ML13003A135

Development of Evacuation Time Estimates, Cover Through Section 7, General Population Evacuation Time Estimates (Ete), Page 7-7

ML13003A135
Person / Time
Site:	Susquehanna
Issue date:	12/30/2012
From:	KLD Engineering, PC
To:	Office of Nuclear Reactor Regulation, Susquehanna
References
KLT TR-527, Rev 0
Download: ML13003A135 (120)

Text

SusquehannaSteam Electric Station Development of Evacuation Time Estimates Work performedfor PPL Susquehanna, LLC, by:

KLD Engineering, P.C.

43 Corporate Drive Hauppauge, NY 11788 mailto:kweinisch kldcompanies.com November, 2012 Final Report, Rev. 0 KLD TR - 527

Table of Contents 1 INTRODUCTION .................................................................................................................................. 1-1 1.1 Overview of the ETE Process ...................................................................................................... 1-1 1.2 The Susquehanna Steam Electric Station Location .................................................................... 1-3 1.3 Prelim inary Activities ................................................................................................................. 1-5 1.4 Com parison with Prior ETE Study .............................................................................................. 1-9 2 STUDY ESTIM ATES AND ASSUM PTIONS ............................................................................................. 2-1 2.1 Data Estim ates ........................................................................................................................... 2-1 2.2 Study M ethodological Assum ptions .......................................................................................... 2-2 2.3 Study Assum ptions ..................................................................................................................... 2-5 3 DEM AND ESTIM ATION ....................................................................................................................... 3-1 3.1 Perm anent Residents ................................................................................................................. 3-2 3.2 Shadow Population .................................................................................................................... 3-8 3.3 Transient Population ................................................................................................................ 3-11 3.3.1 Lodging Facilities .............................................................................................................. 3-11 3.3.2 Hunting Grounds .............................................................................................................. 3-11 3.3.3 Fishing Areas .................................................................................................................... 3-12 3.3.4 Cam pgrounds ................................................................................................................... 3-12 3.3.5 Golf Courses ..................................................................................................................... 3-13 3.3.6 Parks ................................................................................................................................. 3-13 3.4 College Students ...................................................................................................................... 3-13 3.5 Em ployees ................................................................................................................................ 3-17 3.6 M edical Facilities ...................................................................................................................... 3-21 3.7 Total Dem and in Addition to Perm anent Population .............................................................. 3-21 3.8 Special Event ............................................................................................................................ 3-21 3.9 Sum m ary of Dem and ............................................................................................................... 3-23 4 ESTIM ATION OF HIGHW AY CAPACITY ................................................................................................ 4-1 4.1 Capacity Estim ations on Approaches to Intersections .............................................................. 4-2 4.2 Capacity Estim ation along Sections of Highway ........................................................................ 4-4 4.3 Application to the SSES Study Area ............................................................................................ 4-6 4.3.1 Two-Lane Roads ................................................................................................................. 4-6 4.3.2 M ulti-Lane Highway ........................................................................................................... 4-6 4.3.3 Freeways ............................................................................................................................ 4-7 4.3.4 Intersections ...................................................................................................................... 4-8 4.4 Sim ulation and Capacity Estim ation .......................................................................................... 4-8 5 ESTIM ATION OF TRIP GENERATION TIM E.......................................................................................... 5-1 5.1 Background ................................................................................................................................ 5-1 5.2 Fundam ental Considerations ..................................................................................................... 5-3 5.3 Estim ated Tim e Distributions of Activities Preceding Event 5 ................................................... 5-6 5.4 Calculation of Trip Generation Tim e Distribution .................................................................... 5-12 5.4.1 Statistical Outliers ............................................................................................................ 5-13 Susquehanna Steam Electric Station i KLD Engineering, P.C.

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5.4.2 Staged Evacuation Trip Generation ................................................................................. 5-17 5.4.3 Trip Generation for W aterw ays and Recreational Areas ................................................. 5-18 6 DEM AND ESTIM ATIO N FO R EVACUATIO N SCENARIOS ................................................................. 6-1 7 GENERAL POPULATION EVACUATION TIME ESTIMATES (ETE) ..................................................... 7-1 7.1 Voluntary Evacuation and Shadow Evacuation ...................................................................... 7-1 7.2 Staged Evacuation ...................................................................................................................... 7-1 7.3 Patterns of Traffic Congestion during Evacuation ................................. 7-2 7.4 Evacuation Rates ........................................................................................................................ 7-3 7.5 Evacuation Tim e Estim ate (ETE) Results .................................................................................... 7-3 7.6 Staged Evacuation Results ......................................................................................................... 7-5 7.7 Guidance on Using ETE Tables ................................................................................. ................. 7-5 8 TRANSIT-DEPENDENT AND SPECIAL FACILITY EVACUATION TIME ESTIMATES ............................. 8-1 8.1 Transit Dependent People Dem and Estim ate ............................................................................ 8-2 8.2 School Population - Transit Dem and ......................................................................................... 8-4 8.3 M edical Facility Dem and ............................................................................................................ 8-4 8.4 Evacuation Tim e Estim ates for Transit Dependent People ....................................................... 8-5 8.5 Special Needs Population ......................................................................................................... 8-10 8.6 Correctional Facilities ............................................................................................................... 8-11 9 TRAFFIC M ANAGEM ENT STRATEGY .............................................................................................. 9-1 10 EVACUATION RO UTES .................................................................................................................. 10-1 11 SURVEILLANCE O F EVACUATION O PERATIONS ........................................................................ 11-1 12 CO NFIRM ATION TIM E .................................................................................................................. 12-1 A. GLOSSARY O F TRAFFIC ENGINEERING TERM S .............................................................................. A-1 B. DYNAMIC TRAFFIC ASSIGNMENT AND DISTRIBUTION MODEL ..................................................... B-1 C. DYNEV TRAFFIC SIM ULATIO N M ODEL ............................................................................................ C-1 C.1 M ethodology ............................................................................................................................. C-5 C.1.1 The Fundam ental Diagram ........................................................................................... C-5 C.1.2 The Sim ulation M odel ........................................................................................................ C-5 C.1.3 Lane Assignm ent .............................................................................................................. C-13 C.2 Im plem entation ....................................................................................................................... C-13 C.2.1 Com putational Procedure ............................................................................................ C-13 C.2.2 Interfacing with Dynamic Traffic Assignment (DTRAD) .............................................. C-16 D. DETAILED DESCRIPTION O F STUDY PROCEDURE .......................................................................... D-1 E. SPECIAL FACILITY DATA ...................................................................................................................... E-1 F. TELEPHONE SURVEY ........................................................................................................................... F-1 F.1 Introduction ............................................................................................................................... F-1 F.2 Survey Instrum ent and Sam pling Plan ....................................................................................... F-2 F.3 Survey Results ............................................................................................................................ F-3 F.3.1 Household Dem ographic Results ........................................................................................... F-3 Susquehanna Steam Electric Station ii KLD Engineering, P.C.

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F.3.2 Evacuation Response ............................................................................................................. F-7 F.3.3 Tim e Distribution Results ....................................................................................................... F-9 F.4 Conclusions ........................................................... F-12 G. TRAFFIC M ANAGEM ENT PLAN .......................................................................................................... G-1 G.i Traffic Control Points ................................................................................................................ G-1 G.2 Access Control Points ................................................................................................................ G-1 H EVACUATIO N REGIO NS ..................................................................................................................... H-1 J. REPRESENTATIVE INPUTS TO AND OUTPUTS FROM THE DYNEV II SYSTEM ................................. J-i K. EVACUATION ROADW AY NETW O RK .............................................................................................. K-1 L. ERPA BO UNDARIES ............................................................................................................................ L-i M. EVACUATIO N SENSITIVITY STUDIES .......................................................................................... M -1 M .1 Effect of Changes in Trip Generation Tim es ........................................................................ M -1 M.2 Effect of Changes in the Number of People in the Shadow Region Who Relocate ................. M-2 M .3 Effect of Changes in EPZ Resident Population ........................................................................ M-3 N. ETE CRITERIA CHECKLIST ................................................................................................................... N-1 Note: Appendix I intentionallyskipped Susquehanna Steam Electric Station iii KILD Engineering, P.C.

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List of Figures Figure 1-1. Susquehanna Steam Electric Station Location ........................................................................ 1-4 Figure 1-2. Susquehanna Steam Electric Station Link-Node Analysis Network ........................................ 1-7 Figure 2-1. Voluntary Evacuation M ethodology ....................................................................................... 2-4 Figure 3-1. SSES EPZ .................................................................................................................................. 3-3 Figure 3-2. Permanent Resident Population by Sector ............................................................................ 3-6 Figure 3-3. Permanent Resident Vehicles by Sector ................................................................................. 3-7 Figure 3-4. Shadow Population by Sector ................................................................................................. 3-9 Figure 3-5. Shadow Vehicles by Sector ................................................................................................... 3-10 Figure 3-6. Transient Population by Sector ............................................................................................. 3-15 Figure 3-7. Transient Vehicles by Sector ................................................................................................. 3-16 Figure 3-8. Em ployee Population by Sector ............................................................................................ 3-19 Figure 3-9. Em ployee Vehicles by Sector ................................................................................................ 3-20 Figure 4-1. Fundam ental Diagram s ............................................................................................................ 4-9 Figure 5-1. Events and Activities Preceding the Evacuation Trip .............................................................. 5-5 Figure 5-2. Evacuation M obilization Activities ........................................................................................ 5-11 Figure 5-3. Comparison of Data Distribution and Normal Distribution ....................................................... 5-15 Figure 5-4. Comparison of Trip Generation Distributions ....................................................................... 5-21 Figure 5-5. Comparison of Staged and Unstaged Trip Generation Distributions in the 2 to 5 Mile Region

..... ............ ...............................................* ...........o . . . . ,,.oo ..... o............. 5-23.....

5-23 Figure 6-1. SSES EPZ ERPA ......................................................................................................................... 6-5 Figure 7-1. Voluntary Evacuation Methodology ..................................................................................... 7-16 Figure 7-2. SSES Shadow Region ............................................................................................................. 7-17 Figure 7-3. Congestion Patterns at 30 Minutes after the Advisory to Evacuate .................................... 7-18 Figure 7-4. Congestion Patterns at 1 Hour after the Advisory to Evacuate ............................................ 7-19 Figure 7-5. Congestion Patterns at 2 Hours after the Advisory to Evacuate .......................................... 7-20 Figure 7-6. Congestion Patterns at 3 Hours after the Advisory to Evacuate .......................................... 7-21 Figure 7-7. Congestion Patterns at 3 Hours, 30 Minutes after the Advisory to Evacuate ...................... 7-22 Figure 7-8. Evacuation Time Estimates - Scenario 1 for Region R03 ...................................................... 7-23 Figure 7-9. Evacuation Time Estimates - Scenario 2 for Region R03 ...................................................... 7-23 Figure 7-10. Evacuation Time Estimates - Scenario 3 for Region R03 .................................................... 7-24 Figure 7-11. Evacuation Time Estimates - Scenario 4 for Region R03 .................................................... 7-24 Figure 7-12. Evacuation Time Estimates - Scenario 5 for Region R03 .................................................... 7-25 Figure 7-13. Evacuation Time Estimates - Scenario 6 for Region R03 .................................................... 7-25 Figure 7-14. Evacuation Time Estimates - Scenario 7 for Region R03 .................................................... 7-26 Figure 7-15. Evacuation Time Estimates - Scenario 8 for Region R03 .................................................... 7-26 Figure 7-16. Evacuation Time Estimates - Scenario 9 for Region R03 .................................................... 7-27 Figure 7-17. Evacuation Time Estimates - Scenario 10 for Region R03 .................................................. 7-27 Figure 7-18. Evacuation Time Estimates - Scenario 11 for Region R03 .................................................. 7-28 Figure 7-19. Evacuation Time Estimates - Scenario 12 for Region R03 .................................................. 7-28 Figure 7-20. Evacuation Time Estimates - Scenario 13 for Region R03 .................................................. 7-29 Figure 7-21. Evacuation Time Estimates - Scenario 14 for Region R03 .................................................. 7-29 Figure 8-1. Chronology of Transit Evacuation Operations ...................................................................... 8-13 Figure 8-2A. Transit-Dependent Bus Routes (1 of 2) .............................................................................. 8-14 Figure 8-2B. Transit-Dependent Bus Routes (2 of 2) .............................................................................. 8-15 Susquehanna Steam Electric Station iv KLD Engineering, P.C.

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Figure 10-i. General Population Reception Centers and Host Schools .................................................. 10-2 Figure 10-2. Evacuation Route M ap ........................................................................................................ 10-3 Figure B-1. Flow Diagram of Sim ulation-D TRAD Interface ........................................................................ B-5 Figure C-1. Representative Analysis Netw ork ........................................................................................... C-4 Figure C-2. Fundam ental Diagram s ........................................................................................................... C-6 Figure C-3. A UNIT Problem Configuration w ith t, > 0 .............................................................................. C-7 Figure C-4. Flow of Sim ulation Processing (See Glossary: Table C-3) .............................................. C-15 Figure D-i. Flow Diagram of Activities ..................................................................................................... D-5 Figure E-1. Schools and Colleges w ithin the EPZ (1 of 2) .................................................................... E-I0 Figure E-2. Schools and Colleges w ithin the EPZ (2 of 2) .................................................................... E-11 Figure E-3. M edical Facilities w ithin the EPZ .......................................................................................... E-12 Figure E-4. M ajor Em ployers within the EPZ ..................................................................................... E-13 Figure E-5. Recreational Areas w ithin the EPZ................................................................................ E-14 Figure E-6. Lodging w ithin the EPZ .......................................................................................................... E-15 Figure E-7. Correctional Facilities w ithin the EPZ ................................................................................... E-16 Figure F-1. Household Size in the EPZ ....................................................................................................... F-4 Figure F-2. Household Vehicle Availability ................................................................................................ F-4 Figure F-3. Vehicle Availability - 1 to 5 Person Households .................................................................. F-5 Figure F-4. Vehicle Availability - 6 to 9+ Person Households .................................................................... F-5 Figure F-5. Com m uters in Households in the EPZ .................................................................................... F-6 Figure F-6. M odes of Travel in the EPZ ..................................................................................................... F-7 Figure F-7. Num ber of Vehicles Used for Evacuation .............................................................................. F-8 Figure F-8. Households Evacuating w ith Pets ........................................................................................... F-8 Figure F-9. Tim e Required to Prepare to Leave W ork/School .................................................................. F-9 Figure F-I0. W ork to Hom e Travel Tim e ............................................................................................ F-10 Figure F-11. Tim e to Prepare Hom e for Evacuation ........................................................................... F-11 Figure F-12. Tim e to Clear Drivew ay of 6"-8" of Snow ........................................................................... F-12 Figure G-1. Traffic Control Points for the SSES EPZ .................................................................................. G-2 Figure H-i. Region ROl .......................................... .................................................................................. H-4 Figure H-2. Region R02 ............................................................................................................................. H-5 Figure H-3. Region R03 .............................................................................................................................. H-6 Figure H-4. Region R04 ............................................................................................................................. H-7 Figure H-5. Region R05 ............................................................................................................................. H-8 Figure H-6. Region R06 ............................................................................................................................. H-9 Figure H-7. Region R07 ........................................................................................................................... H-I0 Figure H-8. Region R08 ......................................................................................................................... H-11 Figure H-9. Region R09 ................................................................................................. .......................... H-12 Figure H-IO. Region RiO ......................................................................................................................... H-13 Figure H-11 Region R11 .......................................................................................................................... H-14 Figure H-12 Region R12 .......................................................................................................................... H-15 Figure H-13 Region R13 .......................................................................................................................... H-16 Figure H-14 Region R14 .......................... ................................................................................ H-17 Figure H-15 Region R15 ........................................................................................................................... H-18 Figure H-16 Region R16 ........................................................................................................................ H-19 Figure H-17 Region R17 .......................................................................................................................... H-20 Figure H-18 Region R18 .......................................................................................................................... H-2_

Figure H-19 Region R19 .......................................................................................................................... H-22 Susquehanna Steam Electric Station v KLD Engineering, P.C.

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Figure H-20 Region R20 ................................................................................................................... ...... H-23 Figure H-21 Region R21 .......................................................................................................................... H-24 Figure H-22 Region R22 .......................................................................................................................... H-25 Figure H-23 Region R23 .......................................................................................................................... H-26 Figure H-24 Region R24 ................................................. *......................................................................... H-27 Figure H-25 Region R25 .......................................................................................................................... H-28 Figure H-26 Region R26 .......................................................................................................................... H-29 Figure H-27 Region R27 .......................................................................................................................... H-30 Figure H-28 Region R28 .......................................................................................................................... H-31 Figure H-29 Region R29 .......................................................................................................................... H-32 Figure H-30 Region R30 .......................................................................................................................... H-33 Figure J-1. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather (Scenario 1) ........... J-7 Figure J-2. ETE and Trip Generation: Summer, Midweek, Midday, Rain (Scenario 2) ........................... J-7 Figure J-3. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather (Scenario 3) .............. J-8 Figure J-4. ETE and Trip Generation: Summer, Weekend, Midday, Rain (Scenario 4) .......................... J-8 Figure J-5. ETE and Trip Generation: Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5)

................................................................................................................................................................... J-9 Figure J-6. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather (Scenario 6) ............ J-9 Figure J-7. ETE and Trip Generation: Winter, Midweek, Midday, Rain (Scenario 7) ............................... J-10 Figure J-8. ETE and Trip Generation: Winter, Midweek, Midday, Snow (Scenario 8) ............................. J-10 Figure J-9. ETE and Trip Generation: Winter, Weekend, Midday, Good Weather (Scenario 9) .......... J-1l Figure J-10. ETE and Trip Generation: Winter, Weekend, Midday, Rain (Scenario 10) ............. J11 Figure J-11. ETE and Trip Generation: Winter, Weekend, Midday, Snow (Scenario 11) ........... ' J-12 Figure J-12. ETE and Trip Generation: Winter, Midweek, Weekend, Evening, Good Weather (Scenario 12)

................................................................................................................................................................. J-1 2 Figure J-13. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather, Special Event (Scenario 1 3 ) ............................................................................................................................................................ J-13 Figure J-14. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather, Roadway Impact (S ce na rio 14 ) ............................................................................................................................................ J-13 Figure K-1. SSES Link-Node Analysis Network ........................................................................................... K-2 Figure K-2. Link-Node Analysis Network -Grid 1 ..................................................................................... K-3 Figure K-3. Link-Node Analysis Network- Grid 2 ..................................................................................... K-4 Figure K-4. Link-Node Analysis Network -Grid 3 ............................................................................... K-5 Figure K-5. Link-Node Analysis Network - Grid 4 ..................................................................................... K-6 Figure K-6. Link-Node Analysis Network -Grid 5 ..................................................................................... K-7 Figure K-7. Link-Node Analysis Network-Grid 6 ..................................................................................... K-8 Figure K-8. Link-Node Analysis Network -Grid 7 ..................................................................................... K-9 Figure K-9. Link-Node Analysis Network - Grid 8 ............................................................................... K-10 Figure K-10. Link-Node Analysis Network - Grid 9 ............................................................................ K-11 Figure K-11. Link-Node Analysis Network - Grid 10 ............................................................................... K-12 Figure K-12. Link-Node Analysis Network- Grid 11 ............................................................................... K-13 Figure K-13. Link-Node Analysis Network- Grid 12 ............................................................................... K-14 Figure K-14. Link-Node Analysis Network- Grid 13 .......................................................................... K-15 Figure K-15. Link-Node Analysis Network- Grid 14 ............................................................................... K-16 Figure K-16. Link-Node Analysis Network- Grid 15 ............................................................................... K-17 Figure K-17. Link-Node Analysis Network- Grid 16 ............................................................................... K-18 Figure K-18. Link-Node Analysis Network -Grid 17 ............................................................................... K-19 Susquehanna Steam Electric Station vi KLD Engineering. P.C.

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Figure K-19. Link-Node Analysis Netw ork- Grid 18 ................................................. .............................. K-20 Figure K-20. Link-Node Analysis Netw ork - Grid 19 ............................................................................... K-21 Figure K-21. Link-Node Analysis Network- Grid 20 ............................................................................... K-22 Figure K-22. Link-Node Analysis Netw ork - Grid 21 ............................................................................... K-23 Figure K-23. Link-Node Analysis Netw ork - Grid 22 ............................................................................... K-24 Figure K-24. Link-Node Analysis Network - Grid 23 ............................................................................... K-25 Figure K-25. Link-Node Analysis Network- Grid 24 ............................................................................... K-26 Figure K-26. Link-Node Analysis Network- Grid 25 ............................................................................... K-27 Figure K-27. Link-Node Analysis Network- Grid 26 ............................................................................... K-28 Figure K-28. Link-Node Analysis Network- Grid 27 ............................................................................... K-29 Figure K-29. Link-Node Analysis Netw ork- Grid 28 ............................................................................... K-30 Figure K-30. Link-Node Analysis Network- Grid 29 ............................................................................... K-31 Figure K-31. Link-Node Analysis Netw ork - Grid 30 ................................... ;........................................... K-32 Figure K-32. Link-Node Analysis Netw ork - Grid 31 ............................................................................... K-33 Figure K-33. Link-Node Analysis Network - Grid 32 ............................................................................... K-34 Figure K-34. Link-Node Analysis Network - Grid 33 ............................................................................... K-35 Figure K-35. Link-Node Analysis Network - Grid 34 ............................................................................... K-36 Figure K-36. Link-Node Analysis Network - Grid 35 ............................................................................... K-37 Figure K-37. Link-Node Analysis Network - Grid 36 ............................................................................... K-38 Figure K-38. Link-Node Analysis Network- Grid 37 .................................. K-39 Figure K-39. Link-Node Analysis Network - Grid 38 ........................................................................... K-40 Figure K-40. Link-Node Analysis Network - Grid 39 ............................................................................... K-41 Figure K-41. Link-Node Analysis Network - Grid 40 ........................... K-42 Figure K-42. Link-Node Analysis Netw ork - Grid 41 ............................................................................... K-43 Figure K-43. Link-Node Analysis Netw ork - Grid 42 ............................................................................... K-44 Figure K-44. Link-Node Analysis Network - Grid 43 ............................................................................... K-45 Figure K-45. Link-Node Analysis Network - Grid 44 ............................................................................... K-46 Figure K-46. Link-Node Analysis Network- Grid 45 ............................................................................... K-47 Figure K-47. Link-Node Analysis Network- Grid 46 ............................................................................... K-48 Figure K-48. Link-Node Analysis Network- Grid 47 ............................................................................... K-49 Suscuehanna Steam Electric Station vii KILD Engineering, P.C.

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List of Tables Table 1-1. Stakeholder Interaction ........................................................................................................... 1-1 Table 1-2. Highw ay Characteristics ........................................................................................................... 1-5 Table 1-3. ETE Study Com parisons ........................................................................................................... 1-9 Table 2-1. Evacuation Scenario Definitions .............................................................................................. 2-3 Table 2-2. M odel Adjustm ent for Adverse W eather ................................................................................. 2-7 Table 3-1. EPZ Perm anent Resident Population ....................................................................................... 3-4 Table 3-2. Permanent Resident Population and Vehicles by ERPA ............................................. .............. 3-5 Table 3-3. Shadow Population and Vehicles by Sector ............................................................................. 3-8 Table 3-4. Summary of Transients and Transient Vehicles ..................................................................... 3-14 Table 3-5. Summary of Non-EPZ Resident Employees and Employee Vehicles ..................................... 3-18 Table 3-6. SSES EPZ External Traff ic ........................................................................................................ 3-22 Table 3-7. Summary of Population Demand ....................................... 3-24 Table 3-8. Summary of Vehicle Demand ......................................... 3-25 Table 5-1. Event Sequence for Evacuation Activities .................................. 5-3 Table 5-2. Tim e Distribution for Notifying the Public .............................................................................. 5-6 Table 5-3. Time Distribution for Employees to Prepare to Leave Work ................................................... 5-7 Table 5-4. Time Distribution for Commuters to Travel Home .................................................................. 5-8 Table 5-5. Time Distribution for Population to Prepare to Evacuate ........................ 5-9 Table 5-6. Time Distribution for Population to Clear 6"-8" of Snow ...................................................... 5-10 Table 5-7. M apping Distributions to Events ............................................................................................ 5-12 Table 5-8. Description of the Distributions ............................................................................................. 5-13 Table 5-9. Trip Generation Histograms for the EPZ Population for Unstaged Evacuation ..................... 5-20 Table 5-10. Trip Generation Histograms for the EPZ Population for Staged Evacuation ....................... 5-22 Table 6-1. Description of Evacuation Regions ........................................................................................... 6-3 Table 6-2. Evacuation Scenario Definitions ............................................................................................... 6-6 Table 6-3. Percent of Population Groups Evacuating for Various Scenarios ............................................ 6-7 Table 6-4. Vehicle Estim ates by Scenario .................................................................................................. 6-8 Table 7-1. Time to Clear the Indicated Area of 90 Percent of the Affected Population ........................... 7-8 Table 7-2. Time to Clear the Indicated Area of 100 Percent of the Affected Population ....................... 7-10 Table 7-3. Time to Clear 90 Percent of the 2-Mile Area within the Indicated Region ............ 7-12 Table 7-4. Time to Clear 100 Percent of the 2-Mile Area within the Indicated Region .......................... 7-13 Table 7-5. Description of Evacuation Regions ......................................................................................... 7-14 Table 8-1A. Columbia County Transit-Dependent Population Estimates ............................................... 8-16 Table 8-lB. Luzerne County Transit-Dependent Population Estimates .................................................. 8-17 Table 8-2. School Population Dem and Estim ates ................................................................................... 8-18 Table 8-3. Host Schoo ls ........................................................................................................................... 8-19 Table 8-4. M edical Facility Transit Dem and ............................................................................................ 8-20 Table 8-5. Sum m ary of Transportation Resources .................................................................................. 8-21 Table 8-6. Bus Route Descriptions .......................................................................................................... 8-22 Table 8-7. School Evacuation Time Estimates - Good Weather .............................................................. 8-25 Table 8-8. School Evacuation Tim e Estim ates - Rain ............................................................................... 8-26 Table 8-9. School Evacuation Tim e Estim ates - Snow ............................................................................. 8-27 Table 8-10. Summary of Transit-Dependent Bus Routes ........................................................................ 8-28 Table 8-11. Transit-Dependent Evacuation Time Estimates - Good Weather ........................................ 8-29 Table 8-12. Transit-Dependent Evacuation Time Estimates - Rain ......................................................... 8-31 Susquehanna Steam Electric Station viii KLD Engineering, P.C.

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Table 8-13. Transit Dependent Evacuation Time Estimates - Snow ....................................................... 8-33 Table 8-14. Special Facility Evacuation Time Estimates - Good Weather ............................................... 8-35 Table 8-15. M edical Facility Evacuation Time Estimates - Rain .............................................................. 8-37 Table 8-16. Medical Facility Evacuation Time Estimates - Snow ........................................................... 8-39 Table 8-17. Homebound Special Needs Population Evacuation Time Estimates .................................... 8-41 Table 12-i. Estimated Number of Telephone Calls Required for Confirmation of Evacuation .............. 12-2 Table A-i. Glossary of Traffic Engineering Terms ............................................................................... A-1 Table C-i. Selected Measures of Effectiveness Output by DYNEV II ........................................................ C-2 Table C-2. Input Requirem ents for the DYNEV II M odel ........................................................................... C-3 Table C-3 . Glossary ................................................................................................................................... C-8 Table E-i. Schools within the EPZ .............................................. E-2 Table E-2. Colleges w ithin the EPZ ............................................................................................................ E-4 Table E-3. Medical Facilities w ithin the EPZ .............................................................................................. E-5 Table E-4. Major Em ployers w ithin the EPZ ............................................................................................. E-6 Table E-5. Parks/Recreational Attractions within the EPZ ........................................................................ E-7 Table E-6. Lodging Facilities w ithin the EPZ .............................................................................................. E-8 Table E-7. Correctional Facilities w ithin the EPZ ...................................................................................... E-9 Table F-i. Susquehanna Steam Electric Station Telephone Survey Sampling Plan .................................. F-2 Table H-1. Percent of Sub-Area Population Evacuating for Each Region ................................................. H-2 Table J-1. Characteristics of the Ten Highest Volume Signalized Intersections ........................................ J-2 Table J-2. Sample Simulation Model Input .............. ........................... -3 Table J-3. Selected Model Outputs for the Evacuation of the Entire EPZ (Region R03) ........................... J-4 Table J-4. Average Speed (mph) and Travel Time (min) for Major Evacuation Routes (Region R03, Sce n a rio 1) ................................................................................................................................................. J-4 Table J-5. Simulation Model Outputs at Network Exit Links for Region R03, Scenario 1 .................... J-5 Table K-1. Evacuation Roadway Network Characteristics ................................................................ K-50 Table K-2. Nodes in the Link-Node Analysis Network which are Controlled ................. K-i19 Table M-i. Evacuation Time Estimates for Trip Generation Sensitivity Study .................................. M-i Table M-2. Evacuation Time Estimates for Shadow Sensitivity Study .................................................... M-2 Table M -3. ETE Variation w ith Population Change ................................................................................ M -4 Table N-i. ETE Review Criteria Checklist ........................................................................................... N-i Susquehanna Steam Electric Station ix KLD Engineering, P.C.

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EXECUTIVE

SUMMARY

This report describes the analyses undertaken and the results obtained by a study to develop Evacuation Time Estimates (ETE) for the Susquehanna Steam Electric Station (SSES) located in Luzerne County, Pennsylvania. ETE are part of the required planning basis and provide PPL Susquehanna, LLC (PPL) and state and local governments with site-specific information needed for Protective Action decision-making.

In the performance of this effort, guidance is provided by documents published by Federal Governmental agencies. Most important of these are:

• Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR-7002, November 2011.

" Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants, NUREG-0654/FEMA-REP-1, Rev. 1, November 1980.

" Development of Evacuation Time Estimates for Nuclear Power Plants, NUREG/CR-6863, January 2005.

• 10CFR50, Appendix E - "Emergency Planning and Preparedness for Production and Utilization Facilities" Overview of Proiect Activities This project began in March, 2012 and extended over a period of 6 months. The major activities performed are briefly described in chronological sequence:

" Attended "kick-off" meetings with PPL personnel.

" Accessed U.S. Census Bureau data files for the year 2010. Studied Geographical Information Systems (GIS) maps of the area in the vicinity of the SSES, then conducted a detailed field survey of the highway network.

" Synthesized this information to create an analysis network representing the highway system topology and capacities within the Emergency Planning Zone (EPZ), plus a Shadow Region covering the region between the EPZ boundary and approximately 15 miles radially from the plant.

• Designed and sponsored a telephone survey of residents within the EPZ to gather focused data needed for this ETE study that were not contained within the census database. The survey used was carried out in 2008; it is still valid since there has not been a significant change in EPZ demographics. The survey instrument had been reviewed and modified by the licensee and offsite response organization (ORO) personnel prior to conducting the survey.

• Data collection forms (provided to PPL at the kickoff meeting) were returned with data Susquehanna Steam Electric Station ES-1 KLD Engineering, P.C.

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pertaining to employment, transients, and special facilities in each county.

• The traffic demand and trip-generation rates of evacuating vehicles were estimated from the gathered data. The trip generation rates reflected the estimated mobilization time (i.e., the time required by evacuees to prepare for the evacuation trip) computed using the results of the telephone survey of EPZ residents.

" Following federal guidelines, the EPZ is subdivided into 27 ERPA. These ERPA are then grouped within circular areas or "keyhole" configurations (circles plus radial sectors) that define a total of 30 Evacuation Regions.

• The time-varying external circumstances are represented as Evacuation Scenarios, each described in terms of the following factors: (1) Season (Summer, Winter); (2) Day of Week (Midweek, Weekend); (3) Time of Day (Midday, Evening); and (4) Weather (Good, Rain, Snow). One special event scenario - refueling at the plant - was considered. One roadway impact scenario was considered wherein a single lane was closed on Interstate 80 westbound for the duration of the evacuation.

• Staged evacuation was considered for those regions wherein the 2 mile radius and sectors downwind to 5 miles were evacuated.

" As per NUREG/CR-7002, the planning basis for the calculation of ETE is:

" A rapidly escalating accident at the SSES that quickly assumes the status of General Emergency such that the Advisory to Evacuate is virtually coincident with the siren alert, and no early protective actions have been implemented.

" While an unlikely accident scenario, this planning basis will yield ETE, measured as the elapsed time from the Advisory to Evacuate until the stated percentage of the population exits the impacted Region, that represent "upper bound" estimates. This conservative Planning Basis is applicable for all initiating events.

• If the emergency occurs while schools are in session, the ETE study assumes that the children will be evacuated by bus directly to reception centers or host schools located outside the EPZ. Parents, relatives, and neighbors are advised to not pick up their children at school prior to the arrival of the buses dispatched for that purpose. The ETE for schoolchildren are calculated separately.

" Evacuees who do not have access to a private vehicle will either ride-share with relatives, friends or neighbors, or be evacuated by buses provided as specified in the county evacuation plans. Those in special facilities will likewise be evacuated with public transit, as needed: bus, van, or ambulance, as required. Separate ETE are calculated for the transit-dependent evacuees, for homebound special needs population, and for those evacuated from special facilities.

Computation of ETE A total of 420 ETE were computed for the evacuation of the general public. Each ETE quantifies the aggregate evacuation time estimated for the population within one of the 30 Evacuation 0

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Regions to evacuate from that Region, under the circumstances defined for one of the 14 Evacuation Scenarios (30 x 14 = 420). Separate ETE are calculated for transit-dependent evacuees, including school children for applicable scenarios.

Except for Region R03, which is the evacuation of the entire EPZ, only a portion of the people within the EPZ would be advised to evacuate. That is, the Advisory to Evacuate applies only to those people occupying the specified impacted region. It is assumed that 100 percent of the people within the impacted region will evacuate in response to this Advisory. The people occupying the remainder of the EPZ outside the impacted region may be advised to take shelter.

The computation of ETE assumes that 20% of the population within the EPZ but outside the impacted region, will elect to "voluntarily" evacuate. In addition, 20% of the population in the Shadow Region will also elect to evacuate. These voluntary evacuees could impede those who are evacuating from within the impacted region. The impedance that could be caused by voluntary evacuees is considered in the computation of ETE for the impacted region.

Staged evacuation is considered wherein those people within the 2-mile region evacuate immediately, while those beyond 2 miles, but within the EPZ, shelter-in-place. Once 90% of the 2-mile region is evacuated, those people beyond 2 miles begin to evacuate. As per federal guidance, 20% of people beyond 2 miles will evacuate (non-compliance) even though they are advised to shelter-in-place.

The computational procedure is outlined as follows:

" A link-node representation of the highway network is coded. Each link represents a unidirectional length of highway; each node usually represents an intersection or merge point. The capacity of each link is estimated based on the field survey observations and on established traffic engineering procedures.

" The evacuation trips are generated at locations called "zonal centroids" located within the EPZ and Shadow Region. The trip generation rates vary over time reflecting the mobilization process, and from one location (centroid) to another depending on population density and on whether a centroid is within, or outside, the impacted area.

" The evacuation model computes the routing patterns for evacuating vehicles that are compliant with federal guidelines (outbound relative to the location of the plant), then simulate the traffic flow movements over space and time. This simulation process estimates the rate that traffic flow exits the impacted region.

The ETE statistics provide the elapsed times for 90 percent and 100 percent, respectively, of the population within the impacted region, to evacuate from within the impacted region. These statistics are presented in tabular and graphical formats. The 90th percentile ETE have been identified as the values that should be considered when making protective action decisions because the 100th percentile ETE are prolonged by those relatively few people who take longer to mobilize. This is referred to as the "evacuation tail" in Section 4.0 of NUREG/CR-7002.

The use of a public outreach (information) program to emphasize the need for evacuees to Susquehanna Steam Electric Station ES-3 KID Engineering, P.C.

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minimize the time needed to prepare to evacuate (secure the home, assemble needed clothes, medicines, etc.) should also be considered.

Traffic Management This study references the comprehensive traffic management plans provided in the Luzerne and Columbia County Radiological Emergency Response Plans. Due to the detailed plans already in place and the limited traffic congestion within the EPZ, no additional traffic or access control measures have been identified as a result of this study.

Selected Results A compilation of selected information is presented on the following pages in the form of figures and tables extracted from the body of the report; these are described below.

" Figure 6-1 displays a map of the SSES EPZ showing the layout of the 27 ERPA that comprise, in aggregate, the EPZ.

• Table 3-1 presents the estimates of permanent resident population in each ERPA based on the 2010 Census data.

• Table 6-1 defines each of the 30 Evacuation Regions in terms of their respective groups of ERPA.

" Table 6-2 lists the Evacuation Scenarios.

• Tables 7-1 and 7-2 are compilations of ETE. These data are the times needed to clear the indicated regions of 90 and 100 percent of the population occupying these regions, respectively. These computed ETE include consideration of mobilization time and of estimated voluntary evacuations from other regions within the EPZ and from the Shadow Region.

• Tables 7-3 and 7-4 presents ETE for the 2-mile region for un-staged and staged evacuations for the 9 0 th and 1 0 0 th percentiles, respectively.

" Table 8-7 presents ETE for the schoolchildren in good weather.

• Table 8-11 presents ETE for the transit-dependent population in good weather.

• Figure H-8 presents an example of an Evacuation Region (Region R08) to be evacuated under the circumstances defined in Table 6-1. Maps of all regions are provided in Appendix H.

Conclusions

" General population ETE were computed for 420 unique cases - a combination of 30 unique Evacuation Regions and 14 unique Evacuation Scenarios. Table 7-1 and Table 7-2 document these ETE for the 9 0 th and 1 0 0 th percentiles. These ETE range from 1:40 (hr:min) to 3:35 at the 9 0 th percentile.

• Inspection of Table 7-1 and Table 7-2 indicates that the ETE for the 100th percentile are significantly longer than those for the 9 0 th percentile. This is the result of the relatively long mobilization time of a small proportion of the resident population and congestion within the EPZ. When the system becomes congested, traffic exits the EPZ at rates somewhat below capacity until some evacuation routes have cleared. As more routes Susquehanna Steam Electric Station ES-4 KILD Engineering, P.C.

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clear, the aggregate rate of egress slows since many vehicles have already left the EPZ.

Towards the end of the process, relatively few evacuees (those with the longest mobilization times) travel freely out of the EPZ. See Figures 7-8 through 7-21.

• Inspection of Table 7-3 and Table 7-4 indicates that a staged evacuation provides no benefits to evacuees from within the 2 mile region and unnecessarily delays the evacuation of those beyond 2 miles (compare Regions R25 through R30 and Regions R04 through R08 and R02, respectively, in Tables 7-1 and 7-2). See Section 7.6 for additional discussion.

" Comparison of Scenarios 6 and 13 in Table 7-1 indicates that the Special Event -

refueling outage at the plant - does not have a significant impact on the ETE for the 9 0 th percentile. See Section 7.5 for additional discussion.

• Comparison of Scenarios 1 and 14 in Table 7-1 indicates that the roadway closure - one lane westbound on 1-80 from the interchange with SC 339 to the EPZ boundary - does not change the ETE, indicating that there is excess capacity on the highway. See Section 7.5.

" Nanticoke City and Briar Creek Borough and Township are the most congested areas during an evacuation. The last roadway in the EPZ to exhibit traffic congestion is SC 93.

All links within the EPZ are at LOS A (free-flowing traffic conditions) at 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> and 20 minutes after the Advisory to Evacuate. See Section 7.3 and Figures 7-3 through 7-7.

• Separate ETE were computed for schools, medical facilities, transit-dependent persons, homebound special needs persons and correctional facilities. The average single-wave ETE for these sources are within a similar range as the general population ETE at the 9 0 th percentile. See Section 8.

• Table 8-5 indicates that there are enough buses and wheelchair vans available, to evacuate the transit-dependent population within the EPZ in a single wave; however, aid agreements with other counties will need to be activated in order to provide enough ambulances to evacuate the bedridden population in a single wave. See Sections 8.4 and 8.5.

" The general population ETE at the 90th percentile is insensitive to reductions in the base trip generation time of 4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> since the mobilization time of the bulk of evacuees is unchanged by the truncation. See Table M-1.

• The general population ETE is relatively insensitive to the voluntary evacuation of vehicles in the Shadow Region (tripling the shadow evacuation percentage only increases 9 0 th percentile ETE by 5 minutes). See Table M-2.

• Population changes between +30% or -46% are needed to result in ETE changes which meet the criteria for updating ETE between decennial Censuses. See Section M.3.

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Figure 6-1. SSES EPZ ERPA Susquehanna Steam Electric Station ES-6 KLD Engineering, P.C.

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Table 3-1. EPZ Permanent Resident Population ERA 200Pplain 21.Pplto 1 2,132 2,024 2 2,227 2,107 3 2,100 2,041 4 2,117 2,241 5 203 225 6 703 766 7 4,270 4,287 8 959 838 9 1,385 1,453 10 10,552 10,387 11 645 646 12 1,532 1,569 13 1,092 1,166 14 1,247 1,196 15 3,613 4,213 16 1,956 1,912 17 2,105 2,188 18 1,112 1,115 19 671 679 20 5,021 5,377 21 10,930 10,462 22 4,614 5,826 23 609 652 24 2,251 2,324 25 910 973 26 1,501 1,520 27 3,288 3,088 EPZ Population Growth: 2.19%

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Table 6-1. Description of Evacuation Regions Region Description - - -

ERPA

- -

Rein Dsrpin 11 2 13 14 15 16 17 18 19 110 1111 12 13 141 161 18 920 122 324 526 7 R01 2-Mile Ring R02 5-Mile Ring R03 Full EPZ ERPA Region W ind Direction To: 137 8 1 1 R04 NNW, N, NNE __ _1 1 111 NE, W, WNW, NW Refer to RO0 ROS ENE, E, ESE R06 SE, SSE R07 S ROB SSW, SW, WSW ERPA Region Wind Direction To:

1 2 3 4 5 6 7 8 9 11 12 1 14 16 17 18 19 1 22 23 24 25 26 27 R09 N RIO NNE R11 NE R12 ENE R13 E R14 ESE R15 SE R16 SSE R17 S Susquehanna Steam Electric Station ES-8 KLD Engineering, P.C.

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0 ERPA Region Wind Direction To:

1 2 1 3 14 15 1 6 1 7 18 1 9 110 11 1 12 113 114 115 116 117 118 1 19 120 121 122 123 124 12 26 127 R25 NNW, N, NNE NE, W, WNW, NW Refer to RO0 R26 ENE, E, ESE R27 SE, SSE R28 S R29 SSW, SW, WSW SR30 5-Mile Ring ERPA(s) Shelter-in-Place Susquehanna Steam Electric Station ES-9 KLD Engineering, P.C.

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Table 6-2. Evacuation Scenario Definitions Day ofe Tim of 1 Summer Midweek Midday Good None 2 Summer Midweek Midday Rain None 3 Summer Weekend Midday Good None 4 Summer Weekend Midday Rain None 5 Summer Midweek, Evening Good None Weekend 6 Winter Midweek Midday Good None 7 Winter Midweek Midday Rain None 8 Winter Midweek Midday Snow None 9 Winter Weekend Midday Good None

.10 Winter Weekend Midday Rain None 11 Winter Weekend Midday Snow None 12 Winter Midweek, Evening Good None Weekend 13 Winter Midweek Midday Good Refueling SSES 14 Summer Midweek Midday Good Roadway Impact - Lane Closure on 1-80 WB 1 Winter assumes that school is in session (also applies to spring and autumn). Summer assumes that school is not in session.

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Table 7-1. lime to Clear the Indicated Area of 90 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Winter Summer Midweek Weekend MdekMidweek Weekend MdekMidweek Midweek Weekend Weekend Midday

_____________M_________ Midday Eveningnirwek 2-ieRgini-iedeinwadEZeek_

Midday Midday Evening

_________________ Midday Midday Region Good Rain Good Rain Good Good Rain Snow Good Rain Snow Good Special Roadway Weather Weather Weather Weather I I Weather Weather Event Impact Entire 2-Mile Region, S-Mile Region, and EPZ ROl R02 11:5511:55 2:00 2:10 1:40 1:55 145 j2:00 1:40 1:55 1:55 2:05 1:55 2:10 2:35 2:40 1:40 1:55 1.4512:25 2:00 2:30 1:401 1:55 1:50 2:05 r1:55 2:00 R03 2:20 2:30 2:10 2:15 2:15 2:20 2:30 3:00 I 2:10 2:15 2:50 2:15 j 2:25 2:20 2-Mile Region and Keyhole to 5 Miles R04 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 ROS 1:55 2:00 1:40 1:40 1:40 1:55 1:55 2:35 1:40 1:40 2:25 1:40 1:50 1:55 R06 2:00 2:00 1:40 1:40 1:40 2:00 2:00 2:40 1:40 1:40 2:25 1:40 1:55 2:00 R07 2:00 2:00 1:40 1:45 1:40 2:00 j 2:00 2:40 1:40 1:45 2:25 1:40 1:50 2:00 R08 2:00 2:00 1:40 1:40 1:40 2:00 j 2:00 2:40 1:40 1:40 I 2:25 1:40 1:55 2:00 S-Mile Region and Keyhole to EPZ Boundary R09 2:10 2:15 1:55 2:05 1:55 2:10 2:15 2:55 1:55 2:05 2:35 2:00 2:15 2:10 R1O 2:15 2:25 2:05 2:15 2:05 2:15 2:25 3:00 2:10 2:15 2:50 2:10 2:25 2:15 R11 2:10 2:20 2:00 2:10 2:05 2:10 2:20 2:50 2:00 2:10 2:40 2:05 2:15 2:10 R12 2:05 2:10 1:55 2:00 2:00 2:05 2:10 2:45 1:55 2:00 2:30 2:00 2:05 2:05 R13 1:55 2:00 1:50 1:50 1:50 1:55 2:00 2:30 1:50 1:50 2:20 1:50 1:SS 1:55 R14 1:55 2:00 1:50 1:50 1:50 1:55 2:00 2:30 1:50 1:50 2:20 1:50 1:55 1:55 R15 1:55 2:00 1:45 1:50 1:50 1:55 2:00 2:30 1:45 1:50 2:20 1:50 1:55 1:55 R16 1:55 2:00 1:50 1:50 1:50 1:55 2:00 2:30 1:45 1:50 2:20 1:50 1:55 1:55 R17 1:55 2:00 1:45 1:50 1:50 1:55 2:00 2:30 1:45 1:50 2:20 1:50 1:55 1:55 R18 2:05 2:10 1:55 2:00 2:00 2:05 2:10 2:40 1:55 2:00 2:30 2:00 2:05 2:05 R19 2:30 2:45 2:20 2:25 2:25 2:30 2:45 3:10 2:20 2:25 3:00 2:25 2:30 2:30 R20 2:35 2:40 2:20 2:30 2:25 2:35 2:50 3:15 2:20 2:30 3:05 2:25 2:30 2:35 R21 2:35 2:45 2:25 2:30 2:30 2:35 2:45 3:15 2:25 2:30 3:05 2:30 2:35 2:35 R22 2:30 2:40 2:20 2:30 2:20 2:30 2:40 3:10 2:20 2:25 3:00 2:20 2:30 2:30 R23 2:25 2:35 2:10 2:25 2:15 2:25 2:40 3:10 2:15 2:20 3:00 2:15 2:25 2:25 R24 2:10 2:15 1:55 2:05 1:55 2:10 2:15 2:45 1:55 2:05 2:35 1:55 2:10 2:10 Susquehanna Steam Electric Station ES-11 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Weekend Weekend Midweek Weekend Weekend WeekendI Midweek Midweek Midday Midday Evening Midday Midday Evening Midday Midday Region Good Rain Good Rain Good Good Rain Snow Good Rain Snow Good Special Roadway Weather I Weather I Weather Weather I Weather n Weather Event Impact Staged Evacuation Mile Region and Keyhole to 5 Miles R25 2:00 2:00 1:55 1:5S 1:55 2:00 2:00 2:35 1:55 1:55 2:30 1:55 1:55 2:00 R26 2:05 2:05 2:00 2:00 2:00 2:00 2:00 2:35 2:00 2:00 2:35 2:00 2:00 2:05 R27 2:05 2:05 2:05 205 2:05 2:05 205 2:40 2:05 2:03 2:3 2:0 2:05 205 R28 R2 R30 2:05 2:10 2:50 2:05 2:10 2:55 j 2:00 205 2:45 2:00 2:10 2:50 2:00 2:05 2:45 2:05 2:10 2:50 2:05 2:10 2:55 2:40 2:45 3:35 2:00 2:05 2:45 2:00 2:10 2:50 2:35 2:40 3:30 2:00 2:05 2:45 2:00 2:10 2:50 2:05 2:10 2:50 Susquehanna Steam Electric Station ES-12 KLD Engineering, P.C.

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Table 7-2. Time to Clear the Indicated Area of 100 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Winter Summer Midweek Weekend MdekMidweek Weekend MdekMidweek Midweek Weekend Weekend Region Go RanGoood RaiGod God Rinoo Midday Weather Ran Midday Weather Evening Enirwek Weather Weather Midday 2-ieieio.5-ieeeioankP RIn SnoGod Rinnw Go Spca Roawa Sno Weather Midday Ri Snw Evening Weather Midday Event Midday Impact Entire 2-Mile Region, 5-Mile Region, and EPZ Rol 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:35 4:00 4:00 4:30 4:00 4:00 4:00 R02 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 R03 4:10 4:10 4:10 4:10 4:10 , 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 2-Mile Region and Keyhole to 5 Miles R04 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 ROS 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 R06 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 R07 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 ROB 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 5-Mile Region and Keyhole to EPZ Boundary R09 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 RiO 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R11 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R12 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R13 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R14 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R1S 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R16 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R17 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 RIB 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R19 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R20 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R21 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R22 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R23 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 R24 4:10 4:10 4:10 4:10 4:10 4:10 4:10 4:40 4:10 4:10 4:40 4:10 4:10 4:10 Susquehanna Steam Electric Station ES-13 KLD Engineering, P.C.

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Summer Summer Summer Winter Winter Winter Winter Summer Midweek Midweek Midweek Weekend Weekend Weekend Midweek Weekend Weekend Weekend Midweek Midweek Scenari: (i (2 (3I4 S 6 7 9 9) (0 1 )(2 1 )(4 Midday Midday Evening Midday Midday Evening Midday Midday Region Good Rain Good Rain Good Good i Good Rain Snow Good Special Roadway Weather Weather Weather Weather Rain Snow Weather IWeather Event Impact Staged Evacuation Mile Region and Keyhole to 5 Miles R5 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35~ 4:05 4:05 4:35 4:05 4:05 4:05 R26 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 R~27 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 j4:35 4:05 4:05 4:05 R28 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 R29 4:05 4:05 4:05 4:05 4:05 4:05 4:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 R30 4:05 4:05 4:05 4:05 14:05 14:05 14:05 4:35 4:05 4:05 4:35 4:05 4:05 4:05 Rev. 0 Susquehanna Steam Electric Station ES-14 KLD Engineering, P.C.

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Table 7-3. Time to Clear 90 Percent of the 2-Mile Region SumW er Summer Summer Winter Winter Winter Winter Summer Midweek Weekend MdekMidweek Weekend Mdek Midweek Midweek Weekend IWeekendI Midday Midday Evening M____ nirwek2-ieReini-Mldegoadweek___

Midday Midday Evening Midday

____ Midday

___

Region Good I Good Good Good Good IGood Special Roadway ScnRol 1:51:4 (1:5WeteIRain Weather Rain 1:)45 S Weather (:01:5 Weather (7 Rain 1:55 2:51:4 Snow Wate (1045 Rain 2(211)012(1:50 Snow Wahr Eet Ipc (1:5 a -Mile Region, and EPZ Entire 2-Mile Region, 1:55 j 2:25 R02 R04 1:55 1:55 1:55 1:55 1:40 1:40 1:45 1:45 1:40 1:40 1:55 11:55 11:55 T2:35 2-Mile Region and Keyhole 2:35 to 5 Miles 1:40 1:40 1:45 1:45 2:25 1:40 1:40 1 1:50 1:50 1 1:55 1:55 R04 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 RO5 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 R06 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 R07 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 R08 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 Staged Evacuation Mile Region and Keyhole to 5 Miles R25 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 R26 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 R27 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 R28 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1.40 1:45 2:25 1:40 1:50 1:55 R29 1:55 1:55 1:40 1:45 1:40 1:55 1:55 2:35 1:40 1:45 2:25 1:40 1:50 1:55 R30 1:55 1:55 1:40 1:45 1:40 1:55 1 :5 235 1:40 1:5 2:25 1:40 1:50 ,, 1:55 Susquehanna Steam Electric Station ES-15 KLD Engineering, P.C.

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Table 7-4. Time to Clear 100 Percent of the 2-Mile Region Summer Summer Summer Winter Winter Winter Winter Summer Midweek Weekend MdekMidweek Weekend Mdek Midweek Midweek Weekend Weekend RegiWcnaiJ n, ood Rai Midday

(:00

[l___

4:0 Weather an 1400 400

]

0 God Ri 4:0 Midday Weather

,n Good (4) 4:0 j Eveningnirwek M____

(5

0 Weather Good

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4:00 Event Roadwa Midday 14:04:00]

Impact Entire 2-Mile Region, a-Mile Region, and EPZ R02 RO4 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:4:00 4:00 4:00 0

4:00 4:35 4:00 4:00 14:00 4:30 4:30 4:00 4:00 4:00 4:00 1 4:00 4:00

~ 400 RO4:0 40 :00 f 400 2-Mile400 Region and 4:0 Keyhole to 0 Miles 4:35 j4:00 4:00 43 4:0 4:00 J 4:00 R04 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:35 4:00 4:00 4:30 4:00 4:00 4:00

___ 4:00 4:00 4_00 4:00 St0e Ea ti - 2ol5 M 04:le 4:00 4:0 R06 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:35 4:00 4:00 4:30 4:00 4:00 4:00 R07 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:35 4:00 4:00 4:30 4:00 4:00 4:00 Staged Evacuation Mile Region and Keyhole to S Miles R25 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:35 4:00 4:00 4:30 4:00 4:00 4:00 R26. 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:35 4:00 4 .00 4.30 4:00 4:00 4:00 R27 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:35 4:00 4:00 4:30 4:00 4:00 4:00 R29 4:00 4:00 4:00 4:00 4:00 4:00 4:00 4:35 4:00 4:00 4:30 4:00 4:00 4:00 R30 4. ......... ... ........... .............

........................ .....

........... ....... . . ... .. .. 4:00..

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0 Table 8-7. School Evacuation Time Estimates - Good Weather Susquehanna Steam Electric Station ES-17 KLD Engineering, P.C.

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Table 8-11. Transit-Dependent Evacuation Time Estimates - Good Weather zu./ J.U 1,2 80 7.4 10.9 41 30 45.4 5 10o 91 1 30_

3,4 90 7.4 11.2 40 30 45.4 5 10 91 30 2 5,6 100 7.4 12.6 35 30 45.4 68 5 10 91 30 7,8 110 7.4 12.9 34 30 45.4 68 5 10 91 30 9,10,11 120 7.4 13.2 34 30 45.4 68 5 10 91 30 3 1 90 7.4 40.9 11 30 14.8 22 5 10 44 30 2 120 7.4 41.5 11 30 14.8 22 5 10 43 30 4 1 90 4.2 26.7 9 30 43.2 65 5 10 76 30 1 90 10.1 13.0 46 30 30.2 45 5 10 76 30 5 2 105 10.1 15.2 40 30 30.2 45 5 10 76 30 3 120 10.1 16.5 37 30 30.2 45 5 10 76 30 1,2 90 4.6 42.3 7 30 16.1 24 5 10 37 30 6 3,4 105 4.6 42.1 7 30 16.1 24 5 10 37 30 5,6 120 4.6 42.1 7 30 16.1 24 5 10 37 30 7 1 90 2.5 32.8 4 30 14.8 22 5 10 30 30 2 120 2.5 34.4 4 30 14.8 22 5 10 30 30 8 1 90 10.3 42.7 15 30 29.7 45 5 10 74 30 1 90 4.7 37.7 7 30 29.7 45 5 10 59 30 9

2 120 4.7 37.7 7 30 29.7 45 5 10 59 30 10 1 90 4.2 40.5 6 30 34.3 51 5 10 64 30 11 1 90 17.0 36.5 28 30 17.0 26 5 10 73 30 12 1 90 4.3 13.0 20 30 28.1 42 5 10 54 30 2 120 4.3 16.0 16 30 28.1 42 1 5 10 54 30 1 90 4.0 44.1 5 30 34.2 51 5 10 63 30 13 2 120 4.0 44.2 5 30 34.2 51 5 10 63 30 Susquehanna Steam Electric Station ES-18 KLD Engineering, P.C.

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0 Susquehanna Steam Electric Station ES-19 KLD Engineering, P.C.

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Figure H-8. Region R08 Susquehanna Steam Electric Station ES-20 KLD Engineering, P.C.

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1 INTRODUCTION This report describes the analyses undertaken and the results obtained by a study to develop Evacuation Time Estimates (ETE) for the Susquehanna Steam Electric Station (SSES), located in Luzerne County, Pennsylvania. ETE provide State and local governments with site-specific information needed for Protective Action decision-making.

In the performance of this effort, guidance is provided by documents published by Federal Governmental agencies. Most important of these are:

• Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR-7002, November 2011.

• Criteria for Preparation and Evaluation of Radiological Emergency Response Plans and Preparedness in Support of Nuclear Power Plants, NUREG 0654/FEMA REP 1, Rev. 1, November 1980.

• Analysis of Techniques for Estimating Evacuation Times for Emergency Planning Zones, NUREG/CR 1745, November 1980.

• Development of Evacuation Time Estimates for Nuclear Power Plants, NUREG/CR-6863, January 2005.

The work effort reported herein was supported and guided by local stakeholders who contributed suggestions, critiques, and the local knowledge base required. Table 1-1 presents a summary of stakeholders and interactions.

Table 1-1. Stakeholder Interaction Stkhle Naueo Stkhle Interactio PPL Susquehanna, LLC Meetings to define data requirements and set up

____________________________________contacts with local government agencies County Emergency Management Office itData validation 1.1 Overview of the ETE Process The following outline presents a brief description of the work effort in chronological sequence:

1. Information Gathering:

a. Defined the scope of work in discussions with representatives from PPL Susquehanna, LLC.

b. Attended meetings with emergency planners from PPL Susquehanna, LLC to identify issues to be addressed and resources available.

c. Conducted a detailed field survey of the highway system and of area traffic conditions within the Emergency Planning Zone (EPZ) and Shadow Region.

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d. Obtained demographic data from the 2010 census and the counties.

e. Conducted a random sample telephone survey of EPZ residents.

f. Conducted a data collection effort to identify and describe schools, special facilities, major employers, transportation providers, and other important information.

2. Estimated distributions of Trip Generation times representing the time required by various population groups (permanent residents, employees, and transients) to prepare (mobilize) for the evacuation trip. These estimates are primarily based upon the random sample telephone survey.

3. Defined Evacuation Scenarios. These scenarios reflect the variation in demand, in trip generation distribution and in highway capacities, associated with different seasons, day of week, time of day and weather conditions.

4. Reviewed the existing traffic management plan to be implemented by local and state police in the event of an incident at the plant. Traffic control is applied at specified Traffic Control Points (TCP) located within the EPZ.

5. Used existing ERPA to define evacuation regions. The EPZ is partitioned into 27 ERPA along jurisdictional and geographic boundaries. "Regions" are groups of contiguous ERPA for which ETE are calculated. The configurations of these Regions reflect wind direction and the radial extent of the impacted area. Each Region, other than those that approximate circular areas, approximates a "key-hole section" within the EPZ as recommended by NUREG/CR-7002.

6. Estimated demand for transit services for persons at "Special Facilities" and for transit-dependent persons at home.

7. Prepared the input streams for the DYNEV II system.

a. Estimated the evacuation traffic demand, based on the available information derived from Census data, and from data provided by local and state agencies, PPL Susquehanna and from the telephone survey.

b. Applied the procedures specified in the 2010 Highway Capacity Manual (HCM 1 )

to the data acquired during the field survey, to estimate the capacity of all highway segments comprising the evacuation routes.

c. Developed the link-node representation of the evacuation network, which is used as the basis for the computer analysis that calculates the ETE.

d. Calculated the evacuating traffic demand for each Region and for each Scenario.

e. Specified selected candidate destinations for each "origin" (location of each "source" where evacuation trips are generated over the mobilization time) to

'Highway Capacity Manual (HCM 2010), Transportation Research Board, National Research Council, 2010.

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support evacuation travel consistent with outbound movement relative to the location of the SSES.

8. Executed the DYNEV II model to determine optimal evacuation routing and compute ETE for all residents, transients and employees ("general population") with access to private vehicles. Generated a complete set of ETE for all specified Regions and Scenarios.

9. Documented ETE in formats in accordance with NUREG/CR-7002.

10. Calculated the ETE for all transit activities including those for special facilities (schools, medical facilities, etc.), for the transit-dependent population and for homebound special needs population.

1.2 The Susquehanna Steam Electric Station Location The SSES is located along the western shore of the Susquehanna River in Salem Township, Luzerne County, Pennsylvania. The site is approximately 30 miles southwest of Scranton, PA and 45 miles northwest of Allentown, PA. The Emergency Planning Zone (EPZ) consists of parts of Luzerne and Columbia Counties. Figure 1-1 displays the area surrounding the SSES. This map identifies the communities in the area and the major roads.

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Figure 1-1. Susquehanna Steam Electric Station Location Susquehanna Steam Electric Station 1-4 KLD Engineering, P.C.

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1.3 Preliminary Activities These activities are described below.

Field Surveys of the Highway Network KLD personnel drove the entire highway system within the EPZ and the Shadow Region which consists of the area between the EPZ boundary and approximately 15 miles radially from the plant. The characteristics of each section of highway were recorded. These characteristics are shown in Table 1-2:

Table 1-2. Highway Characteristics

• Number of lanes

• Posted speed

• Lane width

• Actual free speed

• Shoulder type & width 0 Abutting land use

• Interchange geometries

• Control devices

• Lane channelization & queuing 0 Intersection configuration (including capacity (including turn bays/lanes) roundabouts where applicable)

• Geometrics: curves, grades (>4%) 0 Traffic signal type

• Unusual characteristics: Narrow bridges, sharp curves, poor pavement, flood warning signs, inadequate delineations, toll booths, etc.

Video and audio recording equipment were used to capture a permanent record of the highway infrastructure. No attempt was made to meticulously measure such attributes as lane width and shoulder width; estimates of these measures based on visual observation and recorded images were considered appropriate for the purpose of estimating the capacity of highway sections. For example, Exhibit 15-7 in the HCM indicates that a reduction in lane width from 12 feet (the "base" value) to 10 feet can reduce free flow speed (FFS) by 1.1 mph - not a material difference - for two-lane highways. Exhibit 15-30 in the HCM shows little sensitivity for the estimates of Service Volumes at Level of Service (LOS) E (near capacity), with respect to FFS, for two-lane highways.

The data from the audio and video recordings were used to create detailed geographical information systems (GIS) shapefiles and databases of the roadway characteristics and of the traffic control devices observed during the road survey; this information was referenced while preparing the input stream for the DYNEV II System.

As documented on page 15-5 of the HCM 2010, the capacity of a two-lane highway is 1700 passenger cars per hour in one direction. For freeway sections, a value of 2250 vehicles per hour per lane is assigned, as per Exhibit 11-17 of the HCM 2010. The road survey has identified several segments which are characterized by adverse geometrics on two-lane highways which are reflected in reduced values for both capacity and speed. These estimates are consistent with the service volumes for LOS E presented in HCM Exhibit 15-30. These links may be Susquehanna Steam Electric Station 1-5 KLD Engineering, P.C.

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identified by reviewing Appendix K. Link capacity is an input to DYNEV II which computes the ETE. Further discussion of roadway capacity is provided in Section 4 of this report.

Traffic signals are either pre-timed (signal timings are fixed over time and do not change with the traffic volume on competing approaches), or are actuated (signal timings vary over time based on the changing traffic volumes on competing approaches). Actuated signals require detectors to provide the traffic data used by the signal controller to adjust the signal timings.

These detectors are typically magnetic loops in the roadway, or video cameras mounted on the signal masts and pointed toward the intersection approaches. If detectors were observed on the approaches to a signalized intersection during the road survey, detailed signal timings were not collected as the timings vary with traffic volume. TCPs at locations which have control devices are represented as actuated signals in the DYNEV II system.

If no detectors were observed, the signal control at the intersection was considered pre-timed, and detailed signal timings were gathered for several signal cycles. These signal timings were input to the DYNEV II system used to compute ETE, as per NUREG/CR-7002 guidance.

Figure 1-2 presents the link-node analysis network that was constructed to model the evacuation roadway network in the EPZ and Shadow Region. The directional arrows on the links and the node numbers have been removed from Figure 1-2 to clarify the figure. The detailed figures provided in Appendix K depict the analysis network with directional arrows shown and node numbers provided. The observations made during the field survey were used to calibrate the analysis network.

Telephone Survey A telephone survey was undertaken to gather information needed for the evacuation study.

Appendix F presents the survey instrument, the procedures used and tabulations of data compiled from the survey returns.

These data were-utilized to develop estimates of vehicle occupancy to estimate the number of evacuating vehicles during an evacuation and to estimate elements of the mobilization process.

This database was also referenced to estimate the number of transit-dependent residents.

Computing the Evacuation Time Estimates The overall study procedure is outlined in Appendix D. Demographic data were obtained from several sources, as detailed later in this report. These data were analyzed and converted into vehicle demand data. The vehicle demand was loaded onto appropriate "source" links of the analysis network using GIS mapping software. The DYNEV II system was then used to compute ETE for all Regions and Scenarios.

Analytical Tools The DYNEV II System that was employed for this study is comprised of several integrated computer models. One of these is the DYNEV (DYnamic Network EVacuation) macroscopic simulation model, a new version of the IDYNEV model that was developed by KLD under contract with the Federal Emergency Management Agency (FEMA).

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Figure 1-2. Susquehanna Steam Electric Station Link-Node Analysis Network Susquehanna Steam Electric Station 1-7 KLD Engineering, P.C.

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DYNEV II consists of four sub-models:

• A macroscopic traffic simulation model (for details, see Appendix C).

• A Trip Distribution (TD), model that assigns a set of candidate destination (D) nodes for each "origin" (0) located within the analysis network, where evacuation trips are "generated" over time. This establishes a set of O-D tables.

• A Dynamic Traffic Assignment (DTA), model which assigns trips to paths of travel (routes) which satisfy the O-D tables, over time. The TD and DTA models are integrated to form the DTRAD (Dynamic Traffic Assignment and Distribution) model, as described in Appendix B.

" A Myopic Traffic Diversion model which diverts traffic to avoid intense, local congestion, if possible.

Another software product developed by KLD, named UNITES (UNIfied Transportation Engineering System) was used to expedite data entry and to automate the production of output tables.

The dynamics of traffic flow over the network are graphically animated using the software product, EVAN (EVacuation ANimator), developed by KLD. EVAN is GIS based, and displays statistics such as LOS, vehicles discharged, average speed, and percent of vehicles evacuated, output by the DYNEV II System. The use of a GIS framework enables the user to zoom in on areas of congestion and query road name, town name and other geographical information.

The procedure for applying the DYNEV II System within the framework of developing ETE is outlined in Appendix D. Appendix A is a glossary of terms.

For the reader interested in an evaluation of the original model, I-DYNEV, the following references are suggested:

• NUREG/CR-4873 - Benchmark Study of the I-DYNEV Evacuation Time Estimate Computer Code

• NUREG/CR-4874 - The Sensitivity of Evacuation Time Estimates to Changes in Input Parameters for the I-DYNEV Computer Code The evacuation analysis procedures are based upon the need to:

• Route traffic along paths of travel that will expedite their travel from their respective points of origin to points outside the EPZ.

• Restrict movement toward the plant to the extent practicable, and disperse traffic demand so as to avoid focusing demand on a limited number of highways.

" Move traffic in directions that are generally outbound, relative to the location of the SSES.

DYNEV II provides a detailed description of traffic operations on the evacuation network. This description enables the analyst to identify bottlenecks and to develop countermeasures that are designed to represent the behavioral responses of evacuees. The effects of these Susquehanna Steam Electric Station 1-8 KLD Engineering, P.C.

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countermeasures may then be tested with the model.

1.4 Comparison with Prior ETE Study Table 1-3 presents a comparison of the present ETE study with the 2010 study. The major factors contributing to the differences between the ETE values obtained in this study and those of the previous study can be summarized as follows:

S Voluntary and shadow evacuations are considered at different percentages.

S Dynamic evacuation modeling that includes actuated signals and TCPs.

S The highway representation is more detailed.

The telephone survey results were re-analyzed using an improved outlier methodology, resulting in slightly shorter trip generation times.

Table 1-3. ETE Study Comparisons To-ic Preiu Std.urn ArcGIS Software using 2000 US Census IT Std blocks; block centroid method used; ArcGIS Software using 2010 US Census Resident Population population extrapolated to 2009 using blocks; area ratio method used.

Basis 2006 census estimates. Population = 71,275 Population = 70,327 Resident Population 2.52 persons/household, 1.30 2.52 persons/household, 1.30 Vehicle Occupancy evacuating vehicles/household evacuating vehicles/household VehicleOccupancy yielding: 1.94 persons/vehicle yielding: 1.94 persons/vehicle Employee estimates based on Employee estimates based on information provided by the counties, information provided by the counties, by internet searches, and by direct by internet searches, and by direct phone calls to major employers. Using phone calls to major employers. Using Employee the Journey to Work census data, the Journey to Work census data, Population estimated the percentage of estimated the percentage of employees residing outside the EPZ. employees residing outside the EPZ.

1.02 employees/vehicle based on 1.02 employees/vehicle based on phone survey results. phone survey results.

Employees = 4,476 Employees = 4,476 Estimates based upon U.S. Census Telephone survey results used to data, the results of the telephone estimate transit dependent population. survey, and data provided in the Transit-Dependent Verified with the information provided Luzerne County RERP. A total of 6,010 Population in the county and municipal emergency vehicle, requiring 103 buses to evacue. Anaditina 10 5 plans. There are a total of 2,040 people requiring 68 buses to evacuate.evca.Anditol10homebound special needs persons needing 53 ambulances.

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-I Toi.rviu. ST td Curn ET Std 0 Transient estimates based on Transient estimates based on Transient information from each county, includes information from each county, Population colleges colleges considered separately Transients = 5,036 Transients = 2,952 Special facility population based on Special facility population based on information provided by each county information provided by each county within the EPZ.

Special Facilities within the EPZ. Current census = 836 Population Special Facility Population = 836 Buses Required 27 Vehicles originating at special facilities Wheelchair Van Required = 15

= 122 Ambulances Required = 85 School population based on School population based on information provided by each county information provided by each county within the EPZ. Does not include School Population colleges. within the EPZ. Includes colleges.

School enrollment =10,771 School enrollment = 13,193 Buses = 185 Buses required = 189 Voluntary 50 percent of population within the evacuation from outer extent of the region; 35 percent 20 percent of the population within within EPZ in areas of population in annular ring between the EPZ, but not within the Evacuation outside region to be the outer extent and the EPZ boundary. Region (see Figure 2-1) evacuated 30% of people outside of the EPZ 20% of people outside of the EPZ Shadow Evacuation within the shadow area. within the Shadow Region (see Figure 7-2)

Network Size 1517 links; 1046 nodes 1675 links; 1,136 nodes Field surveys conducted in 2008. Major intersections were video archived. GIS Field surveys conducted in February Roadway Geometric shape-files of signal locations and 2010. Roads and intersections were Data roadway characteristics created during video archived.

road survey. Road capacities based on Road capacities based on 2010 HCM.

2000 HCM.

School Evacuation Direct evacuation to designated Host Direct evacuation to designated Host Sc o lS School. h o.

School.

50 percent of transit dependent 50 percent of transit-dependent Ridesharing persons will ride with a neighbor or persons will evacuate with a neighbor I friend, or friend.

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To-icPeiu T StdCurn T Std Based on residential telephone survey Based on residential telephone survey of specific pre-trip mobilization of specific pre-trip mobilization activities: activities:

Residents with commuters returning Residents with commuters returning leave between 45 and 330 minutes. leave between 30 and 240 minutes.

Trip Generation for Residents without commuters Residents without commuters Evacuation returning leave between 15 and 300 returning leave between 15 and 180 minutes. minutes.

Employees and transients leave Employees and transients leave between 15 and 120 minutes. between 15 and 135 minutes.

All times measured from the Advisory All times measured from the Advisory to Evacuate. to Evacuate.

Normal, Rain, or Snow. The capacity Normal, Rain, or Snow. The capacity and free flow speed of all links in the and free flow speed of all links in the network are reduced by 10% in the network are reduced by 10% in the event of rain and 20% for snow. event of rain and 20% for snow.

Modeling IDYNEV System: TRAD and PC-DYNEV. DYNEV II System - Version 4.0.10.0 Bell Bend Construction and SSES Refueling SSES Refueling Special Event Special Events Population = 784 additional non-EPZ Special Event Population = 800 employees additional employees 30 Regions (central sector wind 22 Regions and 13 Scenarios producing direction and each adjacent sector 286 unique cases. technique used) and 14 Scenarios producing 420 unique cases.

Evacuation Time ETE reported for 50th, 90th, 95th, and ETE reported for 9 0 th and 1 0 0 th in Estimates Reporting 100th percentile population. Results percentile population. Results presented by Region and Scenario. presented by Region and Scenario.

Winter Weekday Midday, Winter Weekday Midday, Evacuation Time Good Weather: 3:05 Good Weather: 2:20 Estimates for the entire EPZ, 9 0 th percentile Summer Weekend, Midday, Summer Weekend, Midday, Good Weather: 2:50 Good Weather: 2:10 KLD Engineering, P.C.

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2 STUDY ESTIMATES AND ASSUMPTIONS S

This section presents the estimates and assumptions utilized in the development of the evacuation time estimates.

2.1 Data Estimates

1. Population estimates are based upon Census 2010 data.

2. Estimates of employees who reside outside the EPZ and commute to work within the EPZ are based upon data obtained from the counties.

3. Population estimates at special facilities are based on available data from county emergency management offices.

4. Roadway capacity estimates are based on field surveys and the application of the Highway Capacity Manual 2010.

5. Population mobilization times are based on a statistical analysis of data acquired from a random sample telephone survey of EPZ residents (see Section 5 and Appendix F).

6. The relationship between resident population and evacuating vehicles is developed from the telephone survey. Average values of 2.52 persons per household and 1.30 evacuating vehicles per household are used. The relationship between persons and vehicles for transients and employees is as follows:

a. Employees: 1.02 employees per vehicle (telephone survey results) for all major employers.

b. Parks: Vehicle occupancy varies based upon data gathered from local transient facilities.

c. Special Events: Assumed the additional employees for the SSES refueling would evacuate with the same vehicles occupancy as EPZ employees - 1.02 employees per vehicle.

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2.2 Study Methodological Assumptions

1. ETE are presented for the evacuation of the 9 0 th and 1 0 0 th percentiles of population for each Region and for each Scenario. The percentile ETE is defined as the elapsed time from the Advisory to Evacuate issued to a specific Region of the EPZ, to the time that Region is clear of the indicated percentile of evacuees. A Region is defined as a group of ERPA that is issued an Advisory to Evacuate. A scenario is a combination of circumstances, including time of day, day of week, season, and weather conditions.

2. The ETE are computed and presented in tabular format and graphically, in a format compliant with NUREG/CR-7002.

3. Evacuation movements (paths of travel) are generally outbound relative to the plant to the extent permitted by the highway network. All major evacuation routes are used in the analysis.

4. Regions are defined by the underlying "keyhole" or circular configurations as specified in Section 1.4 of NUREG/CR-7002. These Regions, as defined, display irregular boundaries reflecting the geography of the ERPA included within these underlying configurations.

5. As indicated in Figure 2-2 of NUREG/CR-7002, 100% of people within the impacted "keyhole" evacuate. 20% of those people within the EPZ, not within the impacted keyhole, will voluntarily evacuate. 20% of those people within the Shadow Region will voluntarily evacuate. See Figure 2-1 for a graphical representation of these evacuation percentages. Sensitivity studies explore the effect on ETE of increasing the percentage of voluntary evacuees in the Shadow Region (see Appendix M).

6. A total of 14 "Scenarios" representing different temporal variations (season, time of day, day of week) and weather conditions are considered. These Scenarios are outlined in Table 2-1.

7. Scenario 14 considers the closure of a single lane westbound on Interstate-80 from the interchange with SR 339/W 3 rd Street (Exit 242) to the end of the EPZ at the interchange with US-11 (Exit 241).

8. The models of the I-DYNEV System were recognized as state of the art by the Atomic Safety & Licensing Board (ASLB) in past hearings. (Sources: Atomic Safety & Licensing Board Hearings on Seabrook and Shoreham; Urbanik'). The models have continuously been refined and extended since those hearings and were independently validated by a consultant retained by the NRC. The new DYNEV II model incorporates the latest technology in traffic simulation and in dynamic traffic assignment.

1 Urbanik, T., et. al. Benchmark Study of the I-DYNEV Evacuation Time Estimate Computer Code, NUREG/CR-4873, Nuclear Regulatory Commission, June, 1988.

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Table 2-1. Evacuation Scenario Definitions 1 Summer Midweek Midday Good None 2 Summer Midweek Midday Rain None 3 Summer Weekend Midday Good None 4 Summer Weekend Midday Rain None 5 Summer Midweek, Evening Good None Summer Weekend 6 Winter Midweek Midday Good None 7 Winter Midweek Midday Rain None 8 Winter Midweek Midday Snow None 9 Winter Weekend Midday Good None 10 Winter Weekend Midday Rain None 11 Winter Weekend Midday Snow None 12 Winter Midweek, Evening Good None Weekend 13 Winter Midweek Midday Good SSES Refueling Roadway Impact - Lane 14 Summer Midweek Midday Good Closure on 1-80 WB 2 Winter assumes that school is in session (also applies to spring and autumn). Summer assumes that school is not in session.

2-3 KLD Engineering, P.C.

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0 I ý ý1 I / ~ \\\

~R~J

\  !

/ E \.

Keyhole: 2-Mile Rogom It5 Mile Downwin Staged Evacuaton: 2-Mile Region &5 Mks Downwind I II m m I I* Plant Location N Region to be Evocuate4. 100% Evacuation E320% Shadow Ev*acutin *She he vacuat w'lte Figure 2-1. Voluntary Evacuation Methodology Susquehanna Steam Electric Station 2-4 KLD Engineering, P.C.

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2.3 Study Assumptions

1. The Planning Basis Assumption for the calculation of ETE is a rapidly escalating accident that requires evacuation, and includes the following:

a. Advisory to Evacuate is announced coincident with the siren notification.

b. Mobilization of the general population will commence within 15 minutes after siren notification.

c. ETE are measured relative to the Advisory to Evacuate.

2. It is assumed that everyone within the group of ERPA forming a Region that is issued an Advisory to Evacuate will, in fact, respond and evacuate in general accord with the planned routes.

3. 52 percent of the households in the EPZ have at least 1 commuter; 60 percent of those households with commuters will await the return of a commuter before beginning their evacuation trip, based on the telephone survey results. Therefore 31 percent (52% x 60% = 31%) of EPZ households will await the return of a commuter, prior to beginning their evacuation trip.

4. The ETE will also include consideration of "through" (External-External) trips during the time that such traffic is permitted to enter the evacuated Region. "Normal" traffic flow is assumed to be present within the EPZ at the start of the emergency.

5. Access Control Points (ACP) will be staffed within approximately 90 minutes following the siren notifications, to divert traffic attempting to enter the EPZ. Earlier activation of ACP locations could delay returning commuters. It is assumed that no through traffic will enter the EPZ after this 90 minute time period.

6. Traffic Control Points (TCP) within the EPZ will be staffed over time, beginning at the Advisory to Evacuate. Their number and location will depend on the Region to be evacuated and resources available. The objectives of these TCP are:

a. Facilitate the movements of all (mostly evacuating) vehicles at the location.

b. Discourage inadvertent vehicle movements towards the plant.

c. Provide assurance and guidance to any traveler who is unsure of the appropriate actions or routing.

d. Act as local surveillance and communications center.

e. Provide information to the emergency operations center (EOC) as needed, based on direct observation or on information provided by travelers.

In calculating ETE, it is assumed that evacuees will drive safely, travel in directions identified in the plan, and obey all control devices and traffic guides.

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7. Buses will be used to transport those without access to private vehicles:

a. If schools are in session, transport (buses) will evacuate students directly to the designated host schools.

b. It is assumed parents will pick up children at day care centers prior to evacuation.

c. Buses, wheelchair vans and ambulances will evacuate patients at medical facilities and at any senior facilities within the EPZ, as needed.

d. Transit-dependent general population will be evacuated to Reception Centers.

e. Schoolchildren, if school is in session, are given priority in assigning transit vehicles.

f. Bus mobilization time is considered in ETE calculations.

g. Analysis of the number of required round-trips ("waves") of evacuating transit vehicles is presented.

h. Transport of transit-dependent evacuees from reception centers to mass care centers is not considered in this study.

8. Provisions are made for evacuating the transit-dependent portion of the general population to reception centers by bus, based on the assumption that some of these people will ride-share with family, neighbors, and friends, thus reducing the demand for buses. We assume that the percentage of people who rideshare is 50 percent. This assumption is based upon reported experience for other emergencies 3, and on guidance in Section 2.2 of NUREG/CR-7002.

9. Two types of adverse weather scenarios are considered. Rain may occur for either winter or summer scenarios; snow occurs in winter scenarios only. It is assumed that the rain or snow begins earlier or at about the same time the evacuation advisory is issued.

No weather-related reduction in the number of transients who may be present in the EPZ is assumed. It is assumed that roads are passable and that the appropriate agencies are plowing the roads as they would normally when snowing.

Adverse weather scenarios affect roadway capacity and the free flow highway speeds.

The factors applied for the ETE study are based on recent research on the effects of weather on roadway operations 4; the factors are shown in Table 2-2.

3 Institute for Environmental Studies, University of Toronto, THE MISSISSAUGA EVACUATION FINAL REPORT, June 1981. The report indicates that 6,600 people of a transit-dependent population of 8,600 people shared rides with other residents; a ride share rate of 76% (Page 5-10).

4 Agarwal, M. et. Al. Impacts of Weather on Urban Freeway Traffic Flow Characteristics and Facility Capacity, Proceedings of the 2005 Mid-Continent Transportation Research Symposium, August, 2005. The results of this paper are included as Exhibit 10-15 in the HCM 2010.

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10. School buses used to transport students are assumed to transport 70 students per bus for elementary schools and 50 students per bus for middle and high schools, unless specific data was provided. Transit buses used to transport the transit-dependent general population are assumed to transport 30 people per bus.

Table 2-2. Model Adjustment for Adverse Weather Scnai Capacity* Sped Moiizto Tim fo Geea Pouato Rain 90% 90% No Effect Clear driveway before leaving hornle (See Figure F-12)

• Adverse weather capacity and speed values are given as a percentage of good weather conditions. Roads are assumed to be passable.

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3 DEMAND ESTIMATION The estimates of demand, expressed in terms of people and vehicles, constitute a critical element in developing an evacuation plan. These estimates consist of three components:

1. An estimate of population within the EPZ, stratified into groups (resident, employee, transient).

2. An estimate, for each -population group, of mean occupancy per. evacuating vehicle. This estimate is used to determine the number of evacuating vehicles.

3. An estimate of potential double-counting of vehicles.

Appendix E presents much of the source material for the population estimates. Our primary source of population data, the 2010 Census, however, is not adequate for directly estimating some transient groups.

Throughout the year, vacationers and tourists enter the, EPZ. These non-residents may dwell within the EPZ for a short period (e.g. a few days or one or two weeks), or may enter and leave within one day. Estimates of the size of these population components must be obtained, so that the associated number of evacuating vehicles can be ascertained.

The potential for double-counting people and vehicles must be addressed. For example:

• A resident who works and shops within the EPZ could be counted as a resident, again as an employee and once again as a shopper.

• A visitor who stays at a hotel and spends time at a park, then goes shopping could be counted three times.

Furthermore, the number of vehicles at a location depends on time of day. For example, motel parking lots may be full at dawn and empty at noon. Similarly, parking lots at area parks, which are full at noon, may be almost empty at dawn. Estimating counts of vehicles by simply adding up the capacities of different types of parking facilities will tend to overestimate the number of transients and can lead to ETE that are too conservative.

Analysis of the population characteristics of the SSES EPZ indicates the need to identify three distinct groups:

" Permanent residents - people who are year round residents of the EPZ.

• Transients - people who reside outside of the EPZ who enter the area for a specific purpose (shopping, recreation) and then leave the area.

• Employees - people who reside outside of the EPZ and commute to businesses within the EPZ on a daily basis.

Estimates of the population and number of evacuating vehicles for each of the population groups are presented for each ERPA and by polar coordinate representation (population rose).

The SSES EPZ is subdivided into 27 ERPAs. The EPZ is shown in Figure 3-1.

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3.1 Permanent Residents The primary source for estimating permanent population is the latest U.S. Census data. The average household size (2.52 persons/household - See Figure F-1) - and the number of evacuating vehicles per household (1.30 vehicles/household - See Figure F-7) were adapted from the telephone survey results.

Population estimates are based upon Census 2010 data. The estimates are created by cutting the census block polygons by the ERPA and EPZ boundaries. A ratio of the original area of each census block and the updated area (after cutting) is multiplied by the total block population to estimate what the population is within the EPZ. This methodology assumes that the population is evenly distributed across a census block. Table 3-1 provides the permanent resident population within the EPZ, by ERPA based on this methodology.

The year 2010 permanent resident population is divided by the average household size and then multiplied by the average number of evacuating vehicles per household in order to estimate number of vehicles. Permanent resident population and vehicle estimates are presented in Table 3-2. Figure 3-2 and Figure 3-3 present the permanent resident population and permanent resident vehicle estimates by sector and distance from SSES. This "rose" was constructed using GIS software.

It can be argued that this estimate of permanent residents overstates, somewhat, the number of evacuating vehicles, especially during the summer. It is certainly reasonable to assert that some portion of the population would be on vacation during the summer and would travel elsewhere. A rough estimate of this reduction can be obtained as follows:

• Assume 50 percent of all households vacation for a two-week period over the summer.

• Assume these vacations, in aggregate, are uniformly dispersed over 10 weeks, i.e. 10 percent of the population is on vacation during each two-week interval.

" Assume half of these vacationers leave the area.

On this basis, the permanent resident population would be reduced by 5 percent in the summer and by a lesser amount in the off-season. Given the uncertainty in this estimate, we elected to apply no reductions in permanent resident population for the summer scenarios to account for residents who may be out of the area.

0 Susquehanna Steam Electric Station 3-2 KILD Engineering, P.C.

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Figure 3-1. SSES EPZ Susquehanna Steam Electric Station 3-3 KLD Engineering, P.C.

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Table 3-1. EPZ Permanent Resident Population egg.Pplto 200 200 Poplaio 1 2,132 2,024 2 2,227 2,107 3 2,100 2,041 4 2,117 2,241 5 203 225 6 703 766 7 4,270 4,287 8 959 838 9 1,385 1,453 10 10,552 10,387 11 645 646 12 1,532 1,569 13 1,092 1,166 14 1,247 1,196 15 3,613 4,213 16 1,956 1,912 17 2,105 2,188 18 1,112 1,115 19 671 679 20 5,021 5,377 21 10,930 10,462 22 4,614 5,826 23 609 652 24 2,251 2,324 25 910 973 26 1,501 1,520 27 3,288 3,088 EPZ Population Growth: 2.19%

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Table 3-2. Permanent Resident Population and Vehicles by ERPA

• * *g2010 1 2,024 1,050 2 2,107 1,090 3 2,041 1,056 4 2,241 1,158 5 225 118 6 766 403 7 4,287 2,220 8 838 437 9 1,453 755 10 10,387 5,357 11 646 335 12 1,569 810 13 1,166 607 14 1,196 621 15 4,213 2,180 16 1,912 984 17 2,188 1,133 18 1,115 575 19 679 350 20 5,377 2,780 21 10,462 5,400 22 5,826 3,006 23 652 336 24 2,324 1,202 25 973 508 26 1,520 790 27 3,088 1,604 Station Electric Station Steam Electric KID Engineering, P.C.

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N NNW NNE 4,1

- -' - 683 521* '

- 113 WNW W

430 2,65 wSw 18,51 S 123 881 SSW--

S 3 60 N 2,10 Resident Population Miles Subtotal by Ring Cumulative Total 0 1 178 178 1 -2 817 995 2*3 1,043 2,038 3 4 2,584 4,622 W E 4- 5 6,687 11,309 5-6 8;151 19,460 6-7 8,893 .. 28,353 7-8 7,654 36,007 8 -9 8,279 44,286

.9- 10 .. ... .9,513 ,. 53,799.

10 - EPZ 17,476 71,275 Inset Total: 71,275 0-2Miles S Figure 3-2. Permanent Resident Population by Sector Susquehanna Steam Electric Station 3-6 KLD Engineering, P.C.

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N NNW NNE 1, 9-151 S*9160

- -' - 354 S 60 269 S WNW ENE I

1,101 I-W E 04 248 133 223 1,36

-1 WSW %81o ESE

=s "I1 m

10 Miles to EPZ Boundary SSW =I 4458 748 S -N 1,861 Resident Vehicles 12 miles Subtotal by Ring Cumulative Total 30 0 -1 92 92 0 0 1 -2 423 515 2 -3 540 1,055 0 00 3-4 1,343. 2,398 W 4-5 3,4661 5,864 5 6 4,213 10,077 6-7 " 4 9 . 1:4,668 7-8 3961 18,629 8-9 4,28 1 22,910 9-10 4,917 27,827 10- EPZ 9,038 36,865 Inset Total 36,865 0 - 2rMiles S Figure 3-3. Permanent Resident Vehicles by Sector Susquehanna Steam Electric Station 3-7 KLD Engineering, P.C.

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3.2 Shadow Population A portion of the population living outside the evacuation area extending to 15 miles radially from the SSES (in the Shadow Region) may elect to evacuate without having been instructed to do so. Based upon NUREG/CR-7002 guidance, it is assumed that 20 percent of the permanent resident population, based on U.S. Census Bureau data, in this Shadow Region will elect to evacuate.

Shadow population characteristics (household size, evacuating vehicles per household, mobilization time) are assumed to be the same as that for the EPZ permanent resident population. Table 3-3, Figure 3-4, and Figure 3-5 present estimates of the shadow population and vehicles, by sector.

Table 3-3. Shadow Population and Vehicles by Sector Seto Pouain EauaigVhce N 2,531 1,312 NNE 3,929 956 NE 14,279 7,372 ENE 10,091 5,213 E 3,240 1,672 ESE 9,978 5,153 SE 37,348 19,256 SSE 565 296 S 2,175 1,133 SSW 474 246 SW 481 250 WSW 4,981 2,574 W 1,646 857 WNW 2,127 1,109 NW 1,017 532 NNW 1,169 608 Susquehanna Steam Electric Station 3-8 KLD Engineering, P.C.

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N NNW F2,5311 NNE 1,169 WNW ENE 2,-1275 3.470 E

96'ESEEP 74 3,24 0, 1T,64t(

113 WSW 2,064 ESE 4,981 SE F37,3481 SSW .L...." SSE EPZBoundiry toll1 Miles 474 S Shadow PoPulation Miles SubtOtal by Ring Cumulative Total EPZ - 11 4,801 4,801:

11- 12 16,949 21,750 12 -13 26,802 48,552 13 1-i4 . .23,448 72;000 14 15 24,031 96,0311 Total: 96,0'311 Figure 3-4. Shadow Population by Sector Susquehanna Steam Electric Station 3-9 KILD Engineering, P.C.

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N NNW 1,312 NNE 608 F9561 WNW ENE 1.789 036 E

857 so 39 1,Q6 7,2 023 WSW 1.066 ESE SE 1F9256*

SSW * . ° .SSE

~,EPZ Boundary toll Miles s 296 F1,13 3 Shadow Vehicles Miles Subtotal by Ring Cumulative Total EPZ -13 1 .2,49. 3 2,493 11- 12 8,7.43 11,236 12 113 13,844 .25,080

.13-14 12,102 .37,182 14- 15 11,357, 484539 Total: 48,539 Figure 3-5. Shadow Vehicles by Sector Susquehanna Steam Electric Station Susqehana teamEletri StaionKLDEngieerngP.C KLD Engineering, P.C.

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3.3 Transient Population Transient population groups are defined as those people (who are not permanent residents, nor commuting employees) who enter the EPZ for a specific purpose (shopping, recreation).

Transients may spend less than one day or stay overnight at camping facilities, hotels and motels. The SSES EPZ has a number of areas and facilities that attract transients, including:

" Lodging facilities

• Hunting grounds

• Fishing areas

" Campgrounds

• Golf courses

• Parks

" Transient students In depth data collection was carried out in support of the SSES/Bell Bend COLA I in 2008 and updated in 2009. These data were included in the final SSES/Bell Bend ETE report, dated January 2011. In 2012, PPL and the offsite agencies reviewed and updated these data as necessary for use in this study.

There are a total of 2,952 transients in 1,163 vehicles considered in this study. Details on the estimates for each category of transient facility are provided in the following sub-sections and in Appendix E. In addition, there are 2,268 vehicles - 2,260 private vehicles plus 8 passenger car equivalent vehicles (4 buses) - loaded for the commuter students in the winter scenarios.

Table 3-4 summarizes the transient population and vehicles by ERPA. Figure 3-6 and Figure 3-7 present these data by sector and distance from the SSES.

Appendix E summarizes the transient data that was estimated for the EPZ. Table E-5 presents the number of transients visiting parks and recreational areas and Table E-6 shows the number at lodging facilities within the EPZ.

3.3.1 Lodging Facilities A total of 11 lodging facilities were identified within the EPZ. Detailed data for 7 of these facilities were provided during telephone conversations with management of these facilities.

Based on the data provided, the average occupancy for lodging facilities is 89%. Those people staying at lodging facilities are by definition transients. On average, there are 2 people and 1 vehicle per occupied room. A total of 1,082 transients in 541 vehicles are assigned to lodging facilities in the EPZ.

3.3.2 Hunting Grounds The Pennsylvania State Game Lands 55, 58, 187, 224 and 260 (identification numbers provided by the state) are within the EPZ. These were identified using geospatial data obtained from the Pennsylvania Geospatial Data Clearinghouse. Based on a telephone conversation with the Susquehanna Steam Electric Station 3-11 KILD Engineering, P.C.

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Information Officer (10) for the Pennsylvania Game Commission (PGC), there are 900,000 licensed hunters in the state. There are a total of 1.46 million acres of game land within the 0

state (8,158 acres of which are within the EPZ) based on a GIS analysis of the aforementioned geospatial data.

Based on information provided by the 10, the peak hunting season is during the months of November and December - a total of 61 days. It is assumed that each hunter hunts for 7 days of the season, on average, and that these 7 days are uniformly distributed throughout the season.

Multiplying the 900,000 licensed hunters by 7 days of hunting per season and dividing by a 61 day season results in about 103,300 hunters per day, on average. Dividing the 103,000 hunters per day by the 1.46 million acres of state game land results in 0.071 hunters per acre per day.

Multiplying this result by the 8,158 acres of state game land within the EPZ results in 577 hunters in the EPZ. As there are many game lands throughout the state, it is unlikely that people would travel outside of their local area to hunt at a different state game land; therefore, most people hunting in the EPZ are most likely EPZ residents. However, a conservative transient percentage of 53% obtained from the campground data is applied (see item 5 below). Thus, there are 306 transient hunters in the EPZ. These 306 transient hunters are apportioned amongst the 5 state game lands within the EPZ by acreage. It is assumed there are 2 hunters per vehicle based on data obtained from calls to golf courses (see item below) as both activities are recreational sports.

3.3.3 Fishing Areas Using the Pennsylvania State Fishing website, three locations within the EPZ were identified:

one site along the Susquehanna River, one site at Lake Lily and another at Briar Creek Lake. The number of vehicles was estimated by using aerial imagery of the parking lots in the vicinity of the fishing areas. The Pennsylvania Game Commission (PGC) was contacted but did not have data on fishing within the EPZ. The capacity of the parking lot at each facility was estimated using aerial imagery; the average occupancy of 76% and the average percent transients of 53%

obtained for campgrounds in the EPZ were applied to estimate the number of parking spaces used by transients. A total of in 58 vehicles (114 transients) were loaded onto the network to account for transient fishing activity.

3.3.4 Campgrounds Four camping facilities and one children's camp (Camp Louise) were identified within the EPZ.

Camp Louise is dependent on transportation assistance for evacuation and is covered in depth in Section 8.4. Based on telephone conversations with management of the other three camping facilities, the following data, on average, were provided: 1 vehicle and 4 persons per occupied site; 53% of these people are transients; and peak occupancy is 76%. The peak population estimate for camping facilities is 1,002 transients in 215 passenger car equivalents.

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3.3.5 Golf Courses Four major golf courses were identified within the EPZ. Based on telephone conversations with representatives from the golf courses, the peak population at these facilities ranges from 75 to 175 persons and the percent transients ranges from 5% to 70%. All facilities indicated a vehicle occupancy rate of 2 people per vehicle. A total of 162 transients and 81 vehicles are loaded at these facilities.

3.3.6 Parks The Nescopeck State Park is located along the eastern boundary of the EPZ; hiking and fishing are prevalent in the park. Approximately 9% of the park, by area, is within the EPZ. Using aerial imagery of the parking lots within the EPZ, 125 vehicle spaces were estimated. Based on telephone conversations with management of the park, detailed data on peak occupancy and percent transients was not available. The average occupancy of 76% and percent transients of 53% obtained for campgrounds are applied to the 125 parking spaces within the EPZ to estimate the number of transient vehicles. It is assumed that people will travel to the park as a family in a single vehicle; the average household size of 2.52 persons (see Figure F-i) is used to estimate the number of transients based on the number of transient vehicles.

The Susquehanna Riverlands Recreational Area is approximately 400 acres and offers picnicking, hiking, ball fields, playgrounds, fishing along the north branch of the Susquehanna River, and hunting. Based on data provided by management of the facility, the peak season for the facility is from April to June with approximately 300 people per day visiting on the weekends. The percentage of these people which are transients was unknown. The average transient percentage of 53% obtained for campgrounds is applied to this facility to estimate the number of transients. As with the Nescopeck State Park, it is assumed that people will travel to the facility as a family in a single vehicle; the number of transients is divided by the average household size of 2.52 persons to estimate the number of evacuating vehicles.

A total of 286 transients and 113 transient vehicles are loaded at these parks.

3.4 College Students The Penn State Hazelton campus enrollment consists of 475 resident students and 757 commuting students. The number of resident students requiring transportation in an evacuation is conservatively estimated as 475 x 0.5 = 238 (A 50% rideshare percentage is applied for all transit dependents). Using a bus occupancy of 50, 5 buses (10 passenger car equivalent) are required. The ETE for transit dependent students is covered in Section 8.4.

The transient (commuting) students are considered as a unique population group, using the transient/employee trip generation distribution but the school scenario percentages. In addition to the 757 at Penn State, there are 100 at Luzerne County Community College at the Berwick location and 1,403 at the Nanticoke campus. An average vehicle occupancy of 1.0 is assumed for these commuter students, totaling 2,260 vehicles.

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The total enrollment numbers for the colleges are shown in Table E-2. For clarity, the summary tables, Table 3-7 and Table 3-8, show the students and number of vehicles in which they evacuate in a separate column.

Table 3-4. Summary of Transients and Transient Vehicles I ERPA Transients Transient Vehicles I 1 0 0 2 0 0 3 58 19 4 176 8 5 0 0 6 237 83 7 276 122 8 0 0 9 326 82 10 33 17 11 52 26 12 0 0 13 0 0 14 316 79 15 600 300 16 0 0 17 44 22 18 55 28 19 0 0 20 0 0 21 0 0 22 474 224 23 0 0 24 159 80 25 70 35 26 0 0 27 7638 Susquehanna Steam Electric Station 3-14 KLD Engineering, P.C.

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N NNE 157 0

00- -l - *r-ý~ 0 WNW

=14 W

L- W3 0 WSW I SSW SSE ._sZ W - - - o - - - SSE Transients Miles Subtotal by Ring Cumulative Total 0-1 159 159 1-2 326 485 2-3 0 o . 485 3-4 117 602 W E 4-5 371 973 S-6 152 1,125 6-7 265 1,396 7-8 32 1,422 8-9 259 1,681 9-10 836 2,517 110- EPZ . . 435 . . 2,952 Inset Total: 2,952 0- 2 Miles S Figure 3-6. Transient Population by Sector Susquehanna Steam Electric Station 3-15 KLD Engineering, P.C.

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N NNW NNE 0

- 0~ 0 **

WNW ENE E36--

I.

0~

w E 0 12 67~ 1 I71]

wsw 0 IS ESE 173.ý I 2I36 s 0 Boundary SSW s r N Transient Vehicles Miles 0-1

... 1-2 2.-3 3-4 4-S Subtotal by Ring Cumulative Total

.

63 82 0

. 59 1071

.145 63 145 204 311 W

0821 5-6 .76 387 6_-_ 7 53 .440 17-. 8.. ....... .. .16 . 456 8-9 130 586 9-10 . 372 958 10-EPZ 205 1,163 Inset f Total: 1,163 0 - 2 Miles S Figure 3-7. Transient Vehicles by Sector 3-16 KLD Engineering, P.C.

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3.5 Employees Data collected for the 2008 SSES/Bell bend COLA was reviewed, in 2012, by PPL and by Columbia County and Luzerne County Emergency Management Agencies and was approved for use in this study. These data had been obtained from a variety of sources including internet searches and direct phone calls to major employers.

Employees who work within the EPZ fall into two categories:

• Those who live and work in the EPZ

• Those who live outside of the EPZ and commute to jobs within the EPZ.

Those of the first category are already counted as part of the permanent resident population. To avoid double counting, we focus only on those employees commuting from outside the EPZ who will evacuate along with the permanent resident population.

Detailed data were provided by PPL for the current site employment at SSES, including an accurate estimate of the number of employees who live outside the EPZ. For the other major employers, Census Journey to Work data were used to identify the travel and work patterns within Luzerne and Columbia County.

There are a total of 1,583 employees commuting into the EPZ on a daily basis. These employees use 1,555 vehicles. In Table E-4, the number of Employees (Max Shift) is multiplied by the percent non-EPZ factor to determine the number of employees who are not residents of the EPZ. A vehicle occupancy of 1.02 employees per vehicle obtained from the telephone survey (See Figure F-6) was used to determine the number of evacuating employee vehicles for all major employers.

Table 3-5 presents non-EPZ Resident employee and vehicle estimates by ERPA. Figure 3-8 and Figure 3-9 present these data by sector.

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Table 3-5. Summary of Non-EPZ Resident Employees and Employee Vehicles 0RP Emlye0mlyeVhce 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 424 416 8 0 0 9 0 0 10 409 403 11 165 162 12 0 0 13 0 0 14 0 0 15 210 206 16 0 0 17 0 0 18 0 0 19 0 0 20 0 0 21 375 368 22 0 0 23 0 0 24 0 0 25 0 0 26 0 0 27 0 0 Susquehanna Steam Electric Station 3-18 KLD Engineering, P.C.

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N NNW NNE LIE 0

• 0".

WNW ENE

'

i 0

WI 0

w E U 01 SS 0, ' ESE 0

Boundary

--  ! 0 SSW S LIE N 1424 Employees Miles Subtotal by Ring Cumulative Total 0-1 424 424 1-2 0 424 2-3 0 424 3-4 0 424 W 0 E 4-S 173 597 5-6 71 668 6-7 165 833 7-8 165 998 8-9 0 998 9-10 210 1,208 1.0- EPZ 3751 1,583 inset ,

Total: 1,583 0- 2'Miles S Figure 3-8. Employee Population by Sector Susquehanna Steam Electric Station 3-19 KLD Engineering, P.C.

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N NNW NNE

- - -

7--

~~0 WNW ENE I

0~

W E

]

WSW 0 0,

' ESE 565 %

ss0 Boundary SSW 0 3.

S ELI N E416--

Employee Vehicles Miles Subtotal by Ring Cumulative Total 0-1 416 416 1:2 - 0 416 2-3 0 416 3-4 0 416 W

4-5 171 587 5-6 70 657 6-7 162 ........ 819

.7-8 .. . 162 981 8-9 0 981 9-10 206 1,187 10 - EPZ 368 1,555 Inset -.

Total: 1,555 0 - 2 Miles S Figure 3-9. Employee Vehicles by Sector Susquehanna Steam Electric Station 3-20 KLD Engineering, P.C.

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3.6 Medical Facilities There are 11 medical facilities in the EPZ. Table E-3 in Appendix E summarizes the data gathered. Section 8 details the evacuation of medical facilities and their patients. The number and type of evacuating vehicles that need to be provided depend on the patients' state of health. It is estimated that buses can transport up to 30 people; wheelchair vans, up to 4 people; wheelchair buses up to 15 people; and ambulances, up to 2 people.

3.7 Total Demand in Addition to Permanent Population Vehicles will be traveling through the EPZ (external-external trips) at the time of an accident.

After the Advisory to Evacuate is announced, these through-travelers will also evacuate. These through vehicles are assumed to travel on the major routes traversing the EPZ 80 and 1-81.

It is assumed that this traffic will continue to enter the EPZ during the first 90 minutes following the Advisory to Evacuate.

Average Annual Daily Traffic (AADT) data was obtained from Federal Highway Administration to estimate the number of vehicles per hour on the aforementioned routes. The AADT was multiplied by the K-Factor, which is the proportion of the AADT on a roadway segment or link during the design hour, resulting in the design hour volume (DHV). The design hour is usually the 3 0 th highest hourly traffic volume of the year, measured in vehicles per hour (vph). The DHV is then multiplied by the D-Factor, which is the proportion of the DHV occurring in the peak direction of travel (also known as the directional split). The resulting values are the directional design hourly volumes (DDHV), and are presented in Table 3-6, for the routes considered. The DDHV is then multiplied by 1.5 hours5.787037e-5 days <br />0.00139 hours <br />8.267196e-6 weeks <br />1.9025e-6 months <br /> (access control points - ACP - are assumed to be activated at 90 minutes after the advisory to evacuate) to estimate the total number of external vehicles loaded on the analysis network. As indicated, there are 9,994 vehicles entering the EPZ as external-external trips prior to the activation of the ACP and the diversion of this traffic. This number is reduced by 60% for evening scenarios (Scenarios 5 and

12) as discussed in Section 6.

3.8 Special Event One special event (Scenario 13) is considered for the ETE study - refueling of SSES. Data was provided by PPL on the approximate number of additional workers on site.

The refueling outages normally occur between March 1st and May 1st of every spring and last for approximately 35 to 45 days. There are approximately 1,200 supplemental workers, split between 2 shifts (2/3 day shift vs. 1/3 night shift). Considering the maximum shift, up to 800 supplemental workers could be on site which equates to 784 additional vehicles (800 employees/1.02 employees per vehicle).

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Table 3-6. SSES EPZ External Traffic 8642 765 1-80 WB 25,138 0.107 0.5 1,345 2,018 8682 682 1-80 EB 25,138 0.107 0.5 1,345 2,018 8395 395 1-81 NB 37,114 0.107 0.5 1,986 2,979 8755 755 1-81 SB 37,114 0.107 0.5 1,986 2,979 1Highway Performance Monitoring System (HPMS), Federal Highway Administration (FHWA), Washington, D.C., 2012 2HCM 2010 Susquehanna Steam Electric Station 3-22 KILD Engineering, P.C.

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3.9 Summary of Demand A summary of population and vehicle demand is provided in Table 3-7 and Table 3-8, respectively. This summary includes all population groups described in this section. Additional population groups - transit-dependent, special facility and school population - are described in greater detail in Section 8. A total of 192,860 people and 101,174 vehicles are considered in this study.

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Table 3-7. Summary of Population Demand 1 Z,4U4 1UU U U U U U U U 1,114 2 2,107 120 0 0 0 284 0 0 0 2,511 3 2,041 91 58 0 0 743 0 0 0 2,933 4 2,241 150 176 0 70 308 0 0 0 2,945 5 225 0 0 0 0 0 0 0 0 225 6 766 22 237 0 0 0 0 0 0 1,025 7 4,287 230 276 424 0 1,277 0 0 0 6,494 8 838 60 0 0 0 0 0 0 0 898 9 1,453 83 326 0 0 0 0 0 0 1,862 10 10,387 302 33 409 268 1,689 100 0 0 13,188 11 646 19 52 165 0 0 0 0 0 882 12 1,569 88 0 0 0 285 0 0 0 1,942 13 1,166 40 0 0 0 0 0 0 0 1,206 14 1,196 50 316 0 18 0 0 0 0 1,580 15 4,213 90 600 210 0 1,109 1,232 0 0 7,454 16 1,912 112 0 0 0 0 0 0 0 2,024 17 2,188 100 44 0 0 0 0 0 0 2,332 18 1,115 50 55 0 0 0 0 0 0 1,220 19 679 36 0 0 0 0 0 0 0 715 20 5,377 249 0 0 1,080 322 0 0 0 7,028 21 10,462 3,500 0 375 86 2,214 1,403 0 0 18,040 22 5,826 269 474 0 184 1,331 0 0 0 8,084 23 652 19 0 0 0 106 0 0 0 777 24 2,324 68 159 0 110 0 0 0 0 2,661 25 973 28 70 0 0 0 0 0 0 1,071 26 1,520 44 0 0 0 0 0 0 0 1,564 27 3,088 90 76 0 1 0 0 1 0 0 0 3,254 96,031 0 96,821 0 0 00 7e0e0 6 Shadow 0 NOTE: Shadow Population has been reduced to 20% (see Figure 2-1). Special Facilities include both medical facilities and correctional facilities.

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Table 3-8. Summary of Vehicle Demand 1 L,UbU 4 U U U U U U U iUb4 2 1,090 6 0 0 0 10 0 0 0 1,106 3 1,056 4 19 0 0 32 0 0 0 1,111 4 1,158 3 8 0 22 10 0 0 0 1,201 5 118 3 0 0 0 0 0 0 0 121 6 403 2 83 0 0 0 0 0 0 488 7 2,220 10 122 416 0 40 0 0 0 2,808 8 437 2 0 0 0 0 0 0 0 439 9 755 6 82 0 0 0 0 0 0 843 10 5,357 20 17 403 23 72 100 0 0 5,992 11 335 2 26 162 0 0 0 0 0 525 12 810 4 0 0 0 8 0 0 0 822 13 607 2 0 0 0 0 0 0 0 609 14 621 2 79 0 3 0 0 0 0 705 15 2,180 4 300 206 0 32 767 0 0 3,489 16 984 6 0 0 0 0 0 0 0 990 17 1,133 4 22 0 0 0 0 0 0 1,159 18 575 2 28 0 0 0 0 0 0 605 19 350 2 0 0 0 0 0 0 0 352 20 2,780 10 0 0 71 10 0 0 0 2,871 21 5,400 90 0 368 23 80 1403 0 0 7,364 22 3,006 12 224 0 43 46 0 0 0 3,331 23 336 2 0 0 0 4 0 0 0 342 24 1,202 4 80 0 19 0 0 0 0 1,305 25 508 2 35 0 0 0 0 0 0 545 26 790 2 0 0 0 0 0 0 0 792 27 1,604 6 38 0 0 0 0 0 0 1,648 Shadow 0 0 0 0 0 24 0 48,539 9,994 58,557 1,4011c M -

B uses represented as two passenger vehicles. Refer Lo Sectlon 08 r adUilIOnal in IrmaLoln.

- --

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4 ESTIMATION OF HIGHWAY CAPACITY The ability of the road network to service vehicle demand is a major factor in determining how rapidly an evacuation can be completed. The capacity of a road is defined as the maximum hourly rate at which persons or vehicles can reasonably be expected to traverse a point or uniform section of a lane of roadway during a given time period under prevailing roadway, traffic and control conditions, as stated in the 2010 Highway Capacity Manual (HCM 2010).

In discussing capacity, different operating conditions have been assigned alphabetical designations, A through F, to reflect the range of traffic operational characteristics. These designations have been termed "Levels of Service" (LOS). For example, LOS A connotes free-flow and high-speed operating conditions; LOS F represents a forced flow condition. LOS E describes traffic operating at or near capacity.

Another concept, closely associated with capacity, is "Service Volume" (SV). Service volume is defined as "The maximum hourly rate at which vehicles, bicycles or persons reasonably can be expected to traverse a point or uniform section of a roadway during an hour under specific assumed conditions while maintaining a designated level of service." This definition is similar to that for capacity. The major distinction is that values of SV vary from one LOS to another, while capacity is the service volume at the upper bound of LOS E, only.

This distinction is illustrated in Exhibit 11-17 of the HCM 2010. As indicated there, the SV varies with Free Flow Speed (FFS), and LOS. The SV is calculated by the DYNEV II simulation model, based on the specified link attributes, FFS, capacity, control device and traffic demand.

Other factors also influence capacity. These include, but are not limited to:

• Lane width

• Shoulder width

• Pavement condition

• Horizontal and vertical alignment (curvature and grade)

• Percent truck traffic

" Control device (and timing, if it is a signal)

• Weather conditions (rain, snow, fog, wind speed, ice)

These factors are considered during the road survey and in the capacity estimation process; some factors have greater influence on capacity than others. For example, lane and shoulder width have only a limited influence on Base Free Flow Speed (BFFS') according to Exhibit 15-7 of the HCM. Consequently, lane and shoulder widths at the narrowest points were observed during the road survey and these observations were recorded, but no detailed measurements of lane or shoulder width were taken. Horizontal and vertical alignment can influence both FFS and capacity. The estimated FFS were measured using the survey vehicle's speedometer and observing local traffic, under free flow conditions. Capacity is estimated from the procedures of 1 A very rough estimate of BFFS might be taken as the posted speed limit plus 10 mph (HCM 2010 Page 15-15)

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the 2010 HCM. For example, HCM Exhibit 7-1(b) shows the sensitivity of Service Volume at the upper bound of LOS D to grade (capacity is the Service Volume at the upper bound of LOS E).

As discussed in Section 2.3, it is necessary to adjust capacity figures to represent the prevailing conditions during inclement weather. Based on limited empirical data, weather conditions such as rain reduce the values of free speed and of highway capacity by approximately 10 percent. Over the last decade new studies have been made on the effects of rain on traffic capacity. These studies indicate a range of effects between 5 and 20 percent depending on wind speed and precipitation rates. As indicated in Section 2.3, we employ a reduction in free speed and in highway capacity of 10 percent and 20 percent for rain and snow, respectively.

Since congestion arising from evacuation may be significant, estimates of roadway capacity must be determined with great care. Because of its importance, a brief discussion of the major factors that influence highway capacity is presented in this section.

Rural highways generally consist of: (1) one or more uniform sections with limited access (driveways, parking areas) characterized by "uninterrupted" flow; and (2) approaches to at-grade intersections where flow can be "interrupted" by a control device or by turning or crossing traffic at the intersection. Due to these differences, separate estimates of capacity must be made for each section. Often, the approach to the intersection is widened by the addition of one or more lanes (turn pockets or turn bays), to compensate for the lower capacity of the approach due to the factors there that can interrupt the flow of traffic. These additional lanes are recorded during the field survey and later entered as input to the DYNEV II system.

4.1 Capacity Estimations on Approaches to Intersections At-grade intersections are apt to become the first bottleneck locations under local heavy traffic volume conditions. This characteristic reflects the need to allocate access time to the respective competing traffic streams by exerting some form of control. During evacuation, control at critical intersections will often be provided by traffic control personnel assigned for that purpose, whose directions may supersede traffic control devices. The existing traffic management plans documented in the county emergency plans are extensive and were adopted without change.

The per-lane capacity of an approach to a signalized intersection can be expressed (simplistically) in the following form:

3600 G-L ,m (3600 Qcap,m = (3MO) X (G L) = (300 where:

Qcap,m - Capacity of a single lane of traffic on an approach, which executes Susquehanna Steam Electric Station 4-2 KLD Engineering, P.C.

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movement, m, upon entering the intersection; vehicles per hour (vph) hm Mean queue discharge headway of vehicles on this lane that are executing movement, m; seconds per vehicle G Mean duration of GREEN time servicing vehicles that are executing movement, m, for each signal cycle; seconds L = Mean "lost time" for each signal phase servicing movement, m; seconds C - Duration of each signal cycle; seconds Pm = Proportion of GREEN time allocated for vehicles executing movement, m, from this lane. This value is specified as part of the control treatment.

m = The movement executed by vehicles after they enter the intersection: through, left-turn, right-turn, and diagonal.

The turn-movement-specific mean discharge headway hm, depends in a complex way upon many factors: roadway geometrics, turn percentages, the extent of conflicting traffic streams, the control treatment, and others. A primary factor is the value of "saturation queue discharge headway", hsat, which applies to through vehicles that are not impeded by°other conflicting traffic streams. This value, itself, depends upon many factors including motorist behavior.

Formally, we can write, hm =fm(hsat,F, F2 ... )

where:

hsat " = Saturation discharge headway for through vehicles; seconds per vehicle F1,F2 = The various known factors influencing hm fm() Complex function relating hm to the known (or estimated) values of hsat, F1, F2 ,

The estimation of hm for specified values of hsat, F1, F2 , ... is undertaken within the DYNEV II simulation model by a mathematical model 2. The resulting values for hm alwayssatisfy the condition:

hm Ž_ hsat 2Lieberman, E., "Determining Lateral Deployment of Traffic on an Approach to an Intersection", McShane, W. &

Lieberman, E., "Service Rates of Mixed Traffic on the far Left Lane of an Approach". Both papers appear in Transportation Research Record 772, 1980. Lieberman, E., Xin, W., "Macroscopic Traffic Modeling For Large-Scale Evacuation Planning", presented at the TRB 2012 Annual Meeting, January 22-26, 2012 Susquehanna Steam Electric Station 4-3 KLD Engineering, P.C.

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That is, the turn-movement-specific discharge headways are always greater than, or equal to the saturation discharge headway for through vehicles. These headways (or its inverse equivalent, "saturation flow rate"), may be determined by observation or using the procedures of the HCM 2010.

The above discussion is necessarily brief given the scope of this ETE report and the complexity of the subject of intersection capacity. In fact, Chapters 18, 19 and 20 in the HCM 2010 address this topic. The factors, F1, F2,..., influencing saturation flow rate are identified in equation (18-5) of the HCM 2010.

The traffic signals within the EPZ and Shadow Region are modeled using representative phasing plans and phase durations obtained as part of the field data collection. Traffic responsive signal installations allow the proportion of green time allocated (P1m) for each approach to each intersection to be determined by the expected traffic volumes on each approach during evacuation circumstances. The amount of green time (G) allocated is subject to maximum and minimum phase duration constraints; 2 seconds of yellow time are indicated for each signal phase and I second of all-red time is assigned between signal phases, typically. If a signal is pre-timed, the yellow and all-red times observed during the road survey are used. A lost time (L)of 2.0 seconds is used for each signal phase in the analysis.

4.2 Capacity Estimation along Sections of Highway The capacity of highway sections -- as distinct from approaches to intersections -- is a function of roadway geometrics, traffic composition (e.g. percent heavy trucks and buses in the traffic stream) and, of course, motorist behavior. There is a fundamental relationship which relates service volume (i.e. the number of vehicles serviced within a uniform highway section in a given time period) to traffic density. The top curve in Figure 4-1 illustrates this relationship.

As indicated, there are two flow regimes: (1) Free Flow (left side of curve); and (2) Forced Flow (right side). In the Free Flow regime, the traffic demand is fully serviced; the service volume increases as demand volume and density increase, until the service volume attains its maximum value, which is the capacity of the highway section. As traffic demand and the resulting highway density increase beyond this "critical" value, the rate at which traffic can be serviced (i.e. the service volume) can actually decline below capacity ("capacity drop"). Therefore, in order to realistically represent traffic performance during congested conditions (i.e. when demand exceeds capacity), it is necessary to estimate the service volume, VF, under congested conditions.

The value of VF can be expressed as:

VF = R x Capacity where:

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We have employed a value of R=0.90. The advisability of such a capacity reduction factor is based upon empirical studies that identified a fall-off in the service flow rate when congestion occurs at "bottlenecks" or "choke points" on a freeway system. Zhang and Levinson 3 describe a research program that collected data from a computer-based surveillance system (loop detectors) installed on the Interstate Highway System, at 27 active bottlenecks in the twin cities metro area in Minnesota over a 7-week period. When flow breakdown occurs, queues are formed which discharge at lower flow rates than the maximum capacity prior to observed breakdown. These queue discharge flow (QDF) rates vary from one location to the next and also vary by day of week and time of day based upon local circumstances. The cited reference presents a mean QDF of 2,016 passenger cars per hour per lane (pcphpl). This figure compares with the nominal capacity estimate of 2,250 pcphpl estimated for the ETE and indicated in Appendix Kfor freeway links. The ratio of these two numbers is 0.896 which translates into a capacity reduction factor of 0.90.

Since the principal objective of evacuation time estimate analyses is to develop a "realistic" estimate of evacuation times, use of the representative value for this capacity reduction factor (R=0.90) is justified. This factor is applied only when flow breaks down, as determined by the simulation model.

Rural roads, like freeways, are classified as "uninterrupted flow" facilities. (This is in contrast with urban street systems which have closely spaced signalized intersections and are classified as "interrupted flow" facilities.) As such, traffic flow along rural roads is subject to the same effects as freeways in the event traffic demand exceeds the nominal capacity, resulting in queuing and lower QDF rates. As a practical matter, rural roads rarely break down at locations away from intersections. Any breakdowns on rural roads are generally experienced at intersections where other model logic applies, or at lane drops which reduce capacity there.

Therefore, the application of a factor of 0.90 is appropriate on rural roads, but rarely, if ever, activated.

The estimated value of capacity is based primarily upon the type of facility and on roadway geometrics. Sections of roadway with adverse geometrics are characterized by lower free-flow speeds and lane capacity. Exhibit 15-30 in the Highway Capacity Manual was referenced to estimate saturation flow rates. The impact of narrow lanes and shoulders on free-flow speed and on capacity is not material, particularly when flow is predominantly in one direction as is the case during an evacuation.

The procedure used here was to estimate "section" capacity, VE, based on observations made traveling over each section of the evacuation network, based on the posted speed limits and travel behavior of other motorists and by reference to the 2010 HCM. The DYNEV II simulation model determines for each highway section, represented as a network link, whether its capacity would be limited by the "section-specific" service volume, VE, or by the intersection-specific capacity. For each link, the model selects the lower value of capacity.

3Lei Zhang and David Levinson, "Some Properties of Flows at Freeway Bottlenecks," Transportation Research Record 1883, 2004.

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4.3 Application to the SSES Study Area As part of the development of the link-node analysis network for the study area, an estimate of roadway capacity is required. The source material for the capacity estimates presented herein is contained in:

2010 Highway Capacity Manual (HCM)

Transportation Research Board National Research Council Washington, D.C.

The highway system in the study area consists primarily of three categories of roads and, of course, intersections:

" Two-Lane roads: Local, State

" Multi-Lane Highways (at-grade)

" Freeways Each of these classifications will be discussed.

4.3.1 Two-Lane Roads Ref: HCM Chapter 15 Two lane roads comprise the majority of highways within the EPZ. The per-lane capacity of a two-lane highway is estimated at 1700 passenger cars per hour (pc/h). This estimate is essentially independent of the directional distribution of traffic volume except that, for extended distances, the two-way capacity will not exceed 3200 pc/h. The HCM procedures then estimate Level of Service (LOS) and Average Travel Speed. The DYNEV II simulation model accepts the specified value of capacity as input and computes average speed based on the time-varying demand: capacity relations.

Based on the field survey and on expected traffic operations associated with evacuation scenarios:

" Most sections of two-lane roads within the EPZ are classified as "Class I", with "level terrain"; some are "rolling terrain".

• "Class II" highways are mostly those within urban and suburban centers.

4.3.2 Multi-Lane Highway Ref: HCM Chapter 14 Exhibit 14-2 of the HCM 2010 presents a set of curves that indicate a per-lane capacity ranging from approximately 1900 to 2200 pc/h, for free-speeds of 45 to 60 mph, respectively. Based on observation, the multi-lane highways outside of urban areas within the EPZ service traffic with free-speeds in this range. The actual time-varying speeds computed by the simulation model reflect the demand: capacity relationship and the impact of control at intersections. A Susquehanna Steam Electric Station 4-6 KLD Engineering, P.C.

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conservative estimate of per-lane capacity of 1900 pc/h is adopted for this study for multi-lane highways outside of urban areas, as shown in Appendix K.

4.3.3 Freeways Ref: HCM Chapters 10, 11, 12, 13 Chapter 10 of the HCM 2010 describes a procedure for integrating the results obtained in Chapters 11, 12 and 13, which compute capacity and LOS for freeway components. Chapter 10 also presents a discussion of simulation models. The DYNEV II simulation model automatically performs this integration process.

Chapter 11 of the HCM 2010 presents procedures for estimating capacity and LOS for "Basic Freeway Segments". Exhibit 11-17 of the HCM 2010 presents capacity vs. free speed estimates, which are provided below.

Free Speed (mph): 55 60 65 70+

Per-Lane Capacity (pc/h): -2250 2300 2350 2400 The inputs to the simulation model are highway geometrics, free-speeds and capacity based on field observations. The simulation logic calculates actual time-varying speeds based on demand:

capacity relationships. A conservative estimate of per-lane capacity of 2250 pc/h is adopted for this study for freeways, as shown in Appendix K.

Chapter 12 of the HCM 2010 presents procedures for estimating capacity, speed, density and LOS for freeway weaving sections. The simulation model contains logic that relates speed to demand volume: capacity -ratio. The value of capacity obtained from the computational procedures detailed in Chapter 12 depends on the "Type" and geometrics of the weaving segment and on the "Volume Ratio" (ratio of weaving volume to total volume).

Chapter 13 of the HCM 2010 presents procedures for estimating capacities of ramps and of "merge" areas. There are three significant factors to the determination of capacity of a ramp-freeway junction: The capacity of the freeway immediately downstream of an on-ramp or immediately upstream of an off-ramp; the capacity of the ramp roadway; and the maximum flow rate entering the ramp influence area. In most cases, the freeway capacity is the controlling factor. Values of this merge area capacity are presented in Exhibit 13-8 of the HCM 2010, and depend on the number of freeway lanes and on the freeway free speed. Ramp capacity is presented in Exhibit 13-10 and is a function of the ramp free flow speed. The DYNEV II simulation model logic simulates the merging operations of the ramp and freeway traffic in accord with the procedures in Chapter 13 of the HCM 2010. If congestion results from an excess of demand relative to capacity, then the model allocates service appropriately to the two entering traffic streams and produces LOS F conditions (The HCM does not address LOS F explicitly).

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4.3.4 Intersections Ref: HCM Chapters 18, 19, 20, 21 Procedures for estimating capacity and LOS for approaches to intersections are presented in Chapter 18 (signalized intersections), Chapters 19, 20 (un-signalized intersections) and Chapter 21 (roundabouts). The complexity of these computations is indicated by the aggregate length of these chapters. The DYNEV II simulation logic is likewise complex.

The simulation model explicitly models intersections: Stop/yield controlled intersections (both 2-way and all-way) and traffic signal controlled intersections. Where intersections are controlled by fixed time controllers, traffic signal timings are set to reflect average (non-evacuation) traffic conditions. Actuated traffic signal settings respond to the time-varying demands of evacuation traffic to adjust the relative capacities of the competing intersection approaches.

The model is also capable of modeling the presence of manned traffic control. At specific locations where it is advisable or where existing plans call for overriding existing traffic control to implement manned control, the model will use actuated signal timings that reflect the presence of traffic guides. At locations where a special traffic control strategy (continuous left-turns, contra-flow lanes) is used, the strategy is modeled explicitly. Where applicable, the location and type of traffic control for nodes in the evacuation network are noted in Appendix K. The characteristics of the ten highest volume signalized intersections are detailed in Appendix J.

4.4 Simulation and Capacity Estimation Chapter 6 of the HCM is entitled, "HCM and Alternative Analysis Tools." The chapter discusses the use of alternative tools such as simulation modeling to evaluate the operational performance of highway networks. Among the reasons cited in Chapter 6 to consider using simulation as an alternative analysis tool is:

"The system under study involves a group of different facilities or travel modes with mutual interactions invoking several proceduralchapters of the HCM. Alternative tools are able to analyze thesefacilities as a single system."

This statement succinctly describes the analyses required to determine traffic operations across an area encompassing an EPZ operating under evacuation conditions. The model utilized for this study, DYNEV II, is further described in Appendix C. It is essential to recognize that simulation models do not replicate the methodology and procedures of the HCM - they replace these procedures by describing the complex interactions of traffic flow and computing Measures of Effectiveness (MOE) detailing the operational performance of traffic over time and by location. The DYNEV II simulation model includes some HCM 2010 procedures only for the purpose of estimating capacity.

All simulation models must be calibrated properly with field observations that quantify the performance parameters applicable to the analysis network. Two of the most important of Susquehanna Steam Electric Station 4-8 KLD Engineering, P.C.

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these are: (1) Free flow speed (FFS); and (2) saturation headway, hsat. The first of these is estimated by direct observation during the road survey; the second is estimated using the concepts of the HCM 2010, as described earlier. These parameters are listed in Appendix K,for each network link.

Volume, vph Qmax -------

R Qmax-------

" .. QS Density, vpm Speed, mph Vf 1 R vj

-* Density, vpm kf k 0 pt ksk' Figure 4-1. Fundamental Diagrams Susquehanna Steam Electric Station 4-9 KLD Engineering, P.C.

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5 ESTIMATION OF TRIP GENERATION TIME Federal Government guidelines (see NUREG CR-7002) specify that the planner estimate the distributions of elapsed times associated with mobilization activities undertaken by the public to prepare for the evacuation trip. The elapsed time associated with each activity is represented as a statistical distribution reflecting differences between members of the public.

The quantification of these activity-based distributions relies largely on the results of the telephone survey. We define the sum of these distributions of elapsed times as the Trip Generation Time Distribution.

5.1 Background In general, an accident at a nuclear power plant is characterized by the following Emergency Action Levels (see Appendix I of NUREG 0654 for details):

1. Unusual Event

2. Alert

3. Site Area Emergency

4. General Emergency At each level, the Federal guidelines specify a set of Actions to be undertaken by the Licensee, and by State and Local offsite authorities. As a Planning Basis we will adopt a conservative posture, in accordance with Section 1.2 of NUREG/CR-7002, that a rapidly escalating accident will be considered in calculating the Trip Generation Time. We will assume:

1. The Advisory to Evacuate will be announced coincident with the siren notification.

2. Mobilization of the general population will commence within 15 minutes after the siren notification.

3. ETE are measured relative to the Advisory to Evacuate.

We emphasize that the adoption of this planning basis is not a representation that these events will occur within the indicated time frame. Rather, these assumptions are necessary in order to:

1. Establish a temporal framework for estimating the Trip Generation distribution in the format recommended in Section 2.13 of NUREG/CR-6863.

2. Identify temporal points of reference that uniquely define "Clear Time" and ETE.

It is likely that a longer time will elapse between the various classes of an emergency.

For example, suppose one hour elapses from the siren alert to the Advisory to Evacuate. In this case, it is reasonable to expect some degree of spontaneous evacuation by the public during this one-hour period. As a result, the population within the EPZ will be lower when the Advisory to Evacuate is announced, than at the time of the siren alert. In addition, many will engage in preparation activities to evacuate, in anticipation that an Advisory will be broadcast.

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remaining to evacuate the EPZ after the Advisory to Evacuate, will both be somewhat less than the estimates presented in this report. Consequently, the ETE presented in this report are higher than the actual evacuation time, if this hypothetical situation were to take place.

The notification process consists of two events:

1. Transmitting information using the alert notification systems available within the EPZ (e.g. sirens, tone alerts, EAS broadcasts, loud speakers).

2. Receiving and correctly interpreting the information that is transmitted.

The population within the EPZ is dispersed over an area of approximately 377 square miles and is engaged in a wide variety of activities. It must be anticipated that some time will elapse between the transmission and receipt of the information advising the public of an accident.

The amount of elapsed time will vary from one individual to the next depending on where that person is, what that person is doing, and related factors. Furthermore, some persons who will be directly involved with the evacuation process may be outside the EPZ at the time the emergency is declared. These people may be commuters, shoppers and other travelers who reside within the EPZ and who will return to join the other household members upon receiving notification of an emergency.

As indicated in Section 2.13 of NUREG/CR-6863, the estimated elapsed times for the receipt of notification can be expressed as a distribution reflecting the different notification times for different people within, and outside, the EPZ. By using time distributions, it is also possible to distinguish between different population groups and different day-of-week and time-of-day scenarios, so that accurate ETE may be computed.

For example, people at home or at work within the EPZ will be notified by siren, and/or tone alert and/or radio (if available). Those well outside the EPZ will be notified by telephone, radio, TV and word-of-mouth, with potentially longer time lags. Furthermore, the spatial distribution of the EPZ population will differ with time of day - families will be united in the evenings, but dispersed during the day. In this respect, weekends will differ from weekdays.

As indicated in Section 4.1 of NUREG/CR-7002, the information required to compute trip generation times is typically obtained from a telephone survey of EPZ residents. Such a survey was conducted in support of this ETE study. Appendix F presents the survey sampling plan, survey instrument, and raw survey results. It is important to note that the shape and duration of the evacuation trip mobilization distribution is important at sites where traffic congestion is not expected to cause the evacuation time estimate to extend in time well beyond the trip generation period. The remaining discussion will focus on the application of the trip generation data obtained from the telephone survey to the development of the ETE documented in this report.

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5.2 Fundamental Considerations The environment leading up to the time that people begin their evacuation trips consists of a sequence of events and activities. Each event (other than the first) occurs at an instant in time and is the outcome of an activity.

Activities are undertaken over a period of time. Activities may be in "series" (i.e. to undertake an activity implies the completion of all preceding events) or may be in parallel (two or more activities may take place over the same period of time). Activities conducted in series are functionally dependent on the completion of prior activities; activities conducted in parallel are functionally independent of one another. The relevant events associated with the public's preparation for evacuation are:

Event Number Event Description 1 Notification 2 Awareness of Situation 3 Depart Work 4 Arrive Home 5 Depart on Evacuation Trip Associated with each sequence of events are one or more activities, as outlined below:

Table 5-1. Event Sequence for Evacuation Activities I 1-*2 I Receive Notification 1 J I

2- 3 Prepare to Leave Work 2 2,3 -*4 Travel Home 3 2,4 -5 Prepare to Leave to Evacuate 4 N/A Snow Clearance 5 These relationships are shown graphically in Figure 5-1.

• An Event is a 'state' that exists at a point in time (e.g., depart work, arrive home) a An Activity is a 'process' that takes place over some elapsed time (e.g., prepare to leave work, travel home)

As such, a completed Activity changes the 'state' of an individual (e.g. the activity, 'travel home' changes the state from 'depart work' to 'arrive home'). Therefore, an Activity can be described as an 'Event Sequence'; the elapsed times to perform an event sequence vary from one person to the next and are described as statistical distributions on the following pages.

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An employee who lives outside the EPZ will follow sequence (c) of Figure 5-1. A household within the EPZ that has one or more commuters at work, and will await their return before beginning the evacuation trip will follow the first sequence of Figure 5-1(a). A household within the EPZ that has no commuters at work, or that will not await the return of any commuters, will follow the second sequence of Figure 5-1(a), regardless of day of week or time of day.

Households with no commuters on weekends or in the evening/night-time, will follow the applicable sequence in Figure 5-1(b). Transients will always follow one of the sequences of Figure 5-1(b). Some transients away from their residence could elect to evacuate immediately without returning to the residence, as indicated in the second sequence.

It is seen from Figure 5-1, that the Trip Generation time (i.e. the total elapsed time from Event 1 to Event 5) depends on the scenario and will vary from one household to the next.

Furthermore, Event 5 depends, in a complicated way, on the time distributions of all activities preceding that event. That is, to estimate the time distribution of Event 5, we must obtain estimates of the time distributions of all preceding events. For this study, we adopt the conservative posture that all activities will occur in sequence.

In some cases, assuming certain events occur strictly sequential (for instance, commuter returning home before beginning preparation to leave, or removing snow only after the preparation to leave) can result in rather conservative (that is, longer) estimates of mobilization times. It is reasonable to expect that at least some parts of these events will overlap for many households, but that assumption is not made in this study.

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1 2 3 4 5 As An Residents Households wait W -W for Commuters 1

Households without 1 2 5 Commuters and Residents households who do not wait for Commuters Residents, Transients 1 2 4 5 Return to residence, away from then evacuate Residence Residents, 1 2 5 Residents at home; Transients at transients evacuate directly Residence 1 2 3,5 ACTIVITIES EVENTS 1 .* 2 Receive Notification 1. Notification 2 - 3 Prepare to Leave Work 2. Aware of situation 2, 3 __, 4 Travel Home 3. Depart work 2, 4 .-

• 5 Prepare to Leave to Evacuate 4. Arrive home

5. Depart on evacuation trip Ad Activities Consume Time 0 1 Applies for evening and weekends also if commuters are at work.

2 Applies throughout the year for transients.

Figure 5-1. Events and Activities Preceding the Evacuation Trip KLD Engineering, P.C.

Susquehanna Steam Electric Station 5-S 5-5 KLD Engineering, P.C.

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5.3 Estimated Time Distributions of Activities Preceding Event 5 The time distribution of an event is obtained by "summing" the time distributions of all prior contributing activities. (This "summing" process is quite different than an algebraic sum since it is performed on distributions - not scalar numbers).

Time Distribution No. 1, Notification Process: Activity 1 -- 2 It is assumed (based on the presence of sirens within the EPZ) that 87 percent of those within the EPZ will be aware of the accident within 30 minutes with the remainder notified within the following 15 minutes. The notification distribution is given below:

Table 5-2. Time Distribution for Notifying the Public Elapsed Tim Pecnto 0 0%

5 7%

10 13%

15 27%

20 47%

25 66%

30 87%

35 92%

40 97%

45 100%

Susquehanna Steam Electric Station 5-6 KLD Engineering, P.C.

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Distribution No. 2, Prepare to Leave Work: Activity 2 --. 3 It is reasonable to expect that the vast majority of business enterprises within the EPZ will elect to shut down following notification and most employees would leave work quickly. Commuters, who work outside the EPZ could, in all probability, also leave quickly since facilities outside the EPZ would remain open and other personnel would remain. Personnel or farmers responsible for equipment/livestock would require additional time to secure their facility. The distribution of Activity 2 -> 3 shown in Table 5-3 reflects data obtained by the telephone survey. This distribution is plotted in Figure 5-2.

Table 5-3. Time Distribution for Employees to Prepare to Leave Work Cuuatv Cumu0%l0tiv88 5 46% 45 91%

10 60% 50 92%

15 67% 55 92%

20 71% 60 97%

25 72% 75 99%

30 84% 90 99%

35 87% 105 100%

NOTE: The survey data was normalized to distribute the "Don't know" response. That is, the sample was reduced in size to include only those households who responded to this question. The underlying assumption is that the distribution of this activity for the "Don't know" responders, if the event takes place, would be the same as those responders who provided estimates.

Susquehanna Steam Electric Station 5-7 KLD Engineering, P.C.

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Distribution No. 3, Travel Home: Activity 3 -+ 4 These data are provided directly by those households which responded to the telephone survey. This distribution is plotted in Figure 5-2 and listed in Table 5-4.

Table 5-4. Time Distribution for Commuters to Travel Home 0 0% 35 88%

5 15% 40 92%

10 31% 45 96%

15 46% 50 97%

20 62% 55 97%

25 71% 60 100%

30 84%

NOTE: The survey data was normalized to distribute the "Don't know" response Susquehanna Steam Electric Station 5-8 KLD Engineering, P.C.

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Distribution No. 4, Prepare to Leave Home: Activity 2, 4 -> 5 These data are provided directly by those households which responded to the telephone survey. This distribution is plotted in Figure 5-2 and listed in Table 5-5.

Table 5-5. Time Distribution for Population to Prepare to Evacuate fl hI.¶J.E~ir~~~CuImult~'ive 1 0 0%

15 26%

30 61%

45 72%

60 88%

75 95%

90 96%

105 96%

120 99%

135 100%

NOTE: The survey data was normalized to distribute the "Don't know" response KLD Engineering, P.C.

Electric Station Steam Electric Susquehanna Steam Station 5-9 KLD Engineering, P.C.

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Distribution No. 5, Snow Clearance Time Distribution Inclement weather scenarios involving snowfall must address the time lags associated with snow clearance. It is assumed that snow equipment is mobilized and deployed during the snowfall to maintain passable roads. The general consensus is that the snow-plowing efforts are generally successful for all but the most extreme blizzards when the rate of snow accumulation exceeds that of snow clearance over a period of many hours.

Consequently, it is reasonable to assume that the highway system will remain passable - albeit at a lower capacity - under the vast majority of snow conditions. Nevertheless, for the vehicles to gain access to the highway system, it may be necessary for driveways and employee parking lots to be cleared to the extent needed to permit vehicles to gain access to the roadways.

These clearance activities take time; this time must be incorporated into the trip generation time distributions. These data are provided by those households which responded to the telephone survey. This distribution is plotted in Figure 5-2 and listed in Table 5-6.

Table 5-6. Time Distribution for Population to Clear 6"-8" of Snow 0 0%

15 40%

30 73%

45 82%

60 90%

75 94%

90 95%

105 97%

120 99%

135 100%

NOTE: The survey data was normalized to distribute the "Don't know" response 0

Susquehanna Steam Electric Station 5-10 KLD Engineering, P.C.

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Mobilization Activities 100%

" 80%

t o

4.6 N

0 2 60%

DO

- Notification

- Prepare to Leave Work E

U0 - Travel Home

. 40% - Prepare Home M

0. -Time to Clear Snow a.0 2-W C

2 20%

W, CL 0%

0 15 30 45 60 75 90 105 120 135 Elapsed Time from Start of Mobilization Activity (min)

Figure 5-2. Evacuation Mobilization Activities Susquehanna Steam Electric Station 5-11 KLD Engineering, P.C.

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5.4 Calculation of Trip Generation Time Distribution The time distributions for each of the mobilization activities presented herein must be combined to form the appropriate Trip Generation Distributions. As discussed above, this study assumes that the stated events take place in sequence such that all preceding events must be completed before the current event can occur. For example, if a household awaits the return of a commuter, the work-to-home trip (Activity 3 -> 4) must precede Activity 4 -> 5.

To calculate the time distribution of an event that is dependent on two sequential activities, it is necessary to "sum" the distributions associated with these prior activities. The distribution summing algorithm is applied repeatedly as shown to form the required distribution. As an outcome of this procedure, new time distributions are formed; we assign "letter" designations to these intermediate distributions to describe the procedure. Table 5-7 presents the summing procedure to arrive at each designated distribution.

Table 5-7. Mapping Distributions to Events Appl "Smig Algrih To Ditibto Obaie -vn Define Distributions I and 2 Distribution A Event 3 Distributions A and 3 Distribution B Event 4 Distributions B and 4 Distribution C Event 5 Distributions 1 and 4 Distribution D Event 5 Distributions C and 5 Distribution E Event 5 Distributions D and 5 Distribution F Event 5 Table 5-8 presents a description of each of the final trip generation distributions achieved after the summing process is completed.

Susquehanna Steam Electric Station 5-12 KLD Engineering, P.C.

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Table 5-8. Description of the Distributions Disrbto Descripto q

Time distribution of commuters departing place of work (Event 3). Also applies A to employees who work within the EPZ who live outside, and to Transients within the EPZ.

B Time distribution of commuters arriving home (Event 4).

home, leaving home Time distribution of residents with commuters who return to begin the evacuation trip (Event 5).

D Time distribution of residents without commuters returning home, leaving home to begin the evacuation trip (Event 5).

leaving home E Time distribution of residents with commuters who return home, to begin the evacuation trip, after snow clearance activities (Event 5).

Time distribution of residents with no commuters returning home, leaving to begin the evacuation trip, after snow clearance activities (Event 5).

5.4.1 Statistical Outliers As already mentioned, some portion of the survey respondents answer "don't know" to some questions or choose to not respond to a question. The mobilization activity distributions are based upon actual responses. But, it is the nature of surveys that a few numeric responses are inconsistent with the overall pattern of results. An example would be a case in which for 500 responses, almost all of them estimate less than two hours for a given answer, but 3 say "four hours" and 4 say "six or more hours".

These "outliers" must be considered: are they valid responses, or so atypical that they should be dropped from the sample?

In assessing outliers, there are three alternates to consider:

1) Some responses with very long times may be valid, but reflect the reality that the respondent really needs to be classified in a different population subgroup, based upon special needs;

2) Other responses may be unrealistic (6 hours6.944444e-5 days <br />0.00167 hours <br />9.920635e-6 weeks <br />2.283e-6 months <br /> to return home from commuting distance, or 2 days to prepare the home for departure);

3) Some high values are representative and plausible, and one must not cut them as part of the consideration of outliers.

The issue of course is how to make the decision that a given response or set of responses are to be considered "outliers" for the component mobilization activities, using a method that objectively quantifies the process.

There is considerable statistical literature on the identification and treatment of outliers singly or in groups, much of which assumes the data is normally distributed and some of which uses non-Susquehanna Steam Electric Station 5-13 KLD Engineering, P.C.

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parametric methods to avoid that assumption. The literature cites that limited work has been done directly on outliers in sample survey responses.

In establishing the overall mobilization time/trip generation distributions, the following principles are used:

1) It is recognized that the overall trip generation distributions are conservative estimates, because they assume a household will do the mobilization activities sequentially, with no overlap of activities;

2) The individual mobilization activities (prepare to leave work, travel home, prepare home, clear snow) are reviewed for outliers, and then the overall trip generation distributions are created (see Figure 5-1, Table 5-7, Table 5-8);

3) Outliers can be eliminated either because the response reflects a special population (e.g.

special needs, transit dependent) or lack of realism, because the purpose is to estimate trip generation patterns for personal vehicles;

4) To eliminate outliers, a) the mean and standard deviation of the specific activity are estimated from the responses, b) the median of the same data is estimated, with its position relative to the mean noted, c) the histogram of the data is inspected, and d) all values greater than 3.5 standard deviations are flagged for attention, taking special note of whether there are gaps (categories with zero entries) in the histogram display.

In general, only flagged values more than 4 standard deviations from the mean are allowed to be considered outliers, with gaps in the histogram expected.

When flagged values are classified as outliers and dropped, steps "a" to "d" are repeated.

Susquehanna Steam Electric Station 5-14 KLD Engineering, P.C.

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5) As a practical matter, even with outliers eliminated by the above, the resultant histogram, viewed as a cumulative distribution, is not a normal distribution. A typical situation that results is shown below in Figure 5-3.

100.0%

90.0%

80.0% /

70.0%

60.0%

&50.0%

Z Z 40.0%

30.0%

E 20.0%

10.0%

0.0% . . . . . . . . . . . . . .

-r4 r-- r N

,' r '

rq r. U I.r 00 r Or -4 Center of Interval (minutes)

- Cumulative Data - - Cumulative Normal Figure 5-3. Comparison of Data Distribution and Normal Distribution

6) In particular, the cumulative distribution differs from the normal distribution in two key aspects, both very important in loading a network to estimate evacuation times:

Most of the real data is to the left of the "normal" curve above, indicating that the network loads faster for the first 80-85% of the vehicles, potentially causing more (and earlier) congestion than otherwise modeled; The last 10-15% of the real data "tails off" slower than the comparable "normal" curve, indicating that there is significant traffic still loading at later times.

Because these two features are important to preserve, it is the histogram of the data that is used to describe the mobilization activities, not a "normal" curve fit to the data. One could consider other distributions, but using the shape of the actual data curve is unambiguous and preserves these important features;

7) With the mobilization activities each modeled according to Steps 1-6, including preserving the features cited in Step 6, the overall (or total) mobilization times are constructed.

This is done by using the data sets and distributions under different scenarios (e.g. commuter returning, no commuter returning, no snow or snow in each). In general, these are additive, using Susquehanna Steam Electric Station 5-15 KLD Engineering, P.C.

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weighting based upon the probability distributions of each element; Figure 5-4 presents the combined trip generation distributions designated A, C, D, E and F. These distributions are presented on the same time scale. (As discussed earlier, the use of strictly additive activities is a conservative approach, because it makes all activities sequential - preparation for departure follows the return of the commuter; snow clearance follows the preparation for departure, and so forth. In practice, it is reasonable that some of these activities are done in parallel, at least to some extent - for instance, preparation to depart begins by a household member at home while the commuter is still on the road.)

The mobilization distributions that result are used in their tabular/graphical form as direct inputs to later computations that lead to the ETE.

The DYNEV II simulation model is designed to accept varying rates of vehicle trip generation for each origin centroid, expressed in the form of histograms. These histograms, which represent Distributions A, C, D, E and F, properly displaced with respect to one another, are tabulated in Table 5-9 (Distribution B,Arrive Home, omitted for clarity).

The final time period (15) is 600 minutes long. This time period is added to allow the analysis network to clear, in the event congestion persists beyond the trip generation period. Note that there are no trips generated during this final time period.

Susquehanna Steam Electric Station 5-16 KLD Engineering, P.C.

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5.4.2 Staged Evacuation Trip Generation As defined in NUREG/CR-7002, staged evacuation consists of the following:

1. ERPAs comprising the 2 mile region are advised to evacuate immediately

2. ERPAs comprising regions extending from 2 to 5 miles downwind are advised to shelter in-place while the 2 mile region is cleared

3. As vehicles evacuate the 2 mile region, sheltered people from 2 to 5 miles downwind continue preparation for evacuation

4. The population sheltering in the 2 to 5 mile region are advised to begin evacuating when approximately 90% of those originally within the 2 mile region evacuate across the 2 mile region boundary

5. Non-compliance with the shelter recommendation is the same as the shadow evacuation percentage of 20%

Assumptions

1. The EPZ population in ERPAs beyond 5 miles will react as does the population in the 2 to 5 mile region; that is they will first shelter, then evacuate after the 90th percentile ETE for the 2 mile region

2. The population in the shadow region beyond the EPZ boundary, extending to approximately 15 miles radially from the plant, will react as they do for all non-staged evacuation scenarios. That is 20% of these households will elect to evacuate with no shelter delay.

3. The transient population will not be expected to stage their evacuation because of the limited sheltering options available to people who may be at parks, on a beach, or at other venues. Also, notifying the transient population of a staged evacuation would prove difficult.

4. Employees will also be assumed to evacuate without first sheltering.

Procedure

1. Trip generation for population groups in the 2 mile region will be as computed based upon the results of the telephone survey and analysis.

2. Trip generation for the population subject to staged evacuation will be formulated as follows:

a. Identify the 9 0 th percentile evacuation time for the ERPAs comprising the two mile region. This value, Tscen*, is obtained from simulation results. It will become the time at which the region being sheltered will be told to evacuate for each scenario.

b. The resultant trip generation curves for staging are then formed as follows:

i. The non-shelter trip generation curve is followed until a maximum of 20%

of the total trips are generated (to account for shelter non-compliance).

Susquehanna Steam Electric Station 5-17 KLD Engineering, P.C.

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ii. No additional trips are generated until time Tscen-iii. Following time Tscen , the balance of trips are generated:

1. by stepping up and then following the non-shelter trip generation curve (if Tscen is < max trip generation time) or

2. by stepping up to 100% (if Tscen* is > max trip generation time)

c. Note: This procedure implies that there may be different staged trip generation distributions for different scenarios. NUREG/CR-7002 uses the statement "approximately 90th percentile" as the time to end staging and begin evacuating.

The value of Tscen* is 1:45 for non-snow scenarios and 2:15 for snow scenarios.

3. Staged trip generation distributions are created for the following population groups:

a. Residents with.returning commuters

b. Residents without returning commuters

c. Residents with returning commuters and snow conditions

d. Residents without returning commuters and snow conditions Figure 5-5 presents the staged trip generation distributions for both residents with and without returning commuters; the 9 0 th percentile two-mile evacuation time is 105 minutes for good weather and 135 minutes for snow scenarios. At the 9 0 th percentile evacuation time, 20% of the population (who normally would have completed their mobilization activities for an un-staged evacuation) advised to shelter has nevertheless departed the area. These people do not comply with the shelter advisory. Also included on the plot are the trip generation distributions for these groups as applied to the regions advised to evacuate immediately.

Since the 9 0 th percentile evacuation time occurs before the end of the trip generation time, after the sheltered region is advised to evacuate, the shelter trip generation distribution rises to meet the balance of the non-staged trip generation distribution. Following time Tscen , the balance of staged evacuation trips that are ready to depart are released within 15 minutes. After Tscen*+15, the remainder of evacuation trips are generated in accordance with the unstaged trip generation distribution.

Table 5-10 provides the trip generation histograms for staged evacuation.

5.4.3 Trip Generation for Waterways and Recreational Areas Township emergency plans describe the notification procedures for the Susquehanna River as follows:

1. "Boaters will be afforded the same mode of notification (siren) as the rest of the EPZ population.

2. Since public access to the Susquehanna River is restricted throughout the 10 mile EPZ, boaters are not considered as a transient population and therefore will be familiar with actions required upon hearing an emergency siren."

As indicated in Table 5-2, this study assumes 100% notification in 45 minutes. It is assumed that this timeframe is sufficient for the notification of boaters and that resident boaters will be able to start their evacuation trip within the 4 hour4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> timeframe for residents (Table 5-9).

Susquehanna Steam Electric Station 5-18 KLD Engineering, P.C.

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Table 5-9 indicates that all transients will have mobilized within 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> and 15 minutes; it is assumed that this allows sufficient time for campers and other transients to return to their vehicles and begin their evacuation trip.

Susquehanna Steam Electric Station 5-19 KLD Engineering, P.C.

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Table 5-9. Trip Generation Histograms for the EPZ Population for Unstaged Evacuation Percent of Total Trips Generated Within Indicated Time Period Residents Residents With Residents Residents with Without Commuters WithOUt Time Duration Employees Transients Commutors Commuters Snow Commuters Snow Period (Min) (Distribution A) (Distribution A) (Distribution Q (Distribution D) (Distribution E) (Distribution F) 2 15 33% 33% 1% 13% 0% 2%

3 15 30% 30% 4% 26% 1% 9%

4 15 15% 15% 11% 24% 3% 17%

5 15 7% 7% 17% 14% 7% 19%

6 15 5% 5% 18% 11% 12% 16%

7 15 2% 2% 15% 5% 15% 13%

8 15 0% 0% 13% 1% 14% 8%

9 15 1% 1% 8% 2% 13% 5%

10 15 0% 0% 5% 1% 10% 4%

11 30 0% 0% 6% 1% 13% 5%

12 30 0% 0% 1% 0% 7% 1%

13 30 0% 0% 1% 0% 3% 1%

14 30 0% 0% 0% 0% 2% 0%

15 600 0% 0% 0% 0% 0% 0%

NOTE:

• Shadow vehicles are loaded onto the analysis network (Figure 1-2) using Distributions C and E for good weather and snow, respectively.

• Special event vehicles are loaded using Distribution A.

Susquehanna Steam Electric Station 5-20 KILD Engineering, P.C.

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Trip Generation Distributions

-Employees/Transients - Residents with Commuters - Residents with no Commuters

- Res with Comm and Snow - Res no Comm with Snow 100 8.

I.

480 C

-W 0U

.C 60 C

C 20 0

._ 40

.3 0 2 a-0 0 30 60 90 120 150 180 210 240 270 Elapsed Time from Evacuation Advisory (min)

Figure 5-4. Comparison of Trip Generation Distributions KID Engineering, P.C.

Susquehanna Steam Electric Station 5-21 5-21 KLD Engineering, P.C.

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Table 5-10. Trip Generation Histograms for the EPZ Population for Staged Evacuation Pecn ofTtlTisGnrtdWthnIdctdTm0eid Reiet Resient 1 15 0% 0% 0% 0%

2 15 0% 3% 0% 0%

3 15 1% 5% 0% 2%

4 15 2% 5% 1% 4%

5 15 4% 3% 1% 3%

6 15 3% 2% 3% 4%

7 15 3% 1% 3% 2%

8 15 66% 77% 2% 2%

9 15 8% 2% 3% 1%

10 15 5% 1% 62% 75%

11 30 6% 1% 13% 5%

12 30 1% 0% 7% 1%

13 30 1% 0% 3% 1%

14 30 0% 0% 2% 0%

15 600 0% 0% 0% 0%

• Trip Generation for Employees and Transients (see Table 5-9) is the same for Unstaged and Staged Evacuation.

Susquehanna Steam Electric Station 5-22 KLD Engineering, P.C.

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Staged and Unstaged Evacuation Trip Generation

-Employees / Transients -Residents with Commuters

- Residents with no Commuters - Res with Comm and Snow

- Res no Comm with Snow -Staged Residents with Commuters

- Staged Residents with no Commuters - Staged Residents with Commuters (Snow)

-Staged Residents with no Commuters (Snow) 100 80 60 0,00" C

10 8 40 20 0

0 30 60 90 120 150 180 210 240 270 Elapsed Time from Evacuation Advisory (min)

Figure 5-5. Comparison of Staged and Unstaged Trip Generation Distributions in the 2 to 5 Mile Region Susquehanna Steam Electric Station 5-23 KLD Engineering, P.C.

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6 DEMAND ESTIMATION FOR EVACUATION SCENARIOS An evacuation "case" defines a combination of Evacuation Region and Evacuation Scenario.

The definitions of "Region" and "Scenario" are as follows:

Region A grouping of contiguous evacuating ERPA that forms either a "keyhole" sector-based area, or a circular area within the EPZ, that must be evacuated in response to a radiological emergency.

Scenario A combination of circumstances, including time of day, day of week, season, and weather conditions. Scenarios define the number of people in each of the affected population groups and their respective mobilization time distributions.

A total of 30 Regions were defined which encompass all the groupings of ERPA considered.

These Regions are defined in Table 6-1. The ERPA configurations are identified in Figure 6-1.

Each keyhole sector-based area consists of a central circle centered at the power plant, and three adjoining sectors, each with a central angle of 22.5 degrees, as per NUREG/CR-7002 guidance. The central sector coincides with the wind direction. These sectors extend to 5 miles from the plant (Regions R04 through R08) or to the EPZ boundary (Regions R09 through R24).

Regions R01, R02 and R03 represent evacuations of circular areas with radii of 2, 5 and 10 miles, respectively. Regions R25 through R30 are identical to Regions R04 through R08 and R02, respectively; however, those ERPA between 2 miles and 5 miles are staged until 90% of the 2-mile region (Region R01) has evacuated.

A total of 14 Scenarios were evaluated for all Regions. Thus, there are a total of 30 x 14 = 420 evacuation cases. Table 6-2 is a description of all Scenarios.

Each combination of region and scenario implies a specific population to be evacuated. Table 6-3 presents the percentage of each population group estimated to evacuate for each scenario.

Table 6-4 presents the vehicle counts for each scenario for an evacuation of Region R03 - the entire EPZ.

The vehicle estimates presented in Section 3 are peak values. These peak values are adjusted depending on the scenario and region being considered, using scenario and region specific percentages, such that the average population is considered for each evacuation case. The scenario percentages are presented in Table 6-3, while the regional percentages are provided in Table H-1. The percentages presented in Table 6-3 were determined as follows:

The number of residents with commuters during the week (when workforce is at its peak) is equal to the product of 52% (the number of households with at least one commuter) and 60%

(the number of households with a commuter that would await the return of the commuter prior to evacuating). See assumption 3 in Section 2.3. It is estimated for weekend and evening scenarios that 10% of households with returning commuters will have a commuter at work during those times.

Employment is assumed to be at its peak during the winter, midweek, midday scenarios.

Susquehanna Steam Electric Station 6-1 KLD Engineering, P.C.

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Employment is reduced slightly (96%) for summer, midweek, midday scenarios. This is based on the estimation that 50% of the employees commuting into the EPZ will be on vacation for a week during the approximate 12 weeks of summer. It is further estimated that those taking vacation will be uniformly dispersed throughout the summer with approximately 4% of employees vacationing each week. It is further estimated that only 10% of the employees are working in the evenings and during the weekends.

Transient activity is estimated to be at its peak during winter midweek (68%) and less (9%) on the weekend. As shown in Appendix E, there is a significant amount of lodging and campgrounds offering overnight accommodations in the EPZ; thus, transient activity still occurs during evening hours - 16% for summer and 17% for winter. Transient activity on winter weekends is estimated to be 10%.

As noted in the shadow footnote to Table 6-3, the shadow percentages are computed using a base of 20% (see assumption 5 in Section 2.2); to include the employees within the shadow region who may choose to evacuate, the voluntary evacuation is multiplied by a scenario-specific proportion of employees to permanent residents in the shadow region. For example, using the values provided in Table 6-4 for Scenario 1, the shadow percentage is computed as follows:

1,493 20°o x (1 + 11,458 + 25,407/= 21%

One special event - SSES Refueling - was considered as Scenario 13. Thus, the special event traffic is 100% evacuated for Scenario 13, and 0% for all other scenarios.

It is estimated that summer school enrollment is approximately 10% of enrollment during the regular school year for summer, midweek, midday scenarios. School is not in session during weekends and evenings, thus no buses for school children are needed under those circumstances. As discussed in Section 7, schools are in session during the winter season, midweek, midday and 100% of buses will be needed under those circumstances. Transit buses for the transit-dependent population are set to 100% for all scenarios as it is assumed that the transit-dependent population is present in the EPZ for all scenarios.

External traffic is estimated to be reduced by 60% during evening scenarios and is 100% for all other scenarios.

Susquehanna Steam Electric Station 6-2 KLD Engineering, P.C.

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Table 6-1. Description of Evacuation Regions Region Description ERPA RegonDesritio 11 2 13 4 s5 6J 7LO9 1 11 13 114 115 116 117 18I 19 120 121 122 123 124 125 26 127 R01 2-Mile Ring R02 5-Mile Ring R03 Full EPZ ERPA Region Wind Direction To: 2 - 5 6 7 R04 NNW, N, NNE I I I I I I I 2 7 NE, W, WNW, NW Refer to R01 ROS ENE, E, ESE R06 SE, SSE R07 S ROB SSW, SW, WSW ERPA Region Wind Direction To:

R09 N RIO NNE R11 NE R12 ENE R13 E R14 ESE R15 SE R16 SSE R17 S Susquehanna Steam Electric Station 6-3 KLD Engineering, P.C.

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ERPA Region Wind Direction To:

210111112113114115116117118119120121122123 124125126127 R25 NNW, N, NNE NE, W, WNW, NW Refer to R01 R26 ENE, E, ESE R27 SE, SSE R28 S R29 SSW, SW, WSW R30 5-Mile Ring

/ERPA(s) Shelter-in-Place Susquehanna Steam Electric Station 6-4 KLD Engineering, P.C.

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Figure 6-1. SSES EPZ ERPA Susquehanna Steam Electric Station 6-5 KLD Engineering, P.C.

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Table 6-2. Evacuation Scenario Definitions Day of Tmeo Scnai Sesn Wee Day Wete Speia 1 Summer Midweek Midday Good None 2 Summer Midweek Midday Rain None 3 Summer Weekend Midday Good None 4 Summer Weekend Midday Rain None Midweek, 5 Summer Weekend Evening Good None 6 Winter Midweek Midday Good None 7 Winter Midweek Midday Rain None 8 Winter Midweek Midday Snow None 9 Winter Weekend Midday Good None 10 Winter Weekend Midday Rain None 11 Winter Weekend Midday Snow None Midweek, 12 Winter Weekend Evening Good None 13 Winter Midweek Midday Good SSES Refueling Roadway Impact - Lane 14 Summer Midweek Midday Good Closure on 1-80 WB 1 Winter means that school is in session (also applies to spring and autumn). Summer means that school is not in session.

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Table 6-3. Percent of Population Groups Evacuating for Various Scenarios 1 31% 69% 96% 11% 21% 0% 10% 10% 100% 100%

2 31% 69% 96% 11% 21% 0% 10% 10% 100% 100%

3 3% 97% 10% 12% 20% 0% 0% 0% 100% 100%

4 3% 97% 10% 12% 20% 0% 0% 0% 100% 100%

5 3% 97% 10% 16% 20% 0% 0% 0% 100% 40%

6 31% 69% 100% 68% 21% 0% 100% 100% 100% 100%

7 31% 69% 100% 68% 21% 0% 100% 100% 100% 100%

8 31% 69% 100% 68% 21% 0% 100% 100% 100% 100%

9 3% 97% 10% 9% 20% 0% 0% 0% 100% 100%

10 3% 97% 10% 9% 20% 0% 0% 0% 100% 100%

11 3% 97% 10% 9% 20% 0% 0% 0% 100% 100%

12 3% 97% 10% 17% 20% 0% 0% 0% 100% 40%

13 31% 69% 100% 68% 21% 100% 100% 100% 100% 100%

14 31% 69% 96% 11% 21% 0% 10% 10% 100% 100%

Resident Households with Commuters ....... Households of EPZ residents who await the return of commuters prior to beginning the evacuation trip.

Resident Households with No Commuters ..Households of EPZ residents who do not have commuters or will not await the return of commuters prior to beginning the evacuation trip.

Employees .................................................. EPZ employees who live outside the EPZ Transients .................................................. People who are in the EPZ at the time of an accident for recreational or other (non-employment) purposes.

Shadow ...................................................... Residents and employees in the shadow region (outside of the EPZ) who will spontaneously decide to relocate during the evacuation. The basis for the values shown Is a 20% relocation of shadow residents along with a proportional percentage of shadow employees.

Special Events ........................................... Additional vehicles in the EPZ due to the identified special event.

School and Transit Buses ............................ Vehicle-equivalents present on the road during evacuation servicing schools and transit-dependent people (1 bus is equivalent to 2 passenger vehicles).

External Through Traffic ............................. Traffic on Interstates/freeways and major arterial roads at the start of the evacuation. This traffic is stopped by access control approximately 90 minutes after the evacuation begins.

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• 0 Table 6-4. Vehicle Estimates by Scenario Reunn Reunn Spca Scoo Trni Thog Scnai 1 11,458 25,407 1,493 128 10,101 Ee 226 38 216 9,994 59,061 2 11,458 25,407 1,493 128 10,101 - 226 38 216 9,994 59,061 3 1,146 35,719 156 140 9,749 - 2 3 216 9,994 57,120 4 1,146 35,719 156 140 9,749 - - - 216 9,994 57,120 5 1,146 35,719 156 186 9,749 - 216 3,998 51,170 6 11,458 25,407 1,555 791 10,117 - 2,260 378 216 9,994 62,176 7 11,458 25,407 1,555 791 10,117 - 2,260 378 216 9,994 62,176 8 11,458 25,407 1,555 791 10,117 - 2,260 378 216 9,994 62,176 9 1,146 35,719 156 105 9,749 - 216 9,994 57,085 10 1,146 35,719 156 105 9,749 - - 216 9,994 57,085 10 1,146 35,719 156 105 9,749 - - 216 9,994 57,085 12 1,146 35,719 156 198 9,749 - - - 216 3,998 51,182 13 11,458 25,407 1,555 791 10,117 784 2,260 378 216 9,994 62,960 14 11,458 25,407 1,493 128 10,101 - 226 38 216 9,994 59,061 Note: Vehicle estimates are for an evacuation of the entire EPZ (Region R03).

School buses includes 5 buses (10 pce) for Penn State.

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7 GENERAL POPULATION EVACUATION TIME ESTIMATES (ETE)

This section presents the ETE results of the computer analyses using the DYNEV II System described in Appendices B, C and D. These results cover 30 regions within the SSES EPZ and the 14 Evacuation Scenarios discussed in Section 6.

The ETE for all Evacuation Cases are presented in Table 7-1 and Table 7-2. These tables present the estimated times to clear the indicated population percentages from the Evacuation Regions for all Evacuation Scenarios. The ETE of the 2-mile region in both staged and un-staged regions are presented in Table 7-3 and Table 7-4. Table 7-5 defines the Evacuation Regions considered.

The tabulated values of ETE are obtained from the DYNEV II System outputs which are generated at 5-minute intervals.

7.1 Voluntary Evacuation and Shadow Evacuation "Voluntary evacuees" are people within the EPZ in ERPA for which an Advisory to Evacuate has not been issued, yet who elect to evacuate. "Shadow evacuation" is the voluntary outward movement of some people from the Shadow Region (outside the EPZ) for whom no protective action recommendation has been issued. Both voluntary and shadow evacuations are assumed to take place over the same time frame as the evacuation from within the impacted Evacuation Region.

The ETE for the SSES EPZ addresses the issue of voluntary evacuees in the manner shown in Figure 7-1. Within the EPZ, 20 percent of people located in ERPA outside of the evacuation region who are not advised to evacuate, are assumed to elect to evacuate. Similarly, it is assumed that 20 percent of those people in the Shadow Region will choose to leave the area.

Figure 7-2 presents the area identified as the Shadow Region. This region extends radially from the plant to cover a region between the EPZ boundary and approximately 15 miles. The population and number of evacuating vehicles in the Shadow Region were estimated using the same methodology that was used for permanent residents within the EPZ (see Section 3.1). As discussed in Section 3.2, it is estimated that a total of 96,031 people reside in the Shadow Region; 20 percent of them would evacuate. See Table 6-4 for the number of evacuating vehicles from the Shadow Region.

Traffic generated within this Shadow Region, traveling away from the SSES location, has the potential for impeding evacuating vehicles from within the Evacuation Region. All ETE calculations include this shadow traffic movement.

7.2 Staged Evacuation As defined in NUREG/CR-7002, staged evacuation consists of the following:

1. ERPA comprising the 2 mile region are advised to evacuate immediately.

2. ERPA comprising regions extending from 2 to 5 miles downwind are advised to shelter in-place while the two mile region is cleared.

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3. As vehicles evacuate the 2 mile region, people from 2 to 5 miles downwind continue preparation for evacuation while they shelter.

4. The population sheltering in the 2 to 5 mile region is advised to evacuate when approximately 90% of the 2 mile region evacuating traffic crosses the 2 mile region boundary.

5. Non-compliance with the shelter recommendation is the same as the shadow evacuation percentage of 20%.

See Section 5.4.2 for additional information on staged evacuation.

7.3 Patterns of Traffic Congestion during Evacuation Figure 7-3 through Figure 7-7 illustrate the patterns of traffic congestion that arise for the case when the entire EPZ (Region R03) is advised to evacuate during the summer, midweek, midday period under good weather conditions (Scenario 1).

Traffic congestion, as the term is used here, is defined as Level of Service (LOS) F. LOS F is defined as follows (HCM 2010, page 5-5):

The HCM uses LOS F to define operations that have either broken down (i.e., demand exceeds capacity) or have exceeded a specified service measure value, or combination of service measure values, that most users would consider unsatisfactory. However, particularly for planning applications where different alternatives may be compared, analysts may be interested in knowing just how bad the LOS F condition is. Several measures are available to describe individually, or in combination, the severity of a LOS F condition:

- Demand-to-capacity ratios describe the extent to which capacity is exceeded during the analysis period (e.g., by 1%, 15%, etc.);

e Durationof LOS F describes how long the condition persists (e.g., 15 min, 1 h, 3 h); and o Spatial extent measures describe the areas affected by LOS F conditions. These include measures such as the back of queue, and the identification of the specific intersection approaches or system elements experiencing LOS F conditions.

All highway "links" which experience LOS F are delineated in these figures by a thick red line; all others are lightly indicated. Congestion develops rapidly around concentrations of population, most noticeably on the local roadways in Nanticoke City and Berwick Borough. Figure 7-3 displays the developing congestion just 30 minutes after the Advisory to Evacuate (ATE).Throughout the course of the evacuation, there is never significant congestion within 2-miles of the plant.

At one hour after the ATE, Figure 7-4 shows that there is fully-developed congestion in ERPA 21 as evacuating vehicles converge onto US 11 and SC 29 just outside the EPZ. There are also heavy delays at the on-ramp to 1-81 in this area. Traffic is building on US 11 WB through Berwick Susquehanna Steam Electric Station 7-2 KID Engineering, P.C.

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and Briar Creek Boroughs and along the alternate route out of town, SC 93. SC 93 is also congested in the southeastern EPZ through Conyngham Borough and Hazleton. The congestion pattern remains similar for the next 30 minutes.

By 2:00 after the ATE (Figure 7-5), the congestion in Conyngham Borough has receded and US11 is only congested within the borough of Briar Creek. The TCP at the intersection of SR 93 with SR487, near Orangeville, is very important - simulations run before adding this TCP showed vehicles passing through this intersection endured extreme delay. The main streets through Nanticoke City are still heavily congested.

Over the next hour, congestion in all the population centers dissipates and the only congestion within the EPZ is on SC 93 in ERPA 27 and 26 (see Figure 7-6). By 3:10 the LOS has improved from F to E and by 3:20 after the ATE, all links within the EPZ are at LOS A and any remaining evacuating traffic is therefore moving at free-flow speed. Figure 7-7 shows the network at 3:30, at which time the vast majority of evacuees have cleared the EPZ and only those who were slow to mobilize remain.

7.4 Evacuation Rates Evacuation is a continuous process, as implied by Figure 7-8 through Figure 7-21. These figures indicate the rate at which traffic flows out of the indicated areas for the case of an evacuation of the full EPZ (Region R03) under the indicated conditions. One figure is presented for each scenario considered.

As indicated in Figure 7-8, there is typically a long "tail" to these distributions. Vehicles begin to evacuate an area slowly at first, as people respond to the ATE at different rates. Then traffic demand builds rapidly (slopes of curves increase). When the system becomes congested, traffic exits the EPZ at rates somewhat below capacity until some evacuation routes have cleared. As more routes clear, the aggregate rate of egress slows since many vehicles have already left the EPZ. Towards the end of the process, relatively few evacuees (those with the longest mobilization times) travel freely out of the EPZ.

This decline in aggregate flow rate, towards the end of the process, is characterized by these curves flattening and gradually becoming horizontal. Ideally, it would be desirable to fully saturate all evacuation routes equally so that all will service traffic near capacity levels and all will clear at the same time. For this ideal situation, all curves would retain the same slope until the end - thus minimizing evacuation time. In reality, this ideal is generally unattainable reflecting the spatial variation in population density, mobilization rates and in highway capacity over the EPZ.

7.5 Evacuation Time Estimate (ETE) Results Table 7-1 and Table 7-2 present the ETE values for all 30 Evacuation Regions and all 14 Evacuation Scenarios. Table 7-3 and Table 7-4 present the ETE values for the 2-Mile region for both staged and un-staged keyhole regions downwind to 5 miles. The tables are organized as follows:

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II Tabl Cotet ETE represents the elapsed time required for 90 percent of the I 7-1 population within a Region, to evacuate from that Region. All Scenarios are considered, as well as Staged Evacuation scenarios.

ETE represents the elapsed time required for 100 percent of the 7-2 population within a Region, to evacuate from that Region. All Scenarios are considered, as well as Staged Evacuation scenarios.

ETE represents the elapsed time required for 90 percent of the 7-3 population within the 2-mile Region, to evacuate from that Region with both Concurrent and Staged Evacuations.

ETE represents the elapsed time required for 100 percent of the 7-4 population within the 2-mile Region, to evacuate from that Region with both Concurrent and Staged Evacuations.

The animation snapshots described above reflect the ETE statistics for the concurrent (un-staged) evacuation scenarios and regions, which are displayed in Figure 7-3 through Figure 7-21. Most of the congestion is located in ERPA 4 and 7 which are beyond the 5-mile area; this is reflected in the ETE statistics:

" The 1 0 0 th percentile ETE for all regions and scenarios reflects the mobilization time of residents with commuters, due to the fact that the congestion within the EPZ clears nearly an hour before the last residents have left their homes.

• The 9 0 th percentile ETE for Region R02 are 5 to 15 minutes longer than the ETE for R01.

Similarly, the 9 0 th percentile ETE for Region R03 are 5 to 20 minutes longer than the ETE for R02.

• At the 9 0 th percentile level, rain increases the ETE by up to 15 minutes; snow by 30 to 45 minutes.

" The 90th percentile ETE for the 5-mile keyhole regions that concurrently include ERPA 10, 12, 11 and 26, i.e. R19-R22, are slightly higher across all scenarios than the other keyhole ETE. This is due to the high population density within ERPA 10, 11 and 12 and the inhibiting effect of the congestion through ERPA 26 (see Figure 7-4 through 7-6).

Comparison of Scenarios 6 and 13 in Table 7-1 indicates that the Special Event - refueling outage at the plant - does not have a significant impact on the ETE for the 9 0 th percentile. The ETE for the 2-mile region and all 2-mile keyhole regions are actually 5 minutes lower for the special event. This is due to the fact that, proportionately, there are more employees in the 2-mile ring for the special event so the average mobilization time of all evacuees is actually reduced. However, since the results are rounded to the nearest 5 minutes this difference, while consistent, is not significant. At the 100th percentile level, the permanent resident mobilization time determines ETE; 100% of the plant employees are mobilized and evacuated before 100% of the residents have completed their mobilization activities, therefore the ETE is Susquehanna Steam Electric Station 7-4 KLD Engineering, P.C.

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unchanged.

Comparison of Scenarios 1 and 14 in Table 7-1 indicates that the roadway closure - one lane westbound on 1-80 from the interchange with SR 339 to the EPZ boundary - does not change the ETE, indicating that there is excess capacity on the highway.

7.6 Staged Evacuation Results Table 7-3 and Table 7-4 present a comparison of the ETE compiled for the concurrent (un-staged) and staged evacuation studies. Note that Regions R25 through R30 are the same geographic areas as Regions R04 through R08 and R02, respectively.

To determine whether the staged evacuation strategy is worthy of consideration, one must show that the ETE for the 2-mile region can be reduced without significantly affecting the region between 2 miles and 5 miles. In all cases, as shown in these tables, the ETE for the 2-mile region is unchanged when a staged evacuation is implemented. The impedance due to this congestion within the 5-mile area to evacuees from within the 2-mile area is not sufficient to materially influence the 9 0 th percentile ETE for the 2-mile area. Therefore, staging the evacuation to sharply reduce congestion within the 5-mile area provides no benefits to evacuees from within the 2-mile region and unnecessarily delays the evacuation of those beyond 2 miles.

While failing to provide assistance to evacuees from within 2 miles of the SSES, staging produces a negative impact on the ETE for those evacuating from within the 5-mile area. A comparison of ETE between Regions R25 through R30 with R04 though R08 and R02 respectively, reveals that staging retards the 9 0 th percentile ETE for those in the 2 to 5-mile area by up to 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> (see Table 7-1). This extending of ETE is due to the delay in beginning the evacuation trip, experienced by those who shelter, plus the effect of the trip-generation "spike" (significant volume of traffic beginning the evacuation trip at the same time) that follows their eventual ATE, in creating congestion within the EPZ area beyond 2 miles. The 1 0 0 th percentile ETE is unaffected by staging (see Table 7-2).

In summary, the staged evacuation protective action strategy provides no benefits and adversely impacts many evacuees located beyond 2 miles from the SSES.

7.7 Guidance on Using ETE Tables The user first determines the percentile of population for which the ETE is sought (The NRC guidance calls for the 90th percentile). The applicable value of ETE within the chosen Table may then be identified using the following procedure:

1. Identify the applicable Scenario:

• Season

" Summer

" Winter (also Autumn and Spring)

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SDay of Week 0 Midweek 0 Weekend

• Time of Day

" Midday

" Evening

" Weather Condition

" Good Weather

" Rain

" Snow

• Special Event

" Refueling outage at SSES

" Road Closure (one lane on 1-80 WB is closed)

• Evacuation Staging

" No, Staged Evacuation is not considered

" Yes, Staged Evacuation is considered While these Scenarios are designed, in aggregate, to represent conditions throughout the year, some further clarification is warranted:

• The conditions of a summer evening (either midweek or weekend) and rain are not explicitly identified in the Tables. For these conditions, Scenarios (2) and (4) apply.

• The conditions of a winter evening (either midweek or weekend) and rain are not explicitly identified in the Tables. For these conditions, Scenarios (7) and (10) for rain apply.

• The conditions of a winter evening (either midweek or weekend) and snow are not explicitly identified in the Tables. For these conditions, Scenarios (8) and (11) for snow apply.

• The seasons are defined as follows:

N Summer assumes that public schools are not in session.

0 Winter (includes Spring and Autumn) considers that public schools are in session.

• Time of Day: Midday implies the time over which most commuters are at work or are travelling to/from work.

2. With the desired percentile ETE and Scenario identified, now identify the Evacuation Region:

• Determine the projected azimuth direction of the plume (coincident with the wind direction). This direction is expressed in terms of compass orientation: towards N, NNE, NE, ...

• Determine the distance that the Evacuation Region will extend from the nuclear power plant. The applicable distances and their associated candidate Regions are given below:

• 2 Miles (Region R01)

• To 5 Miles (Region R02, R04 through R08 and staged regions R25 through R30)

• To EPZ Boundary (Regions R03, R09 through R24)

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• Enter Table 7-5 and identify the applicable group of candidate Regions based on the distance that the selected Region extends from the plant. Select the Evacuation Region identifier in that row, based on the azimuth direction of the plume, from the first column of the Table.

3. Determine the ETE Table based on the percentile selected. Then, for the Scenario identified in Step 1 and the Region identified in Step 2, proceed as follows:

• The columns of Table 7-1 are labeled with the Scenario numbers. Identify the proper column in the selected Table using the Scenario number defined in Step 1.

• Identify the row in this table that provides ETE values for the Region identified in Step 2.

• The unique data cell defined by the column and row so determined contains the desired value of ETE expressed in Hours:Minutes.

Example It is desired to identify the ETE for the following conditions:

• Sunday, August 10th at 4:00 AM.

• It is raining.

• Wind direction is toward the northeast (NE).

• Wind speed is such that the distance to be evacuated is judged to be a 5-mile radius and downwind to 10 miles (to EPZ boundary).

• The desired ETE is that value needed to evacuate 90 percent of the population from within the impacted Region.

• A staged evacuation is not desired.

Table 7-1 is applicable because the 9 0 th percentile ETE is desired. Proceed as follows:

1. Identify the Scenario as summer, weekend, evening and raining. Entering Table 7-1, it is seen that there is no match for these descriptors. However, the clarification given above assigns this combination of circumstances to Scenario 4.

2. Enter Table 7-5 and locate the Region described as "Evacuate 5-Mile Radius and Downwind to the EPZ Boundary" for wind direction toward the NE (from the SW) and read Region R11 in the first column of that row.

3. Enter Table 7-1 to locate the data cell containing the value of ETE for Scenario 4 and Region R11. This data cell is in column (4) and in the row for Region R11; it contains the ETE value of 2:10.

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