysis performed to assess the effect on the dose of adding covers of varying thickness (Figure 20). The results are displayed both in text reports or graphically and may be used as input to cost-benefit analysis models.

Sensitivity and uncertainty analyses can also be applied to assess the effects on time-dependent concentrations in various media. The results may then be used in performing ALARA analyses, as discussed in the response to Question 8, or in developing monitoring strategies, as discussed in the response to Question 10.

2.6.2 RESRAD-BUILD With the exception of the sensitivity analysis feature and graphical output (not currently available in RESRAD-BUILD), the same applies to RESRAD-BUILD.

2.7 Question 7

7. To what extent has the dose model been tested and included in benchmarking studies?

51 NUREG/CP-0163

DOSE: Co40 AN Pathwers Summed with SA on Cover septh a _ .

l4 l l l l l nolk h l

=

l l l l 200  :

{~ ls\ ll ll I l 'sJl l l

%Q lh

"}_ Jhk 1 10 100 I _I 1 .

1000 Years O- war . -S ese a HB- w== .s Figure 20. Example Sensitivity Analysis Graphical Output - Dose vs. Cover Thickness 2.7.1 RESRAD The RESRAD code is subject to strict configuration control under ANL's RESRAD Software QA Plan. Under this plan, changes to RESRAD must be approved by the Project Leader and Program Manager. A modification must be reviewed by:

- An independent scientist or programmer, . .

- the Project Systems Analyst, e the Project Leader, and

- the Program Manager.

All modifications are reviewed prior to a new code release by all programmers to ensure that there are no internal conflicts. Modifications to the code are made to maintain a state-of-the-art methodology, as well as implement suggestions made by users and sponsoring agencies.

The code has been verified and validated since 1989. An independent verification was performed by a competitively selected contractor who was entirely independent of the development of RESRAD in June 1994 (Halliburton NUS,1994). RESRAD has been included in international code validation studies, including the Biospheric Model Validation Study: Phase II (BIOMOVS II) (Gnanapragasam and Yu,1997a) and the Validation of Model Predictions (VAMP) study (Yu and Gnanapragasam,1995; Gnanapragasam and Yu,1997b) sponsored by the International Atomic Energy Agency (IAEA,1996). These studies used actual monitoring data obtained in Europe from the Chemobyl accident and actual uranium mill tailing data. In NUREG/CP-0163 52

_ _ _ _ _ _ - _ _ _ _ . _ . _ _ . _ _ _ . _ _ _ _ _ _ _ _ i

these " blind" studies, real-world data were provided to the panicipants who used their models to evaluate the data and provide an estimate of radiation dose. RESRAD has provided results that compare favorably with the " official" answers, which are only furnished after the estimates of each code developer are submitted.

RESRAD has been benchmarked against a number of other pathway analysis codes and methodologies, including GENII, GENII-S, DECOM, PRESTO, PATRHRAE, NUREG/CR-5512 (Faillace et al.,1994) and MEPAS and MMSOILS (Cheng et al.,1995; Mills et al.,1997).

The latter was sponsored by the EPA (Laniak et al.,1997). These benchmarking studies have provided valuable information on how each code addresses a similar set of input parameters and exposure scenarios. These comparisons are useful in assessing the limitations of each code. In some cases, this has led to uncovering errors or initiating modification in a few of the codes that were benchmarked. RESRAD has performed satisfactorily in both benchmarking studies.

Independent of Argonne and DOE, the NRC has evaluated RESRAD prior to approving it )

for use by its staff and licensees. Technical suggestions furnished by the NRC staff were incorporated into the code and additional radionuclides were added. Similarly, the EPA's Science Advisory Board reviewed RESRAD as part of its review of the development of generally applicable standards for residual radiation at sites after cleanup (Wolbarst et al.,1996).

RESRAD also has benefited from more than a decade of field applications at over 300 sites in the United States and overseas. It is used as a teaching tool at a dozen universities, including Oregon State University, Ohio State University, Rensselaer Polytechnic Institute, and the University of Tennessee.

More than 60 RESRAD training workshops have been conducted at various locations in the United States upon request of several federal (including DOE, NRC, and EPA) and state environmental, health, and safety agencies (e.g., New York, Louisiana, Connecticut, among others). Over 1,000 people have been trained at these workshops.

A computerized user database is maintained to inform users when a major revision of the code has been issued. Users may also visit the RESRAD Family of Codes web page at "www.ead.anl. gov /restad.html" for cede status and updates, an on-line version of the Data j Collection Handbook, upcoming training workshops, and other information. Surveys and  !

questionnaires are issued periodically to obtain feedback. Users may also contact ANL directly through e-mail at "RESRAD@anl. gov" or by phone to obtain technical assistance. Feedback obtained from users through technical assistance, training workshops, and surveys is incorporated i into code revisions.

53 NUREG/CP-0163

.2.7.2 RESRAD-BUILD RESRAD-BUILD is under the same software QA plan as RESRAD. Code modification and verification have been documented since 1994. The external gamma calculations performed by the code have been successfully benchmarked against MICROSHIELD (a point-kernel code) and MCNP (a Monte Carlo code). Over 10 RESRAD-BUILD training workshops have been conducted since 1996; approximately 200 people have been trained at these workshops.

2.8 Question 8

8. To what extent can the analytical method handle complex: (a) source term

- characterization; (b) multiple source terms; (c) hydrologic and hydrogeo-logical conditions; (d) exposure pathway combinations; (e) remedial methods linked to cost and monitoring programs; and (f) ALARA considerations?

2.8.1 RESRAD (a) The RESRAD source term is entered as average soil concentrations ofinitially present radionuclides. The user may also enter groundwater concentrations to estimate the radionuclides Kds. Short-lived radionuclides are assumed to be in secular equilibrium with their parents.

Ingrowth, decay, leaching, off-gassing (C-14), and evapotranspiration (tritium) are all used to estimate the change in source concentrations as a function of time; the erosion rate is used to estimate changes in the cover and/or source thickness as a function of time (Figure 21).

(b) Multiple source terms, as well as hot spots, may be modeled by adding the results from separate runs. Features in the text and graphic output reports allow users to export data to spreadsheet pmgrams for ease of analysis.

(c) Precipitation, irrigation, runoff, and evapotranspiration are all considered in estimating

'the infiltration rate. The RESRAD model assumes homogeneous hydrogeological soil properties within each horizontal layer. Up to five unsaturated layers, each with unique properties, may be modeled. These soil layers are illustrated in Figure 16. Two one-dimensional groundwater models, the mass-balance model and the nondispersion model (shown in Figure 22), may be selected for the calculations of on-site doses. For off-site groundwater transport, a three-dimensional dispersion /one-dimensional advection model is being tested and evaluated.

Potentially contaminated water for drinking, household uses,' livestock, and irrigation may be modeled as originating from a well and/or pond.

NUREG/CP-0163 54

mixing iayer I 4

"" EAT'"*' sion cnntggated "20 Zones I

time time t (0) t(n)

Figure 21. RESRAD Time-Dependent Source Evolution i i i i i i k44du,=1.e.4 IA WL '

f" ' l s i

) i

,s.- L -

a 4""#'de i j water ,9

~

,f,, f I l g i 1_e

+ ;

• ene weer Gramowater Fiow Sa:uraiec Zone (Aouder) g  %

N Figure 22. RESRAD Non Dispersion Groundwater Model (d) One or more pathway combinations, up to a total of all nine exposure pathways, may be simulated in a single run (the radon pathway can only be evaluated when a radon precursor is part of a source). It is easy to turn pathways on or off in RESRAD. Once a pathway is tumed off, parameters that are unique to the pathways are suppressed, and users do not need to provide data for those parameters.

(e) RESRAD may be used as a tool to evaluate various remedial methods. The scenarios and input parameters can be easily modified, and multiple runs can be performed for each alternative. Also, the sensitivity and uncertainty analysis features of the code discussed in the l

responses to questions 3 and 6 may be applied to parameters related to alternative remedial methods (e.g., cover thickness or thickness of the contaminated zone) to assess their impact when the resulting doses or concentrations are entered in a cost-benefit model or are used to establish monitoring programs.

I 55 NUREG/CP-0163

(f) Sensitivity and uncertainty analysis features, as well as multiple mns, may also be applied as a modeling tool when conducting the ALARA analysis. The output provided by RESRAD for a number of different scenarios or parameter variations can.be used as input in a cost-benefit model. RESRAD has been used as an ALARA tool at a number of DOE sites, including Hanford and Fernald. The DOE draft ALARA standard (DOE 1997) provides additional infonnation on using RESRAD for ALARA analysis and includes case studies for sites (Colonie, Elza Gate, Maywood, Ventron, and Weldon Springs) where RESRAD has been ,

used as an ALARA tool.

l

)

1 2.8.2 RESRAD-BUILD RESRAD-BUILD can be used to simulate four types of sources and up to 10 sources per run. For more details on parts (a) and (b) of this question, see the response to Question 5.

Because the RESRAD-BUILD code does not assess the dose from groundwater contamination, part (c) of this question does not apply. In response to part (d), the user may assess doses from any combination of the seven pathways available (the radon pathway can only be evaluated when a radon precursor is part of a source). The response to parts (e) and (f) for RESRAD also applies to RESRAD-BUILD.

2.9 Question 9

9. Does the dose model include software graphical outputfor portraying dose vs. timefor various exposure pathways and specified radionuclides and total efective dose equivalents, including uncertainties?

2.9.1 RESRAD The graphical software package allows the user to view not just dose versus time, but also soil guidelines and concentrations as a function of time. The user may view the total effective dose equivalents or the contribution of individual radionuclides (including decay products) (see the example in Figure 23), as well as the dose from all pathways or the contribution of individual j pathways (see the example in Figure 24). The user may also view the sensitivity of j dose / guidelines as a function of time for each parameter selected for sensitivity (see Figures 9 and 20). A separate graphics package included with the uncertainty analysis allows the user to view the results of multiple iterations of the code; the cumulative distribution of total dose; and .

statistical plots showing minimum, maximum, average, and standard deviations of the total dose l as a function of time (see Figures 11 and 12). Different plotting options (logarithmic vs. linear plots, color vs. black and white, solid lines vs. dashed lines) are available to the user. The data j from the plots may be exported to a spreadsheet or copied to the clipboard for incorporation into i documents.

NUREG/CP-0163 56

l l

l DOSE: As NuclMiss Summed. AN Pathways Summed

,o .

i I Il i I i t! l

,, I  ! !A i l ,.

l 3.

i I/ 11

_,N.. 1- !y l '

,, ih. /!

N T ,l il \ / i (

, I I A X /  ! )

I i N N I / )

l ,

I N-dhi/ (

iIWt/ I i (

1 to 100 10oo Years

e. + . +-

Figure 23. RESRAD Graphical Output-Dose Contributions by Radionuclides i

t oose. a nu e sum d.c , ,s te I i  ! i kii I

' I i i /t Ki i

! ,, V ! i\i  !

/ ! iI i l

v s.

/! II l

, I 'Tw /i i \

I i i N / i \i i imAN i/ I \

,L 4 - >a ww m+ L 1 to ,co , coo Va.re

+- + - - e - +

+- ,- - +.- 4---

- . - - - -- +- +

Figure 24. RESRAD Graphical Output-Dose Contributions by Pathway l

l 57 NUREG/CP-0163

2.9.2 RESRAD-BUILD The current version of RESRAD-BUILD does not have a graphical output package.

However, RESRAD-BUILD provides graphical visual feedback of the source types / direction, number of sources and receptors, and their locations relative to each other.

2.10 Question 10

10. Can the analytical method consider various restrictions on land use and site boundaries in calculating concentrations and/or doses and in determining monitoring strategies?

l 2.10.1 RESRAD The RESRAD model can be used to assess most land uses, whether restricted or unrestricted, by simply altering the scenarios as indicated in the response to question 2. In l addition, the cleanup criteria can be formulated to take into account a period of institutional control prior to the unrestricted release of the property. Soil cleanup criteria are calculated automatically by the code for each radionuclides entered, on the basis of a user-specified annual dose limit. By estimating the times at which the peak doses from water-independent pathways and water-dependent pathways occur (Figure 25), the code can be used to prioritize the DOSE: 4238. Water hulependent & Dependent Sutheele I ii l I I i l I. I  !

[

ll i

l i

l i /

/ I t

i I i l I / i I I I i/ l l t,,,

I + \

w m i i

\

i NI i 1 .1 i I/mW 't 1 10 100 1000 Years

.e. -

Figure 25. RESRAD Graphical Output-Water Independent and Dependent Subtotals NUREG/CP-0163 58

' - . -- -__m ____ m.- __ __ _ _ _ __ __ ---. _ _ ____.__ __-_m

monitoring strategies for various media such as soil, air, water, and food products. The code also predicts time-dependent radionuclides concentrations in various media (see the example in Figure 26), which can be used to determine monitoring strategies and data quality objectives. The off-site receptor airbome dispersion and groundwater transport methodology described in the users' manual can be used to evaluate conditions at or beyond the site boundary.

2.10.2 RESRAD-BUILD As indicated in the response to Question 5, RESRAD-BUILD does not have significant l spatial limitations and can be used to assess very site-specific building contamination problems.

However, with the exception of the external gamma pathway, assessments are limited to locations inside a building. The code can assess the dose to single or multiple receptors from contamination in a number of sources in single or multiple rooms of a building. The effect of building-use restrictions may be easily assessed by modifying the parameter values (typically receptor locations, occupancy factors, consumption rates, and/or release factors) to accommodate the desired usage scenario. The results can also be used as input for monitoring strategies, particularly for extemal gamma dose rates and airborne contaminant levels. The code is particularly useful in estimating changes in concentrations over time as a function of decay, ingrowth, or physical removal rates.

CONCENTRATION:St 40, Drs**j waeor 1A ll-l l l l l, I l l

" l l l ll\ l l l 1.0 ll I 4\ III s

• o l ill u

I [ }i' Ill I

~

0.4 l  ! ( lIl OJ l l  : l\ llll l l I .. i: I hl lll  !.

4. . .

Years Figure 26. RESRAD Graphical Output-Radionuclides Concentration in Drinking Water l

l l

l 59 NUREG/CP-0163 1

l 3 REFERENCES Cheng, 31., et al.,1991, RESRAD Parameter Sensitivity Analysis, ANIJEAIS-3, Argonne National Laboratory, Argonne,IL.

Cheng,1.1., et al.,1995, Benchmarking Analysis of Three Multimedia Models: RESRAD,

'MMSOIIJ, and MEPAS, prepared for the U.S. Department of Energy, Office of Environmental Management, Washington, D.C.

Eckerman, K.F., et al.,1988, Limiting Values of Radionuclides Intake and Air Concentration and Dose Conversion Factorsfor Inhalation, Submersion, and Ingestion, EPA-520I1-88-020, Federal Guidance Report No. I1, U.S. Environmental Protection Agency, Office of Radiation Programs, Washington, DC.

Eckerman, K.F., and J. Ryman,1993, External Exposure to Radionuclides in Air and Water and Soil, Federal Guidance Repon No.12, EPA-402-R-93-081, U.S. Environmental Protection Agency, Office of Radiation Programs, Washington, DC.

Faillace, E.R., et al.,1994, RESRAD Benchmarking against Six Radiation Exposure Pathway Models, AN1JEAD/FM-24, Argonne National Laboratory, Argonne,IL.

Gilbert, T.L., et al.,1989, A Manualfor implementing Residual Radioactive Material Guidelines, ANIJES-160, DOE /CH/8901, Argonne National Laboratory, Argonne, IL.

Gnanapragasam, E.K., and C. Yu,1997a, Analysis of BIOMOVS II Uranium Mill Tailings Scenario 1.07 with the RESRAD Computer Code, ANIJEAD/TM-66, Argonne National Laboratory, Argonne,IL.

Gnanapragasam, E.K., and C. Yu,1997b, Application of the RESRAD Computer Code to VAMP Scenario S, ANIJEAD/FM-70, Argonne National Laboratory, Argonne, IL.

Halliburton NUS,1994, Verification of RESRAD - A Code for implementing Residual Radioactive Material Guidelines, Version 5.03, HNUS-ARPD-94-174, Gaithersbutg, MD.

International Atomic Energy Agency,1996, Validation ofModels Using Chernobyl Fallout Data from Southem Finland - Scenario S, IAEA-TECDOC-904, Second Repon of the VAMP

- Multiple Pathways Assessment Working Group,IAEA, Vienna, Austria.

Laniak, G.F., et al.,1997,"An Overview of a Multimedia Benchmarking Analysis for Three Risk Assessment Models: RESRAD, MMSOILS, and MEPAS," Risk Analysis 17(2):203-214.

NUREG/CP-0163 60

Mills, W.B., et al.,1997, Multimedia Benchmarking Analysisfor Three Risk Assessment Models:

RESRAD, MMSOILS, and MEPAS, Risk Analysis 17(2):187-201.

U.S. Department of Energy,1997, " Applying the ALARA Process for Radiation Protection of the Public and Environmental Compliance with 10 CFR Part 834 and DOE 5400.5 ALARA Program Requirements," Draft DOE Standard, Washington, DC.

Wang, Y.Y., et al.,1993, A Compilation of Radionuclides Transfer Factorsfor the Plant, Meat, Milk,'and Aquatic Food Pathways and the Suggested Default Values for the RESRAD Code, ANIJEAIS/TM-103, Argonne National Laboratory, Argonne,IL.

Wolbarst, A.B., et al.,1996," Technical Basis for EPA's Proposed Regulation on the Cleanup of Sites Contaminated with Radioactivity," Health Physics 71(5):644-660.

i Yu, C., et al.,1993a, Data Collection Handbook to Support Modeling the impacts ofRadioactive Materialin Soil, ANIJEAIS-8, Argonne National Laboratory, Argonne,IL.

Yu, C., et al.,1993b, Manualfor implementing Residual Radioactive Material Guidelines Using RESRAD, Version 5.0, ANIJEAD/LD-2, Argonne National Laboratory, Argonne,IL.

Yu, C., et al.,1994, RESRAD-BUILD: A Computer Modelfor Analyzing the Radiological Doses Resulting from the Remediation and Occupancy of Buildings Contaminated with Radioactive Material, ANL/EAD/LD-3, Argonne National Laboratoy, Argonne,IL.

Yu, C., and E. Gnanapragasam,1995, " Testing RESRAD Predictions with Chernobyl Data," in proceedings of the International Symposium on Environmental Impact of Radioactive Releases, IAEA-SM-339/129, Vienna, Austria, May 1995.

Yu, C., et al.,1997, Argonne National Laboratory, unpublished information (Dec.1997). l l

61 NUREG/CP-0163

i

)

Response to Nuclear Regulatory Commission's Ten Questions Pertaining to Site-Specific Models for Use in the License Termination Rule: Multimedia Environmental Pollutant Assessment System (MEPAS)

John W. Buck, Gene, Whelan. Dennis L. Strenge, Bonnie L. Hoopes, John P. Mcdonald, Karl J. Castleton, Mitch A. Pelton, Gariann M. Gelston, and Randall Y. Taira Pacific Northwest National Laboratory P.O. Box 999 Richland, WA 99352 Introduction MEPAS takes the nontraditional approach of combining all major exposure pathways into a multimedia computational This paper is in response to the US Nuclear Regulatory tool for public health impact. MEPAS is a physics-based Commission (NRC) ten questions posed at the Modeling approach that couples contaminant release, migration and Workshop held November 13 and 14,1997. The ten ques. fate for environmental media (groundwater, surface water, tions were developed in advance of the workshop to allow air) with exposure routes (inhalation, ingestion, dermal con-model developers to prepare a presentation at the Workshop. tact, external dose) and risk / health consequences for radio-This paperis an expanded version of the Multimedia Envi- logical and non-radiological carcinogens and non-ronmental Pollutant Assessment System (MEPAS) presenta- carcinogens.

tion given at the Modeling Workshop by Pacific Northwest .

National Laboratory (PNNL) staff. This integration of models to provide an overall assessment is the key benefit of using MEPAS. Assessmg risks involves This paper is organized by the ten questions asked by the examining pathways for contaminants to reach humans.

NRC, each sections devoted to a single question. The cur- Whereas past systems often looked at one pathway at a rent version of methodology is MEPAS 3.2 (NRC 1997) and time, MEPAS looks at all pathways and computes total risk the discussion in this paper will pertain to that version. In to humans from a particular site. The software prompts the some cases, MEPAS 4.0, which is currently being devel- user to supply the necessary information, integrates popula-oped under the Framework for Risk Analysis in Multimedia tion exposure routes into the analysis, and computes the Environmental Systems (FRAMES)(Whelan et al 1997), subsequent risks for the site. Investigators can easily locate will be referenced to inform the reader of potential capabili- site data and files and modify them to assess the risks of var-ties in the near future. A separate paper is included in the ious cleanup options or scenarios. The system ranks envi-document that discusses the FRAMES concept. ronmental problems according to potential for human health impacts--helping to assign priorities to cleanup efforts.

Brief Description of the MEPAS software For farther information on MEPAS please refer to MEPAS web site address: httpl/mepas.pnl. gov:2080, MEFAS The Multimedia Environmental Pollutant Assessment Sys. Email: mepas@pnl. gov, or call Gariann Gelston at 509 376-tem (MEPAS) software utilizes sophisticated modeling 8308 codes to quickly and easily assess risks from activities that could impact human health, such as remediating hazardous . .

waste sites (Whelan et al 1987, Whelan et al 1992, Buck et QueSilon 1: Describe the history of the al 1995). This innovative computer program for PC and UNIX systems helps answer such questions as "How risky analytical method's development?

is this hazardous waste site?" and "What is the low-risk The MEPAS software package was first conceived by cleanup solution?" The software integrates models and PNNL staff and submitted to the US Department of Energy quickly provides an overall evaluation of risk for a site or an (DOE)in 1984. The initial mathematical formulations for incident. This capability supports key decisions on priorities the MEPAS was developed and published for external and low-risk solutions to waste cleanup. The MEPAS soft- review in 1987. Based on review comments for DOE, other ware provides physics-based modeling codes for environ- government agencies, and private companies, these formu-mental risk assessment. It quickly integrates rer.alts from lations were modified and converted into computer soft-separate models of contaminant behavior in various media ware. The MEPAS software was initially developed for the (air, soil, ground water, surface water) and for different sce- DOE's Environmental Survey Project that evaluated and narios, turning a task that could take weeks (or might never ranked waste sites from 36 DOE installations across the be attempted)into a few hours' work. country. The first version of MEPAS was completed in aEPAS integrates and evaluates transport and exposure 1989 and applied to 16 DOE installations (DOE 1988).

pathways for chenucal and radioactive releases aceording t MEPAS 2.0 was completed and applied to the 36 DOE their potential human health impacts (multimedia in this installations in 1991. This completed the initial application context refers to multiple environmental transport media). of the MEPAS software and worked out many of the appli-63 NUREG/CP-0163

MEPAS cation bugs and user issues associated with the software (known emissions from stacks, vents, pipes). For each time package. step, the depletion and addition of mass is balanced with the initial source mass and partitioned to the appropriate trans-Version 3.0 of MEPAS was completed in 1994 with fund.ng port media. The key result from the STRM are time varying l from DOE and internal funds at Battelle to make the soft- contaminant emissions from the different release mecha-ware more tailored to site-specific analyses and assess- nisms and the remaining mass at the source. Figure 2 shows ments. The user interface was upgraded to allow users to a schematic of tne STRM and its release mechanisms.

input site-specific data and to conduct calibration analy.ses for the source, transpon, and exposure components of The transpon modules consist of an atmospheric, surface MEPAS. Version 3.1 of MEPAS was completed in 1995 and water, surface / subsurface soil (vadose zone), and groundwa-included some refinements in the user interface and the out- ter (saturated zone) modules. These transport modules put of the exposure / risk module. Version 3.2 of MEPAS interact with each other to allow for complex transpon sce-was co-funded by DOE and NRC (NRC 1997) to allow for narios. An example of a complicated transport scenario that annual dose and risk information and to include a new MEPAS can simulate is: three vadose zones of different soil Source-Term Release Module. This Source-Term Release characteristics leaching to a saturated zone that discharges Module allowed for mass balance of contaminants from the into a river (surface water). The atmospheric transpon mod-different source terms and to ensure mass partitioning ule (Droppo and Buck 1996) provides long term time-vary-between the different transpon media. Version 4.0 of ing air and soil (from dry and wet deposition)

MEPAS is curremly in development and is expected to be concentrations to the area surrounding the source. The available by summer of 1998. This version willinclude a atmospheric transpon module uses site-specific or regional Wm' dows-based user interface and will allow for linking of climatology data (frequency of occurrence by wind speed, MEPAS modules with other environmental models devel- wind direction, and atmospheric stability) averaged over a oped independent of MEPAS. minimum of several years. These air and soil concentra-tions are sector averaged over 16 directions and 10 distances The MEPAS software has gone through extensive ir- nal (from 100m to 80,000m) centered on the source.

and external scientific review to ensure that its s' .ms are defensible and appropriate to assessment r .Jons. The surface / subsurface soil module (vadose zone) simulates Table I gives a brief summary of some of th- ;xternal the aqueous contaminant transport though the partially satu-reviews of MEPAS. Table 2 provides a sum. 7 of the rated soil layers. The vadose zone module (Whelan et al major applications that have used MEPAS for assessing 1996) uses a one-dimensional aavective, one-dimensional contaminant release, transport, exposure and impacts. dispersive equation to simulate water and contaminant flow Extensive application of MEPAS has ensured that the soft- though the partially saturated soil. Several vadose zone ware is operating co Tectly and is flexible to the needs of the modules can be link together to simulate a complicated soil users and clients. horizon at a site. Each vadose zone is model separately with the time-varying contaminant fluxes output from the previ-ous zone as input to the next vadose zone. This ensures mass Question 2: What transport balance though the system and allows for modeling of sites mechanisms, scenarios, and exposure with complex geohydrology. He contaminant fluxes from the vadose zone (s) can be divened to several saturated zones pathways are considered? by assigning percentage of fluxes to the difrerent saturated

. . zones (main aquifer and perched aquifers). Figure 3 is a dia-The current version of MEPAS (version 3.2) has four main gram of how the vadose and saturated zones can be linked in sets of modules associated with its structure. These are MEPAS.

source, transpon, exposure and impact modules. Figure 1 provides a diagram of the overall structure of MEPAS 3.2. The groundwater or saturated zone module (Whelan et al The Source-Term Release Module (STRM) (Streile et al 1996) uses a one-dimensional advective, three-dimensional 1996) ensure mass balance and partitioning to the appropri- dispersive equation to simulate water and contaminant flow ate transport media via the following release mechanisms: though the saturated soil. A saturated zone can be a source volatilization, wind and mechanical suspension of panicles, or transport module in the MEPAS structure. Up to 10 dif-infiltration in to the subsoil, overland runoff and flow, and ferent groundwater and groundwater to surface water recep-decay / degradation at the source through radioactive decay tors can be simulated in a given run. The surface water and reducing processes such as hydrolysis, photolysis, and module includes river and wetlands. This surface water chemical transformations. External mass sources and sinks module (Whelan and Mcdonald 1996)is a steady tate one-can be defined by the user to simulation additional activities dimensional advective, two-dimensional dispersive equation at the source. There are four main source types handled by for solute transpon. It is for nontidal rivers with unidirec-the MEPAS STRM; surface / subsurface soil, surface tional flow in definable channels. This module can be impoundments, saturated soils (aquifers), and active sites linked to the groundwater and source term (overland or NUREG/CP-0163 64

MEPAS l

l dir:ct discharge) modules. Different surface water recep- mine which parameters are the most sensitive for the given tors can be simulated with varying discharge rates. models and site characteristics. Once the sensitive parame.

ters have been determined, uncertainty analysis can be con-The exposure module (Strenge and Chamberlain 1995) sim- ,

ducted to understand how conservative and uncenain the ulates four exposure routes: ingestion, inhalation, dermal results from the evaluation are. These analyses can be con-contact, and external exposure. There are 25 different expo- m cm ant kses as wee as Huxes, cacem sure pathways associated with these exposure pathways.

rations, and impacts. The results are graphical wtput of the Figures 4 -8 show these exposure pathways in MEPAS exposure module by environmental media. 'Ihe exposure cumulative and probability density function for the endpoint sele ted. The partial R can be obtained for each parameter module inputs environmental concentrations from contami-

. analyzed.

nited soil, water, and air and produces time-varying doses as output. The time scale of these doses can be varied based on user needs. The risk module inputs time-varying doses Question 4: What radionuclides, and from the exposure module and computes carcinogeme ,

impacts from radionuclides and chemicals and noncarcino. chemicals which can affect transport, genic impacts from hazardous chemicals. These impacts are considered? Is decay and in-growth ein be in the form of cancer incidence or fatalities fc aadio-nuclides, cancer incidence for carcinogenic chemicals, or considered? To what extent 9 hazard quotient for noncarcinogenic chemicals.

MEPAS has an extensive set of radionuclides and chemicals that can be evaluated by the software. The Multimedia Question 3: How are parameter values Mode:ing Environmental Database and Editor (MMEDE) module (Warren and Strenge 1994) contains 197 radionu-determm, ed forinput? Can clides and 408 organic / inorganic chemicals with all the uncertainties be incorporated into the required physical, chemical and health related parameters

. (Strenge and Peterson 1989). Constituents can be easily p:rameter distributions and dose added to MEPAS through a constituent database editor.

c"Iculations? MEPAS constituent database contains all the long-lived radionuclides (1/2 life greater that a day) that the DandD Though the development and implementation of the software does. This was confirmed with Sandia National MEPAS software a hierarchy of data to be used for a param- Laboratory in 1996. MEPAS has a few special constituents i eter has been developed. If at all possible, site-specific that are handled different from the other constituents. These p:rameter values should be used. In most cases MEPAS are H3, Cl4,1129, and Rn222.

allows users to input site-specific information into the mod-MEPAS does consider radioactive decay in all the source ules where appropriate. If site-specific data is not available, g, g g MEPAS documen.ation (Buck et al 1995) suggests were code decay sequences. The waterborne transport component regional data can be obtained for parameter values. These of MEPAS 3.2 requires that the progeny have the same kind of data are generally climatological, treteorological, transpon propenies as their parent consistent. This issue and geohydrology type data. If regional dan is not available for the assessment, representative parameter values are pro- 911 be resolved in the MEPAS 4.0 version, where progeny will have transport propenies independent of their parent vided by the different modules to allow the user ta complete e nstituents.The dosimetry calculations used in MEPAS are the essessment. These representative parameter values are fr m Federal Guidance Repons 11 and 12.

based on studies and characteristics of the site. Examples of such data are bulk density, porosity, field capacity and distri-bution coefficients. All these parameter values are referen-cable. MEPAS does not supply default values at are Question 5: What are the time and , , ,

considered conservative for all situations because different spatial geometry h,m,tations i mherent in ,

application goals and site situations can affect results such the analytical methods?

that conservatism can not be guaranteed l MEPAS has been used on site-specific, area-specific, instal-MEPAS has a sensitivity and uncertainty module (Doctor et lation-specific, regional-specific and nationwide assess-al 1990) that allows the user to input and determine distribu-ments. There are no real bounds on the spatial and temporal tions for most of the parameters required for MEPAS runs.

ge metry in the MEPAS methodology. MEPAS methodol-A Latin hypercube sampling system (modified Monte ,

gy can easily be handle site to national scale assessments.

Carlo)is used to sample the different paramt r ;s selected by The normal bounds of MEPAS transport is 80 km for the the user for the evaluation. A s'iite of distribu.lon types is atm spheric transport pathway but this can be expanded to available to the user. This module allows the user to deter-much great distances very easily. The Waterborne transpon 65 NUREG/CP-("63

MEPAS pathway general has no limits of distance. It uses what ever benchmarking studies?

the assessment requires. The normal time dimensions of MEPAS varies from 1 year to 10,000 years but models are ne dose model associated with the MEPAS methodology not limited to these dimensions. MEPAS has been used for has been in use by PNNL and DOE for over 10 years. These analysis of less than a year and more than 1,000,000 years ten years of application along with the model's full QA/QC and the user can easily define this assessment-specific documentation in accordance with DOE orders and PNNL issues. The spatial and temporal geometry flexibility is standards ensure appropriate testing of the software. Some associated with source, t. ansport, exposure and impacts. of these applications have resulted in model comparisons MEPAS output has been linked to Graphical Information (Moskowitz et al 1996, Morris and Meinhold 1988. EPA Systems (GIS) to provide useful displays of spatial and tem- 1988, Health and Welfare Canada 1992 Holmes et al 1994).

poral information. Figure 9 provides an example of an Recently the MEPAS methodology was benchmarked with installation-wide display of risk information. other multimedia environmental model. The RESRAD, MMSOILS, and MEPAS methodologies were benchmarked through a co-funded DOE and EPA effort. The resulting-Question 6: To what extent can EPA / DOE document (EPA / DOE 1995) provides compari-sons of the three modeling methodologies based on evalua-alternative remedial action be addressed tions of several selected sites. In general, the three and compared? Comparison of methodologies gave similar results for the dose calculations.

Here were some significant differences between the meth-concentrations? Dose and costs?  ;

ods on the sonrce and transport calculations. MEPAS expo-The MEPAS methodology was developed to assess human sure and risk models have also been compared with the  !

health impacts from radioactive and hazardous waste sites. GENIl model developed for DOE by PNNL to compute The results of this methodology can be used to determine if radioactive dose values for residual contamination. The further action is required for the waste sites. A logical MEPAS models compared very well with this separate extension of the MEPAS methodology is to take its outputs model, and assess the type of alternative remedial actions required for site and the cost of such actions. That is why DOE ,

funded PNNL to development the Remedial Action Assess- QueSilon 8: To what extent can the ment System (RAAS) (technologies (Hartz and Whelan. analytical method handle complex 1988). MEPAS and RAAS have been integrated to allow .

users to assess the human health impacts from waste sites source term characterizations?

and the type of alternative remedial actions applicable for Multiple source terms? Hydrologic and each waste site. Figure 10 shows the integration between .

MEPAS and RAAS software.

hydrogeologic conditions? Exposure Pathway combinations? Remedial he RAAS software (windows-based) contains over 100 remedial technologies (Hartz and Whelan.1988, Bagnasen methods linked to cost and monitoring et al 1993) that can operation separately or in tech jory programs? ALARA considerations?

trains to implement risk reduction at waste sites. A hst of the RAAS technologies is provided in Figure 11. The inte- MEPAS has a Source Term Release Module (STRM) that gration of the MEPAS and RAAS software allows the user can handle several complex source types and configurations.

I to assess pre , during a.nd post-remediation human health The STRM can evaluate soil (surface and subsurface), sur-impacts for a single or a set of waste sites. Results from face impoundments, aquifers, and active sites (i.e., stacks, RAAS can be used by decision makers to support environ- vents, and direct discharges). The STRM also allows for the mental decisions by providing a comprehensive conceptual user to input know contaminant emission rates for all or site mode, baseline human health impacts (via MEPAS some of the contaminants. The STRM can also evaluate methodology), applicable technologies, remediation alterna- remediated sites that have caps and waste form that are l tives, contaminant concentrations, residual impact esti- cement or glass.

mates, secondary waste streams, completion time estimates, preliminary cost estimates, and worker impact estimates. The STRM conducts mass balance from the source for all contaminates over the simulation time period. This is accomplished by evaluating mass changes for each contami-Question 7: To what extent has the dose nant for each time set for each release mechanism (soil sus-Pension, volatilization, infiltration, overland runoff, decay /

model been tested and included in ,

degradation at the source, and known mflow/ outflow).

These mass losses are than partitioned to the appropriate NUREG/CP-0163 66

MEPAS environmental media for transport. MEPAS 3.2 can evalu- inclusion in repons because this version of MEPAS will be ate multiple and secondary sources through a two-step pro- Windows-based.

c:ss. MEPAS 4.0 (due in summer of 1998) will be able to evaluate multiple and secondary as a single step.

Sites with complex geology and hydrology can be assessed Question 10: Can the analytical method using MEPAS vadose and aquifer modules. The vadose and consider various restrictions on land use aquifer modules use the advective-dispersive equation to and site boundaries in calculating evaluate water and contaminant movement in the soil col-umn and groundwater. This allows for variations of concen- concentrations and/or dosest 3Dd in tations with time and depth. The vadose module assumes determining monitoring strategies?

homogeneous soil properties but several vadose zones can be modelin secession to simulate different soillayers with MEPAS was developed to deal with different kinds of DOE depth. In the MEPAS 4.0 version, multip'e aquifers can be and EPA waste sites. This means that land use (agricultural, linked together to simulate transport thro;gh heterogeneous industrial, recreational, and residential) is a critical issue groundwater. that MEPAS addresses in the exposure module. MEPAS can compute individual and population impacts for on-site The MEPAS exposure module allows the user to develop and off-site receptors. Figure 14 provides a summary of the complex combinations of exposure pathways. The exposure different types of receptors applicable to MEPAS. The module allows for four exposure routes (ingestion, inhala- results from MEPAS can be provided by contaminant, envi-tion, dermal contact, and external exposure). These routes ronmental media, exposure scenario, and receptor. This link to 25 different exposure pathways that can be evaluated flexibility allows the user to review and repon their results in MEPAS. Complex food chams can be developed such as n many different ways to understand the assessment in inigation of crops to cows to milk to humans using bioaccu- many dimensions. Results can be summed up to provide mulation factors. Figure 12 shows an example of a typical summary and cumulative informadon.

food cbain pathway used in MEPAS.

As mentioned in Question 6, MEPAS is linked to the RAAS software that allows for evaluation and comparison of dif-References ferent alternative remedial actions. MEPAS have been used Bagaasen, L. M.1993. Remedial Action Assessment Sys-to develop and refine monitoring programs at the Hanford tem - Remedial Investigation / Feasibility Study Reference Site. Based on modeling into the future, new monitoring Document (Draft). PNL-8751. Pacific Nonhwest Labora-efforts were developed and refined to adjust for the move-

, tory, Richland, Washington.

mint contaminants with time.

B uck, J. W., G. Whelan, J. G. Droppo, Jr., D. L. Strenge, K.

J. Castleton, J. P. Mcdonald, C. Sato, and G. P. Streile.

Question 9: Does the analytical method 1995. Multimedia Environmental Pollutant Assessment Sys-tem (MEPAS) Application Guidance, Guidelines for Evalu-include software graphical output for ating MEPAS Input portraying dose verses time for various Parameters for Version 3.1. PNL-10395, Pacific Nonhwest exposure pathways and specified Laboratory, Richland, Washington.

r:dionuclides and total effective dose Doctor, P. G., T. B. Miley, and C. E. Cowan.1990. Multime-equivalents including uncertainties? dia Environmental Pollutant Assessment System (MEPAS)

Sensitivity Analysis of Computer Codes. PNL-7296 Pacific The MEPAS 3.2 version does not produce graphical output Northwest Laboratory, Richland, Washington.

of the different results. Results from MEPAS 3.2 can easily DOE.1988. Environmental Survey Preliminary Summary be imported (use of comma delimited file format) into MS , Report of the Defense Production Facilities. DOE /EH-0072,

]

EXCEL or other graphical system to product the required U.S. Depanment of Energy; Environment, Srfety, and plots. An example of such a MS EXCEL plot is shown in

, Heahh; Office of Environmental Audit; Washington, D.C.

! Figure 13. The sensitivity /uncertamty module does product l graphical results of the cumulative and density functions as Droppo, J. G., Jr. and J. W. Buck.1996. Multimedia Envi-l a function of the results. ronmental Pollutant Assessment System (MEPAS): Atmo-l spheric Pathway Formulations. PNL !!080. Pacific MEPAS 4.0 will have graphical viewers for all the main Northwest National Laboratory, Richland, Washington.

results of the MEPAS (contaminant emissions, contammant concentrations, doses, and impacts). These graphical will be tasy in import into any work processor software for 67 NUREG/CP-0163 l

l _ _ _ - _ _ _ _ _ _ _ _ _ _

MEPAS EPA.1988. Analysis of Alternatives to the Superfund Haz- Models. PL10523. Pacific Northwest Laboratory, Rich-ard Ranking System. Prepared by Industrial Economics, land, Washington.

Incorporated, Cambridge, Massachusetts. Warren, B. R. and D. L. Strenge.1994. Multimedia Model-EPA / DOE 1995. Benchmarking of Three Multimedia Mod. ing Environmental Database and Editor (MMEDE).

els: RESRAD, MMSOILS, and MEPAS, DOE /ORO-2033,

,helan, G., D. L. Strenge, J. G. Droppo, Jr., and B. L.

Oak Ridge National Laboratory, Oak Ridge, Tennessee. Steelman.1987. The Remedial Action Priority System Hartz, K. E., and G. Whelan.1988. "MEPAS and RAPS (RAPS): Mathematical Formulations. PE6200, Pacific Methodologies As Integrated into the RI/EA/FS Process." In Nonhwest Laboratory, Richland, Washington.

Superfund '88, Proceedings of the 9th Nationa! Conference, Whelan, G., J. W. Buck, D. L. Strenge, J. G. Droppo, Jr.,

November 28-30,1988, Washington, D.C.

and B. L. Hoopes.1992. " Overview of the Multimedia Health and Welfare Canada.1992. Review and Assessment Environmental Pollutant Assessment System (MEPAS)."

of Two Multimedia Exposure Models: MEPAS and MUL- Hazardous Waste & Hazardous Materials, Vol. 9, No. 2, pp.

TIMED. Prepared by Intera Information Technologies Cor- 191-208.

potation, Environmental Sciences Division, Nepean, Whelan, G., J. P. Mcdonald, and C. Sato.1996. Multimedia Ontario, Canada. Environmental Pollutant Assessment System (MEPAS):

Holmes, J. A., B. E Lyon, M. R. Patterson, R. Phillipi, C. C. Groundwater Pathway Formulations. PL10907. Pacific Travis, and T. C. Tucker.1994. Description, Analysis, and Northwest National Laboratory, Richland, Washington.

Comparison of MEPAS and Other Multimedia Models for Whelan, G., and J. P. Mcdonald.1996. Multimedia Envi-Atmospheric, Groundwater, Food Chain Transpon, and ronmental Pollutant Assessment System (MEPAS): Riverine Exposure Pathways. ORNL/I'M-12421, Oak Ridge Pathway Formulations. PNNL-11176. Pacific Northwest National Laboratory, Oak Ridge, Tennessee. Nationt_1 Laboratory, Richland, Washington.

Morris, S. C., and A. E Meinhold.1988. Repon of Techni- Whelan, G., KJ. Castleton, J.W. B uck, G.M. Gelston, B.L cal Support for the Hazardous Waste Remedial Action Pro- Hoopes, M.A. Pelton, D.L. Strenge, and R.N. Kickert.1997.

gram on Health and Environmental Risks ofInactive . Concepts of a Framework for Risk Analysis in Multimedia Hazardous Waste Sites. BE42339 Brookhaven National Environmental Systems (FRAMES). Pacific Nonhwest Laboratory, Long Island, New York. National Laboratory, Richland, Washington.

Moskowitz, P.D., R. Pardi, V.M. Fthenakis, S. Holtzman, L.C. Sun , and B. Irla.1996. "An Evaluation of Three Rep-resentative Multimedia Models Used to Suppon Cleanup Decision-Making at Hazardous, Mixed, and Radioactive Waste Sites," Risk Analysis, Vol.16, No.2.

NRC 1997. Description of Multimedia Environmental Pol-lutant Assessment System (MEPAS) Version 3.2 Modifica-tion for the Nuclear Regulatory Commission. NUREG/CP.

6566, PL11676, Prepared for Division of Regulatory Applications, Office of Nuclear Regulatory Research, U.S.

Nuclear Regulatory Commission, Washington, DC.

Streile, G. P., K. D. Shields, J. L. Stroh, L. M. B agaasen, G.

Whelan, J. P. Mcdonald, J. G. Droppo, and J. W. Buck.

1996. Multimedia Environmental Pollutant Assessment System (MEPAS): Source Term Formulations. PEl1248.

Pacific Northwest National Laboratory, Richland, Washing-ton.

Strenge, D. L., and S. R. Peterson.1989. Chemical Data Bases for the Multimedia Environmental Pollutant Assess-ment System (MEPAS): Version 1. PE7145, Pacific Nonhwest Laboratory, Richland, Washington.

',trenge, D. L. and P. J. Chamberlain II.1995. Multimedia Environmental Pollutant Assessment System (MEPAS):

Exposure Pathway and Human Health Impact Assessment NUREG/CP-0163 68

l l

• l MEPAS l TABLE L List of major external reviews of MEPAS software US EPA Review of HRS and other models (1988)

NAS Hanford Single Shell Tanks Panel (1989)

External Review of DOE Priority System (1991)

US EPA review (November 1991)

NAS Review of DPM and other models (1991)

Health and Welfare Canada Review (1992)

External Review for Programmatic Environmental Impact Statement (1993)

NAS Risk Prioritization Report (1994)

National and International Multimedia Model Benchmarking (1995) i TABLE 2. List of major applications conducted using MEPAS software Hanford Single ShellTanks (1989)

DOE Survey uses MEPAS (1990)

Hanford Grout Study INEL Risk-Based Ranking State of Washington (1990)

Hanford 100-A:ca Study (1992)

U.S. Air Force Base Applications DOE's Programmatic Emironmental Impact Statement (PEIS)

Hanford Remedial Action-Environmental Impact Statement (1994) l Baseline Environmental Management Report (1995) l Waste Isolation Pilot Plant (1996)

Hanford Integrated Risk Assessment Project (1993-1996) 69 NUREG/CP-0163

MEPAS 3.2 STRUCTURE Source Transport Exposure Impacts Volatilization Population Air Inhalation MEI Surface Impacts Suspension IWater Ingestion ll Radionuclides Infiltration Water Carcinogen 8 No carci 3

stact et, Soil Direct Source ~I Figure 1. Diagram of MEPAS Overall Structure STC METHODOLOGY RET. EASE = %D + %S + %V + %R + %L VOLATIZATION RUNOFF - %R

-%V SUSPENSION - %S WASTE SITE I

m> DECAY - %D

• t e

Figure 2. Diagram of Source Term Release Modules NUREG/CP-0163 70

Diagram of Modeled Zones l

l Waste Site

- -- 1 EFe- memannemumme  !

Saturated _

. _l

• .E'"'

"iggjg1 zone n '

_ j l

Figure 3. Example of the Linkage between Vadose and Saturated Zones Air Exposure Routes Ingestion

• Resuspension

- Leafy Vegetables _ g ;;

- Other Vegetables External

- Meat

- Milk

- Soil p{

4

• _g

- Air

• Dermal + -

• ~

- Soil ,.* -

• Inhalation

- Air l

Figure 4. Exposure Routes and Pathways for the Atmospheric Medium 71 NUREG/CP-0163

Groundwater Exposure Routes

• Ingestion

- Drinking Water

- Showering h' c--]s

- Leafy Vegetables . g.,: ..l

- Other Vegetables pf

- Meat

- Milk

.-.s g- h - 4

.-.. ' evg

^="-'-

• Dermal [. .- 'A Y

- Showering

• Inhalation

- Showering

'rJ;gc/ s- e i

Figure 5. Exposure Routes and Pathways for the Groundwater Medium Surface Water Exposure Routes

• Inges on

- Drink.mg Water

- FinFish hl ... -

- Shell Fish A

- Showering

1. T

- Leafy Vegetables

+

- Other Vegetables e m, Ar=w

- Meat sex,

- Milk 8 D

%s -

s

.,s

?.),},.. ]

a.mm. Aquate Foods Figure 6. Exposure Routes and Pathways for the Surface Water Medium NUREG/CP-0163 72

-w. -. -

Surface Water Exposure Routes rp Dermal - "%

- Showering k

- Swimming Q

- Shoreline -. .j 8" " ""8 i

Inhalation

- Showering External

- Swimming

- Boatmg _

^ '

- Shoreline --

~

, ~

Figure 7. Exposure Routes ar.d Pathways for the Surface Water Medium (Cont)

Soil and Direct Exposure Routes Direct Soil Exposure Direct Radiation

- Ingestion - External

- Dermal r

- Resuspension Direct Food

- External - Ingestion Extemal i1 Exposure

n. K

~ ~

1 p 1 v _ SoilIngestion Figure 8. Exposure Routes and Pathways for the Soil and Direct Medium l

73 NUREG/CP-0163

Baseline risk isopleths for residential scenario at time 0 N Columbia River

.. i

. l

' ,5

.I

%l, o o

/

& 4 sh ,

-f lllllL N '

b. -

M Figure 9. Illustration of Spatial and Temporal Dimcasions of MEPAS Results Relationship of RAAS to ReOpt and MEPAS RAAS V1.1 MEPAS V3.1 ReOpt V3.1

_ site.

,,,.,y s technology conceptual

l. pulation.

> ... <.i;

$ technok3hr he contaminant - ,,,,,,,,

appl 6cabliity "d

descriptions and i  : essmate -

flow diagrams ( contaminant data maximum tehnology . . ,gyg, fg*

. regulatory detai medium release site e '

indNI a applicability - assessment ,-

esmate . .

technology feasibility analysis technology effectiveness estimates I attemative performance comparisons )

I Figure 10. Diagram of the integration of MEPAS and RAAS Software Capabilities NUREG/CP-0163 74

" Building Block" Technologies for Contaminated Soil Remedial Alternatives institutional control technologies access coreois land use resinctions monnonng removal :w : containment

];[ Co m OL technologies h technologies acn s .- - ho f ,

ousr/vapw suppresson J ,E4 P.

underground tank removat

• /? $.1Alg N Eie"y -49:w w ijf o Td@)

surface water control su, tace water removat in situ treatment technologies emetrokawte separaban m := solofr.sterwycten sad flushno m situ RNo4Hoventmo m se sobddesteorumang sad vasor extrachorwr vi su no.i.no v.mm : m sau vnnrcm.on sodv.por. a cuorwi m se as nemme n urse.uon surt.co . remova j

Figure 11. Diagram of the Different Technologies Available in RAAS Software Example Exposure Route hi -

Food chain j @

model b Inhalation Ingestion Dermal Contact 7 External Dose Figure 12. Example of Food Chain Pathway in MEPAS 75 NUREG/CP-0163 i

l l

l Cancer in:Idence for U238 by Groundwater Exposure Route 1.00E-17 1.00E-18 i - #

l I ,

8 1.00E-19

/ I -L

! i >

$ . -. DnnW 1.00E-20 [ ,

$ l l l 1 - Meat Milk  !

E j j  ;

j 1.00E-21 l' l l

' l 1.00E-22 '

/  !

1.00E-23 O 500 1000 1500 2000 2500 3000 3500 Time (years)

Figure 13. Example of Graphical Output of MEPAS Results via MS EXCEL n

k Exposure Media

• Air Public

- Agricultural

- Regional e

-l

• Groundwater ,

• Surface Water Family

• Direct $

- Soil -

Boundary

- Radiation Farm

- Food Family i

Figure 14. Diagram of Different Receptor Typses Available in MEPAS Methodology NUREG/CP-0163 76

Frcmswerk fer Risk An: lysis in Multimedia Environmental Systems (FRAMES)

Gene Whelan, Ph.D., John W. Buck, Karl J. Castleton, Bonnie L. Hoopes, Mitch A. Pelton, John P. Mcdonald, Gariann M. Gelston, Randall Y. Taira Pacific Northwest National Laboratory P.O. Box 999 Richland, WA 99352 Introduction or 3) linking DandD to modules of other Level 2 models, where appropriate. Regardless of the chosen approach,it is The objectives of the Nu: lear Regulatory Commission imperative that some sort of commonality exists between (NRC) Workshop on the Review of Dose Modeling Meth- the Level 1 and Level 2 versions of "DandD," which results ods for Demonstration of Compliance with the Radiological in a smooth transition. Consistency between the Level 1 Criteria for License Termination are to 1) provide the NRC and 2 versions should be a very important from a regulatory staff and the public with an overview of currently available perspective. In effect, an approach may be required to allow Federally-Sponsored dose models appropriate for decom- linkages between components of different models to help in missioning assessments and 2) discuss NRC staff-developed the smooth transit.on from a Level 1 to a Level 2 assess-questions related to model selection criteria with the fmal ment.

rule on " Radiological Criteria for License Termination" (62 FR 39058). The NRC has been working on regulatory guid- As part of the NRC Workshop on the Review of Dose Mod-ance for residual radioactive contamination from decom- cling Methods for Demonstration of Compliance with the Radiological Criteria for License Termination, NRC has missioning. Detailed documentation of the scenarios and cdculations are presented in NUREG-5512. Volume 1 identified ten questions to help in the evaluation process of includmg approaches other than DandD and its default-data (Kennedy and Strenge 1992). The NRC with the suppon of Sandia National Laboratory (SNL) has been developing a set (NRC 1997). Because the NRC staff envisions that the decision methodology (i.e., NUREG-1549) that can imple. Screening calculations will be performed using DandD, a ment NUREG-5512 as part of the decommissioning of sites.

Pl atform or framework for linking modules with DandD may be beneficial to help meet the needs of NRC for mov-This Decontamination and Decommissioning (DandD) ing DandD from a Level 1 analysis to a Level 2 assessment.

methodology was developed to specifically address the Discussion of such a framework would, in effect, link the dose-based criteria for license termination and utilizes a ten NRC questions.

series of box models that have been connected to represent scenarios that address the release of contaminants from a source into the environment, contaminant movement History of Framework Development through various environmental media, and exposure / dose to humans through various exposure routes. DandD incorpo- For over 40 years, medium specific models have been and rates all of the information necessary for a Level I screening will continue to be developed in an effort to understand and assessment (e.g., NRC 1994), where the necessary scenarios Predict environmental phenomena, meluding fluid-flow pat-and pathways have been "hard-wired" into the model, tems (e.g, groundwater, surface water, and air), contami-including building scenario, residential occupancy, ground- nant migration and fate, human or wildlife exposures, ,

water transport to drinking water, and building renovation. impacts from specific toxicants to specific species and their A Level 1 assessment " embodies a procedure for screening rgans, cost-benefit analyses, impacts from remediation candidate hazardous waste sites," and a Leve! 2 assessment alternatives, etc. For nearly 40 years, medium-specific estimates site-specific " environmental risks and remediation m dels have been combmed for either sequential or concur-costs"(NRC 1994). rent assessments (Whelan et al.1986). The evoluticn of multiple-media assessment tools has followed a logic pro-DandD is based on an extensive default parameter library gression, as illustrated by Figure 1:

and attempts to provide a conservative assessment with non-

• In 1959, the Stanford Watershed Model (SWM) was site-specific parameter values. As a cost-effective and developed and represented one of the first " integrated" quick-assessment analysis, this approach meets Level 1 models, as it linked multiple processes by simulating the screening guidelines. 'Ihe NRC is lookmg to move the land-phase of the hydrologic cycle for an entire water-DandD methodology to more site-specific analyses, hence, a shed (Crawford and Linsley 1966).

i Level 2 assessment. The intent is not necessarily to choose

! another model to replace DandD but to formulate a strategy

• In 1969, Oak Ridge National Laboratory presented the Unified Transport Approach (UTA) and more refined

( to smoothly transition from a screening level analysis to a versions like the Unified Transport Model (UTM-TOX; more site-specific assessment. 'Ihis strategy may be repre.

sented by 1) updating the default parameter database with Patterson et al.1984), which coupled (i.e.,"hard-wired")

more site-specific information,2) updating the modules of detailed numerical models, describing individual envi-the DandD code to represent more site-specific phenomena, ronmental media (e.g., groundwater, air, surface water, 77 NUREG/CP-0163 l

FRAMES and soil). Although these models have been funded by existing system. In multiple-component systems, models, the U.S. Environmental Protection Agency (EPA; Patter- modules, attributes, or subroutines are usually linked to son 1986), the UTA did not progress into general use each other in the typical" spider-web" arrangement. Each possibly because 1) the models tended to be difficult to time a new attribute is added to the system, connections understand, operate, modify, and maintain; 2) data to (e.g., data processor or mathematical algorithm) are operate the models were generally unavailable; and most arranged between new features and existing ones. In many importantly 3) computer power to drive the system was instances, modifications to the actual programs themselves lacking at the time. must be initiated, thereby changing the legacy of the model. j Experience has clearly demonstrated that modifications e In 1978, mixing-tank models, which represent compart- l ments with uniformly mixed contents, began a large within the " spider-web" construct many times results in >

resurgence in the assessment arena. Mackay and Pater- unnecessary and unexpected changes in other components.

son (1986) noted that Baughman and Lassiter (1978) Although changes can be made, the process tends to be suggested using evaluative models, which suppressed time- and resource-consuming.

the phenomenological detail usually associated with the A " cleaner" approach for incorporating new models, mod-more mechamsu,cally-based models. As a result, numer- ules, attributes, or subroutines is to reduce the number of ous mixing tank models with varying degrees of sophis- variations in the connections so that existing and new tication have been developed (Burns et al.1982; Mackay attributes maintain their original legacy, realizing that some 1979; McCall et al.1983; McKone and Kastenberg relatively minor modifications may be necessary. If the 1986); Renner 1995). interaction and connection of components is focused at the e In 1984, development of the first semianalytically based, interface between the components, then adding new compo-fully coupled, sequential multimedia model, which nents or modifying existing ones would not impact the sys-accounted for temporally and spacially varying contami- tem as a whole, as illustrated by Figure 3. Changes in the nation (chemicals and radionuclides) within designated assessment do occur over the life of the project, and a sys-media (i.e., compartments) began (Whelan et al.1987). tem should be able to adjust (within reason). By specifying Each medium-specific model was "hard-wired" into the interface specifications, models, modules, databases, and system, so replacing medium-specific components was other frameworks can now effectively communicate, as each not built into the system. Since 1984, a number of semi- one will know a priori the connection requirements (e.g.,

analytical multimedia models have been mtroduced " telephone numbers") for communication.

(Whelan et al.1992;Yu 1993; Hung 1996; Moskowitz et al.1996; Laniak et al.1997; Mills et al.1997). These Significant changes also occur with the computational multimedia models were made possible with the intro- power of computers, programing languages, new and inno-duction of desktop computing. vative concepts and approaches, more enhanced databases, and access to new and improved databases, etc. Also, dif-e in 1987, the development oflarge multipurpose frame-ferent organizations and people require different relation-works began, which "hard-wired" a suite of codes ships between models and assessments to meet needs. To together and investigated, not just the distribution of contaminants in the environment, but relationships allow a suite of users the flexibility and versatility to con-between a suite ofissues deemed valuable (e.g., regula- struct, combine, and couple attributes that meet their spe-cific needs without unnecessarily burdening the user with tory criteria, data quality objectives, CERCLA and extraneous capabilities, the development of a computer-RCRA processes, etc.) (Hartz and Whelan 1987). Some based methodology to implement a Risk Analysis in Multi-of these multipurpose frameworks include the Remedial media Environmental Systems (FRAMES) was begun in Action Assessment System (RAAS;Whelan et al.1990) and Sandia Environmental Decision-Support System 1994. FRAMES represents a platform which links elements together and yet does not represent the models : hat are (SEDSS). linked to or within it; therefore, changes to elements that are In all of these approaches, individual components (or mod- linked to or within FRAMES do not change the framework.

zls) are "hard-wired" into the systems, and to a certain degree, the legacy of the original model that has to be forced into the system is compromised. Any changes to the com- Structure ponents willinvariable result in changes to the system, because these systems were not designed to accommodate Over the past 10 years, researchers have focused on devel-change. oping fully integrated, physics-based, intermedia models that allow for a more transparent connection between indi-If significant modifications are required in these existing vidual medium-specific modules. These models take a systems, the changes tend to be cumbersome, as illustrated holistic approach to environmental assessment of potential by Figures 2 and 3. Figure 2 illustrates the interrelation- contaminant impacts as they simulate 1) the release of con-ships and connections between components composing an taminants into the environment,2) migration and fate NUREG/CP-0163 78

FRAMES through various environmental media (i.e., groundwater, nant source and release to environment (including surface surfa.:e water, air, and overland surfaces), and 3) resultant hydrology); overland, vadose zone, saturated zone, atmo-exposures and impacts. The overall scope of these models spheric, surface water, food-supply (including animals and includes evaluation of on- and off-site impacts from active plants to humans); intake computation, and health impacts.

and inactive sites involving both chemical and radioactive Each of these elements, and many that are not listed. will be wastes. Although differing in their individual scope, these represented by separate modules. Each of these modules multimedia models tend to be " analytical"in nature (e.g., should:

miinly compartmental, analytical, semianalytical, and/or empirical algorithms) Just because numerical and struc- = be object oriented. An object-oriented module repre-tured-value (e.g., Hazard Ranking System) models are tradi- sua a c mp nent that is independent of other compo-tionally not associated with the physics-based multimedia nents. Each component is viewed as an entity, where models, this should not preclude their use within this holis- interactions and linkages occur at interfacing junctions tic approach or from access as an outside model. In addi- and where a transfer ofinformation can occur. Object-tion, there is no reason why a framework cannot be riented design currently represents the state-of-the-art established that accounts for both the level of detail (i.e., in design.

r: solution) of the models (e.g., structured-value, analytical, import the data required for execution. The data may be and numerical) and the scale of the assessment (e.g., imported from result files contained in FRAMES or medium-specific, watershed, regional, and global). directly from the user. It is a requirement of each mod-ule to read all data items correctly from the appropriated A number of governmen agencies and private companies files in FRAMES.

have used single and multimedia models for federal regula- . execute the model correctly, given the data gathered in tory and compliance activities associated with NEPA, CER- the import process.

CLA, and RCRA as well as for state regulatory and e correctly export data to FRAMES data files.

compliance activities. The advantage is in consolidating e n t have data redundancy, as when data are accessible, these single-medium and multimedia models into one stan-dard tool Consolidating the best aspects of these models visible, and transferable to all components. The data-could highiight their strengths and minimize their shortcom- VerlaP concept is contrary to object-onented design and ings. In addition, EPA and DOE have developed many other results in a less eHicient system. Object-Oriented useful models that would benefit from access to this new designs do not tisually reqm,re data to be visible to all framework (e.g., IEM, EPACMTP, EXAMS, WASP, TOXI- compeents.

WASP, HELP, PRZM, GENII, AT123D, etc.), thereby pro- There are three software considerations with respect to data-viding users with greater access to these models. As transfer linkages: dtta redundancy, dynamically linked technology advances, a next-generation framework would modules, and a franework user interface. ,

eventually be needed to address regulatory, compliance, i oversight, and site-specific applications, and would be Data redundancy linked to a GIS to facilitate data transfer and analysis and Data redundancy occurs when the same information is presentatims. This expanded system could also link stored more than onc e. Within a given element classifica-human-health / ecological impacts with remedial technology assessment, cost analyses, and risk reduction. The new tion (e.g., vadose zor,e), certain data requirements exist. For framework (e.g., FRAMES) could service various agency,s oisture content is a traditional characteristic of needs in defining soil cleanup levels and waste-site exit con- the vadose zone. Specifying the exact form of the data in ,

centration criteria, evaluating risk reduction by remediation each element could limit access by new modules that may I be added to the system, and any data storage and retrieval technologies, generating end point cost drivers, meeting regulatory applications, conductmg programmatic studies, system should not be developed that may limit access. For and assessing site-specific applications. The result could be example, even though two vadose-zone modules require moisture content as a characteristic of the element, one a compositely constructed system, that greatly enhances versatility and flexibility to allow more focused and cost- module may require the information as a dry-mass fraction and the other may require the same information as a volu-effective multimedia modehng assessments.

l metric fraction. Mandating the exact form of the character-istics describing the el: ment would mandate wholesale D:ta Linkages and Information changes to the data in;ut requirements of each module. In addition, this approach would limit flexibility and versatility Transfer by not allowing FRAMES to address future new and inno-vative trends contained in potentially new models trying to Within the modeling-based FRAMES resides a collection of gain access to the framework. Therefore, a new system computer algorithms that simulate elements of a transpon, must easily allow for el ange without constraining access to exposure, and risk-assessment system, including contami-future developments. The burden to absorb change should 79 NUREG/CP-0163

FRAMES never be on the framework;if so designed, FRAMES would fer ofinformation to the framework or another module. The become obsolete in a short period of time. input and/or output data files used for transferring informa-tion have the following attributes:

To meet these needs and constraints, FRAMES structures its data linkages to allow for the following types of data files:

• The files should be easily used by the most common m deling languages and software. Typical languages e Primary Data Communication Files (PDCF): PDCFs are melude FORTRAN, C, C++, Pascal, and Visual Basic; the data files that are used to transfer mformation typical software includes Excel and Lotus.

between modules. These files embody the concept of

• Where appropriate, the files should include both the object-oriented design by specifically identifying and numerical values and their corresponding units.

segregating data associated with the linkages at the

• The files should be self-descriptive. When a user with boundaries of the modules.

n knowledge of the file or its specifications views the

. Global Input Data Files (GIFs): The GIF files will be IlI** ** "S*T should be able to correctly interpret the data stored where all user input is stored. Each module is stored therem..

responsible for deciding what data are included for

• As much as possible, the files need to be computer plat-itself.The GIF files contain Modular User Interface Sec.

tions (MUISs). The MUISs represent the user-supplied form independent. Platform independence will allow information that is transferred through the Modular User Part of an assessment to be completed on more powerful Interface (MUI). These sections allow for updates to computers.

each module, new data requirements for each module,

• Separate input and output data files should be developed.

and changes without constraining access to future devel- ne input data refer to those required for a successful opments. completion of a mod ile's application. All input data will be stored in the GIF file, which is required to suc-e Other Data Files: Under the design, FRAMES has cessfully operate the module. User hput data are iso-unlimited access to data and databases. Other data files could include, but are not limited to: lated from all calculated results to ensure that the sensitivity / uncertainty analysis runs efficiently and aids

= Imported Data Files: Data files that contain information in the ability to reproduce results. Output data refer to needed for models. (i.e., laboratory results of soil, air, calculated results.

and water samples, which are typically in spreadsheet form). Framework UserInterface

. Exported Data Files: Data files that serve as input t A Framework User Interface (FUI) must be desiEned and larger assessments (e.g., results of a site assessment are .

implemented that will 1) allow for relatively easy m, clusion reformatted for efficiency in the Modular Risk Approach f additional modules and models,2) promote access to (MRA; Whelan et al.1994)]. national databases; 3) minimize data-exchange require-

= Maintained Databases: Databases that are maintained .

ments within FRAMES,4) allow for unlimited access to by other m. dividuals (e.g., IRIS for toxicological data, data, and 5) address linkage concerns. The responsibilities GEMS for population data. etc.). for the FUI need to be established so each module can func-Dynamically Linked Modules tion within the system without added restrictions but still allow the responsibilities to be defined. He FUI is responsi-The modules must be linked as the direct result of user ble for the following selection. This requires strict protocols to determine the

• Ensuring that the modules are connected properly and validity of various linkages and resolve all data-transfer 8 Appropriately.

needs. Linkage concerns include the following:

• Ensuring that the module has access to an unlimited sup-

= A system should be constructed such that 1) data, spe- ply of data, where appropriate.

cific and unique to each module but not produced by

• Allowing for unique forms of data entry (i.e., selecting other modules, can be user-supplied and 2) data, specific sml properties from a map of the United States or from and unique to each module but produced by other mod- ,

the Soil Conservation Service soil tnangle, or retrieving ules, can be supplied by other modules. data directly from sources on the Internet).

• Individual modules must be linked m. such a manner as

• Edli% N6 fWesppe d to facilitate data transfer at the interface between mod- g gg to be run until input data requirements through the MUI File specifications describe how all information is to be are complete and data required from other modules are stored within the framework and passed between modules, available.

Rese file specifications are not associated with information storage or transfer within each module, only with the trans-NUREG/CP-0163 80

FRAMES e Ensuring that if a module behaves inappropriately, then establishes protocol to 1) select the appropriate modules the data for the other modules are protected from the needed to address the problem,2) controls the flow ofinfor-errant module, and inform the user of errant behavior of mation to and from the modules chosen for the problem, and l

I modules. 3) segregates input from output data by placing the data into l = Managing storage of user data and results. specialinput and output data files [i.e., Global Input and e Managing information to inform the user of which mod. Output Data Files (GIFs and GOFs)].

ules are available in FRAMES. F gure 5 presents a more detailed illustration of the actual I implementation of a module within FRAMES. As illus-trated in Figure 4, each module is contained within the FUI.

Object-Oriented Design ,

The user initially interacts with the FUI, identifying the con-l A structure should be developed so that the type of model stituents of interest, developing the Conceptual Site Model l

employed within the framework is (more or less) unimpor- (CSM), and iniuating the sequence of selected modules tant. In effect, the structure should view all ofits compo- from within FRAMES and models from outside FRAMES.

nents as real-world objects, uninterested in the inner The FUI i iput and output data are stored in the GIFs and workings of the objects. For example, FRAMES should not GOFs, respectively. The first module, which is chosen by discriminate between an analytical or numerical model. If the user with the help of the FUI, is then initiated as part of l

time-varying concentrations at a location are required, the CSM. The first MUIis then activated, and the user I

FRAMES should not be concerned with the model that pro. inputs the appropriate information for that module. Addi-duced them. If the objects represent real-world compo- uonal information could also be supplied to the MUI from previous modules. The GIFs and GOFs interact with the nents, the user will be able to conceptualize the problem and construct modules that address the conceptualization. MUI through a data-processing program (i.e., circles in Fig-

! ure 5). The output from the MUIis converted to the appro-To develop an " object-oriented" framework, specifications priate units and stored in the GIF using a data-processing for structuring FRAMES must be identified: 1) the form of program. Other parameters calculated from input data (e.g.,

the boundary conditions between modules,2) units,3) stor- retardation factors, which are calculated from moisture con-l age protocol for input and output data,4) user-interface tent, distribution coefficient, and bulk density) are likewise l requirements,5) scale (physical size and attributes of the stored in the appropriate GOF for use by succeeding mod-l assessment),6) mesh resolution (i.e., level of detail associ. ules (including GIS or sensitivity /unc rtainty modules) l ated with the boundary conditions between modules), etc. from within FRAMES or other, outside frameworks.

! FRAMES should allow the user to choose models to use.

! FRAMES should allow the user the option to 1) incorporate As Figure 5 shows, the MUiinteracts directly with the GIFs these models into the framework as a working module or and GOFs through data processing programs. The FUI acc ss the model from outside FRAMES,2) access outside actually truuates each module's application (i.e., runs the l m dule). A data-processing program reads input from a

data,3) pick and choose and match modules,4) obtain help /

guidance, and 5) interact with other frameworks. FRAMES GIF, which originated from the MUI. The boundary condi-thould represent a constant among the ever-changing mod- 15 "8 f r the module are read from a GOF. These boundary condiuons may ongmate from the FUI, MUI, or a model I els and modules that are replaced over time. By developing an approach that uses an object-oriented framework, a sys- utside of FRAMES. The outside model's output would be i tem can be developed that provides a mechanism for using stored m, a GOF in FRAMES by way of a data processmg .

Program (see Figure 5). All data from the GIFs and GOFs l

! models that have been previously developed, as well as

! models that will be developed be developed in the future. are pmeessed into the appropriate units and formats by data-l processmg programs, which m effect reformat the informa-tion so the individual module does not have to be modified.

l l Figure 4: 1) represents a framework that encompasses, inter- j acts with, and connects modules that are typically associ- After the module is implemented, it writes its information to ated with current physics-based multimedia assessments its normal files and processes selected data output for a (e.g., MMSOILS, MEPAS, RESRAD, PRESTO, etc.); 2) GOF by way of a data-processing program. Therefore, mul-illustrates how FRAMES surrounds and interacts with tiple data-processing programs may be required for each medium- or attribute-specific modules; and 3) presents the module. These programs basically convert the information interrelationships between a FUI and the modules housed to the correct units and store data within the proper time and within the FUI. Typical modules include those identified in  ; pace scales, where appropriate. Techniesi specifications the figure, where modules can be added or deleted depend- for these data-processing programs should contain as few ing on the assessment. For example,if ecological or GIS constraints as possible. Becattse all it:put data are stored in modules are required, they can simply be added, as long as a GIF, sensitivity / uncertainty analyses are easy to imple-they meet framework specifications. Likewise, a probabilis- ment. All output is stored in GOFs, allowing for easy access tic module can be added when Monte Carlo assessments are and analysis, including plotting, statistical analyses, QA/

r: quired. The FUI helps the user define the problem, which QC, report writing, summations, etc. As Figure 5 shows,if l

81 NUREG/CP-0163 ,

1 1 _ _ _ _ _ _ _ _ _ _ _ _ _______________ i

l l

l l

FRAMES more than one module was selected by the user, the FUI prior to running each of the modules in their appropriate would call up the next module's UI, and the process would order.

1. E ** ' Real-world, object-oriented design represents the founda-Because the analysis is dependent on the constraints of the tion of FRAMES. By structuring FRAMES so the objects problem to be solved, different problems may require differ- represent real entities (e.g.,3-m thick, sandy-loam, vadose-ent models or features. Any framework should be structured zone layer), the FUIis able to visually capture the essence to take advantage of the appropriate models required for the of the CSM for the user. In effect, the FUI offers a tool for analysis. As opposed to trying to convert all needed models " laying out the plumbing" to perform waste site assess- i or programs to meet its constructs. FRAMES should pro- ments. From 50 to 80% of the learning that is generated l vide an access port for these models. Under FRAMES, occurs during the CSM-development phase (i.e., prior to  ;

these models would have access to GOFs though a data-pro- model simulation). Learning results from asking and j I

cessing program. The specifications for this program would answering basic questions such as, identify the format for easy access witho'.it unduly burden- ,What is connected to what?'

ing the preexisting model or program. Figure 5 illustrates l

'How does the process really work?' )

the means by which these outside programs could access and interact with FRAMES. 'What is consumed when this and that are produced?'.

]

Once the " plumbing" has been arrayed, the software shifts to serve as a vehicle for tracing the dynamics that are Frarnework User Interface (FUI) implied by the " plumbing."

The user or a automated-access program (also referred t Figures 6 and 7 present very simple illustrative examples of as a " user') interacts through the FRAMES FUI. The FUI how the user visually constructs the CSM using the FUI.

is the mterface that accesses the contaminant database and Icons are available that describe the modules housed within subroutines for setting up the problem and establishing the the FUI (e.g., source, vadose zone, saturated zone, nyer, air, CSM. The current chemical database contains between 500 receptors, food chain, etc.). The user chooses and connects and 800 chemicals and radionuclides. Information includes icons that recreate the actual or potential path of the con-physical and chemical characteristics of each constituent, taminants as they move from the source to the receptor.

environmental partitiomng data, transfer and uptake rates, and exposure and risk data. Databases traditionally used by Figure 6 (i.e., Site 1) illustrates the emission of a contami-EPA, DOE, and NRC are included, where appropriate, so nant from a source, as it partitions to the air (e.g., volatiliza-the user can meet specific needs dictated by the problem at tion or suspension) and to a saturated zone (e.g., leaching or hand. The CSM includes the construction of the problem direct discharge). Two receptor locations are identified.

that the user needs solved. With the help of the FUI, the Both receptors are breathing air and drinking water contam-user describes the problem and chooses the appropriate inated by the source, and risk calculations are being com-modules and models to address it. All tuodules under . puted for each receptor location. The lines connecting the FRAMES would be available for selection from a pop-down source to the receptor via the air and saturated zone visually menu. He user sequentially selects the appropriate source- show the path that the contaminant follows.

term modules, transport pathways, and exposure routes that Figure 7 (i.e., Site 2) illustrates the emission of a contami-specifically address the problem. The FUI organizes the nant from a source, as it partitions to 1) the air (e.g., volatil-selection process to ensure that only appropriate selections ization or suspension),2) the first of two vadose zones (e.g.,

are available. Allinput data to the system resides in GIFs.

leaching or direct discharge), and 3) a river (e.g,, direct dis-Input data are segregated from other data so sensitivity /

uncertainty analyses can be easily performed within charge). nree receptor locations are identified. The first FRAMES. Any input data modified within the FUI would receptor 1)is directly in the path of the atmospheric plume, emanating from the source, and 2) breathes the contami-be stored in designated GOFs. Access to both GIFs and nated air. The second receptor eats contaminated crops that GOFs would be made available to all modules that reside were irrigated from water taken from the river, which was within FRAMES. Both GIFs and GOFs would also be available for access by outside frameworks, models, or con. contaminated by the source. The third receptor is directly trol programs (see Figure 4). Following selection of the exposed to contaminated drinking water from contamina-tion that migrated through two vadose zones and a saturated appropriate modules and models, the FUI would automati.

cally call up each individual MUI of the selected modules in zone to a drinking-water well. Three sets of risk calcula-tions are perfonned, but only two icons are defined because the correct order. When the user has interacted with each MUI and addressed all inquiries sequentially, the FUI would the assumptions forming the basis of the risk calculations are the same for two of the receptors.

iraplement all analyses in the appropriate order. Therefore, all MUIs would be sequentially accessed and implemented NUREG/CP-0163 82

FRAMES Figure 8 presents a detailed illustrative example of what the .

Every problem must begin somewhere. In FRAMES, current FUI looks like and illustrates the release of contami- the source represents the beginning, and the user desig-nants from a source (i.e., Hanford Tanks), as it partitions to nates what the source is. For example, the source could the air (Hanford Air) and the first of two vadose zones (Zone be designated by groundwater concentrations at a drink-I 1 and Zone 2). Vadose-Zone contamination eventually ing-water well, where no transport calculations are migrates and contaminates the saturated zone (Hanford required. The water concentrations would be directly Aqu), which discharges to two different rivers (Columbia used in any dose / risk computations.

and Yakima). Two receptors are identified (Native Ameri-

. The FUI does not allow cyclic dependencies. Contami-can and Adult Pop) and are exposed to air and water con-nation from a source will not be allowed to cycle tamination that has made its way through three different through several modules and return to its point of origin, food chain locations and routes (Richland, Kennewick, and as illustrated by Figure 9. In Figure 9, there is an emis-Pasco). He Native American and Adult Pop live in all three sion from the source to the air, which then deposits con-locations but have different life styles and breathe air and tamination back on the original source. Because the consume food and water differently. Separate risk calcula- results from one module sequentially interact with the tions are, therefore, computed for each receptor (Native next module, concurrent and simultaneous analyses with Risk and Adult Pop Risk). feedback loops between modules are not addressed.

Each icon in Figure 8 contains three circles (see left side of each icon in Figure 8) of which only one circle is visible. If the topmost circle (red light on the actual screen) is visible, Scale and Resolution Considerations this denotes that a model has been chosen to represent the The world is an extremely complex place. Any attempt to icon; this condition is not illustrated in Figure 8. If the cen-develop a framework that is all-encompassing will result in ter circle is visible, as illustrated in all but one of the icons an extremely cumbersome tool that is difficult to use or con-(yellow light on the actual screen), then this denotes that the tains an undue amount of constraints. The most eflicient module's database has been populated. Finally,if the lower-most circle is viable, as illustrated with the " Contaminants" frameworks are developed to address specific problems. By developing an approach that solves too many broad ques-icon, then the module has been run. This street-light tions, unnecessary constraints are placed on the system.

approach provides the user with an instantaneous visualiza-tion of the status of the assessment. As one can imagine, the If a global assessment is required, then this framework pictures in Figures 6 through 8 can quickly become very should not have to also meet requirements to address site-messy and appear to be fairly complex. If the pictures do specific analyses. This is not to say that a site-specific anal-become too detailed, it conveys to the user that a very com- ysis may not be important, but the site-specific analysis plex problem is being assessed. should represent a boundary condition to the global assess-ment. The temporal, spacial, and data requirements for a In addition to presenting a flow diagram of the CSM, the global assessment are different from those associated with a FUI it is also responsible for coordinating icon names and three-dimensional locations, which are relative to a refer- site specific assessment. Frameworks should be developed separately for these differences in scale and resolution, but ence point for the geographic location. For example, nearly the different frameworks should be structured so they can all the sites at the Hanford installation in Richland, Wash-communicate with each other. In this manner, the site-spe-ington, are given coordinates related to the most northwest cific release at Chornobyl, for example, can be included as a corner of the installation. The third dimension is the eleva-boundary condition to an ensuing regional assessment. Any tion of the icon. A unique name is required for each icon, tool that is developed to solve ALL problems is a tool that and the same name for two icons implies that the icons are usually is too cumbersome to use for most problems. Divid-the same icon. By allowing multiple icons with the same ing the problem into manageable components allows for an name, the FUI can account for different activities impacting efficient and effective analysis, the same icon.

When frameworks are developed to integrate the effects of Even though the pull-down-icon approach is flexible and multiple components, scale must be considered in the devel-versatile, certain protocol are enforced. For example, opment process. Scale is defined as the physical size and

• One icon can represent and encompass a rather detailed attributes of the problem that is being addressed. Four basic and complex model type. For example, a source-term scales could be defined as follows: medium-specific, water-release module may include many different types of shed, regional, and global. Medium specific refers to those sources (e.g., elevated and heated stacks, landfills, models and assessments that address specific media during ponds, etc.), although the source is only represented by the analysis, such as, waste site, vadose zone, saturated one icon. zone, river, air, e tuary, overland runoff, even geochemical modules. In other words, a specific code has been devel-oped to address a particular aspect of the environment. De 83 NUREG/CP-0163

FPAMES information is generally site-specific, although regional and FRAMES should be flexible enough to allow a less complex national data may be incorporated into the model. Exam- model to be used, where appropriate; therefore, the level of ples of a multimedia framework composed of medium-spe- detail associated with the model does not dictate the resolu-cific modules include PRESTO, RESRAD, HRS, SSL, tion associated with FRAMES; the boundary conditions MEPAS, MMSOILS, MULTIMED, GEOTOX, SMCM, and between modules dictate the resolution.

DPM. Watershed scale refers to watershed analyses and the A matrix correlating mesh resolutio.: with scaling depen-aspects of dealing with watersheds as an entity; typical dency is presented in Table 1. Because no methodology or models include DHSVM, ARM, HSPF, CREAMS, and framework can efficiently and effectively address every j NPS. Similar comments could be made about assessments ,

level dealmg with scale and resolution, the shaded areas m, and tools used on regional and global scales. It should be the table represent the resolution and scale envisioned for noted that a model of any level of detail could be associated the first framework silo. Addiuonal silos would be devel-with each of these scales. For example, analytical and numerical models can be used in a medium. specific assess. Ped for other scale and resolution combinations. The scale and resolution categories are impoitant for comparing the ment; likewise, global assessments are not necessarily lim-different modehng systems with FRAMES. The different ited to numerically based models, categories of scale are, but are not hmited to, site-specific, Resolution refers to the temporal- and spacial-mesh resolu- field / facility, regional, watershed /airshed, and global. The tion associated with the assessment (i.e., requirements asso- different resolution categories will include, but not be lim-ciated with the transfer of data). Although the mesh ited to, screer'ng, analytical, and numerical. It is important resolution could be defined a number of different ways,it is to match the scale and resolution requirements of an assess-defmed herein based on the types of assessments that are ment to the appropriate modeling system. FRAMES is ini-typically performed. Three mesh sizes have been identified: tially being designed to meet the needs of a single waste low, medium, and high. A typicallow-resolution approach site, multiple waste site, and multiple waste site / multiple would be represented by a structured-value approach or an geographical area assessments. Although FRAMES is approach that lends itself to being self-contained, even if being designed for these types of assessments,its design simple quantitative calculations are involved. With this allows for linkages with modeling systems of different scale approach, these models would most likely not be subdivided and resolution for special analysis, into componects but be used as a single entity; examples . .

Figures 10 and 11 illustrate the interrelationships and inter-include HRS, DPM, and SSL. A low-resolution approach ,

actmns between frameworks representing different scales.

could be associated with any of the four scales identified Ey housing approaches as they differ by scale and resolu-earlier (e g., medium-specific, watershed, regional, or glo- tion, efficient frameworks can be developed. Because the bal). frameworks have similar constructs, and because GIFs and A typical medium-resolution approach is physics-based GOFs form the basis of each framework, multiple frame-(e.g., compartmental, analytical, empirical, or numerical) works can communicate. Because units, types and forms of and lends itself to " uniform or average con litions" over an data and formats are known for each framework, data-pro-area or plane. The assessment is not unduly burdened with cessing programs can be developed to access the GIFs aad detailed temporal and spacial discretizations. Although the GOFs of other frameworks. Therefore,if a medium-specific type of model may inherently influence the level of resolu- analysis is required as a boundary condition to a regional tion (e.g., structured-value for low resolution and analytical analysis, the regional analysis would have access to this for medium resolution), specifications of the boundary con- assessment, and a data-processing program would transfer didons between models will tend to dictate the mesh resolu- the information from the medium-specific framework to the tion. For example, spacially uniform flow conditions are regional framework. Outside access to another model or traditionally associated with a medium-resolution-based framework would be similar.

problem. Spacially uniform flow conditions could be sup-plied by an analytically or numerically based model. The boundary conditions dictate the mesh resolution (i.e., References medium), not the model that is employed in the assessment. .

Bt'rns, L.A., D.M. Cline, R.R. Lassiter. 1982. Exposure A typical high-resolution approach is traditionally physics- Analysis Modeling System (EXAMS): User Manual and based, where finer resolution is required both temportlly System Documentation. EPA-600/3-82-023. U.S. Environ-and spacially. For example, the high-resolution framework mental Protection Agency, Athens, GA.

may require the abil.ty to track three-dimensional variations Baughman, G.L. and R.R. Lassiter. 1978. J. Cairns, Jr.,

in time with concurrent interactions at all locations. These K.G. Dickson, A.W. Maki, (Eds.), Estimating the Hazard of types of requirements are typical of numerical models. Chemical Substances to A9uatic Life. ASTM Pub. 657, Although numerical models are traditionally used in thesc Philadelphia, PA.

situations, analytical models can also be used,if desired.

NUREG/CP-0163 84

FRAMES Crawford, N.H. and R.K. Linsley, Jr. 1966. Digital Simula- License. Prepared by Ann Riley & Associates, LTD. for the tion in Hydrology: Stanford Watershed ModelIV. Techni- U.S. Nuclear Regulatory Commission, Washington, DC.

cal Report 39. Department of Civil Engineering, Stanford (November 13-14,1997).

University, Stanford, CA (July 1966).

NRC.1994. Ranking Hazardous-Waste Sites for Remedia!

Hartz, K.E. and G. Whelan.1988. MEPAS and RAAS Action. National Research Council, National Academy Methodologies as Integrated into the R1/EA/FS Process. In: Press, Washington, DC.

Proceedings of the 9th National Conference: Superfund '88.

Hazardous Materials Control Research Institute, Silver Patterson, M.R. 1986. Unified Transport Model for Or8an-Springs, Maryland, November 28-30. pp. 295-299. ses. Y. Cohen (Ed.), Pollutants m a Multimedia Environ-ment. Plenum Press,NewYork. pp.93-115.

Hung, C.Y.1996. User's Guide for PRESTO-EPA-CPG Operation System, Version 2.1. EPA 402-R-96-103, U.S. Patterson, M.R., TJ. Sworski, A.L. Sjoreen, M.G. Brow-Environmental Protection Agency, Washington, D.C. man, C.C. Coutant, D.M. Hetnck, B.D. Murphy, and RJ.

Raridon.1984. A User's Manual for UTM-TOX, the Um,-

Kennedy, W.E. Jr. and D1. Strenge. 1992. Residual Radio- fled Transport Model. ORNL-6064. Oak Ridge National active Contamination From Decommissioning. NUREG/ Laboratory, Oak Ridge, TN.

CR-5512. Vol.1. PNL-7994. U.S. Nuclear Regulatory Commission, Washington, DC. Renner, R.1995. Predicting Chemical Risks with Multime-dia Fate Models. Environ. Sci. Technol. 29(12):556-559.

Laniak, G.E, J.G. Droppo, E.R. Faillace, E.K. Gnanapra-gasam, W.B. Mills, D.L. Strenge, G. Whelan. and C. Yu. Whelan, G., J.W. Buck, and A. Nazerali. 1994. Modular 1997. Overview of the Multimedia Benchmarkmg Analysis Risk Analysis for Assessing Multiple Waste Sites. PNL-for Three Risk Assessment Models: RESRAD, MMSOILS, SA-24239. Pacific Northwest Laboratory, Richland, WA.

and MEPAS. Risk Analysis. 17(2),203 214. Whelan, G.. J. W. Buck, Di. Strenge, J.G. Droppo, Jr., B.L.

Mackay, D.1979. Finding Fugacity Feasible. Environ. Hoopes, and RJ. Aiken.1992. An Overview of the Multi-Sci. Technol. 13:1218. media Assessment Methodology MEPAS. Haz. Waste Haz.

Mat. 9(2):191-208.

Mackay, D. and S. Paterson.1986. The Fugacity Approach to Multimedia Environmental Modeling. Y. Cohen (Ed.), Whelan, G., K.E. Hartz, and N.D. Hilliard. 1990. Remedial Pollumnts n a fultimedia Environment. Plenum Press, Action Assessment System: Evaluation of Selected Feasi-bility Studies of CERCLA Hazardous Waste Sites. PNL PP -

7229. Pacific Northwest Laboratory. Richland,WA.

McCall, PJ., D.A. Laskowski, R1. Swann, and HJ. Dish-burger.1983. Estimation of Environmental Partitioning of Whelan, G., D1. Strenge, J.G. Droppo, Jr., B.L. Steelman, Organic Chermcals in Model Ecosystems. Residue and J.W. Buck.1987. The Remedial Action Priority Sys-Reviews. Springer-Verlag, New York. 85:231-244. tem (RAPS): MathematicalFormulations. DOE /RIJ87-09.

PNL-6200. Pacific Northwest Laboratory, Richland, WA.

McKone, T.E. and W.E. Kastenburg.1986. Application of Multimedia PollutantTransport Models to Risk Analysis. Y. Whelan, G., D1. Strenge, J.G. Droppo, Jr., and Bl. Steel-Cohen (Ed.), Pollutants in a Multimedia Environment. Ple- man.1986. Overview of the Remedial Action Priority Sys- ,

num Press, New York. pp. 167-189. tem (RAPS). Y. Cohen (Ed.), Pollutants m a Multimedia Environment. Plenum Press,NewYork. pp. 191-227.

Mills, W.B., JJ. Cheng, J.G. Droppo, Jr., E.R. Faillace, E.K.

Gnanapragasam, R.A. Johns, G.E Lamak, C.S. Lew, D.L. Yu, C., AJ. Zielen, J.-J. Cheng, Y.C. Yuan, L.G. Jones, DJ.

Strenge, J.E Sutherland, G. Whelan, and C.Yu. 1997. Mul- LePoire, Y.Y. Wang, C.O. Loureiro, E. Gnanapragasam, E.

timedia Benchmarkmg Analysis for Three Risk Assessment Faillace, A. Wallo III, W.A. Williams, and H. Peterson.

Models: RESRAD, MMSOILS, and MEPAS. Risk Analy- 1993. Manual for Implementing Residual Radioactive sis,17(2):187-201. Material Guidelines Using RESRAD, Version 5.0, ANIJ EAD/LD-2, Argonne National Laboratory, Argonne,IL.

Moskowitz, P.D., R. Pardi, V.M. Fthenakis, S. Holtzman, LC. Sun, and B. Irla.1996. An Evaluation of Three Repre-sentative Multimedia Models Used to Support Cleanup Decision-making at Hazardous, Mixed, and Radioactive Waste Sites. Risk Analysis, 16(2):279-287.

NRC.1997. Official Transcript of Proceedings: United States of America, Nuclear Regulatory Commission -

Workshop on Review of Dose Modeling Methods for Dem-onstration of Compliance with the Radiological Criteria for 85 NUREG/CP-0163

FRAMES s

TAllLE I. Matrix Correlating Mesh Resolution with Scaling Dependency SCALE MEDIUM RESOLUTION SPECIFIC WATERSHED REGIONAL GLOBAL MEDIUM HIGH

a. Shaded areas represent resolution and scale envisioned for the first framework silo. Additional silos would be )

l developed for other scale and resolution combinations, 1 i

Experience Timeline for Framework Development

- Flow Path for Problem-Specific, Object-Oriented Framework' Watershed Models 1995 Problem Specific Ful:y-Coupled Sequential Object Oriented se,ie lp70 1990 I

",**j l I I l996 o

1964 1979 1984 t,,,e Multipurpose Fully Framework Unified Framework Figure 1. Time Line for Multimedia Model Development NUREG/CP-0163 86

r FRAMES Without A Specification Object 1 Object 2 Model mg _

_, ],_- ,

' r-1 ;;

ets 3:':':':*

. . . _ . - ~.

Model '

r' ~- --)

Set C ) O~~~~~~~.. ~ ~ ~ ~ ~

l lj O = oata processor Figure 2. Illustration of the Interrelationships and Connections Between Components Comprising a Typical Existing System Wita A Specification Objdl Objat2 Model Set A . . ' -

Specification '

r Model 4 ....

Set B 2 Model , - J ~ ~ "-Il Set C / l-----  !

Figure 3. I!!ustration of the Connection Between Components with Interface Specifications 87 NUREG/CP-0163

Framework Userinterface 0 O 1 Globalinput Files Global Output Files l AIR TRANSPORT MODU LE SOURCE TERM MODU LE (p VADOSE ZCNE MODU LE i p SATURATED ZONE MODULE

. ~ ~ . . /tjng ,oh SURFACE WATER h other hme.

MODU LE Q

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( -I  !' DOSE MODULE (l HEALTH lMPACTS MODU LE

>hBM I I Figure 4. Structure of FRAMES User interface and Global input & Output Data Files, which House Median > Specific Modules NUREG/CP-0163 88

Framework User Interface d h GlobalInput Files Global Output Files Module #1 ser Interface

/

P (Boundarh

\ r cesso Conditions)

Da (mr.was Processor se:auw _,3mw:3

$ Data u ide Data Data e.g, $ Wem Pr c sor Module Process di h p

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sor

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Programs Module #2 Data v ata e.g ,

UserInterface ,- Processor ~

di o h Da

$ Data from

< tw.wa s.n e-waee.m u'en=> Outside j

g System Figure 5. Detailed illustration of the implementation of a Module within FRAMES 89 NUREG/CP-0163 Y - __ _ _ _ _ _ _ _ _ _ _ _ - _ _ _ - - _ _ - _ - - _ _ - _ - - - - - - _ _ _ - - _ _ - - - - - - - - - - - - - - - - -

FRAMES file Edit Add Run etc.

E 515I641n 4- na l

p

.. Y E I-sne i \ sae r / / / / / f Figure 6. Simple FUI Example Illustrating Contaminant Emissions to the Air and Saturated Zone with Two Receptor locations File Edit Add Run etc.

~~~'

5141516M MIN &a a m .,_

LEJ b b- b h .-

4' sne1 / sne r / / / f f f Figure 7. Simple Framework User Interface Example lllustrating Contaminant Emissions to the Air, tow Vadose Zones, and a River with Three Receptor locations NUREG/CP-0163 90

FRAMES Contaminants I

Hanfor Tanks HanfordAir Rchland NativeAmerican NativeRisk Zo el l

Columbi Kennewick Zo 2 Pasco AdultPep AdultPopRisk HanfordAou Yak'rna Figure 8. Illustrative Example of the Framework User Interf ace Describing the Conceptual Site Modeling Scenario file Edh Add Run etc.

B151516leMI-sud3&l N

l l

l Ske t / sae r / / / / / /

l Figure 9. Illustrative Example of a Feedback loop 91 NUREG/CP-0163

FRAMES WATERSHED j 9

l M @

a v J

Global

- . . . Input / Output w m

, m. g E il O

O W! O 3  !

l REGIONAL

@ = Processing Program Figure 10. Interactioits Between Frameworks Representing Different Scales FRAMEWORK SILO CONCEPT O O qv

,JQ~ @O?

$$? 15$-

qi  :.G~c Yp;; M:.

I lo

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.k- Each Framework Silo is associated with  ?

ghf: Low, Medium, and High Resolutions

@;.f; Figure 11. Illustration of the Interaction of Between Different Framework Silos !

NUREG/CP-0163 92

OVERVIEW OF PRESTO MODEL l

Cheng Y. Hung Office of Radiation and Indoor Air U.S. Environmental Protection Agency Washington, D.C. 20460 ABSTRACT: This paper presents an overview of the PRESTO model characteristics to facilitate selecting and applying models for dose assessments. The model was designed by the US .

EPA to assess the health impacts for regulatory analysis ofa radioactive waste disposal site or of a soil cleanup site. The model was designed to provide the effective dose, cancer incident risk, and mortality risk to the maximum exposed individual and the cumulative fatal cancer death and genetic health effects to the general population for cost-benefit, marginal cost, and ALARA analyses for the implementation of a regulation or an environmental standard. In order to provide meaningful, convincing, and accurate cost-benefit and ALARA analysis results, special attention was given to design accurate transport submodels related to the groundwater pathway. In addition, special attention was also given to simplify the model to save computer processing time and to reduce the required time in preparing the data matrix for the regulatory analysis decision model.

1 INTRODUCTION The intent of this paper is to present an overview of the development and capabilities of PRESTO in support of an NRC effort to develop a methodology for selecting a site specific model for regulatory and compliance applications. The U.S. Nuclear Regulatory Commission is developing a regulatory guide on " Demonstrating Compliance with the Radiological Criteria for License Termination." As a supporting tool to demonstrate compliance, NRC is in the process of developing a methodology for site-specific modeling. This methodology is to be used for supplementing the currently available screening model, DandD.

A workshop was held November 13-14 at Nuclear Regulatory Commission Headquarters as one of a series ofinteractions with Agreemeat States, incensees, and the public to gather suggestions and ideas for developing this guide. Developers of currently available dose models were invited to the workshop to present an overview of their models. Presentations of MEPAS, RESRAD, PRESTO and DandD models were included. The purpose of the presentations was to provide an overview of each model for NRC staff's consideration in developing regulatory guidance for selecting a dose model to be used in demonstrating compliance with the final rule on

" Regulatory Criteria for License Termination." To assess the applicability of each model, ten questions were compiled by tne NRC modeling committee for'the speakers to use as guideline for

. their presentation.  !

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The subjects concerning the ten questions that NRC modeling committee compil:d were:  ;

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1. History of the model development,

2. Transport mechanisms, scenarios, and exposure pathways considered, I

3. Determination ofinput parameter values,

4. Radionucliide transpon effects considered,

5. Time and spatial geometry limitations inherent in the analytical method,

6. Assessment of alternative remedial action,

7. Extent of modeltesting,

8. Handling of source term, hydrologic and geohydrologic conditions, exposure pathway combinations, cost and monitoring programs, and ALARA,

9. Graphical capability of plotting time distribution and probability density distribution,

10. Adaptability ofland-use scenario and flexibility of output format.

This paper summarizes the oveniew of PRESTO presented in the workshop. The primary focus is to address these ten questions and to discuss the model's accuracy.

2. CHARACTERISTICS OF PRESTO MODEL 2.1 History of PRESTO Model Development The design of the PRESTO model (Prediction of Radiological Effects due to Shallow Trench Operation) was conducted by staff members of the Office ofRadiation and Indoor Air (ORIA), Environmental Protection Agency (EPA) in 1979, for the purpose of supporting the development of EPA's Environmental Standards for Management and Disposal of Radioactive Waste. The design, including model structure and mathematical formulations, was coded into a computer model at Oak Ridge National Laboratory in 1980 under EPA's extramural contract.

The integrated PRESTO model included three parts: (1) atmospheric transport inherited from existing AIRDOS-EPA model, (2) newly coded transport models based on EPA's design specifications, and (3) an infiltration model coded by an ORIA staffmember.

To support EPA's Low Level Waste rule, a regulatory decision model was developed using operation research techniques. The regulatory decision model compared various viable alternatives to optimize the disposal cost using the environmental standard as a constraint. To support the decision mcdel, PRESTO was designed to calculate: (1) cumulative population health effects, (2) cumulative genetic effects, and (3) maximum committed effective dose. The number of years of premature death was not included in the output because the monetary value of human life could not be included in the decision model.

Although a screening model would have been sufficient for the regulatory analysis, PRESTO was designed to be a simple, yet accurate, site-specific model. A dynamic simulation of the radionuclides transport in the multimedia was used because this is the only way to maintain reasonable accuracy. Because the groundwater pathway is the major pathway of human exposure, extra attention was given to developing the groundwater related submodels, including NUREG/CP-0163 94 )

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infiltration, leaching, release, and groundwater transport.

A one-dimensional groundwater transport model was selected even though this simplification may theoretically introduce significant error. This selection was inevitable because employing a two- or three-dimensional model would considerably increase the complexity and the numerical calculation instability of the model. In addition, code stability would become more diflicult when the daughter nuclide ingrowth effects are integrated into the transport system.

Fortunately, after careful investigation, the potential error was found to be small for normal applications. A detailed discussion of the error is presented in Chapter 3.

The first version of PRESTO was completed in 1982 and was reviewed by ORIA staff members. The model was modified in 1984 by Rogers and Associates, Engineering Co. (RAECO) to accommodate disposal alternatives being considered by EPA to support the Low Level Waste rule. A year long third party extramural review was conducted in 1983, and an extensive International Experts Review was conducted in February 1984. The model underwent EPA Science Advisory Board review before being released to the public in 1987.

The version ofPRESTO released in 1987 included executable computer codes and a user manual containing model methodology. PRESTO was divided into two models, PRESTO-EPA-CPG and PRESTO-EPA-POP (Refs. I and 2). The CPG model calculates the maximum individual committed effective dose, while the POP model calculates cumulative health and genetic effects. PRESTO was subsequently improved and interface software added to facilitate operation. Updated versions ofPRESTO-EPA-CPG and PRESTO-EPA-POP were published in 1992 and 1996, respectively.

PRESTO has been expanded to cover the scenarios normally encountered in soil cleanup, including restricted, partially restricted and unrestricted land-use and various soil treatments. The expanded versions were coded and tested by the model developers (planned and designed by ORIA staff and coded by RAECO) and undenvent third party independent quality assurance.

These new versions are designated as PRESTO-EPA-CLNCPG and PRESTO-EPA-CLNPOP.

Their documentation and user's manuals are being prepared and are scheduled to be published in 1998.

2.2 Transport Mechanism, Scenarios, and Exposure Pathways Considered PRESTO is designed to handle scenarios having waste disposal in shallow trenches or contaminated soil with or without a clean soil cover. The waste can be either solidified or remain in as is form, and can also be modeled with or without containerization. Humid or arid meteorological conditions can be analyzed for the case of a frozen ground, which retards infiltration.

The contaminated soil scenario option includes clean soil cover, chemical treatment, or mechanical treatment. The land-use scenario options include unrestricted land-use (urban and suburban usage), restricted land-use (fenced with surveillance ), and partially restricted (limited land-use, such as a recreational or industrial park).

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To calculate the transport of radionuclides from the source to the environmental receptors, PRESTO considers three major environmental transport pathways, atmospheric, surface water, and groundwater. Infiltration rate and overland flow, which are the driving forces for the transport of radionuclides in the groundwater and surface water pathways, are calculated using dynamic equations of the overland flow, subsurface flow, and atmospheric diffusion systems.

Simplified system of equations are used for the complex infiltration analysis which enables the calculation to be integrated into PRESTO. This infiltration submodel was verified using results obtained from field investigations conducted by the USGS and the NRC (Ref. 5). The results obtained from PRESTO agreed well with the results obtained from field investigators.

A multi-phase dispersion concept leaching model was used to calculate the leaching rate of radionuclides out of the waste / contaminated soil. The results obtained from this model agreed with the field data better than those obtained from a steady uniform leaching model.

As stated in Section 2.1, a one-dimensional model is used for the groundwater transport reaches, even though a one-dimensional model may, in principle, induce significant theoretical crror into the calculation of the rate of radionuclides transport. Fortunately, the error could potentially be induced was proven to be small for a maximum individual dose calculation (no theoretical error can be induced in cumulative cancer deaths and genetic effects calculations). A detailed discussion of this error is presented in Chapter 3.

The radionuclides concentration in a well calculated by PRESTO-EPA-CPG, depends heavily on the depth that the well penetrates into the aquifer and the treatment of the well mechanics. The model requires the depth of effective mixing as an input to calculate radionuclides concentrations in the well. The effective mixing depth is calculated based on the well mechanics and the depth that the well penetrates into the aquifer. It is recommended that a olausible scenario be used to determine the depth of penetration. Under this scenario, the depth of well penetrating into the aquifer is determined based on current state regulations (see Section 3.5 for further detail). The effective mixing depth of the dilution water stream is calculated based on the pumping rate and the aquifer characteristics; the pumping rate is calculated from the sum cf drinking water, cattle feed, and crop irrigation for a family of four members.

A plug flow model, with no dispersion and benthos load effects, is used for the surface water transport model. This model, although simple, is considered sufficient for PRESTO applications. This is because an annual average transport rate is required for the dose calculation, and the complex retardation effects that exist in surface water transpon will not affect the annual average transport.

A conventional Gaussian plume atmospheric transport model is used to calculate the transport of resuspended radionuclides from the source area to downstream emironmental receptor (s). The depletion of the plume due to fallout and electrochemical deposition is calculated based on the methodology adapted from the AIRDOS-EPA model (Ref. 6).

Health impacts are calcuaed for three human receptors (an on-site resident, an off-site resident, and the general population), and the concentration for three emironmental receptors NUREG/CP-0163 96

(groundwater, surface water, and air). The model conciders all significant pathways that result in exposure to human receptors. These exposure pathwayi vary with the human receptors being considered. The exposure pathways for the off-site resiient include: ingestion of drinking water, crops, milk, livestock, fish, and soil; inhalation from air; direct exposure from the ground and air; and immersion in the air. Exposure pathways for an onstte resident include inhalation ofindoor and outdoor radon and the direct exposure in a basement, in addition to all pathways to an off-site resident. Finally, the general populatioa is exposed to all pathways that an off-site resident is exposed to except the inhalation, direct exposure, and immersion from air.

2.3 Determination ofInput Parameter Values 1

Generally speaking, the input parameter values used in the model are divided into four l groups: important site-specific data, meteorological data, national average generic data and health impact conversion factors. Because the model is designed to be a site-specific, site-specific input values are to be supplied by the user. In this context, the physical meaning of these parameters is explained thoroughly in the user's manual. The source of parameter values is expected to be from field data, generic engineering handbooks, or from educated expertjudgement as a last resort.

The selection of these sources depends on the sensitivity of the parameter, the availability of resources, and desi"d modeling accuracy.

National average generic data, such as the water consumption rate, are given in the standardized input file included in the PRESTO model package. These data may be used without modification.

The meteorological data includes hourly rainfall, daily average temperature, and daylight length. Three data sets are provided to represent the humid South (South Carolina), the humid North (New York State), and the arid West (Nevada). The user may select the meteorological data set closest to the specific site being analyzed. The hourly rainfall data given in the data set are to be used as the relative rainfall distribution. The true hourly rainfall for a specific site is l calculated in the model using the user assigned average annual rainfall data and the relative hourly rainfall distribution from the selected data set.

The health impacts conversion factors include fatal cancer, cancer incidence, genetic effects, committed effective dose, mortality risk, and incidence risk. Conversion factors for the forty radionuclides normally found in low-level radioactive waste are included. These conversion factors are taken from Federal Guidance Report No 11 and 12. The users may add additional nuclides.

PRESTO includes two types of models, deterministic and probabilistic. The probabilistic model requires two types ofinput files to perform an uncertainty analysis. The first type includes all the input files required to run the detenninistic model, while the second type includes the data to specify the probability distribution of random input parameters. The types of probability distribution for the random input parameters are limited to the uniform, log-uniform, normal (truncated), log-normal (truncated), and triangular distributions. The maximum r. umber of realizations that the model can take is 3000.

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l 2.4 Radionuclides Transport Effects Considered The PRESTO model only calculates the transpon ofradioactive chemical species.

Chemical reactions which may occur during the course of transport are not included. All together, forty radionuclides commcnly found in the low-level radioactive waste are built into the model. For the groundwater transport pathway, all potential changes in the transport characteristics due to physico-chemical reactions are lumped together into a linear sorption model known as the distribution coefficient (K ). Because of differences in the physico-chemical environment in each transport reach considered, different K, values can be assigned to the ground sudace, waste matrix, unsaturated soil, and aquifer reaches, respectively.

To accommodate complex waste forms, three options are available for calculating the rate i ofleaching of radionuclides from the waste or contaminated soil matrix. These options include chemical exchange (K ), chemical exchange with solubility limits, and annual release rates. The first and second options apply to the sorption-desorption waste, and the third option applies to a solidified waste.

The physico-chemical reactions and benthos load effects are not considered in the surface water transpon. This simplification is acceptable, because the celerity of the transport is so great that the time required to transport a radionuclides from the source area to the receptor ofinterest (hours or days) is much shoner than the duration of average value that PRESTO uses to calculate health impacts (one year).

Radioactive decay and daughter nuclide ingrowth effects are considered in all transport reaches, including groundwater, surface water, and atmospheric transport pathways. The analysis employs a moving control volume concept. The model assumes that there is no relative movement between the parent nuclide and daughter nuclides. Therefore one may consider an imaginary control volume which moves with the same speed as the parent nuclide. This assumption is theoretically acceptable in the sudace water transport reach because there is no retardation effect being considered in the transport process. However, the assumption is not theoretically acceptable for the atmospheric and groundwater transport reaches because relative motion between parent and daughter nuclides is expected in a generic case.

An additional crude assumption was needed to validate the above basic assumption for atmospheric and groundwater transport reaches. This crude assumption involves assuming that the deposition velocities (atmospheric pathway) and the distribution coefficient (groundwater pathway) for the parent and daughter nuclides are identical. This assumption is theoretically not true. However, due to the fact that the travel distance is normally short (< 300 meters), the error induced from this assumption is normally small. In addition, only up to four members of daughter nuclides in the decay chain is considered to simplify the calculation.

2.5 Time and Spatial Geometry Limitations Inherent in the Analytical Method In general, if the distance from the boundary of the contaminated source to the well l i

l receptor is relatively short compared to the length of the source area, significant errors may be NUREG/CP-0163 98 i

induced in the calculation ofgroundwater transport when the contaminated area is assumed to be a point source. Unfortunately, most of the maximum individual effective dose calculation i

scenarios fall into this category. In addition, this error increases rapidly as the size of the contaminated siteincreases. Therefore, the size of a contaminated site should be limited if a

(

I point source is assumed and a reasonable accuracy of analysis is desired. Although PRESTO assumes a point source in calculating the atmospheric transport, an area source is assumed for the calculation of the groundwater transport. Therefore, there is no limitation on the spatial geometry I of a source area.

Since a dynamic integration of the radionuclides transport is involved, the duration of the I simulation time is limited by the available computer storage. The current version of the model limits the real time of simulations to 10,000 years. This limitation is suf5cient for most normal applications, because the committed effective doses for critical radionuclides reach peak values in hundreds of years.

L From a numerical analysis viewpoint, the space and time increments control the stability of l numencal calculations. PRESTO assumes a one-year increment for all transport analysis except for the calculation of the infiltration rate through the contaminated source matrix which, assumes a one-hour increment. A space integral is used in integrating the radionuclides transport to the i

downstream section of the contaminated source matrix (collection reach). A space increment equal to one-tenth the length of the contaminated site is used in this integration. These time and space increments are built into the model without user's interaction. Over ten years ofmodel applications, the preset time and space increments have proven to be adequate without inducing any instability in the numerical calculations.

2.6 Assessment of Alternative Remedial Action As mentioned in Section 2.1, PRESTO was designed to generate a data matrix required by the regulatory analysis decision model, which is used to optimize the cost ofwaste disposal or soil cleanup. Therefore, the model has to be designed as a site-specific application model. To achieve this goal, dynamic simulation submodels were used, to the extent practicable, for increasing the model accuracy and the comparability of viable scenarios. In addition to the ultimate outputs discussed in the previous sections, the concentrations of radionuclides in well water are also printed out for reference use. This feature enhances the flexibility of comparing remedial action scenarios.

1 In comparing costs and benefits, the cumulative health impacts (EPA uses the sum of cumulative fatal cancer deaths and cumulative genetic effects) should be considered. EPA's past studies showed that there is no correlation between the maximum dose and the cumulative health impacts. A simulation model calculating the cumulative health impacts is therefore essential in comparing the benefits resulting from a postulated scenario. PRESTO was designed to provide the above data. The output from PRESTO can also be used for cleanup / disposal cost estimation,

{

allowing the results to be used for benefit and cost comparisons. '

An alternative cost-benefit comparison would use the number ofyears of premature death.

PRESTO did not include this parameter in the output because the establishment of the monetary i

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value for this parameter is still in a premature stage. The PRESTO model can easily incorporate this feature as soon as the above difficulty is resolved.

2.7 Extent of Model Testing Quality assurance (QA) was considered to be the first priority in the course of model development. QA ofPRESTO began right after the completion of the draft ofmodel planning and design. The model also underwent extensive in-house and interagency technical review and test runs when the first version of the computer code was completed.

. A year long third party extramural review was conducted by Inter Systems Inc. in 1983 (Ref. 7), as soon as the in-house preliminary system analysis was completed for the Low-Level Waste mle. The QA included the review of each mathematical formulation, the algorithm and accuracy of the computer coding, and test runs of the program An extensive International Experts Review was conducted in Febmary 1984. The attendees included experts from national laboratories, federal agencies, industrial entities, and international experts. A two-day meeting was held to discuss the adequacy of the mathematical formulation, input data used in the analysis, and justification of the results.

Following extensive system analysis for generating the data matrix and the marginal cost ofimplement.ag the Low-Level Waste Rule, the model undenvent an eight-month long EPA Science Advisory Board review. Three subcommittees were formed to review the adequacy of submodels in the area of transport, food-chain, and health effects conversion factors. The model was approved with some recommended improvements.

Recent modi 6 cations in 1997 to accommodate the soil cleanup scenario underwent QA by S. Cohen & Associates /RAECO. An in-house QA effort is currently underway to complete the PRESTO-EPA-CLNCPG and PRESTO-EPA-CLNPOP models.

2.8 Handling of Source Term, Hydrologic and Geohydrologic Conditions, Exposure Pathway Combinations, Cost and Monitoring Programs, and ALARA As stated in Section 2.1, PRESTO is specifically designed for the purpose of regulatory analysis. Therefore, special attention was given to the handling of the source term, hydrologic and geo-hydrologic conditions, exposure pathway combinations, cost and monitoring programs, and ALARA. Detailed descriptions of each are contained in the following subsections.

2.8.1 Source Term Handling 2.8.1.1 Source Term Characterization The source terms PRESTO can handle are divided into three categories, contaminated soil, waste, and their mixture. The contaminated soil contains mostly natural soil, and it responds NUREG/CP-0163 100

_ _ _ _ _ _ _ _ _ _ __________a

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to the infiltrating water by a sorption-desorption process (Kd The waste can be in a form of activated metal or absorbing waste. The absorbing waste can be either in an as-is or a solidified form. Furthermore, the waste can be disposed of with or without a container.

In actual modeling applications, the source terms are categorized as absorbing waste, solidified waste, and activated metal. Because of the concentration difference, the absorbing waste is further divided into absorbing waste and trash; the solidified waste is divided into solidified waste and incinerated / solidified waste. The model does not have the option to handle liquid waste form, because the current NRC 10 CF". 61 Regulations for the disposal oflow-level radioactive waste do not allow the disposal ofliquid waste without solidification.

The leaching characteristics of an absorbing waste are assumed to follow the linear sorption-desorption model, and the release rate is derived based on a mass-balance equation assuming a compartment type model. Detailed discussion of the multi-phase leaching model used in PRESTO is described in Section 2.8.2.2.

The conventional empirical formula, which assumes a constant fractional release rate is used to calculate the release of radionuclides from a solidified waste. The container effects are treated based on the assumption that: (1) no release could occur when the container is intact, (2) release occurs once the container breaks, and (3) the number of container failures increases linearly with time within the user assigned time period.

2.8.1.2 Multiple Source Term PRESTO can handle multiple source terms as stated in Subsection 2.8.1.1. However, the model considers each of the source terms to be uniformly distributed over the entire waste volume. Theoretically speaking, the distribution of waste with different characteristics could affect the results of the health impacts analysis, especially when a small volume of high concentration waste is placed in an isolated spot in the disposal volume. PRESTO provides the flexibility of handling this type of case with some manipulation of the calculation scheme. The process includes two computer runs, one for the concentrated waste only, and the other for all waste excluding the concentrated waste. The results of combined dose versus time can then be obtained by adding up the results of doses for both runs obtained at the same time step. The peak of the combined dose is the maximum dose expected for the waste site.

2.8.2 Hydrologic and Geohydrologic Conditions 2.8.2.1 Infiltration Model A dynamic model is employed for calculating the annual infiltration rate. Since infiltration water is the driving force for leaching radionuclides out of the waste matrix and is one of the most sensitive variables in a risk assessment model, the accuracy of the infiltration rate analyses directly affects the accuracy of the results of modeling.

Controlling both computation time and the stability of numerical analysis is known to be 101 NUREG/CP-0163

extremely difficult in direct solution of the original system equations representing the overland flow, subsurface ficw, and atmospheric diffusion. The PRESTO model employs a simplification technique (Ref. 8) to overcome these difficulties. The technique involves the transformation of the original partial differential system equations into ordinary differential system equations by dividing the soil moisture into three components, hygroscopic, pellicular, and gravity water.

Hourly rainfall and daily average temperature data are used to calculate frozen soil conditions and the rate ofinfiltration, overland flow, and evaporation loss. The computation time and the stability of numerical analysis are controlled to an acceptable level by this technique.

2.8.2.2 Leaching Model i A multi-phase leaching model concept is used in PRESTO, which assumes that water l

infdtrating into the waste matrix will be concentrated into some conduits because of the heterogeneity of the waste matrix and the non uniform distribution of the water infiltrated from upstream. A linear sorption model in conjunction with the mass balance equation is used in I deriving the basic equation for calculating the rate of leaching from the waste matrix. Finally, an j i

Ad Hoc model, incorporating the multi-phase leaching concept, is used. Details of this model and its characteristics are discussed in Chapter 3.

2.8.2.3 Groundwater Transport Model A steady uniform one-dimensional model is used for all groundwater transport reaches, including the unsaturated, collection, and aquifer reaches. The accuracy of this model will be discussed in the next chapter. The linear sorption model equation in conjunction with its mass balance equation is used to calculate the rate of radionuclides passing thr agh a section of interest. The accuracy of using a one-dimensional model is discussed in atail in Chapter 3.

2.8.3 Exposure Pathway Combination As stated previously, the PRESTO modelis designed for preparing the data matrix for the decision model for least cost optimization required in regulatory analysis. Therefore, the main output is health impacts expressed in a form combining all pathways and all radionuclides. The components for each individual pathway and radionuclides are also printed for reference.

2.8.4 Remedial Methods Linked to Cost and Monitoring Programs Since PRESTO is designed for cost optimization, the postulated disposal technique or remediation methods used in the analyses are reflected in the input parameters. These parameters provide inputs to remediation cost estimation and ultimately to the decision model for cost optimization.

i The output generated from PRESTO for a particular remedial method can, in conjunction with input parameters, provide useful basic data for monitoring system planning and design as

)

well as for evaluating a monitoring program. I NUREG/CP-0163 102

2.8.5 ALARA The output from PRESTO can also provide the data matrix to the decision model for maximizing the benefits ofdisposal or cleanup operation, known as ALARA analysis. The .

decision model used in ALARA analysis is similar to that used in the regulatory analysis and is an optimization model to maximize benefits using the remediation cost as a constraint. During the courre of optimization, many scenarios will be generated accompanied with cost and benefit (number of cancer deaths saved). Observing the whole spectrum of the remedial options, one can select one or a wries of remedial actions which maximize benefits at a reasonable cost; these scenarios are the rc nits of ALARA analysis. l 2.9 Graphical Capability of Plotting Time Distribution and Probability Density Distribution PRESTO has the capability of plotting variations of the combined effective dose equivalent (combined effects from all pathways and all radionuclides) with time. The model also prints out the variation of effective dose equivalent for each radionucFde and pathway using the user specified time interval. The plot of the effective dose for each racionuclide and pathway can, therefore, be either plotted manually or by executing a computer run with unwanted radionuclides and pathways being disabled.

The model also has the capability to plot the probability distribution for the combined effective dose as well as for the selected random distribution input values, when a probabilistic (Monte Carlo) run is selected.

2.10 Adaptability of Land-Use Scenario and Flexibility of Output Format As stated previously, the model can handle many land use scenarios, including restricted, unrestricted, and partially restricted scenarios. The unrestricted land use can be urban, suburban, business, or rural farm. The restricted land use option will restrict access to the general public and the area will be under surveillance. The partially restricted land use option will open the area to limited human activity such as a recreational park or an industrial park.

In addition, a variety of parameters are printed out for either follow-up analysis or a quality assurance activity. The effective dose equivalent, cumulative fatal cancer deaths, genetic health effects, and the concentration in well water are part of the main output normally used in the cost be7efit analysis and in the ALARA decision model analyses. The concentration, dose equivalent, and other transport outputs resulting from a postulated land-use scenario can be used as a reference in determining monitoring strategies.

)

3. ACCURACY OF PRESTO MODEL 3.1 General Discussion PRESTO calculates health impacts through a series ofindependent transport submodels.

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Errors may incur from each submodel due to overly conservative assumptions and may accumulate to an uncontrollable level in some cases. To control the error, one should avoid overly conservative assumptions and design a submodel as accurately as possible. Furthermore, special attention should be given to the development of a submodel used in the calculatim. of more sensitive pathways.

The groundwater pathway is known to be the most important pathway in calculating the

, l maximum individual dose equivalent from a waste disposal site or from a soil cleanup site. Based on our past experience, the dose to a maximum exposed individual from the groundwater pathway contributes over 90% of the total dose in nine out of ten cases. Therefore, special attention was given to groundwater related submodels, including infiltration, leaching, and groundwater transport.

No special attention is given to the atmospheric transport model because the contribution to the dose of the maximum exposed individual is negligible. The surface water pathway may contribute a significant amount to the dose of the maximum exposed individual in some cases.

Therefore, the accuracy of the surface water model is also important in maintaining the accuracy of the maximum individual dose analysis. A simple plug flow model used in PRESTO, as stated in Section 2.2, is considered to be accurate enough. This is because an annual average rate of radionuclides transport is used to calculate the effective dose, and the travel time of a disturbance from one station to another (on the order of hours or days) is much shorter than the duration of the time average (a year). That is, any errors incurred in the transport analysis would compensate each other when a long-term average value is of main interest.

In addition, dynamic equations are used as much as possible in PRESTO to maintain its accuracy. The use of an empirical or a statistical model was avoided because there is, in general, not enough data being collected for developing such models. It may not be reliable to apply an empirical equation developed for other types of applications.

The accuracy of the transport models involved in calculating the groundwater pathway are discussed in the following sections.

3.2 Infiltration Model As stated in Section 2.8.2.1, dynamic system equations are employed for the infiltration model because the infiltration water is the driving force ofleaching radionuclides out of the waste matrix and is known to be one of the most sensitive variables in a dose model. Therefore, the accuracy of the infiltration rate analysis directly affects the accuracy of the dose model analysis.

The derivation and the discussion of the infiltration model characteristics are discussed in Section 2.8.2.1. As a part of model veri 6 cation, the model was compared with Hillel and Van Bavel (Ref. 9) and Ripple et al. (Ref.10) studies in the subsurface flow regime. The results agreed very well with those obtained from the infiltration model. The model was also validated against field studies conducted by the USGS and the NRC (Ref.11) on a long-term groundwater recharge. The results of the USGS and the NRC studies indicated that the annual recharge in the NUREG/CP-0163 104 l

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Barnwell site (South Carolina) was 14 to 17 in/yr and 14 in/yr, respectively. Comparing the results obtained by PRESTO modei of 15.8 in/yr, one can conclude that PRESTO can proside reasonable infiltration results.

3.3 Leaching Model A steady uniform flow model is a simple and commonly used model, which assumes that the flow of the infiltrated water is steady and uniform. Because of the simplicity in the mathematical formulation, an analytical solution has been developed and used in various dose models. However, the infiltration rate calculated from a steady uniform flow model is normally much higher than that observed in the field (Ref.12).

PRESTO employs an Ad Hoc model derived from Hung's multi-phase leaching model to calculate the rate of radionuclides leaching out of the waste matrix (Ref.13). The multi-phase leaching model assumes that the flow of the infiltration water will not be uniform but will be concentrated in preferential conduits. This non-uniform distribution of the infiltration water is primarily caused by the heterogeneity of hydraulic conductivity of the waste matrix. Transport of radionuclides in the preferential conduit is assumed to be carried by convective flow, but :he transport of radionuclides between conduits is assumed to be transported by diffusion to the nearby conduit first, and subsequently downward by convective flow.

Although the results of the analysis obtained from the multi-phase leaching model are much closer to field data, the calculation of the teaching rate is much more complex. This complexity prevents the model from being integrated into PRESTO. Therefore, an Ad Hoc model was developed using the multi-phase leaching model as a tool. The development involved the generation of an extensive data matrix and employed a dimensional analysis technique to quantify the correction factor. The results of the analysis are normally more conservative than the results obtained from the multi-phase leaching model, but closer to the field data than that obtained from a steady uniform leaching model.

The relative error between the Ad Hoc model and the steady uniform model depends on the radionuclides characteristics (decay constant and K, value) and the geohydrologic conditions of the aquifer (lumped together in a term, " time of arrival"). The characteristics of this error have been thoroughly studied by Hung (Ref.14). The results of Hung's study indicated that the relative error will be approximately 100% for an extremely long half-life radionuclides with a retardation factor of one, and the time of arrival of 30 years (in the collection reach).

3.4 Groundwater Model As stated in Section 2.2, a one-dimensional model is used for all of the groundwater transport reaches, including the unsaturated soil, collection, and aquifer reaches. Since it is generally known that a one-dimensional model may induce significant theoretical error in calculating the rate ofradionuclide transport, special attention has been given to the characteristics of this error.

105 NUREG/CP-0163

l A recent study conducted by Gnanapragasam et al.(Ref.15) indicated that the relative 3

error on the plume concentration between a one-dimensional model (PRESTO model) and a three-dimensional dispersion model (MEPAS model) varies from 0% to approximately 700%

when the well receptor is moved from source (x = 0 meter) to 104,000 meters away. The results also indicated that the relative error stays in a 10% range when the location of the well receptor is limited within approximately 300 meters away from the source. Since the application of PRESTO for calculating the maximum individual dose is limited to a distance from the source of no more than 300 meters, the relative error of employing a one-dimensional model is expected to be tolerably small(less than 10%). l Moreover, a worst case radionuclides, Sr-90 (only 28.1 years of half-life), was used in the benchmarking study; the errors are expected to be suppressed to some extent for a longer half-life nuclide. In addition, the width of the source was taken to be only 8 meters. This would considerably shorten the length of the no-disturbance zone (by lateral dispersion). One should note that the relative error due to the lateral dispersion is zero in the no-disturbance zone. The length of the no-disturbance zone may be conservatively estimated as three times the source width for the purpose of this discussion. Therefore, in an actual application, with a source width of say 100 meters, the well receptor will still be near the boundary of the no-disturbance zone ( the length of the no-disturbance zone is approximately 300 meters). Therefore, in an actual application, the error of employing a one-dimensional transport model is expected to be negligibly small.

3.5 Well Mechanics Treatment As stated in Section 2.2, the results of calculating the radionuclides concentration in the well depend heavily on the depth of the pumping well penetrating into the aquifer and the treatment of the well mechanics. The results of these calculations, in some cases, may differ by as much as an order ofmagnitude.

As stated in Section 2.2, users of PRESTO are recommended to adopt a olausible scenario in determining the depth of penetration of the well. The scenario considers the current state regulatory practice. An important regulation commonly stated is that "a domestic well can only be drilled by a licensed well driller." Thus, once the well driller mobilized the drilling machine at a site, the well drilling cost will normally stay the same up to 200 or 300 feet because of the cost of machine mobilization. On the other hand, it is normally known that the deeper the well penetrates below the groundwater table, the better the water quality and the better the security on the water quantity. Therefore, the well will generally penetrate far below the water table. The result of using the plausible scenario is generally quite different from using the concept of maximum a probable scenario (a scenario assuming the well penetrates into a contaminated aquifer at a depth producing maximum well water concentration).

After the depth of well penetration is determined, the effective mixing depth of the dilution water stream is calculated based on the pumping rate and the aquifer characteristics. The {

l pumping rate is calculated from the sum of drinking water, cattle feed, and crop irrigation for a family of four members. PRESTO accepts the effective mixing depth as input to calculate the NUREG/CP-0163 106 l

_ _ _ _ _ _ _ _ _ _ _______________-.______-._______________-__________________________________________..______________-.__u

available dilution water and then calculates the radionuclides concentration in the well water.

Let us assume a plume migrating in a background groundwater flow of 10 meters /yr (Darcy) as an example. The unit width rate of transpon ir assumed to be 1 Ci/yr/ meter when the plume reaches peak at the well. The radionuclides concentration in the well water is calculated to be 0.1 Ci/m' (= 1/10) if a maximum probable scenario is used (assuming the screen depth is 1 meter). However, when a plausible scenario is used, the concentration is calculated to be 0.005 Ci/m' (= 1/{ 10x20); assuming the effective mixing depth is calculated to be 20 meters). A factor of20 can be expected between the results obtained using a maximum probable scenario and a plausible scenario.

One can clearly see the importance of the well mechanics treatment from this example.

The selection of the scenario will be, of course, up to the policy maker In ORIA, the plausible scenario has been employed for all analyses performed with PRESTO.

4 CONCLUSIONS

1. The PRESTO model was designed by the US EPA to generate the data matrix required by regulatory analysis decision models. This includes models for assessing the marginal cost

~

of environmental standard implementation and for ALARA analysis.

2. PRESTO outputs include the cumulative fatal cancer deaths, genetic health effects, maximum individual effective dose and radionuclides concentrations in well water.

3. PRESTO is a complete multimedia model considering all signi6 cant environmental transport pathways, including atmospheric, surface water and groundwater pathways. The food-chain pathways, include irrigation and cattle feed, and the pathway transporting radon gas into a basement and to the ground surface are also included. Three types of human receptors are considered, an onsite resident, an offsite resident and the general population. The human exposure pathways considered for these human receptors include ingestion of drinking water (from ground and surface water), crops, fish, milk, meat, and soil; inhalation of air, radon gas (outdoors and in a basement); immersion in air; and direct exposure from ground, basement, and air.

4. PRESTO considers the source to be an area source for the important groundwater pathway simulation; therefore, there is no limitation on the maximum area that the model can have without incurring unacceptable errors. However, due to the dynamic nature of the model, the health impacts to human receptors are calculated for each year. The maximum real time of simulation is, therefore, limited to 10,000 years.

5. PRESTO was designed for site-specific applications as well as for system analysis (alternative remedial action analysis). Therefore, special attention-was given to the design of the mathematical formulation for those submodels relating to the ground water pathway. This was intended to maintain the required accuracy of the overall model and a meaningful system analysis.

6. The input parameters are divided into four categories: site-specific data, meteorological data, national average data, and model provided conversion factors. The site specific data requires users to pay special attention.

107 NUREG/CP-0163 i

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7. PRESTO can also perform Monte Carlo type simulations for uncertainty analysis; the distribution of the selected random input parameters can be either uniform, log-uniform, normal, log-normal or triangular; and the distribution of the input and output parameters can be displayed graphically.

8. PRESTO was designed to handle soil cleanup sites as well as radioactive waste disposal sites having waste in the form of absorbing, solidified, or activated metal, or a mixture of them. The waste can also be with or without containers.

9. PRESTO can handle various land-use scenarios, including restricted, unrestricted and partially restricted use. A clean soil cover (may contain residual radionuclides) is always required in a waste disposal scenario to cover the waste and to expel rainwater from infiltrating into the waste. However, in a soil cleanup scenario, the contaminated soil can be either covered with clean soil or exposed to the air without a soil cover. The remediation scenarios include chemical treatment and/or mechanical treatment.

10. PRESTO is fully tested, well documented, and has undergone extensive quality assurance.

In addition, the model is user friendly and easy to operate.

REFERENCE 1

U.S. Environmental Protection Agency, PRESTO-EPA-POP: A Low-LevelRadioactive Waste Environmental Transport andRisk Assessment Code - Vol.1, Methodology Manual, EPA 520/1-87-024-1, Washington, D.C.,1987.

2. U.S. Environmental Protection Agency, PRESTO-EPA-CPG: A Low-LevelRadioactive Waste Environmental Transport and Risk Assessment Code - Documentation and User's Manual, EPA 520/1-87-026, Washington, D.C.,1987.

3. Hung, C.Y., User 's Guidefor PRESTO-EPA-CPG Operation System, Version 2.1, EPA report, EPA 402-R-96-013, June 1996.

4. Hung, C.Y., User's Guidefor PRESTO-EPA-POP Operation System, Version 2.1, EPA report, EPA 405-R-95-015, August 1995

5. U.S. Nuclear Regulatory Commission, Environmental Assessmentfor the Barnwell Low-Level Waste DisposalFacilities, a report prepared by Division of Waste Management, NUREG-0879, January 1982.

6. Moore, R. E., C. F. Baes III, L. M. McDowell-Boyer, Watson, A.P., Hoffman, F.O.,

Pleasant, J.C., and Miller, C.W., AIRDOS-EPA: A ComputerizedMethodologyfor Estimating Environmental Concentrations and Dose to Manfrom Airborne Releases of Radionuclides. ORNL-5532 (Oak Ridge National Laboratory, Oak Ridge, Tennessee),

1979.

7. Inter Systems, Inc., PRESTO-EPA Guality Assurance Audit, final report prepared for EPA, September 1983.

8. Hung, C. Y., A Model to Simulate Infiltration ofRainwater Through the Cover ofa Radioactive Waste Trench Under Saturatedand Unsaturated Conditions, in Role of the Unsaturated Zone in Radioactive and Hazardous Waste Disposal, edited by James W.

Mercer, et al., Ann Arbor Science,1983.

9. Hillel, D. and Van Bavel, C., Simulation ofProfile Water Storage as Related to Soil NUREG/CP-0163 log

l l

l Hydraulic Properties, Journal, Soil Science Society of America, Vol. 40., No. 6, Nov.

, 1971

10. Ripple, C. C., Rubin J., and Van Hylkama, T., Estimating Steady-State Evaporation Rate from Bare Soil under Conditions ofHigh Water Table. U.S. Geological Survey, Water Supply, pp. 2019-A,1972.

11. U.S. Nuclear Regulatory Commission, Environmental Assessmentfor the Barnwell l Low-Level Waste Di.sposalFacilities, report prepared by Division of Waste Management, NUREG-0879, January 1982.

12. Inter Systems, Inc., The Peer Review ofPRESTO-EPA, a Summary report prepared for EPA, February 1984.

13. Hung, C. Y., A Multi-phase LeachingModel to Predict the Leaching ofRadionuclides from a Radioactive Waste disposalsite, a paper presented at the second International Workshop on Leaching of Low- and Medium- Level Waste Packages under Disposal Conditions, October 13-16,1986.

14 Hung, C. Y., Reevaluation ofEPA 's PRESTO-EPA Model- Conservatism ofIts Leaching Submodel, proceedings of 17th Annual US DOE Low-Level Radioactive Waste Management Conference, Dec. 12-14,1995.

15 Gnanapragasam, E.K., Yu, C., Whelan, G., Mills, W.B., Mcdonald, J.P., Lew, C. S.,

Hung, C.Y., Hoffmeyer, D., Comparison ofMultimedia ModelPredictionsfor a Contaminant Plume Migration Scenario, a paper submitted to Water Resources Research Journal for publication, October 1997.

l 1

109 NUREG/CP-0163

NRC FORM 335 u.S. NUCLEAR. EeULAToRY CoMMtsSION 1. REPORT NUMBER

$*C% no2' (Assigned t>y NRC, Add Vol., supp., Rev.,

3201,3202 and AddandumNumbers,if anyJ BIBLIOGRAPHIC DATA SHEET (See mstructos on the reverse)

2. TITLE AND SUBTITLE NUREG/CP-0163 l

Proceedings of the Workshop on Review of Dose Modeling Methods for Demonstration of Compliance with the Radiological Criteria for License Termination 3 DATE REPORT PUBLISHED uoNTH YEAR l

May 1998

4. FIN oR GRANT NUMBER

5. AUTHOR (S) 6. TYPE OF REPORT Thomas J. Nicholson and Jack D. Parrott, Editors Conference Proceedings

7. PERIOD COVERED (inctusveDates)

November 13-14,1997 8 PERFORMING ORGANIZATION NAME AND ADDRESS (# NRc.prence Dwse, omce or Rega, U.S. Nucear Regulatory comnnsson, and maeng adeess. # contractor, prowoe name and memng so$ess)

Division of Regulatory Applications Division of Waste Management Office of Nuclear Regulatory Research Office of Nuclear Material Safety and Safeguards U.S. Nuclear Regulatory Commission U.S. Nuclear Regulatory Commission Wmhington, DC 20555 -0001 Washington, DC 20555-0001

9. SPONSORING ORGANIZATION - NAME AND ADDRESS (#NRC type same as soove; econtractor prowce NRc Dwse, osce orRega, u 3 NucearReputatory commessaan, and mahng acwess) j Same as above l 1

i

10. SUPPLEMENTARY NOTES Public workshop proceedings in support of decommissioning rulemaking guidance

11. ABSTRACT (200 worcs oress)

The public " Workshop on Review of Dose Modeling Methods for Demonstration of Compliance with the Radiological Criteria for License Termination" was held at the NRC Headquarters Auditorium, Rockville, Maryland, on November 13-14,1997. The workshop was one in a senes to support NRC staff development of guidance for implementing the final rule on " Radiological Criteria for License Termination." The workshop topics included discussion of: dose models used for decommissioning r; views; identification of enteria for evaluating the acceptability of dose models; and selection of parameter values for demonstrating compliance with the final rule. The 2-day public workshop was jointly organized by RES and NMSS staff responsible for reviewing dose modeling methods used in decommissioning reviews. The workshop was noticed in the Federal Register (62 FR 51706). The workshop presenters included: NMSS and RES staff, who discussed both dose modeling needs for licensing reviews, and development of guidance related to dose modeling and parameter selection needs; DOE national laboratory scientists, who provided responses to earlier NRC staff-developed questions and discussed their v:rious Federally-sponsored dose models (i.e., DandD, RESRAD, and MEPAS codes); and an EPA scientist, who presented details on the EPA dose assessment model (i.e., PRESTO code). The workshop was formatted to provide opportunities for the attendees to observe computer demonstrations of the dose codes presented. More than 120 workshop attendees from NRC He'dquarters and the Regions, Agreement States; as well as industry representatives and consultants; scientists from EPA, DOD, DNFSB, DOE, and the nationallaboratories; and interested members of the public participated. A complete transcript of the workshop, including viewgraphs and attendance lists, is available in the NRC Public Document Room. This NUREG/CP documents the formal presentations made during the workshop, and provides a preface outlining the workshop's focus, objectives, background, topics and questions provided to the invited speakers, and those raised during the panel discussion.

NUREG/CP-0163 also provides technical bases supporting the development of decommissioning guidance.

12. KEY WORDS/DESCRIPTORS (Last mores orphrases shat m# assst researchers m Aocatmp the soport J 13 AVAILAbiuTY 6IATEMENT code selection criteria unlimited decommissioning 14 SECURITY CLAS$6FICATioN dose modeling (rtus eage; environmental pathway analysis ground-water pathway unclassified license termination crh,s Report) prmeter selection unclassified pathway analysis.

15. NUMBER OF PAGES radiological critena r:dionuclide transport regulatory compliance 16. PRICE NRC FORM 336 (249)

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