PNP 2022-032, 2022 Evacuation Time Estimate Report

2022 Evacuation Time Estimate Report

ML22250A524
Person / Time
Site:	Palisades
Issue date:	09/07/2022
From:	Fleming J Holtec Decommissioning International
To:	Document Control Desk, Office of Nuclear Reactor Regulation
References
HDI PNP 2022-032
Download: ML22250A524 (368)

Text

Krishna P. Singh Technology Campus, 1 Holtec Blvd., Camden, NJ 08104 HOLTEC Telephone (856) 797-0900 DECOMMISSIONING Fax (856) 797-0909 INTERNATIONAL HDI PNP 2022-032 10 CFR 50, Appendix E September , 2022 U.S. Nuclear Regulatory Commission ATTN: Document Control Desk Washington, DC 20555-0001

Subject:

Palisades Nuclear Plant 2022 Evacuation Time Estimate Report Palisades Nuclear Plant Docket No. 50-255 Renewed Facility Operating License No. DPR-20 In accordance with Title 10 of the Code of Federal Regulations Part 50 (10 CFR 50),

Appendix E, Emergency Planning and Preparedness for Production and Utilization Facilities,Section IV., Content of Emergency Plans, Paragraph 4., Holtec Decommissioning International, LLC, is submitting on behalf of Holtec Palisades, LLC, the 2022 Evacuation Time Estimate (ETE) Report for Palisades Nuclear Plant (PNP). The PNP 2022 ETE Report is provided in the Enclosure to this letter.

This letter contains no new commitments and no revised commitments.

Should you have any questions or require additional information, please contact Jim Miksa, Regulatory Assurance Engineer at (269) 764-2945.

Respectfully, Jean A. Fleming Digitally signed by Jean A. Fleming Date: 2022.09.07 11:26:48 -04'00' Jean A. Fleming Vice President of Licensing, Regulatory Affairs & PSA Holtec International

Enclosure:

Palisades Nuclear Plant 2022 Evacuation Time Estimate Report cc: NRC Region Ill Regional Administrator NRC Senior Resident Inspector - Palisades Nuclear Plant NRC Project Manager - Palisades Nuclear Plant State of Michigan Official

Enclosure to HDI PNP 2022-032 Palisades Nuclear Plant Palisades Nuclear Plant 2022 Evacuation Time Estimate Report (366 Pages)

Palisades Power Plant Development of Evacuation Time Estimates Work performed for Entergy/Holtec, by:

KLD Engineering, P.C.

1601 Veterans Memorial Highway, Suite 340 Islandia, NY 11749 e mail: kweinisch@kldcompanies.com September 1, 2022 Final Report, Rev. 0 KLD TR - 1254

Table of Contents EXECUTIVE

SUMMARY

............................................................................................................................. ES 1 1 INTRODUCTION..................................................................................................................................1 1 1.1 Overview of the ETE Process......................................................................................................1 1 1.2 The Palisades Power Plant Location ..........................................................................................1 3 1.3 Preliminary Activities ................................................................................................................. 1 3 1.4 Comparison with Prior ETE Study ..............................................................................................1 6 2 STUDY ESTIMATES AND ASSUMPTIONS.............................................................................................2 1 2.1 Data Estimates Assumptions......................................................................................................2 1 2.2 Methodological Assumptions ....................................................................................................2 2 2.3 Assumptions on Mobilization Times ..........................................................................................2 3 2.4 Transit Dependent Assumptions................................................................................................2 3 2.5 Traffic and Access Control Assumptions ....................................................................................2 5 2.6 Scenarios and Regions ............................................................................................................... 2 5 3 DEMAND ESTIMATION....................................................................................................................... 3 1 3.1 Permanent Residents ................................................................................................................. 3 2 3.2 Shadow Population .................................................................................................................... 3 2 3.3 Transient Population.................................................................................................................. 3 3 3.3.1 Seasonal Transient Population...........................................................................................3 3 3.4 Employees ..................................................................................................................................3 4 3.5 Medical Facilities........................................................................................................................ 3 5 3.6 School Population Demand........................................................................................................3 5 3.6.1 Commuter College ............................................................................................................. 3 6 3.7 Special Event .............................................................................................................................. 3 6 3.8 Access and/or Functional Needs Population .............................................................................3 7 3.9 Transit Dependent Population...................................................................................................3 7 3.10 External Traffic ........................................................................................................................... 3 9 3.11 Background Traffic ...................................................................................................................3 10 3.12 Summary of Demand ...............................................................................................................3 10 4 ESTIMATION OF HIGHWAY CAPACITY................................................................................................4 1 4.1 Capacity Estimations on Approaches to Intersections ..............................................................4 2 4.2 Capacity Estimation along Sections of Highway ........................................................................4 4 4.3 Application to the PPP Study Area.............................................................................................4 6 4.3.1 Two Lane Roads ................................................................................................................. 4 6 4.3.2 Multilane Highway ............................................................................................................. 4 7 4.3.3 Freeways ............................................................................................................................ 4 7 4.3.4 Intersections ...................................................................................................................... 4 8 4.4 Simulation and Capacity Estimation ..........................................................................................4 8 4.5 Boundary Condition ................................................................................................................... 4 9 5 ESTIMATION OF TRIP GENERATION TIME..........................................................................................5 1 5.1 Background ................................................................................................................................5 1 5.2 Fundamental Considerations .....................................................................................................5 3 Palisades Power Plant i KLD Engineering, P.C.

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5.3 Estimated Time Distributions of Activities Preceding Event 5...................................................5 4 5.4 Calculation of Trip Generation Time Distribution......................................................................5 5 5.4.1 Statistical Outliers .............................................................................................................. 5 6 5.4.2 Staged Evacuation Trip Generation ...................................................................................5 8 5.4.3 Trip Generation for Waterways and Recreational Areas.................................................5 10 6 DEMAND ESTIMATION FOR EVACUATION 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 2 7.3 Patterns of Traffic Congestion during Evacuation .....................................................................7 2 7.4 Evacuation Rates........................................................................................................................ 7 3 7.5 Evacuation Time Estimate (ETE) Results ....................................................................................7 4 7.6 Staged Evacuation Results .........................................................................................................7 5 7.7 Guidance on Using ETE Tables ...................................................................................................7 6 8 TRANSIT DEPENDENT AND SPECIAL FACILITY EVACUATION TIME ESTIMATES .................................8 1 8.1 ETEs for Schools, Transit Dependent People, and Special Facilities..........................................8 2 8.2 ETE for Access and/or Functional Needs Population.................................................................8 9 9 TRAFFIC MANAGEMENT STRATEGY ...................................................................................................9 1 9.1 Assumptions............................................................................................................................... 9 2 9.2 Additional Considerations..........................................................................................................9 2 10 EVACUATION ROUTES and Reception Centers ............................................................................10 1 10.1 Evacuation Routes.................................................................................................................... 10 1 10.2 Reception Centers....................................................................................................................10 1 List of Appendices A. GLOSSARY OF TRAFFIC ENGINEERING TERMS .................................................................................. A 1 B. DYNAMIC TRAFFIC ASSIGNMENT AND DISTRIBUTION MODEL .........................................................B 1 C. DYNEV TRAFFIC SIMULATION MODEL ...............................................................................................C 1 C.1 Methodology..............................................................................................................................C 2 C.1.1 The Fundamental Diagram.................................................................................................C 2 C.1.2 The Simulation Model ........................................................................................................ C 2 C.1.3 Lane Assignment ................................................................................................................C 6 C.2 Implementation .........................................................................................................................C 6 C.2.1 Computational Procedure..................................................................................................C 6 C.2.2 Interfacing with Dynamic Traffic Assignment (DTRAD) .....................................................C 8 D. DETAILED DESCRIPTION OF STUDY PROCEDURE .............................................................................. D 1 E. SPECIAL FACILITY DATA ...................................................................................................................... E 1 F. DEMOGRAPHIC SURVEY..................................................................................................................... F 1 Palisades Power Plant ii KLD Engineering, P.C.

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F.1 Introduction ............................................................................................................................... F 1 F.2 Survey Instrument and Sampling Plan ....................................................................................... F 1 F.3 Survey Results ............................................................................................................................ F 2 F.3.1 Household Demographic Results ........................................................................................... F 2 F.3.2 Evacuation Response ............................................................................................................. F 3 F.3.3 Time Distribution Results....................................................................................................... F 4 G. TRAFFIC MANAGEMENT PLAN.......................................................................................................... G 1 G.1 Manual Traffic Control .............................................................................................................. G 1 G.2 Analysis of Key ACP Locations................................................................................................... G 1 H EVACUATION REGIONS ..................................................................................................................... H 1 J. REPRESENTATIVE INPUTS TO AND OUTPUTS FROM THE DYNEV II SYSTEM ..................................... J 1 K. EVACUATION ROADWAY NETWORK..................................................................................................K 1 L. PAA BOUNDARIES .............................................................................................................................. L 1 M. EVACUATION SENSITIVITY STUDIES ............................................................................................. M 1 M.1 Effect of Changes in Trip Generation Times ............................................................................ M 1 M.2 Effect of Changes in the Number of People in the Shadow Region Who Relocate ................. M 1 M.3 Effect of Changes in the Permanent Resident Population....................................................... M 2 M.4 Effect of Changes in Average Household Size.......................................................................... M 3 M.5 Enhancements in Evacuation Time .......................................................................................... M 3 N. ETE CRITERIA CHECKLIST ................................................................................................................... N 1 Note: Appendix I intentionally skipped Palisades Power Plant iii KLD Engineering, P.C.

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List of Figures Figure 1 1. PPP Location .......................................................................................................................... 1 12 Figure 1 2. PPP Link Node Analysis Network...........................................................................................1 13 Figure 2 1. Voluntary Evacuation Methodology .......................................................................................2 9 Figure 3 1. PAAs Comprising the PPP EPZ................................................................................................3 18 Figure 3 2. Permanent Resident Population by Sector............................................................................3 19 Figure 3 3. Permanent Resident Vehicles by Sector ................................................................................3 20 Figure 3 4. Shadow Population by Sector................................................................................................3 21 Figure 3 5. Shadow Vehicles by Sector ....................................................................................................3 22 Figure 3 6. Transient Population by Sector..............................................................................................3 23 Figure 3 7. Transient Vehicles by Sector..................................................................................................3 24 Figure 3 8. Employee Population by Sector.............................................................................................3 25 Figure 3 9. Employee Vehicles by Sector .................................................................................................3 26 Figure 4 1. Fundamental Diagrams.......................................................................................................... 4 10 Figure 5 1. Events and Activities Preceding the Evacuation Trip............................................................5 17 Figure 5 2. Evacuation Mobilization Activities........................................................................................5 18 Figure 5 3. Comparison of Data Distribution and Normal Distribution.......................................................5 19 Figure 5 4. Comparison of Trip Generation Distributions.......................................................................5 20 Figure 5 5. Comparison of Staged and Unstaged Trip Generation Distributions in the 2 to 5 Mile Region ....................................................................................................5 21 Figure 6 1. PAA Comprising the PPP EPZ ...................................................................................................6 8 Figure 7 1. Voluntary Evacuation Methodology .....................................................................................7 14 Figure 7 2. PPP Shadow Region ............................................................................................................... 7 15 Figure 7 3. Congestion Patterns at 30 Minutes after the Advisory to Evacuate .....................................7 16 Figure 7 4. Congestion Patterns at 1 Hour after the Advisory to Evacuate.............................................7 17 Figure 7 5. Congestion Patterns at 2 Hours after the Advisory to Evacuate ...........................................7 18 Figure 7 6. Congestion Patterns at 2 Hours and 30 Minutes after the Advisory to Evacuate .................7 19 Figure 7 7. Evacuation Time Estimates Scenario 1 for Region R03 ......................................................7 20 Figure 7 8. Evacuation Time Estimates Scenario 2 for Region R03 ......................................................7 20 Figure 7 9. Evacuation Time Estimates Scenario 3 for Region R03 ......................................................7 21 Figure 7 10. Evacuation Time Estimates Scenario 4 for Region R03 ....................................................7 21 Figure 7 11. Evacuation Time Estimates Scenario 5 for Region R03 ....................................................7 22 Figure 7 12. Evacuation Time Estimates Scenario 6 for Region R03 ....................................................7 22 Figure 7 13. Evacuation Time Estimates Scenario 7 for Region R03 ....................................................7 23 Figure 7 14. Evacuation Time Estimates Scenario 8 for Region R03 ....................................................7 23 Figure 7 15. Evacuation Time Estimates Scenario 9 for Region R03 ....................................................7 24 Figure 7 16. Evacuation Time Estimates Scenario 10 for Region R03 ..................................................7 24 Figure 7 17. Evacuation Time Estimates Scenario 11 for Region R03 ..................................................7 25 Figure 7 18. Evacuation Time Estimates Scenario 12 for Region R03 ..................................................7 25 Figure 7 19. Evacuation Time Estimates Scenario 13 for Region R03 ..................................................7 26 Figure 7 20. Evacuation Time Estimates Scenario 14 for Region R03 ..................................................7 26 Figure 8 1. Chronology of Transit Evacuation Operations ......................................................................8 26 Figure 10 1. Evacuation Route Map.........................................................................................................10 6 Figure 10 2. Transit Dependent Bus Routes ............................................................................................10 7 Figure 10 3. General Population Reception Centers and Temporary Host Facilities ..............................10 8 Figure B 1. Flow Diagram of Simulation DTRAD Interface........................................................................B 5 Palisades Power Plant iv KLD Engineering, P.C.

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Figure C 1. Representative Analysis Network......................................................................................... C 13 Figure C 2. Fundamental Diagrams.........................................................................................................C 14 Figure C 3. A UNIT Problem Configuration with t1 > 0 ............................................................................C 15 Figure C 4. Flow of Simulation Processing (See Glossary: Table C 3) ....................................................C 16 Figure D 1. Flow Diagram of Activities..................................................................................................... D 5 Figure E 1. Schools and Preschools within the EPZ....................................................................................E 7 Figure E 2. Medical Facilities within the EPZ ............................................................................................. E 8 Figure E 3. Major Employers within the EPZ............................................................................................. E 9 Figure E 4. Recreational Areas within the EPZ......................................................................................... E 10 Figure E 5. Marinas within the EPZ .......................................................................................................... E 11 Figure E 6. Lodging Facilities within the EPZ............................................................................................ E 12 Figure F 1. Household Size in the EPZ .......................................................................................................... 7 Figure F 2. Household Vehicle Availability................................................................................................... 7 Figure F 3. Vehicle Availability 1 to 6+ Person Households....................................................................... 8 Figure F 4. Household Ridesharing Preference............................................................................................ 8 Figure F 5. Commuters in Households in the EPZ........................................................................................ 9 Figure F 6. Modes of Travel in the EPZ ........................................................................................................ 9 Figure F 7. Commuters Impacted by COVID 19.......................................................................................... 10 Figure F 8. Households with Functional or Transportation Needs ............................................................. 10 Figure F 9. Number of Vehicles Used for Evacuation ................................................................................ 11 Figure F 10. Preferred Shelter Locations .................................................................................................... 11 Figure F 11. Households Evacuating with Pets .......................................................................................... 12 Figure F 12. Time Required to Prepare to Leave Work/College ................................................................ 12 Figure F 13. Work to Home Travel Time .................................................................................................... 13 Figure F 14. Time to Prepare Home for Evacuation................................................................................... 13 Figure F 15. Time to Clear Driveway of 6" 8" of Snow .............................................................................. 14 Figure G 1. Access Control Points for PPP ............................................................................................... G 4 Figure H 1. Region R01............................................................................................................................. H 3 Figure H 2. Region R02............................................................................................................................. H 4 Figure H 3. Region R03............................................................................................................................. H 5 Figure H 4. Region R04............................................................................................................................. H 6 Figure H 5. Region R05............................................................................................................................. H 7 Figure H 6. Region R06............................................................................................................................. H 8 Figure H 7. Region R07............................................................................................................................. H 9 Figure H 8. Region R08........................................................................................................................... H 10 Figure H 9. Region R09........................................................................................................................... H 11 Figure H 10. Region R10......................................................................................................................... H 12 Figure H 11. Region R11......................................................................................................................... H 13 Figure H 12. Region R12......................................................................................................................... H 14 Figure H 13. Region R13......................................................................................................................... H 15 Figure J 1. Network Sources/Origins.......................................................................................................... J 5 Figure J 2. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather (Scenario 1) .............. J 6 Figure J 3. ETE and Trip Generation: Summer, Midweek, Midday, Rain (Scenario 2) ............................... J 6 Figure J 4. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather (Scenario 3).............. J 7 Figure J 5. ETE and Trip Generation: Summer, Weekend, Midday, Rain (Scenario 4) .............................. J 7 Figure J 6. ETE and Trip Generation: Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5) ....................................................................................................................... J 8 Palisades Power Plant v KLD Engineering, P.C.

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Figure J 7. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather (Scenario 6) ................ J 8 Figure J 8. ETE and Trip Generation: Winter, Midweek, Midday, Rain (Scenario 7) ................................. J 9 Figure J 9. ETE and Trip Generation: Winter, Midweek, Midday, Snow (Scenario 8) ............................... J 9 Figure J 10. ETE and Trip Generation: Winter, Weekend, Midday, Good Weather (Scenario 9) ............ J 10 Figure J 11. ETE and Trip Generation: Winter, Weekend, Midday, Rain (Scenario 10)........................... J 10 Figure J 12. ETE and Trip Generation: Winter, Weekend, Midday, Snow (Scenario 11) ......................... J 11 Figure J 13. ETE and Trip Generation: Winter, Midweek, Weekend, Evening, Good Weather (Scenario 12)..................................................................................................... J 11 Figure J 14. ETE and Trip Generation: Summer, Weekend, Evening, Good Weather, Special Event (Scenario 13) ............................................................................................ J 12 Figure J 15. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather, Roadway Impact (Scenario 14) ...................................................................................... J 12 Figure K 1. PPP 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 Figure K 19. Link Node Analysis Network - Grid 18 ................................................................................K 20 Figure K 20. Link Node Analysis Network - Grid 19 ................................................................................K 21 Figure K 21. Link Node Analysis Network - Grid 20 ................................................................................K 22 Figure K 22. Link Node Analysis Network - Grid 21 ................................................................................K 23 Figure K 23. Link Node Analysis Network - 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 Network - Grid 28 ................................................................................K 30 Figure K 30. Link Node Analysis Network - Grid 29 ................................................................................K 31 Figure K 31. Link Node Analysis Network - Grid 30 ................................................................................K 32 Palisades Power Plant vi KLD Engineering, P.C.

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List of Tables Table 1 1. Stakeholder Interaction ........................................................................................................... 1 7 Table 1 2. Highway Characteristics ........................................................................................................... 1 7 Table 1 3. ETE Study Comparisons............................................................................................................ 1 8 Table 2 1. Evacuation Scenario Definitions...............................................................................................2 7 Table 2 2. Model Adjustment for Adverse Weather.................................................................................2 8 Table 3 1. EPZ Permanent Resident Population ......................................................................................3 11 Table 3 2. Permanent Resident Population and Vehicles by PAA ...........................................................3 11 Table 3 3. Shadow Population and Vehicles by Sector............................................................................3 11 Table 3 4. Summary of Transients and Transient Vehicles......................................................................3 12 Table 3 5. Summary of Employees and Employee Vehicles Commuting into the EPZ ............................3 12 Table 3 6. Medical Facility Transit Demand.............................................................................................3 13 Table 3 7. School Population Demand Estimates ....................................................................................3 14 Table 3 8. Demand Estimates for Homebound Population with Access and/or Functional Needs ........3 15 Table 3 9. Transit Dependent Population Estimates...............................................................................3 15 Table 3 10. Palisades EPZ External Traffic ............................................................................................... 3 16 Table 3 11. Summary of Population Demand..........................................................................................3 16 Table 3 12. Summary of Vehicle Demand................................................................................................3 17 Table 5 1. Event Sequence for Evacuation Activities..............................................................................5 11 Table 5 2. Time Distribution for Notifying the Public .............................................................................5 11 Table 5 3. Time Distribution for Commuters to Prepare to Leave Work/College ..................................5 11 Table 5 4. Time Distribution for Commuters to Travel Home ................................................................5 12 Table 5 5. Time Distribution for Population to Prepare Home to Evacuate...........................................5 12 Table 5 6. Time Distribution for Population to Clear 6" 8" of Snow ......................................................5 13 Table 5 7. Mapping Distributions to Events............................................................................................5 13 Table 5 8. Description of the Distributions.............................................................................................5 14 Table 5 9. Trip Generation Histograms for the EPZ Population for Unstaged Evacuation .....................5 15 Table 5 10. Trip Generation Histograms for the EPZ Population for Staged Evacuation .......................5 16 Table 6 1. Description of Evacuation Regions...........................................................................................6 4 Table 6 2. Evacuation Scenario Definitions...............................................................................................6 5 Table 6 3. Percent of Population Groups Evacuating for Various Scenarios ............................................6 6 Table 6 4. Vehicle Estimates by Scenario..................................................................................................6 7 Table 7 1. Time to Clear the Indicated Area of 90 Percent of the Affected Population...........................7 9 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 Region within the Indicated Region.........................7 11 Table 7 4. Time to Clear 100 Percent of the 2 Mile Region within the Indicated Region.......................7 12 Table 7 5. Description of Evacuation Regions......................................................................................... 7 13 Table 8 1. Summary of Transportation Resources ..................................................................................8 11 Table 8 2. School Evacuation Time Estimates Good Weather..............................................................8 13 Table 8 3. School Evacuation Time Estimates - Rain/Light Snow...........................................................8 15 Table 8 4. School Evacuation Time Estimates - Heavy Snow .................................................................8 17 Table 8 5. Transit Dependent Evacuation Time Estimates Good Weather ..........................................8 19 Table 8 6. Transit Dependent Evacuation Time Estimates - Rain/Light Snow.......................................8 20 Table 8 7. Transit Dependent Evacuation Time Estimates - Heavy Snow..............................................8 21 Table 8 8. Medical Facility Evacuation Time Estimates - Good Weather...............................................8 22 Table 8 9. Medical Facility Evacuation Time Estimates - Rain/Light Snow ............................................8 23 Palisades Power Plant vii KLD Engineering, P.C.

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Table 8 10. Medical Facility Evacuation Time Estimates - Heavy Snow.................................................8 24 Table 8 11. Homebound Population with Access and/or Functional needs Evacuation Time Estimates..........................................................................................8 25 Table 10 1. Summary of Transit Dependent Bus Routes.........................................................................10 2 Table 10 2. Bus Route Descriptions ......................................................................................................... 10 3 Table 10 3. Temporary Host Facilities .....................................................................................................10 5 Table A 1. Glossary of Traffic Engineering Terms .................................................................................... A 1 Table C 1. Selected Measures of Effectiveness Output by DYNEV II ........................................................C 9 Table C 2. Input Requirements for the DYNEV II Model .........................................................................C 10 Table C 3. Glossary..................................................................................................................................C 11 Table E 1. Schools and Preschools within the EPZ.................................................................................... E 2 Table E 2. Medical Facilities within the EPZ............................................................................................... E 3 Table E 3. Major Employers within the EPZ............................................................................................... E 3 Table E 4. Recreational Areas within the EPZ ............................................................................................ E 4 Table E 5. Marinas within the EPZ ............................................................................................................. E 5 Table E 6. Lodging Facilities within the EPZ .............................................................................................. E 6 Table F 1. Palisades Demographic Survey Sampling Plan ............................................................................ 6 Table G 1. List of Key Manual Traffic Control Locations........................................................................... G 3 Table G 2. ETE with No MTC ..................................................................................................................... G 3 Table H 1. Percent of PAA Population Evacuating for Each Region.......................................................... H 2 Table J 1. Sample Simulation Model Input ................................................................................................ J 2 Table J 2. Selected Model Outputs for the Evacuation of the Entire EPZ (Region R03) ........................... J 3 Table J 3. Average Speed (mph) and Travel Time (min) for Major Evacuation Routes (Region R03, Scenario 1)................................................................................... J 3 Table J 4. Simulation Model Outputs at Network Exit Links for Region R03, Scenario 1 ......................... J 4 Table K 1. Summary of Nodes by the Type of Control..............................................................................K 1 Table M 1. Evacuation Time Estimates for Trip Generation Sensitivity Study ........................................ M 5 Table M 2. Evacuation Time Estimates for Shadow Sensitivity Study ..................................................... M 5 Table M 3. Evacuation Time Estimates for Variation with Population Change....................................... M 6 Table M 4. Evacuation Time Estimates for Change in Average Household Size...................................... M 6 Table N 1. ETE Review Criteria Checklist ................................................................................................. N 1 Palisades Power Plant viii 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 Palisades Power Plant (PPP) located in Van Buren County, Michigan. ETE are part of the required planning basis and provide Entergy/Holtec 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:

Title 10, Code of Federal Regulations, Appendix E to Part 50 (10CFR50), Emergency Planning and Preparedness for Production and Utilization Facilities, NRC, 2011.

Revision 1 of the Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR 7002, February 2021.

FEMA, Radiological Emergency Preparedness Program Manual (FEMA P 1028),

December 2019.

Project Activities This project began in February 2021 and extended over a period of about 17 months. The major activities performed are briefly described in chronological sequence:

Attended kick off meetings with Entergy/Holtec personnel and emergency management personnel representing state and county governments.

Accessed the 2020 U.S. Census Bureau data files.

Estimated the number of employees who reside outside the Emergency Planning Zone (EPZ) and commute to work within the EPZ based upon data provided by the counties.

The plant employee data was provided by Entergy/Holtec.

Studied Geographic Information Systems (GIS) maps of the area in the vicinity of the plant, then conducted a detailed field survey of the highway network to observe any roadway changes relative to the previous ETE study done in 2012.

Updated the analysis network representing the highway system topology and capacities within the EPZ, plus a Shadow Region covering the region between the EPZ boundary and approximately 15 miles radially from the plant.

Designed and conducted an online demographic 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 instrument was reviewed and modified by the licensee and offsite response organization (ORO) personnel prior to the survey.

A data needs matrix (requesting data) was provided to Entergy/Holtec and the OROs at the kickoff meeting. Available data was provided by Allegan, Berrien, and Van Buren County emergency management officials for transient attractions, schools, and special Palisades Power Plant ES 1 KLD Engineering, P.C.

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facilities. Internet searches were also utilized where data was missing. If updated information was not provided or available, the data gathered for the 2012 ETE study was utilized (after being reviewed and confirmed as accurate by the OROs).

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

Following federal guidelines, the EPZ is subdivided into 7 Protective Action Areas (PAA).

These PAAs are then grouped within circular areas or keyhole configurations (circles plus radial sectors) that define a total of 13 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/Light Snow, Heavy Snow). One special event scenario, South Havens Fourth of July Celebration, was considered. One roadway impact scenario was considered wherein a single lane was closed on Interstate 196 northbound 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, Rev. 1, the Planning Basis for the calculation of ETE is:

A rapidly escalating accident at the PPP that quickly assumes the status of General Emergency such that the Advisory to Evacuate (ATE) 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 ATE 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 the temporary host facilities 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, wheelchair transport, or ambulance, as required.

Separate ETE are calculated for the transit dependent evacuees, for homebound population with access and/or functional needs, and for those evacuated from special facilities.

Palisades Power Plant ES 2 KLD Engineering, P.C.

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A final meeting was held with Entergy/Holtec personnel and emergency management personnel representing the OROs to present final results from the study.

Computation of ETE A total of 182 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 13 Evacuation Regions to evacuate from that Region, under the circumstances defined for one of the 14 Evacuation Scenarios (13 x 14 = 182). Separate ETE are calculated for transit dependent evacuees, including schoolchildren 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 ATE applies only to those people occupying the specified impacted region. It is assumed that 100% of the people within the impacted region will evacuate in response to this ATE. 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% and 100%, 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 Palisades Power Plant ES 3 KLD Engineering, P.C.

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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, Rev. 1.

Traffic Management This study reviewed, modeled and analyzed the existing comprehensive Traffic Management Plans (TMP) provided by Allegan, Berrien, and Van Buren Counties. Due to the limited traffic congestion within the EPZ, no additional Traffic Control Points (TCPs) or Access Control Points (ACPs) have been identified as a result of this study. Refer to Section 9 and Appendix G for additional information.

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.

Table 3 1 presents the estimates of permanent resident population in each PAA based on the 2020 Census data.

Table 6 1 defines each of the 13 Evacuation Regions in terms of their respective groups of PAA.

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% 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 when evacuating additional PAAs downwind to 5 miles for un staged and staged evacuations for the 90th and 100th percentiles, respectively.

Table 8 2 presents ETE for the schoolchildren in good weather.

Table 8 5 presents ETE for transit dependent population in good weather.

Table 8 8 presents ETE for the medical facilities in good weather.

Figure 6 1 displays a map of the PPP EPZ showing the layout of the 7 PAAs that comprise, in aggregate, the EPZ.

Figure H 5 presents an example of an Evacuation Region (Region R05) to be evacuated under the circumstances defined in Table 6 1. Maps of all regions are provided in Appendix H.

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Conclusions General population ETE were computed for 182 unique cases - a combination of 13 unique Evacuation Regions and 14 unique Evacuation Scenarios. Table 7 1 and Table 7 2 document these ETE for the 90th and 100th percentiles. These ETE range from 2:05 (hr:min) to 3:30 at the 90th percentile and 4:45 to 6:10 at the 100th 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 90th percentile. This is the result of the relatively long mobilization time of a small proportion of the resident population and some isolated traffic 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 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 7 through 7 20. Federal guidance recommends using the 90th percentile ETE in formulating protective action decisions.

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 adversely impacts evacuees located beyond 2 miles from the plant (compare Regions R02, R04 and R05 with Regions R11, R12 and R13, respectively, in Tables 7 1 and 7 2). See Section 7.6 for additional discussion.

Comparison of Scenarios 5 (summer, weekend, evening, good weather) and 13 (summer, weekend, evening, 4th of July Celebration) in Table 7 1 indicates that the special event significantly impacts (increases of up to 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 10 minutes) the 90th percentile ETE for Evacuation Regions wherein PAA 4 evacuates, but does not affect the 100th percentile ETE (Table 7 2). See Section 7.5 for additional discussion.

Comparison of Scenarios 1 and 14 in Table 7 1 indicates that the roadway closure - one lane northbound on I 196 from the interchange with County Road 378 (Exit 13) to the interchange with County Road 89 (Exit 32) - does not have a material impact on the ETE.

See Section 7.5 for additional discussion.

South Haven and Watervliet are the two most congested areas in the EPZ during an evacuation. Watervliet is the last location in the EPZ to be clear of traffic congestion. All congestion within the EPZ clears by 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> and 35 minutes after the ATE. See Section 7.3 and Figures 7 3 through 7 6.

Separate ETE were computed for schools, medical facilities, transit dependent persons and access and/or functional needs persons. The average single wave ETE for schools and medical facilities are less than the general population ETE at the 90th percentile. The average single wave ETE for transit dependent persons and access and/or functional needs persons exceed the 90th percentile ET for the general population. See Section 8.

Table 8 1 indicates that there are enough transportation resources to evacuate the schools, medical facilities, transit dependent population, and access and/or functional needs population within the EPZ in a single wave. Nonetheless, second wave ETE were Palisades Power Plant ES 5 KLD Engineering, P.C.

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computed for these populations in the event there is a shortfall of transportation resources or drivers. See Section 8.

The general population ETE at the 90th percentile is sensitive 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 /> and 45 minutes. See Table M 1.

The general population ETE is insensitive to the voluntary evacuation of vehicles in the Shadow Region. When the shadow percent is increased to 100%, the ETE only increases by 5 minutes. See Table M 2.

An increase in permanent resident population (EPZ plus Shadow Region) of 107% or greater results in an increase in the longest 90th percentile ETE of 30 minutes, which meets the federal criterion for performing a fully updated ETE study between decennial censuses. See Section M.3.

A decrease in the average household size from 2.77 people per household to 2.41 people per household results in approximately 15% more evacuating vehicles and increases the 90th percentile ETE by up to 25 minutes; 100th percentile ETE are not impacted. See Section M.4.

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Table 3 1. EPZ Permanent Resident Population PAA 2010 Population 2020 Population 1 1,548 1,463 2 2,205 2,019 3 2,221 1,841 4 10,356 10,040 5 14,675 14,231 6 0 0 7 0 0 EPZ TOTAL: 31,005 29,594 EPZ Population Growth (2010 2020): 4.55%

Table 6 1. Description of Evacuation Regions Radial Regions PAA Region Description 1 2 3 4 5 6 7 R01 2 Mile Region X X R02 5 Mile Region X X X X R03 Full EPZ X X X X X X X Evacuate 2 Mile Region and Downwind to 5 Miles Wind Direction PAA Region From (Degrees) 1 2 3 4 5 6 7 N/A 56 and <169 Refer to R01 R04 169 and <236 X X X N/A 236 and <303 Refer to R02 R05 303 and <56 X X X Evacuate 2 Mile Region and Downwind to the EPZ Boundary Wind Direction PAA Region From (Degrees) 1 2 3 4 5 6 7 R06 56 and <169 X X X R07 169 and <236 X X X X X R08 236 and <303 X X X X X X R09 303 and <348 X X X X R10 348 and <56 X X X X X Staged Evacuation 2 Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind Direction PAA Region From (Degrees) 1 2 3 4 5 6 7 R11 5 Mile Region X X X X N/A 56 and <169 Refer to R01 R12 169 and <236 X X X N/A 236 and <303 Refer to R11 R13 303 and <56 X X X PAA(s) Shelter in Place until PAA(s) Evacuate PAA(s) Shelter in Place 90% ETE for R01, then Evacuate Palisades Power Plant ES 7 KLD Engineering, P.C.

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Table 6 2. Evacuation Scenario Definitions Scenario Season1 Day of Week Time of Day Weather Special 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 Light 7 Winter Midweek Midday Rain/Snow None 8 Winter Midweek Midday Heavy Snow None 9 Winter Weekend Midday Good None Light 10 Winter Weekend Midday Rain/Snow None 11 Winter Weekend Midday Heavy Snow None Midweek, 12 Winter Weekend Evening Good None South Haven Fourth 13 Summer Weekend Evening Good of July Celebration Roadway Impact -

14 Summer Midweek Midday Good Lane Closure on I 196 Northbound 1

Winter means that school is in session at normal enrollment levels (also applies to spring and autumn). Summer means that school is in session at summer school enrollment levels (lower than normal enrollment).

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Table 7 1. Time to Clear the Indicated Area of 90 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Midday Midday Evening Midday Midday Evening Evening Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Radial Regions - 2 Mile, 5 Mile, Full EPZ R01 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R02 2:20 2:20 2:10 2:15 2:15 2:20 2:20 3:05 2:10 2:15 2:50 2:15 2:15 2:20 R03 2:40 2:40 2:20 2:25 2:25 2:45 2:45 3:30 2:25 2:25 3:15 2:25 3:15 2:45 Evacuate 2 Mile Radius and Downwind to 5 Mile Radius R04 2:15 2:15 2:10 2:10 2:15 2:15 2:15 2:55 2:10 2:10 2:40 2:15 2:15 2:15 R05 2:15 2:15 2:10 2:10 2:15 2:15 2:15 2:45 2:10 2:10 2:30 2:10 2:15 2:15 Evacuate 2 Mile Radius and Downwind to the EPZ Boundary R06 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R07 2:35 2:35 2:15 2:15 2:20 2:35 2:35 3:25 2:15 2:15 3:05 2:20 3:30 2:40 R08 2:40 2:40 2:20 2:25 2:25 2:45 2:45 3:30 2:25 2:25 3:15 2:25 3:15 2:45 R09 2:35 2:35 2:20 2:25 2:25 2:40 2:40 3:30 2:20 2:25 3:10 2:25 2:25 2:35 R10 2:35 2:35 2:20 2:25 2:25 2:40 2:40 3:30 2:20 2:25 3:10 2:25 2:25 2:35 Staged Evacuation 2 Mile Radius Evacuates, then Evacuate Downwind to 5 Mile Radius R11 2:35 2:35 2:30 2:30 2:35 2:35 2:35 3:05 2:30 2:30 2:50 2:35 2:35 2:35 R12 2:30 2:30 2:30 2:30 2:35 2:30 2:30 2:55 2:30 2:30 2:40 2:35 2:35 2:30 R13 2:25 2:25 2:20 2:20 2:25 2:25 2:25 2:45 2:20 2:20 2:35 2:25 2:25 2:25 Palisades Power Plant ES 9 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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Midday Midday Evening Midday Midday Evening Evening Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Radial Regions - 2 Mile, 5 Mile, Full EPZ R01 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R02 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 R03 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 5:00 4:55 Evacuate 2 Mile Radius and Downwind to 5 Mile Radius R04 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 R05 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 Evacuate 2 Mile Radius and Downwind to the EPZ Boundary R06 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:10 4:45 4:45 6:10 4:45 4:45 4:45 R07 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 5:00 4:55 R08 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 5:00 4:55 R09 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 4:55 4:55 R10 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 4:55 4:55 Staged Evacuation 2 Mile Radius Evacuates, then Evacuate Downwind to 5 Mile Radius R11 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 R12 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 R13 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 Palisades Power Plant ES 10 KLD Engineering, P.C.

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Table 7 3. Time to Clear 90 Percent of the 2 Mile Region within the Indicated Region Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Midday Midday Evening Midday Midday Evening Evening Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Unstaged Evacuation 2 Mile Region and 5 Mile Region R01 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R02 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 Unstaged Evacuation 2 Mile Region and Keyhole to 5 Miles R04 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R05 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 Staged Evacuation 2 Mile Region and Keyhole to 5 Miles R11 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R12 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R13 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 Palisades Power Plant ES 11 KLD Engineering, P.C.

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Table 7 4. Time to Clear 100 Percent of the 2 Mile Region within the Indicated Region Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Midday Midday Evening Midday Midday Evening Evening Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Unstaged Evacuation 2 Mile Region and 5 Mile Region R01 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R02 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 Unstaged Evacuation 2 Mile Region and Keyhole to 5 Miles R04 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R05 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 Staged Evacuation 2 Mile Region and Keyhole to 5 Miles R11 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R12 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R13 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 Palisades Power Plant ES 12 KLD Engineering, P.C.

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Table 8 2. School Evacuation Time Estimates - Good Weather Travel Time Travel Dist. from Time to EPZ EPZ Driver Loading Dist. To Average EPZ Bdry to Bdry to ETA to Mobilization Time EPZ Bdry Speed Bdry ETE THF THF THF School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

ALLEGAN COUNTY, MI Baseline Middle School 90 15 4.5 55.0 5 1:50 14.7 17 2:10 North Shore Elementary School 90 15 3.9 55.0 5 1:50 14.7 17 2:10 BERRIEN COUNTY, MI Salem Lutheran Preschool 90 15 1.4 21.9 4 1:50 15.1 17 2:10 Watervliet North Elementary School 90 15 1.0 9.3 7 1:55 0.4 1 2:00 Coloma Elementary School 90 15 0.9 25.3 3 1:50 15.1 17 2:10 Coloma Intermediate School 90 15 0.9 25.3 3 1:50 15.1 17 2:10 Coloma High School 90 15 0.9 25.3 3 1:50 15.1 17 2:10 Coloma Junior High School 90 15 0.9 25.3 3 1:50 15.1 17 2:10 VAN BUREN COUNTY, MI Maple Grove Elementary School 90 15 7.5 55.0 9 1:55 14.7 17 2:15 Head Start South Haven 90 15 7.0 50.1 9 1:55 14.7 17 2:15 Covert Middle School 90 15 10.1 30.6 20 2:05 0.6 1 2:10 Covert High School 90 15 10.1 30.6 20 2:05 0.6 1 2:10 Covert Elementary School 90 15 10.1 30.6 20 2:05 0.6 1 2:10 Head Start Migrant at Lincoln Elementary 90 15 7.0 44.8 10 1:55 14.7 17 2:15 Lincoln Elementary School 90 15 7.0 44.8 10 1:55 14.7 17 2:15 L.C. Mohr High School 90 15 7.0 44.8 10 1:55 14.7 17 2:15 St. Paul Lutheran School 90 15 6.9 52.9 8 1:55 14.7 17 2:15 St. Basil Catholic School 90 15 6.9 46.1 9 1:55 14.7 17 2:15 WAY South Haven Schools (LMC Campus) 90 15 5.7 55.0 7 1:55 14.7 17 2:15 Lake Michigan College South Haven 90 15 5.7 55.0 7 1:55 14.7 17 2:15 Campus Palisades Power Plant ES 13 KLD Engineering, P.C.

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Travel Time Travel Dist. from Time to EPZ EPZ Driver Loading Dist. To Average EPZ Bdry to Bdry to ETA to Mobilization Time EPZ Bdry Speed Bdry ETE THF THF THF School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

Wood School 90 15 4.0 41.2 6 1:55 14.2 16 2:15 Bangor High School 90 15 0.4 19.5 2 1:50 14.2 16 2:10 Bangor Middle School 90 15 0.4 19.5 2 1:50 14.2 16 2:10 Head Start Bangor 90 15 0.4 19.5 2 1:50 14.2 16 2:10 Bangor Alternative High School 90 15 0.4 19.5 2 1:50 14.2 16 2:10 South Walnut Elementary School 90 15 0.4 19.5 2 1:50 14.2 16 2:10 Maximum for EPZ: 2:05 Maximum: 2:15 Average for EPZ: 1:55 Average: 2:15 Palisades Power Plant ES 14 KLD Engineering, P.C.

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Table 8 5. Transit Dependent Evacuation Time Estimates - Good Weather One Wave Two Wave Route Distance Travel Route Route Route Travel Pickup to Rec. Time to Driver Travel Pickup Route Number Mobilization Length Speed Time Time ETE Ctr. Rec. Ctr. Unload Rest Time Time ETE Number of Buses (min) (miles) (mph) (min) (min) (hr:min) (miles) (min) (min) (min) (min) (min) (hr:min) 1 1 150 9.8 55.0 11 30 3:15 8.3 9 5 10 30 30 4:40 2 1 150 9.0 55.0 10 30 3:10 14.7 16 5 10 36 30 4:50 3 1 150 8.6 51.0 10 30 3:15 0.4 0 5 10 20 30 4:20 2 150 5.8 48.3 7 30 3:10 14.7 16 5 10 29 30 4:40 4

2 170 5.8 48.5 7 30 3:30 14.7 16 5 10 29 30 5:00 2 150 6.2 46.8 8 30 3:10 14.2 15 5 10 30 30 4:40 5

1 170 6.2 47.2 8 30 3:30 14.2 15 5 10 30 30 5:00 2 150 7.8 55.0 9 30 3:10 14.4 16 5 10 33 30 4:45 6

1 170 7.8 55.0 9 30 3:30 14.4 16 5 10 33 30 5:05 Maximum ETE: 3:30 Maximum ETE: 5:05 Average ETE: 3:20 Average ETE: 4:50 Palisades Power Plant ES 15 KLD Engineering, P.C.

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Table 8 8. Medical Facility Evacuation Time Estimates - Good Weather Travel Loading Time to Rate Total EPZ Mobilization (min per Loading Dist. To EPZ Boundary ETE Medical Facility Patient (min) person) People Time (min) Bdry (mi) (min) (hr:min)

Ambulatory 90 1 43 30 4.9 6 2:10 Country Side Nursing Wheelchair bound 90 5 46 75 4.9 6 2:55 Home Bedridden 90 15 4 30 4.9 6 2:10 Forest Beach AFC Home Inc Ambulatory 90 1 16 16 1.4 10 2:00 Ambulatory 90 1 2 2 1.3 8 1:40 Juniper Home Wheelchair bound 90 5 4 20 1.3 8 2:00 Ambulatory 90 1 3 3 6.8 7 1:40 Bronson South Haven Wheelchair bound 90 5 2 10 6.8 7 1:50 Hospital Bedridden 90 15 1 15 6.8 8 1:55 South Haven Nursing & Ambulatory 90 1 10 10 6.8 7 1:50 Rehabilitation Community Wheelchair bound 90 5 51 75 6.8 7 2:55 Ambulatory 90 1 3 3 8.9 10 1:45 Turner Tender Care Wheelchair bound 90 5 3 15 8.9 10 1:55 Ambulatory 90 1 26 26 4.8 5 2:05 River Ridge Retirement Wheelchair bound 90 5 13 65 4.8 5 2:40 Village Bedridden 90 15 3 30 4.8 5 2:05 Maximum ETE: 2:55 Average ETE: 2:05 Palisades Power Plant ES 16 KLD Engineering, P.C.

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Figure 6 1. PAAs Comprising the PPP EPZ Palisades Power Plant ES 17 KLD Engineering, P.C.

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Figure H 5. Region R05 Palisades Power Plant ES 18 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 Palisades Power Plant (PPP), located in Van Buren County, Michigan. 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 Government agencies. Most important of these are:

• Title 10, Code of Federal Regulations, Appendix E to Part 50 (10CFR50), Emergency Planning and Preparedness for Production and Utilization Facilities, NRC, 2011.

• Revision 1 of the Criteria for Development of Evacuation Time Estimate Studies, NUREG/CR 7002, February 2021.

• FEMA, Radiological Emergency Preparedness Program Manual (FEMA P 1028),

December 2019.

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.

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 Entergy/Holtec.

b. Attended meetings with emergency planners from the State of Michigan and Allegan, Berrien and Van Buren County Emergency Management Offices 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.

d. Obtained demographic data from the 2020 Census (See Section 3.1).

e. Conducted an online demographic survey of EPZ residents.

f. Conducted a data collection effort to identify and describe schools, special facilities, major employers, tourist attractions, 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 online demographic survey.

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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 (TMP) to be implemented by local and state police in the event of an incident at the plant. Traffic and access control is applied at specified Traffic Control Points (TCP) and Access Control Points (ACP) located within the EPZ.

5. Used existing Protective Action Areas (PAA) to define Evacuation Regions. The EPZ is partitioned into 7 PAA along political and geographic boundaries. Regions are groups of contiguous PAA 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, Rev. 1.

6. Estimated demand for transit services for persons at Special Facilities (schools, medical facilities, etc.) and for transit dependent persons at home.

7. Prepared the input streams for the DYNEV II system, which computes ETE (see Appendices B and C).

a. Estimated the evacuation traffic demand, based on the available information derived from Census data, and from data provided by local and state agencies, Entergy/Holtec and from the demographic survey.

b. Updated the link node representation of the evacuation network, using observations from the field survey and aerial imagery, which is used as the basis for the computer analysis that calculates the ETE.

c. Applied the procedures specified in the 2016 Highway Capacity Manual (HCM1) to the data acquired during the field survey, to estimate the capacity of all highway segments comprising the evacuation routes.

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

8. Executed the DYNEV II models to provide the estimates of evacuation routing and 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, Rev. 1.

10. Calculated the ETE for all transit activities including those for special facilities, for the transit dependent population and for homebound population with access and/or functional needs.

1 Highway Capacity Manual (HCM 2016), Transportation Research Board, National Research Council, 2016.

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1.2 The Palisades Power Plant Location The PPP is located on the shores of Lake Michigan in Van Buren County, Michigan. The site is approximately 55 miles southwest of Grand Rapids, Michigan and 75 miles northeast of Chicago, Illinois. The EPZ consists of parts of Allegan, Berrien and Van Buren Counties. Figure 1 1 displays the area surrounding the PPP, identifying the communities in the area and the major roads.

1.3 Preliminary Activities These activities are described below.

Field Surveys of the Highway Network In March 2021, 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 listed in Table 1 2.

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 2016 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 46 in the HCM 2016 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 Geographic 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 6 of the HCM 2016, the capacity of a two lane highway is 1,700 passenger cars per hour in one direction. For freeway sections, a value of 2,250 vehicles per hour per lane is assigned, as per Exhibit 12 37 of the HCM 2016. 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 46. 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.

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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, Rev. 1 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.

Demographic Survey A demographic 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 responses.

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).

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 (O) 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 Palisades Power Plant 14 KLD Engineering, P.C.

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(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 plant.

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 countermeasures may then be tested with the model.

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1.4 Comparison with Prior ETE Study Table 1 3 presents a comparison of the present ETE study with the previous ETE study (KLD TR 500, dated August 2012). The 90th percentile ETE for the entire EPZ increased by 40 minutes for a winter midweek midday scenario and by 15 minutes for a summer weekend midday scenario when compared with the 2012 study. The 100th percentile ETE increased by 15 minutes for both a winter midweek midday scenario and for a summer weekend midday scenario. 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:

Although the permanent resident population decreased by 4.55%, the number of evacuating vehicles (approximately 16,000 vehicles) for the permanent resident population is comparable with the 2012 study. Similarly, the number of evacuating vehicles from the Shadow Region from the 2012 and current studies are nearly the same. Thus, permanent resident population change should have minimal impact on ETE.

The transient population and number of transient vehicles increased by 12.5% and 8.6%,

respectively, mostly due to more seasonal population identified in this study. This could lead to longer ETE for weekend scenarios when transient population is at its peak.

Trip generation and mobilization characteristics have changed. The time to mobilize 100% of residents with commuters and residents without commuters takes an additional 15 minutes in this study relative to the 2012 study. This directly explains the 15 minute increase in 100th percentile ETE given that traffic congestion clears well before mobilization time (see Section 7.3) and trip generation times dictate the ETE.

The increases in 90th percentile ETE can also be explained by changes in mobilization time:

o It took 150 minutes to mobilize about 90% of residents with commuters returning in the 2012 study versus 180 minutes in this study, a difference of 30 minutes.

o It took 105 minutes to mobilize 90% of residents without commuters returning in the 2012 study versus 150 minutes in this study, a difference of 45 minutes.

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Table 1 1. Stakeholder Interaction Stakeholder Nature of Stakeholder Interaction Attended kickoff meeting to define project methodology and data requirements. Set up contacts with local government agencies. Provided Entergy/Holtec emergency planning personnel recent plant employee data. Reviewed and approved all project assumptions. Engaged in the ETE development and was informed of the study results and coordinated with the OROs.

Attended kickoff meeting to discuss the project methodology, key project assumptions and to define data needs. Provided state and county State of Michigan and Allegan, Berrien and Van emergency plans, special facility data and existing Buren County Emergency Management Offices traffic management plans. Reviewed and approved all project assumptions. Engaged in the ETE development and was informed of the study results.

Table 1 2. Highway Characteristics Number of lanes Posted speed Lane width Actual free speed Shoulder type & width Abutting land use Interchange geometries Control devices Lane channelization & queuing Intersection configuration (including capacity (including turn bays/lanes) roundabouts where applicable)

Geometrics: curves, grades (>4%) Traffic signal type Unusual characteristics: Narrow bridges, sharp curves, poor pavement, flood warning signs, inadequate delineations, toll booths, etc.

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Table 1 3. ETE Study Comparisons Topic Previous ETE Study Current ETE Study ArcGIS Software using 2010 US ArcGIS Software using 2020 US Resident Population Census blocks; area ratio method Census blocks; area ratio method Basis used. used.

Population = 31,005 Population = 29,594 2.40 persons/household, 1.25 2.77 persons/household, 1.50 evacuating vehicles/household evacuating vehicles/household Resident Population yielding: 1.92 persons/vehicle. yielding: 1.85 persons/vehicle.

Vehicle Occupancy Resident vehicles = 16,169 Resident vehicles = 15,898 ArcGIS Software using 2010 US ArcGIS Software using 2020 US Census blocks; area ratio method Census blocks; area ratio method used. used.

Shadow Population Shadow Population = 24,296 Shadow Population = 23,192 Shadow vehicles = 12,698 Shadow vehicles = 12,446 Employee estimates based on Employee estimates based on information provided about major information provided about major employers in EPZ by the employers employers in EPZ by the employers themselves. 1.08 employees per themselves. 1.10 employees per Employee Population vehicle based on the telephone vehicle based on the demographic survey results. survey results.

Employees = 797 Employees = 753 Employee vehicles = 738 Employee vehicles = 684 Transient estimates based upon Transient estimates based upon information provided about transient information provided about transient attractions in EPZ, supplemented by attractions in EPZ, supplemented by observations of the facilities during observations of the facilities during the road survey and from aerial the road survey and from aerial Transient Population photography. Seasonal population photography. Seasonal population estimated using vacant household estimated using vacant household data from the U.S. Census Bureau. data from the U.S. Census Bureau.

Transients = 18,965 Transients = 21,347 Transient vehicles = 8,837 Transient vehicles = 9,596 Palisades Power Plant 18 KLD Engineering, P.C.

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Topic Previous ETE Study Current ETE Study Special facility population based on Medical facility population based on information provided by each county information provided by each county within the EPZ. within the EPZ.

Current census = 224 Current census = 230 Medical Facilities Buses Required = 7 Buses Required = 8 Wheelchair Buses Required = 10 Wheelchair Buses Required = 9 Wheelchair Vans Required = 0 Wheelchair Vans Required = 3 Ambulances Required = 6 Ambulances Required = 5 School population based on School population based on information provided by each county information provided by each county within the EPZ.

School Population within the EPZ. Current enrollment = 5,740 Current enrollment = 7,219 Buses required = 107 (excluding 109 Buses required = 105 private vehicles for commuter students at Lake Michigan College)

Voluntary evacuation 20% of the population within the EPZ, 20% of the population within the EPZ, from within EPZ in but not within the Evacuation Region but not within the Evacuation Region areas outside region to (see Figure 2 1) (see Figure 2 1) be evacuated 20% of people outside of the EPZ 20% of people outside of the EPZ Shadow Evacuation within the Shadow Region (see Figure within the Shadow Region (see Figure 7 2) 7 2)

Network Size 795 Links; 556 Nodes. 898 Links; 630 Nodes.

Field surveys conducted in November Field surveys conducted in March of Roadway Geometric of 2010. Major intersections were 2021. Major intersections were video Data video archived. archived.

Road capacities based on 2010 HCM. Road capacities based on HCM 2016.

Direct evacuation to designated Direct evacuation to designated School Evacuation Reception Center/ Temporary Host Reception Center/ Temporary Host Facilities. Facilities.

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Topic Previous ETE Study Current ETE Study Estimates based upon U.S. Census Estimates based upon U.S. Census data and the results of the data and the results of the telephone demographic survey. A total of 336 survey. A total of 733 people who do people who do not have access to a not have access to a vehicle, vehicle, requiring 13 buses to requiring 50 buses to evacuate. An Transit Dependent evacuate. An additional 55 additional 21 homebound people Population homebound people with access with access and/or functional needs and/or functional needs are reported are reported within the three within the three counties.

counties. Special transportation to Transportation needed to evacuate: 2 evacuate: 1 ambulance, 1 wheelchair ambulances, 3 wheelchair accessible accessible van, and 3 regular buses.

buses, and 3 regular buses.

76% of transit dependent persons 50% of transit dependent persons will ride out with a neighbor or friend Ridesharing will ride out with a neighbor or friend as per the demographic survey as per NUREG/CR 7002.

results.

Based on residential telephone Based on the demographic survey of survey of specific pre trip specific pre trip mobilization mobilization activities: activities:

Residents with commuters returning Residents with commuters returning leave between 30 and 270 minutes. leave between 30 and 285 minutes.

Trip Generation for Residents without commuters Residents without commuters Evacuation returning leave between 0 and 210 returning leave between 15 and 225 minutes. minutes.

Employees and transients leave Employees and transients leave between 0 and 105 minutes. between 0 and 105 minutes.

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

Normal, Rain/Light Snow, or Heavy Normal, Rain, or Snow. The capacity Snow. The capacity and free flow and free flow speed of all links in the speed of all links in the network are Weather network are reduced by 10% in the reduced by 10% in the event of event of rain and 20% for snow. rain/light snow and 15% and 25% for heavy snow, respectively.

Modeling DYNEV II System - Version 4.0.0.0 DYNEV II System - Version 4.0.20.0 Fourth of July celebration at North and South Beach in South Haven, MI. Fourth of July celebration at North Special Events Attracts approximately 15,000 and South Beach in South Haven, MI.

people, 35% of which are considered Attracts 33,899 transients.

transients.

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Topic Previous ETE Study Current ETE Study Transients: 4,302 Transients: 33,899 Vehicles: 1,434 Vehicles: 9,908 10 Regions (central sector wind 13 Regions (central sector wind direction and each adjacent sector direction and each adjacent sector Evacuation Cases technique used) and 14 Scenarios technique used) and 14 Scenarios producing 140 unique cases. producing 182 unique cases.

ETE reported for 90th and 100th ETE reported for 90th and 100th Evacuation Time percentiles. Results presented by percentiles. Results presented by Estimates Reporting Region and Scenario. Region and Scenario.

Winter Weekday Midday, Winter Weekday Midday, Evacuation Time Good Weather (Scenario 6): 2:05 Good Weather (Scenario 6): 2:45 Estimates for the entire EPZ, 90th Summer Weekend, Midday, Summer Weekend, Midday, percentile Good Weather (Scenario 3): 2:05 Good Weather (Scenario 3): 2:20 Winter Weekday Midday, Winter Weekday Midday, Evacuation Time Good Weather (Scenario 6): 4:40 Good Weather (Scenario 6): 4:55 Estimates for the entire EPZ, 100th Summer Weekend, Midday, Summer Weekend, Midday, percentile Good Weather (Scenario 3): 4:40 Good Weather (Scenario 3): 4:55 Palisades Power Plant 1 11 KLD Engineering, P.C.

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Figure 1 1. PPP Location Palisades Power Plant 1 12 KLD Engineering, P.C.

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Figure 1 2. PPP Link Node Analysis Network Palisades Power Plant 1 13 KLD Engineering, P.C.

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2 STUDY ESTIMATES AND ASSUMPTIONS This section presents the estimates and assumptions utilized in the development of the evacuation time estimates.

2.1 Data Estimates Assumptions

1. The permanent resident population is based on the 2020 U.S. Census population from the Census Bureau website1. A methodology, referred to as the area ratio method, is employed to estimate the population within portions of census blocks that are divided by Protective Action Area (PAA) boundaries. It is assumed that the population is evenly distributed across a census block in order to employ the area ratio method. (See Section 3.1.)

2. Estimates of employees who reside outside the Emergency Planning Zone (EPZ) and commute to work within the EPZ are based upon data provided by each county and by Entergy/Holtec. (See Section 3.4.)

3. Population estimates at transient and special facilities are based on the data from the previous ETE study confirmed and updated by the EPZ county emergency management agencies.

4. The relationship between permanent resident population and evacuating vehicles is based on the results of the recent online demographic survey (see Appendix F). Values of 2.77 persons per household and 1.50 evacuating vehicles per household are used for the permanent resident population.

5. Where data is not provided, the average household size is assumed to be the vehicle occupancy rate for transient facilities.

6. Employee vehicle occupancies are based on the results of the demographic survey. 1.10 employees per vehicle are used in the study. In addition, it is assumed there are two people per carpool, on average. (See Appendix F, sub section F.3.1 and Figure F 6.)

7. The maximum bus speed assumed within the EPZ is 55 mph based on state laws for buses and on average posted speed limits on major roadways within the EPZ.

8. Roadway capacity estimates are based on field surveys performed in 2021 (verified by aerial imagery), and the application of the Highway Capacity Manual 2016.

a. In accordance with NUREG/CR 7002, Rev. 1, only those roadway construction projects that are completed prior to the finalization of this report are considered in an ETE study. As no roadway projects were identified by Entergy/Holtec or the OROs, no future roadway improvement projects (affecting roadway capacity estimates) are considered in this study.

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2.2 Methodological Assumptions

1. The Planning Basis Assumption for the calculation of ETE is a rapidly escalating accident that requires evacuation, and includes the following2 (as per NRC guidance):

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

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

c. ETE is measured relative to the ATE.

2. The center point of the plant is located at the center of the containment building 42°19'22.1"N, 86°18'51.5"W.

3. The DYNEV II3 system is used to compute ETE in this study.

4. Evacuees will drive safely, travel radially away from the plant to the extent practicable given the highway network and obey all traffic control devices and traffic guides. All major evacuation routes are used in the analysis.

5. The existing EPZ and PAA boundaries are used. See Figure 3 1.

6. The Shadow Region extends to 15 miles radially from the plant or approximately 5 miles radially from the EPZ boundary, as per NRC guidance. See Figure 7 2.

7. One hundred percent (100%) of the people within the impacted keyhole will evacuate.

Twenty percent (20%) of the population within the Shadow Region and within PAAs of the EPZ not advised to evacuate will voluntarily evacuate, as shown in Figure 2 1, as per NRC guidance. Sensitivity studies explore the effect on ETE of increasing the percentage of voluntary evacuees in the Shadow Region (see Appendix M).

8. Shadow population characteristics (household size, evacuating vehicles per household, and mobilization time) are assumed to be the same as that of the permanent resident population within the EPZ.

9. The ETE is presented at the 90th and 100th percentiles in graphical and tabular format, as per NRC guidance. The percentile ETE is defined as the elapsed time from the ATE issued to a specific Region of the EPZ, to the time that Region is clear of the indicated percentile of evacuees.

10. This study does not assume that roadways are empty at the start of the evacuation.

Rather, there is an initialization period (often referred to as fill time in traffic simulation) wherein the anticipated traffic volumes from the start of the evacuation are 2

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 stages of an emergency.

3 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 DYNEV II model incorporates the latest technology in traffic simulation and in dynamic traffic assignment.

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loaded onto roadways in the study area. The amount of initialization/fill traffic that is on the roadways in the study area at the start of the evacuation depends on the scenario and the region being evacuated. See Section 3.11.

11. To account for boundary conditions (roadway conditions outside the study area that are not specifically modeled due to the limited radius of the study area) beyond the study area, this study assumes a 25% reduction in capacity on two lane roads and multi lane highways for roadways that have traffic signals downstream. The 25% reduction in capacity is based on the prevalence of actuated traffic signals in the study area and the fact that the evacuating traffic (main street) volume is more significant than the competing traffic (side street) volume at any downstream signalized intersections, thereby warranting a more significant percentage (75% in this case) of the signal green time. There is no reduction in capacity for freeways due to boundary conditions.

12. The ETE also includes consideration of through (External External, traffic that originates its trip outside of the study area and has its destination outside of the study area) trips during the time that such traffic is permitted to enter the evacuated Region. See Section 3.10.

2.3 Assumptions on Mobilization Times

1. Trip generation time (also known as mobilization time, or the time required by evacuees to prepare for the evacuation) are based upon the results of the recent online demographic survey (see Section 5 and Appendix F). It is assumed that stated events take place in sequence such that all preceding events must be completed before the current event can occur.

2. One hundred percent (100%) of the EPZ population can be notified within 45 minutes, in accordance with the 2019 Federal Emergency Management Agency (FEMA) Radiological Emergency Preparedness Program Manual.

3. Commuter percentages (and percentage of residents awaiting the return of a commuter) are based on the results of the demographic survey. According to the survey results, 86% of the households in the EPZ have at least 1 commuter; 58% of those households with commuters will await the return of a commuter before beginning their evacuation trip (see Appendix F, sub sections F.3.1 and F.3.2). Therefore, 50% (86% x 58% = 50%) of EPZ households will await the return of a commuter, prior to beginning their evacuation trip.

2.4 Transit Dependent Assumptions

1. The percentage of transit dependent people who will rideshare with a neighbor or friend is based on the results of the demographic survey. According to the survey results, 76%

of the transit dependent population will rideshare (see Appendix F, sub section F.3.1).

2. Buses are used to transport those without access to private vehicles:

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i. If schools and preschools are in session, transport (buses) will evacuate students directly to the designated temporary host facilities.

ii. Buses will evacuate children at preschools within the EPZ, as needed.

iii. Children at day cares within the EPZ are picked up by parents and evacuated in private vehicles.

iv. For the schools/preschools that are evacuated via buses, it is assumed no school children are picked up by their parents prior to the arrival of the buses.

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

b. Medical Facilities

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

ii. The percent breakdown of ambulatory (46%), wheelchair bound (50%)

and bedridden patients (4%) from the 2012 study are used to determine the number of ambulatory, wheelchair bound and bedridden patients at the medical facilities within the EPZ.

c. Transit dependent permanent residents:

i. Transit dependent general population is evacuated to reception centers.

ii. Access and/or functional needs population may require county assistance (ambulance, bus or wheelchair transport) to evacuate. This is considered separately from the general population ETE, as per NRC guidance.

iii. Households with 3 or more vehicles were assumed to have no need for transit vehicles.

d. Analysis of the number of required round trips (waves) of evacuating transit vehicles are presented.

e. Transport of transit dependent evacuees from reception centers to congregate care centers are not considered in this study.

3. Transit vehicle capacities:

a. School buses = 70 students per bus for primary schools/preschools and 50 students per bus for middle/high schools

b. Ambulatory transit dependent persons and medical facility patients = 30 persons per bus

c. Vans = 5 persons

d. Ambulances = 2 bedridden persons (includes advanced and basic life support)

e. Wheelchair vans = 4 wheelchair bound persons

f. Wheelchair buses = 15 wheelchair bound persons

4. Transit vehicles mobilization times, which are considered in ETE calculations:

a. School buses will arrive at schools and preschools to be evacuated within 90 minutes of the ATE.

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b. Transit dependent buses are mobilized when approximately 90% of residents with no commuters have completed their mobilization. If necessary, multiple waves of buses are utilized to gather transit dependent people who mobilize more slowly.

c. Vehicles will arrive at hospitals, medical facilities, and senior living facilities to be evacuated within 90 minutes of the ATE.

5. Transit Vehicle loading times:

a. Concurrent loading on multiple buses/transit vehicles is assumed.

b. School buses are loaded in 15 minutes.

c. Transit Dependent buses will require 1 minute of loading time per passenger.

d. Buses for hospitals and medical facilities will require 1 minute of loading time per ambulatory passenger.

e. Wheelchair transport vehicles will require 5 minutes of loading time per passenger.

f. Ambulances are loaded in 15 minutes per bedridden passenger.

6. Drivers for all transit vehicles are available.

2.5 Traffic and Access Control Assumptions

1. Traffic Control Points (TCP) and Access Control Points (ACP) as defined in the approved county and state emergency plans are considered in the ETE analysis, as per NRC guidance. See Appendix G.

2. TCP and ACP are staffed approximately 120 minutes after the ATE, as per NRC guidance.

It is assumed that no through traffic will enter the EPZ after this 120 minute time period.

3. All transit vehicles and other responders entering the EPZ to support the evacuation are unhindered by personnel manning TCPs and ACPs.

2.6 Scenarios and Regions

1. A total of 14 Scenarios representing different temporal variations (season, time of day, day of week) and weather conditions are considered. Scenarios to be considered are defined in Table 2 1:

a. The Fourth of July Celebration in South Haven is considered as the special event (single or multi day event that attracts a significant population into the EPZ; recommended by NRC guidance) for Scenario 13.

b. As per NRC guidance, one segment of one of the highest volume roadways is out of service or one lane outbound on a freeway must be closed for a roadway impact scenario. This study will consider the closure of one lane on I 196 northbound from the interchange with County Road 378/32nd Ave (Exit 13) to the interchange with Blue Star Highway (Exit 30) for the roadway impact scenario - Scenario 14.

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2. 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 at about the same time the evacuation advisory is issued. Thus, no weather related reduction in the number of transients who may be present in the EPZ is assumed.

It is further assumed that snow removal equipment is available, the appropriate agencies are clearing/treating the roads as they would normally during snow, and the roads are passable albeit at lower speeds and capacities.

3. Adverse weather affects roadway capacity and free flow speeds. Transportation research indicates capacity and speed reductions of about 10% for rain and a range of 10% to 25%

for snow. In accordance with Table 3 1 of Revision 1 to NUREG/CR 7002, this study assumes a 10% reduction in speed and capacity for rain/light snow and a speed and capacity reduction of 15% and 25%, respectively, for heavy snow. These factors are shown in Table 2 2.

4. Some evacuees will need additional time to clear their driveways and access the public roadway system for heavy snow scenarios. The distribution of time for this activity was gathered through the demographic survey of the public and takes up to 180 minutes (see Appendix F, Figure F 15). It is assumed that the time needed by evacuees to remove snow from their driveways is sufficient time for snow removal crews to mobilize and clear/treat the public roadway system.

5. Employment is reduced slightly in the summer for vacations.

6. Mobilization and loading times for transit vehicles are slightly longer in adverse weather.

Mobilization times are 10 minutes and 20 minutes longer in rain/light snow and heavy snow, respectively. Loading times for school buses are 5 minutes and 10 minutes longer in rain/light snow and heavy snow, respectively. Loading times for transit buses are 10 minutes and 20 minutes longer in rain/light snow and heavy snow, respectively. Refer to Table 2 2.

7. Regions are defined by the underlying keyhole or circular configurations as specified in Section 1.4 of NUREG/CR 7002, Rev. 1. These Regions, as defined, display irregular boundaries reflecting the geography of the PAAs included within these underlying configurations. All 16 cardinal and intercardinal wind direction keyhole configurations are considered. Regions to be considered are defined in Table 6 1. It is assumed that everyone within the group of PAAs forming a Region that is issued an ATE will, in fact, respond and evacuate in general accord with the planned routes.

8. Due to the irregular shapes of the PAAs, there are instances wherein a small portion of a PAA (a sliver) is within the keyhole and the population within that small portion is low (less than 500 people or 10% of the PAA population, whichever is less). Under those circumstances, the PAA would not be included in the Region so as to not evacuate large numbers of people outside of the keyhole for a small number of people that are actually in the keyhole, unless otherwise stated in the PAR document.

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9. Staged evacuation is considered as defined in NUREG/CR 7002, Rev. 1 - those people between 2 miles and 5 miles will shelter in place until 90% of the 2 Mile Region has evacuated, then they will evacuate. See Regions R11 through R13 in Table 6 1.

Table 2 1. Evacuation Scenario Definitions Time of Scenario Season4 Day of Week Day Weather Special 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, Weekend Evening Good None 6 Winter Midweek Midday Good None Light 7 Winter Midweek Midday Rain/Snow None Heavy 8 Winter Midweek Midday Snow None 9 Winter Weekend Midday Good None Light 10 Winter Weekend Midday Rain/Snow None Heavy 11 Winter Weekend Midday Snow None 12 Winter Midweek, Weekend Evening Good None South Haven Fourth 13 Summer Weekend Evening Good of July Celebration Roadway Impact -

14 Summer Midweek Midday Good Lane Closure on I 196 Northbound 4

Winter means that school is in session at normal enrollment levels (also applies to spring and autumn). Summer means that school is in session at summer school enrollment levels (lower than normal enrollment).

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Table 2 2. Model Adjustment for Adverse Weather Loading Free Mobilization Time Loading Time Time for Highway Flow for General Mobilization for School Transit Scenario Capacity* Speed* Population Time Buses Buses5 Rain/Light 10 minute 5 minute 10 minute 90% 90% No Effect Snow increase increase increase Clear driveway Heavy 20 minute 10 minute 20 minute 75% 85% before leaving home Snow increase increase increase (See Figure F 15)

• Adverse weather capacity and speed values are given as a percentage of good weather conditions.

Roads are assumed to be passable.

5 Does not apply to medical facilities and those with access and/or functional needs as loading times for these people are already conservative.

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Figure 2 1. Voluntary Evacuation Methodology Palisades Power Plant 29 KLD Engineering, P.C.

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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 2020 Census, 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 PPP EPZ indicates the need to identify four 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.

Seasonal Transients people who reside outside of the EPZ and enter the area and stay in accommodations other than hotels.

Employees people who reside outside of the EPZ and commute to work 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 PAA and by polar coordinate representation (population rose).

The PPP EPZ is subdivided into 7 PAAs. The PAAs comprising the EPZ are shown in Figure 3 1.

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3.1 Permanent Residents The primary source for estimating permanent population is the 2020 U.S. Census data with an availability date of September 16, 2021. The average household size (2.77 persons/household -

See Appendix F, Sub section F.3.1) and the number of evacuating vehicles per household (1.50 vehicles/household - See Appendix F, Sub section F.3.2) were adapted from the demographic survey.

The permanent resident population is estimated by cutting the census block polygons by the PAA and EPZ boundaries using GIS software. 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 the population within the EPZ. This methodology (referred to as the area ratio method) assumes that the population is evenly distributed across a census block. Table 3 1 provides permanent resident population within the EPZ, by PAA, for 2010 and for 2020 (based on the methodology above). As indicated, the permanent resident population within the EPZ has decreased by 4.55% since the 2010 Census.

To estimate the number of vehicles, the 2020 Census permanent resident population is divided by the average household size and multiplied by the average number of evacuating vehicles per household. 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 the PPP. This population rose was constructed using GIS software. Note, the 2020 Census includes residents living in group quarters, such as skilled nursing facilities, group homes, etc. These people are transit dependent (will not evacuate in personal vehicles) and are included in the special facility evacuation demand estimates. To avoid double counting vehicles, the vehicle estimates for these people have been removed. The resident vehicles in Table 3 2 and Figure 3 3 have been adjusted accordingly.

3.2 Shadow Population A portion of the population living outside the evacuation area extending to 15 miles radially from the PPP may elect to evacuate without having been instructed to do so. This area is called the Shadow Region. Based upon NUREG/CR 7002, Rev. 1 guidance, it is assumed that 20 percent of the permanent resident population, based on U.S. Census Bureau data, in the Shadow Region will elect to evacuate.

Shadow population characteristics (household size, evacuation 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. Similar to the EPZ resident vehicle estimates, resident vehicles at group quarters have been removed from the shadow population vehicle demand in Table 3 3 and Figure 3 5.

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3.3 Transient Population Transient population groups are defined as those people (who are not permanent residents, nor commuting employees or students) 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.

Data for transient facilities within the EPZ was provided by the counties within the EPZ. This data includes the number of transients and vehicles during the peak times. Where data was not provided, the maximum capacities of people or parking spaces were obtained by internet searches and aerial imagery. It is assumed that visitors travel to transient facilities as a family/household. As such, the average household size (2.77 persons/household - see Section 3.1) was used to estimate the number of transients and vehicles. The transient facilities within the PPP EPZ are summarized as follows:

Beaches - 2,027 transients and 638 vehicles; an average of 3.18 transients per vehicle Campgrounds - 3,849 transients and 1,513 vehicles; an average of 2.54 transients per vehicle (Note, recreational vehicles (RVs) at campgrounds are treated as 2 vehicles due to their larger size and more sluggish operating characteristics)

Golf Courses - 384 transients and 97 vehicles; an average of 3.96 transients per vehicle Marinas - 2,555 transients and 1,285 vehicles; an average of 1.99 transients per vehicle (Note, vehicles with boat trailers at marinas are treated as 1.5 vehicles)

Parks - 1,370 transients and 615 vehicles; an average of 2.23 transients per vehicle Casino - 5,000 transients and 2,500 vehicles; an average of 2.00 transients per vehicle Lodging Facilities - 2,586 transients and 971 vehicles; an average of 2.66 transients per vehicle Appendix E summarizes the transient data that was estimated for the EPZ. Tables E 4 and E 5 include the number of transients visiting recreational areas and marinas, while Table E 6 presents the number of transients at lodging facilities within the EPZ.

3.3.1 Seasonal Transient Population The PPP EPZ has a second category of transient population which is seasonal residents. These people will enter the area during the summer months and may stay considerably longer (several weeks or the entire season) than the average transient using a hotel or motel. The seasonal population use other lodging facilities such as condominiums, beach houses and summer rentals that otherwise would not be captured in a typical lodging population.

2020 census block data was used to estimate the seasonal resident population. Each census block includes information regarding the number of vacant and occupied households. An average vacant household percentage was calculated for the entire PPP EPZ (29.7%) using this data.

It is assumed that seasonal residents will be renting homes near the Lake Michigan shoreline.

Using only those census blocks that are within one mile of the shoreline, the number of seasonal homes was calculated. It is further assumed that 29.7% (EPZ average) of the vacant Palisades Power Plant 33 KLD Engineering, P.C.

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homes within these census blocks are not rental homes and are in fact vacant homes. The remaining households were considered to be seasonal households. An average household size of 2.77 persons per household was used to determine the seasonal transient population, and 1.50 evacuating vehicles per seasonal household was used to determine the number of seasonal transient vehicles.

It is estimated that there is an additional seasonal population of 3,576 transients and 1,977 transient vehicles within the PPP EPZ.

In total, there are 21,347 transients in the EPZ at peak times, evacuating in 9,596 vehicles (an average vehicle occupancy of 2.22 transients per vehicle). Table 3 4 presents the transient population and vehicle estimates by PAA. Figure 3 6 and Figure 3 7 present these data by sector and distance from the plant.

3.4 Employees Employees who work within the EPZ fall into three categories:

Those who live and work in the EPZ Those who live outside of the EPZ and commute to jobs within the EPZ Those who are migratory workers who commute into the EPZ daily to do agricultural work 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.

Employment data was provided by Entergy/Holtec and by Van Buren County, including the maximum shift employment and percentage of employees commuting into the EPZ. As per NUREG/CR 7002, Rev. 1 guidance, employers with 200 or more employees working in a single shift are considered as major employers. As such, the employers not meeting this criterion are not considered in this study.

Those of the third category were not considered in this study. Allegan, Berrien and Van Buren Counties estimate that the migratory workforce would constitute approximately 5% of the EPZ population during peak times. However, data on where these individuals are working is difficult to obtain because it can change on a daily basis. A sensitivity study was performed to determine the impact on ETE of changes in resident population. Table M 3 in Appendix M documents the results of this study; as indicated a 108% change (more than twenty one times the estimated migratory workforce) in population is needed to significantly impact on the ETE.

Therefore, considering the migratory workforce in this study would not have a significant effect on ETE.

To estimate the evacuating employee vehicles, a vehicle occupancy rate of 1.10 employees per vehicle obtained from the demographic survey (see Appendix F, Sub section F.3.1) was applied for all the major employers. Appendix E, Table E 3 includes the detailed information of each Palisades Power Plant 34 KLD Engineering, P.C.

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major employer. Table 3 5 presents employee and vehicle estimates commuting into the EPZ by PAA. Figure 3 8 and Figure 3 9 present these data by sector.

3.5 Medical Facilities Data for medical facilities identified within the EPZ were provided by the county emergency agencies, supplemented by internet searches where no data was provided. Table E 2 in Appendix E summarizes the data gathered for medical facilities. Table 3 6 presents the census of medical facilities in the EPZ. As shown in these tables, 230 people have been identified as living in, or being treated in, these facilities. This data includes the number of ambulatory, wheelchair bound and bedridden patients at each facility. The average breakdown of ambulatory (46%), wheelchair bound (50%) and bedridden patients (4%) from the 2012 ETE study was used to determine the number of ambulatory, wheelchair bound, and bedridden patients at the medical facilities wherein updated data was not provided.

The transportation requirements for the special facility population are also presented in Table 3 6. The number of ambulance runs is determined by assuming that up to 2 patients can be accommodated per ambulance trip; the number of wheelchair bus runs assumes up to 15 wheelchairs per trip; the number of wheelchair van runs assumes up to 4 wheelchairs per trip, and the number of bus runs estimated assumes 30 ambulatory patients per trip.

3.6 School Population Demand Table 3 7 presents the school population and transportation requirements for the direct evacuation of all schools within the EPZ for the 2020 2021 school year. This information was provided by the counties supplemented by internet searches where no data was provided. The column in Table 3 7 entitled Buses Required specifies the number of buses required for each school under the following set of assumptions and estimates:

No students will be picked up by their parents prior to the arrival of the buses.

While many high school students commute to school using private automobiles (as discussed in Section 2.4 of NUREG/CR 7002, Rev. 1), the estimate of buses required for school evacuation does not consider the use of these private vehicles, since the intent of schools is to evacuate all students by bus.

Bus capacity, expressed in students per bus, is set to 70 for primary schools and 50 for middle and high schools.

Those staff members who do not accompany the students will evacuate in their private vehicles.

No allowance is made for student absenteeism, which is typically 3 percent daily.

Commuter students at Lake Michigan College - South Haven Campus will use passenger vehicles. See Sub Section 3.6.1 below for more details.

The counties in the EPZ could introduce procedures whereby the schools are contacted prior to the dispatch of buses from the depot, to ascertain the current estimate of students to be evacuated. In this way, the number of buses dispatched to the schools will reflect the actual Palisades Power Plant 35 KLD Engineering, P.C.

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number needed. The need for buses would be reduced by any high school students who have evacuated using private automobiles (if permitted by school authorities). Those buses originally allocated to evacuate schoolchildren that are not needed due to children being picked up by their parents, can be gainfully assigned to service other facilities or those persons who do not have access to private vehicles or to ride sharing.

Table 10 3 presents a list of the host schools for each school in the EPZ. Students will be transported to these host schools where they will be subsequently retrieved by their respective families or guardians.

3.6.1 Commuter College There is one college campus within the EPZ: Lake Michigan College - South Haven Campus. It is located in PAA 4, 7.0 miles north northeast of the plant. Data provided by Van Buren County indicates the college has an enrollment of 400 students at this campus. Since the campus does not provide student living accommodations, all students commute to school. According to the previous ETE study, approximately 30% of these students commute from outside of the EPZ.

Thus, there are 120 (400 x 30%) commuting students. The remaining 280 (400 - 120) students who live within the EPZ are considered as permanent residents that have been included in Section 3.1. The vehicle occupancy rate for commuting students was obtained from the demographic survey (1.10 commuting students/vehicle obtained - See Appendix F, Sub Section F.3.1). As such, a total of 120 students and 109 (120 ÷ 1.10) vehicles were assigned to this commuter college.

3.7 Special Event A special event can attract large numbers of transients to the EPZ for short periods of time, creating a temporary surge in demand as per Section 2.5.1 of NUREG/CR 7002, Rev. 1. The county and state emergency management agencies were polled regarding potential special events in the EPZ. The only potential special event identified by the county and state agencies that attracts transients from outside the EPZ is the Fourth of July Celebration in South Haven.

Thus, the special event considered for this study is the annual Fourth of July Celebration held at both the North and South Beaches in South Haven. The data for this event was provided by the Executive Director of the South Haven/Van Buren County Convention and Visitors Bureau:

All parking spaces in the City of South Haven, including along all side streets from Baseline Road to the intersection of Monroe Blvd and Blue Star Highway and at least as far east as Blue Star Hwy are filled. Aerial imagery was used to estimate 6,346 parking spaces. Thus, there are 6,346 transient vehicles. It is assumed that there are 4 transients per vehicle, for a total of 25,384 transients There are approximately 1,075 seasonal/long term rental units that are members of the South Haven/Van Buren County Convention and Visitors Bureau. It is estimated that there are 2 vehicles and 4 people per rental unit for a total of 2,150 vehicles and 4,300 transients.

There are approximately 1,200 short term (Airbnb, VRBO, etc.) rentals in South Haven. It Palisades Power Plant 36 KLD Engineering, P.C.

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is estimated that there are 2 vehicles and 5 people per rental unit for a total of 2,400 vehicles and 6,000 transients.

As discussed in Section 3.3.1, there are 3,576 seasonal residents and 1,977 seasonal resident vehicles already considered in the EPZ; of those, 1,785 seasonal residents and 988 seasonal resident vehicles are in South Haven. These people/vehicles are subtracted from the Special Event vehicles to avoid double counting.

A total of 33,899 transients (25,384 + 4,300 + 6,000 - 1,785) and 9,908 transient vehicles (6,346

+ 2,150 + 2,400 988) are considered for this special event. The special event vehicle trips are generated utilizing the same mobilization distributions as transients. The special event vehicles are uniformly distributed amongst the roadways in South Haven.

3.8 Access and/or Functional Needs Population The county emergency management agencies have an annual registration for homebound (non institutionalized) people with access and/or functional needs. Based on data provided by Van Buren, Berrien, and Allegan Counties, there are an estimated 55 homebound people with access and/or functional needs who require transportation assistance to evacuate. Among them, 32, 19, and 4 people are within the Van Buren, Berrien, and Allegan County portions of the EPZ respectively. The percentage breakdown of bedridden (6%), wheelchair bound (38%),

and ambulatory (56%) people was provided by Van Buren County and was applied to Allegan and Berrien Counties as well to estimate the functional needs of the total homebound population with access and/or functional needs. Thus, 31 of these residents require buses, 21 require wheelchair buses/vans and 3 people need ambulances to evacuate. See Table 3 8.

3.9 Transit Dependent Population The demographic survey (see Appendix F) results were used to estimate the portion of the population requiring transit service, including:

• Those persons in households that do not have a vehicle available.

• Those persons in households that do have vehicle(s) that would not be available at the time the evacuation is advised.

In the latter group, the vehicle(s) may be used by a commuter(s) who does not return (or is not expected to return) home to evacuate the household. Table 3 9 presents estimates of transit dependent people. Note:

• Estimates of persons requiring transit vehicles include schoolchildren. For those evacuation scenarios where children are at school when an evacuation is ordered, separate transportation is provided for the schoolchildren. The actual need for transit vehicles by residents is thereby less than the given estimates. However, estimates of transit vehicles are not reduced when schools are in session.

• It is reasonable and appropriate to consider that many transit dependent persons will evacuate by ridesharing with neighbors, friends or family. For example, nearly 80% of Palisades Power Plant 37 KLD Engineering, P.C.

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those who evacuated from Mississauga, Ontario1 who did not use their own cars, shared a ride with neighbors or friends. Other documents report that approximately 70% of transit dependent persons were evacuated via ride sharing. Based on the results of the demographic survey (see Appendix F, sub section F.3.1), approximately 76% of the transit dependent population will rideshare.

The estimated number of bus trips needed to service transit dependent persons is based on an estimated average bus occupancy of 30 persons at the conclusion of the bus run. Transit vehicle seating capacities typically equal or exceed 60 children on average (roughly equivalent to 40 adults). If transit vehicle evacuees are two thirds adults and one third children, then the number of adult seats taken by 30 persons is 20 + (2/3 x 10) = 27. On this basis, the average load factor anticipated is (27/40) x 100 = 68%. Thus, if the actual demand for service exceeds the estimates of Table 3 9 by 50%, the demand for service can still be accommodated by the available bus seating capacity.

2 20 10 40 1.5 1.00 3

Table 3 9 indicates that transportation must be provided for 336 people. Therefore, a total of twelve (12) bus run is required from a capacity standpoint. In order to service all of the transit dependent population and have at least one bus drive through each of the PAAs to pick up transit dependent people, 13 buses are used in the ETE calculations. See Section 8.1 for further discussion. These buses are represented as two vehicles in the ETE simulations due to their larger size and more sluggish operating characteristics.

To illustrate this estimation procedure, we calculate the number of persons, P, requiring public transit or ride share, and the number of buses, B, required for the PPP EPZ:

Where:

A = Percent of households with commuters C = Percent of households who will not await the return of a commuter 10,684 0.189 2.04 1 0.856 0.417 0.492 2.98 2 0.856 0.417 1408 1 0.762 30 0.238 1,408 30 12 These calculations, based on the demographic survey results, are explained as follows:

• The total number of persons requiring public transit is the sum of such people in HH 1

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 77% (Page 5-10).

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with no vehicles, or with 1 or 2 vehicles that are away from home.

• The number of households (HH) is computed by dividing the EPZ population by the average household size (29,594 2.77) and is 10,684.

• There are no households with zero vehicles available.

• The members of HH with 1 vehicle away (18.9%), who are at home, equal (2.04 1).

The number of HH where the commuter will not return home is equal to (10,684 x 0.189 x 1.04 x 0.856 x 0.417), as 85.6% of EPZ households have a commuter, 41.7%

of which would not return home in the event of an emergency. The number of persons who will evacuate by public transit or ride share is equal to the product of these two terms.

• The members of HH with 2 vehicles that are away (49.2%), who are at home, equal (2.98 - 2). The number of HH where neither commuter will return home is equal to 10,684 x 0.492 x 0.98 x (0.856 x 0.417)2. The number of persons who will evacuate by public transit or ride share is equal to the product of these two terms (the last term is squared to represent the probability that neither commuter will return).

• Households with 3 or more vehicles are assumed to have no need for transit vehicles.

• The number of buses is computed based on 76.2% of the transit dependent population ridesharing with a neighbor or friend and a capacity of 30 people per bus.

The estimate of transit dependent population in Table 3 9 exceeds the number of registered transit dependent persons (access and/or functional needs population) in the EPZ (discussed in Section 3.8). This is consistent with the findings of NUREG/CR 6953, Volume 2, in that a large majority of the transit dependent population within the EPZs of U.S. nuclear plants does not register with their local emergency response agency.

3.10 External Traffic Vehicles will be traveling through the EPZ (external external trips which have their origins and destinations outside of the EPZ) 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 - I 194 and I 94. It is assumed that this traffic will continue to enter the EPZ during the first 120 minutes following the Advisory to Evacuate.

Average Annual Daily Traffic (AADT) data was obtained from the Michigan Department of Transportation using their interactive online traffic volume map 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 30th 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 10, for each of the routes considered. The DDHV is then multiplied by 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> (access control points - ACP - are assumed to be activated at 120 minutes Palisades Power Plant 39 KLD Engineering, P.C.

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after the advisory to evacuate) to estimate the total number of external vehicles loaded on the analysis network. As indicated, there are 7,950 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.

3.11 Background Traffic Section 5 discusses the time needed for the people in the EPZ to mobilize and begin their evacuation trips. As shown in Table 5 9, there are 15 time periods during which traffic is loaded on to roadways in the study area to model the mobilization time of people in the EPZ. Note, there is no traffic generated during the 15th time period, as this time period is intended to allow traffic that has already begun evacuating to clear the study area boundaries.

This study does not assume that roadways are empty at the start of the evacuation (Time Period 1). Rather, there is an initialization period (often referred to as fill time in traffic simulation) wherein the anticipated traffic volumes from the start of the evacuation are loaded onto roadways in the study area. The amount of initialization/fill traffic that is on the roadways in the study area at the start of the evacuation depends on the scenario and the region being evacuated (see Section 6). There are 1,699 vehicles on the roadways in the study area at the end of fill time for an evacuation of the entire EPZ (Region R03) under Scenario 3 (summer, weekend, midday, good weather) conditions.

3.12 Summary of Demand A summary of population and vehicle demand is summarized in Table 3 11 and Table 3 12, respectively. This summary includes all population groups described in this section. A total of 96,486 people and 46,896 vehicles are considered in this study.

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Table 3 1. EPZ Permanent Resident Population PAA 2010 Population 2020 Population 1 1,548 1,463 2 2,205 2,019 3 2,221 1,841 4 10,356 10,040 5 14,675 14,231 6 0 0 7 0 0 EPZ TOTAL: 31,005 29,594 EPZ Population Growth (2010 2020): 4.55%

Table 3 2. Permanent Resident Population and Vehicles by PAA PAA 2020 Population Resident Vehicles 1 1,463 789 2 2,019 1,091 3 1,841 993 4 10,040 5,369 5 14,231 7,656 6 0 0 7 0 0 EPZ TOTAL: 29,594 15,898 Table 3 3. Shadow Population and Vehicles by Sector Evacuating Sector Population Vehicles N 0 0 NNE 1,038 561 NE 1,536 833 ENE 1,406 746 E 2,071 1,109 ESE 1,462 784 SE 4,677 2,513 SSE 2,102 1,134 S 3,406 1,797 SSW 5,494 2,969 SW 0 0 WSW 0 0 W 0 0 WNW 0 0 NW 0 0 NNW 0 0 TOTAL: 23,192 12,446 Palisades Power Plant 3 11 KLD Engineering, P.C.

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Table 3 4. Summary of Transients and Transient Vehicles Seasonal Total Transient Seasonal Resident Total Transient PAA Transients Vehicles Residents Vehicles Transients Vehicles 1 792 230 591 322 1,383 552 2 314 107 118 68 432 175 3 1,052 526 113 62 1,165 588 4 9,151 3,781 2,207 1,223 11,358 5,004 5 6,462 2,975 547 302 7,009 3,277 6 0 0 0 0 0 0 7 0 0 0 0 0 0 EPZ TOTAL: 17,771 7,619 3,576 1,977 21,347 9,596 Table 3 5. Summary of Employees and Employee Vehicles Commuting into the EPZ PAA Employees Employee Vehicles 1 403 366 2 0 0 3 0 0 4 140 127 5 210 191 6 0 0 7 0 0 EPZ TOTAL: 753 684 Palisades Power Plant 3 12 KLD Engineering, P.C.

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Table 3 6. Medical Facility Transit Demand Wheel Wheel Wheel chair chair Current Ambu chair Bed Bus Bus Van Ambulance PAA Facility Name Municipality Capacity Census latory Bound ridden Runs Runs Runs Runs ALLEGAN COUNTY, MI 4 Country Side Nursing Home South Haven 93 93 43 46 4 2 4 0 2 Allegan County Subtotal: 93 93 43 46 4 2 4 0 2 BERRIEN COUNTY, MI 5 Forest Beach AFC Home Inc Watervliet 20 16 16 0 0 1 0 0 0 5 Juniper Home Watervliet 6 6 2 4 0 1 0 1 0 Berrien County Subtotal: 26 22 18 4 0 2 0 1 0 VAN BUREN COUNTY, MI 4 Bronson South Haven Hospital South Haven 8 6 3 2 1 1 0 1 1 South Haven Nursing & Rehabilitation South Haven 4 Community 88 61 10 51 0 1 4 0 0 4 Turner Tender Care South Haven 6 6 3 3 0 1 0 1 0 4 River Ridge Retirement Village South Haven 44 42 26 13 3 1 1 0 2 Van Buren County Subtotal: 146 115 42 69 4 4 5 2 3 TOTAL: 265 230 103 119 8 8 9 3 5 Palisades Power Plant 3 13 KLD Engineering, P.C.

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Table 3 7. School Population Demand Estimates Buses PAA School Name Enrollment Required ALLEGAN COUNTY, MI 4 Baseline Middle School 460 10 4 North Shore Elementary School 314 5 Allegan County Subtotal: 774 15 BERRIEN COUNTY, MI 5 Salem Lutheran Preschool 6 1 5 Watervliet North Elementary School 293 5 5 Coloma Elementary School 375 6 5 Coloma Intermediate School 375 8 5 Coloma High School 430 9 5 Coloma Junior High School 300 6 Berrien County Subtotal: 1,779 35 VAN BUREN COUNTY, MI 2 Maple Grove Elementary School 303 5 2 Head Start South Haven 40 1 3 Covert Middle School 73 2 3 Covert High School 102 3 3 Covert Elementary School 100 2 4 Head Start Migrant at Lincoln Elementary 15 1 4 Lincoln Elementary School 207 3 4 L.C. Mohr High School 522 11 4 St. Paul Lutheran School 73 2 4 St. Basil Catholic School 125 2 4 WAY South Haven Schools (LMC Campus) 30 1 4 Lake Michigan College South Haven Campus 400 109 5 Wood School 25 1 5 Bangor High School 360 8 5 Bangor Middle School 335 7 5 Head Start Bangor 47 1 5 Bangor Alternative High School 100 2 5 South Walnut Elementary School 330 5 Van Buren County Subtotal: 3,187 166 TOTAL: 5,740 216 Note: Total Buses Required for Lake Michigan College South Haven Campus is equal to the number of commuter student vehicles. See Section 3.6.1 for additional information.

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Table 3 8. Demand Estimates for Homebound Population with Access and/or Functional Needs Population Group Transportation Needed Population Vehicles deployed ALLEGAN COUNTY, MI Ambulatory Bus 2 1 Wheelchair bound Wheelchair Bus 2 1 Bedridden Ambulance 0 0 Allegan County Subtotal: 4 2 BERRIEN COUNTY, MI Ambulatory Bus 11 1 Wheelchair bound Wheelchair Bus 7 1 Bedridden Ambulance 1 1 Berrien County Subtotal: 19 3 VAN BUREN COUNTY, MI Ambulatory Bus 18 1 Wheelchair bound Wheelchair Bus 12 1 Bedridden Ambulance 2 1 Van Buren County Subtotal: 32 3 TOTAL: 55 8 Table 3 9. Transit Dependent Population Estimates Survey Average HH Survey Percent Size Survey Percent HH Survey Percent HH Total People Population with Indicated No. of Estimated with Indicated No. of Percent HH with Non People Estimated Requiring Requiring 2020 EPZ Vehicles No. of Vehicles with Returning Requiring Ridesharing Public Public Population 0 1 2 Households 0 1 2 Commuters Commuters Transport Percentage Transit Transit 29,594 0.00 2.04 2.98 10,684 0.00% 18.90% 49.20% 85.61% 41.73% 1,408 76.2% 336 1.1%

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Table 3 10. Palisades EPZ External Traffic Upstream Downstream Road Hourly External Direction AADT2 K Factor3 D Factor3 Node Node Name Volume Traffic 8089 89 I 94 Eastbound 24,008 0.107 0.5 1,284 2,568 8060 60 I 196 Southbound 24,008 0.107 0.5 1,284 2,568 8082 81 I 94 Westbound 26,300 0.107 0.5 1,407 2,814 TOTAL: 7,950 Table 3 11. Summary of Population Demand Schools, Transit Medical Preschools, Special Shadow External PAA Residents Dependent Transients4 Employees Facilities Colleges Event Population5 Traffic Total 1 1,463 17 1,383 403 0 0 0 0 0 3,266 2 2,019 23 432 0 0 343 0 0 0 2,817 3 1,841 21 1,165 0 0 275 0 0 0 3,302 4 10,040 114 11,358 140 208 2,146 33,899 0 0 57,905 5 14,231 161 7,009 210 22 2,976 0 0 0 24,609 6 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 Shadow Region 0 0 0 0 0 0 0 4,638 0 4,638 TOTAL: 29,594 336 21,347 753 230 5,740 33,899 4,638 0 96,537 2

MDOT Traffic Volumes Map 3

HCM 2016 4

Transients include seasonal population 5

Shadow Population has been reduced to 20%. Refer to Figure 2-1 for additional information.

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Table 3 12. Summary of Vehicle Demand Schools, Transit Medical Preschools, Special Shadow External PAA Residents Dependent Transients Employees Facilities Colleges Event Vehicles6 Traffic Total 1 789 2 552 366 0 0 0 0 0 1,709 2 1,091 2 175 0 0 12 0 0 0 1,280 3 993 2 588 0 0 14 0 0 0 1,597 4 5,369 8 5,004 127 37 179 7 9,908 0 0 20,632 5 7,656 12 3,277 191 5 118 0 0 0 11,259 6 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 Shadow Region 0 0 0 0 0 0 0 2,489 7,950 10,439 TOTAL: 15,898 26 9,596 684 42 323 9,908 2,489 7,950 46,916 NOTE: Buses represented as two passenger vehicles. Refer to Section 8 for additional information.

6 Shadow vehicles have been reduced to 20%

7 Includes 109 commuter vehicles for the students at Lake Michigan College - South Haven Campus Palisades Power Plant 3 17 KLD Engineering, P.C.

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Figure 3 1. PAAs Comprising the PPP EPZ Palisades Power Plant 3 18 KLD Engineering, P.C.

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Figure 3 2. Permanent Resident Population by Sector Palisades Power Plant 3 19 KLD Engineering, P.C.

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Figure 3 3. Permanent Resident Vehicles by Sector Palisades Power Plant 3 20 KLD Engineering, P.C.

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Figure 3 4. Shadow Population by Sector Palisades Power Plant 3 21 KLD Engineering, P.C.

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Figure 3 5. Shadow Vehicles by Sector Palisades Power Plant 3 22 KLD Engineering, P.C.

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Figure 3 6. Transient Population by Sector Palisades Power Plant 3 23 KLD Engineering, P.C.

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Figure 3 7. Transient Vehicles by Sector Palisades Power Plant 3 24 KLD Engineering, P.C.

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Figure 3 8. Employee Population by Sector Palisades Power Plant 3 25 KLD Engineering, P.C.

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Figure 3 9. Employee Vehicles by Sector Palisades Power Plant 3 26 KLD Engineering, P.C.

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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 2016 Highway Capacity Manual (HCM 2016). This section discusses how the capacity of the roadway network was estimated.

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. Service Volume (SV) 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 SV at the upper bound of LOS E, only.

Thus, in simple terms, the SV is the maximum traffic that can travel on a road and still maintain a certain perceived level of quality to a driver based on the A, B, C, rating system (LOS). Any additional vehicles above the SV would drop the rating to a lower letter grade.

This distinction is illustrated in Exhibit 12 37 of the HCM 2016. 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 (BFFS1) according to Exhibit 15 7 of the HCM. Consequently, lane and shoulder widths at the narrowest points were observed 1

A very rough estimate of BFFS might be taken as the posted speed limit plus 10 mph (HCM 2016, Page 15-15)

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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 vehicles speedometer and observing local traffic, under free flow conditions. Free flow speeds ranged from 25 to 75 mph.

Capacity is estimated from the procedures of the HCM 2016. For example, HCM Exhibit 7 1(b) shows the sensitivity of SV at the upper bound of LOS D to grade (capacity is the SV at the upper bound of LOS E).

The amount of traffic that can flow on a roadway is effectively governed by vehicle speed and spacing. The faster that vehicle can travel when closely spaced, the higher the amount of flow.

As discussed in Section 2.6, it is necessary to adjust capacity figures to represent the prevailing conditions. Adverse conditions like inclement weather, construction, and other incidents tend to slow traffic down and often, also increases vehicle to vehicle separation, thus decreasing the amount of traffic flow. Based on limited empirical data, weather conditions such as rain reduce the values of free flow speed and of highway capacity by approximately 10 percent. Over the last decade new studies have been made on the effects of rain/light snow and heavy snow on traffic capacity. These studies indicate a range of effects between 5 and 25 percent depending on wind speed and precipitation rates. As indicated in Section 2.6, we employ a reduction in free speed and in highway capacity of 10% for rain/light snow and a reduction in free speed and in highway capacity of 15% and 25% for heavy 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 county emergency plans are extensive and were adopted without change. See Appendix G for more information.

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

3600 3600 where:

Qcap,m = Capacity of a single lane of traffic on an approach, which executes 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, 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, Palisades Power Plant 43 KLD Engineering, P.C.

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The estimation of hm for specified values of hsat, F1, F2, ... is undertaken within the DYNEV II simulation model by a mathematical model2. The resulting values for hm always satisfy the condition:

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 2016.

The above discussion is necessarily brief given the scope of this evacuation time estimate (ETE) report and the complexity of the subject of intersection capacity. In fact, Chapters 19, 20 and 21 in the HCM 2016 address this topic. The factors, F1, F2,, influencing saturation flow rate are identified in equation (19 8) of the HCM 2016.

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 (Pm) 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 1 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 SV (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 SV increases as demand volume and density increase, until the SV 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 SV) 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 SV, VF, under congested conditions.

2 Lieberman, 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 Palisades Power Plant 44 KLD Engineering, P.C.

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The value of VF can be expressed as:

where:

R = Reduction factor which is less than unity 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 Levinson3 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 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 K for 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 ETE 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 46 in the HCM 2016 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.

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

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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 HCM 2016. 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.

4.3 Application to the PPP 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:

2016 Highway Capacity Manual (HCM 2016)

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 Multilane Highways (at grade)

Freeways Each of these classifications will be discussed.

4.3.1 Two Lane Roads Ref: HCM 2016 Chapter 15 Two lane roads comprise the majority of highways within the study area (EPZ and Shadow Region). The per lane capacity of a two lane highway is estimated at 1,700 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 3,200 pc/h.

The HCM 2016 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 study area, are classified as Class I, with "level terrain"; some are rolling terrain.

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

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4.3.2 Multilane Highway Ref: HCM 2016 Chapter 14 Exhibit 12 8 of the HCM 2016 presents a set of curves that indicate a per lane capacity ranging from approximately 1,900 to 2,200 pc/h, for free speeds of 45 to 70 mph, respectively. Based on observation, the multilane highways outside of urban areas within the study area service traffic with free speeds in this range. The actual time varying speeds computed by the simulation model reflect the demand to capacity relationship and the impact of control at intersections. A conservative estimate of per lane capacity of 1,900 pc/h is adopted for this study for multilane highways outside of urban areas, as shown in Appendix K.

4.3.3 Freeways Ref: HCM 2016 Chapters 10, 12, 13, 14 Chapter 10 of the HCM 2016 describes a procedure for integrating the results obtained in Chapters 12, 13 and 14, 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 12 of the HCM 2016 presents procedures for estimating capacity and LOS for Basic Freeway Segments". Exhibit 12 37 of the HCM 2016 presents capacity vs. free speed estimates, which are provided below.

Free Speed (mph): 55 60 65 70+

Per Lane Capacity (pc/h): 2,250 2,300 2,350 2,400 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 2,250 pc/h is adopted for this study for freeways, as shown in Appendix K.

Chapter 13 of the HCM 2016 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 13 depends on the "Type" and geometrics of the weaving segment and on the "Volume Ratio" (ratio of weaving volume to total volume).

Chapter 14 of the HCM 2016 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 14 10 of the HCM Palisades Power Plant 47 KLD Engineering, P.C.

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2016 and depend on the number of freeway lanes and on the freeway free speed. Ramp capacity is presented in Exhibit 14 12 and is a function of the ramp FFS. The DYNEV II simulation model logic simulates the merging operations of the ramp and freeway traffic in accord with the procedures in Chapter 14 of the HCM 2016. 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 2016 does not address LOS F explicitly).

4.3.4 Intersections Ref: HCM 2016 Chapters 19, 20, 21, 22 Procedures for estimating capacity and LOS for approaches to intersections are presented in Chapter 19 (signalized intersections), Chapters 20, 21 (un signalized intersections) and Chapter 22 (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. The type of traffic control for nodes in the evacuation network are noted in Appendix K..

4.4 Simulation and Capacity Estimation Chapter 6 of the HCM 2016 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 HCM chapters. Alternative tools are able to analyze these facilities 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 2016 - 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 Palisades Power Plant 48 KLD Engineering, P.C.

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by location. The DYNEV II simulation model includes some HCM 2016 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 these are: (1) 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 2016, as described earlier. These parameters are listed in Appendix K, for each network link.

It is important to note that simulation is a mathematical representation of an assumed set of conditions using the best available knowledge and understanding of traffic flow and available inputs. Simulation should not be assumed to be a prediction of what will happen under any event because a real evacuation can be impacted by an infinite number of things - many of which will differ from these test cases - and many others cannot be taken into account with the tools available.

4.5 Boundary Condition As illustrated in Figure 1 2 and in Appendix K, the link node analysis network used for this study is finite. The analysis network does extend well beyond the 15 mile radial study area in some locations in order to model intersections with other major evacuation routes beyond the study area. However, the network does have an end at the destination (exit) nodes as discussed in Appendix C. Beyond these destination nodes, there may be signalized intersections or merge points that impact the capacity of the evacuation routes leaving the study area. Rather than neglect these boundary conditions, this study assumes a 25% reduction in capacity on two lane roads (Section 4.3.1 above) and multilane highways (Section 4.3.2 above). There is no reduction in capacity for freeways due to boundary conditions. The 25% reduction in capacity is based on the prevalence of actuated traffic signals in the study area and the fact that the evacuating traffic volume will be more significant than the competing traffic volume at any downstream signalized intersections, thereby warranting a more significant percentage (75% in this case) of the signal green time.

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Volume, vph Capacity Drop Qmax R Qmax Qs Density, vpm Flow Regimes Speed, mph Free Forced vf R vc Density, vpm kf kopt kj ks Figure 4 1. Fundamental Diagrams Palisades Power Plant 4 10 KLD Engineering, P.C.

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5 ESTIMATION OF TRIP GENERATION TIME Federal guidance (see NUREG/CR 7002, Rev. 1) specify that the Evacuation Time Estimate (ETE) study 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 demographic 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 Section C of Part IV of Appendix E of 10 CFR 50 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 the state and local offsite agencies. As a Planning Basis, we will adopt a conservative posture, in accordance with Section 1.2 of NUREG/CR 7002, Rev. 1, that a rapidly escalating accident at the plant wherein evacuation is ordered promptly and no early protective actions have been implemented will be considered in calculating the Trip Generation time. We will assume:

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

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

3. The ETE are measured relative to the ATE.

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 ATE. 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 Emergency Planning Zone (EPZ) will be lower when the ATE 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 broadcasted. Thus, the time needed to complete the mobilization activities and the number of people remaining to Palisades Power Plant 51 KLD Engineering, P.C.

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evacuate the EPZ after the ATE, 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 and notification systems (ANS) 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 183 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, Rev. 1 the information required to compute trip generation times is typically obtained from a demographic survey of EPZ residents. Such a survey was conducted in support of this ETE study for this site. Appendix F discusses the survey sampling plan, documents the survey instrument utilized, and provides the 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 ETE 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 demographic 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" (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 in Table 5 1:

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)

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.

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.

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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.

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 Federal regulations (10CFR50 Appendix E, Item IV.D.3) stipulate, [t]he design objective of the prompt public alert and notification system shall be to have the capability to essentially complete the initial alerting and initiate notification of the public within the plume exposure pathway EPZ within about 15 minutes. Furthermore, the 2019 Federal Emergency Management Agency (FEMA) Radiological Emergency Preparedness (REP) Program Manual Part V, Section B.1, bullet 3 states that arrangements will be made to assure 100% coverage within 45 minutes of the population who may not have received the initial notification within the entire plume exposure EPZ.

Given the federal regulations and guidance, and the presence of sirens within the EPZ, it is assumed that 100% of the population in the EPZ can be notified within 45 minutes. The assumed distribution for notifying the EPZ population is provided in Table 5 2. The distribution is plotted in Figure 5 2.

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 demographic survey for employees working inside or outside of the EPZ who return home prior to evacuating and for commuting college students who return home prior to evacuating. This distribution is also applicable for residents to leave stores, restaurants, parks, and other locations within the EPZ.

This distribution is plotted in Figure 5 2.

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

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

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 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. Evacuation would not be prudent during an extreme blizzard.

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 demographic survey. This distribution is plotted in Figure 5 2 and listed in Table 5 6.

Note that those respondents (23% - see Appendix F, Figure F 15) who answered that they would not take time to clear their driveway were assumed to be ready immediately at the start of this activity. Essentially, they would drive through the snow on the driveway to access the roadway and begin their evacuation trip.

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 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.

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Table 5 8 presents a description of each of the final trip generation distributions achieved after the summing process is completed.

5.4.1 Statistical Outliers As already mentioned, some portion of the survey respondents answer decline to state 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 600 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 access and/or functional 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 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.,

access and/or functional needs, transit dependent) or lack of realism, because the purpose is to estimate trip generation patterns for personal vehicles; Palisades Power Plant 56 KLD Engineering, P.C.

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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. However, other flagged values between 3.5 and 4 standard deviations from the mean were also removed based on careful consideration.

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

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.

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 weighting based upon the probability distributions of each element; Figure 5 4 presents the combined trip generation distributions for each population group considered. 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 - travel home from work follows preparation to leave work; preparation for departure follows the return of the commuter; snow clearance follows the preparation for departure, and so forth. In practice, it is reasonable Palisades Power Plant 57 KLD Engineering, P.C.

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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 distribution results 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.

5.4.2 Staged Evacuation Trip Generation As defined in NUREG/CR 7002, Rev. 1, staged evacuation consists of the following:

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

2. PAAs 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 PAAs beyond 5 miles will shelter in place. A non compliance voluntary evacuation percentage of 20% is assumed for this population.

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.

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Procedure

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

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

a. Identify the 90th percentile evacuation time for the PAAs 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).

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; however, that was not the case for this site.

NUREG/CR 7002, Rev. 1, uses the statement approximately 90th percentile as the time to end staging and begin evacuating. The value of TScen* is 2:00 for all scenarios (see Region R01 in Table 7 1; average ETE is 2:08).

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 heavy snow conditions

d. Residents without returning commuters and heavy snow conditions Figure 5 5 presents the staged trip generation distributions for both residents with and without returning commuters and with and without heavy snow. The average 90th percentile two mile evacuation time is 128 minutes. At TScen*, 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 90th 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.

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5.4.3 Trip Generation for Waterways and Recreational Areas The Allegan County Emergency Operations Plan (Emergency Services Function 2 - ESF2 -

Warning & Communication) specifies that warnings will be provided to the local area through means such as the National Oceanic and Atmospheric Administration (NOAA) broadcast, AM and FM commercial radio stations, television stations, the local Emergency Alert System, as well as siren warning systems.

Additional information provided by Allegan, Berrien, and Van Buren Counties specifies that boaters on Lake Michigan will be notified through marine radio as well as marine patrol boats.

Recreational facilities will be notified through the facilities public address (PA) and warning systems. This information is also published in the Palisades Power Plant public information brochure.

As indicated in Table 5 2, this study assumes 100% notification in 45 minutes which is consistent with the 2019 FEMA REP Program Manual. Table 5 9 indicates that all transients will have mobilized within 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes. It is assumed that this 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 45 minutes timeframe is sufficient time for boaters, campers and other transients to return to their vehicles and begin their evacuation trip.

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Table 5 1. Event Sequence for Evacuation Activities Event Sequence Activity Distribution 1 2 Receive Notification 1 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 Table 5 2. Time Distribution for Notifying the Public Elapsed Time Percent of (Minutes) Population Notified 0 0%

5 7%

10 13%

15 27%

20 47%

25 66%

30 87%

35 92%

40 97%

45 100%

Table 5 3. Time Distribution for Commuters to Prepare to Leave Work/College Cumulative Percent Cumulative Percent Elapsed Time Commuters Leaving Elapsed Time Commuters Leaving (Minutes) Work/College (Minutes) Work/College 0 0% 40 90%

5 28% 45 91%

10 54% 50 91%

15 71% 55 91%

20 80% 60 98%

25 81% 65 99%

30 85% 70 99%

35 86% 75 100%

NOTE: The survey data was normalized to distribute the "Decline to State" 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 Decline to State responders, if the event takes place, would be the same as those responders who provided estimates.

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Table 5 4. Time Distribution for Commuters to Travel Home Cumulative Cumulative Elapsed Time Percent Elapsed Time Percent (Minutes) Returning Home (Minutes) Returning Home 0 0% 35 90%

5 15% 40 93%

10 42% 45 95%

15 59% 50 98%

20 73% 55 99%

25 78% 60 100%

30 86%

NOTE: The survey data was normalized to distribute the "Decline to State" response Table 5 5. Time Distribution for Population to Prepare Home to Evacuate Cumulative Elapsed Time Percent Ready to (Minutes) Evacuate 0 0%

15 6%

30 27%

45 45%

60 67%

75 79%

90 83%

105 84%

120 87%

135 94%

150 95%

165 96%

180 97%

195 100%

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Table 5 6. Time Distribution for Population to Clear 6" 8" of Snow Cumulative Elapsed Time Percent Ready to (Minutes) Evacuate 0 23%

15 43%

30 61%

45 73%

60 80%

75 86%

90 89%

105 92%

120 94%

135 98%

150 99%

165 99%

180 100%

NOTE: The survey data was normalized to distribute the "Decline to State" response Table 5 7. Mapping Distributions to Events Apply Summing Algorithm To: Distribution Obtained Event Defined Distributions 1 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 Palisades Power Plant 5 13 KLD Engineering, P.C.

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Table 5 8. Description of the Distributions Distribution Description 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).

Time distribution of residents with commuters who return home, leaving home C

to begin the evacuation trip (Event 5).

Time distribution of residents without commuters returning home, leaving home D

to begin the evacuation trip (Event 5).

Time distribution of residents with commuters who return home, leaving home E

to begin the evacuation trip, after snow clearance activities (Event 5).

Time distribution of residents with no commuters returning home, leaving to F

begin the evacuation trip, after snow clearance activities (Event 5).

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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 Residents With Without Residents with Without Commuters Commuters Time Duration Employees Transients Commuters Commuters Snow Snow Period (Min) (Distribution A) (Distribution A) (Distribution C) (Distribution D) (Distribution E) (Distribution F) 1 15 6% 6% 0% 0% 0% 0%

2 15 31% 31% 0% 4% 0% 1%

3 30 50% 50% 6% 31% 2% 13%

4 30 11% 11% 25% 36% 11% 25%

5 15 2% 2% 16% 9% 10% 12%

6 15 0% 0% 15% 3% 12% 10%

7 30 0% 0% 16% 7% 20% 13%

8 30 0% 0% 10% 6% 15% 11%

9 30 0% 0% 6% 2% 12% 7%

10 15 0% 0% 2% 2% 4% 2%

11 60 0% 0% 4% 0% 11% 5%

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

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

14 15 0% 0% 0% 0% 1% 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.

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Table 5 10. Trip Generation Histograms for the EPZ Population for Staged Evacuation Percent of Total Trips Generated Within Indicated Time Period*

Residents Residents Without Residents with Without Residents With Commuters Time Duration Commuters Commuters Commuters Snow Snow Period (Min) (Distribution C) (Distribution D) (Distribution E) (Distribution F) 1 15 0% 0% 0% 0%

2 15 0% 1% 0% 0%

3 30 1% 6% 0% 3%

4 30 5% 7% 3% 5%

5 15 3% 2% 2% 2%

6 15 3% 1% 2% 2%

7 30 66% 73% 48% 62%

8 30 10% 6% 15% 11%

9 30 6% 2% 12% 7%

10 15 2% 2% 4% 2%

11 60 4% 0% 11% 5%

12 30 0% 0% 1% 1%

13 30 0% 0% 1% 0%

14 15 0% 0% 1% 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.

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1 2 3 4 5 Residents Households wait 1

for Commuters Households without 1 2 5 Commuters and Residents households who do not wait for Commuters (a) Accident occurs during midweek, at midday; year round Residents, 1 2 4 5 Transients Return to residence, away from then evacuate Residence Residents, 1 2 5 Residents at home; Transients at transients evacuate directly Residence (b) Accident occurs during weekend or during the evening2 1 2 3, 5 (c) Employees who live outside the EPZ 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 Activities Consume Time 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 Palisades Power Plant 5 17 KLD Engineering, P.C.

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Mobilization Activities 100%

Percent of Population Completing Mobilization Activity 80%

60%

Notification Prepare to Leave Work/College Travel Home 40%

Prepare Home Time to Clear Snow 20%

0%

0 15 30 45 60 75 90 105 120 135 150 165 180 195 Elapsed Time from Start of Mobilization Activity (min)

Figure 5 2. Evacuation Mobilization Activities Palisades Power Plant 5 18 KLD Engineering, P.C.

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100.0%

90.0%

80.0%

70.0%

Cumulative Percentage (%)

60.0%

50.0%

40.0%

30.0%

20.0%

10.0%

0.0%

112.5 2.5 7.5 12.5 17.5 22.5 27.5 32.5 37.5 42.5 47.5 52.5 57.5 67.5 82.5 97.5 Center of Interval (minutes)

Cumulative Data Cumulative Normal Figure 5 3. Comparison of Data Distribution and Normal Distribution Palisades Power Plant 5 19 KLD 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 Percent of Population Beginning Evacuation Trip 80 60 40 20 0

0 60 120 180 240 300 360 420 Elapsed Time from Evacuation Advisory (min)

Figure 5 4. Comparison of Trip Generation Distributions Palisades Power Plant 5 20 KLD Engineering, P.C.

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Staged and Unstaged Evacuation Trip Generation Employees / Transients Residents with Commuters Residents with no Commuters Residents with Commuters and Snow Residents no Commuters with Snow Staged Residents with Commuters Staged Residents with no Commuters Staged Residents with Commuters (Snow)

Staged Residents with no Commuters (Snow) 100 Percent of Population Beginning Evacuation Trip 80 60 40 20 0

0 30 60 90 120 150 180 210 240 270 300 330 360 390 Elapsed Time from Evacuation Advisory (min)

Figure 5 5. Comparison of Staged and Unstaged Trip Generation Distributions in the 2 to 5 Mile Region Palisades Power Plant 5 21 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 PAA 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 13 Regions were defined which encompass all the groupings of PAAs considered.

These Regions are defined in Table 6 1. The PAA 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 and R05) or to the EPZ boundary (Regions R06 through R10).

Regions R01, R02 and R03 represent evacuations of circular areas with radii of 2, 5 and 10 miles, respectively. Regions R11 through R13 are identical to Regions R02, R04 and R05, respectively; however, those PAAs 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 13 x 14 = 182 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; 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 86% (the number of households with at least one commuter) and 58%

(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.

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 Palisades Power Plant 61 KLD Engineering, P.C.

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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% of all households vacation for a period over the summer.

Assume these vacations, in aggregate, are uniformly dispersed over 10 weeks, i.e., 10%

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% 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.

Employment is assumed to be at its peak (100%) during the winter, midweek, midday scenarios.

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 summer weekends and less during the week. As shown in Appendix E, there is a large casino that attracts a significant transient population and a significant number of lodging facilities and campgrounds offering overnight accommodations in the EPZ; thus, transient activity is estimated to be high during evening hours - 75% for summer and 55% for winter. Transient activity is less in the winter - 30% during the week and 45% on weekends.

Seasonal population is estimated to be 100% during summer months, and 0% during all other times.

As noted in the shadow footnote to Table 6 3, the shadow percentages are computed using a base of 20% (see assumption 7 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:

657 20% 1 21%

7,894 8,004 One special event - South Haven Fourth of July Celebration - was considered as Scenario 13.

Thus, the special event traffic is 100% evacuated for Scenario 13, and 0% for all other scenarios.

Vehicles evacuation medical facilities include buses, wheelchair buses and ambulance as Palisades Power Plant 62 KLD Engineering, P.C.

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discussed in Section 3.5. These vehicles are 100% evacuated for all scenarios as the medical facility population is present in the EPZ for all scenarios.

As discussed in the footnote to Table 2 1, schools are in session during the winter season, midweek, midday and 100% of buses will be needed under those circumstances. 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.

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 significantly less (40%) during evening scenarios and is 100%

for all other scenarios.

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Table 6 1. Description of Evacuation Regions Radial Regions PAA Region Description 1 2 3 4 5 6 7 R01 2 Mile Region X X R02 5 Mile Region X X X X R03 Full EPZ X X X X X X X Evacuate 2 Mile Region and Downwind to 5 Miles Wind Direction From PAA Region (Degrees) 1 2 3 4 5 6 7 N/A 56 and <169 Refer to R01 R04 169 and <236 X X X N/A 236 and <303 Refer to R02 R05 303 and <56 X X X Evacuate 2 Mile Region and Downwind to the EPZ Boundary Wind Direction From PAA Region (Degrees) 1 2 3 4 5 6 7 R06 56 and <169 X X X R07 169 and <236 X X X X X R08 236 and <303 X X X X X X R09 303 and <348 X X X X R10 348 and <56 X X X X X Staged Evacuation 2 Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind Direction From PAA Region (Degrees) 1 2 3 4 5 6 7 R11 5 Mile Region X X X X N/A 56 and <169 Refer to R01 R12 169 and <236 X X X N/A 236 and <303 Refer to R11 R13 303 and <56 X X X PAA(s) Shelter in Place until PAA(s) Evacuate PAA(s) Shelter in Place 90% ETE for R01, then Evacuate Palisades Power Plant 64 KLD Engineering, P.C.

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Table 6 2. Evacuation Scenario Definitions Scenario Season1 Day of Week Time of Day Weather Special 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 Light 7 Winter Midweek Midday Rain/Snow None 8 Winter Midweek Midday Heavy Snow None 9 Winter Weekend Midday Good None Light 10 Winter Weekend Midday Rain/Snow None 11 Winter Weekend Midday Heavy Snow None Midweek, 12 Winter Weekend Evening Good None South Haven Fourth 13 Summer Weekend Evening Good of July Celebration Roadway Impact -

14 Summer Midweek Midday Good Lane Closure on I 196 Northbound 1

Winter means that school is in session at normal enrollment levels (also applies to spring and autumn). Summer means that school is in session at summer school enrollment levels (lower than normal enrollment).

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Table 6 3. Percent of Population Groups Evacuating for Various Scenarios Households Households With Without External Returning Returning Medical Seasonal School Transit Through Scenario Commuters Commuters Employees Transients Shadow Special Event Facilities Population Buses Buses Traffic 1 50% 50% 96% 55% 21% 0% 100% 100% 10% 100% 100%

2 50% 50% 96% 55% 21% 0% 100% 100% 10% 100% 100%

3 5% 95% 10% 85% 20% 0% 100% 100% 0% 100% 100%

4 5% 95% 10% 85% 20% 0% 100% 100% 0% 100% 100%

5 5% 95% 10% 75% 20% 0% 100% 100% 0% 100% 40%

6 50% 50% 100% 30% 21% 0% 100% 0% 100% 100% 100%

7 50% 50% 100% 30% 21% 0% 100% 0% 100% 100% 100%

8 50% 50% 100% 30% 21% 0% 100% 0% 100% 100% 100%

9 5% 95% 10% 45% 20% 0% 100% 0% 0% 100% 100%

10 5% 95% 10% 45% 20% 0% 100% 0% 0% 100% 100%

11 5% 95% 10% 45% 20% 0% 100% 0% 0% 100% 100%

12 5% 95% 10% 55% 20% 0% 100% 0% 0% 100% 40%

13 5% 95% 10% 75% 20% 100% 100% 100% 0% 100% 40%

14 50% 50% 96% 55% 21% 0% 100% 100% 10% 100% 100%

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

Households without Returning 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 Event..............................................Additional vehicles in the EPZ due to the identified special event.

Medical Facilities........................................Vehicle equivalents present on the road during evacuation servicing medical facility population (buses and wheelchair buses are equivalent to 2 passenger vehicles each, ambulances are 1 passenger vehicle).

Seasonal Population ..................................People who reside outside of the EPZ and enter the area to stay in accommodations other than hotels.

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 at the start of the evacuation. This traffic is stopped by access control approximately 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> after the evacuation begins.

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Table 6 4. Vehicle Estimates by Scenario Households Households With Without External Total Returning Returning Special Medical Seasonal School Transit Through Scenario Scenario Commuters Commuters Employees Transients Shadow Event Facilities Population Buses Buses Traffic Vehicles 1 7,894 8,004 657 4,190 2,592 42 1,977 32 26 7,950 33,364 2 7,894 8,004 657 4,190 2,592 42 1,977 32 26 7,950 33,364 3 789 15,109 68 6,476 2,500 42 1,977 26 7,950 34,937 4 789 15,109 68 6,476 2,500 42 1,977 26 7,950 34,937 5 789 15,109 68 5,714 2,500 42 1,977 26 3,180 29,405 6 7,894 8,004 684 2,286 2,596 42 323 26 7,950 29,805 7 7,894 8,004 684 2,286 2,596 42 323 26 7,950 29,805 8 7,894 8,004 684 2,286 2,596 42 323 26 7,950 29,805 9 789 15,109 68 3,429 2,500 42 26 7,950 29,913 10 789 15,109 68 3,429 2,500 42 26 7,950 29,913 11 789 15,109 68 3,429 2,500 42 26 7,950 29,913 12 789 15,109 68 4,190 2,500 42 26 3,180 25,904 13 789 15,109 68 5,714 2,500 9,908 42 1,977 26 3,180 39,313 14 7,894 8,004 657 4,190 2,592 42 1,977 32 26 7,950 33,364 Note: Vehicle estimates are for an evacuation of the entire EPZ (Region R03)

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Figure 6 1. PAA Comprising the PPP EPZ Palisades Power Plant 68 KLD Engineering, P.C.

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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 13 regions within the PPP 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 for 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 PAAs for which an Advisory to Evacuate (ATE) has not been issued, yet who elect to evacuate. Shadow evacuation is the voluntary evacuation 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 PPP EPZ addresses the issue of voluntary evacuees in the manner shown in Figure 7 1. Within the EPZ, 20% of permanent residents located in PAAs outside of the evacuation region who are not advised to evacuate, are assumed to elect to evacuate. Similarly, it is assumed that 20% of those permanent residents 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 23,192 people reside in the Shadow Region; 20% of them would evacuate. See Table 6 4 for the number of evacuating vehicles from the Shadow Region.

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

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

1. PAAs comprising the 2 Mile region are advised to evacuate immediately.

2. PAAs 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, 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 6 illustrate the patterns of traffic congestion that arise for the case when the entire EPZ (Region R03) is advised to evacuate during the summer, weekend, midday period under good weather conditions (Scenario 3 - the non special event scenario with the largest number of evacuating vehicles - see Table 6 4).

Traffic congestion, as the term is used here, is defined as Level of Service (LOS) F. LOS F is defined as follows (HCM 2016):

The HCM uses LOS F to define operations that have either broken down (i.e., demand exceeds capacity) or have reached a point that most users would consider unsatisfactory, as described by a specified service measure value (or combination of service measure values). However, analysts may be interested in knowing just how bad the LOS F condition is, particularly for planning applications where different alternatives may be compared. 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%).

• Duration of LOS F describes how long the condition persists (e.g., 15 min, 1 h, 3 h).

• 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 Palisades Power Plant 72 KLD Engineering, P.C.

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and traffic bottlenecks.

At 30 minutes after the Advisory to Evacuate (ATE), Figure 7 3 displays the developing traffic congestion in South Haven (the most densely populated area in the EPZ) at the I 196 on ramps from N Shore Dr and from County Road (CR) 388 (Phoenix Hwy) . Pronounced congestion can be seen at the driveway of Four Winds Casino to access Red Arrow Highway. Red Arrow Highway is also between Watervliet and Hartford as a result of the transients leaving the Four Winds Casino. Interstate 196 (I 196) and Interstate 94 (I 94), which are servicing the external external trips and the entering evacuating trips, are displaying only moderate traffic demand (LOS B and C). Congestion is developing along CR 687 southbound leaving Hartford and along Michigan State Route 140 (MI 140) southbound leaving Watervliet.

At one hour after the ATE, Figure 7 4 displays pronounced traffic congestion within South Haven and areas to the north of South Haven as evacuees try to access the various ramps to I 196. CR 388 is particularly congested. Moderate traffic volume is observed along CR 388 eastbound leaving the EPZ and in the Shadow Region, along CR 380 eastbound towards Breedsville, and along CR 378 eastbound through Bangor. Congestion persists leaving the Four Winds Casino. Traffic congestion has intensified in Coloma, Watervliet, and Hartford, with MI 140 southbound leaving Watervliet operating at LOS F. Traffic is also operating at LOS F at the interchange of I 196 and I 94 in the Shadow Region as evacuating vehicles from I 196 southbound and I 94 southbound merge.

At 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> after the ATE, as shown in Figure 7 5, congestion in Bangor, Coloma and Hartford has subsided. The N Shore Dr on ramp to I 196 in the northern portion of South Haven is displaying moderate traffic congestion at this time; the remainder of South Haven is free flowing.

Pronounced traffic congestion is seen northbound along 68th St leaving the EPZ due to the stop sign at 109th Ave. Evacuees from South Haven use 68th St northbound as an alternate route to bypass the congestion at the on ramps for I 196. The intersection of 56th St and 109th Ave is also operating at LOS F in the Shadow Region. This intersection is also stop controlled. MI 140 southbound through Watervliet is still operating at LOS F at this time due to the resident population in the area and transients visiting Paw Paw Lake. Congestion has dissipated at the interchange of I 196 and I 94.

Traffic congestion has cleared from the entire EPZ at two and half hours after the ATE as displayed in Figure 7 6. Moderate traffic volume (LOS B) is observed near the EPZ boundary on M 140 southbound through Watervliet, on I 94 in the Shadow Region between Hartford and Lawrence and on 109th Ave near the I 196 on ramp in the Shadow Region. All roadways in the study area are operating at LOS A five minutes later.

7.4 Evacuation Rates Evacuation is a continuous process, as implied by Figure 7 7 through Figure 7 20. 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.

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As indicated in Figure 7 7, 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 through Table 7 2 present the ETE values for all 13 Evacuation Regions and all 14 Evacuation Scenarios. Table 7 3 through Table 7 4 present the ETE values for the 2 Mile region for both staged and un staged keyhole regions downwind to 5 miles. They are organized as follows:

Table Contents ETE represents the elapsed time required for 90% of the population 71 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% of the population 72 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% of the population 73 within the 2 mile Region, to evacuate from that Region with both Concurrent and Staged Evacuations.

ETE represents the elapsed time required for 100% of the population 74 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 6.

Most of the traffic congestion is located in PAAs 4 and 5 which are beyond the 5 mile region, thereby explaining why 90th percentile ETE are longer for Region R03 than for Region R02 ranging from 10 minutes to 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br />. Also, the 90th percentile ETE for keyhole evacuations extending to 10 miles (Regions R07 through R10 - note R06 extends over Lake Michigan) are 20 Palisades Power Plant 74 KLD Engineering, P.C.

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minutes longer, on average, than ETE for keyhole evacuations extending to 5 miles (Regions R04 and R05).

The 100th percentile ETE for all Regions and for all Scenarios are equal to mobilization time plus a nominal travel time to the boundary of the region being evacuated. This fact implies that the congestion within the EPZ dissipates prior to the end of mobilization, as is displayed in Figure 7 6.

Comparison of Scenarios 5 and 13 in Table 7 1 indicates that the Special Event - the South Haven Fourth of July Celebration - increases the 90th percentile ETE by up to 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 10 minutes for those Regions wherein PAA 4 evacuates. The additional 9,908 vehicles present for the special event exacerbate congestion along CR 388 eastbound and on the on ramps to I 196, thereby prolonging ETE. While the additional vehicles present for the special event prolong traffic congestion in South Haven beyond 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> and 30 minutes from the ATE, congestion still clears prior to the end of mobilization time at 4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> and 45 minutes. Thus, the 100th percentile ETE are not significantly impacted by the special event.

Comparison of Scenarios 1 and 14 in Table 7 1 indicates that the roadway closure - one lane northbound on I 196 from the interchange with CR 378 (Exit 13) to the interchange with CR 89 (Exit 32) - does not have a material impact (at most 5 minute increases) on the 90th percentile ETE or the 100th percentile ETE (no change). As discussed in Section 7.3, I 196 does not experience significant levels of congestion. Rather, the ramps to access I 196 are the bottlenecks. Thus, the reduced capacity on I 196 still provides adequate capacity to service the evacuation demand.

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 R11 through R13 are the same geographic areas as Regions R02, R04, and R05, 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 90th percentile and 100th percentile ETE for the 2 mile region are unchanged when a staged evacuation is implemented. The reason for this is that the congestion within the 5 mile region does not extend upstream to the extent that it penetrates to within 2 miles of the PPP. Consequently, 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 90th percentile ETE for the 2 mile area.

Therefore, staging the evacuation to reduce congestion within the 5 mile area, provides no benefits to evacuees from within the 2 mile region.

While failing to provide benefit to evacuees from within 2 miles of the PPP, staging produces a negative impact on the ETE for those evacuating from within the 2 to 5 mile area. A comparison of ETE between Regions, R11 and R02; R12 and R04; and R13 and R05; reveals that staging retards the 90th percentile evacuation time for those in the 2 to 5 mile area by up to 20 Palisades Power Plant 75 KLD Engineering, P.C.

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minutes (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 - see Figure 5 5) that follows their eventual ATE, in creating congestion within the EPZ area beyond 2 miles. The 100th percentile ETE are not impacted.

In summary, the staged evacuation option provides no benefits to evacuees from the 2 mile region and adversely impacts many evacuees located beyond 2 miles from the PPP.

7.7 Guidance on Using ETE Tables The user first determines the percentile of population for which the ETE is sought (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 (Step 1):

• Season Summer Winter (also Autumn and Spring)

• Day of Week Midweek Weekend

• Time of Day Midday Evening

• Weather Condition Good Weather Rain/Light Snow Heavy Snow

• Special Event South Haven Fourth of July Celebration

• Roadway Impact Road Closure (a lane on I 196 northbound 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/light snow are not explicitly identified in the Tables. For these conditions, Scenarios (7) and (10) for rain/light snow apply.

• The conditions of a winter evening (either midweek or weekend) and heavy snow Palisades Power Plant 76 KLD Engineering, P.C.

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are not explicitly identified in the Tables. For these conditions, Scenarios (8) and (11) for heavy snow apply.

• The seasons are defined as follows:

Summer assumes public school is in session, at summer enrollment levels (lower than normal enrollment).

Winter (includes Spring and Autumn) considers that public schools are in session, at normal enrollment levels.

• 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 (Step 2):

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

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

2 Miles (Region R01)

To 5 Miles (Region R02, R04, R05, and staged regions R11 through R13)

To EPZ Boundary (Regions R03, R06 through R10)

• 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 Evacuation 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.

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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 from the southwest (SW) or from 225°.

• Wind speed is such that the distance to be evacuated is judged to be a 2 mile radius and downwind to 10 miles (to EPZ boundary).

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

• A staged evacuation is not desired.

Table 7 1 is applicable because the 90th 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 2 Mile Radius and Downwind to the EPZ Boundary for wind direction from the SW or 225°) and read Region R07 in the first column for the row with Wind Direction From (Degrees) listed as 169 and <236.

3. Enter Table 7 1 to locate the data cell containing the value of ETE for Scenario 4 and Region R07. This data cell is in column (4) and in the row for Region R07; it contains the ETE value of 2:15.

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Table 7 1. Time to Clear the Indicated Area of 90 Percent of the Affected Population Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Midday Midday Evening Midday Midday Evening Evening Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Radial Regions - 2 Mile, 5 Mile, Full EPZ R01 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R02 2:20 2:20 2:10 2:15 2:15 2:20 2:20 3:05 2:10 2:15 2:50 2:15 2:15 2:20 R03 2:40 2:40 2:20 2:25 2:25 2:45 2:45 3:30 2:25 2:25 3:15 2:25 3:15 2:45 Evacuate 2 Mile Radius and Downwind to 5 Mile Radius R04 2:15 2:15 2:10 2:10 2:15 2:15 2:15 2:55 2:10 2:10 2:40 2:15 2:15 2:15 R05 2:15 2:15 2:10 2:10 2:15 2:15 2:15 2:45 2:10 2:10 2:30 2:10 2:15 2:15 Evacuate 2 Mile Radius and Downwind to the EPZ Boundary R06 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R07 2:35 2:35 2:15 2:15 2:20 2:35 2:35 3:25 2:15 2:15 3:05 2:20 3:30 2:40 R08 2:40 2:40 2:20 2:25 2:25 2:45 2:45 3:30 2:25 2:25 3:15 2:25 3:15 2:45 R09 2:35 2:35 2:20 2:25 2:25 2:40 2:40 3:30 2:20 2:25 3:10 2:25 2:25 2:35 R10 2:35 2:35 2:20 2:25 2:25 2:40 2:40 3:30 2:20 2:25 3:10 2:25 2:25 2:35 Staged Evacuation 2 Mile Radius Evacuates, then Evacuate Downwind to 5 Mile Radius R11 2:35 2:35 2:30 2:30 2:35 2:35 2:35 3:05 2:30 2:30 2:50 2:35 2:35 2:35 R12 2:30 2:30 2:30 2:30 2:35 2:30 2:30 2:55 2:30 2:30 2:40 2:35 2:35 2:30 R13 2:25 2:25 2:20 2:20 2:25 2:25 2:25 2:45 2:20 2:20 2:35 2:25 2:25 2:25 Palisades Power Plant 79 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 Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Midday Midday Evening Midday Midday Evening Evening Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Radial Regions - 2 Mile, 5 Mile, Full EPZ R01 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R02 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 R03 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 5:00 4:55 Evacuate 2 Mile Radius and Downwind to 5 Mile Radius R04 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 R05 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 Evacuate 2 Mile Radius and Downwind to the EPZ Boundary R06 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:10 4:45 4:45 6:10 4:45 4:45 4:45 R07 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 5:00 4:55 R08 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 5:00 4:55 R09 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 4:55 4:55 R10 4:55 4:55 4:55 4:55 4:55 4:55 4:55 6:10 4:55 4:55 6:10 4:55 4:55 4:55 Staged Evacuation 2 Mile Radius Evacuates, then Evacuate Downwind to 5 Mile Radius R11 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 R12 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 R13 4:50 4:50 4:50 4:50 4:50 4:50 4:50 6:05 4:50 4:50 6:05 4:50 4:50 4:50 Palisades Power Plant 7 10 KLD Engineering, P.C.

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Table 7 3. Time to Clear 90 Percent of the 2 Mile Region within the Indicated Region Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Midday Midday Evening Midday Midday Evening Evening Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Unstaged Evacuation 2 Mile Region and 5 Mile Region R01 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R02 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 Unstaged Evacuation 2 Mile Region and Keyhole to 5 Miles R04 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R05 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 Staged Evacuation 2 Mile Region and Keyhole to 5 Miles R11 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R12 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 R13 2:05 2:10 2:05 2:05 2:10 2:05 2:10 2:20 2:05 2:05 2:15 2:05 2:10 2:05 Palisades Power Plant 7 11 KLD Engineering, P.C.

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Table 7 4. Time to Clear 100 Percent of the 2 Mile Region within the Indicated Region Summer Summer Summer Winter Winter Winter Summer Summer Midweek Midweek Midweek Weekend Midweek Weekend Weekend Midweek Weekend Weekend Scenario: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Midday Midday Evening Midday Midday Evening Evening Midday Region Good Good Good Good Rain/Light Heavy Good Rain/Light Heavy Good Special Roadway Rain Rain Weather Weather Weather Weather Snow Snow Weather Snow Snow Weather Event Impact Unstaged Evacuation 2 Mile Region and 5 Mile Region R01 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R02 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 Unstaged Evacuation 2 Mile Region and Keyhole to 5 Miles R04 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R05 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 Staged Evacuation 2 Mile Region and Keyhole to 5 Miles R11 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R12 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 R13 4:45 4:45 4:45 4:45 4:45 4:45 4:45 6:00 4:45 4:45 6:00 4:45 4:45 4:45 Palisades Power Plant 7 12 KLD Engineering, P.C.

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Table 7 5. Description of Evacuation Regions Radial Regions PAA Region Description 1 2 3 4 5 6 7 R01 2 Mile Region X X R02 5 Mile Region X X X X R03 Full EPZ X X X X X X X Evacuate 2 Mile Region and Downwind to 5 Miles Wind Direction From PAA Region (Degrees) 1 2 3 4 5 6 7 N/A 56 and <169 Refer to R01 R04 169 and <236 X X X N/A 236 and <303 Refer to R02 R05 303 and <56 X X X Evacuate 2 Mile Region and Downwind to the EPZ Boundary Wind Direction From PAA Region (Degrees) 1 2 3 4 5 6 7 R06 56 and <169 X X X R07 169 and <236 X X X X X R08 236 and <303 X X X X X X R09 303 and <348 X X X X R10 348 and <56 X X X X X Staged Evacuation 2 Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind Direction From PAA Region (Degrees) 1 2 3 4 5 6 7 R11 5 Mile Region X X X X N/A 56 and <169 Refer to R01 R12 169 and <236 X X X N/A 236 and <303 Refer to R11 R13 303 and <56 X X X PAA(s) Shelter in Place until PAA(s) Evacuate PAA(s) Shelter in Place 90% ETE for R01, then Evacuate Palisades Power Plant 7 13 KLD Engineering, P.C.

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Figure 7 1. Voluntary Evacuation Methodology Palisades Power Plant 7 14 KLD Engineering, P.C.

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Figure 7 2. PPP Shadow Region Palisades Power Plant 7 15 KLD Engineering, P.C.

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Figure 7 3. Congestion Patterns at 30 Minutes after the Advisory to Evacuate Palisades Power Plant 7 16 KLD Engineering, P.C.

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Figure 7 4. Congestion Patterns at 1 Hour after the Advisory to Evacuate Palisades Power Plant 7 17 KLD Engineering, P.C.

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Figure 7 5. Congestion Patterns at 2 Hours after the Advisory to Evacuate Palisades Power Plant 7 18 KLD Engineering, P.C.

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Figure 7 6. Congestion Patterns at 2 Hours and 30 Minutes after the Advisory to Evacuate Palisades Power Plant 7 19 KLD Engineering, P.C.

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Evacuation Time Estimates Summer, Midweek, Midday, Good (Scenario 1) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

30 25 Vehicles Evacuating 20 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 7. Evacuation Time Estimates Scenario 1 for Region R03 Evacuation Time Estimates Summer, Midweek, Midday, Rain (Scenario 2) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

30 25 Vehicles Evacuating 20 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 8. Evacuation Time Estimates Scenario 2 for Region R03 Palisades Power Plant 7 20 KLD Engineering, P.C.

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Evacuation Time Estimates Summer, Weekend, Midday, Good (Scenario 3) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

30 25 Vehicles Evacuating 20 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 9. Evacuation Time Estimates Scenario 3 for Region R03 Evacuation Time Estimates Summer, Weekend, Midday, Rain (Scenario 4) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

30 25 Vehicles Evacuating 20 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 10. Evacuation Time Estimates Scenario 4 for Region R03 Palisades Power Plant 7 21 KLD Engineering, P.C.

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Evacuation Time Estimates Summer, Midweek, Weekend, Evening, Good (Scenario 5) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

30 25 Vehicles Evacuating 20 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 11. Evacuation Time Estimates Scenario 5 for Region R03 Evacuation Time Estimates Winter, Midweek, Midday, Good (Scenario 6) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

25 20 Vehicles Evacuating 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 12. Evacuation Time Estimates Scenario 6 for Region R03 Palisades Power Plant 7 22 KLD Engineering, P.C.

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Evacuation Time Estimates Winter, Midweek, Midday, Rain (Scenario 7) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

25 20 Vehicles Evacuating 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 13. Evacuation Time Estimates Scenario 7 for Region R03 Evacuation Time Estimates Winter, Midweek, Midday, Snow (Scenario 8) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

25 20 Vehicles Evacuating 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 14. Evacuation Time Estimates Scenario 8 for Region R03 Palisades Power Plant 7 23 KLD Engineering, P.C.

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Evacuation Time Estimates Winter, Weekend, Midday, Good (Scenario 9) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

25 20 Vehicles Evacuating 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 15. Evacuation Time Estimates Scenario 9 for Region R03 Evacuation Time Estimates Winter, Weekend, Midday, Rain (Scenario 10) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

25 20 Vehicles Evacuating 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 16. Evacuation Time Estimates Scenario 10 for Region R03 Palisades Power Plant 7 24 KLD Engineering, P.C.

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Evacuation Time Estimates Winter, Weekend, Midday, Snow (Scenario 11) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

25 20 Vehicles Evacuating 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 17. Evacuation Time Estimates Scenario 11 for Region R03 Evacuation Time Estimates Winter, Midweek, Weekend, Evening, Good (Scenario 12) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

25 20 Vehicles Evacuating 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 18. Evacuation Time Estimates Scenario 12 for Region R03 Palisades Power Plant 7 25 KLD Engineering, P.C.

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Evacuation Time Estimates Summer, Weekend, Evening, Good, Special Event (Scenario 13) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

40 35 Vehicles Evacuating 30 25 20 (Thousands) 15 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 19. Evacuation Time Estimates Scenario 13 for Region R03 Evacuation Time Estimates Summer, Midweek, Midday, Good, Roadway Impact (Scenario 14) 2 Mile Region 5 Mile Region Entire EPZ 90% 100%

30 Vehicles Evacuating 25 20 15 (Thousands) 10 5

0 0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time After Evacuation Recommendation (h:mm)

Figure 7 20. Evacuation Time Estimates Scenario 14 for Region R03 Palisades Power Plant 7 26 KLD Engineering, P.C.

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8 TRANSIT DEPENDENT AND SPECIAL FACILITY EVACUATION TIME ESTIMATES This section details the analyses applied and the results obtained in the form of ETE for transit vehicles (e.g., buses, wheelchair transport, and ambulances). The demand for transit service reflects the needs of three population groups:

residents with no vehicles available; residents of special facilities such as schools, medical facilities; and homebound population with access and/or functional needs.

These transit vehicles mix with the general evacuation traffic that is comprised mostly of passenger cars (pcs). The presence of each transit vehicle in the evacuating traffic stream is represented within the modeling paradigm described in Appendix D as equivalent to two pcs.

This equivalence factor represents the longer size and more sluggish operating characteristics of a transit vehicle, relative to those of a pc.

Transit vehicles must be mobilized in preparation for their respective evacuation missions.

Specifically:

• Bus drivers must be alerted

• They must travel to the bus depot

• They must be briefed there and assigned to a route or facility These activities consume time. Based on discussion with the offsite agencies, it is estimated that bus mobilization time will average approximately 90 minutes for schools and medical facilities extending from the ATE, to the time when buses first arrive at the facility to be evacuated.

During this mobilization period, other mobilization activities are taking place. One of these is the action taken by parents, neighbors, relatives and friends to pick up children from school prior to the arrival of buses, so that they may join their families. Virtually all studies of evacuations have concluded that this bonding process of uniting families is universally prevalent during emergencies and should be anticipated in the planning process. The current public information disseminated to residents of the PPP EPZ indicates that schoolchildren will be evacuated to temporary host facilities (THF) at emergency action levels of Site Area Emergency or higher, and that parents should pick schoolchildren up at the appropriate THF. As discussed in Section 2, this study assumes a fast breaking general emergency. Therefore, children are evacuated to the THF. Picking up children at school could add to traffic congestion at the schools, delaying the departure of the buses evacuating schoolchildren, which may have to return in a subsequent wave to the EPZ to evacuate the transit dependent population. This report provides estimates of buses under the assumption that no children will be picked up by their parents (in accordance with NUREG/CR 7002, Rev. 1), to present an upper bound estimate of buses required. It is assumed that children at day care centers are picked up by parents or guardians and that the time to perform this activity is included in the trip generation times discussed in Section 5.

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The procedure for computing transit dependent ETE is to:

• Estimate demand for transit service

• Estimate time to perform all transit functions

• Estimate route travel times to the EPZ boundary and to the THF/reception centers ETE for transit trips were developed using both good weather and adverse weather conditions.

Figure 8 1 presents the chronology of events relevant to transit operations. The elapsed time for each activity will now be discussed with reference to Figure 8 1.

8.1 ETEs for Schools, Transit Dependent People, and Special Facilities Available transportation resources were provided by the Berrien and Van Buren County emergency management agencies. Allegan County does not provide transportation services in the EPZ. Table 8 1 lists the transportation resources by provider and the transportation needs to evacuate the transit dependent and special facility population in the EPZ. As shown in the table, there are sufficient bus resources to evacuate the entire school, transit dependent population and ambulatory population at medical facilities. EPZ bus resources are assigned to evacuating schoolchildren (if school is in session at the time of the ATE) as the first priority in the event of an emergency. In the event that the allocation of buses dispatched from the depots to the various facilities and to the bus routes is somewhat inefficient, or if there is a shortfall of available drivers, then there may be a need for some buses to return to the EPZ from the reception center or THF after completing their first evacuation trip, to complete a second wave of providing transport service to evacuees. For this reason, the ETE for the transit dependent population will be calculated for both a one wave transit evacuation and for two waves. Of course, if the impacted Evacuation Region is other than R03 (the entire EPZ),

then there will likely be ample transit resources relative to demand in the impacted Region and this discussion of a second wave would likely not apply.

When school evacuation needs are satisfied, subsequent assignments of buses to service the transit dependent population should be sensitive to their mobilization time. Clearly, the buses should be dispatched after people have completed their mobilization activities and are in a position to board the buses when they arrive at the pick up points.

School Evacuation Activity: Mobilize Drivers (A B C)

Mobilization is the elapsed time from the ATE until the time the buses arrive at the facility to be evacuated. It is assumed that for a rapidly escalating radiological emergency with no observable indication before the fact, drivers would likely require 90 minutes to be contacted, to travel to the depot, be briefed, and to travel to the transit dependent facilities. Mobilization time is slightly longer in adverse weather - 100 minutes for rain/light snow, and 110 minutes for heavy snow.

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Activity: Board Passengers (C D)

Based on discussions with offsite agencies, a loading time of 15 minutes (20 minutes for rain/light snow and 25 minutes for heavy snow) for school buses is used. See Section 2.4, assumption 5 and Table 2 2.

Activity: Travel to EPZ Boundary (D E)

The buses servicing the schools are ready to begin their evacuation trips at 105 minutes after the ATE - 90 minute mobilization time plus 15 minute loading time - in good weather. The UNITES software discussed in Section 1.3 was used to define bus routes along the most likely path from a school being evacuated to the EPZ boundary, traveling toward the appropriate THF.

This is done in UNITES by interactively selecting the series of nodes from the school to the EPZ boundary. Each bus route is given an identification number and is written to the DYNEV II input stream. DYNEV computes the route length and outputs the average speed for each 5 minute interval, for each bus route. The specified bus routes are documented in in Section 10 in Table 10 2 (refer to the maps of the link node analysis network in Appendix K for node locations).

Data provided by DYNEV during the appropriate timeframe depending on the mobilization and loading times (i.e., 105 minutes after the ATE for good weather) were used to compute the average speed for each route, as follows:

. 60 .

. . 1 .

60 .

1 .

The average speed computed (using this methodology) for the buses servicing each of the schools in the EPZ is shown in Table 8 2 through Table 8 4 for school evacuation, The travel time to the EPZ boundary was computed for each bus using the computed average speed and the distance to the EPZ boundary along the most likely route out of the EPZ. Speeds were reduced in Table 8 2 through Table 8 4 to 55 mph (50 mph for rain/light snow - a 10% decrease

- and 47 mph for snow - a 15% decrease) for those calculated bus speeds which exceed 55 mph, as the school bus speed limit for state routes in Michigan is 55 mph (see assumption 7 in Section 2.1).

Table 8 2 (good weather), Table 8 3 (rain/light snow) and Table 8 4 (heavy snow) present the following ETE (rounded up to the nearest 5 minutes) for schools in the EPZ:

1. The elapsed time from the ATE until the bus exits the EPZ; and

2. The elapsed time until the bus reaches the THF.

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The evacuation time out of the EPZ can be computed as the sum of times associated with Activities A B C, C D, and D E (For example: 90 min. + 15 + 2 = 107 minutes or 1:50, rounded up to the nearest 5 minutes, for Bangor High School, with good weather). The average single wave ETE, for schools, is less than the 90th percentile ETE for evacuation of the general population in the entire EPZ (Region R03) under winter, midweek, midday, good weather (Scenario 6) conditions and will not impact protective action decision making.

The evacuation time to the THF is determined by adding the time associated with Activity E F (discussed below), to this EPZ evacuation time.

Activity: Travel to THF (E F)

The distances from the EPZ boundary to the THF are measured using GIS software along the most likely route from the EPZ exit point to the THF. The THF are mapped in Figure 10 3. For a one wave evacuation, this travel time outside the EPZ does not contribute to the ETE. For a two wave evacuation, the ETE for buses must be considered separately when making a protective action decision, since it could exceed the ETE for the general public. Assumed bus speeds of 55 mph, 50 mph (10% reduction), and 47 mph (15% reduction) for good weather, rain/light snow, and heavy snow, respectively, will be applied for this activity for buses servicing the school population.

Activity: Passengers Leave Bus (F G)

A bus can empty within 5 minutes. The driver takes a 10 minute break.

Activity: Bus Returns to Route for Second Wave Evacuation (G C D E)

As shown in Table 8 1, there are sufficient buses for evacuation of children in a single wave, if the entire EPZ is evacuated at once (a highly unlikely event). However, there might be a shortfall of drivers. As such, a two wave evacuation may be needed for some schools. Due to the large number of schools in the EPZ, second wave ETE were not computed for each school.

Rather, the following representative ETE is provided to estimate the additional time needed for a second wave evacuation of schools. The travel time from the THF back to the EPZ boundary and then back to the school was computed assuming an average speed of 55 mph (good weather), 50 mph (rain/light snow) and 47 mph (heavy snow) as buses will be traveling counter to the evacuation traffic. Time and distance are based on averages for all schools in the EPZ for good weather:

• School buses arrive at THF at 2:15.

• Bus discharges passengers (5 minutes) and driver takes a 10 minute rest: 15 minutes.

• Bus returns to EPZ and completes second route: 14 minutes to return to the EPZ (equal to average travel time to THF for good weather) + 5 minutes to return to the start of the route (4.3 miles, average distance to EPZ boundary from Table 8 2 @ 55 mph) + 5 minutes to perform a second wave of service on the route (4.3 miles, average distance to EPZ boundary from Table 8 2 @ 55 mph, average network speed at this time) = 24 minutes.

• Loading Time: 15 minutes.

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• Bus exits EPZ at time 2:15 + 0:15 + 0:24 + 0:15 = 3:10 after the ATE, rounded to the nearest 5 minutes.

Given the average single wave ETE for schools is 1:55, a second wave evacuation would require an additional 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 15 minutes, on average for good weather.

Evacuation of Transit Dependent People (Residents without access to a vehicle)

As detailed in Section 3.9, transit dependent population estimates were calculated using the results of the demographic survey. KLD designed 6 bus routes to service the major evacuation routes and major population centers in the EPZ (see Section 10 for additional discussion). The routes are shown graphically in Figure 10 2 and described in Table 10 1.

Activity: Mobilize Drivers (A B C)

Mobilization time is the elapsed time from the ATE until the time the buses arrive at their designated route. The buses dispatched from the depots to service the transit dependent evacuees will be scheduled so that they arrive at their respective routes after a majority of their passengers have completed their mobilization. As shown in Figure 5 4 (Residents with no Commuters), approximately 90% of the evacuees will have completed their mobilization when the buses will begin their routes, approximately 150 minutes after the ATE for good weather.

Those routes with multiple buses have been designed such that buses are dispatched using 20 minute headways. The use of bus headways ensures that those people who take longer to mobilize will be picked up.

Activity: Board Passengers (C D)

For multiple stops along a pick up route (transit dependent bus routes) estimation of travel time must allow for the delay associated with stopping and starting at each pick up point. The time, t, required for a bus to decelerate at a rate, a, expressed in ft/sec/sec, from a speed, v, expressed in ft/sec, to a stop, is t = v/a. Assuming the same acceleration rate and final speed following the stop yields a total time, T, to service boarding passengers:

2 ,

Where B = Dwell time to service passengers. The total distance, s in feet, travelled during the deceleration and acceleration activities is: s = v2/a. If the bus had not stopped to service passengers, but had continued to travel at speed, v, then its travel time over the distance, s, would be: s/v = v/a. Then the total delay (i.e., pickup time, P) to service passengers is:

Assigning reasonable estimates:

• B = 50 seconds: a generous value for a single passenger, carrying personal items, to board per stop

• v = 25 mph = 37 ft/sec

• a = 4 ft/sec/sec, a moderate average rate Then, P 1 minute per stop. It is assumed that the bus has a capacity of 30 passenger per bus.

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Thus, bus pick up time is 30 minutes per bus, for good weather. It is assumed that bus acceleration and speed will be less in rain/light snow and heavy snow resulting in loading times that are 10 minutes and 20 minutes longer, respectively.

Activity: Travel to EPZ Boundary (D E)

The travel distance along the respective pick up routes within the EPZ is estimated using the UNITES software. Bus travel times within the EPZ are computed using average speeds computed by DYNEV, using the aforementioned methodology that was used for school evacuation.

Table 8 5 through Table 8 7 present the transit dependent population evacuation time estimates for each bus route calculated using the above procedures for good weather, rain/light snow and heavy snow, respectively. Similar to schools, bus speeds are capped at 55mph for good weather, 50mph for rain/light snow, and 47mph for heavy snow.

For example, the ETE for the bus route servicing PAA 1 (Route 1) is computed as 150 + 11 + 30 =

3:15 for good weather (rounded up to nearest 5 minutes). Here, 11 minutes is the time to travel 9.8 miles at 55.0 mph, the average speed output by the model for this route starting at 150 minutes. As mentioned before, 30 minutes is the bus pickup time for good weather.

The ETE for a second wave (discussed below) is presented in the event there is a shortfall of available buses or bus drivers, as previously discussed.

The average ETE for a one wave evacuation of transit dependent people exceeds the ETE for the general population by 35 minutes at the 90th percentile for an evacuation of the entire EPZ (Region R03) under winter, midweek, midday, good weather (Scenario 6) and could impact protective action decision making.

Activity: Travel to Reception Centers (E F)

The distances from the EPZ boundary to the reception centers are measured using GIS software along the most likely route from the EPZ exit point to the reception center. The general population reception centers are mapped in Figure 10 3. For a single wave evacuation, this travel time outside the EPZ does not contribute to the ETE. Assumed bus speeds of 55 mph, 50 mph, and 47 mph for good weather, rain/light snow, and heavy snow, respectively, will be applied for this activity for buses servicing the transit dependent population.

Activity: Passengers Leave Bus (F G)

A bus can empty within 5 minutes. The driver takes a 10 minute break.

Activity: Bus Returns to Route for Second Wave Evacuation (G C D E)

The buses assigned to return to the EPZ to perform a second wave evacuation of transit dependent evacuees will be those that have already evacuated transit dependent people who mobilized more quickly. The first wave of transit dependent people departs the bus, and the bus then returns to the EPZ, travels to its route and proceeds to pick up more transit dependent evacuees along the route. The travel time back to the EPZ is equal to the travel time to the reception center.

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The second wave ETE for the bus route servicing PAA 1 (Route 1) is computed as follows for good weather:

• Bus arrives at reception center at 3:24 in good weather (3:15 to exit EPZ + 9 minute travel time to reception center).

• Bus discharges passengers (5 minutes) and driver takes a 10 minute rest: 15 minutes.

• Bus returns to EPZ and completes second route: 9 minutes (equal to travel time to reception center) + 11 minutes (9.8 miles @ 55 mph - assumed speed to start of route) + 11 minutes (9.8 miles @ 55.0 mph - network wide speed at the time the bus starts route for the second time) = 31 minutes.

• Bus completes pick ups along route: 30 minutes.

• Bus exits EPZ at time 3:24 + 0:15 + 0:31 + 0:30 = 4:40 after the ATE.

The ETE for the completion of the second wave for all transit dependent bus routes are provided in Table 8 5 through Table 8 7. The average ETE for a two wave evacuation of transit dependent people exceeds the ETE for the general population at the 90th percentile for an evacuation of the entire EPZ (Region R03) under winter, midweek, midday, good weather (Scenario 6) and could impact protective action decision making.

The relocation of transit dependent evacuees from the reception centers to congregate care centers, if the counties decide to do so, is not considered in this study.

Evacuation of Medical Facilities As discussed in Section 2.4, assumption 4c and in Table 2 2, it is assumed that the mobilization time for medical facilities average 90 minutes in good weather, 100 minutes in rain/light snow and 110 minutes for heavy snow. Specially trained medical support staff (working their regular shift) will be on site to assist in the evacuation of patients. Additional staff (if needed) could be mobilized over this same 90 minute timeframe.

Activity: Board Passengers (C D)

Assumption 5 in Section 2.4 discusses transit vehicle loading times for medical facilities.

Loading times are assumed to be 1 minute per ambulatory passenger, 5 minutes per wheelchair bound passenger, and 15 minutes per bedridden passenger for buses, wheelchair transport vehicles, and ambulances, respectively. Assumption 3 in Section 2.4 discusses transit vehicle capacities to cap loading times per vehicle type - 30 minutes per bus (30 passengers times 1 minute per passenger), 20 minutes per wheelchair van (4 passengers times 5 minutes per passenger), 75 minutes per wheelchair bus (15 passengers time 5 minutes per passenger) and 30 minutes per ambulance (2 passengers times 15 minutes per passenger). Concurrent loading on multiple buses, wheelchair vans, wheelchair buses, and ambulances at capacity is assumed such that the maximum loading times for buses, wheelchair vans, wheelchair buses and ambulances are 30, 20, 75, and 30 minutes, respectively.

Activity: Travel to EPZ Boundary (D E)

The travel distance along the respective pick up routes within the EPZ is estimated using the Palisades Power Plant 87 KLD Engineering, P.C.

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UNITES software. Transit vehicle travel times within the EPZ are computed using average speeds computed by DYNEV, using the aforementioned methodology that was used for school and transit dependent evacuation.

Table 8 8 through Table 8 10 summarize the ETE for medical facilities within the EPZ for good weather, rain/light snow, and heavy snow. Average speeds output by the model for Scenario 6 (Scenario 7 for rain/light snow and Scenario 8 for heavy snow) Region 3, capped at 55 mph (50 mph for rain/light snow and 47 mph for heavy snow), are used to compute travel time to the EPZ boundary. The travel time to the EPZ boundary is computed by dividing the distance to the EPZ boundary by the average travel speed. The ETE is the sum of the mobilization time, total passenger loading time, and travel time out of the EPZ boundary. All ETE are rounded up to the nearest 5 minutes.

For example, the calculation of ETE for the Country Side Nursing Home with 43 ambulatory residents during good weather is:

ETE: 90 + 30 x 1 + 6 = 126 min or 2:10 (rounded up to the nearest 5 minutes)

It is assumed that medical facility population is directly evacuated to appropriate host medical facilities outside of the EPZ. Relocation of this population to permanent facilities and/or passing through the reception center before arriving at the host facility are not considered in this analysis.

The average single wave ETE for medical facilities in the EPZ does not exceed the 90th percentile ETE for the general population for a winter, midweek, midday, good weather scenario and should not impact protect action decision making.

Activity: Vehicles Travel to Host Facilities (E F), Passengers Leave (F G), Vehicle Returns to Route for Second Wave Evacuation (G C D E)

As shown in Table 8 1, there are sufficient wheelchair buses, wheelchair vans, and ambulances to evacuate the wheelchair bound and bedridden patients at the medical facilities in the EPZ. It is assumed that these medical facilities are evacuated to the Lakeland Medical Center in St.

Joseph, Michigan, which is 11 miles from the EPZ boundary.

For simplicity, second wave ETE for these vehicle types were not computed for each medical facility. Rather, the following representative ETE is provided to estimate the additional time needed for a second wave evacuation for ambulances.

Times and distances are based on facility wide averages:

• Bedridden patients:

o Ambulances arrive at Host Hospitals at 2:15 (2:03 Average ETE for ambulances to exit the EPZ plus 12 minutes to travel 11 miles at 55 mph).

o Ambulances discharges passengers (25 minutes - average loading time for ambulances from Table 8 8) and driver takes a 10 minute rest: 35 minutes.

o Ambulances returns to facility: 12 minutes to travel back to the EPZ boundary (time needed to travel 11 miles back to the EPZ at 55 mph) + 6 minutes to travel back to the facility (average distance to EPZ = 5.5 miles for ambulances from Palisades Power Plant 88 KLD Engineering, P.C.

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Table 8 8 @ 55 mph) = 18 minutes.

o Remaining patients loaded on ambulance (average): 25 minutes.

o Ambulance travels to EPZ boundary: 6 minutes (average distance from medical facilities to EPZ boundary (5.5 miles) at 55 mph (network wide average speed at 3:35).

o Ambulances exits EPZ at time 2:15 + 0:35 + 0:18 + 0:25 + 0:06 = 3:40 (rounded up to nearest 5 minutes) after the ATE.

Thus, the second wave evacuation for ambulances requires about 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 40 minutes more than the first wave ETE. The average ETE for a two wave evacuation of medical facilities exceeds the ETE for the general population at the 90th percentile for a winter, midweek, midday, good weather scenario (Scenario 6) conditions and could impact protective action decision making.

8.2 ETE for Access and/or Functional Needs Population The access and/or functional needs population was provided by the offsite agencies and is further discussed in Section 3.8. Table 8 11 summarizes the ETE for access and/or functional needs population. The table is broken down by weather condition and by vehicle type. It is assumed that the special needs population will be picked up from their homes. Furthermore, it is conservatively assumed that bedridden households are spaced 3 miles apart. Bus, wheelchair bus, and ambulance speeds approximate 20 mph between households in good weather (10%

slower in rain/light snow, 15% slower in heavy snow). Mobilization times of 90 minutes were used (100 minutes for rain/light snow, and 110 minutes for heavy snow). The last household is assumed to be 5 miles from the EPZ boundary, and the network wide average speed, capped at 55 mph (50 mph for rain/light snow and 47 mph for heavy snow), after the last pickup is used to compute travel time.

ETE is computed by summing mobilization time, loading time at the first household, travel to the subsequent households, loading time at subsequent households, and travel time to the EPZ boundary. All ETE are rounded up to the nearest 5 minutes.

For example, assuming no more than one special needs person per household implies that 3 households need to be serviced for bedridden patients. Ambulances are assumed to have a capacity of two persons per ambulance resulting in a total of 2 ambulances needed to complete the evacuation in a single wave. The following outlines the ETE calculations:

1. Assume 2 ambulances are deployed, each with about 2 stops, to service a total of 3 HH.

2. The ETE is calculated as follows:

a. Ambulances arrive at the first pickup location: 90 minutes

b. Load passenger at first pickup: 15 minutes

c. Travel to next pickup location: 9 minutes (assumed 3 miles @ 20 mph)

d. Load passenger at subsequent pickup location: 15 minutes

e. Travel to EPZ boundary: 5 minutes (5 miles @ 55 mph).

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The ETE of a single wave evacuation of the access and/or functional needs population within the EPZ is 45 minutes greater than the 90th percentile ETE for evacuation of the general population in the Full EPZ (Region R03) under winter, midweek, midday, good weather (Scenario 6) conditions and could impact protective action decision making.

The following outlines the ETE calculations of a second wave using ambulances after the medical facilities have been evacuated assuming the host medical facilities are located 11 miles away from the EPZ boundary:

a. Ambulances arrive at host medical facilities: 2:15 (2:03 Average ETE for ambulances to exit the EPZ from Table 8 8 plus 12 minutes to travel 11 miles @ 55 mph) on average.

b. Unload patients at host medical facilities: 30 minutes.

c. Driver takes 10 minute rest: 10 minutes.

d. Travel time back to EPZ: 12 minutes (11 miles @ 55 mph).

e. Travel to first household: 15 minutes (5 miles @ 20 mph).

f. Loading time at first household: 15 minutes.

g. Travel to subsequent pickup location: 1 @ 9 minutes = 9 minutes

h. Loading time at subsequent household: 1 stop @ 15 minutes = 15 minutes

i. Travel time to EPZ boundary: 5 miles @55 mph (at 4:01) = 5 minutes Bus exits EPZ at time: 2:15 + 30 + 10 + 12 + 15 + 15 + 9 + 15 + 5 = 4:10 after the ATE, rounded to the nearest 5 minutes.

The average ETE of a second wave evacuation of the bedridden access and/or functional needs population within the EPZ is 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 25 minutes longer than the 90th percentile ETE for an evacuation of the general population in the Full EPZ (Region R03) under winter, midweek, midday, good weather (Scenario 6) conditions and could impact protective action decision making.

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Table 8 1. Summary of Transportation Resources Wheelchair Wheelchair Transportation Provider1 Cars Buses Vans Ambulances Buses Vans Resources Available BERRIEN COUNTY, MI Benton Harbor Schools (FST) 0 30 3 2 0 0 Berrien County Public Transportation 0 0 1 18 0 1 Berrien RESA (FST) 0 0 24 20 0 0 Berrien Springs Public Schools 0 20 8 0 0 0 Brandywine Community Schools 1 10 1 0 2 0 Bridgman Public Schools 0 8 4 1 0 0 Buchanan Community Schools 0 12 9 0 0 0 Coloma Community Schools 0 11 4 0 0 0 Eau Claire Public School 0 12 4 0 0 0 Medic 1 0 0 0 0 0 6 New Buffalo Schools 0 10 6 0 0 0 Niles Community Schools (FST) 0 35 3 3 2 0 Pine Ridge 1 0 1 0 0 0 Resource Transportation Group 25 0 25 10 0 0 SHAES 0 0 0 0 0 1 St Joseph Public Schools 0 14 7 0 0 0 Twin Cities Area Transportation Authority 2 0 2 0 2 2 Watervliet Public Schools 0 8 3 1 0 0 West Woods of Bridgman 0 0 0 1 0 0 Berrien County Subtotal: 29 170 105 56 6 10 1

According to Allegan County Emergency Management, Allegan County does not provide transportation services inside the 10-mile EPZ.

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Wheelchair Wheelchair Transportation Provider1 Cars Buses Vans Ambulances Buses Vans VAN BUREN COUNTY, MI Bangor School District 0 13 0 1 0 0 Bloomingdale School District 0 17 0 0 1 0 Covert School District 0 7 0 1 0 0 Decatur School District 0 9 0 1 0 0 Gobles School District 0 9 0 0 0 0 Hartford School District 0 12 0 0 0 0 Lawrence School District 0 8 0 0 0 0 Lawton School District 0 13 0 0 1 0 Mattawan School District 0 37 0 5 0 0 Paw Paw School District 0 19 0 1 0 0 South Haven School District 0 17 0 2 0 0 Van Buren ISD 0 9 0 25 0 0 Van Buren Transit 0 1 0 19 3 0 Van Buren County Subtotal: 0 171 0 55 5 0 EPZ TOTAL: 29 341 105 111 11 10 Resources Needed Schools (Table 3 7): 0 1072 0 0 0 0 Transit Dependent Population (Table 3 9): 0 13 0 0 0 0 Medical Facilities (Table 3 12): 0 8 0 9 3 5 Homebound Population with Access and/or 0 3 0 3 0 2 Functional Needs (Table 3 8):

TOTAL TRANSPORTATION NEEDS: 0 131 0 12 3 7 2

Resources needed for schools exclude 109 private vehicles used by the commuter students at Lake Michigan College - South Haven Campus Palisades Power Plant 8 12 KLD Engineering, P.C.

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Table 8 2. School Evacuation Time Estimates Good Weather Travel Time Travel Dist. from Time to EPZ EPZ Driver Loading Dist. To Average EPZ Bdry to Bdry to ETA to Mobilization Time EPZ Bdry Speed Bdry ETE THF THF THF School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

ALLEGAN COUNTY, MI Baseline Middle School 90 15 4.5 55.0 5 1:50 14.7 17 2:10 North Shore Elementary School 90 15 3.9 55.0 5 1:50 14.7 17 2:10 BERRIEN COUNTY, MI Salem Lutheran Preschool 90 15 1.4 21.9 4 1:50 15.1 17 2:10 Watervliet North Elementary School 90 15 1.0 9.3 7 1:55 0.4 1 2:00 Coloma Elementary School 90 15 0.9 25.3 3 1:50 15.1 17 2:10 Coloma Intermediate School 90 15 0.9 25.3 3 1:50 15.1 17 2:10 Coloma High School 90 15 0.9 25.3 3 1:50 15.1 17 2:10 Coloma Junior High School 90 15 0.9 25.3 3 1:50 15.1 17 2:10 VAN BUREN COUNTY, MI Maple Grove Elementary School 90 15 7.5 55.0 9 1:55 14.7 17 2:15 Head Start South Haven 90 15 7.0 50.1 9 1:55 14.7 17 2:15 Covert Middle School 90 15 10.1 30.6 20 2:05 0.6 1 2:10 Covert High School 90 15 10.1 30.6 20 2:05 0.6 1 2:10 Covert Elementary School 90 15 10.1 30.6 20 2:05 0.6 1 2:10 Head Start Migrant at Lincoln Elementary 90 15 7.0 44.8 10 1:55 14.7 17 2:15 Lincoln Elementary School 90 15 7.0 44.8 10 1:55 14.7 17 2:15 L.C. Mohr High School 90 15 7.0 44.8 10 1:55 14.7 17 2:15 St. Paul Lutheran School 90 15 6.9 52.9 8 1:55 14.7 17 2:15 St. Basil Catholic School 90 15 6.9 46.1 9 1:55 14.7 17 2:15 WAY South Haven Schools (LMC Campus) 90 15 5.7 55.0 7 1:55 14.7 17 2:15 Lake Michigan College South Haven 90 15 5.7 55.0 7 1:55 14.7 17 2:15 Campus Palisades Power Plant 8 13 KLD Engineering, P.C.

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Travel Time Travel Dist. from Time to EPZ EPZ Driver Loading Dist. To Average EPZ Bdry to Bdry to ETA to Mobilization Time EPZ Bdry Speed Bdry ETE THF THF THF School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

Wood School 90 15 4.0 41.2 6 1:55 14.2 16 2:15 Bangor High School 90 15 0.4 19.5 2 1:50 14.2 16 2:10 Bangor Middle School 90 15 0.4 19.5 2 1:50 14.2 16 2:10 Head Start Bangor 90 15 0.4 19.5 2 1:50 14.2 16 2:10 Bangor Alternative High School 90 15 0.4 19.5 2 1:50 14.2 16 2:10 South Walnut Elementary School 90 15 0.4 19.5 2 1:50 14.2 16 2:10 Maximum for EPZ: 2:05 Maximum: 2:15 Average for EPZ: 1:55 Average: 2:15 Palisades Power Plant 8 14 KLD Engineering, P.C.

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Table 8 3. School Evacuation Time Estimates - Rain/Light Snow Travel Time Travel Dist. from Time to EPZ EPZ Driver Loading Dist. To Average EPZ Bdry to Bdry to ETA to Mobilization Time EPZ Bdry Speed Bdry ETE THF THF THF School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

ALLEGAN COUNTY, MI Baseline Middle School 100 20 4.5 50.0 6 2:10 14.7 18 2:30 North Shore Elementary School 100 20 3.9 50.0 5 2:05 14.7 18 2:25 BERRIEN COUNTY, MI Salem Lutheran Preschool 100 20 1.4 18.2 5 2:05 15.1 19 2:25 Watervliet North Elementary School 100 20 1.0 9.1 7 2:10 0.4 1 2:15 Coloma Elementary School 100 20 0.9 23.0 3 2:05 15.1 19 2:25 Coloma Intermediate School 100 20 0.9 23.0 3 2:05 15.1 19 2:25 Coloma High School 100 20 0.9 23.0 3 2:05 15.1 19 2:25 Coloma Junior High School 100 20 0.9 23.0 3 2:05 15.1 19 2:25 VAN BUREN COUNTY, MI Maple Grove Elementary School 100 20 7.5 50.0 9 2:10 14.7 18 2:30 Head Start South Haven 100 20 7.0 46.5 10 2:10 14.7 18 2:30 Covert Middle School 100 20 10.1 26.1 24 2:25 0.6 1 2:30 Covert High School 100 20 10.1 26.1 24 2:25 0.6 1 2:30 Covert Elementary School 100 20 10.1 26.1 24 2:25 0.6 1 2:30 Head Start Migrant at Lincoln Elementary 100 20 7.0 41.7 11 2:15 14.7 18 2:35 Lincoln Elementary School 100 20 7.0 41.7 11 2:15 14.7 18 2:35 L.C. Mohr High School 100 20 7.0 41.7 11 2:15 14.7 18 2:35 St. Paul Lutheran School 100 20 6.9 49.1 9 2:10 14.7 18 2:30 St. Basil Catholic School 100 20 6.9 43.0 10 2:10 14.7 18 2:30 WAY South Haven Schools (LMC Campus) 100 20 5.7 50.0 7 2:10 14.7 18 2:30 Lake Michigan College South Haven 100 20 5.7 50.0 7 2:10 14.7 18 2:30 Campus Palisades Power Plant 8 15 KLD Engineering, P.C.

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Travel Time Travel Dist. from Time to EPZ EPZ Driver Loading Dist. To Average EPZ Bdry to Bdry to ETA to Mobilization Time EPZ Bdry Speed Bdry ETE THF THF THF School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

Wood School 100 20 4.0 37.8 7 2:10 14.2 18 2:30 Bangor High School 100 20 0.4 19.8 2 2:05 14.2 18 2:25 Bangor Middle School 100 20 0.4 19.8 2 2:05 14.2 18 2:25 Head Start Bangor 100 20 0.4 19.8 2 2:05 14.2 18 2:25 Bangor Alternative High School 100 20 0.4 19.8 2 2:05 14.2 18 2:25 South Walnut Elementary School 100 20 0.4 19.8 2 2:05 14.2 18 2:25 Maximum for EPZ: 2:25 Maximum: 2:35 Average for EPZ: 2:10 Average: 2:30 Palisades Power Plant 8 16 KLD Engineering, P.C.

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Table 8 4. School Evacuation Time Estimates - Heavy Snow Travel Time Dist. Travel Dist. To to EPZ Time from Driver Loading EPZ Average EPZ Bdry to EPZ Bdry ETA to Mobilization Time Bdry Speed Bdry ETE THF to THF THF School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

ALLEGAN COUNTY, MI Baseline Middle School 110 25 4.5 47.0 6 2:25 14.7 19 2:45 North Shore Elementary School 110 25 3.9 47.0 5 2:20 14.7 19 2:40 BERRIEN COUNTY, MI Salem Lutheran Preschool 110 25 1.4 16.5 6 2:25 15.1 20 2:45 Watervliet North Elementary School 110 25 1.0 8.2 8 2:25 0.4 1 2:30 Coloma Elementary School 110 25 0.9 22.2 3 2:20 15.1 20 2:40 Coloma Intermediate School 110 25 0.9 22.2 3 2:20 15.1 20 2:40 Coloma High School 110 25 0.9 22.2 3 2:20 15.1 20 2:40 Coloma Junior High School 110 25 0.9 22.2 3 2:20 15.1 20 2:40 VAN BUREN COUNTY, MI Maple Grove Elementary School 110 25 7.5 47.0 10 2:25 14.7 19 2:45 Head Start South Haven 110 25 7.0 42.7 10 2:25 14.7 19 2:45 Covert Middle School 110 25 10.1 32.6 19 2:35 0.6 1 2:40 Covert High School 110 25 10.1 32.6 19 2:35 0.6 1 2:40 Covert Elementary School 110 25 10.1 32.6 19 2:35 0.6 1 2:40 Head Start Migrant at Lincoln Elementary 110 25 7.0 38.4 11 2:30 14.7 19 2:50 Lincoln Elementary School 110 25 7.0 38.4 11 2:30 14.7 19 2:50 L.C. Mohr High School 110 25 7.0 38.4 11 2:30 14.7 19 2:50 St. Paul Lutheran School 110 25 6.9 45.0 10 2:25 14.7 19 2:45 St. Basil Catholic School 110 25 6.9 39.4 11 2:30 14.7 19 2:50 WAY South Haven Schools (LMC Campus) 110 25 5.7 47.0 8 2:25 14.7 19 2:45 Lake Michigan College South Haven 110 25 5.7 47.0 8 2:25 14.7 19 2:45 Campus Wood School 110 25 4.0 35.3 7 2:25 14.2 19 2:45 Palisades Power Plant 8 17 KLD Engineering, P.C.

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Travel Time Dist. Travel Dist. To to EPZ Time from Driver Loading EPZ Average EPZ Bdry to EPZ Bdry ETA to Mobilization Time Bdry Speed Bdry ETE THF to THF THF School Time (min) (min) (mi) (mph) (min) (hr:min) (mi.) (min) (hr:min)

Bangor Middle School 110 25 0.4 19.3 2 2:20 14.2 19 2:40 Head Start Bangor 110 25 0.4 19.3 2 2:20 14.2 19 2:40 Bangor Alternative High School 110 25 0.4 19.3 2 2:20 14.2 19 2:40 South Walnut Elementary School 110 25 0.4 19.3 2 2:20 14.2 19 2:40 Bangor Middle School 110 25 0.4 19.3 2 2:20 14.2 19 2:40 Maximum for EPZ: 2:35 Maximum: 2:50 Average for EPZ: 2:25 Average: 2:45 Palisades Power Plant 8 18 KLD Engineering, P.C.

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Table 8 5. Transit Dependent Evacuation Time Estimates Good Weather One Wave Two Wave Route Distance Travel Route Route Route Travel Pickup to Rec. Time to Driver Travel Pickup Route Number Mobilization Length Speed Time Time ETE Ctr. Rec. Ctr. Unload Rest Time Time ETE Number of Buses (min) (miles) (mph) (min) (min) (hr:min) (miles) (min) (min) (min) (min) (min) (hr:min) 1 1 150 9.8 55.0 11 30 3:15 8.3 9 5 10 30 30 4:40 2 1 150 9.0 55.0 10 30 3:10 14.7 16 5 10 36 30 4:50 3 1 150 8.6 51.0 10 30 3:15 0.4 0 5 10 20 30 4:20 2 150 5.8 48.3 7 30 3:10 14.7 16 5 10 29 30 4:40 4

2 170 5.8 48.5 7 30 3:30 14.7 16 5 10 29 30 5:00 2 150 6.2 46.8 8 30 3:10 14.2 15 5 10 30 30 4:40 5

1 170 6.2 47.2 8 30 3:30 14.2 15 5 10 30 30 5:00 2 150 7.8 55.0 9 30 3:10 14.4 16 5 10 33 30 4:45 6

1 170 7.8 55.0 9 30 3:30 14.4 16 5 10 33 30 5:05 Maximum ETE: 3:30 Maximum ETE: 5:05 Average ETE: 3:20 Average ETE: 4:50 Palisades Power Plant 8 19 KLD Engineering, P.C.

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Table 8 6. Transit Dependent Evacuation Time Estimates - Rain/Light Snow One Wave Two Wave Route Distance Travel Route Number Route Route Travel to Rec. Time to Driver Travel Route of Mobilization Length Speed Time Pickup ETE Ctr. Rec. Ctr. Unload Rest Time Pickup ETE Number Buses (min) (miles) (mph) (min) Time (min) (hr:min) (miles) (min) (min) (min) (min) Time (min) (hr:min) 1 1 160 9.8 50.0 12 40 3:35 8.3 10 5 10 34 40 5:15 2 1 160 9.0 50.0 11 40 3:35 14.7 18 5 10 40 40 5:30 3 1 160 8.6 46.4 11 40 3:35 0.4 0 5 10 22 40 4:55 2 160 5.8 44.2 8 40 3:30 14.7 18 5 10 33 40 5:20 4

2 180 5.8 43.6 8 40 3:50 14.7 18 5 10 33 40 5:40 2 160 6.2 42.4 9 40 3:30 14.2 17 5 10 33 40 5:15 5

1 180 6.2 41.4 9 40 3:50 14.2 17 5 10 33 40 5:35 2 160 7.8 50.0 9 40 3:30 14.4 17 5 10 36 40 5:20 6

1 180 7.8 49.9 9 40 3:50 14.4 17 5 10 36 40 5:40 Maximum ETE: 3:50 Maximum ETE: 5:40 Average ETE: 3:40 Average ETE: 5:25 Palisades Power Plant 8 20 KLD Engineering, P.C.

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Table 8 7. Transit Dependent Evacuation Time Estimates - Heavy Snow One Wave Two Wave Route Distance Travel Route Number Route Route Travel to Rec. Time to Driver Travel Route of Mobilization Length Speed Time Pickup ETE Ctr. Rec. Ctr. Unload Rest Time Pickup ETE Number Buses (min) (miles) (mph) (min) Time (min) (hr:min) (miles) (min) (min) (min) (min) Time (min) (hr:min) 1 1 170 9.8 47.0 13 50 3:55 8.3 11 5 10 34 50 5:45 2 1 170 9.0 47.0 11 50 3:55 14.7 19 5 10 40 50 6:00 3 1 170 8.6 42.8 12 50 3:55 0.4 1 5 10 23 50 5:25 2 170 5.8 41.4 8 50 3:50 14.7 19 5 10 34 50 5:50 4

2 190 5.8 41.7 8 50 4:10 14.7 19 5 10 33 50 6:10 2 170 6.2 39.3 9 50 3:50 14.2 18 5 10 35 50 5:50 5

1 190 6.2 39.1 10 50 4:10 14.2 18 5 10 34 50 6:10 2 170 7.8 47.0 10 50 3:50 14.4 18 5 10 37 50 5:50 6

1 190 7.8 47.0 10 50 4:10 14.4 18 5 10 36 50 6:10 Maximum ETE: 4:10 Maximum ETE: 6:10 Average ETE: 4:00 Average ETE: 5:55 Palisades Power Plant 8 21 KLD Engineering, P.C.

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Table 8 8. Medical Facility Evacuation Time Estimates - Good Weather Travel Loading Time to Rate Total EPZ Mobilization (min per Loading Dist. To EPZ Boundary ETE Medical Facility Patient (min) person) People Time (min) Bdry (mi) (min) (hr:min)

Ambulatory 90 1 43 30 4.9 6 2:10 Country Side Nursing Wheelchair bound 90 5 46 75 4.9 6 2:55 Home Bedridden 90 15 4 30 4.9 6 2:10 Forest Beach AFC Home Inc Ambulatory 90 1 16 16 1.4 10 2:00 Ambulatory 90 1 2 2 1.3 8 1:40 Juniper Home Wheelchair bound 90 5 4 20 1.3 8 2:00 Ambulatory 90 1 3 3 6.8 7 1:40 Bronson South Haven Wheelchair bound 90 5 2 10 6.8 7 1:50 Hospital Bedridden 90 15 1 15 6.8 8 1:55 South Haven Nursing & Ambulatory 90 1 10 10 6.8 7 1:50 Rehabilitation Community Wheelchair bound 90 5 51 75 6.8 7 2:55 Ambulatory 90 1 3 3 8.9 10 1:45 Turner Tender Care Wheelchair bound 90 5 3 15 8.9 10 1:55 Ambulatory 90 1 26 26 4.8 5 2:05 River Ridge Retirement Wheelchair bound 90 5 13 65 4.8 5 2:40 Village Bedridden 90 15 3 30 4.8 5 2:05 Maximum ETE: 2:55 Average ETE: 2:05 Palisades Power Plant 8 22 KLD Engineering, P.C.

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Table 8 9. Medical Facility Evacuation Time Estimates - Rain/Light Snow Travel Loading Time to Rate Total EPZ Mobilization (min per Loading Dist. To EPZ Boundary ETE Medical Facility Patient (min) person) People Time (min) Bdry (mi) (min) (hr:min)

Ambulatory 100 1 43 30 4.9 6 2:20 Country Side Nursing Wheelchair bound 100 5 46 75 4.9 6 3:05 Home Bedridden 100 15 4 30 4.9 6 2:20 Forest Beach AFC Home Ambulatory 100 1 16 16 1.4 14 2:10 Inc Ambulatory 100 1 2 2 1.3 9 1:55 Juniper Home Wheelchair bound 100 5 4 20 1.3 8 2:10 Ambulatory 100 1 3 3 6.8 8 1:55 Bronson South Haven Wheelchair bound 100 5 2 10 6.8 8 2:00 Hospital Bedridden 100 15 1 15 6.8 8 2:05 South Haven Nursing & Ambulatory 100 1 10 10 6.8 8 2:00 Rehabilitation Community Wheelchair bound 100 5 51 75 6.8 8 3:05 Ambulatory 100 1 3 3 8.9 11 1:55 Turner Tender Care Wheelchair bound 100 5 3 15 8.9 11 2:10 Ambulatory 100 1 26 26 4.8 6 2:15 River Ridge Retirement Wheelchair bound 100 5 13 65 4.8 6 2:55 Village Bedridden 100 15 3 30 4.8 6 2:20 Maximum ETE: 3:05 Average ETE: 2:20 Palisades Power Plant 8 23 KLD Engineering, P.C.

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Table 8 10. Medical Facility Evacuation Time Estimates - Heavy Snow Travel Loading Time to Rate Total EPZ Mobilization (min per Loading Dist. To EPZ Boundary ETE Medical Facility Patient (min) person) People Time (min) Bdry (mi) (min) (hr:min)

Ambulatory 110 1 43 30 4.9 7 2:30 Country Side Nursing Wheelchair bound 110 5 46 75 4.9 7 3:15 Home Bedridden 110 15 4 30 4.9 7 2:30 Forest Beach AFC Home Ambulatory 110 1 16 16 1.4 9 2:15 Inc Ambulatory 110 1 2 2 1.3 9 2:05 Juniper Home Wheelchair bound 110 5 4 20 1.3 9 2:20 Ambulatory 110 1 3 3 6.8 9 2:05 Bronson South Haven Wheelchair bound 110 5 2 10 6.8 9 2:10 Hospital Bedridden 110 15 1 15 6.8 9 2:15 South Haven Nursing & Ambulatory 110 1 10 10 6.8 9 2:10 Rehabilitation Community Wheelchair bound 110 5 51 75 6.8 9 3:15 Ambulatory 110 1 3 3 8.9 11 2:05 Turner Tender Care Wheelchair bound 110 5 3 15 8.9 11 2:20 Ambulatory 110 1 26 26 4.8 6 2:25 River Ridge Retirement Wheelchair bound 110 5 13 65 4.8 6 3:05 Village Bedridden 110 15 3 30 4.8 6 2:30 Maximum ETE: 3:15 Average ETE: 2:30 Palisades Power Plant 8 24 KLD Engineering, P.C.

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Table 8 11. Homebound Population with Access and/or Functional needs Evacuation Time Estimates Total Travel Mobiliza Loading Loading Time to People tion Time at Travel to Time at EPZ Requiring Vehicles Weather Time 1st Stop Subsequent Subsequent Boundary Vehicle Type Vehicle deployed Stops Conditions (min) (min) Stops (min) Stops (min) (min) ETE (hr:min)

Good 90 90 5 3:20 Buses 31 3 11 Rain 100 1 100 10 6 3:40 Snow 110 110 7 4:00 Good 90 54 5 3:05 Wheelchair 21 3 7 Rain 100 5 60 30 6 3:25 Buses Snow 110 66 7 3:40 Good 90 9 5 2:15 Ambulances 3 2 2 Rain 100 15 10 15 6 2:30 Snow 110 11 7 2:40 Maximum ETE: 4:00 Average ETE: 3:30 Palisades Power Plant 8 25 KLD Engineering, P.C.

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Event A Advisory to Evacuate B Bus Dispatched from Depot C Bus Arrives at Facility/Pick up Route D Bus Departs for Reception Center E Bus Exits Region F Bus Arrives at Reception Center/THF G Bus Available for Second Wave Evacuation Service Activity A B Driver Mobilization B C Travel to Facility or to Pick up Route C D Passengers Board the Bus D E Bus Travels Towards Region Boundary E F Bus Travels Towards Reception Center/THF Outside the EPZ F G Passengers Leave Bus; Driver Takes a Break Figure 8 1. Chronology of Transit Evacuation Operations Palisades Power Plant 8 26 KLD Engineering, P.C.

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9 TRAFFIC MANAGEMENT STRATEGY This section discusses the suggested Traffic Management Plan (TMP) that is designed to expedite the movement of evacuating traffic. The resources required to implement the TMP include:

• Personnel with the capabilities of performing the planned control functions of traffic guides (preferably, not necessarily, law enforcement officers).

• The Manual on Uniform Traffic Control Devices (MUTCD) published by the Federal Highway Administration (FHWA) of the U.S.D.O.T. provides guidance for Traffic Control Devices to assist these personnel in the performance of their tasks. All state and most county transportation agencies have access to the MUTCD, which is available online:

http://mutcd.fhwa.dot.gov which provides access to the official PDF version.

• A written plan that defines all Traffic Control Point (TCP) and Access Control Point (ACP) locations, provides necessary details and is documented in a format that is readily understood by those assigned to perform traffic control.

The functions to be performed in the field are:

1. Facilitate evacuating traffic movements that safely expedite travel out of the EPZ.

2. Discourage traffic movements that move evacuating vehicles in a direction which takes them significantly closer to the power plant, or which interferes with the efficient flow of other evacuees.

We employ the terms "facilitate" and "discourage" rather than "enforce" and "prohibit" to indicate the need for flexibility in performing the traffic control function. There are always legitimate reasons for a driver to prefer a direction other than that indicated. For example:

• A driver may be traveling home from work or from another location, to join other family members prior to evacuating.

• An evacuating driver may be travelling to pick up a relative, or other evacuees.

• The driver may be an emergency worker en route to perform an important activity.

The implementation of a TMP must also be flexible enough for the application of sound judgment by the traffic guide.

The TMP is the outcome of the following process:

1. The existing TCPs and ACPs identified by the offsite agencies in their existing emergency plans serve as the basis of the TMP, as per NUREG/CR 7002, Rev. 1. The ETE analysis treated all controlled intersections that are existing TCP or ACP locations in the county plans as being controlled by actuated signals. Appendix K identifies the number of intersections that were modeled as TCPs.

2. Evacuation simulations were run using DYNEV II to predict traffic congestion during evacuation (see Section 7.3 and Figure 7 3 through Figure 7 6). These simulations help to identify the best routing and critical intersections that experience pronounced traffic congestion during an evacuation. Any critical intersections that would benefit from Palisades Power Plant 91 KLD Engineering, P.C.

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traffic or access control which are not already identified in the existing offsite plans are examined. No additional TCPs or ACPs were identified as part of this study.

3. Prioritization of TCPs and ACPs. Application of traffic and access control at some TCPs and ACPs will have a more pronounced influence on expediting traffic movements than at other TCPs and ACPs. For example, TCPs controlling traffic originating from areas in close proximity to the power plant could have a more beneficial effect on minimizing potential exposure to radioactivity than those TCPs located far from the power plant.

Key locations for Manual Traffic Control (MTC) were analyzed and their impact to ETE was quantified, as per NUREG/CR 7002, Rev. 1. See Appendix G for more detail.

Appendix G documents the existing TMP and a list of priority TCPs using the process enumerated above.

9.1 Assumptions The ETE calculations documented in Section 7 and 8 assume that the TMP is implemented during evacuation.

The ETE calculations reflect the assumptions that all external external trips are interdicted and diverted after 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> have elapsed from the ATE.

All transit vehicles and other responders entering the EPZ to support the evacuation are assumed to be unhindered by personal manning TCPs and ACPs.

Study assumptions 1 through 3 in Section 2.5 further discuss TCP and ACP operations.

9.2 Additional Considerations The use of Intelligent Transportation Systems (ITS) technologies can reduce the manpower and equipment needs, while still facilitating the evacuation process. Dynamic Message Signs (DMS) can be placed within the EPZ to provide information to travelers regarding traffic conditions, route selection, and reception center information. DMS placed outside of the EPZ will warn motorists to avoid using routes that may conflict with the flow of evacuees away from the power plant. Highway Advisory Radio (HAR) can be used to broadcast information to evacuees during egress through their vehicles stereo systems. Automated Travel Information Systems (ATIS) can also be used to provide evacuees with information. Internet websites can provide traffic and evacuation route information before the evacuee begins their trip, while the on board navigation systems (GPS units) and smartphones can be used to provide information during the evacuation trip.

These are only some examples of how ITS technologies can benefit the evacuation process.

Consideration should be given that ITS technologies be used to facilitate the evacuation process, and any additional signage placed should consider evacuation needs.

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10 EVACUATION ROUTES AND RECEPTION CENTERS 10.1 Evacuation Routes Evacuation routes are comprised of two distinct components:

• Routing from a PAA being evacuated to the boundary of the Evacuation Region and thence out of the EPZ.

• Routing of transit dependent evacuees (schools, medical facilities and residents, employees or transients who do not own or have access to a private vehicle) from the EPZ boundary to THF/reception centers.

Evacuees will select routes within the EPZ in such a way as to minimize their exposure to risk.

This expectation is met by the DYNEV II model routing traffic away from the location of the plant, to the extent practicable. The DTRAD model satisfies this behavior by routing traffic so as to balance traffic demand relative to the available highway capacity to the extent possible.

See Appendices B through D for further discussion. The major evacuation routes for the EPZ are presented in Figure 10 1. These routes will be used by the general population evacuating in private vehicles, and by the transit dependent population evacuating in buses. Transit dependent evacuees will be routed to reception centers. General population may evacuate to either a reception center or some alternate destination (e.g., lodging facilities, relatives home, campgrounds) outside the EPZ.

The routing of transit dependent evacuees from the EPZ boundary to reception centers is designed to minimize the amount of travel outside the EPZ, from the points where these routes cross the EPZ boundary. The six bus routes, shown graphically in Figure 10 2 and described in Table 10 1, were designed as part of this ETE study for the express purpose of computing ETE for the transit dependent population. The routes were designed to traverse the major routes through the population centers in the EPZ. This does not imply that these exact routes would be used in an emergency. It is assumed that residents will walk to and congregate along the routes or walk along major evacuation routes to flag down a bus.

Schools and medical facilities were routed along the most likely path from the facility being evacuated to the EPZ boundary, traveling toward the appropriate THF or medical host facility.

The specified bus routes for all the transit dependent population are documented in Table 10 2 (refer to the maps of the link node analysis network in Appendix K for node locations). This study does not consider the transport of evacuees from reception centers to congregate care centers if the counties do make the decision to relocate evacuees.

10.2 Reception Centers Figure 10 3 maps the primary reception centers and THF for evacuees. Table 10 3 identifies the THF for each of the schools in the EPZ. It is assumed that all school evacuees will be taken to the appropriate THF and subsequently picked up by parents or guardians. Transit dependent evacuees are transported to the nearest reception center for each county.

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Table 10 1. Summary of Transit Dependent Bus Routes No. of Length Route Buses Descriptions (mi.)

1 1 Servicing communities in PAA 1 9.8 2 1 Servicing communities in PAA 2 9.0 3 1 Servicing communities in PAA 3 8.6 4 4 Servicing communities in PAA 4 5.8 5 3 Servicing communities in PAA 5 6.2 6 3 Servicing communities in PAA 5 7.8 Total: 13 Palisades Power Plant 10 2 KLD Engineering, P.C.

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Table 10 2. Bus Route Descriptions Bus Route Number Description Nodes Traversed from Route Start to EPZ Boundary Transit Dependent Routes 96, 322, 297, 298, 321, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 1 Transit Dependent Route for PAA 1 309, 310, 311, 312, 313 109, 110, 111, 112, 368, 113, 114, 115, 116, 117, 118, 566, 161, 44, 45, 2 Transit Dependent Route for PAA 2 46, 47, 48, 49, 50, 51 211, 476, 212, 477, 478, 213, 214, 215, 216, 217, 514, 218, 219, 513, 3 Transit Dependent Route for PAA 3 512, 220 115, 116, 117, 118, 119, 120, 121, 435, 380, 381, 382, 436, 123, 603, 4 Transit Dependent Route for PAA 4 604, 124, 125, 126, 127, 128, 129 5 Transit Dependent Route for PAA 5 (1 of 2) 426, 427, 428, 402, 524, 403, 263, 386, 387, 388, 264 6 Transit Dependent Route for PAA 5 (2 of 2) 234, 233, 383, 232, 231, 230, 15, 14, 13, 12, 11, 10 School Routes 9 Salem Lutheran Preschool 537, 517, 247, 248, 249, 373, 250 10 Watervliet North Elementary School 219, 513, 512, 220, 511 Bangor High School, Bangor Middle School, 11 Head Start Bangor, Bangor Alternative High 387, 388, 264 School, South Walnut Elementary School 12 Wood School 402, 524, 403, 263, 386, 387, 388, 264 Covert High School, Covert Middle School, 211, 476, 212, 477, 478, 213, 214, 215, 216, 217, 514, 218, 219, 513, 14 Covert Elementary School 512, 220 15 North Shore Elementary School 469, 122, 380, 381, 163, 46, 47, 48, 49, 50, 51 16 Baseline Middle School 121, 435, 380, 381, 163, 46, 47, 48, 49, 50, 51, 52 L.C. Mohr High School, Lincoln Elementary 473, 472, 471, 202, 470, 201, 150, 466, 467, 118, 566, 161, 44, 45, 46, 29 School, Head Start Migrant at Lincoln 47, 48, 49, 50, 51 Elementary 30 St. Paul Lutheran School 165, 154, 115, 116, 117, 118, 566, 161, 44, 45, 46, 47, 48, 49, 50, 51, 52 32 Head Start South Haven 166, 165, 154, 115, 116, 117, 118, 566, 161, 44, 45, 46, 47, 48, 49, 50, 51 Palisades Power Plant 10 3 KLD Engineering, P.C.

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Bus Route Number Description Nodes Traversed from Route Start to EPZ Boundary School Routes (Continued) 545, 474, 202, 470, 201, 150, 466, 467, 118, 566, 161, 44, 45, 46, 47, 48, 33 St. Basil Catholic School 49, 50, 51 Coloma High School, Coloma Junior High 34 School, Coloma Intermediate School, Coloma 249, 373, 250 Elementary School 35 Maple Grove Elementary School 168, 115, 116, 117, 118, 566, 161, 44, 45, 46, 47, 48, 49, 50, 51, 52 Lake Michigan College South Haven Campus, 36 571, 565, 563, 161, 44, 45, 46, 47, 48, 49, 50, 51, 52 WAY South Haven Schools (LMC Campus)

Medical Facility Routes 24 Juniper Home 515, 243, 219, 513, 512, 220 25 Forest Beach AFC Home Inc 535, 619, 618, 218, 219, 513, 512, 220 Bronson South Haven Hospital, South Haven 26 153, 154, 115, 116, 117, 118, 566, 161, 44, 45, 46, 47, 48, 49, 50, 51, 52 Nursing & Rehabilitation Community 27 Country Side Nursing Home 157, 601, 121, 435, 380, 381, 163, 46, 47, 48, 49, 50, 51, 52 28 River Ridge Retirement Village 121, 435, 380, 381, 163, 46, 47, 48, 49, 50, 51, 52 37 Turner Tender Care 440, 439, 160, 563, 161, 44, 45, 46, 47, 48, 49, 50 Palisades Power Plant 10 4 KLD Engineering, P.C.

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Table 10 3. Temporary Host Facilities School Temporary Host Facility Baseline Middle School Fennville Middle School North Shore Elementary School Salem Lutheran Preschool St. Joseph High School Watervliet North Elementary School Watervliet South Elementary Coloma Elementary School Coloma Intermediate School St. Joseph High School Coloma High School Coloma Junior High School Maple Grove Elementary School Fennville Middle School Head Start - South Haven Covert Middle School Covert High School Hartford High School Covert Elementary School Head Start - Migrant at Lincoln Elementary Lincoln Elementary School L.C. Mohr High School St. Paul Lutheran School Fennville Middle School St. Basil Catholic School WAY South Haven Schools (LMC Campus)

Lake Michigan College - South Haven Campus Wood School Bangor High School Bangor Middle School Bloomingdale High School Head Start - Bangor Bangor Alternative High School South Walnut Elementary School Palisades Power Plant 10 5 KLD Engineering, P.C.

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Figure 10 1. Evacuation Route Map Palisades Power Plant 10 6 KLD Engineering, P.C.

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Figure 10 2. Transit Dependent Bus Routes Palisades Power Plant 10 7 KLD Engineering, P.C.

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Figure 10 3. General Population Reception Centers and Temporary Host Facilities Palisades Power Plant 10 8 KLD Engineering, P.C.

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APPENDIX A Glossary of Traffic Engineering Terms

A. GLOSSARY OF TRAFFIC ENGINEERING TERMS Table A 1. Glossary of Traffic Engineering Terms Term Definition Analysis Network A graphical representation of the geometric topology of a physical roadway system, which is comprised of directional links and nodes.

Link A network link represents a specific, one directional section of roadway. A link has both physical (length, number of lanes, topology, etc.) and operational (turn movement percentages, service rate, free flow speed) characteristics.

Measures of Effectiveness Statistics describing traffic operations on a roadway network.

Node A network node generally represents an intersection of network links. A node has control characteristics, i.e., the allocation of service time to each approach link.

Origin A location attached to a network link, within the EPZ or Shadow Region, where trips are generated at a specified rate in vehicles per hour (vph). These trips enter the roadway system to travel to their respective destinations.

Prevailing Roadway and Relates to the physical features of the roadway, the nature (e.g.,

Traffic Conditions composition) of traffic on the roadway and the ambient conditions (weather, visibility, pavement conditions, etc.).

Service Rate Maximum rate at which vehicles, executing a specific turn maneuver, can be discharged from a section of roadway at the prevailing conditions, expressed in vehicles per second (vps) or vehicles per hour (vph).

Service Volume Maximum number of vehicles which can pass over a section of roadway in one direction during a specified time period with operating conditions at a specified Level of Service (The Service Volume at the upper bound of Level of Service, E, equals Capacity).

Service Volume is usually expressed as vehicles per hour (vph).

Signal Cycle Length The total elapsed time to display all signal indications, in sequence.

The cycle length is expressed in seconds.

Signal Interval A single combination of signal indications. The interval duration is expressed in seconds. A signal phase is comprised of a sequence of signal intervals, usually green, yellow, red.

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Term Definition Signal Phase A set of signal indications (and intervals) which services a particular combination of traffic movements on selected approaches to the intersection. The phase duration is expressed in seconds.

Traffic (Trip) Assignment A process of assigning traffic to paths of travel in such a way as to satisfy all trip objectives (i.e., the desire of each vehicle to travel from a specified origin in the network to a specified destination) and to optimize some stated objective or combination of objectives. In general, the objective is stated in terms of minimizing a generalized "cost". For example, "cost" may be expressed in terms of travel time.

Traffic Density The number of vehicles that occupy one lane of a roadway section of specified length at a point in time, expressed as vehicles per mile (vpm).

Traffic (Trip) Distribution A process for determining the destinations of all traffic generated at the origins. The result often takes the form of a Trip Table, which is a matrix of origin destination traffic volumes.

Traffic Simulation A computer model designed to replicate the real world operation of vehicles on a roadway network, so as to provide statistics describing traffic performance. These statistics are called Measures of Effectiveness.

Traffic Volume The number of vehicles that pass over a section of roadway in one direction, expressed in vehicles per hour (vph). Where applicable, traffic volume may be stratified by turn movement.

Travel Mode Distinguishes between private auto, bus, rail, pedestrian and air travel modes.

Trip Table or Origin A rectangular matrix or table, whose entries contain the number Destination Matrix of trips generated at each specified origin, during a specified time period, that are attracted to (and travel toward) each of its specified destinations. These values are expressed in vehicles per hour (vph) or in vehicles.

Turning Capacity The capacity associated with that component of the traffic stream which executes a specified turn maneuver from an approach at an intersection.

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APPENDIX B DTRAD: Dynamic Traffic Assignment and Distribution Model

B. DYNAMIC TRAFFIC ASSIGNMENT AND DISTRIBUTION MODEL This section describes the integrated dynamic trip assignment and distribution model named DTRAD (Dynamic Traffic Assignment and Distribution) that is expressly designed for use in analyzing evacuation scenarios. DTRAD employs logit based path choice principles and is one of the models of the DYNEVII System. The DTRAD module implements path based Dynamic Traffic Assignment (DTA) so that time dependent Origin Destination (OD) trips are assigned to routes over the network based on prevailing traffic conditions.

To apply the DYNEV II System, the analyst must specify the highway network, link capacity information, the time varying volume of traffic generated at all origin centroids and, optionally, a set of accessible candidate destination nodes on the periphery of the EPZ for selected origins.

DTRAD calculates the optimal dynamic trip distribution (i.e., trip destinations) and the optimal dynamic trip assignment (i.e., trip routing) of the traffic generated at each origin node traveling to its set of candidate destination nodes, so as to minimize evacuee travel cost.

Overview of Integrated Distribution and Assignment Model The underlying premise is that the selection of destinations and routes is intrinsically coupled in an evacuation scenario. That is, people in vehicles seek to travel out of an area of potential risk as rapidly as possible by selecting the best routes. The model is designed to identify these best routes in a manner that realistically distributes vehicles from origins to destinations and routes them over the highway network, in a consistent and optimal manner, reflecting evacuee behavior.

For each origin, a set of candidate destination nodes is selected by the software logic and by the analyst to reflect the desire by evacuees to travel away from the power plant and to access major highways. The specific destination nodeswithin this set that are selected by travelers and the selection of the connecting paths of travel, are both determined by DTRAD. This determination is made by a logit based path choice model in DTRAD, so as to minimize the trip cost, as discussed later.

The traffic loading on the network and the consequent operational traffic environment of the network (density, speed, throughput on each link) vary over time as the evacuation takes place.

The DTRAD model, which is interfaced with the DYNEV simulation model, executes a succession of sessions wherein it computes the optimal routing and selection of destination nodes for the conditions that exist at that time.

Interfacing the DYNEV Simulation Model with DTRAD The DYNEV II system reflects NRC guidance that evacuees will seek to travel in a general direction away from the location of the hazardous event. An algorithm was developed to support the DTRAD model in dynamically varying the Trip Table (O D matrix) over time from one DTRAD session to the next. Another algorithm executes a mapping from the specified geometric network (link node analysis network) that represents the physical highway system, to a path network that represents the vehicle [turn] movements. DTRAD computations are performed on the path network: DYNEV simulation model, on the geometric network.

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DTRAD Description DTRAD is the DTA module for the DYNEV II System.

When the road network under study is large, multiple routing options are usually available between trip origins and destinations. The problem of loading traffic demands and propagating them over the network links is called Network Loading and is addressed by DYNEVII using macroscopic traffic simulation modeling. Traffic assignment deals with computing the distribution of the traffic over the road network for given O D demands and is a model of the route choice of the drivers. Travel demand changes significantly over time, and the road network may have time dependent characteristics, e.g., time varying signal timing or reduced road capacity because of lane closure, or traffic congestion. To consider these time dependencies, DTA procedures are required.

The DTRAD DTA module represents the dynamic route choice behavior of drivers, using the specification of dynamic origin destination matrices as flow input. Drivers choose their routes through the network based on the travel cost they experience (as determined by the simulation model). This allows traffic to be distributed over the network according to the time dependent conditions. The modeling principles of D TRAD include:

It is assumed that drivers not only select the best route (i.e., lowest cost path) but some also select less attractive routes. The algorithm implemented by DTRAD archives several efficient routes for each O D pair from which the drivers choose.

The choice of one route out of a set of possible routes is an outcome of discrete choice modeling. Given a set of routes and their generalized costs, the percentages of drivers that choose each route is computed. The most prevalent model for discrete choice modeling is the logit model. DTRAD uses a variant of Path Size Logit model (PSL). PSL overcomes the drawback of the traditional multinomial logit model by incorporating an additional deterministic path size correction term to address path overlapping in the random utility expression.

DTRAD executes the Traffic Assignment (TA) algorithm on an abstract network representation called "the path network" which is built from the actual physical link node analysis network. This execution continues until a stable situation is reached: the volumes and travel times on the edges of the path network do not change significantly from one iteration to the next. The criteria for this convergence are defined by the user.

Travel cost plays a crucial role in route choice. In DTRAD, path cost is a linear summation of the generalized cost of each link that comprises the path. The generalized cost for a link, a, is expressed as ca ta la sa ,

where ca is the generalized cost for link a, and , , and are cost coefficients for link travel time, distance, and supplemental cost, respectively. Distance and supplemental costs are defined as invariant properties of the network model, while travel time is a dynamic property dictated by prevailing traffic conditions. The DYNEV simulation model Palisades Power Plant B2 KLD Engineering, P.C.

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computes travel times on all edges in the network and DTRAD uses that information to constantly update the costs of paths. The route choice decision model in the next simulation iteration uses these updated values to adjust the route choice behavior. This way, traffic demands are dynamically re assigned based on time dependent conditions.

The interaction between the DTRAD traffic assignment and DYNEV II simulation models is depicted in Figure B 1. Each round of interaction is called a Traffic Assignment Session (TA session). A TA session is composed of multiple iterations, marked as loop B in the figure.

The supplemental cost is based on the survival distribution (a variation of the exponential distribution).The Inverse Survival Function is a cost term in DTRAD to represent the potential risk of travel toward the plant:

sa = ln (p), 0 p l ; 0 p=

dn = Distance of node, n, from the plant d0 =Distance from the plant where there is zero risk

= Scaling factor The value of do = 10 miles, the outer distance of the EPZ. Note that the supplemental cost, sa, of link, a, is (high, low), if its downstream node, n, is (near, far from) the power plant.

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Network Equilibrium In 1952, John Wardrop wrote:

Under equilibrium conditions traffic arranges itself in congested networks in such a way that no individual trip maker can reduce his path costs by switching routes.

The above statement describes the User Equilibrium definition, also called the Selfish Driver Equilibrium. It is a hypothesis that represents a [hopeful] condition that evolves over time as drivers search out alternative routes to identify those routes that minimize their respective costs. It has been found that this equilibrium objective to minimize costs is largely realized by most drivers who routinely take the same trip over the same network at the same time (i.e.,

commuters). Effectively, such drivers learn which routes are best for them over time. Thus, the traffic environment settles down to a near equilibrium state.

Clearly, since an emergency evacuation is a sudden, unique event, it does not constitute a long term learning experience which can achieve an equilibrium state. Consequently, DTRAD was not designed as an equilibrium solution, but to represent drivers in a new and unfamiliar situation, who respond in a flexible manner to real time information (either broadcast or observed) in such a way as to minimize their respective costs of travel.

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Start of next DTRAD Session A

Set T0 Clock time.

Archive System State at T0 Define latest Link Turn Percentages Execute Simulation Model from B time, T0 to T1 (burn time)

Provide DTRAD with link MOE at time, T1 Execute DTRAD iteration; Get new Turn Percentages Retrieve System State at T0 ;

Apply new Link Turn Percents DTRAD iteration converges?

No Yes Next iteration Simulate from T0 to T2 (DTA session duration)

Set Clock to T2 B A Figure B 1. Flow Diagram of Simulation DTRAD Interface Palisades Power Plant B5 KLD Engineering, P.C.

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APPENDIX C DYNEV Traffic Simulation Model

C. DYNEV TRAFFIC SIMULATION MODEL The DYNEV traffic simulation model is a macroscopic model that describes the operations of traffic flow in terms of aggregate variables: vehicles, flow rate, mean speed, volume, density, queue length, on each link, for each turn movement, during each Time Interval (simulation time step). The model generates trips from sources and from Entry Links and introduces them onto the analysis network at rates specified by the analyst based on the mobilization time distributions. The model simulates the movements of all vehicles on all network links over time until the network is empty. At intervals, the model outputs Measures of Effectiveness (MOE) such as those listed in Table C 1.

Model Features Include:

Explicit consideration is taken of the variation in density over the time step; an iterative procedure is employed to calculate an average density over the simulation time step for the purpose of computing a mean speed for moving vehicles.

Multiple turn movements can be serviced on one link; a separate algorithm is used to estimate the number of (fractional) lanes assigned to the vehicles performing each turn movement, based, in part, on the turn percentages provided by the DTRAD model.

At any point in time, traffic flow on a link is subdivided into two classifications: queued and moving vehicles. The number of vehicles in each classification is computed. Vehicle spillback, stratified by turn movement for each network link, is explicitly considered and quantified. The propagation of stopping waves from link to link is computed within each time step of the simulation. There is no vertical stacking of queues on a link.

Any link can accommodate source flow from zones via side streets and parking facilities that are not explicitly represented. This flow represents the evacuating trips that are generated at the source.

The relation between the number of vehicles occupying the link and its storage capacity is monitored every time step for every link and for every turn movement. If the available storage capacity on a link is exceeded by the demand for service, then the simulator applies a metering rate to the entering traffic from both the upstream feeders and source node to ensure that the available storage capacity is not exceeded.

A path network that represents the specified traffic movements from each network link is constructed by the model; this path network is utilized by the DTRAD model.

A two way interface with DTRAD: (1) provides link travel times; (2) receives data that translates into link turn percentages.

Provides MOE to animation software, EVAN Calculates ETE statistics Palisades Power Plant C1 KLD Engineering, P.C.

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All traffic simulation models are data intensive. Table C 2 outlines the necessary input data elements.

To provide an efficient framework for defining these specifications, the physical highway environment is represented as a network. The unidirectional links of the network represent roadway sections: rural, multi lane, urban streets or freeways. The nodes of the network generally represent intersections or points along a section where a geometric property changes (e.g. a lane drop, change in grade or free flow speed).

Figure C 1 is an example of a small network representation. The freeway is defined by the sequence of links, (20,21), (21,22), and (22,23). Links (8001, 19) and (3, 8011) are Entry and Exit links, respectively. An arterial extends from node 3 to node 19 and is partially subsumed within a grid network. Note that links (21,22) and (17,19) are grade separated.

C.1 Methodology C.1.1 The Fundamental Diagram It is necessary to define the fundamental diagram describing flow density and speed density relationships. Rather than settling for a triangular representation, a more realistic representation that includes a capacity drop, (I R)Qmax, at the critical density when flow conditions enter the forced flow regime, is developed and calibrated for each link. This representation, shown in Figure C 2, asserts a constant free speed up to a density, k , and then a linear reduction in speed in the range, k k k 45 vpm, the density at capacity. In the flow density plane, a quadratic relationship is prescribed in the range, k k 95 vpm which roughly represents the stop and go condition of severe congestion. The value of flow rate, Q , corresponding to k , is approximated at 0.7 RQ . A linear relationship between k and k completes the diagram shown in Figure C 2. Table C 3 is a glossary of terms.

The fundamental diagram is applied to moving traffic on every link. The specified calibration values for each link are: (1) Free speed, v ; (2) Capacity, Q  ; (3) Critical density, k 45 vpm ; (4) Capacity Drop Factor, R = 0.9 ; (5) Jam density, k . Then, v , k k

. Setting k k k , then Q RQ k for 0 k k 50 . It can be shown that Q 0.98 0.0056 k RQ for k k k , where k 50 and k 175.

C.1.2 The Simulation Model The simulation model solves a sequence of unit problems. Each unit problem computes the movement of traffic on a link, for each specified turn movement, over a specified time interval (TI) which serves as the simulation time step for all links. Figure C 3 is a representation of the unit problem in the time distance plane. Table C 3 is a glossary of terms that are referenced in the following description of the unit problem procedure.

The formulation and the associated logic presented below are designed to solve the unit problem for each sweep over the network (discussed below), for each turn movement serviced Palisades Power Plant C2 KLD Engineering, P.C.

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on each link that comprises the evacuation network, and for each TI over the duration of the evacuation.

Given Q , M , L , TI , E , LN , G C , h , L , R , L , E , M Compute O , Q , M Define O O O O ; E E E

1. For the first sweep, s = 1, of this TI, get initial estimates of mean density, k , the R - factor, R and entering traffic, E , using the values computed for the final sweep of the prior TI.

For each subsequent sweep, s 1 , calculate E P O S where P , O are the relevant turn percentages from feeder link, i , and its total outflow (possibly metered) over this TI; S is the total source flow (possibly metered) during the current TI.

Set iteration counter, n = 0, k k , and E E .

2. Calculate v k such that k 130 using the analytical representations of the fundamental diagram.

Q TI G Calculate Cap 3600 C LN , in vehicles, this value may be reduced due to metering Set R 1.0 if G C 1 or if k k ; Set R 0.9 only if G C 1 and k k L

Calculate queue length, L Q LN

3. Calculate t TI . If t 0 , set t E O 0 ; Else, E E .

4. Then E E E ; t TI t

5. If Q Cap , then O Cap , O O 0 If t 0 , then Q Q M E Cap Else Q Q Cap End if Calculate Q and M using Algorithm A below

6. Else Q Cap O Q , RCap Cap O

7. If M RCap , then Palisades Power Plant C3 KLD Engineering, P.C.

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t Cap

8. If t 0, O M ,O min RCap M , 0 TI Q E O If Q 0 , then Calculate Q , M with Algorithm A Else Q 0, M E End if Else t 0 O M and O 0 M M O E; Q 0 End if

9. Else M O 0 If t 0 , then O RCap , Q M O E Calculate Q and M using Algorithm A

10. Else t 0 M M If M ,

O RCap Q M O Apply Algorithm A to calculate Q and M Else O M M M O E and Q 0 End if End if End if End if

11. Calculate a new estimate of average density, k k 2k k ,

where k = density at the beginning of the TI k = density at the end of the TI k = density at the mid point of the TI All values of density apply only to the moving vehicles.

If k k and n N where N max number of iterations, and is a convergence criterion, then Palisades Power Plant C4 KLD Engineering, P.C.

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12. set n n 1 , and return to step 2 to perform iteration, n, using k k .

End if Computation of unit problem is now complete. Check for excessive inflow causing spillback.

13. If Q M , then The number of excess vehicles that cause spillback is: SB Q M ,

where W is the width of the upstream intersection. To prevent spillback, meter the outflow from the feeder approaches and from the source flow, S, during this TI by the amount, SB. That is, set SB M 1 0 , where M is the metering factor over all movements .

E S This metering factor is assigned appropriately to all feeder links and to the source flow, to be applied during the next network sweep, discussed later.

Algorithm A This analysis addresses the flow environment over a TI during which moving vehicles can join a standing or discharging queue. For the case Qb vQ shown, Q Cap, with t 0 and a queue of Qe Qe length, Q , formed by that portion of M and E that reaches the stop bar within the TI, but could v not discharge due to inadequate capacity. That is, Mb Q M E . This queue length, Q v Q M E Cap can be extended to Q by L3 traffic entering the approach during the current TI, traveling at speed, v, and reaching the rear of the t1 t3 queue within the TI. A portion of the entering TI vehicles, E E , will likely join the queue. This analysis calculates t , Q and M for the input values of L, TI, v, E, t, L , LN, Q .

When t 0 and Q Cap:

L L Define: L Q . From the sketch, L v TI t t L Q E .

LN LN Substituting E E yields: vt E L v TI t L . Recognizing that the first two terms on the right hand side cancel, solve for t to obtain:

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L t such that 0 t TI t E L v

TI LN If the denominator, v 0, set t TI t .

t t t Then, Q Q E , M E 1 TI TI The complete Algorithm A considers all flow scenarios; space limitation precludes its inclusion, here.

C.1.3 Lane Assignment The unit problem is solved for each turn movement on each link. Therefore it is necessary to calculate a value, LN , of allocated lanes for each movement, x. If in fact all lanes are specified by, say, arrows painted on the pavement, either as full lanes or as lanes within a turn bay, then the problem is fully defined. If however there remain un channelized lanes on a link, then an analysis is undertaken to subdivide the number of these physical lanes into turn movement specific virtual lanes, LNx.

C.2 Implementation C.2.1 Computational Procedure The computational procedure for this model is shown in the form of a flow diagram as Figure C 4. As discussed earlier, the simulation model processes traffic flow for each link independently over TI that the analyst specifies; it is usually 60 seconds or longer. The first step is to execute an algorithm to define the sequence in which the network links are processed so that as many links as possible are processed after their feeder links are processed, within the same network sweep. Since a general network will have many closed loops, it is not possible to guarantee that every link processed will have all of its feeder links processed earlier.

The processing then continues as a succession of time steps of duration, TI, until the simulation is completed. Within each time step, the processing performs a series of sweeps over all network links; this is necessary to ensure that the traffic flow is synchronous over the entire network. Specifically, the sweep ensures continuity of flow among all the network links; in the context of this model, this means that the values of E, M, and S are all defined for each link such that they represent the synchronous movement of traffic from each link to all of its outbound links. These sweeps also serve to compute the metering rates that control spillback.

Within each sweep, processing solves the unit problem for each turn movement on each link.

With the turn movement percentages for each link provided by the DTRAD model, an algorithm allocates the number of lanes to each movement serviced on each link. The timing at a signal, if Palisades Power Plant C6 KLD Engineering, P.C.

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any, applied at the downstream end of the link, is expressed as a G/C ratio, the signal timing needed to define this ratio is an input requirement for the model. The model also has the capability of representing, with macroscopic fidelity, the actions of actuated signals responding to the time varying competing demands on the approaches to the intersection.

The solution of the unit problem yields the values of the number of vehicles, O, that discharge from the link over the time interval and the number of vehicles that remain on the link at the end of the time interval as stratified by queued and moving vehicles: Q and M . The procedure considers each movement separately (multi piping). After all network links are processed for a given network sweep, the updated consistent values of entering flows, E; metering rates, M; and source flows, S are defined so as to satisfy the no spillback condition.

The procedure then performs the unit problem solutions for all network links during the following sweep.

Experience has shown that the system converges (i.e. the values of E, M and S settle down for all network links) in just two sweeps if the network is entirely under saturated or in four sweeps in the presence of extensive congestion with link spillback. (The initial sweep over each link uses the final values of E and M, of the prior TI). At the completion of the final sweep for a TI, the procedure computes and stores all measures of effectiveness for each link and turn movement for output purposes. It then prepares for the following time interval by defining the values of Q and M for the start of the next TI as being those values of Q and M at the end of the prior TI. In this manner, the simulation model processes the traffic flow over time until the end of the run. Note that there is no space discretization other than the specification of network links.

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C.2.2 Interfacing with Dynamic Traffic Assignment (DTRAD)

The DYNEV II system reflects NRC guidance that evacuees will seek to travel in a general direction away from the location of the hazardous event. Thus, an algorithm was developed to identify an appropriate set of destination nodes for each origin based on its location and on the expected direction of travel. This algorithm also supports the DTRAD model in dynamically varying the Trip Table (O D matrix) over time from one DTRAD session to the next.

Figure B 1 depicts the interaction of the simulation model with the DTRAD model in the DYNEV II system. As indicated, DYNEV II performs a succession of DTRAD sessions; each such session computes the turn link percentages for each link that remain constant for the session duration, T , T , specified by the analyst. The end product is the assignment of traffic volumes from each origin to paths connecting it with its destinations in such a way as to minimize the network wide cost function. The output of the DTRAD model is a set of updated link turn percentages which represent this assignment of traffic.

As indicated in Figure B 1, the simulation model supports the DTRAD session by providing it with operational link MOE that are needed by the path choice model and included in the DTRAD cost function. These MOE represent the operational state of the network at a time, T T , which lies within the session duration, T , T . This burn time, T T , is selected by the analyst. For each DTRAD iteration, the simulation model computes the change in network operations over this burn time using the latest set of link turn percentages computed by the DTRAD model. Upon convergence of the DTRAD iterative procedure, the simulation model accepts the latest turn percentages provided by the Dynamic Traffic Assignment (DTA) model, returns to the origin time, T , and executes until it arrives at the end of the DTRAD session duration at time, T . At this time the next DTA session is launched and the whole process repeats until the end of the DYNEV II run.

Additional details are presented in Appendix B.

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Table C 1. Selected Measures of Effectiveness Output by DYNEV II Measure Units Applies To Vehicles Discharged Vehicles Link, Network, Exit Link Speed Miles/Hours (mph) Link, Network Density Vehicles/Mile/Lane Link Level of Service LOS Link Content Vehicles Network Travel Time Vehicle hours Network Evacuated Vehicles Vehicles Network, Exit Link Trip Travel Time Vehicle minutes/trip Network Capacity Utilization Percent Exit Link Attraction Percent of total evacuating vehicles Exit Link Max Queue Vehicles Node, Approach Time of Max Queue Hours:minutes Node, Approach Length (mi); Mean Speed (mph); Travel Route Statistics Route Time (min)

Mean Travel Time Minutes Evacuation Trips; Network Palisades Power Plant C9 KLD Engineering, P.C.

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Table C 2. Input Requirements for the DYNEV II Model HIGHWAY NETWORK Links defined by upstream and downstream node numbers Link lengths Number of lanes (up to 6) and channelization Turn bays (1 to 3 lanes)

Destination (exit) nodes Network topology defined in terms of downstream nodes for each receiving link Node Coordinates (X,Y)

Nuclear Power Plant Coordinates (X,Y)

GENERATED TRAFFIC VOLUMES On all entry links and source nodes (origins), by Time Period TRAFFIC CONTROL SPECIFICATIONS Traffic signals: link specific, turn movement specific Signal control treated as fixed time or actuated Location of traffic control points (these are represented as actuated signals)

Stop and Yield signs Right turn on red (RTOR)

Route diversion specifications Turn restrictions Lane control (e.g., lane closure, movement specific)

DRIVERS AND OPERATIONAL CHARACTERISTICS Drivers (vehicle specific) response mechanisms: free flow speed, discharge headway Bus route designation.

DYNAMIC TRAFFIC ASSIGNMENT Candidate destination nodes for each origin (optional)

Duration of DTA sessions Duration of simulation burn time Desired number of destination nodes per origin INCIDENTS Identify and Schedule of closed lanes Identify and Schedule of closed links Palisades Power Plant C 10 KLD Engineering, P.C.

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Table C 3. Glossary The maximum number of vehicles, of a particular movement, that can discharge Cap from a link within a time interval.

The number of vehicles, of a particular movement, that enter the link over the E

time interval. The portion, ETI, can reach the stop bar within the TI.

The green time: cycle time ratio that services the vehicles of a particular turn G/C movement on a link.

h The mean queue discharge headway, seconds.

k Density in vehicles per lane per mile.

The average density of moving vehicles of a particular movement over a TI, on a k

link.

L The length of the link in feet.

The queue length in feet of a particular movement, at the [beginning, end] of a L ,L time interval.

The number of lanes, expressed as a floating point number, allocated to service a LN particular movement on a link.

L The mean effective length of a queued vehicle including the vehicle spacing, feet.

M Metering factor (Multiplier): 1.

The number of moving vehicles on the link, of a particular movement, that are M ,M moving at the [beginning, end] of the time interval. These vehicles are assumed to be of equal spacing, over the length of link upstream of the queue.

The total number of vehicles of a particular movement that are discharged from a O

link over a time interval.

The components of the vehicles of a particular movement that are discharged from a link within a time interval: vehicles that were Queued at the beginning of O ,O ,O the TI; vehicles that were Moving within the link at the beginning of the TI; vehicles that Entered the link during the TI.

The percentage, expressed as a fraction, of the total flow on the link that P

executes a particular turn movement, x.

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The number of queued vehicles on the link, of a particular turn movement, at the Q ,Q

[beginning, end] of the time interval.

The maximum flow rate that can be serviced by a link for a particular movement Q in the absence of a control device. It is specified by the analyst as an estimate of link capacity, based upon a field survey, with reference to the HCM 2016.

R The factor that is applied to the capacity of a link to represent the capacity drop when the flow condition moves into the forced flow regime. The lower capacity at that point is equal to RQ .

RCap The remaining capacity available to service vehicles of a particular movement after that queue has been completely serviced, within a time interval, expressed as vehicles.

S Service rate for movement x, vehicles per hour (vph).

t Vehicles of a particular turn movement that enter a link over the first t seconds of a time interval, can reach the stop bar (in the absence of a queue down stream) within the same time interval.

TI The time interval, in seconds, which is used as the simulation time step.

v The mean speed of travel, in feet per second (fps) or miles per hour (mph), of moving vehicles on the link.

v The mean speed of the last vehicle in a queue that discharges from the link within the TI. This speed differs from the mean speed of moving vehicles, v.

W The width of the intersection in feet. This is the difference between the link length which extends from stop bar to stop bar and the block length.

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8011 8009 2 3 8104 8107 6 5 8008 8010 8 9 10 8007 8012 12 11 8006 8005 13 14 8014 15 25 8004 16 24 8024 17 8003 23 22 21 20 8002 Entry, Exit Nodes are 19 numbered 8xxx 8001 Figure C 1. Representative Analysis Network Palisades Power Plant C 13 KLD Engineering, P.C.

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Volume, vph Capacity Drop Qmax R Qmax Qs Density, vpm Flow Regimes Speed, mph Free Forced vf R vc Density, vpm kf kc kj ks Figure C 2. Fundamental Diagrams Palisades Power Plant C 14 KLD Engineering, P.C.

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Distance OQ OM OE Down Qb vQ Qe v

v L

Mb Me Up t1 t2 Time E1 E2 TI Figure C 3. A UNIT Problem Configuration with t1 > 0 Palisades Power Plant C 15 KLD Engineering, P.C.

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Sequence Network Links Next Time step, of duration, TI A

Next sweep; Define E, M, S for all B

Links C Next Link D Next Turn Movement, x Get lanes, LNx Service Rate, Sx ; G/Cx Get inputs to Unit Problem:

Q b , Mb , E Solve Unit Problem: Qe , Me , O No D Last Movement ?

Yes No Last Link ? C Yes No B Last Sweep ?

Yes Calc., store all Link MOE Set up next TI :

No A Last Time - step ?

Yes DONE Figure C 4. Flow of Simulation Processing (See Glossary: Table C 3)

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APPENDIX D DETAILED DESCRIPTION OF STUDY PROCEDURE

D. DETAILED DESCRIPTION OF STUDY PROCEDURE This appendix describes the activities that were performed to compute Evacuation Time Estimates. The individual steps of this effort are represented as a flow diagram in Figure D 1.

Each numbered step in the description that follows corresponds to the numbered element in the flow diagram.

Step 1 The first activity was to obtain EPZ boundary information and create a GIS base map. The base map extends beyond the Shadow Region which extends approximately 15 miles (radially) from the power plant location. The base map incorporates the local roadway topology, a suitable topographic background and the EPZ and PAA boundaries.

Step 2 2020 Census block information was obtained in GIS format. This information was used to estimate the permanent resident population within the EPZ and Shadow Region and to define the spatial distribution and demographic characteristics of the population within the study area. The employee, transient, school and other special facility data used in the 2012 ETE study was updated by the county emergency management agencies and by Entergy/Holtec.

Step 3 A kickoff meeting was conducted with major stakeholders (state and county emergency planning personnel, on site and off site utility emergency planning personnel, local and state law enforcement agencies). The purpose of the kickoff meeting was to present an overview of the work effort, identify key agency personnel, and indicate the data requirements for the study. Specific requests for information were presented to county emergency planning personnel. Unique features of the study area were discussed to identify the local concerns that should be addressed by the ETE study.

Step 4 Next, a physical survey of the roadway system in the study area was conducted to determine the geometric properties of the highway sections, the channelization of lanes on each section of roadway, whether there are any turn restrictions or special treatment of traffic at intersections, the type and functioning of traffic control devices, gathering signal timings for pre timed traffic signals (if any exist within the study area), and to make the necessary observations needed to estimate realistic values of roadway capacity. Roadway characteristics were also verified using aerial imagery.

Step 5 An online demographic survey of households within the EPZ was conducted to identify household dynamics, trip generation characteristics, and evacuation related demographic information of the EPZ population. This information was used to determine important study factors including the average number of evacuating vehicles used by each household, and the time required to perform pre evacuation mobilization activities.

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Step 6 A computerized representation of the physical roadway system, called a link node analysis network, was developed using the most recent UNITES software (see Section 1.3) developed by KLD. Once the geometry of the network was completed, the network was calibrated using the information gathered during the road survey (Step 4) and information obtained from aerial imagery. Estimates of highway capacity for each link and other link specific characteristics were introduced to the network description. Traffic signal timings were input accordingly. The link node analysis network was imported into a GIS map. The 2020 permanent resident population estimates (Step 2) were overlaid in the map, and origin centroids where trips would be generated during the evacuation process were assigned to appropriate links.

Step 7 The EPZ is subdivided into 7 PAAs. Based on wind direction and speed, Regions (groupings of PAAs) that may be advised to evacuate, were developed.

The need for evacuation can occur over a range of time of day, day of week, seasonal and weather related conditions. Scenarios were developed to capture the variation in evacuation demand, highway capacity and mobilization time, for different time of day, day of the week, time of year, and weather conditions.

Step 8 The input stream for the DYNEV II model, which integrates the dynamic traffic assignment and distribution model, DTRAD, with the evacuation simulation model, was created for a prototype evacuation case - the evacuation of the entire EPZ for a representative scenario.

Step 9 After creating this input stream, the DYNEV II System was executed on the prototype evacuation case to compute evacuating traffic routing patterns consistent with the appropriate NRC guidelines. DYNEV II contains an extensive suite of data diagnostics which check the completeness and consistency of the input data specified. The analyst reviews all warning and error messages produced by the model and then corrects the database to create an input stream that properly executes to completion.

The model assigns destinations to all origin centroids consistent with a (general) radial evacuation of the EPZ and Shadow Region. The analyst may optionally supplement and/or replace these model assigned destinations, based on professional judgment, after studying the topology of the analysis highway network. The model produces link and network wide measures of effectiveness as well as estimates of evacuation time.

Step 10 The results generated by the prototype evacuation case are critically examined. The examination includes observing the animated graphics (using the EVAN software - see Section 1.3) and reviewing the statistics output by the model. This is a labor intensive activity, requiring the direct participation of skilled engineers who possess the necessary practical experience to interpret the results and to determine the causes of any problems reflected in Palisades Power Plant D2 KLD Engineering, P.C.

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the results.

Essentially, the approach is to identify those bottlenecks in the network that represent locations where congested conditions are pronounced and to identify the cause of this congestion. This cause can take many forms, either as excess demand due to high rates of trip generation, improper routing, a shortfall of capacity, or as a quantitative flaw in the way the physical system was represented in the input stream. This examination leads to one of two conclusions:

The results are satisfactory; or The input stream must be modified accordingly.

This decision requires, of course, the application of the user's judgment and experience based upon the results obtained in previous applications of the model and a comparison of the results of the latest prototype evacuation case iteration with the previous ones. If the results are satisfactory in the opinion of the user, then the process continues with Step 13. Otherwise, proceed to Step 11.

Step 11 There are many "treatments" available to the user in resolving apparent problems. These treatments range from decisions to reroute the traffic by assigning additional evacuation destinations for one or more sources, imposing turn restrictions where they can produce significant improvements in capacity, changing the control treatment at critical intersections so as to provide improved service for one or more movements, adding routes or in prescribing specific treatments for channelizing the flow so as to expedite the movement of traffic along major roadway systems. Such "treatments" take the form of modifications to the original prototype evacuation case input stream. All treatments are designed to improve the representation of evacuation behavior.

Step 12 As noted above, the changes to the input stream must be implemented to reflect the modifications undertaken in Step 11. At the completion of this activity, the process returns to Step 9 where the DYNEV II System is again executed.

Step 13 Evacuation of transit dependent evacuees and special facilities are included in the evacuation analysis. Fixed routing for transit buses and for school buses, ambulances, and other transit vehicles are introduced into the final prototype evacuation case data set. DYNEV II generates route specific speeds over time for use in the estimation of evacuation times for the transit dependent and special facility population groups.

Step 14 The prototype evacuation case was used as the basis for generating all region and scenario specific evacuation cases to be simulated. This process was automated through the UNITES user interface. For each specific case, the population to be evacuated, the trip generation Palisades Power Plant D3 KLD Engineering, P.C.

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distributions, the highway capacity and speeds, and other factors are adjusted to produce a customized case specific data set.

Step 15 All evacuation cases are executed using the DYNEV II System to compute ETE. Once results were available, quality control procedures were used to assure the results were consistent, dynamic routing was reasonable, and traffic congestion/bottlenecks were addressed properly. Traffic management plans are analyzed, and traffic control points are prioritized, if applicable.

Additional analysis is conducted to identify the sensitivity of the ETE to changes in some base evacuation conditions and model assumptions.

Step 16 Once vehicular evacuation results are accepted, average travel speeds for transit and special facility routes were used to compute ETE for transit dependent permanent residents, schools, medical facilities, and homebound population with access and/or functional needs .

Step 17 The simulation results are analyzed, tabulated and graphed. The results were then documented, as required by NUREG/CR 7002, Rev. 1.

Step 18 Following the completion of documentation activities, the ETE criteria checklist (see Appendix N) was completed. An appropriate report reference is provided for each criterion provided in the checklist.

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A Step 1 Step 10 Create GIS Base Map Examine Prototype Evacuation Case using EVAN and DYNEV II Output Step 2 Gather Census Block and Demographic Data for Results Satisfactory Study Area Step 11 Step 3 Modify Evacuation Destinations and/or Develop Conduct Kickoff Meeting with Stakeholders Traffic Control Treatments Step 4 Step 12 Field Survey of Roadways within Study Area Modify Database to Reflect Changes to Prototype Evacuation Case Step 5 Conduct Demographic Survey and Develop Trip Generation Characteristics B

Step 13 Step 6 Establish Transit and Special Facility Evacuation Review and Calibrate Link Node Analysis Routes and Update DYNEV II Database Network Step 14 Step 7 Generate DYNEV II Input Streams for All Evacuation Cases Develop Evacuation Regions and Scenarios Step 15 Step 8 Execute DYNEV II to Compute ETE for All Create and Debug DYNEV II Input Stream Evacuation Cases Step 16 Step 9 Use DYNEV II Average Speed Output to Compute ETE for Transit and Special Facility Routes B Execute DYNEV II for Prototype Evacuation Case Step 17 Documentation A Step 18 Complete ETE Criteria Checklist Figure D 1. Flow Diagram of Activities Palisades Power Plant D5 KLD Engineering, P.C.

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APPENDIX E Special Facility Data

E. SPECIAL FACILITY DATA The following tables list population information, as of May 2022, for special facilities that are located within the PPP EPZ. Special facilities are defined as schools, preschools, and medical facilities. Transient population data is included in the tables for recreational areas (beaches, campgrounds, golf courses, marinas, parks, other recreational areas) and lodging facilities.

Employment data is included in the table for major employers. Each table is grouped by county.

The location of the facility is defined by its straight line distance (miles) and direction (magnetic bearing) from the center point of the plant. Maps of each school, preschool, medical facility, major employer, recreational area (beach, campground, golf course, marina, park, casino), and lodging facility are also provided.

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Table E 1. Schools and Preschools within the EPZ Distance Dire Enroll PAA (miles) ction School Name Street Address Municipality ment ALLEGAN COUNTY,MI 4 7.4 NNE Baseline Middle School 7357 Baseline Rd South Haven 460 4 7.6 NNE North Shore Elementary School 7320 N Shore Dr South Haven 314 Allegan County Subtotal: 774 BERRIEN COUNTY,MI 5 9.1 S Salem Lutheran Preschool 275 Marvin St Coloma 6 5 9.1 SSE Watervliet North Elementary School 287 Baldwin Ave Watervliet 293 5 9.7 S Coloma Elementary School 262 S W St Coloma 375 5 9.7 S Coloma Intermediate School 274 S W St Coloma 375 5 10.0 S Coloma High School 300 W St Joseph St Coloma 430 5 10.1 S Coloma Junior High School 300 W St Joseph St Coloma 300 Berrien County Subtotal: 1,779 VAN BUREN COUNTY,MI 2 5.0 NE Maple Grove Elementary School 72399 12th Ave South Haven 303 2 5.0 NNE Head Start South Haven 540 Aylworth Ave South Haven 40 3 3.6 SE Covert Middle School 35323 M 140 Hwy Covert 73 3 3.6 SE Covert High School 35323 M 140 Hwy Covert 102 3 3.6 SE Covert Elementary School 35323 M 140 Hwy Covert 100 4 5.2 NNE Head Start Migrant at Lincoln Elementary 500 Elkenburg St South Haven 15 4 5.2 NNE Lincoln Elementary School 500 Elkenburg St South Haven 207 4 5.3 NNE L.C. Mohr High School 600 Elkenburg St South Haven 522 4 5.3 NNE St. Paul Lutheran School 718 Arbor Ct South Haven 73 4 5.6 NNE St. Basil Catholic School 94 Superior St South Haven 125 4 7.0 NNE WAY South Haven Schools (LMC Campus) 125 Veterans Blvd South Haven 30 4 7.0 NNE Lake Michigan College South Haven Campus 125 Veterans Blvd South Haven 400 5 6.6 E Wood School 29842 66th St Bangor 25 5 9.9 E Bangor High School 801 W Arlington St Bangor 360 5 9.9 E Bangor Middle School 803 W Arlington St Bangor 335 5 10.4 E Head Start Bangor 305 W Douglas St Bangor 47 5 10.4 E Bangor Alternative High School 12 N Walnut St Bangor 100 5 10.5 E South Walnut Elementary School 309 S Walnut St Bangor 330 Van Buren County Subtotal: 3,187 EPZ TOTAL: 5,740 Palisades Power Plant E2 KLD Engineering, P.C.

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Table E 2. Medical Facilities within the EPZ Ambul Wheel Bed Distance Dire Cap Current atory chair ridden PAA (miles) ction Facility Name Street Address Municipality acity Census Patients Patients Patients ALLEGAN COUNTY,MI 4 7.0 NNE Country Side Nursing Home 120 Baseline Rd South Haven 93 93 43 46 4 Allegan County Subtotal: 93 93 43 46 4 BERRIEN COUNTY,MI 5 8.7 SSE Forest Beach AFC Home Inc 8021 Forest Beach Rd Watervliet 20 16 16 0 0 5 9.1 SSE Juniper Home 612 Van Atter Ct Watervliet 6 6 2 4 0 Berrien County Subtotal: 26 22 18 4 0 VAN BUREN COUNTY,MI 4 5.4 NNE Bronson South Haven Hospital 955 S Bailey Ave South Haven 8 6 3 2 1 4 5.5 NNE South Haven Nursing & Rehabilitation Community 850 Phillips St South Haven 88 61 10 51 0 4 6.8 NE Turner Tender Care 10871 68th St South Haven 6 6 3 3 0 4 7.1 NNE River Ridge Retirement Village 706 Kentucky Ave South Haven 44 42 26 13 3 Van Buren County Subtotal: 146 115 42 69 4 EPZ TOTAL: 265 230 103 119 8 Table E 3. Major Employers within the EPZ

% Employee Employees Employees Vehicles Distance Dire Employees Commuting Commuting Commuting PAA (miles) ction Facility Name Street Address Municipality (Max Shift) into the EPZ into the EPZ into the EPZ VAN BUREN COUNTY,MI 1 Palisades Nuclear Generating Station 27780 Blue Star Memorial Hwy Covert 568 71.0% 403 366 4 6.4 NNE Meijer 1223 Phoenix St South Haven 234 60.0% 140 127 5 9.8 SSE Four Winds Casino Hartford 68600 Red Arrow Hwy Hartford 300 70.0% 210 191 Van Buren County Subtotal: 1,102 753 684 EPZ TOTAL: 1,102 753 684 Palisades Power Plant E3 KLD Engineering, P.C.

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Table E 4. Recreational Areas within the EPZ Distance Dire PAA (miles) ction Facility Name Street Address Municipality Facility Type Transients Vehicles ALLEGAN COUNTY,MI 4 7.6 NNE Jensen's RV Park & Motel 7366 N Shore Dr South Haven Campground 80 30 4 7.8 NNE Cousins' R/V park 105 Blue Star Hwy N. Shore Dr South Haven Campground 600 140 4 8.2 NNE Singing Sands RV Park 262 74th St South Haven Campground 360 240 4 10.3 NNE Hawkshead Links 523 Hawks Nest Dr South Haven Golf Course 100 50 Seasonal Population: 503 281 Allegan County Subtotal: 1,643 741 BERRIEN COUNTY,MI 5 8.6 SSW Hagar Park/Beach 5408 M 63 Coloma Beach 277 100 5 8.7 SSE Paw Paw River Campgrounds 5355 M 140 Watervliet Campground 264 132 5 9.1 S Paw Paw Lake Golf Club 4548 Forest Beach Rd Watervliet Golf Course 200 25 5 9.7 SSW Coloma St. Joseph KOA 3527 Coloma Rd Riverside Campground 500 125 Seasonal Population: 547 302 Berrien County Subtotal: 1,788 684 VAN BUREN COUNTY,MI 1 0.7 NE Van Buren State Park 23960 Ruggles Rd South Haven Park 450 84 1 1.6 SSW Covert Township Park 80559 32nd Ave Covert Park 342 146 3 4.3 SE Covert / South Haven KOA Holiday 39397 Michigan 140 Covert Campground 732 366 3 4.5 S Dune Lake Campground 80739 County Rd 376 Coloma Campground 320 160 4 5.6 NNE South Beach Water St South Haven Beach 875 269 4 6.0 NNE North Beach Lakeshore Dr South Haven Beach 875 269 4 6.7 NNE Kal Haven Trail North Bailey Ave South Haven Park 38 13 4 6.8 NE Black River Trails Campground 68840 8th Ave South Haven Campground 194 74 4 6.9 NNE Lake Michigan College 125 Veterans Blvd South Haven Park 240 222 4 7.0 NE Beeches Golf Club 09601 68th St South Haven Golf Course 84 22 4 9.2 NE Kal Haven Outpost 00500 Co Rd 687 South Haven Campground 231 104 4 9.5 NE Yogi Bear's Jellystone Park Camp Resort 03403 64th St South Haven Campground 568 142 4 10.5 ENE GingerMan Raceway 61414 Phoenix Rd South Haven Park 300 150 5 10.1 SSE Four Winds Casino 68600 Red Arrow Hwy Hartford Casino 5,000 2,500 Seasonal Population: 2,526 1,394 Van Buren County Subtotal: 12,775 5,915 EPZ TOTAL: 16,206 7,340 Palisades Power Plant E4 KLD Engineering, P.C.

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Table E 5. Marinas within the EPZ Distance Dire PAA (miles) ction Facility Name Street Address Municipality Transients Vehicles BERRIEN COUNTY,MI 5 8.3 S Paw Paw Lake Yacht Club 5097 Shoreview Dr Coloma 27 7 Berrien County Subtotal: 27 7 VAN BUREN COUNTY,MI 4 5.8 NNE South Haven Municipal Marina South 345 Water St South Haven 733 458 4 5.9 NNE South Haven Municipal Marina North 148 Black River St South Haven 350 174 4 6.0 NNE South Haven Yacht Club 401 Williams St South Haven 28 7 4 6.0 NNE All Seasons Marine Inc 234 Black River St South Haven 200 50 4 6.1 NNE Maritime Docks 268 Black River St South Haven 112 56 4 6.3 NNE Slip Away Cove Marina and Residences 132 Dunkley Ave South Haven 50 27 4 6.4 NNE 1st Choice Marine Inc. 626 Dunkley Ave South Haven 8 4 4 6.4 NNE Black River Park Marina and Boat Launch E Wells St South Haven 240 120 4 6.6 NNE Black River Yacht Club Oak St South Haven 275 138 4 6.6 NNE River Noire Yacht Club Oak St South Haven 90 23 4 6.7 NNE Jones River Services 12 N Bailey Ave South Haven 90 45 4 6.8 NNE Woodland Harbor Marina 525 Kentucky Ave South Haven 352 176 Van Buren County Subtotal: 2,528 1,278 EPZ TOTAL: 2,555 1,285 Palisades Power Plant E5 KLD Engineering, P.C.

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Table E 6. Lodging Facilities within the EPZ Distance Dire PAA (miles) ction Facility Name Street Address Municipality Transients Vehicles ALLEGAN COUNTY,MI 4 7.4 NNE A Country Place Bed & Breakfast 79 N Shore Dr South Haven 55 25 4 7.6 NNE Sleepy Hollow Resort 7400 N Shore Dr South Haven 120 40 4 7.6 NNE Jensen's RV Park & Motel 7366 N Shore Dr South Haven 24 14 4 8.1 NNE Sun N Sand Resort 176 N Blue Star Hwy South Haven 91 33 4 9.6 NNE Martha's Vineyard 473 Blue Star Hwy South Haven 57 26 Allegan County Subtotal: 347 138 BERRIEN COUNTY,MI 5 7.6 S Duffield's Cottages 7039 Little Paw Paw Lake Rd Coloma 36 17 5 7.6 SSW Sand Castles of Lake Michigan 6125 Ontario St Coloma 18 9 5 8.2 SSW Sweet Cherry Resort 3312 Chestnut Ave Coloma 36 12 5 8.5 S Paw Paw Lake Motel 4881 Wil O Paw Dr Coloma 104 48 Berrien County Subtotal: 194 86 VAN BUREN COUNTY,MI 2 3.9 NNE Lake Bluff Inn & Suites 76648 11th Ave South Haven 208 52 2 4.7 NNE Great Lakes Inn Suites 9814 Michigan 140 South Haven 106 55 4 5.6 NE Monroe Manor Inn Bed & Breakfast 72861 8th Ave South Haven 26 12 4 6.0 NNE Sunset Inn Bed & Breakfast 72 N. Shore Dr South Haven 22 11 4 6.0 NNE Carriage House at the Harbor 118 Woodman St South Haven 23 12 4 6.0 NNE Historic Hotel Nichols 201 Center St South Haven 34 17 4 6.0 NNE Last Resort Bed & Breakfast 86 N Shore Dr South Haven 21 14 4 6.1 NNE Old Harbor Inn 515 Williams St South Haven 180 45 4 6.2 NNE Yelton Manor Boutique Hotel B&B 140 N Shore Dr South Haven 17 17 4 6.2 NNE Inn at the Park Bed & Breakfast 233 Dyckman Ave South Haven 20 10 4 6.4 NNE A&R's North Beach Cottages 282 N Shore Dr South Haven 40 14 4 6.4 NNE MichiMonaMac Lakeshore Cottage 337 N Shore Dr South Haven 30 7 4 6.5 NNE Hampton Inn 4299 Cecilia Dr South Haven 180 120 4 6.6 NNE Victoria Resort Bed & Breakfast 241 Oak St South Haven 64 16 4 6.6 NNE Baymont Inn & Suites 1555 Phoenix St South Haven 360 90 4 6.7 NE Holiday Inn Express Hotel & Suites South Haven 1741 Phoenix St South Haven 186 62 4 6.7 NE Comfort Suites 1755 Phoenix St South Haven 244 61 4 7.2 NNE Great Lakes Inn & Suites 186 Blue Star Hwy South Haven 270 125 4 7.9 NE Black River Inn Bed and Breakfast 704 70th St South Haven 6 3 4 9.8 NE Elmhurst Farm Inn 634 64th St South Haven 8 4 Van Buren County Subtotal: 2,045 747 EPZ TOTAL: 2,586 971 Palisades Power Plant E6 KLD Engineering, P.C.

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Figure E 1. Schools and Preschools within the EPZ Palisades Power Plant E7 KLD Engineering, P.C.

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Figure E 2. Medical Facilities within the EPZ Palisades Power Plant E8 KLD Engineering, P.C.

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Figure E 3. Major Employers within the EPZ Palisades Power Plant E9 KLD Engineering, P.C.

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Figure E 4. Recreational Areas within the EPZ Palisades Power Plant E 10 KLD Engineering, P.C.

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Figure E 5. Marinas within the EPZ Palisades Power Plant E 11 KLD Engineering, P.C.

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Figure E 6. Lodging Facilities within the EPZ Palisades Power Plant E 12 KLD Engineering, P.C.

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APPENDIX F Demographic Survey

F. DEMOGRAPHIC SURVEY F.1 Introduction The development of ETE for the PPP EPZ requires the identification of travel patterns, car ownership and household size of the population within the EPZ. Demographic information can be obtained from Census data. The use of this data has several limitations when applied to emergency planning. First, the Census data do not encompass the range of information needed to identify the time required for preliminary activities (mobilization) that must be undertaken prior to evacuating the area. Secondly, Census data do not contain attitudinal responses needed from the population of the EPZ and consequently may not accurately represent the anticipated behavioral characteristics of the evacuating populace.

These concerns are addressed by conducting a demographic survey of a representative sample of the EPZ population. The survey is designed to elicit information from the public concerning family demographics and estimates of response times to well defined events. The design of the survey includes a limited number of questions of the form What would you do if ? and other questions regarding activities with which the respondent is familiar (How long does it take you to ?)

F.2 Survey Instrument and Sampling Plan Attachment A presents the final survey instrument used for the demographic survey in this study. A draft of the instrument was submitted to stakeholders for comment. Comments were received and the survey instrument was modified accordingly, prior to conducting the survey.

Following the completion of the instrument, a sampling plan was developed. Since the demographic survey discussed herein began in July 2021 before the release of the 2020 Census data in September 2021, 2010 Census data was used to develop the sampling plan. A sample size of approximately 379 completed survey forms yields results with a sampling error of +/-5%

at the 95% confidence level. The desired sample was to be obtained from the EPZ population.

Consequently, a list of zip codes in the EPZ was developed using geographic information system (GIS) software. This list is shown in Table F 1. Along with each zip code, an estimate of the population and number of households in each area was determined by overlaying 2010 Census data and the EPZ boundary, again using GIS software. The proportional number of desired completed survey interviews for each area was identified, as shown in Table F 1. Note that the average household size computed in Table F 1 was an estimate for sampling purposes and was not used in the ETE study.

A total of 133 completed surveys were obtained in the survey, corresponding to a sampling error of +/-8.5% at the 95% confidence level based on the 2010 Census data. Although the number of completed surveys provided in Table F 1 was less than the desired number of surveys, the analysis results are somewhat in line with the 2010 telephone survey used in the previous (2012) ETE study Palisades Power Plant F1 KLD Engineering, P.C.

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F.3 Survey Results The results of the survey fall into two categories. First, the household demographics of the area can be identified. Demographic information includes such factors as household size, automobile ownership, and automobile availability. The distributions of the time to perform certain pre evacuation activities are the second category of survey results. These data are processed to develop the trip generation distributions used in the evacuation modeling effort, as discussed in Section 5.

A review of the survey instrument reveals that several questions have a decline to state entry for a response. It is accepted practice in conducting surveys of this type to accept the answers of a respondent who offers a decline to state response for a few questions or who refuses to answer a few questions. To address the issue of occasional decline to state responses from a large sample, the practice is to assume that the distribution of these responses is the same as the underlying distribution of the positive responses. In effect, the decline to state responses are ignored, and the distributions are based upon the positive data that is acquired.

F.3.1 Household Demographic Results Household Size Figure F 1 presents the distribution of household size within the EPZ based on the responses to the demographic survey. According to the responses, the average household contains 2.77 people. The estimated average household size from the 2010 Census data is 2.51 people and from the 2020 Census data is 2.41 people. A sensitivity study was conducted to estimate the impact of using the 2020 Census data household size on ETE - see Appendix M.

Automobile Ownership The average number of automobiles available per household in the EPZ is 2.26. It should be noted that all households within the EPZ have access to an automobile according to the demographic survey. The distribution of automobile ownership is presented in Figure F 2.

Figure F 3 presents the automobile availability by household size.

Ridesharing The overwhelming proportion (76%) of the households surveyed responded that they would share a ride with a neighbor, relative, or friend if a car was not available to them when advised to evacuate in the event of an emergency, as shown in Figure F 4.

Commuters Figure F 5 presents the distribution of the number of commuters in each household.

Commuters are defined as household members who travel to work or college on a daily basis.

The data shows an average of 1.53 commuters per household in the EPZ, and 86% of households have at least one commuter.

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Commuter Travel Modes Figure F 6 presents the mode of travel that commuters use on a daily basis. The vast majority (89%) of commuters use their private automobiles to travel to work or college. The data shows an average of 1.10 employees per vehicle, assuming 2 people per vehicle - on average - for carpools.

Impact of COVID 19 on Commuters Figure F 7 presents the distribution of the number of commuters in each household that were temporarily impacted by the COVID 19 pandemic. Forty two percent (42.4%) of households indicated someone in their household had a work and/or school commute that was temporarily impacted by the COVID 19 pandemic. The commuter patterns were compared to the telephone survey conducted for the previous ETE study (2012). The commuter travel patterns are very similar between the telephone survey and the demographic survey, despite the significant number of households impacted by the COVID 19 pandemic.

Functional or Transportation Needs Figure F 8 presents the distribution of the number of individuals with functional or transportation need. The survey results show that 11 households (3.4% of the total surveyed) have functional or transportation needs. Of those with functional or transportation needs, 6 homes (55%) require a bus, and 5 homes (45%) require some other transportation mode. As discussed in Section 3.8, there are 55 people registered with the EPZ counties as having access and/or functional needs, which is only 0.2% of the EPZ population.

F.3.2 Evacuation Response Several questions were asked to gauge the populations response to an emergency. These are now discussed:

How many of the vehicles would your household use during an evacuation? The response is shown in Figure F 9. On average, evacuating households would use 1.50 vehicles.

Would your family await the return of other family members prior to evacuating the area?

Of the survey participants who responded, 58% said they would await the return of other family members before evacuating and 42% indicated that they would not await the return of other family members.

Emergency officials advise you to take shelter in place in an emergency. Would you? This question is designed to elicit information regarding compliance with instructions to shelter in place. The results indicate that 72% of households who are advised to shelter in place would do so; the remaining 28% would choose to evacuate the area. Note the baseline ETE study assumes 20% of households will not comply with the shelter advisory, as per Section 2.5.2 of NUREG/CR 7002, Rev. 1. Thus, the compliance rate obtained through the survey is higher (8%

more) than the federal guidance recommendation. A sensitivity study was conducted to estimate the impact of shadow evacuation (non compliance to a shelter advisory) on ETE - see Appendix M.

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Emergency officials advise you to take shelter in place now in an emergency and possibly evacuate later while people in other areas are advised to evacuate now. Would you? This question is designed to elicit information specifically related to the possibility of a staged evacuation. That is, asking a population to shelter in place now and then to evacuate after a specified period of time. Results indicate that 51% of households would follow instructions and delay the start of evacuation until so advised, while the balance of 49% would choose to begin evacuating immediately.

Emergency officials advise you to evacuate due to an emergency. Where would you evacuate to? This question is designed to elicit information regarding the destination of evacuees in case of an evacuation. Approximately 56% of households indicated that they would evacuate to a friend or relatives home, 3% to a reception center, 15% to a hotel, motel or campground, 5%

to a second or seasonal home, and the remaining 21% answered other/decline to state to this question, as shown in Figure F 10. It should be noted that none of the households surveyed indicated they would not evacuate.

If you had a household pet, would you take your pet with you if you were asked to evacuate the area? Based on the responses to the survey, 66% of households have a family pet, service animal, and or animal/livestock. Of the households with pets, 97% percent of them indicated that they would take their pets with them; approximately 34% of households would take their pets to a shelter with them, 63% would take their pets with them somewhere else, and 3%

would leave their pet at home, as shown in Figure F 11.

What type of pet(s) and/or animal(s) do you have? Based on the responses to the survey, 87% of households have a household pet (dog, cat, bird, reptile, or fish), 9% of households have farm animals (horse, chicken, goat, pig, etc.), and 4% have other small pets/animals.

F.3.3 Time Distribution Results The survey asked several questions about the amount of time it takes to perform certain pre evacuation activities. These activities involve actions taken by residents during the course of their day to day lives. Thus, the answers fall within the realm of the responders experience.

As discussed in Section F.3.1 and shown in Figure F 7, the majority (57.6%) of respondents indicated no commuters were impacted by the COVID 19 pandemic; therefore the results for the time distribution of commuters (time to prepare to leave work/college and time to travel home from work/college) were used, as is, in this study.

The mobilization distributions provided below are the result of having applied the analysis described in Section 5.4.1 on the component activities of the mobilization.

How long does it take the commuter to complete preparation for leaving work/college?

Figure F 12 presents the cumulative distribution; in all cases, the activity is completed within 75 minutes. Eighty five percent (85%) can leave within 30 minutes.

How long would it take the commuter to travel home? Figure F 13 presents the work/college to home travel time for the EPZ. About 86 percent of commuters can arrive home Palisades Power Plant F4 KLD Engineering, P.C.

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within 30 minutes of leaving work/college; all within 60 minutes.

How long would it take the family to pack clothing, secure the house, and load the car?

Figure F 14 presents the time required to prepare for leaving on an evacuation trip. In many ways this activity mimics a familys preparation for a short holiday or weekend away from home. Hence, the responses represent the experience of the responder in performing similar activities.

The distribution shown in Figure F 14 has a long tail. About 83% of households can be ready to leave home within 90 minutes; the remaining households require up to an additional one hour and 45 minutes.

How long would it take you to clear 6 to 8 inches of snow from your driveway? During adverse, snowy weather conditions, an additional activity may be performed before residents can depart on the evacuation trip. Although snow scenarios assume that the roads and highways have been plowed and are passable (albeit at lower speeds and capacities), it may be necessary to clear a private driveway prior to leaving the home so that the vehicle can access the street.

Figure F 15 presents the time distribution for removing 6 to 8 inches of snow from a driveway.

Approximately 80% of driveways are passable within 60 minutes; the remaining households would require up to an additional two hours to begin their evacuation trip. Note that those respondents (approximately 23%) who answered that they would not take time to clear their driveway were assumed to be ready immediately at the start of this activity. Essentially, they would drive through the snow on the driveway to access the roadway and begin their evacuation trip.

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Table F 1. Palisades Demographic Survey Sampling Plan Population Households Desired Obtained Zip Code within EPZ within EPZ Number of Samples (2010) (2010) Samples 49013 3,352 1,205 37 10 49022 181 70 2 2 49038 7,935 3,239 99 8 49043 2,462 854 26 10 49056 306 106 3 2 49057 977 377 12 5 49064 40 18 1 2 49090 12,760 5,265 161 90 49098 2,992 1,235 38 4 Total EPZ 31,005 12,369 379 133 1

Average HH Size : 2.51 1

It is an estimate for sampling purposes and was not used in the ETE study Palisades Power Plant 6 KLD Engineering, P.C.

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PPP Household Size 50%

42.9%

40%

Percent of Households 30%

24.1%

20%

12.8%

9.8%

10%

5.3% 5.3%

0%

1 2 3 4 5 6+

Household Size Figure F 1. Household Size in the EPZ PPP Vehicle Availability 60%

49.2%

50%

Percent of Households 40%

30%

22.0%

18.9%

20%

10% 7.6%

2.3%

0.0%

0%

0 1 2 3 4 5+

Vehicles Figure F 2. Household Vehicle Availability Palisades Power Plant 7 KLD Engineering, P.C.

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Distribution of Vehicles by HH Size 1 6+ Person Households 1 Person 2 People 3 People 4 People 5 People 6+ People 100%

80%

Percent of Households 60%

40%

20%

0%

1 2 3 4 5+

Vehicles Figure F 3. Vehicle Availability 1 to 6+ Person Households PPP Rideshare with Neighbor/Friend 100%

76.2%

80%

Percent of Households 60%

40%

23.8%

20%

0%

Yes No Figure F 4. Household Ridesharing Preference Palisades Power Plant 8 KLD Engineering, P.C.

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PPP Commuters 50%

40% 37.1%

34.8%

Percent of Households 30%

20%

14.4%

10.6%

10%

3.0%

0%

0 1 2 3 4+

Commuters Figure F 5. Commuters in Households in the EPZ PPP Travel Mode to Work 100%

88.8%

80%

Percent of Commuters 60%

40%

20%

10.2%

0.0% 0.5% 0.5%

0%

Rail Bus Walk/Bike Drive Alone Carpool (2+)

Mode of Travel Figure F 6. Modes of Travel in the EPZ Palisades Power Plant 9 KLD Engineering, P.C.

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PPP Covid 19 Pandemic Impact to Commuters 70%

60% 57.6%

50%

Percent of Households 40%

30%

22.7%

20%

11.4%

10%

4.5% 3.8%

0%

0 1 2 3 4+

Commuters Figure F 7. Commuters Impacted by COVID 19 Functional Vehicle Transportation Needs 7

6 6

5 5

Number of Households 4

3 2

1 0 0 0 0

Bus Medical Bus/Van Wheelchair Ambulance Other Accessible Vehicle Figure F 8. Households with Functional or Transportation Needs Palisades Power Plant 10 KLD Engineering, P.C.

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Evacuating Vehicles Per Household 100%

80%

Percent of Households 56.4%

60%

38.3%

40%

20%

4.5%

0.0% 0.8%

0%

0 1 2 3 4+

Evacuating Vehicles Figure F 9. Number of Vehicles Used for Evacuation Shelter Locations 60%

56.5%

50%

Percent of Households 40%

30%

20.6%

20%

15.3%

10%

4.6%

3.1%

0%

Friend/Relative's Reception Center Hotel, Motel, A Second/Seasonal Other/Don't Know Home or Campground Home Figure F 10. Preferred Shelter Locations Palisades Power Plant 11 KLD Engineering, P.C.

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Pets/Animals Evacuation Response 80%

63.2%

60%

Percent of Households 40%

33.3%

20%

3.4%

0%

Take with me to a Shelter Take with me to Somewhere Leave Pet at Home Else Figure F 11. Households Evacuating with Pets Time to Prepare to Leave Work/College 100%

80%

Percent of Commuters 60%

40%

20%

0%

0 15 30 45 60 75 Preparation Time (min)

Figure F 12. Time Required to Prepare to Leave Work/College Palisades Power Plant 12 KLD Engineering, P.C.

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Time to Commute Home From Work/College 100%

80%

Percent of Commuters 60%

40%

20%

0%

0 15 30 45 60 Travel Time (min)

Figure F 13. Work to Home Travel Time Time to Prepare to Leave Home 100%

80%

Percent of Households 60%

40%

20%

0%

0 30 60 90 120 150 180 210 Preparation Time (min)

Figure F 14. Time to Prepare Home for Evacuation Palisades Power Plant 13 KLD Engineering, P.C.

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Time to Remove Snow from Driveway 100%

80%

Percent of Households 60%

40%

20%

0%

0 30 60 90 120 150 180 Time (min)

Figure F 15. Time to Clear Driveway of 6" 8" of Snow Palisades Power Plant 14 KLD Engineering, P.C.

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ATTACHMENT A Demographic Survey Instrument Palisades Power Plant 15 KLD Engineering, P.C.

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APPENDIX G Traffic Management Plan

G. TRAFFIC MANAGEMENT PLAN NUREG/CR 7002, Rev. 1 indicates that the existing Traffic Management Plans (TMP) consisting of Traffic Control Points (TCPs) and Access Control Points (ACPs) identified by the offsite agencies should be used in the evacuation simulation modeling. The TMP for the EPZ were provided in the emergency plans from each of the counties within the EPZ.

These plans were reviewed and only ACPs were identified. These ACPs were modeled accordingly. An analysis of the ACP locations was performed, and it was determined to model the ETE simulations with the existing ACPs that were provided in the approved county emergency plans, with no additional ACPs recommended.

G.1 Manual Traffic Control The ACPs are forms of Manual Traffic Control (MTC). As discussed in Section 9, MTC at intersections (which are controlled) are modeled as actuated signals. If an intersection has a pre timed signal, stop, or yield control, and the intersection is identified as an ACP, the control type was changed to an actuated signal in the DYNEV II system, in accordance with Section 3.3 of NUREG/CR 7002, Rev. 1. MTCs at existing actuated traffic signalized intersections were essentially left alone.

Table K 1 provides the number of nodes with each control type. If the existing control was changed due to the point being an ACP, the control type is indicated as ACP in Table K 1. The ACPs within the emergency plans are mapped as in Figure G 1. These ACPs are concentrated on roadways giving access to the EPZ and to individual PAAs within the EPZ. These ACPs would be manned during evacuation by traffic guides who would direct evacuees in the proper direction away from the PPP and facilitate the flow of traffic through the intersections. No additional locations for MTC are suggested in this study.

It is assumed that the ACPs will be established within 120 minutes of the ATE to discourage through travelers from using major through routes which traverse the study area. As discussed in Section 3.10, external traffic was considered on Interstate (I) 194 and I 94 in this analysis.

G.2 Analysis of Key ACP Locations As discussed in Section 5.2 of NUREG/CR 7002, Rev. 1, MTC at intersections could benefit from the ETE analysis. The MTC locations identified in the TMPs were analyzed to determine key locations where MTC would be most useful and could be readily implemented. As previously mentioned, signalized intersections that were actuated based on field data collection were essentially left as actuated traffic signals in the model, with modifications to green time allocation as needed. Other controlled intersections (pre timed signals, stop signs and yield signs) were changed to actuated traffic signals to represent the MTC that would be implemented according to the TMPs.

The majority of the ACPs identified in the TMPs were located at intersections with stop control.

Table G 1 shows a list of the controlled intersections that were identified as MTC points in the Palisades Power Plant G1 KLD Engineering, P.C.

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TMPs that were not previously actuated signals, including the type of control that currently exists at each location. To determine the impact of MTC at these locations, a summer, weekend, midday, with good weather scenario (Scenario 3) evacuation of the 2 Mile Region, 5 Mile Region, and the Entire EPZ (Region R01, R02, and R03) were simulated wherein these intersections were left as is (without MTC). The results were compared to the results presented in Section 7 for Scenario 3 and Regions R01, R02, and R03. The ETE were not impacted when compared to the cases wherein these controlled intersections were modeled as actuated signals (with MTC) as presented in Table G 2. Although localized congestion may worsen, there is no impact to the 90th and 100th percentile ETE when MTC was not present at these intersections. The remaining ACPs at controlled intersections were left as actuated signals in the model and, therefore, had no impact to ETE.

As shown in Figure 7 3 through Figure 7 6, several population centers in the study area experience moderate to heavy traffic congestion. The congestion in the EPZ lasted for nearly two and half hours after the ATE. During this time, the major bottlenecks including the ramps to I 196 near South Haven and MI 140 southbound at the intersection with Red Arrow Hwy exhibit persistent congestion. These bottlenecks which are causing delays and prolonging ETE are at intersections with actuated traffic signals or at ramps to freeways wherein MTC will have no impact. As a result, the ACPs within the EPZ do not impact the 90th percentile ETE. In addition, congestion within the EPZ clears prior to the completion of mobilization time, indicating that 100th percentile ETE is dictated by mobilization time. Thus, MTC has no impact on the 100th percentile ETE.

Although there is no reduction in ETE when MTC is implemented, traffic and access control can be beneficial in the reduction of localized congestion and driver confusion and can be extremely helpful for fixed point surveillance and the prevention of vehicles from entering various PAAs (as a majority of the ACPs are located at the PAA boundaries), amongst other things. Should there be a shortfall of personnel to staff the ACPs, the list of locations provided in Table G 1 could be considered as priority locations when implementing the TMP.

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Table G 1. List of Key Manual Traffic Control Locations Node Number Type of Control ACP Number (See Appendix K) (Prior to being an ACP)

V 10 211 Stop Control V 15h 166 Stop Control V 17 168 Yield Control/Traffic Circle V 48 484 Stop Control V 60g 183 Stop Control V 60k 264 Stop Control V 63 390 Stop Control A 38 462 Stop Control Table G 2. ETE with No MTC Scenario 3 th Region 90 Percentile ETE 100th Percentile ETE Base No MTC Difference Base No MTC Difference R01 (2 Mile Region) 2:05 2:05 0:00 4:50 4:50 0:00 R02 (5 Mile Region) 2:10 2:10 0:00 4:55 4:55 0:00 R03 (Full EPZ) 2:20 2:20 0:00 5:00 5:00 0:00 Palisades Power Plant G3 KLD Engineering, P.C.

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Figure G 1. Access Control Points for PPP Palisades Power Plant G4 KLD Engineering, P.C.

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APPENDIX H Evacuation Regions

H EVACUATION REGIONS This appendix presents the evacuation percentages for each Evacuation Region (Table H 1) and maps of all Evacuation Regions (Figure H 1 through Figure H 13). The percentages presented in Table H 1 are based on the methodology discussed in assumption 7 of Section 2.2 and shown in Figure 2 1.

Note the baseline ETE study assumes 20 percent of households will not comply with the shelter advisory, as per Section 2.5.2 of NUREG/CR 7002, Rev. 1.

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Table H 1. Percent of PAA Population Evacuating for Each Region Radial Regions PAA Region Description 1 2 3 4 5 6 7 R01 2 Mile Region 100% 20% 20% 20% 20% 100% 20%

R02 5 Mile Region 100% 100% 100% 20% 20% 100% 20%

R03 Full EPZ 100% 100% 100% 100% 100% 100% 100%

Evacuate 2 Mile Region and Downwind to 5 Miles Wind Direction PAA Region From (Degrees) 1 2 3 4 5 6 7 N/A 56 and <169 Refer to R01 R04 169 and <236 100% 100% 20% 20% 20% 100% 20%

N/A 236 and <303 Refer to R02 R05 303 and <56 100% 20% 100% 20% 20% 100% 20%

Evacuate 2 Mile Region and Downwind to the EPZ Boundary Wind Direction PAA Region From (Degrees) 1 2 3 4 5 6 7 R06 56 and <169 100% 20% 20% 20% 20% 100% 100%

R07 169 and <236 100% 100% 20% 100% 20% 100% 100%

R08 236 and <303 100% 100% 100% 100% 100% 100% 20%

R09 303 and <348 100% 20% 100% 20% 100% 100% 20%

R10 348 and <56 100% 20% 100% 20% 100% 100% 100%

Staged Evacuation 2 Mile Region Evacuates, then Evacuate Downwind to 5 Miles Wind Direction PAA Region From (Degrees) 1 2 3 4 5 6 7 R11 5 Mile Region 100% 100% 100% 20% 20% 100% 20%

N/A 56 and <169 Refer to R01 R12 169 and <236 100% 100% 20% 20% 20% 100% 20%

N/A 236 and <303 Refer to R11 R13 303 and <56 100% 20% 100% 20% 20% 100% 20%

PAA(s) Shelter in Place until PAA(s) Evacuate PAA(s) Shelter in Place 90% ETE for R01, then Evacuate Palisades Power Plant H2 KLD Engineering, P.C.

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Figure H 1. Region R01 Palisades Power Plant H3 KLD Engineering, P.C.

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Figure H 2. Region R02 Palisades Power Plant H4 KLD Engineering, P.C.

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Figure H 3. Region R03 Palisades Power Plant H5 KLD Engineering, P.C.

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Figure H 4. Region R04 Palisades Power Plant H6 KLD Engineering, P.C.

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Figure H 5. Region R05 Palisades Power Plant H7 KLD Engineering, P.C.

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Figure H 6. Region R06 Palisades Power Plant H8 KLD Engineering, P.C.

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Figure H 7. Region R07 Palisades Power Plant H9 KLD Engineering, P.C.

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Figure H 8. Region R08 Palisades Power Plant H 10 KLD Engineering, P.C.

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Figure H 9. Region R09 Palisades Power Plant H 11 KLD Engineering, P.C.

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Figure H 10. Region R10 Palisades Power Plant H 12 KLD Engineering, P.C.

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Figure H 11. Region R11 Palisades Power Plant H 13 KLD Engineering, P.C.

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Figure H 12. Region R12 Palisades Power Plant H 14 KLD Engineering, P.C.

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Figure H 13. Region R13 Palisades Power Plant H 15 KLD Engineering, P.C.

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APPENDIX J Representative Inputs to and Outputs from the DYNEV II System

J. REPRESENTATIVE INPUTS TO AND OUTPUTS FROM THE DYNEV II SYSTEM This appendix presents data input to and output from the DYNEV II System.

Table J 1 provides source (vehicle loading) and destination information for several roadway segments (links) in the analysis network. In total, there are a total of 342 source links (origins) in the model. The source links are shown as centroid points in Figure J 1. On average, evacuees travel a straight line distance of 6.72 miles to exit the study area.

Table J 2 provides network-wide statistics (average travel time, average delay, average speed and number of vehicles) for an evacuation of the entire EPZ (Region R03) for each scenario. As expected, rain and snow scenarios (Scenarios 2, 4, 7, 8, 10 and 11) exhibit slower average speeds, higher delays and longer average travel times than the corresponding good weather scenarios. When comparing scenario 13 (special event) and scenario 5, evacuees during the special event experience slower average speeds, longer delays and increased travel times as a result of the approximately the 10,000 additional evacuating vehicles attending the special event in South Haven. When comparing scenario 14 (roadway closure) and scenario 1, the lane closure on I 196 northbound reduces the average speed, causes longer delays and increases travel time.

Table J 3 provides statistics (average speed and travel time) for the major evacuation routes -

Interstate 94, Blue Star Hwy, MI 43 Eastbound, and Interstate 196 - for an evacuation of the entire EPZ (Region R03) under Scenario 1 (summer, midweek, midday with good weather) conditions. These major evacuation routes do not experience significant traffic congestion except on their access ramps and in the small sections of roadway in population centers. There is evidence of some of this localized congestion in the speed and travel time trends along MI 43 Eastbound and Blue Star Hwy Northbound, while the remaining routes do not experience localized congestion and maintain relatively constant speeds throughout the evacuation.

Table J 4 provides the number of vehicles discharged and the cumulative percent of total vehicles discharged for each link exiting the analysis network, for an evacuation of the entire EPZ (Region R03) under Scenario 1 conditions.

Figure J 2 through Figure J 15 plot the trip generation time versus the ETE for each of the 14 Scenarios considered. The distance between the trip generation and ETE curves is the travel time. Plots of trip generation versus ETE are indicative of the level of traffic congestion during evacuation. For low population density sites, the curves are close together, indicating short travel times and minimal traffic congestion. For higher population density sites, the curves are farther apart indicating longer travel times and the presence of traffic congestion. As seen in Figure J 2 through Figure J 15, the curves are spatially separated as a result of the traffic congestion in the EPZ, which was discussed in detail in Section 7.3. As expected, the special event (Scenario 13) experiences the longest travel times (up to 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> and 30 minutes) due to the delays caused by the additional 10,000 vehicles evacuating from South Haven.

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Table J 1. Sample Simulation Model Input Vehicles Entering Upstream Downstream Network Directional Destination Destination Route Name Node Node on this Link Preference Nodes Capacity 8320 2,850 Blue Star Hwy 96 322 2 S 8540 1,275 8089 6,750 8320 2,850 Blue Star Hwy 298 321 81 S 8540 1,275 8089 6,750 8200 1,275 Co Rd 388 192 193 97 NE 8554 1,275 8635 1,275 8060 4,500 Meijer Dr 567 566 239 NE 8554 1,275 8635 1,275 8320 2,850 Co Rd 372 233 383 463 S 8540 1,275 8089 6,750 8540 1,275 Coloma Rd 375 376 81 S 8089 6,750 8634 1,275 62nd St 523 524 47 E 8082 4,500 8557 1,275 8554 1,275 109th Ave 228 461 14 NE 8635 1,275 SR 63 316 317 49 SW 8320 2,850 8554 1,275 Co Rd 215 446 455 0 NE 8635 1,275 Palisades Power Plant J2 KLD Engineering, P.C.

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Table J 2. Selected Model Outputs for the Evacuation of the Entire EPZ (Region R03)

Scenario 1 2 3 4 5 6 7 Network Wide Average 1.1 1.2 1.2 1.5 1.4 1.0 1.2 Travel Time (Min/Veh Mi)

Network Wide Average 0.0 0.0 0.0 0.3 0.2 0.0 0.0 Delay Time (Min/Veh Mi)

Network Wide Average 57.1 50.3 48.3 41.4 44.3 58.7 52.1 Speed (mph)

Total Vehicles 35,116 35,240 36,818 36,948 30,346 31,485 31,590 Exiting Network Scenario 8 9 10 11 12 13 14 Network Wide Average 1.3 1.1 1.2 1.3 1.2 2.2 1.4 Travel Time (Min/Veh Mi)

Network Wide Average 0.1 0.0 0.0 0.1 0.0 1.0 0.2 Delay Time (Min/Veh Mi)

Network Wide Average 46.5 55.9 49.3 45.6 51.8 27.0 44.1 Speed (mph)

Total Vehicles 31,600 31,594 31,731 31,743 26,757 40,788 35,120 Exiting Network Table J 3. Average Speed (mph) and Travel Time (min) for Major Evacuation Routes (Region R03, Scenario 1)

Elapsed Time (hours) 1:00 2:00 3:00 4:00 4:55 Travel Length Speed Time Travel Travel Travel Travel Route Name (miles) (mph) (min) Speed Time Speed Time Speed Time Speed Time I 94 Eastbound 22.4 69.8 19.2 66.2 20.3 73.7 18.2 71.3 18.8 73.7 18.2 I 94 Westbound 22.4 72.7 18.5 72.8 18.4 73.6 18.2 72.6 18.5 73.7 18.2 Blue Star Hwy 15.4 57.1 16.2 57.4 16.1 57.6 16.0 57.3 16.1 57.6 16.0 Southbound Blue Star Hwy 17.7 50.1 21.1 51.1 20.7 51.4 20.6 52.2 20.3 53.1 20.0 Northbound MI 43 Eastbound 17.6 47.6 22.2 47.2 22.3 47.9 22.0 46.9 22.5 49.0 21.5 I 196 Northbound 34.8 71.0 29.4 72.6 28.8 72.7 28.7 72.1 29.0 68.9 30.3 I 196 Southbound 34.7 71.9 28.9 71.9 29.0 72.5 28.7 72.0 28.9 72.5 28.7 Palisades Power Plant J3 KLD Engineering, P.C.

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Table J 4. Simulation Model Outputs at Network Exit Links for Region R03, Scenario 1 Elapsed Time (hours)

Upstream Downstream 1 2 3 4 5 Route Name Node Node Cumulative Vehicles Discharged by the Indicated Time Cumulative Percent of Vehicles Discharged by the Indicated Time Interval 1,977 5,356 6,424 6,856 6,918 I 196 NB 59 60 21.7% 21.0% 19.6% 19.7% 19.7%

1,997 6,314 8,067 8,229 8,270 I 94 EB 80 81 22.0% 24.7% 24.6% 23.7% 23.6%

2,987 6,153 7,937 8,318 8,387 I 94 WB 88 89 32.8% 24.1% 24.2% 23.9% 23.9%

217 1,008 1,372 1,494 1,522 MI 43 EB 190 191 2.4% 3.9% 4.2% 4.3% 4.3%

183 735 991 1,083 1,099 109th Ave EB 229 554 2.0% 2.9% 3.0% 3.1% 3.1%

110 475 645 708 718 56th St NB 229 635 1.2% 1.9% 2.0% 2.0% 2.0%

163 631 830 909 926 MI 63 SB 319 320 1.8% 2.5% 2.5% 2.6% 2.6%

242 859 1,132 1,216 1,236 W Main St WB 540 558 2.7% 3.4% 3.5% 3.5% 3.5%

405 1,067 1,308 1,408 1,425 Blue Star Hwy NB 552 553 4.5% 4.2% 4.0% 4.1% 4.1%

81 578 808 874 884 Red Arrow Hwy EB 556 557 0.9% 2.3% 2.5% 2.5% 2.5%

523 1,222 1,699 1,901 1,952 MI 140 SB 624 226 5.7% 4.8% 5.2% 5.5% 5.6%

81 363 503 558 570 Co Rd 388 EB 625 200 0.9% 1.4% 1.5% 1.6% 1.6%

93 400 562 622 634 US 31 SB 628 629 1.0% 1.6% 1.7% 1.8% 1.8%

43 394 527 569 576 MI 51 SB 633 634 0.5% 1.5% 1.6% 1.6% 1.6%

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Figure J 1. Network Sources/Origins Palisades Power Plant J5 KLD Engineering, P.C.

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ETE and Trip Generation Summer, Midweek, Midday, Good (Scenario 1)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 2. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather (Scenario 1)

ETE and Trip Generation Summer, Midweek, Midday, Rain (Scenario 2)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 3. ETE and Trip Generation: Summer, Midweek, Midday, Rain (Scenario 2)

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ETE and Trip Generation Summer, Weekend, Midday, Good (Scenario 3)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 4. ETE and Trip Generation: Summer, Weekend, Midday, Good Weather (Scenario 3)

ETE and Trip Generation Summer, Weekend, Midday, Rain (Scenario 4)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 5. ETE and Trip Generation: Summer, Weekend, Midday, Rain (Scenario 4)

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ETE and Trip Generation Summer, Midweek, Weekend, Evening, Good (Scenario 5)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 6. ETE and Trip Generation: Summer, Midweek, Weekend, Evening, Good Weather (Scenario 5)

ETE and Trip Generation Winter, Midweek, Midday, Good (Scenario 6)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 7. ETE and Trip Generation: Winter, Midweek, Midday, Good Weather (Scenario 6)

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ETE and Trip Generation Winter, Midweek, Midday, Rain (Scenario 7)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 8. ETE and Trip Generation: Winter, Midweek, Midday, Rain (Scenario 7)

ETE and Trip Generation Winter, Midweek, Midday, Snow (Scenario 8)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 6:30 Elapsed Time (h:mm)

Figure J 9. ETE and Trip Generation: Winter, Midweek, Midday, Snow (Scenario 8)

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ETE and Trip Generation Winter, Weekend, Midday, Good (Scenario 9)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 10. ETE and Trip Generation: Winter, Weekend, Midday, Good Weather (Scenario 9)

ETE and Trip Generation Winter, Weekend, Midday, Rain (Scenario 10)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 11. ETE and Trip Generation: Winter, Weekend, Midday, Rain (Scenario 10)

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ETE and Trip Generation Winter, Weekend, Midday, Snow (Scenario 11)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 6:00 6:30 Elapsed Time (h:mm)

Figure J 12. ETE and Trip Generation: Winter, Weekend, Midday, Snow (Scenario 11)

ETE and Trip Generation Winter, Midweek, Weekend, Evening, Good (Scenario 12)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 13. ETE and Trip Generation: Winter, Midweek, Weekend, Evening, Good Weather (Scenario 12)

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ETE and Trip Generation Summer, Weekend, Evening, Good, Special Event (Scenario 13)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 14. ETE and Trip Generation: Summer, Weekend, Evening, Good Weather, Special Event (Scenario 13)

ETE and Trip Generation Summer, Midweek, Midday, Good, Roadway Impact (Scenario 14)

Trip Generation ETE 100%

Percent of Total Vehicles 80%

60%

40%

20%

0%

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 5:30 Elapsed Time (h:mm)

Figure J 15. ETE and Trip Generation: Summer, Midweek, Midday, Good Weather, Roadway Impact (Scenario 14)

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APPENDIX K Evacuation Roadway Network

K. EVACUATION ROADWAY NETWORK As discussed in Section 1.3, a link node analysis network was constructed to model the roadway network within the study area. Figure K 1 provides an overview of the link node analysis network. The figure has been divided up into 30 more detailed figures (Figure K 2 through Figure K 31) which show each of the links and nodes in the network.

The analysis network was calibrated using observations made during the field survey conducted in March 2021.

Table K 1 summarizes the number of nodes by the type of control (stop sign, yield sign, pre timed signal, actuated signal, access control point [ACP], uncontrolled).

Table K 1. Summary of Nodes by the Type of Control Number of Control Type Nodes Uncontrolled 476 Pretimed 4 Actuated 8 Stop 96 ACP 40 Yield 6 Total: 630 Palisades Power Plant K1 KLD Engineering, P.C.

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Figure K 1. PPP Link Node Analysis Network Palisades Power Plant K2 KLD Engineering, P.C.

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Figure K 2. Link Node Analysis Network - Grid 1 Palisades Power Plant K3 KLD Engineering, P.C.

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Figure K 3. Link Node Analysis Network - Grid 2 Palisades Power Plant K4 KLD Engineering, P.C.

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Figure K 4. Link Node Analysis Network - Grid 3 Palisades Power Plant K5 KLD Engineering, P.C.

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Figure K 5. Link Node Analysis Network - Grid 4 Palisades Power Plant K6 KLD Engineering, P.C.

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Figure K 6. Link Node Analysis Network - Grid 5 Palisades Power Plant K7 KLD Engineering, P.C.

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Figure K 7. Link Node Analysis Network - Grid 6 Palisades Power Plant K8 KLD Engineering, P.C.

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Figure K 8. Link Node Analysis Network - Grid 7 Palisades Power Plant K9 KLD Engineering, P.C.

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Figure K 9. Link Node Analysis Network - Grid 8 Palisades Power Plant K 10 KLD Engineering, P.C.

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Figure K 10. Link Node Analysis Network - Grid 9 Palisades Power Plant K 11 KLD Engineering, P.C.

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Figure K 11. Link Node Analysis Network - Grid 10 Palisades Power Plant K 12 KLD Engineering, P.C.

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Figure K 12. Link Node Analysis Network - Grid 11 Palisades Power Plant K 13 KLD Engineering, P.C.

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Figure K 13. Link Node Analysis Network - Grid 12 Palisades Power Plant K 14 KLD Engineering, P.C.

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Figure K 14. Link Node Analysis Network - Grid 13 Palisades Power Plant K 15 KLD Engineering, P.C.

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Figure K 15. Link Node Analysis Network - Grid 14 Palisades Power Plant K 16 KLD Engineering, P.C.

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Figure K 16. Link Node Analysis Network - Grid 15 Palisades Power Plant K 17 KLD Engineering, P.C.

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Figure K 17. Link Node Analysis Network - Grid 16 Palisades Power Plant K 18 KLD Engineering, P.C.

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Figure K 18. Link Node Analysis Network - Grid 17 Palisades Power Plant K 19 KLD Engineering, P.C.

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Figure K 19. Link Node Analysis Network - Grid 18 Palisades Power Plant K 20 KLD Engineering, P.C.

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Figure K 20. Link Node Analysis Network - Grid 19 Palisades Power Plant K 21 KLD Engineering, P.C.

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Figure K 21. Link Node Analysis Network - Grid 20 Palisades Power Plant K 22 KLD Engineering, P.C.

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Figure K 22. Link Node Analysis Network - Grid 21 Palisades Power Plant K 23 KLD Engineering, P.C.

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Figure K 23. Link Node Analysis Network - Grid 22 Palisades Power Plant K 24 KLD Engineering, P.C.

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Figure K 24. Link Node Analysis Network - Grid 23 Palisades Power Plant K 25 KLD Engineering, P.C.

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Figure K 25. Link Node Analysis Network - Grid 24 Palisades Power Plant K 26 KLD Engineering, P.C.

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Figure K 26. Link Node Analysis Network - Grid 25 Palisades Power Plant K 27 KLD Engineering, P.C.

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Figure K 27. Link Node Analysis Network - Grid 26 Palisades Power Plant K 28 KLD Engineering, P.C.

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Figure K 28. Link Node Analysis Network - Grid 27 Palisades Power Plant K 29 KLD Engineering, P.C.

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Figure K 29. Link Node Analysis Network - Grid 28 Palisades Power Plant K 30 KLD Engineering, P.C.

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Figure K 30. Link Node Analysis Network - Grid 29 Palisades Power Plant K 31 KLD Engineering, P.C.

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Figure K 31. Link Node Analysis Network - Grid 30 Palisades Power Plant K 32 KLD Engineering, P.C.

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APPENDIX L PAA Boundaries

L. PAA BOUNDARIES PAA 1 County: Van Buren Defined as the area within the following boundary: Includes Van Buren state park and western parts of Covert bounded by M 140 to the east; 16th Ave to the north; Lake Michigan to the west; and 34th Ave to the south.

PAA 2 County: Van Buren Defined as the area within the following boundary: South Haven Township bounded by Elkenburg St., Kalamazoo St. and Aylworth Ave to the north; 69th St. and SR 43 to the east; 16th Ave, M 140 and 24th Ave to the south; and Lake Michigan to the west.

PAA 3 County: Van Buren Defined as the area within the following boundary: Eastern Covert bounded by Lake Michigan, M 140 and 34th Ave to the west, 24th Ave to the north, 69th St and 70th St the east, and the Berrien / Van Buren County line to the south.

PAA 4 County: Allegan and Van Buren Defined as the area within the following boundary: The City of South Haven bounded by Elkenburg St., Kalamazoo St., Aylworth Ave, SR 43, 69th St. and Lake Michigan to the west; 24th Ave to the south; CR 681, the Van Buren /

Allegan County line, 63rd St., 102nd Ave and 66th St. to the east; and 107th Ave to the north. Includes all of South Haven and West Bangor.

PAA 5 County: Berrien and Van Buren Defined as the area within the following boundary: Parts of Coloma, Watervliet and Bangor bounded by the Berrien / Van Buren County Line, M 140 and 24th Ave to the north; CR 681, 48th Ave and CR 687 to the east; Red Arrow Hwy / Coloma Rd to the south; and Lake Michigan to the west. Excludes Hartford.

PAA6 Lake Area 6 Area 6 is the portion of Lake Michigan within a 5 mile radius of the PPP.

PAA7 Lake Area 7 Area 7 is the portion of Lake Michigan between 5 and 10 miles from the PPP.

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APPENDIX M Evacuation Sensitivity Studies

M. EVACUATION SENSITIVITY STUDIES This appendix presents the results of a series of sensitivity analyses. These analyses are designed to identify the sensitivity of the ETE to changes in some base evacuation conditions.

M.1 Effect of Changes in Trip Generation Times A sensitivity study was performed to determine whether changes in the estimated trip generation time have an effect on the ETE for the entire EPZ. Specifically, if the tail of the mobilization distribution were truncated (i.e., if those who responded most slowly to the ATE could be persuaded to respond much more rapidly) or if the tail were elongated (i.e., spreading out the departure of evacuees to limit the demand during peak times), how would the ETE be affected?

The case considered was Scenario 3, Region 3; a summer, weekend, midday, with good weather evacuation of the entire EPZ. Table M 1 presents the results of this study.

If evacuees mobilize one hour quicker, the 90th percentile ETE is reduced by 15 minutes and the 100th percentile ETE is reduced by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> (a significant change), respectively. If evacuees mobilize one hour slower, the 90th percentile and 100th percentile ETE are increased by 40 minutes and 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br />, respectively - both significant changes.

As discussed in Section 7.3, traffic congestion persists within the EPZ for about 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> and 30 minutes after the ATE, well before the completion of trip generation time at 4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br /> and 45 minutes. As such, the 100th percentile ETE directly parallel mobilization time. The 90th percentile are impacted by traffic congestion as evidenced by the ETE only dropping by 15 minutes when evacuees mobilize 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> faster. See Table M 1.

M.2 Effect of Changes in the Number of People in the Shadow Region Who Relocate A sensitivity study was conducted to determine the effect on ETE of changes in the percentage of people who decide to relocate from the Shadow Region. The case considered was Scenario 3, Region 3; a summer, weekend, midday, with good weather evacuation of the entire EPZ. The movement of people in the Shadow Region has the potential to impede vehicles evacuating from an Evacuation Region within the EPZ. Refer to Section 3.2 and Section 7.1 for additional information on population within the Shadow Region.

Table M 2 presents the ETE for each of the cases considered. The results show that eliminating (0%),

doubling (40%), tripling (60%), and quadrupling (80%) the shadow evacuation has no effect on the 90th and 100th percentile ETE. A full shadow evacuation (100%) increases the 90th percentile ETE by 5 minutes and has no effect on the 100th percentile ETE.

Note the demographic survey results presented in Appendix F indicate that 28% of households would elect to evacuate if advised to shelter, which is significantly higher than the base assumption of 20% non compliance suggested in the NUREG/CR 7002, Rev. 1. A sensitivity study was run using 28% shadow evacuation and the 90th and 100th percentile ETE were not impacted.

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The Shadow Region for PPP is sparsely populated except for two population centers Hartford and Watervliet (half of which is in the EPZ). These towns are too small to cause a significant disruption to the evacuation of the EPZ. As shown in Figure 7 3 through Figure 7 6, the congestion within Hartford does not propagate into the EPZ such that EPZ evacuees would be delayed.

Congestion near Watervliet does propagate into the EPZ for about two hours; however, most of this congestion is caused by Paw Paw Lake and the northern half of Watervliet - both of which are in the EPZ.

M.3 Effect of Changes in the Permanent Resident Population A sensitivity study was conducted to determine the effect on ETE of changes in the permanent resident population within the study area (EPZ plus Shadow Region). As population in the study area changes over time, the time required to evacuate the public may increase, decrease, or remain the same. Since the ETE is related to the demand to capacity ratio present within the study area, changes in population will cause the demand side of the equation to change and could impact ETE if there is not a corresponding increase in capacity (i.e., roadway improvements).

As per the NRCs response to the Emergency Planning Frequently Asked Question (EPFAQ) 2013 001, the ETE population sensitivity study must be conducted to determine what percentage increase in permanent resident population causes an increase in the 90th percentile ETE of 25%

or 30 minutes, whichever is less. The sensitivity study must use the scenario with the longest 90th percentile ETE (excluding the roadway impact scenario and the special event scenario if it is a one day per year special event).

Thus, the sensitivity study was conducted using the following planning assumptions:

1. The percent change in population within the study area was increased by up to 107%.

Changes in population were applied to permanent residents only (as per federal guidance), in both the EPZ and the Shadow Region.

2. The transportation infrastructure (as presented in Appendix K) remained fixed; the presence of future proposed roadway changes and/or highway capacity improvements were not considered.

3. The study was performed for the 2 Mile Region (R01), 5 Mile Region (R02) and the Entire EPZ (R03).

4. The scenario (excluding roadway impact and special event) which yielded the longest 90th percentile ETE values was selected as the case to be considered in this sensitivity study (Scenario 8 - Winter, Midweek, Midday with Heavy Snow).

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Table M 3 presents the results of the sensitivity study.Section IV of Appendix E to 10 CFR Part 50, and NUREG/CR 7002, Rev. 1, Section 5.4, require licensees to provide an updated ETE analysis to the NRC when a population increase within the EPZ causes the longest 90th percentile ETE values (for the 2 Mile Region, 5 Mile Region, or entire EPZ) to increase by 25% or 30 minutes, whichever is less. The base ETE values for the 2 Mile Region (R02), 5 Mile Region (R02) and for the Entire EPZ (R03) are greater than 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />; 25% of these base ETE is always greater than 30 minutes. Thus, the criterion for updating is 30 minutes.

The percent population change which results in the longest 90th percentile ETE change greater than or equal to 30 minutes is highlighted in red in Table M 3 - a 107% or greater increase in the 2 Mile Region permanent resident population. Entergy/Holtec will have to estimate the EPZ population on an annual basis. If the 2 Mile Region population increases by 107% or more, an updated ETE analysis will be needed.

M.4 Effect of Changes in Average Household Size As discussed in Appendix F, the average household size obtained from the results of the demographic survey is 2.77 persons per household. The 2020 Census indicates an average household size of 2.41 persons per household. The difference between the Census data and survey data is 14.9%, which exceeds the survey sampling error of 8.5%. Upon discussions with Entergy/Holtec, it was decided that the estimated household size (2.77 persons per household) from the demographic survey results would be used in the ETE study. A sensitivity study was performed to determine how sensitive the ETE is to changes in the average household size. It should be noted that only resident and shadow vehicles were changed for this sensitivity study.

The case considered was Scenario 3 a summer, weekend, midday, with good weather evacuation of the 2 Mile Region (R01), 5 Mile Region (R02), and the Entire EPZ (R03). Table M 4 presents the results of this study.

As discussed in Sections 3.1 and 3.2, the permanent resident evacuating vehicles in the EPZ and in the Shadow Region are determined by dividing the 2020 Census population by the average household size, then multiplying by the average evacuating vehicles per household obtained from the demographic survey. Give that household size is in the denominator of the equation used to compute evacuating vehicles, decreasing the average household size by 14.9% increases the total number of permanent resident evacuating vehicles in the EPZ and in the Shadow Region by 14.9%.

The change in average household size increases the 90th percentile ETE by 15 minutes and 25 minutes for the 5 Mile Region (R02) and Entire EPZ (R03), respectively. These changes are not significant, which is defined in the federal regulations as 25% or 30 minutes, whichever is less. The change in average household size does not impact ETE at the 100th percentile as the traffic congestion in the major population centers within the EPZ clears within about 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> and 30 minutes and trip generation time dictates the ETE. The ETE for the 2 Mile Region (R01) is not impacted by the change in average household size.

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M.5 Enhancements in Evacuation Time This appendix documents sensitivity studies on critical variables that could potentially impact ETE.

Possible improvements to ETE are further discussed below:

Reducing trip generation time by an hour reduces the 90th percentile ETE by 15 minutes, and the 100th percentile ETE by 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> (Section M.1). Public outreach encouraging evacuees to mobilize more quickly or in a timely manner can decrease ETE.

Increasing the shadow evacuation percentage has minimal impact on ETE (Section M.2).

Nonetheless, public outreach could be considered to inform those people within the EPZ (and potentially beyond the EPZ) that if they are not advised to evacuate, they should not.

Population growth results in more evacuating vehicles, which could significantly increase ETE (Section M.3). Decreasing the average household size (increasing the total number of evacuating vehicles) increases the 90th percentile ETE by up to 25 minutes (Section M.4).

Public outreach to encourage EPZ residents to carpool and evacuate as a family in a single vehicle could reduce the number of evacuating vehicles and could reduce ETE or offset the impact of population growth.

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Table M 1. Evacuation Time Estimates for Trip Generation Sensitivity Study Trip Generation Evacuation Time Estimate for Entire EPZ Period th 90 Percentile 100th Percentile 3 Hours and 45 Minutes 2:05 3:55 4 Hours and 45 Minutes (Base) 2:20 4:55 5 Hours and 45 Minutes 3:00 5:55 Table M 2. Evacuation Time Estimates for Shadow Sensitivity Study Percent Shadow Evacuating Shadow Evacuation Time Estimate for Entire EPZ Evacuation Vehicles1 90th Percentile 100th Percentile 0 0 2:20 4:55 20 (Base) 2,500 2:20 4:55 28 (Survey) 3,500 2:20 4:55 40 5,000 2:20 4:55 60 7,500 2:20 4:55 80 10,000 2:20 4:55 100 12,500 2:25 4:55 1

The Evacuating Shadow Vehicles in Table M-2 represent the residents and employees 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. See Section 6 for further discussion.

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Table M 3. Evacuation Time Estimates for Variation with Population Change EPZ and 20%

Shadow Permanent Base 105% 106% 107%

Resident Population 34,232 70,176 70,518 70,860 ETE (hrs:mins) for the 90th Percentile Population Change Region Base 105% 106% 107%

2 Mile Region (R01) 2:20 2:45 2:45 2:50 5 Mile Region (R02) 3:05 3:25 3:25 3:25 Entire EPZ (R03) 3:30 3:50 3:50 3:50 th ETE (hrs:mins) for the 100 Percentile Population Change Region Base 105% 106% 107%

2 Mile Region (R01) 6:00 6:05 6:05 6:05 5 Mile Region (R02) 6:05 6:05 6:05 6:05 Entire EPZ (R03) 6:10 6:15 6:15 6:15 Table M 4. Evacuation Time Estimates for Change in Average Household Size Base Case Average Sensitivity Case Household Size (2.77 Average Household EPZ and Shadow Evacuating people per Size (2.41 people per Vehicles household) household) 18,398 vehicles 21,146 vehicles ETE (hrs:mins) for the 90th Percentile 2 Mile Region (R01) 2:05 2:05 5 Mile Region (R02) 2:10 2:25 Entire EPZ (R03) 2:20 2:45 th ETE (hrs:mins) for the 100 Percentile 2 Mile Region (R01) 4:45 4:45 5 Mile Region (R02) 4:50 4:50 Entire EPZ (R03) 4:55 4:55 Palisades Power Plant M6 KLD Engineering, P.C.

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APPENDIX N ETE Criteria Checklist

N. ETE CRITERIA CHECKLIST Table N 1. ETE Review Criteria Checklist Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 1.0 Introduction

a. The emergency planning zone (EPZ) and surrounding area is Yes Section 1 described.

b. A map is included that identifies primary features of the site Yes Figures 1 1, 3 1, 6 1 including major roadways, significant topographical features, boundaries of counties, and population centers within the EPZ.

c. A comparison of the current and previous ETE is provided Yes Table 1 3 including information similar to that identified in Table 1 1, ETE Comparison.

1.1 Approach

a. The general approach is described in the report as outlined Yes Section 1.1, Section 1.3, Appendix D, in Section 1.1, Approach. Table 1 1, 1.2 Assumptions

a. Assumptions consistent with Table 1 2, General Yes Section 2 Assumptions, of NUREG/CR 7002 are provided and include the basis to support use.

1.3 Scenario Development

a. The scenarios in Table 1 3, Evacuation Scenarios, are Yes Section 6, Table 6 2 developed for the ETE analysis. A reason is provided for use of other scenarios or for not evaluating specific scenarios.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 1.4 Evacuation Planning Areas

a. A map of the EPZ with emergency response planning areas Yes Figure 3 1, Figure 6 1 (ERPAs) is included.

1.4.1 Keyhole Evacuation

a. A table similar to Table 1 4 Evacuation Areas for a Keyhole Yes Table 6 1, Table 7 5, Table H 1 Evacuation, is provided identifying the ERPAs considered for each ETE calculation by downwind direction.

1.4.2 Staged Evacuation

a. The approach used in development of a staged evacuation is Yes Section 7.2 discussed.

b. A table similar to Table 1 5, Evacuation Areas for a Staged Yes Table 6 1, Table 7 5, Table H 1 Evacuation, is provided for staged evacuations identifying the ERPAs considered for each ETE calculation by downwind direction.

2.0 Demand Estimation

a. Demand estimation is developed for the four population Yes Section 3 groups (permanent residents of the EPZ, transients, special facilities, and schools).

2.1 Permanent Residents and Transient Population

a. The U.S. Census is the source of the population values, or Yes Section 3.1 another credible source is provided.

b. The availability date of the census data is provided. Yes Section 3.1

c. Population values are adjusted as necessary for growth to Yes N/A 2020 used as the base year of the reflect population estimates to the year of the ETE. analysis Palisades Power Plant N2 KLD Engineering, P.C.

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d. A sector diagram, similar to Figure 2 1, Population by Yes Figure 3 2 Sector, is included showing the population distribution for permanent residents.

2.1.1 Permanent Residents with Vehicles

a. The persons per vehicle value is between 1 and 3 or Yes Section 3.1 justification is provided for other values.

2.1.2 Transient Population

a. A list of facilities that attract transient populations is Yes Section 3.3, Table E 4, Table E 5 and included, and peak and average attendance for these Table E 6 facilities is listed. The source of information used to develop attendance values is provided.

b. Major employers are listed. Yes Section 3.4, Table E 3

c. The average population during the season is used, itemized Yes Table 3 4, Table 3 5 and Appendix E and totaled for each scenario. itemize the peak transient population and employee estimates. These estimates are multiplied by the scenario specific percentages provided in Table 6 3 to estimate average transient population by scenario - see Table 6 4.

d. The percentage of permanent residents assumed to be at Yes Section 3.3 and Section 3.4 facilities is estimated.

e. The number of people per vehicle is provided. Numbers may Yes Section 3.3 and Section 3.4 vary by scenario, and if so, reasons for the variation are discussed.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

f. A sector diagram is included, similar to Figure 2 1, Yes Figure 3 6 (transients) and Figure 3 8 Population by Sector, is included showing the population (employees) distribution for the transient population.

2.2 Transit Dependent Permanent Residents

a. The methodology (e.g., surveys, registration programs) used Yes Section 3.9 to determine the number of transit dependent residents is discussed.

b. The State and local evacuation plans for transit dependent Yes Section 8.1 residents are used in the analysis.

c. The methodology used to determine the number of people Yes Section 3.8 with disabilities and those with access and functional needs who may need assistance and do not reside in special facilities is provided. Data from local/county registration programs are used in the estimate.

d. Capacities are provided for all types of transportation Yes Item 3 of Section 2.4 resources. Bus seating capacity of 50 percent is used or justification is provided for higher values.

e. An estimate of the transit dependent population is provided. Yes Section 3.9, Table 3 9, Table 3 11

f. A summary table showing the total number of buses, Yes Table 3 12, Table 8 1 ambulances, or other transport assumed available to support evacuation is provided. The quantification of resources is detailed enough to ensure that double counting has not occurred.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 2.3 Special Facility Residents

a. Special facilities, including the type of facility, location, and Yes Table E 2 lists all medical facilities by average population, are listed. Special facility staff is facility name, location, and average included in the total special facility population. population.

b. The method of obtaining special facility data is discussed. Yes Section 3.5

c. An estimate of the number and capacity of vehicles assumed Yes Table 3 6 available to support the evacuation of the facility is provided.

d. The logistics for mobilizing specially trained staff (e.g., Yes Section 8.1 - under Evacuation of medical support or security support for prisons, jails, and Medical Facilities other correctional facilities) are discussed when appropriate.

There are no Correctional Facilities within the EPZ 2.4 Schools

a. A list of schools including name, location, student Yes Table 3 7, Table E 1, Section 3.6 population, and transportation resources required to support the evacuation, is provided. The source of this information should be identified.

b. Transportation resources for elementary and middle schools Yes Section 3.6 are based on 100 percent of the school capacity.

c. The estimate of high school students who will use personal Yes Section 3.6 vehicle to evacuate is provided and a basis for the values used is given.

d. The need for return trips is identified. Yes Section 8.1 Palisades Power Plant N5 KLD Engineering, P.C.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 2.5 Other Demand Estimate Considerations 2.5.1 Special Events

a. A complete list of special events is provided including Yes Section 3.7 information on the population, estimated duration, and season of the event.

b. The special event that encompasses the peak transient Yes Section 3.7 population is analyzed in the ETE.

c. The percentage of permanent residents attending the event Yes Section 3.7 is estimated.

2.5.2 Shadow Evacuation

a. A shadow evacuation of 20 percent is included consistent Yes Item 7 of Section 2.2, Figure 2 1 and with the approach outlined in Section 2.5.2, Shadow Figure 7 1, Section 3.2 Evacuation.

b. Population estimates for the shadow evacuation in the Yes Section 3.2, Table 3 3, Figure 3 4 shadow region beyond the EPZ are provided by sector.

c. The loading of the shadow evacuation onto the roadway Yes Section 5 - Table 5 9 (footnote) network is consistent with the trip generation time generated for the permanent resident population.

2.5.3 Background and Pass Through Traffic

a. The volume of background traffic and pass through traffic is Yes Section 3.10 and Section 3.11 based on the average daytime traffic. Values may be reduced for nighttime scenarios.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

b. The method of reducing background and pass through traffic Yes Section 2.2 - Assumptions 10 and 11 is described.

Section 2.5 Section 3.10 and Section 3.11 Table 6 3 - External Through Traffic footnote

c. Pass through traffic is assumed to have stopped entering the Yes Section 2.5 EPZ about two (2) hours after the initial notification.

2.6 Summary of Demand Estimation

a. A summary table is provided that identifies the total Yes Table 3 11, Table 3 12, and Table 6 4 populations and total vehicles used in the analysis for permanent residents, transients, transit dependent residents, special facilities, schools, shadow population, and pass through demand in each scenario.

3.0 Roadway Capacity

a. The method(s) used to assess roadway capacity is discussed. Yes Section 4 3.1 Roadway Characteristics

a. The process for gathering roadway characteristic data is Yes Section 1.3, Appendix D described including the types of information gathered and how it is used in the analysis.

b. Legible maps are provided that identify nodes and links of Yes Appendix K the modeled roadway network similar to Figure A 1, Roadway Network Identifying Nodes and Links, and Figure A 2, Grid Map Showing Detailed Nodes and Links.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 3.2 Model Approach

a. The approach used to calculate the roadway capacity for the Yes Section 4 transportation network is described in detail, and the description identifies factors that are expressly used in the modeling.

b. Route assignment follows expected evacuation routes and Yes Appendix B and Appendix C traffic volumes.

c. A basis is provided for static route choices if used to assign N/A Static route choices are not used to evacuation routes. assign evacuation routes. Dynamic traffic assignment is used.

d. Dynamic traffic assignment models are described including Yes Appendix B and Appendix C calibration of the route assignment.

3.3 Intersection Control

a. A list that includes the total numbers of intersections Yes Table K 1 modeled that are unsignalized, signalized, or manned by response personnel is provided.

b. The use of signal cycle timing, including adjustments for Yes Section 4, Appendix G manned traffic control, is discussed.

3.4 Adverse Weather

a. The adverse weather conditions are identified. Yes Assumption 2, 3, 4 and 6 of Section 2.6

b. The speed and capacity reduction factors identified in Table Yes Table 2 2 3 1, Weather Capacity Factors, are used or a basis is provided for other values, as applicable to the model.

c. The calibration and adjustment of driver behavior models for N/A Driver behavior is not adjusted for adverse weather conditions are described, if applicable. adverse weather conditions.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

d. The effect of adverse weather on mobilization is considered Yes Table 2 2 and assumptions for snow removal on streets and driveways are identified, when applicable.

4.0 Development of Evacuation Times 4.1 Traffic Simulation Models

a. General information about the traffic simulation model used Yes Section 1.3, Table 1 3, Appendix B, in the analysis is provided. Appendix C

b. If a traffic simulation model is not used to perform the ETE N/A Not applicable since a traffic simulation calculation, sufficient detail is provided to validate the model was used.

analytical approach used.

4.2 Traffic Simulation Model Input

a. Traffic simulation model assumptions and a representative Yes Section 2, Appendix J set of model inputs are provided.

b. The number of origin nodes and method for distributing Yes Appendix J, Appendix C vehicles among the origin nodes are described.

c. A glossary of terms is provided for the key performance Yes Appendix A measures and parameters used in the analysis.

4.3 Trip Generation Time

a. The process used to develop trip generation times is Yes Section 5 identified.

b. When surveys are used, the scope of the survey, area of the Yes Appendix F survey, number of participants, and statistical relevance are provided.

c. Data used to develop trip generation times are summarized. Yes Appendix F, Section 5 Palisades Power Plant N9 KLD Engineering, P.C.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

d. The trip generation time for each population group is Yes Section 5 developed from site specific information.

e. The methods used to reduce uncertainty when developing Yes Appendix F trip generation times are discussed, if applicable.

4.3.1 Permanent Residents and Transient Population

a. Permanent residents are assumed to evacuate from their Yes Section 5 discusses trip generation for homes but are not assumed to be at home at all times. Trip households with and without returning generation time includes the assumption that a percentage commuters. Table 6 3 presents the of residents will need to return home before evacuating. percentage of households with returning commuters and the percentage of households either without returning commuters or with no commuters. Appendix F presents the percent households who will await the return of commuters. Section 2.3, Assumption 3

b. The trip generation time accounts for the time and method Yes Section 5 to notify transients at various locations.

c. The trip generation time accounts for transients potentially Yes Section 5, Figure 5 1 returning to hotels before evacuating.

d. The effect of public transportation resources used during Yes Section 3.7 special events where a large number of transients are Public Transportation is not provided expected is considered. for the special event and was therefore not considered.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 4.3.2 Transit Dependent Permanent Residents

a. If available, existing and approved plans and bus routes are N/A Established bus routes do not exist.

used in the ETE analysis.

Section 8.1 under Evacuation of Transit Dependent People

b. The means of evacuating ambulatory and non ambulatory Yes Section 8.1 under Evacuation of Transit residents are discussed. Dependent People, Section 8.2

c. Logistical details, such as the time to obtain buses, brief Yes Section 8.1, Figure 8 1 drivers and initiate the bus route are used in the analysis.

d. The estimated time for transit dependent residents to Yes Section 8.1 under Evacuation of Transit prepare and then travel to a bus pickup point, including the Dependent People expected means of travel to the pickup point, is described.

e. The number of bus stops and time needed to load Yes Section 8.1, Table 8 5 though Table 8 7 passengers are discussed.

f. A map of bus routes is included. Yes Figure 10 2

g. The trip generation time for non ambulatory persons Yes Section 8.2 including the time to mobilize ambulances or special vehicles, time to drive to the home of residents, time to load, and time to drive out of the EPZ, is provided.

h. Information is provided to support analysis of return trips, if Yes Section 8.1 and 8.2 necessary.

4.3.3 Special Facilities

a. Information on evacuation logistics and mobilization times is Yes Section 2.4, Section 8.1, Table 8 8 provided. through Table 8 10 Palisades Power Plant N 11 KLD Engineering, P.C.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

b. The logistics of evacuating wheelchair and bed bound Yes Section 8.1, Table 8 8 through Table 8 residents are discussed. 10

c. Time for loading of residents is provided. Yes Section 2.4, Section 8.1, Table 8 8 through Table 8 10

d. Information is provided that indicates whether the Yes Section 8.1 evacuation can be completed in a single trip or if additional trips are needed.

e. Discussion is provided on whether special facility residents Yes Section 8.1 are expected to pass through the reception center before being evacuated to their final destination.

f. Supporting information is provided to quantify the time Yes Section 8.1 elements for each trip, including destinations if return trips are needed.

4.3.4 Schools

a. Information on evacuation logistics and mobilization times is Yes Section 2.4, Section 8.1, Table 8 2 provided. through Table 8 4

b. Time for loading of students is provided. Yes Section 2.4, Section 8.1, Table 8 2 through Table 8 4

c. Information is provided that indicates whether the Yes Section 8.1 evacuation can be completed in a single trip or if additional trips are needed.

d. If used, reception centers should be identified. A discussion Yes Section 8.1, Table 10 3 is provided on whether students are expected to pass through the reception center before being evacuated to their final destination.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

e. Supporting information is provided to quantify the time Yes Section 8.1, Table 8 2 through Table 8 4 elements for each trip, including destinations if return trips are needed.

4.4 Stochastic Model Runs

a. The number of simulation runs needed to produce average N/A DYNEV does not rely on simulation results is discussed. averages or random seeds for statistical

b. If one run of a single random seed is used to produce each N/A confidence. For DYNEV/DTRAD, it is a ETE result, the report includes a sensitivity study on the 90 meso scopic simulation and uses percent and 100 percent ETE using 10 different random dynamic traffic assignment model to seeds for evacuation of the full EPZ under Summer, obtain the "average" (stable) network Midweek, Daytime, Normal Weather conditions. work flow distribution. This is different from microscopic simulation, which is monte carlo random sampling by nature relying on different seeds to establish statistical confidence. Refer to Appendix B for more details 4.5 Model Boundaries

a. The method used to establish the simulation model Yes Section 4.5 boundaries is discussed.

b. Significant capacity reductions or population centers that Yes Section 4.5 may influence the ETE and that are located beyond the evacuation area or shadow region are identified and included in the model, if needed.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA) 4.6 Traffic Simulation Model Output

a. A discussion of whether the traffic simulation model used Yes Appendix B must be in equilibration prior to calculating the ETE is provided.

b. The minimum following model outputs for evacuation of the Yes 1. Appendix J, Table J 2 entire EPZ are provided to support review: 2. Table J 2

1. Evacuee average travel distance and time. 3. Table J 4

2. Evacuee average delay time. 4. None and 0%. 100 percent ETE is

3. Number of vehicles arriving at each destination node. based on the time the last

4. Total number and percentage of evacuee vehicles not vehicle exits the evacuation exiting the EPZ. zone

5. A plot that provides both the mobilization curve and 5. Figures J 2 through J 15 (one evacuation curve identifying the cumulative percentage plot for each scenario of evacuees who have mobilized and exited the EPZ. considered)

6. Average speed for each major evacuation route that exits 6. Table J 3 the EPZ.

c. Color coded roadway maps are provided for various times Yes Figure 7 3 through Figure 7 6 (e.g., at 2, 4, 6 hrs.) during a full EPZ evacuation scenario, identifying areas where congestion exists.

4.7 Evacuation Time Estimates for the General Public

a. The ETE includes the time to evacuate 90 percent and 100 Yes Table 7 1 and Table 7 2 percent of the total permanent resident and transient population.

b. Termination criteria for the 100 percent ETE are discussed, if N/A 100 percent ETE is based on the time not based on the time the last vehicle exits the evacuation the last vehicle exits the evacuation zone. zone.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

c. The ETE for 100 percent of the general public includes all Yes Section 5.4.1 - truncating survey data members of the general public. Any reductions or truncated to eliminate statistical outliers data is explained.

Table 7 2 - 100th percentile ETE for general population

d. Tables are provided for the 90 and 100 percent ETEs similar Yes Table 7 3 and Table 7 4 to Table 4 3, ETEs for a Staged Evacuation, and Table 4 4, ETEs for a Keyhole Evacuation.

e. ETEs are provided for the 100 percent evacuation of special Yes Section 8 facilities, transit dependent, and school populations.

5.0 Other Considerations 5.1 Development of Traffic Control Plans

a. Information that responsible authorities have approved the Yes Section 9, Appendix G traffic control plan used in the analysis are discussed.

b. Adjustments or additions to the traffic control plan that Yes Section 9, Appendix G affect the ETE is provided.

5.2 Enhancements in Evacuation Time

a. The results of assessments for enhancing evacuations are Yes Appendix M provided.

5.3 State and Local Review

a. A list of agencies contacted is provided and the extent of Yes Table 1 1 interaction with these agencies is discussed.

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Addressed in ETE NRC Review Criteria Comments Analysis (Yes/No/NA)

b. Information is provided on any unresolved issues that may Yes Results of the ETE study were formally affect the ETE. presented to state and local agencies at the final project meeting. There are no unresolved issues.

5.4 Reviews and Updates

a. The criteria for when an updated ETE analysis is required to Yes Appendix M, Section M.3 be performed and submitted to the NRC is discussed.

5.4.1 Extreme Conditions

a. The updated ETE analysis reflects the impact of EPZ N/A This ETE is being updated as a result of conditions not adequately reflected in the scenario the availability of US Census Bureau variations. decennial census data.

5.5 Reception Centers and Congregate Care Center

a. A map of congregate care centers and reception centers is Yes Figure 10 3 provided.

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