ML20197J813
| ML20197J813 | |
| Person / Time | |
|---|---|
| Site: | Monticello  |
| Issue date: | 12/31/1997 |
| From: | EARTH TECHNOLOGY CO. |
| To: | |
| Shared Package | |
| ML20197J805 | List: |
| References | |
| NUDOCS 9801050102 | |
| Download: ML20197J813 (70) | |
Text
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O Evacuation Time Estimates for the Plume Exposure Pathway Emergency Planning Zone O' Monticello Nuclear Power Plant l
Preparedfor:
i Northem States Power Company i
Prepared by:
Earth Tech j 196 Baker Avenue Concord, MA 01742 l December 1997
{ O' l nro==
F mas PDR
i
.m (v ) EXECUTIVE
SUMMARY
This report documents the results and methodology of Evacuation Time Estimates (ETE) prepared by Earth Tech (formerly llMM Associates, Inc.) for the Monticello Nuclear Power Plant in Monticello Township, Minnesota. This study supersedes the ETE study completed by llMM Associates in 1992. It is based on the most recent available population data.
Other than the updates to the population, there are several changes from the previous ETE, as fellows:
e improvements to roads.
4 Modification of the evacuation analysis cases from 90 degree quadrants to key-hole sectors to match the cases provided in the emergency plans.
- Addition of a winter weeknight, adverse weather scenario.
The 1996 permanent resident population in the EPZ is estimated at 41,950 persons, an increase of 23.0% from 1990. The 1996 seasonal resident population in the EPZ is estimated at 6,744 persons, an increase of 18.8% from 1990, The transient population, which includes large workplaces, hotels / motels,
(") recreational areas and shopping centers, was estimated at 3,898 persons for a winter weekday,2,483 persons for a winter weeknight and 9.336 persons for a summer weekend. The transient population has increased 58.8%,139.7% and 16.8%,
respectiveu, The specit I facilities population, which represents schools, hospitals, nursing homes and correctional facilities, was estimated at 12,091 persons for a winter weekday, 455 persons for a winter weeknight and 335 persons for a summer weekend. The special facilities population has increased 14.3%,8.9% and -24.2%, respectively.
The total population was estimated at 57,939 persons for a winter weekday,44,888 persons for a winter weeknight and 58,365 persons for a summer weekend. The total population has increased 23.0%,26.3% and 21.1%, respectively.
The full EPZ evacuation times range from 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />, 45 minutes for the winter weeknight fair weather condition to 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> for winter weekday and summer weekend adverse weather conditions, The evacuation times are essentially the same as the previous ETE study. Although the population has significantly increased, road improvements have served to keep the evacuation times at approximately the same level.
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O Executive Summary Pagei 23627/metefinal
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TABLE 0F CONTENTS -
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Page
' l'. INTRODUCTION 11 1.1 General 11 1.2 Site Location and Emergency Planning Zone (EPZ) 12 1.3 Evacuation Areas 13 1.4 Reception Center 13
- 2. METilODOLOGY AND ASSUMPTIONS - 21 2.1 Sources of Data ' 21 -
i 2.2 Assumptions 21 2.3 Summary of Methodology 23 2.4 Conditions Modeled 25
- 3. POPULATION AND VEHICLE DEMAND ESTIMATION 3-1 3.1 Permanent Residents 31 3.1.1 Auto-Owning Permanent Population 32 2 3.1.2 Transport Dependent Permanent Population 32 3.2 Seasonal Residents 32 3.3 Transient Population 32 33
-\/[]- 3.4 Special Facilities Population 3.5 Changes in Population 34
- 4. EVACUATION ROADWAY NETWORK 41 4.1 Network Definition 41 4.2 Evacuation Route Desen.vions 4-2 4.3 Characterizing the Evacuation Network 4-2
- 5. EVACUATION TIME ESTIM ATE METHODOLOGY S-1 5.1 Evacuation Analysis Cases 5-1 5.2 Initial Notification 5-1 5.3 Evacuation Preparation Times and Departure Distributions 5-2 5.4 Evacuation Simulation 53
- 6. ANALYSIS OF EVACUATION TIMES 6-1 6.1 Evacuation Time Estimate Summary 6-1
- 6.2 Evacuation Times for Specif.c Evacuation Areas 6 6.3 Evacuation Times for Combinations of Evacuation Areas 6-2 6.4 Queuing Locations 6-2 7.SUPPLEMEf'TAL ANALYSIS 7-1 7.1 Evacuation Confirmation 71
. , -y 7.2 Evacuation Management Points and Other Potential Mitigating Measures 7-1 i )-
.%J .
Table ofContents - l' age il 23627/metefinal
O ^reesaicos Appendix A Transient and Special Facility Population Data Appendix H Permanent Population Assignments Appendis C Roadway Network Listing and Capacities from NETVAC
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Table ofContects Page til 23627/metefinal
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) LIST OF FIGURES ni j Page Figure 1 1 Monticello Nuclear Power Plant Site Vicinity 1-4 ;
Figure 1-2 Monticello Nuclear Power Plant EPZ,l.PZs and Sectors 1-5 l Figure 41 EPZ Evacuation Network ;
Figure 5-1 Notification / Preparation / Mobilization Time Distributions 5-7 Figure 71 Recommended Traffic Management Locations 7-3 g- g i
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- l ) Fold-out map in back of report.
~J Table ofContents Pagetv 23627/metefinal
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f LIST OF TABLES :
~Page Table 1 1 Municipalities Totally or Partially.Within the Monticello EPZ_ l6-Table 12 Monticello EPZ Evacuation Analysis Cases ;l 7
. Table 3-1 Population Data by Subarca for the Monticello EPZ --
- Winter Weekday 3-5 ,
Table 3 2 Population Data by Subarea for the Monticello EPZ .
- Winter Weeknight 3-6 Table 3-3 Population Data by Subarca for the Monticello EPZ
- Summer Weekend 3 Table 3 4 Population Data by Evacuation Analysis Area for the Monticello EPZ- Winter Weekday 38' l Table 3 5 Populatic. 7ata by Evacuation Analysis Area for the Monticello EPZ- Winter Weeknight 3-9 Table 3 6 Population Data by Evacuation Analysis Area for the
= Monticello EPZ- Summer Weekend 3-10' Table 3 7 Permanent Population Distribution By Sector 3 11 Table 3-8 Seasonal Population Distribution By Sector 3 12 Table 3 9 Transient Population Distribution By Sector
- Winter Weekday 3 13 Table 3 10 Transient Population Distribution By Sector I4 - Winter Wecknight 3 14 Tcble 3 11 Transient Population Distribution By Sector
- Summer Weekend 3-15 Table 3 12 Special Facility Population Distribution By Sector
- Winter Weekday 3-16 Table 3 13 Special Facility Population Distribution By Sector ,
- Winter Weeknigh: 3 17 Table 3-14 Special Facility Population Distribution By Sector
- Summer Weekend 3 18 Table 3-15 Changes in Population Within the Monticello EPZ 3-19 Table 6-1 Evacuation Time Estimates 6-4
. . Table 71 Recommended Traffic Management Locations - 7-4 O ,
Table ofContents : Page v 2362Nmetefinal
- 1. INTRODUCTION v/ -
1.1 General Evacuation time studies analyze the manner in which the population within the Plume Exposure Pathway Emergency Planning Zone (EPZ) surrounding a nuclear power plant site would evacuee during a radiological emergency. Evacuation time studies provide licensees State and local governments site-specific information helpful to protec,ive actici ion-making. The studies estimate, for officials who would make protective action secisions, the time necessary to evacuate the EPZ, and identify instances in which unusual evacuation constraints exist.
Estimates of the time required to evacuate from areas around nuclear pow er plant sites are required for all operating plants in the United States. Federal guidance has been prepared to outline the format and content of these evacuation time estimates (NUREG-0654, Rev.ll and NUREG/CR-48312),
Previous evacuation time estimate (ETE) studies were last updated for the Monticello Nuclear Power Plant Plume Exposure Pathway EPZ in 1992. The guidance presented in NUREG-0654. Rev. I and NUREG/CR-4831 indicate that the evacuation time estimates should be updated as local conditions change. Although there are no o specified time frames for updating the evacuation time estimates, they were updated Q for the following reasons:
- The previous data was approximately 5 years old
- There has been some growth within the EPZ The evacuation time estimates have been developed using current population, local roadway network data and the NETVAC computer simulation model. The NETVAC model was developed specifically by Earth Tech to provide evacuation time estimates and related information for use in emergency planning. The preparation of the ETE study has been accomplished with the direct input and review of the state, counties and NSP.
' friteria. fqt Preparation and Evaluation of Radiolozical Emercency Resnonse Plans and Preparedness in SE20rt of Nuclear Power Plants, NUREG 0654, FEMA-REP-1, Rev.1, U.S. Nuclear Regulatory Commission, Federal Emergency Management Agency, November,1980.
2 State of the Art in Evacuation Time Estimate Studies for Nuclear Power Plants, NUREG/CR-4831. T. E.
Urbanik and J. D. Jamison, Pacific Northwest Laboratory, U.S. Nuclear Regulatory Commission, March, I)
LJ 1992.
Introduction Page1-1 23627/metefinal
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[,n) Evacuation times have been estimated for various areas, times and weather conditions, 1 I
as suggested in Appendix 4 of NUREG 0654, Rev.1. These evacuation times represent the times required for completingthe followinF actions-l
- 1) Public noti 0 cation;
- 2) Preparationand mobilization;and i
- 3) Actual movement out of the EPZ (i.e., on-road travel time, including delays associated with vehicle queuing).
1.2 Site Location ant! Emergency Planning Zone (EPZ)
The Monticello Nuclear Power Plant is located on the southwestern shore of the Mississippi River in Monticello Township within Wright County, Minnesota. The plant site is located approximately 30 miles northwest of Minneapolis. A site vicinity map for the plant is included as Figure 1 1. A listing of the municipalitiesand their 1996 permanent resident population within the Monticello EPZ is presented in Table l-1.
The plume exposure pathway EPZ is the geographic area surrounding a nuclear power plant within which the Nuclear Regulatory Commission (NRC) requires advance
( planning for evacuatien or other short-term protective actions in the event of a V radiologicalernergency. NRC regulations denne the plume exposure pathway EPZ as follows:
" Generally, the Plume Exposure Pathway EPZ for nuclear power plants shall consist of an area about 10 miles (16 kilometers)in radius.. The exact size d con 0guration of the EPZ surrounding a particular nuclear power reactor shall be determined in relation to local emergency response needs and capabilities as they are affected by such conditions as demography, topography, land characteristics, access routes and jurisdictionalboundaries."3 ne state and county governments of Minnesota have prepared pims for emergencies at the Monticello Nuclear Power Plant. These agencies have denned and designated the plume exposure pathway EPZ consisting of an irregularly shaped boundary located approximately 10 miles from the Monticello Nuclear Power Plant as shown in Figure 1-2.
3 10 CFR, Section 50.47(c)(2), The NRC provides further guidance for defining the Plume Exposure Pathway EPZ in NUREG 0654 Rev.1.
Introduction Page 1-2 23627/metefinal
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\s' 1.3 Evacuation Areas The EPZ has been subdivided into 12 areas referred to as Subarcas based on such conditions as demography, topography, land characteristics, access / egress routes and jurisdictionalboundaries. The Subarcas are shown with sixteen 22.5* radial sectors in Figure 1-2. For purposes of anslyzing evacuation times for various scenarios, the Subarcas have been combined in various ways to form different evacuation cases, as shown in Table !-2.
1.4 Reception Center The reception center for evacuees is provided at a location outside the EPZ, at the Osseo Jr. liigh School in Osseo, Minnesota. During an eva:uation all persons are expected to leave the EPZ by the most direct route. Those persons going to the reception center are expected to make their way to the reception center after leaving the EPZ.
Osseo Jr. liigh School is located approximately 35 miles southeast of the Monticello plant, it is reached via U.S. Interstate 94 to 95* Street / County Road north.
Some schools will be evacuated to other locations but this does not effect evacuation time estimates, i
G Intrmfuction Page 1-3 23627/metefinal
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'ntroduchon page t-5
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[~ : Table 1 Municipalities Totally or Partially Within the Monticello EPZ
\
Permanent Resident Municipality Population Within EPZ8 Wright County Monticello Township 10,546 (including City of Monticello)
BufTalo Township 4,616 (including City of Buffalo)
Ostego Township5 1,390-Maple Lake Township 3,532
- (including City of Maple Lake)
Silver Creek Township 2,112 Corinna Township 751 Clearwater Township 1&01 (including City of Clearwater)
Total Wright County 24,551 Sherburne County flecker Township 4,876 e (including City of Becker)
-( Big Lake Township (including City of Big Lake) 9,573 Orrock Township 1,785 Palmer Township 78 Clear 1,ake Township 707 Santiago Township 308
- j. Elk River City 22 Total Sherburne County 17,399 Total 1996 Permanent Resident Population 41,950 4
1996 population estimates for municipalities and townships were obtained from the Minnesota Planning Office, 5 Since the 1990 Census, Frankfort Township has been annexed into several communi;ies. The portion of N Frankfort Township which was in the EPZ was annexed by Ostego Township.
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Introducthm PageI 6 23627/me.: final l-l.
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' I Table 21 Monticello FPZ Esacuation Analysis Cases -
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Evacuation Wind Direction Evacuation Area i Case (degrees from) Ring- _ Downwind Subarcas 1 2 mile 2 2 -348.75-11.25 2 mile & 5-mile 2, SS, SW ,
3 -- 2 mile & 10-mile 2, SS, SW,10SE,10S,10SW i 4- l 1.25-33.75 2 mile & 5 mile 2, SS, SW 5 2-mile & 10-mile 2, SS, SW,105,10SW,10W 6 33.75-56.25 2 mile & 5-mile 2, SS, SW 7 2 mile & 10-mile 2, SS, S W,10S,10SW,10W 8 56.25 78.75 2-mile & 5 mile 2, SS, SW 9 2-mile & 10-mile 2, 5 S, SW,10SW,10W -
10 78.75-101.25 2 mile & 5-mile 2, SW II 2 mile & 10 mile 2, SW,10SW,10W,10NW 12 101.25 123.75 2-mile & 5 mile 2, SW, SN 13 2 mile & 10-mile 2, SW, SN,10W,10NW 14 123.75-146.25 2 mile & 5-mile 2, SW, SN 15 2 mile & 10-mile 2, SW, SN,10W,10NW,10N 2,SW,SN p 16 146.25 168.75 2 mile & 5-mile 2, SW, SN,10NW,10N
-( / 17 2-mile & 10-mile 18 168.75-191.25 2-mile & 5-mile 2, SN 19
. mile & 10-mile 2, SN,10NW,10N,10E ~
20 191.25-213.75 2-mile & 5 mile 2, SN, SE 21 2-mile & 10-mile 2,5N, SE, ION,10E 22 213.75-236.25 2-mile & 5-mile 2,SN,SE 23 2-mile & 10-mile 2, SN,5 E, ION,10E 24 236.25-258.75 2 mile & 5-mile 2,SN,SE
. 25 2 mile & 10-mile 2, SN, SE,10E 26 258.75 281.25 2-mile & 5-mile 2,5E,5S 27 2-mile & 10 mile 2, SE, SS,10E,10SE 28 -281,25 303.75 2-mile & 5-mile 2, SE, SS 29 2-mile & 10 mile 2, SE, SS,10SE 30 303.75 326.25 2-mile & 5-mile 2,SE,SS 31 2-mile & 10-mile 2, SE, SS,10SE,10S 32- 326.25 348.75 2-mile & 5 mile- 2, SS 33- 2-mile & 10-mile 2,SS,10SE,10S 34 5-mile 2, SN, SE, SS, SW
-ft 35 10-mile Full EPZ v
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intmluction . l' age I 7 23627/metefinal
(; 2. METIIODOLOGY AND ASSUMPTIONS C/
2,1 Sourecs of Data The following data sources were reviewed in order to deselop the appropriate input required for the computer simulation model used for the evacuation analysis:
- Population estimates for municipalities and townships in were obtained from 1996 Minnesota Planning Of6ce data.
- Seasonal residents were estimated using the 1990 census data and applying a ratio for the increase in permanent residents, e Lists of special facilities (schools, hospitals, rest homes and incarceration facilities), transient facilities (parks, hotels, motels, recreational) and major places of employment (greater than 50 people) were obtained from the 1992 study, phone books, internet searches, local Chambers of Commerce, and Minnesota Department of Trade and Economic Development Community Profiles. Population estimates were collected from phone call surveys to the facilities conducted by Earth Tech during 1997.
. Roadway geometric and operational data were updated in June and July,1997
\ through Deld surveys, (d
2.2 Assumptions The following assumptions were made in order to simulate an evacuation of the plume exposure EPZ:
- The evacuation will be conducted in accordance with the current state and county radiological emergency response plans.
- Preparation and mobilization times have been developed for each population component (i.e., permanent residents, seasonal residents, transients and enecial facilities). These times were developed in consultation with State and County emergency preparedness ofGcials. The speci6c times are discussed in Sections 5.2 and 5.3.
- The evacuation time estimates represent the time required to evacuate the population from the designated Subarcas included in the evacuation analysis cases and include the time required for initial noti 6 cation.
. it is assumed that all persons within the EPZ area will evacuate. Evacuation of the EPZ will be considered complete after all evacuating vehicles are outside of Ci the EPZ or analysis area.
LI Afethmlology and Assumptiom l' age :-) 23627/metefinal
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( ) . The general public will be evacuated to the Reception Center outside the EPZ,
" Children from schools will be transported directly to designated areas.
o The public will travel out of the plume exposure EPZ along evacuation routes designated by state and county emergency preparedness officials, e it is assumed that the permanent population sector will evacuate from their places of residence. All households having more than one vehicle will use one automobile. Existing research indicates that people will not evacuate, regardless of danger, until all family members are accounted for and arrangements have been made for their evacuation. Thus, there is a strong tendency for evacuees to evacuate as a family unit w here possible.6
. The transport-dependent population will be evacuated by bus or ambulance through efforts coordinated by County and municipal emergency preparedness officials.
e it is assumed that existing lane utilization and existing traflic control devices will prevail during the course of the evacuation. it is also assumed that appropriate State and County personnel will restrict unauthorized access into the EPZ.
(Oj e Vehicle occupancy rates used for the various population categories are as
follows:
- Permanent and seasonal residents - I vehicle per household.
- Schools 60 persons per bus.
- llospitals/ Nursing flomes/ Correctional Facilities - number of vehicles provided by the counties.
- Major places of employment - I schicle per employee; 1.25 employees per vehicle at the Monticello and Sherburne County generating plants.
- llotels/ Motels - I vehicle per room.
- Regional Shopping Centers - I vehicle per parking space.
- Recreational areas - I vehicle per campsite or 4 persons per vehicle; 2.5 people per vehicle at the state parks and golf courses.
Evacuation Risks- An Evaluation llans and Sell, USEPA, July 1974; and livacuation Plannine in Emereency
[]
\
J Manacement Perry, Lindell and Green, Lexington Books,1981.
i l
l Methodology and Anumptions Page 2-2 23627/metefinal
I f';
- The evacuation analysis cases which have been analyzed are summarized in V Section 2.3 and represent a range of conditions, per guidance presented in Appendix 4 of NUREG-0654, Rev.1 (1980). These cases have been carefully chosen to present an appropriate range of conditions to be used in the protective action decision-making process. Although additional conditions can be identined, the cases analyzed reflect the bounds (i.e, low, typical and high) of possible cases. The conditions modeled include:
- Winter weekday, fair and adverse weather
- Winter weeknight, fair and adverse weather
- Summer weekend, fair and adverse weather e Adverse weather refers to severe rainstonus that would reduce effective roadway capacity by twenty (20) percent for summer conditions end snowstorms that would reduce capacity by thirty (30) percent for winter conditions 7 2.3 Summary of Methodology The evacuation time estimates developed for the Monticello EPZ are based upon a time distribution of evacuati(n. events as opposed to a summation of sequential events. This methodology assumes that the various time components in an evacuation (i.e., the time ast.ociated with preparation, mobilization, etc.) overlap and
[V] occur within certain time ranges. The sequential methodology, which assumes that each phase of the evacuation must be completed before the next one begins, tends to over-estimate evacuation times. The time distribution approach, although more complex than the sequential approach, is based upon more realistic assumptions, hence it leads to more realistic evacuation times.
The NETVAC computer simulation model was used to develop the evacuation time estimates. This is a computer program developed by Earth Tech, in collaboration with Professor Yosef Sheffi of the Massachusetts Institute of Technology's (MIT)
Center for Transportation Studies. The model was developed specifically to provide evacuation time estimates and related infonnation for use in emergency planning.
The NETVAC program has the following characteristics:
. The model accounts for the detailed distribution of vehicle demand.
7 Extrapolated from data presented in The Environmental influence of Rain on Freeway Canacity, E. Roy Jones and Merrell E. Goolsby, liighway Research Record No. 321, Highway Research Board,1970; and IIcadway Approach to Intersection Canacity, Donald S. Ilerry and P.D. Gandhi, Highway Research Record
[] I No. 453, liighway Research Board,1973.
v Afethodology ami Assumptions Page 2 3 23627/metefinal
e The model considers fundamental physical and operational characteristics of the
)
'u evacuation road network.
e The model accounts for dynamic characteristics of evacuation time flows.
e The model provides thorough documentation of results.
- The model provides a means for examining a complex problem in a structured manner.
- The model can readily address fair weather versus adverse wcather conditions.
- The model can readily address evacuation scenarios occurring at different times ofday.
- The model can readily address changes in population which would be likely to occur within the EPZ at different times of the week and different times of the year.
The NETVAC program is a compute, simulation model which uses traffic How relationships to calculate and record traffic densities, speeds, Dows, queues and other relevant information throughout the evacuation process. The model employs a O sophisticated list processing method to represent the evacuation as a series oflinks V (roadway segments) and nodes (intersections). Traffic is first entered at designated entry nodes on the roadway network. At every simulation interva!, the model processes vehicles from the links entering an intersection to the links emanating from it. The NETVAC model includes a dynamic route selection feature whereby drivers' choice of outbound links at every intersection is based on two criteria:
- 1. The degree to which an outbound link leads away from the plant or the direction of specific evacuation routings where such plans exist, and
- 2. The traffic conditions on the outbound links (i.e., travel speeds and presence of vehicle queuing or congestion).
The roadway and intersection approach capacities calculated by the NETVAC program are based upon recorded geometric and operational field data and accepted traffic flow relationships presented in the liighway Capacity Manuals and related traffic engineering reference material. Due to the dynamic route assignment mechanism, approach capacities are updated at each simulation interval to account for potential changes in turning movement volumes. The intersection control 8
Ilichway Canacity Manual. Transportation Research p?.ard Special Report 209, National Research Council, 1985 and flichway Canacity Manual, liighway ' .:scarch Board Special Report 27, National Research council,
(]
J 1965.
Methodology and Anumptiom Page 2 4 23627/metefinal
options which can be specified with the NETVAC model include intersections with (m'") traffic signals and priority control intersections (i.e., stop or yield signs).
A more detailed description of the NETVAC program is described in Section S A.
2.4 Conditions Modeled Pursuant to NUREG 0654, Rev. I guidance, evacuation time estimates have been prepared for a range of temporal, seasonal and weather conditions. Estimates have been prepared for fair and adverse weather conditions luring winter weekday, winter weckr.ight and summer weekend.
Fair weather refers to conditions where roadways are clear and dry, and visibility is not impaired. Adverse weather during summer periods is defined as a rainstorm condition where visibility is impaired and roadway capacities and speeds are reduced by 20 percent. Adverse weather during winter periods is defined as a snowstorm condition where roadway capacities and speeds are reduced by 30 percent.
The various population components which have been incorporated in the evacuation conditions modeled are summarized below:
- 1. Winter Weekday: This situation representa a typical day period during the Q
V winter when school is in session and the work force is at a full daytime level.
Assumptions on the population levels for this condition include tha following:
. Permanent residents within the EPZ will evacuate from their places of residence; e Major work places are fully staffed at typical daytime levels;
- The Monticello Plant employment is at an estimated peak daytime level;
- Schools are in session; e llospitals, nursing homes and correctional facilities are full; e llotel and motel facilities are fully occupied; and
. Recreational facilities are at winter daytime levels.
- 2. Winter Wecknight: This situation reflects a typical night period when permanent residents are home and the work force is at a night-time level.
Assumptions on the population levels for this condition include the following:
- Permanent residents within the EPZ will evacuate from their places of (m)
<_J residence; AlethoJology and Assumptions Page 2-5 23627/metefinal
e Major work places are at typical night time 'evels; lv) e The Monticello Plant employment is at an estimated peak night-time level;
- Day schools are closed; e llospitals, nursing homes and correctional facilities are fully occupied at night-time levels:
e llotel and motel facilities are fully occupied; and e Recreational facilities are at winter night-time levels.
- 3. Summer Weekend: The t'2mmer weekend situation represents a daytime period when permanent residents are home and major work places are at typical weekend levels. Assumptions on the population levels for this conditica include the following:
- Permanent residents within the EPZ will evacuate from their places of residence; e Seasonal residents will evacuate from their places of residence; rm.
(v ) e Major work placer are at typical weekend levels; e The Monticello Plant employment is at an estimated weekend level; e Schools are closed; e Ilospitals, nursing homes and correctional facilities are fully occupied at weekend levels; e flotel and motel facilities are fully occupied; e Recreational facilities are at summer weekend levels, s.
I
.d Alethodology and Assumptions l' age 2-6 23627/metefinal
I O C 3. POPULATION AND VElllCLE DEMAND ESTIMATION The development of vehicle demand estimates for the Monticello EPZ consisted of two primary steps. The first step was the detennination of the number and distribution of the population to be evacuated. The second step was the determination of the appropriate number of vehicles for each of the population categories. Federal guidance (NUREG 0654, Rev.1) indicates that three population categories should be considered: permanent residents, transients, and persons in special facilities (such as schools, medical facilities and nursing homes).
The methodology used to develop the total population and vehicle demand estimates within the Monticello EPZ incorporates intrinsic double-counting. For example, it is reasonable to assume that a portion of the identined employees and visitors to recreational areas are also permanent residents within the EPZ. In addition, school children, treated as an independent special facility category, are also included in the permanent population estimates. Accordingly, the population and vehicle demand estimates which have been developed are considered to be conservative (i.e., they over-estimate actual population and vehicle levels which may be in the area at any given time). For the purpose of developing evacuation time estimates, however, these Ogures are considered appropriate since they more accurately reacct vehicle activity along the evacuation network of persons traveling home or picking up children prior to evacuating the EPZ. Population and vehicle demand estimates for each of the population categories are summarized below.
The following sections summarize the methodology and data sources used to update the penuarient, seasonal, transient, and specia. facilities population data.
3.1 Permanent Itcsidents Pennanent residents are defined as those persons having a permanent residence within the EPZ. The 1996 Minnesota Planning Office data was used to detennine population for municipalities and townships within the EPZ. Using the 1990 U.S.
Census Bureau population data, growth rates were determined for each community.
These growth rates were applied to the permanent resident sector and subarea data contained in the 1992 ETE study to obtain 1996 population distributions. The 1992 ETE pennanent resident population distributions were based on land area allocation using the detailed 1990 Census block maps.
An estimated 41,950 persons reside oermanently within the Monticello Nuclear Power Plant EPZ. Table 1-1 presents the data by municipality. Tables 3-1 through 3-3 present the permanent resident population by Subarca in tabular format. Tables 3-4 through 3-6 present the permanent resident population by Evacuation Analysis Area. The distribution of the total permanent resident population to 22.5* sectors and one-mile increments is listed in Table 3-7.
Population and Vehicle Demand Estimation Page 3-1 23627/metefinal
-1 I
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( 3.1.1 Auto-Owning Permanent Population
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For the purpose of estimating the vehicle demand associated with the permanent resident population, the average household occupancy rate within each municipality was used. Using an average household occupancy rate to estimate the vehicle demand assumes that one vehicle will evacuate from each permanent residence.
This is consistent with existing research indicating the tendency of persons to evacuate, where possible, as a family unit.'
3.1.2 Transport Dependent Permanent Population Current County emergency response plans specify that the transport-dependent population will receive transportation assistance through efforts coordinated by County emergency service personnel, in order to estimate the total vehicle demand associated with the transport dependent population for evacuation modeling purposes, the same occupancy rate as that used for the auto-owning population was used. This is a conservative estimate of the vehicle demand associated with the transport-dependent population,since many households may be evacuated by bus, or travel with a neighbor friend.
3.2 Seasonal Residents
(~3 The seasonal population category includes those residents who reside in the area on V a temporary basis, particularly during the summer period. Seasonal residences are typically not insulated and are suitable for occupancy for only a portien of the ys ir.
The permanent population growth factors were applied to the seasonal data contained in the 1992 ETE report. The 1992 ETE data was obtained from the 1990 U.S. Census of Populati on and flousing seasonal housing residences assuming an average occupancy factor of 5.4 persons per seasonal unit. An estimated 6,744 persons reside within the Monticello Nuclear Power Plant EPZ on a seasonal basis.
The corresponding vehicle demand estimates for this population segment was based on the household occupancy rate for the permanent resident population. Tables 31 through 3 3 present this seasonal resident population by Subarea in tabular format.
Tables 3 4 through 3-6 present the seasonal resident population by Evacuation Analysis Area. The distribution of the total seasonal resident population to 22.5 sectors and one-mile increments is listed in Table 3 8.
3.3 Transient Population The transient population segment includes persons in the work force, hotels / motels, recreational areas and regional shopping centers. Listings of major industrial and Evccuation Risks An Evaluation, llans and Sell, USEPA, July 1974; and " Evacuation Planning in Emergency O - Management", Perry, Lindell, ed Green, Lexington Books,1981.
G Popu;ation and Vehicle Demand Dtimation Page 3-2 23627/metefinal
plant employers, hotels / motels, recreational areas and regional shopping centers
('v')
within the EPZ are presented in Appendix A.
Lists of major employers were updated based on employer listings from local Chambers of Commerce, and Minnesota Department of Trade and Economic Developnxnt Community Profiles. Employee population estimatea were updated through a telephone survey.
Lists of hotels / motels, recreational areas and regional shopping centers were updated based on information obtained from local Chambers of Commerce, Minnesota Department of Trade and Economic Development Community Profiles, telephone books and directed internet searches. The population estimates were updated through a telephone survey.
For purposes of estimating the total number of vehicles associated with the transient population segment, an auto occupancy factor of 1 person per vehicle was used for all work places except at the Monticello and Sherburne County generating plants where an average occupancy of 1.25 persons per vehicle was used, For the hotel / motel and recreational population, it was assumed that there would be i vehicle per hotel / motel unit or campsite and that recreational parking lots would be at capacity. Similarly, for regional shopping centers, it was assumed that all n available parking spaces would be filled, with an average of 1.5 persons per vehicle.
) The occupancy rates were developed for an estimate of peak vehicle demand where transient facilities are fully occupied. The resultant vehicle demand is conservative for periods when occupancy of these transient facilities is lower than peak levels.
Population data and vehicle demand estimates for the transient popolation segment, including the work force, motels, recreational areas and regional shopping centers are presented by facility in Appendix A, As previously indicated, intrinsic double.
counting of total vehicle demand is incorporated in these estimates since a ponion of the identified employees, and visitors to the recreational areas are also permanent residents of the EPZ.
Tables 31 through 3-3 present the transient population by Subarea. Tables 3-4 through 3-6 present the transient population by Evacuation Analysis Area. Transient population is listed by sector for winter weekday, winter weeknight and summer weekend in Tables 3 9 through 311.
3.4 Special Facilities Population The special facility population segment includes persons in schools, hospitals, nursing homes and correctional facilities. Lists of special facilities by county are provided in Appendix A.
l a
Population and Vehicle Demand Esnmation Page 3-3 23627/metefinal
r~s .
Lists of schools, hospitals, nursing homes and correctional facilities were updated (V) based on information obtained from locci Chambers of Commerce, Minnesot Department of Trade and Economic Development Community Pronles, telephone books 'and directed internet searches. The population estimates were updated through telephone survey.
Within the EPZ there are 9 schools,2 hospitals, and 2 ciderly homes in Wright County, Within the EPZ there are no correctional facilities in Wright County.
Within the EPZ there are 6 schools in Shertari.e County. With:n the EP7, there are no hospitals, nursing homes or correctional facilities in Sherburne County. Vehicle demand estimates were provided by each of the county emerpncy management of0cials.
A detailed listing of the special facilities within the EPZ and their associated vehicle demand is presented in Appendix A. 'iables 3-1 through 3 3 present the special facility population by Subarca. Tables 3-4 through 3 6 present the special facilities population by Evacuation Analysis Area. The special facility population is listed by sector for winter weekday, winter weeknight and summer weekend in Tables 312 through 3 14.
3.5 Changes in Population l'3 (g Table 315 compares the 1992 population levels (used in the previous ETE study) with the current 1997 population. It further addresses the percent change in population for that time period.
A Population and l'ehicle Demand Dtimation Pag 3-4 23027/metefinal
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Table 3-1: Population Data by Sebarra for the Monticello EPZ - Winter Weekday Analysis Permanent Seasonal Total Work Recru- Overnight / Total . Medical / - Total Special : Total Area Resident - Resident Resident - Force tional . Shopping Transient School Iscarceration Facilities - Population 2- 4,675- 0 4,675 ' 647 5 0 652 't,175' O- 1,175.' - 6,502; SN 3,994 0 3,994 550 8 82 640 1,930 0 1,930 '.6,564 SE 9,645 0 9,64; 104 2 311 417 2,265 0 2,265 12,327 -
SS. 6,749 0 6,749 1,138 2 209 1,349 2,865 170 3.035 I l.133 SW 2,236 0 1,236 0 102 0 102 0 0 0. 2,338 ION 391 0 391 0 0 0 0 0 0 0 391 10E I,785 0 1,785 0 0 0 0 0 0 0 1,785 10SE 1,390 0 1,390 0 0 0 0 0 0 0 1,390 10S 4,616 0 4,616 571 0 167 738 2,312 190 -2.502 .7,856 10SW 3,408 0 3,408 0 0 0 0 1.184 0 1,134 4,592 10W. 2,354 0 2,354 0 0 0 0 0' 0' O 2.354 -
10NW 707 0 707 0 0 0 0 0 0 0 .707 ,
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i Population and Vehicle Demand Estimation Pege 3-5 23627/metefinal
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Table 3-2: Popuistion Data by Subares for the Monticello EPZ- Winter Weeknight Analysis Permanent Seasons! Total Work Recrea- Overnight / Total - MedicaIl .- Total Special Total Area Resident Resident Resident Force tional Shopping Transient School Incarceration FaciHties Population 2 4,675 0 4.675 200 5 0 205 'O O O 4,880
$N 3,994 0 3,994 199 8 82 289 30 0 30 4,313' SE 9,645 0 9,645 ~ 33 2 310 345 0 0 0 9,990 SS 6,749 0 6.749 788 0 208 996 0 170 170. 7,915 5W~ 2,236 0 2,236 0 2 0 2 0 0 0 '2,238 -
10N 391 0 391 0 0 0 0 0 0 0 391-15E 1,785 0 1,785 0 0 0 0 0 0 0 'I,785.
10SE 1,390 0 1,390 0 0 0 0 0 0 'O l 1,390 '
IOS 4,616 0 4,616 493 0 153 646 65 190 .255 = 5.517 10SW 3,408 0 3,408 0 0 0 0 0 0 0 3,408 10W 2,354 0 2,354 0 0 0 0 0 0 0 2,354 L
10NW 707 0 707 0 0 0 0 0 0 0 707 Population and l'ehicle DemandEstimation Page 3-6 23627/metefinal
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Table 3-3: Pepelsties Data by Soberes for the Monticelle EPZ- Sommer Weekend
- i s
4 Analysis Permiseest Semeenst' Total Work Recres- O,ereight! Total WiesF. Total .W Total Area - Resadent Resadest . Resident si est Si, r _,. T-eassent Scheel t=uecerat M Facdsters Pepelstion l 2 4.675. 0 4.675 200 170' O 370 0 0 C 5.345 i I
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0 IOS - 4.616 831 5.447 489 0 171 660 165 165 6.272 ;
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i TaWe3-7: Peresseest Popeineses Distribution By SecterW i
Sector threctose M H H M .M 51 .g ' H M %I0 1F M ,
!- Plant Plant O' O O O O O O O 'O O O 9 i .
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G SE O 1,109 1,625 1.908 270 242 312 173 172 268 859 II SSE- 20- 206 81 704 8% 107 88 99 44 113 13s' 2,496 :
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-.. Table 3-15: Changes in Population Within the Monticello EPZ t i> -
t 1992 Population Levels 1997 Population imets Percent Change in Popeteties
> Winter . %: ster Susenser Winter Winter Seneseer Winter Winter Sessener Population Type Day Night Weekend Day Night Weekend Day Night Weekend Permanent 34,094 34,094 34,094 41,950 41,950 41,950 23.0 23.0 23.0 !
i Seasonal 0 0 5.677 0 0 6,744 0 0 18.8 ;
Total Residents ' 34,094 34,094 39,771 41,950 41.950 48,694 23.0 23.0 4.1 i
l i
Workforce 1,809 490 603 3,010 1,713 1.582 66.4 249.6 162.4 i Ilotels/ Motels / Shopping 546 546 546 769 753 781 40.8 37.9 43.0 i Recreational 100 0 6,846 119 17 6.973 19.0 100.0 1.9 l
j- Total Transient 2.455 1.036 7,995 3,898 2,483 9,336 58.8 139.7 16.8 }
i i
! Schools 10,086 108 0 11,731 95 0 163 -12.0 0 i
l MedicallIncarceration 488 310 442 360 360 335 -26.2 16.1 ' 24.2
.t Total Special Facilities 10.574 418 442 12.091 455 335' 14 3 8.9 -24.2 j Total Population 47,123 35,548 48,298 57,939 44.888 58,365 - 23.9 26.3 21.1 ;
Percent Annual Average leeresse in Total Population ' 4.6 5,3 4.2 i .
Population and Vehicle Demand Estimation Page 3-19 23627/metefirul W wi 3--- + -- ., ..
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- 4. EVACUATION ROADWAY NETWORK 4.1 Network Definition in order to estimate evacuation times for the Monticello Nuclear Power Plant EPZ, an evaluation of the roadway network likely to be used by departing vehicles was undertaken. In denning the evacuation roadway network, Earth Tech relied heavily on several sources ofinformation.
- 1) The evacuation routes described in the existing State, County and local emergencyresponse plans;
- 2) State, County and local highway maps of the EPZ area;
- 3) Discussion with State, County and local emergency preparedness omclals, ,
and l
- 4) A comprehensive neld survey of the EPZ.
l 11ased on this data, an evacuation network was identined to be used for evacuation simulation modeling. The trame network elements considered in the evacuation modeling consist of the major streets and intersections within the EPZ. The major O streets include roadways of the following classifications:
G e Expressways are characterized by high design standa ds, limited access, !
grade separation, and primarily through trafne. Interstate Route 94 is an example cf an expressway within the Monticello EPZ.
- Arterial Streets are characterized by continuity of travel; connecting business, population, or major recreation areas, and trame controls and geometric designs which enhance trame now and safety. Examples of main arterials are State liighway 25 in Wright County and U.S. Route 10 in SherbumeCounty, a Collector Streets represented by links between residential areas and arter41 streets. Rese roads are characterized by lower design standards and frequent stops at minor intersections. Examples of collector streets ;
include County Road 75 in Wright County and County Road 75 in 1
SherburneCounty.
i Evacuarion Roac%m Netwark Page &I 23627/metefinal P
.. , nw-,,r,w. ..,,,,--,-,v v.,,-e-, - . , ,,-y --~-..-.,,v-r ,-v +-e. ,, . . , , , . - , , .o-.w...,-vwe,w-w,...n.--,-,---.-- ,,--,,,w>., - - - -
The smaller local residential roadways are not specifically evaluated as part of the (mU) model simulation, but are taken into account as part of the vehicle leading process.
The primary evacuation routings used in the modeling are indicated on Figure 4.1.i2 4.2 Evacuation Route Destdptions The primary evacuation routings were deseloped to pennit a general radial travel pattern away from the plant, toward designated Reception Center. In some cases, the evacuating routes travel tow ard the plant for a short distance until access to an outw ard evacuation route is obtained. Each designated evacuation route is ultimately intended to carry evacuating traf0c out of the EPZ.
4.3 Characterliing the Evacuation Network The evacuation network was characterizedas part of the previous study. After dcuning and mapping the links (roadway sections) and nodes (intersections) included in the evacuation roadway network, both physical and operational characteristics of the system were inventoried. Using both field studies and available maps, the geometric descriptions for each component of the network were prepared. Field data which were recorded included the number of lanes, lane widths, shoulder widths, distances to obstructions, grades, cruise speeds, trafne controls and other data necessary to calculate the traf0c capacity of each link in the system. Traf0c capacity information bsI G
for each intersection in the network was also collected. Link lengths were measured from available maps.
For the present study, tne roadway netwo L,w hich was developed in prior ETE studies, was updated by Deld veri 0 cation of the network data and by contacting county highway of0cials. Changes in the network including those under construction,were incorporatedinto the existing network. As a reruit of the Geld update and infonnation provided by county road officials and NSP, the following changes in the evacuation network wcre noted:
e liighway 25 will be expanded to 4 lanes from Monticellosouth about 2 miles e Lane widths and approach widths were modined at several locations throughout the EPZ due to roadway improvements Other than the identined road improvement projects, no other temporary conditions affecting the evacuation network w ere identined.
The updated data collected from these efkrts were coded for input to the NETVAC model. The model,in turn, provides a listing of the evacuation roadway network and O'
v Feld out map in back of report.
1:wwuarwn 1%Ing Netuvrk Page &2 236Himetefinal
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its characteristics. The network listing, presented in Appendix C, describes the d geometric characteristicsof each link in the network. The listing also describes the possible turning movements from each node and the traffic capacity of each link in the network (vehicles per hour that can be accommodated on each link during an '
evacuation). The listing of geometric characteristicsand capacities is prosided by the preprocessor for the NETVAC computer model prior to the actual esacuation simulationcalculations.
l'or the purpose of identincation, and for subsequently calculating evacuation times, the network.has been coded into a system of 153 directionallinks and 149 nodes. l'or modeling purposes,certain intersectionsin the network are designated as nodes where vehicles enter the system. 'lhese " entry" nodes act as surrogates for actual access points (l.c., parking lots, driveways, minor collector roadways) from which the evacuating vehicles originate, in addition, " exit" nodes or "800 series" nodes are designated to reflect points at w hich vehicles leave the defined transportation network.
All other nodes are used to indicate intersection locations The evacuation network w hich was used for computer simulatien is shown in Figure 4.1. This figure shows the location and number codes for each node in the network.
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Dwuathm R<alwgv Networt Page 4 3 23627/metefinal
_~______ _ _ _ _ _ . _ _ _ _ _ _ _ _ _ . _ _ _ . _ -
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- 5. EVACUATION TIME ESTIMATE METHODOLOGY l l
5.1 - Evacuation Analysis Cases l l
l Pursuant to NUREG 0654 guidance, evacuation time estimates have been prepared {
for the area within two miles of the Monticello Nuclear Power Plaat; for various combinations of Subarcas; and for the entire Plume Exposure EPZ. The evacuation i
- areas are discussed in Section 1.3. These evacuation analysis areas represent a [
modi 0 cation from the previous study which used 90 degree quadrants to a key hole j approach to match the cases provided in the emergency plans. l l
Time estimates have been prepared for a general evacuation scenario for each of l these analysis cases for (1) Winter Weekday, Good Weather, (2) Winter Weekday, j Adverse Weather, (3) Winter Weeknight, Good Weather, (4) Winter Wecknight, i Adverse Weather, (5) Summer Weekend, Good Weather, and (6) Summer Weekend, I Adverse Weather. The Winter Wecknight, Adverse Weather scenario was not !
included in the prior ETE study. These analysis cases provide for a range of evacuation times. During an emergency, the case which best approximates the t current condition should be used to determine the anticipated evacuation time, it is important for emergency responders to be familiar with the assumptions used for each analysis.
During a general evacuation, all permanent residents, visitors and seasonal residents of ,
i the affected analysis areas will be instructed to leave the EPZ. The primary means of transportation for evacuation will be the privately-owned vehicles of the evacuees.
Since most residents within the EPZ have access to private vehicles, and since there is l little dependence on public transportation, primary reliance on private vehicles is [
reasonable.
5.2 Initial Notification The EPZ surrounding the Monticello Nuclear Power Plant has an outdoor siren ,
noti 0 cation system consistent with NUREG 0654, Rev.1/ FEMA REP 1 Appendix 3 guidelines. This system will be used by State, County and local of0cials to alert the )
population to turn on their radios and television sets. Pursuant to NUREG 0654, l f
Rev. I guidance, noti 0 cation messages will commence on the designated television and Emergency Alerting System (EAS) radio stations concurrent veith sounding of the sirens. Within 15 minutes of a decision to alert, essentially all the population .
within the EPZ will have begun to receive an informational or instructional message, Notification of exception areas in remote areas is provided by emergency vehicles ,
traveling along pre-determined routesc ,
If evacuation is deemed necessary,the timing of the order to evacuate and notification measures will be controlled by the State, County and local emergency preparedness ;
i Evacuathm Tume Estumate MethoWow I' age 3 1 23627/metefinal a
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omcials. They may choose to alert and mobilire an emergency response work force to cont vl and expedite evacuation prior to the evacuation order.
5.3 Evneustion Preparation Times and Departure Distributions The time estimates developed in this study assume that the clock starts when an evacuation decision is made. It is assumed that no vehicles will begin to evacuate during the 15 minute initial notincation period. It is also assumed that there will be a minimum preparation time of l$ minutes for all population sectors. Accordingly,in the model simulations, no vehicles will begin to evacuate until 30 minutes following the decision to evacuate. Network loading distribution assumptions for the permanent population, transients and special facilities are explained below and summarized in l'igurc S. I .
Permanent andSeawnal Population Permanent and seasonat residents will take varying amounts of time to begin evacuating. Some persons will leave as quickly as possible; most will take some time to prepare, pack valuables and clothes and then depart; some will take added time to secure property before departing; and some may require transportation assistance. In addition, actual departure and preparation times may vary according to the perceived severity of a particular evacuation order.
V ilased upon these factors and discussions with S, ate, County and local emergency preparedness of0cials,it was assumed that there would be a two hour period over which the permanent residents would begin to evacuate. That is, resident households would begin to evacuate between 30 and 150 minutes after the decision was made to evacuate. It was further assumed that 15 percent of the resident population would b; gin to evacuate between 30 and 60 minutes following the evacuation decision,40 percent would begin to evacuate between 60 and 90 minutes, an additional 40 percent would begin to evacuate between 90 and 120 minutes, and the remaining 5 percent w ould begin to evacuate betw een 120 and 150 minutes after the decision to evacuate.
Transient Population it was assumed that the work force would receive initial noti 0 cation promptly. It was also assumed that the majority of the work force would be released expeditiously. This includes the preparation time required for securing businesses and/or shutting down actise operations. Therefore, it was assumed that the work force preparation / mobilization times would be uniformly distributed over a 30 minute period. Discussions with emergency preparedness omcials also indicate that this distribution is also reasonable for the other transient population categories within the EPZ, including hotelvmotelsand campgrounds. Therefore,it was assumed that all ei b
Evxuation Time Estimate Aterhodology Page 3 2 23627/metefinal
the transient population s chicles would begin to evacuate between 30 and 60 minutes following the decision to evacuate.
Special Facilities it was assumed that special facilities (i.e., schools, hospitals, nursing homes, correctional facilities) within the EPZ would also receive initial notincation promptly, Ilased upon discussions with State, County and local emergency preparedness omcials, as well as data obtained frem previous studies, whicle departure timec renecting a notincation/ prepuation/mobilitation time distribution were developed.
Consistent with the current off site emergency response plans, it was assumed that schools will be evacuated via bus to designated reception centers. For school facilities, it was assumed that up to I hour may be required to essemble buses,
'ransport vehicles to schools and to load students onto buses. Vehicles stationed at the facilities at the time of the ordered evacuation could be loaded in as little as 15 minutes following notincation. Accordingly, school buses were loaded onto the evacuation network from the period between 30 and 90 minutes following the decision to evacuate.
Evacuation of hospitals, nursing home facilities and correctional facilities would require additional time associated with preparation and transport of vehicles to the respectise facilities. Ilased upon discussions with County emergency preparedness ofucials, it was assumed that these facilities would begin to evacuate between 1 and 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> following the 15 minute notincation period. Therefore, vehicles (i.e.,
ambulances, vans, etc.) serving these sr ial facilities would begin to evacuate between 75 and 135 minutes following the evacuation decision.
5,4 Evacuation Simulation Evacuations were simulated using the population and vehicle demand distribution data, evacuation network data, and evacuation preparation and departure time distribution assumptions discussed in previous sections. The actual simulated evacuations were performed using the NE1VAC computer model. The following describes the general structure of the NE1YAC model and three of its major features: the dynamic route selection, the priority treatment of How at intersections not having trame signals, and the roadway and intersection capacity calculations.
GeneralStructure The NETVAC program is organized in four basic units (procedures): the main program, the data procedure, the preprocessor, and the simulator. This section L.cuy explains the function of each of these units.
V Evacuatwn Time Estimate Methaiology Page3 3 23627/metefinal
(o) The main program controls the simulation execution. P starts by calling on the data procedure, which reads in the data and the execution instructions, then calls in the preprocessor which perfonns some preliminary capacity calculations. Next, the main program controls the simulation itself and the reporting of the network conditions at speci0ed intervals. This program also controls the rest of the reports and the length of the simulation by terminating the program once the network is empty.
The data procedure reads in the network, the parameters and the options to be used in the simulation. The data procedure performs a set of checks on the network to ensure connectivity and validity, it also performs a set of checks on the input data to identify coding errors. The data procedure also produces a set of warnings if unlikely (but possible) situations are encountered.
The preprocessor procedure converts the physical description of each link into measures of capacity, speed and density. For each specined type of link, the preprocessor computes two types of capacitj:
- Section capacity. the capacity along the link regardless of downstream intersection restrictions; and e Approach ca; acity the capacity of the link to handle vehicles approaching the dow nstream intersection.
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Section capacities are associated with highway sections whereas the trafUc Dow through intersections is controlled by the approach capacity The NETVAC program computes both capacities since they serve ditTerent purposes. 'Ibe section capacity serves as an upper bound on the Dow that can move along a link, restricting the number of vehicles that will reach the intersection during a simulation interval and the number of vehicles that can be loaded onto a link from the intersection. The approach capacity, on the other hand, limits the number of vehicles that can actually move through the intersection. Veh'cles that reach the intersection but cannot move through it are assigned to a queue.
The NET \ AC simulator includes two separate precedures, the link pass and the node paw 1he link pass handles the Dow on the links while the node pass handles the transfer of How from link to link.
Dynamic Route Selection The NETVAC program does not use a pre-specified set of turning movements at each intersection; instead, the turning movements are detennined at each simulation interval as a function of the changing trafDc conditions and directionality of the evacuation links. Drivers approaching an intersection are assumed to make a choice of outbound (away from the intersection) links based on how fast this outbound link
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can get them to safety. This, in turn, is a function of the direction of the outbound links on the network (away from the nuclear plant or hazard area) and the trame conditions on the outbound links i lhe route selection procedure used in the NETVAC program reDeets the two above.
mentioned choice criteria through a user supplied " preference factor" which is speci0ed for each link and the speeds on each of the outbound links. In order to facilitate the explanation of the route choice mechanism, let PFj denote the preference factor for theJ th outbound link at some intersection. In other words, the relative 'a priori' preference of link j is PFj /ILPFk whcre the sum goes over all the links (L's) emanating out of the node under consideration (including j). The choice probability, or the share of drivers choosing an outbound link j out of a given intersection at (simulated) time t, Pj(t), is determined as a function of the preference frctors and the ,peeds on all the outbound links as:
PF)
- U,(t) j P (t) = $ PF,
- U,(t) where U,(t) is the speed on link j at time i 11 should be noted that driver behavior during an evacuation is assumed to be myopo in that only information regarding the immediate outbound links at each intersection is assumed to induence route choice decisions.
The Priority Treatment Even under evacuation conditions, it can be npected that trame approaching an intersection without trame signals from certain links would have the right of way over incoming traf 0c from lower priority approaches. Since it is not clear that such priority would conespond to the existing intersection controls, the input to NETVAC includes a user speci0ed link priority parameter. This is a binary parameter indicating primary or secondary priority of a link.
The volume of vehicles being processed (at every intersection and at each simulation interval) and transferred from inbound to outbound links is subject to several constraints which determine the effective capacity of the intersection. During the simulation, trame entering from all primary priority links is assigned to the intersection Orst, subject only to the intersection capacity constraints. Lower priority trame, on the other hand, is restricted by both the capacity of the
- intersection and the effect of the higher priority trame.
The capacity of the secondary priority appros ;hes is a function of the gap acceptance behavior of the minor approach drivers and se headway distribution in the primary approaches' Dow. In order to model the capacity of secondary priority approaches, a V
Ewcuathm Dme f.mmare AlethoMogy Page3 3 23627/ men: final
capacity allocation problem procedure is utilized. The secondary priority
' approaches emit traffic only under one of the following conditions: first,if there is residual intersection capacity from the primary priority traffic, flow can be emitted into the intersection from the secondary priority road subject to the residual capacity constraint. Second, if the residual capacity is rero, NETVAC provides some small capacity for the lower priority approaches to allow for " sneak in" effects.
Capacity Calculations The capacity of a transportation facility is the maximum flow that can go through the facility. The NE'lYAC program detennines capacity in two stages: first, the preprocessor assigns a section capacity and an approach capacity to each link in the network. Second, approach capacities are updated continuously, throughout the simulation as changing turning movements affect the maximum volume of trafDc processed along each link into its downstream intersection.
The section capacity is calculated in the preprocessor for links with and without physical separation between opposing directions while the approach capacity is calculated as a function of the physical conditions (width, parking, turning pockets, etc.), environmental conditions (area type, peak hour and load factors), trafUc characteristics (trallic mix and percentage of turning movements), and approach type.
The capacity of the i th approach coming into an intersection at simulation interval t.
C,(t)is given by:
C,(t) = C,
- AL(t)* AR(t) where C3 is the standard capacity oflink i calculated by the preprocessor and AL(t) and AR(t) are the correction factors for left and right ;uming movements, respectively. These correction factors are a function of the percentage of turning traffic, the approach width, and parking allowance, and do not apply when the turning trafTic is using special tuming lanes or turning pockets.
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- 6. ANALYSIS OF EVACUATION TIMES _
6.1 Evacuation Time Estimate Summary- !
Evacuation time estimstes for each evacuation analysis case are presented in Table j 6-1. lhese estimates represent the total time for vehicles within the respective areas j to leave the area being evacuated.1he estimates include the time required for ;
notification, preparation and mobilization activities.
The times for al' of the scenarios are very close to each other 1hese times are also._ (
close to the times contained in the previous ETE.1his is an indication that the road 1 i network is adequate to handle the population even with the significant increases in ;
the various population groups. In particular, the modeling of liighway 25 with j multiple lancs in Monticello has decreased the congestion even though the l population increased. !
1he Winter Weekday scenario represents the highest evacuation times with 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />,-
$$ minutes for fair *veather and 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> for adverse weather.1his scenario included 57,939 people, the second highest population of the three scenarios studied. The -[
most significant factor influencing these times is the cumulative effect of the permanent resident, school and work force vehicles using the area roadways and i resultant congestion primarily along liighway 25 from Monticello to IlufTalo. l O The Summer Weekend scenario represents the seccnd highest evacuation times with t
2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />, $$ minutes for fair weather and 3 hours3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> for adverse weather. This scenario included 58,365 people, the highest population of the three scenarios. In general the high recreational population in this scenario is located in areas of low congestion.
The most significant factor influencing these times is the cumulative cliect of the p*manent resident and recreational vehicles using the area roadways and resultant congestion primarily along liighway 25 from Monticello to Iluffalo and in the Maple j
!.ake area.
The Winter Wecknight scenario 1; esents the lowest evacuation times with 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />, 45 minutes for fair weather and 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> 55 minutes for adverse weather. This -
scenario included 44,888 people, the lowest population of the three scenarios. ;
Congestion primarily along liighway 25 from Monticello to lluffalo was the most significant factor influencing the times.
l Analysis qf Emcuation Times Page 6-1 23627/metefinal
r 6,2 Evacuation Times for Specific Evacuation Areas As explained in Section 1.3, evacuation times have been developed for various ,
combinations of Subaress. The following is a discussion of the different cases; j e ' The area around the plant (Subarca 2) has the lowest evacuation times. This area h primarily consists of the Monticello plant and permanent residents. Times for i this r.rea have decreased from the prior study since liighway 25 had been :
modeled as one lane in Monticello. Back.ups into Subarec 2 along County Road l 75 have been climinated, e All scenarios have adequate' road capacity to accommodate the evacuating- j population. The mobilization time assumption requires that the evacuation time be at least 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br />,30 minutes plus drive time out of the evacuating area. Times l that . re in this range are not impacted by congestion. l
- Scenarios which include the City of fluffalo are impacted by congestion in the !
vicimty of the city. This includes the population coming down liighway 25 [
from the scuth side of Monticello. This impacts the times for all cases with j Subarca 10S, These have the highest times of all the analysis cases.
t
- No congestion was observed in Sherburne County for any of the scenarios.
6.3 Evacuation Times for Combinations of Evacuation Areas Evacuation travel times for evacuating all persons within partial EPZ evacuation areas not analyzed in this study may be estimated by using a combination of the evacuation areas. In order to estimate the evacuation travel time for such an area, a ,
combination of evacuation areas which cover, but do not extend beyond the area in question, must be identified (they may overlap). The longest time for any of the individual evacuation areas included is the evacuation time. For example, if the wind is coming from 335 and it was decided to evacuate the 5 mile radius and out to ;
10-miles in the downwind direction, the times for both the 5 mile radius (case 34) and the 2 mile radius and out to 10 miles (case 33) should be reviewed. In this example the Winter Weekday time for case 34 is 2:35 and for case 33 the time is ,
2:55. Therefore, the time foi evacuating both areas is 2:55, the highest time for the !
overlapping areas.
- 6.4 Queuing Locations ,
i As the result of road capacity limitations, queuing may occur at a number of locations in the plume exposure pathway Ep2 during an evacuation. Queuing results
- when the vehicles reach an intersection along the network and cannot move through !
it due to a restricted approach capacity which limits the number of vehicles that can !
actually move through the intersection. Tbus, ii'a venicle .nust wait to move through l Analpis ofEvacuatwn Dmes Page 6 2 23627/metefinal l
i
, , , - . _______, _, _ _ . - ~ . , _ - _ . - . _ _ , _ _ _ _ _ _ . . - . - _ _
an intersection, it is assigned to a queue by the NETVAC program. The extent to
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V which a roadway queue can be impacted either fasorably or adsersely by weather conditions depends on the specine traf0c conditions causing the queue. For example, a roadway may experience less queuing during adverse weather if the conditions result in cars moving slower behind the queued roadway, resulting in less back up.1.ikewise, some roadways may experience more queuing under adverse conditions if volumes are high enough that the slewing of trafnc behina the queue is not sumcient to alkviate the backup.
Tl e following areas have been identified as areas where queuing is likely to occur during an evacuation:
e Vehicles exiting the City of Monticello result in several queuing locations.
locations impacted by this population include:
- The entrance to Interstate 94 including the eastbound on ramp.
- Queuing is also obsen ed back into Monticello during the weekday case only along liighway 25 and the intersections with Fourth Street and County Road 75.
- Vehicles attempting to exit through the City of 11utTalo cause long queues back up liighway 25 from the intersection with liighway 55.
i'
. Within lluffalo traf0c merging onto liighway 55 at 8* Street NE also causes congestion.
- During the summer weekend scenario, congestion is apparent in Mcple Lake at thejunction of County Road 8 with liighway 55.
- Some congestion is observed at the Monticello plant entrance road primarily during the weckday scenario.
These areas of queuing were considered in the recommendations included in Section 7.2.
C\
U Analysis of bacuation nmes Page 6-3 2362hmetefinal
Table bli b acuation Time Dtimmtes l isevation Time thours:minuteill3 Wind Direction I tarustion Aren %ister Day W6mter Sight bommer % rekend Case idegrees from) king Domemand but> areas f air Adietse init Adterne f air Adierte 1 2elle 2 2,25 2 25 2 25 2.25 2.25 2.25 2 348 75 11.25 2ede & 5 mile 2,55. S W 2 35 2 45 235 2 40 235 2.40 3 2 mile A 10eile 2, $$. SW,1050, IOS.10SW 2 55 3 00 2 40 2 50 2 50 3 00 4 11.25 33 75 2eile & 5-mile 2, $$. SW 235 2 45 235 2 40 2JS 2 40 5 2eile & 10-mile 2. 55, S W, IDS.10SW,10W 2 55 3 00 . 2.40 . 2 50 2 50 3 00 6 3175 5625 2-milc & 5 mile 2, 5 5, S W 235 2 45 2 JS 2 40 235 2 40 l
7 2. mile & 10-mile 2. 55. $W,105,10$W,10W 2 55 3.00 2 40 2 50 2 50 3 00 l
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8 5625 78 75 2-mile & 5 mile 2, $$. S W 2 35 2 45 2 35 2 40 235 .2 40 9 2 mile & theile 2, SS, SW,10SW, IDW 2 40 2.45 40 2 45 2 40 2 45 10 78 75 101.25 2 mile & Selle 2,5 W 2.35 2.40 235 2.40 235 2 35 i 11 2elle & 10 mile 2, SW, IDSW, IDW,10NW 2 40 2 45 2 40 2.45 2 40 2 45 12 101.25 123 75 2 mile & 5 mile 2,SW,$N 235 2 40 2.35 2 40 235 2 40 13 2 mile & lheile - 2, S W. 5N,10W.10NW 2 40 2:45 2 40- 2 45 2 40 2 45 ;
d 14 123.75 186 25 2 inile & Selle 2,SW,$N 2 35 2 40 235 2 40 235 2 40 15 2 mile & 10-mile 2, S W, SN,10W,10NW,10N 2 40 2 45 2 40 2 45 2 40 2 45 i- 16 146 25 168 75 2-mile & 5-mile 2,SW.5N 235 2 40 2 35 2 40 2 35 2 40 17 2este & lo-mile 2, SW, SN,10NW,10N 2 35 2 45 2 35 2 45 2 35 2 40 18 168 75 191.25 2 mile & 5-mile 2, $N 235 2 40 2 35 2 40 2 35 2 40 19 2-mile & 10-mile 2, $N,10NW,10N 10I: 2 45 2 SS 2 45 2.55 2 45 2 50 20 191.25 213.75 2 mile & 5 mde 2,$N,SE 2.35 2 40 235 2 40 2 35 2 40 21 2-mile & 10 mile 2,$N,51;10N 100 2 45 2 55 2 45 2.55 2 45 2 50 22 213 75 236.25 2eile & 5 mile 2, $N St. 235 2 40 235 2 40 2.35 2.40 23 2 mile & 10-mile 2, SN,50.10N 10! 2 45 2.55 2 45 2 55 2 45 2.50 24 236 25-258 75 2 mile & 5-mile 2,$N,SE 235 2 40 235 2 40 2 35 2 40 25 2eiie & 10-mile 2,$N,SI 100 2 45 2:55 2 45 2.55 2.45 2.50 26 258 75 281.25 2 mile & 5-mile 2,51; SS 235 2.45 2:35 2 40 2 35 2 40 27 2-mile & 10-mile 2,51; $$,101.,1050 2.45 2.55 2 45 2.55 2 45 2 50 28 281.25 303.75 2eile & 5 tmle 2,50.SS 235 2 45 2 35 2 40 235 2 40 29 2eile & lo mile 2,SE,55,1050 235 2.45 235 2 40 2 35 2 40 30 303.75 326.25 2-mile & 3-mile 2,50,SS 2.35 2 45 235 2 40 2 35 2 40 31 2 m61e & 10eile 2,50.55,10Sl;105 2.55 3 00 2 40 2:50 2 50 3 00 32 320 25 348 75 2eile & 5-mile 2, $$ 2 35 2 45 2 35 2 40 235 235 33 2 mile & 10-m6te 2,SS,1050,105 . 2.55 3 00 2 40 230 2 50 3 00 34 5 mile 2, SN,51,55, SW 2 35 2 45 2.35 2.40 235 2 40 35 10-mile I ull I11 2.55 3 00 2 45 2 55 150 3 00 l
33 la order to estunais the evacuation ume for perual EPZ cases not included stute, driermme the combmation of cases which cover Ivt do cut csecrsi twyorst the area in question (they may overlapt The lorgest ume for any of the iruhsmiual evacuanon areas as (tw esecuauon hme, oce Secton 6 3 for an enample)
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Analyste ofhocuation Dmes l' age 6-4 23627/metefinal
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- 7. SUPPLEMENTAL ANAINSIS L
7,1 Evacuation Confirmation !
I ConGrmation of the evacuation is performed to assure that the entire population that !
desires to c"acuate has been notified and left the area, and to assist those persons !
having dif0culties in evacuating. Several candidate methods for performing the con 0rmation process may include:
- 1. A sampling approach, where a sample of ti c tmal households would be ,
contacted, generally by way of telephone calls, to .. rify notification.
- 2. 'the use of vehicles passing through the plume exposure pathway EPZ along planned routes, visually inspecting whether evacuation has occurred t
- 3. The use of a placard placed on the front of the door afler evacuating. This would aid in the vehicle inspection msthod outlined in (2), above.
Method 2 has the advantage of allowing assistana to be rendered immediately, whereas Method I would require the dispatch of .dditional personnel to render ,
asdtance. Although Mcthod 3 is used in some EPZs, it has the disadvantage of ,
identifying empty houses to potential kmters. It is recommended that the vehicle inspection method (2) be considered.
The actual time associated with the con 0rmation process would depend on both the number of personnel and the amount of equipment available. These resources may change signincantly under various emergency conditions. Nevertheless, with the use of Method 2 it is anticipated that the con 0rmation process could be completed for the entire Monticello EpZ within approximately four hours.
7,2 _ Evacuation Management Points and Other Potential Mitigating Measures The NETVAC simulation model output was examined in detail to identify key intersection locations where vehicle queuing and delays may warrant traf0c management during the course of an evacuation. The locations of vehicle queuing, or congestion, which wouid be anticipated during an evacuation have been discussed in Section 6 4, for evacuation of all areas within the EPZ.
i The network and evacuation times for each of the evacuation scenarios hage been further reviewed to determine which hwations, if any, would beneGt from the
- utilization of traf0c management. Eight (8) potential management points have been
- identined for the Monticello EPZ as shown on Figure 71. These points are listed in Table 7 1. The following is a discussion of each traffic management point:
l Syplemental Ana& sis Page 7 i 23627/metefinal
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I Located at Node 65. Traf0c management personnel should
' aid vehicles entering the Interstate 94 eastbound on ramp.
2 Located at Node 66. TrafGe managt; ment personnel should aid vehicles enter Interstate 94 frem the on ramp.
3, 4 Located at Nodes 64 and 63. Traf0c management persunel should aid vehicles merge onto liighway 25. These locations are primarily required for the weekday scenario.
5 Located at Node 4 7. TrafDe management personnel should in; prove green time allecation. The highest number of vehicles can be expected coming south on liighway 25.
6 Located at Node 49. Traf0c management personnel should improve green time allocation and assist vehicles merge onto liighway 55.
7 Located at Node 33. TrafGe management personnel should aid merging vehicles. This location is required primarily in the summer scenarios.
- 8' Located at Node 2. Traf0c management personnel should aid vchicles exiting from the Monticello plant onto Coumy Road 75. This location is primerily required during the weekday scenario.
The responsibility for both trafnc control and access control during an evacuation of the Montictilo EPZ will be the shared responsibility of State, County and local emergency services and law enforcement personnel, as available. The traffic and access control polat locations for the Monticello EPZ are identified in the County plans and procedures.
Traffic management personnel at these key locations would reduce the number of vehicle conflicts and promote more progressive movement through the area. He traf6c management personnel would also act to instill confidence in evacuees by directing evacuating traffic in the most efficient manner possible, and by being available to respend to unpredictah's or changing events.
The assignment of trafGc management personnel at the locations addressed in Section 6-4 are also helpful in improving traffic Dow by giving higher priority to vehicles on the assigned evacuation routes and lower priority to competing movements. It is assumed that trafnc management personnel at these points will
,s dictate traf6c flows and signals will be overridden when necessary to maintain
) traffic flow, (J
w Supplemental Ana& sis Page 7-2 T3627/metefinal
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- Table 71: Recommended Trame Management Locatione Location Number . Description 1 liighway 25 and' the entrance to the 194 castbound on ramp
'2 Eastbound on ramp and I 94
.3 liighway 25 and Fourth Street 4 liighway 25 and County Road 75 5 liighway 25 and liighway 55 6 1-lighway 55 and 8* Street NE 7 niighway 8 and liighway 55 8 Plant Access Road and County Road 75 t
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Supplemenf L4nalysis Page 7 23627hnetefinal i-aw w -. - -
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Appendix A Transient and Special Facility Population Data O
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/
Tr:nstant Workforce Population and Vehicle Demand Estimates Population Vehicle
- Winter Winter Summer Winter %"mter Summer No. Municipality - Facility name Sector Distance Direction Sub-Area Day Night Weekend Day Night ' Weekend Node Sherburne C9.mty WI Becker Becker Furniture World R 3-4 NNW SN 50 34 45 50 34' 45 75 W2 Decker Becker Truss Inc. R 3-4 NNW ?N 35 15 0 35 15 0 75 W3 Big Lake Remmele Engineering (Piant #30) E 5-6 E SE 60- 30 10 60 30 10 102 W4- ' Big Lake Shelburne Co. Telephone E 5-6 E SE 44 3 3 44 3 3- 102 W5 Becker Decorative Services Inc. A 8-9 N SN 40 0 0 40 0- 0 87 W29- Becker Shelburne Co. Plant Q 3-4 NW SN 425 150 75 340 120 60 75 Wright County W6 Monticello Sunny Fresh Foods G 3-4 SE SS 250 250 250 250 250 250 64 W7 Monticello Fulfillment Systems G 3-4 SE SS 100 10 0' 100 10 0 66 W8 Monticello Fingerhut Corp. G 3-4 SE SS 100 75 30 100 75 30 65 W9 Monticello 's he Il-Window Ccmpany G 3-4 SE SS 55 0 0 55 0 0 126 W10 Monticello Tappers Inc. G 3-4 SE SS 30 20 30 30 20 30 65 WII Monticello Remmele Engineering (Plant #20) G 3-4 SE SS 52 20 8 52 20 8 65 W12 Meticello K-Mart G 3-4 SE SS 130 100 130 130 100 130 66 Wl3 Monticello Maus Foods G 3-4 SE SS 150 150 150 150 150 ISO 64 Wl4 Monticello Standard Iron and Wireworks Inc. G 4-5 SE SS 95 95 95 95 95 95 54 WIS Monticello lloglund. Transportation Inc. G 4-5 SE SS 73 . 0 0 73 0 0 54 W16 Monticello Bondbus Corp. G 3-1 SE SS 60 60 60 60 60 60 68 Wl7 Monticello A.M.E G 5-6 SE SS 17 .0 2 17 0 2 54 W18 Buffalo Von Bridam Msg. J 10+ S 105 45 15 0 45 15 0 49 Wl9 BufD,a Whiritronics Inc. J 10' S 105 55 55 55 55 55 55 - 50 W20 Buffalo Wal-Mart J 10+ S 10S 214 214 214 214 '214 214 47 W21 Buffalo Universal Circuits J 10+ S 10S 105 105 105 105 105 105 50 W22 Buffalo Buffalo Bituminous inc. J 10+ S IOS 5 0 0 5 0 0 50 W23 BulTalo Target J 10+ S 105 50 50 85 50 50 85 50 W24 BufTalo Buffalo Veneer & Plywood Co. J 10+ S _10S 47 4 0 47 4 0 51 W25 Buffalo Econofoods
- J 9-10 S 105 50 50 30 50 50 30 49 W26 Monticello Electro Industries G I-2 SE 2 47 0 0 47 0 0 58 W27 Monticello Monticello Generating Station -
0-1 -
2 600 '200 200 480 160 160- I W28 Monticello Marquette Bank G 3-4 SE SS 26 8 5 26 8 5 64 l Total 3.010 1.713 1,582 2.805 1.643 f.527 l A-1 A1 Tables.xis
m, ~
. j ., .
l
\_-)
A t . Trcnsient Workforce Population rad Vehicle Demand Estimates Notes :
- 1) Population based on telephone survey by Earth Tech in July-September,1997.
- 2) Vehicle demand based on 1.25 persons / vehicle at the Monticello and Sherburne County Plants and 1 person /sehicle at other facilities.
- 3) Node refers to point ofentry onto the evacuation roadway network.
l i
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E i
i I
i A-2 blTables31s
u x> V Transient Recreational Population and Vehicle Demand Estinistes Population . Vehicle Winter Wints Summer Winter Winter . Summer No. Municipality Facility name ' Sector Distance Direction Sub-Area Sites Day Night Weektml Day Night Weekend Node Shelburne County R1 Big Lake Shady River Campgrounds C 5-6 NE SE .I15 0 'O 460 0 0- 115 107 R2 Big Lake flarty's Place C 5-6 NE SE 15 0 0 60 0 0 15 .105 R3 Big Lake Carefree Coun ry Club E 9-10 E SE 400 2 2 1600 1 I -400 116 R4 Big Lake Big Oaks Campground F 2-3 ESE 2 40 5 5 170 2- 2 43 73 R5 Big Lake All Serssons Campground -E 5 's E SE 300 0 0 1200 0 0 300 _100 R6 Clear Lake Travelers Country Club of Clear Lake Q 10+ NW 10NW 200 0 0 800 0 0 200_ 82 R7 Clear take Travelers Country Club of Mississippi P 8-9 WNW 10NW 299 0 0 11 % 0 0 299 78 R8 Becker Pebble Creek Country Club R 4-5 NNW SN - 8 8 560 8 8- 280 125 Wright County R9 Monticello Silver Springs Golf Course 11 2-3 SSE 5S - 2 0 215 2 0 107 65 R10 . Silver Lake Olson Campground M 6-7 WSW SW 85 2 2 562 I I 142 22 Ril Silver Lake Lake Maria State Park M I,-5 WSW SW - 100 0 150 40 0 60 23 l Total 1,454 I19 17 6.973' 54 12 1,961 l Notes :
- 1) Population based on telephone survey by Earth Tech in July-September,1997; includes patientfresidents and staff.
- 2) Population based on 4 persons / campsite at campgrounds.
- 3) Vehicle demand based on one vehicle / campsite.
- 4) Node refers to point of entry onto the evacuation roadway network. ,
A-3 MTablesaris
- p. ,. -m
\
' Transient flotel, Trailer Park and Shopping Center Population and Vehicle Demand Estimate Population Vehicle Winter Winter Summer Winter Winter Summer No. Municipality Facility name Sector Distance Direction Sub-Area Rooms Day Night Weekend Day Night Weekend Node Shelbume County TI Big Lake Super 8 (Strawbeny Motel) E 4-5 E SE 32 53 53 54 32 32 32 101 12 Big Lake Lake Aire Motel E 4-5 E SE 4 7 7 7 4 4 4 .101 T3 Big Lake Big Lake Estates D 4-5 ENE SE 124 251 250 251 127 126 127 94 T4 Becker Pine Ridge Coun R 4-5 NNW SN 40 82 82 82 42 42 42 122 Wright County T5 BulTalo Super 8 Motel of ButTalo J 10+ S 10S 32 56 49 56 32 32 32 49 T6 BufTalo Country Inn by Carlson-Buffalo J 10+ S 10S 50 82 76 87 50 50 50 49 T7 Buffalo Buffalo llotel J 10+ S 19S 18 28 28 28 18 18 18 49 T8 Monticello Americinn Motel G 3-4 SE SS 30 51 51 55 30 30 30 65 T9 Monticello Best Western Silver Fox G 3-4 SE SS 70 105 105 105 70 70 70 65 T10 Monticello Comfort inn G 3-1 SE SS 33 53 52 56 33 33 33 126 l Total 769 753 781 438 437 438 l Notes : i
- 1) Population based on telephone survey by Eanh Tech in July-Septernber,1997.
- 2) Population based on 1.5 persons per room / trailer
- 3) Vehicle demand based on one vehicle per unit at hotel' trailer puk
- 4) Node refers to point of entry onto the vacuation roadway network.
A-4 AiTables.xis
Special Facilities Schools Population and Vehicle Demand Estimate Population . Vehicle Wimer Winter . Summer Wntr. Day Wntr. Nght Smr. Wknd Re. . Municipality Facility name Sector Distance Direction Sub-Area Day Nigist Weekend Buses Cars Buses Cars Buses Cars Node Sherbume County Si Becker Becker Elementary R 4-5 NNW SN 725 30 0 11 75 0 15 0 0 122 S2 Becker Becker liigh School R 4-5 NNW SN 1205 0 0 19 100 'O O O O 122 S3 Big Lake Big Lake Elementary E 5-6 E SE 935 0 0 15 85 0 0 0 0 102 S4 Big Lake Big Lake liigh School E 5-6 E SE $90 0 0 9 50 0 0 0 0 102 ,
I SS Big Lake Big Lake Middle School E 5-6 E SE 690 0 0 11 50 0 0 0 .O. 102 S14 Big Lake Rivercrest Christian School F 3-4 ESE SE 50 0 0 1 7 0 0 0 0 97 Wright County S7 Buffalo Buffalo intermediate J 9-10 S 10S 739 0 0 11 90 0 0 0 0 47 S8 Buffalo Buffalo liigh School J 10+ S 10S 1255 0 0 20 100 0 0 0 0 47 S9 . Monticello Linie Mountain Elementary G 4-5 SE SS 780 0 0 12 70 0 0 0 0 65 S10 Maple Lake Maple Lake fligh & Elementary L 10+ SW 10SW I100 0 0 17 100 0 0- 0 0 33 SI1 Monticello Monticello liigh School G 3-4 SE SS 1110 0 0 17 I10 0 0 0 0 69 S12 Monticello Monticello Middle School G 3-4 SE SS 975 0 0 15 75 0 0 0 0 . 65 S13 Monticello Pinewood Elementary G 2-3 SE 2 1175 0 0 19 75 0 0 0 0 69 SIS Maple Lake St. Timothy's Catholic School L 10+ SW 10SW 84 0 0 2 14 0 0 0. 0 33 S16 BulTalo Wright Technical Center J 9-10 S 10S 318 65 0 5 38 0 65 0- 0 46 l Total 11,731 95 0 184 1.039 0 80 0 0 l Notes :
- 1) Population based on telephone survey by Earth Tech in September,1997.
- 2) Vehic!c demand based on 60 students / bus and I stafT/ vehicle during school hours and I person / vehicle for evening classes;
- 3) Node refers to point of entry onto the evacuation roadway network.
A-5 A(Tables.. tis ,
V: % - %/
Special Facilities Medical and Incarceration Facilities Population and Vehicle Demand Estimate 1
Population Vehicle Winter Winter Summer Winter Winter Summer Re. Municipality Facility name Sector Distance Direction Sub-Area Amb. Day Night Weekend Day Night Weekend Node Wright County til BufTalo BufTalo ilospital J 9-10 S IOS 2 190 190 165 144 144 119 48 116 Monticello Monticello-Big Lake llospital G 3-4 SE SS 3 30 30 30 60 60 50 70 117 Monticello Mississippi Shores Retirement flousing G 4-5 SE SS 1 Bus 49 49 49 12 12 12 71 118 Monticello Monticello-Big Lake Nursing flome G 3-4 SE SS -
91 91 91 163 163 163 67 l Total 360 360 335 379 379 344 l Notes :
- 1) Population based on telephone survey by Earth Tech in July-September,1997; includes patients / residents and staff.
- 2) Vehicle demand based on county provided numbers.
- 3) Node refers to point of entry onto the evacuation roadway network.
A-6 MTables.xis
I
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Appendix B :
Permanent Population Assignments O
O
ar%
4 ) Permanent Population Assignments
-Q f Cespuni t F M ggg Qggj {fg,jg ) ComuRW),jg g {gg Qggg ggdg )
- Becker 1 50, 3.3 los 499. Sant l igo 1 217, 3.3 91 100.
Becker '1 15. 3.3 107 100. Santiago 1 91. 3.3 96 100.
Becker 1 15. 3.3 122 100. ElkRio ar 1 14. 2.9 114 100.
Becker 1 104. 3.3 123 100. Elkkives 3 34. 2.9 116 100.
Becker 1 102. 3.3 125 100. Monticle 1 795. 3.0 120 100.
Becker 1 180. 3.3 73 100. Monticlo 1 557, 3.0 124 100.
Becker 1 264. 3.3 14 *00. Monticio 1 717 3.0 126 200.
Becker 1 66. 3.3 71 i 1 Monticlo 1 1249. 3.0 2 100.
Becker 1 692. 3.3 76 100. Monticlo 1 313, 3.0 3 100.
Becka r - 1 280. 3.3 77 lt 0. Monticlo 1 1152. 3.0 34 100.
Becker 1 175. 3.3 79 p. Montielo 1 167. 3.0 39 100.
Becker 1 176 3.3 to 100. Monticlo 1 306. 3.0 4 100.
Becker 1 65. 3.3 83 100. Monticlo 1 108, 3.0 40 100.
Becken 1 176. 3.3 85 100. Monticlo 1 56. 3.0 41 100.
Becker 1 229. 3.3 06 100. Monticlo 1 43. 3.0 42 100.
Becker 1 77 3.3 67 100. Monticlo 1 15. 3.0 5 100.
Becker 1 260. 3.3 to 100. Monticio 1 79. 3.0 52 100.
Secker 1 735. 3.3 89 100. Monticlo 1 90 3.0 54 100.
Becker 1 113, 3.3 to 100. Monticle 1 491. 3.0 55 100.
- Becker 1 51. 3.3 91 100. Monticlo 1 13(. 3.0 56 100.
Becker 1 232. 3.3 92 100. Monti.'.o 1 33, 3.0 57 100.
becker 1 674 3.3 95 100. Monticlo 1 195. 3.0 54 100.
- Becker 1 127. 3.3 96 100. Monticlo 1 303. 3.0 59 100.
BigLake 1 425. 3.0 100 100. Monticlo 1 860. 3.0 60 100.
BigLak e 1 668 3.0 101 100. Monticlo 1 435. 3.0 61 100.
Bigtake 1 911. 3.0 102 100 Monticlo 1 252. 3.0 62 100.
BigLake 1 180. 3.0 103 100. Monticlo 1 102, 3.0 63 200.
BigLake 1 115. 3.0 1 04 100. Monticlo 1 1066. 3.0 64 100.
Big Lake 1 33. 3.0 105 100. Monticlo 1 268. 3.0 67 100.
B1g Lake 1 20. 3.0 108 100. Monticlo 1 199 3.0 65 100.
BigLake 1 St. 3.t 109 100. Monticlo 1 124. 3.0 69 100.
BigLake 1 342. 3.0 111 10' Monticlo 1 137 3.0 70 100.
% Bigbake 1 003. 3.0 112 100. Monticlo 1 298. 3.0 127 200.
Bigbake 1 237. 3.0 113 100. Buffalo 1 26, 2.9 40 100.
g BigLake i 102. 3.0 114 100. Buffalo 1 461. 2.9 42 100.
/
U Biglake 1 101. 3.0 115 100. Buffalo 1 549 2.9 43 100.
Big Lak e 1 1981. 3.0 116 100. Buffalo 1 8. 2.9 44 100.
Big Lake 1 433. 3.0 117 100. Buffalo 1 331. 2.9 45 100, Big Lak e 1 596. 3.0 lie 100. Buffalo 1 511, 2.9 46 100.
Big Lake 1 52. 3.0 119 100. Buffalo 1 185. 2.9 47 100.
BigLake 1 257. 3.0 123 100. Buffalo 1 745. 2.9 48 100.
Big Lake 1 67 3.0 72 100. Buffalo 1 927 2.9 4* 100.
BigLake 1 95. 3.0 73 100. Buffalo 1 423. 2.9 'O 100.
Big Lake 1 4 3.0 89 100. Buffalo 1 115. 7.9 El 100.
BigLake 1 43, 3.0 92 100. Buffalo 1 111, 2 52 100.
BigLake 1 178. 3.0 93 100. Buffalo 1 224. 2.9 53 100.
BigLake 1 560. 3,0 94 100. C1rwater 1 512. 3.0 10 100.
Big Lake 1 70. 3.0 97 200. Chrwater 1 192. 3.0 11 100.
Big Lak e 1 013. 3,0 98 100. Ctrwater 1 79. 3.0 12 100.
BigLake 1 324. .1. 0 99 100. Clrwater 1 94. 3.0 16 100.
Ci r Lake 1 76. 3.0 77 100. Ctrwater 1 63. 3.0 17 100.
C1rtake 1 121. 3.0 78 100. C1rvater 1 90. 3.0 19 100.
Ci r Lake 1 60. 3.0 to 100. Clrwater 1 170. 3.0 36 100.
ClrLake 1 181. 3.0 81 100. Cirwater 1 14, 3.0 7 100.
C1 Lake 1 92. 3.0 82 100. Cirwater 1 208. 3.0 8 100.
C1 Lake 1 130. 3.0 83 100. Ctrwater 1 111. 3.0 9 200.
ClrLake 1 37. 3,0 85 100 Corinna 1 118. 2.s 16 100.
CarLake 1 10. 3.0 a6 100. Corinna 1 72, 2.0 20 100.
Orrock 1 227. 3.1 105 100. Corinna 1 50. 2.8 32 130.
Orrock 1 J64. 3.1 107 100. Corinna 3 343. 2.8 36 100.
Orrock 1 301. 3.1 104 100. Corinna 1 168. 2.8 37 200.
Ottock 1 334. 3.1 109 100. Frnkfort 1 76. 3.4 53 100.
Orrock 1 4. 3.1 110 100. Frnkfort 1 16, 3.4 56 100.
Orrock 1 30, 3.1 113 100. Frnkfort 1 298. 3.4 57 100.
Ottock 1 261. 3.1 114 100. MpleLake 1 21. 29 124 100.
Orrock 1 2?8. 3.1 119 100. MpleLake 1 15. 2.9 23 100.
Orrock 1 23. 3.1 123 100. MpleLake 1 4. 2.9 24 100.
Ortock 1 46. 3.1 95 100. MpleLake 1 8. 2.9 25 100.
Otrock 1 17 3.1 94 100.' Mplebake 1 14. 2.9 27 100.
Palmer 1 14. 3.0 83 100. MpleLau 1 10, 2.9 28 100.
[ Palmer 1 414 3.0 85 200. MpleLake 1 109 2.9 30 100.
( Palmer 3.0 91 100. MpleLake 430. 2.9 31 100.
/ 1 .3. 1
%d Permanent Population B-l 23627/metefinal
lf'~'N ' pyyg '
( Cceannitv Ig1), [,gg ff01g . 1._
'\
'MpleLake 1 1159, 2.9 32 .-100.
Mpl eLeke -. 1 249 2.9 . 33 200.
. MpleLake l' .484, 2.9 35 100.-
Mplebake 1 1, 2.9 36 100.
Mplebeke 1- -362. 2.9 40-100.
MpleLake 1- 418, 2.9 44 100.
MpleLake 1 '1522 2.9 4% 100.
MpleLake .1 10. 2.9 46 100. 4 Otetgo 1 391. 3.3 120 100.
Otsego 1 391. 3.3 121 100.
Otsego_ -1 22. 3. 3 _ 56 100.
Dr.eego 1 196. 3.3 $7 100.
. 81vrCrok 1 - 54, 3.0 12 100.
81vrCrok 1 209. 3.0 124 100.
SlvrCrok 1 36. 3.0 *4 100.
51vrCrok 1 188. 3.0 21 100.
SlvrCrok - 1 170. 4.0 22 100.
81vrCrek 1 434. 3.0 23 100.
SavrCrok 1 151, 3.0 24 100.
81vrCrok 1 69. 3.0 25 100.
81vrCrok 1 44, 3.0 26 100.
81vrCrok 1 8. 3.0 28 100.
81vrCrek 1 15. 3.0 29 100.
81ercrek != 53. 3.0 30 100.
81vrCrok 1 44. 3.0 4 100.
81vrCrok 1 9. 3.0 40 100.
81vrCrok 1 '335. 3.0 5 100.
51vrCrok 1 239. 3.0 6 100.
81vrCrok - 1 li t > 3.0 7 100.
51vrCrok .1 16, 3.0 8. 100, null 1 1. 3.0 10 100.
Seasonal Population A
( ) Becker 1 24, 3.3 to 100.
- SigLake 1 102. 3.0 98 100.
j/
BigLake. 1 300. 3.0 103 100.
BigLake 1 205, 3.0 104 100.
310 Lake 1 211. 3.0 114 100.
ClearLak 1 264. 3.0 53 100.
Orrock 1 .540, 3.1 105 100.
Ortock 1 61. 3.1 107 100.
Otrock 1 154. 3.1 119 100.
Palmer 1 59, 3.0 84 100.
' Santiago 1 7. 3.3 91' 100.
Buttato 1 147 2.9 42 100.
Buttato 1 3*0. 2.9 43 100.
Buttano 1 84, 2.9 50 100.
ClearWtr 1 203. 3+0 0 100, ClearWtr 1 230. 3.0 . 16 100.
ClearWtr 1 49, 3.0 9 100.
Corinna 1 929. 2.8 16 100.
Corinna 1 159. 2.8 20 100.
Corinna- 1 467. 2.8 37 100.
. Frankf or 1 -13. 3.4 57 100.
Maplelak 1 94 <. 2.9 40 100.
Maplelak 1 69. 2.9 -44 100.
Map 1elak 1 $49, 2.9 31 100.
Maplelak 1 190. 2.9 32 100.
Montical 1 32. 3.0 127 100.
Monticel 1 124. 3.0 124 700.
Oatego 1 6. 3.3 121 100.
SilverCr 1 141 3.0 23 100.
SlaverCr 1 117. 3.0 24 100.
SilverCr 1 44. 3.0 26 100.
. SlaverCr 1 40). 3.0 22 100, SilverCr 1 81, 3.0 7 200.
- f 1
.4 V
~. Permanent Population . B-2 2368/metefinal M
s.
Appendix C Roadway Network Listing and Capacities from NETVAC l0 o
O v
Network Listing L1rp F9s To Lsu As Le #5 L FB LT AT Pt SFD Jan Fat FCAP STS stLT CAF BGT $ PLT CAP LFT SPLT CAD 1>1A0 BFLT CAP 1 -1 2 1128, 17, 10, 6. 1 1 7 4 F 44. Ill. 1 00 1780. 0 00 2000 3 .00 6. la .00 0 0 00 0 2 3 3 800. 13, 13 6. 1 1 7 4 F $0 179 50 2000 4 00 1624, 0 .00 c. 0 .00 C. 0 .00 9 3 14 8800. St. 13. 6. 1 1 1 4 7 10. 191, 50 3000. 40 .00 1736, 0 .00 0. 0 00 0. 0 .00 6 4 3 4 14049. 13. 12. 4. I 1 7 4 F 60.149.1.00 2000 - 5 00 1624. 0 00 C. 0 00 c. 0 00 9.
$ 4 6 7049 12. 12. 6. 1 1 7 4 F 60. 149. 1 00 2000. 6 -00 telt. D 00 0. 0 .00 c. 0 .00 0, 4 5 6 5400. 13 < 13, 6. 1 1 7 4 F 60. 149. 1.00 2000. ? 00 1624. 0 00 4. 0 .to 0. 0 .00 6.
7 6 7 1940, 13. 12. 6. 1 1-1 4 F $0. 149 1.00 2000. 4 09 1624. 0 04 0 12 .00 0 0 00 C.
G 1 il 600. 12 12 6. 1 1 7 4 F ll . 163 .30 2000. 0 00 1634. 13 00 0 0 .00 C. 0 .07 0, 9 8 10949. 13, 1J. 4. 1 1 7 4 F S0. 179, 50 2000. 9 00 1634. 0 00 6. 0 00 4. 0 00 0-to 8 9 IT160. 13. 12. 6. 1 1 7 4 F 10. 179. 1.00 2004, 10 .e6 1624 0 .00 6. t .00 0. 0 .00 6.
11 9 10 3620, 34, 13 6. 1 1 7 e F 40. 224 ,90 2000- $14 .00 2050 0 00 0 14 00 6 0 .00 9 12 11 3530. 10. 10, 1 I 1 7 4 F 301 224 .10 1600. 314 .00 1400 0 .00 0. 0 .00 9. 0 .00 9 il 10 14 1740. 12. 12. 6. 1 1 7 4 F 30. 299. .30 2000 0 .00 1614 0 .00 6. O .00 8. Il .00 16.4 34 814 3120. 20= 13. 6. 1 1 7 3 F 30. 399 .90 2000, 0 ,00 2000 0 00 9. 0 =00 0, 0 .00 v-Il 11 416 .'52 0 : 12 13. 6 1 1 7 3 F 10. 399. 1.00 2000 0 .00 1634. 0 00 C. 0 .00 6. 0 .00 0.
16 12 13 1120. 18. 14 4. I 1 1 1 F 30 243 ,90 3000. 0 .00 1700. 0 .00 6. 0 00 4. It 00 1900-17 21 12)20. II. St. 6. I 1 7 4 F ll. 163. .10 3000. 22 ,00 1624. 0 .00 0 9 .00 C. 0 .00 0.
14 13 35 37200. 34. 12, 4. 2 1 0 4 F ll. 145 1.00 2000. 4tt .00 2000, 0 .00 0, 0 .00 9. 0 .00 0.
19 14 14 1320, 18 14 6. I 1 1 4 F 30. 201 1.00 2000 0 .00 2000 0 00 0. 0 .00 0. ell .00 1800.
29 Il 416 1760. 24 II, 6. I 1 0 4 F &l. 144, 1.00 2000. 0 .00 2000. 0 .00 9. 0 .00 0 0 .00 0, 31 16 19 11000. 11 11. 1. 1 1 7 4 F ll. 140. 1.00 1920 20 00 till. 0 .00 6. 9 .00 0. 0 .00 Om 32- 17 14 .1300. 11 11, 1 1 1 1 4 F ll ;40 1 00 1920. 19 .00 1512 0 .00 9. 0 .00 C. 0 .00 6.
23 14 14 3000. 34. 12 4 I 1 7 4 F 30 299. 1 00 2000. 0 .00 3000 0 00 0. 15 .00 0 0 .00 6.
24 19 20 4040. 11 11, 6- 1 1 7 4 F 15, 147, 1.00 2000. 0 .00 1812. 36 00 C. 6 .00 0. 0 .00 0.
- 25 to 36 4000. 10. 10 1 1 1 7 4 F 40- 164. 1 00 1660 0 .00 1400, 0 .00 0. 37 .00 0 0 .00 6.
26 31 32 11440. 12. 12, 4. 1 1 7 4 F 55. 163. 1,00 2000. 25 .00 1624. 0 .00 0. O .00 C. 0 .00 0.
27 32 25 1940. 13. 13. 6. 1 1 7 4 7 li 151. 1.00 2000. 26 00 1624. 0 .00 0. 9 .00 9. 0 .00 0, 28 33 24 7000. 13. 13. 6. I 1 7 4 F ll . 163. 75 2000. 25 .00 1624. 0 ,00 0. 0 .00 0, 0 .00 0 39 30 14000, 13. 13 1. 1 1 1 4 F ll. 156. .26 1000. 31 .00 1624. 0 .00 9. 0 00 0. 0 .00 4 10 24 Il 6600. 13. 12. 6. 1 3 7 4 F ll . 161. 1.00 2000 0 .00 1634. 0 .00 0. 26 ,00 0. 0 .00 0 31 Il 24 4400. 12 II. 6. I 1 7 4 F 55 165. 1.00 3000. 28 .eu 1824. 37 .00 6. 0 .00 6. 0 .00 c.
32 26 27 atte. 13, 12. 6. 1 1 7 4 F ll. 163 ,90 2000. 37 .00 1634. 0 00 0. 0 00 9. 0 .00 C.
In 28 44ww. 13, 13. 4 1 4 7 4 7 ll. 16). 10 2000 39 00 1624 0 00 6. 0 00 9. 0 .00 0.
Il 27 37 7930, 12 13. 6 1 1 7 4 F ll . 161. 1.00 2000 014 00 1624. 0 .00 0. t .00 9. 0 00 0.
Il as 29 2640 13 12. 6. 1 1
- 4 F 15. 163 1 00 2000. 32 00 1 24. 0 .00 C. 0 .00 c. 0 .00 c.
36 39 33 14520. 13. 12, 6 1 1 7 4 F ll. 161. 1.00 2000. 33 00 1424. 0 00 0. 0 .00 9. 0 .00 0 37 30 31 7480. 12 12. 6. I 1 7 4 F 19. ~43. 1.00 2010. 0 .00 1624 33 .00 0. 0 .00 0, 0 90 0 18 31 32 18920 20. 12, 6 I 2 7 4 r 54 143. 1.00 2004. 0 04 3000- 0 .00 9. 33 00 9 0 .00 9 39 12 31 1320. 23. 14. O. 1 1 5 1 7 30. 217. 1.00 30c0. 0 .00 1663 39 .00 0. 14 .00 0 0 00 0.
4 p* to 31 34 eaa. 3 3. 14. O. I 1 6 3 7 30. 377 .90 2000. 812*0.00 1661. 0 .00 6. 0 .00 0 0 .J0 c.
90 1210. .00 .00 0.
( ) 41 39 1983 13. 13.
42 14 813 15a0 14. 14
- 4. I 1 4 3 P 30, 247.
1 1 4 3 P 30 Joe.
10 2000 all to 2000 0 0
0 0e
,00 0.
C.
0 0 .00 4
0.
0 0 .00 6,
'% # 4. .00 14'l 45 35 013 1080. 10 12. 4. 1 1 7 4 F 19. 163. 1.00 2000, 0 .00 3000. 0 .00 0. 0 .00 0. 0 .00 4.
44 le 17 2440, 11. 10 1, 1 1 7 4 F 45 123, 1.00 1680 0 .00 1612. 8 14 00 0. 6 00 9. 0 .00 0 49 37 414 5720. 13. 12. 6. 1 1 7 4 F 45 199. 1.40 2000. 0 00 1624. 0 00 0. 0 .00 0, e 00 0.
46 3A 41 3$20. 22. 12 6. I 1 7 4 F ll , 16 3 1 00 2000. 43 .00 3060. 0 .00 0- $2 .00 0. 0 .00 0.
47 39 41 1000. 13. 13. 6. 1 2 7 4 F 10. 299, 1 00 2040 0 .00 1624. 42 00 6 0 .00 9. 0 .00 9 ea 40 31 10560. 22. 12. 6. 1 1 7 4 F ll 163. 2% SLuo. la ,00 2000. 0 00 0; O 00 4. 0 .00 0.
49 44 16728 13, 12. 6- 1 1 7 4 F ll . 161. 1$ 2000. 41 .00 1424. 0 .00 0. 0 .00 0- 0 .00 6.
18 41 42 1730 31. 11, 6. 1 1 7 4 F ll . 147. .50 2000. 41 00 3000, 0 .00 0 0 .00 0. 0 00 C.
All 42 11000. 12. 13 6. I 1 7 4 F 15. 161. $0 2000. ll .00 1424 13 00 0 0 .00 c. 0 .00 0.
61 42 43 14$30 34. 11, 6, 1 1 7 4 F ll . 147 1,00 2000. 46 00 2000, 0 00 0. 0 .00 0 0 00 0.
52 el to Geo. 31 11. 6. 1 1 7 4 F 55 141. 1 00 2000. 47 10 2000. 0 .00 0 0 .00 0- 0 .00 0.
l) 44 41 1960. 12. 13. 3. I 1 7 4 F 45. 194. 1.00 3000. 0 .00 1624. 0 00 0. 47 .30 1200 0 .00 C.
64 49 47 4800. 22, 12. 6. I 1 4 3 F ll. 149 1.00 2000. 49 .00 2000, til .00 C. 0 00 9. 0 00 0 ll 46 47 7200. 24. 14, 4. 1 1 4 3 P 49. 196. 1.00 3000- Gli .00 2000. 0 .40 0 49 .00 6. 0 .00 0.
le 47 til 800. 31 11. 4. I 1 4 3 F 30. 213. .90 1900. 0 .00 2000. 0 .00 0. 6 .00 0. 0 00 0 51 49 1400. 28 12. 6. J 1 4 3 F 30 367 30 20f i- la 60 1981. 0 .00 C. 0 .00 0. 0 .00 0, le 45 49 4600. 12. 13. 6. I 1 4 3 F 30. 261 1.00 1s 0 00 1334- 0 00 6. 50 .4s 1300_ 0 00 0.
to 49 le 400. 20. 33. 6, 2 1 4 2 P 30. 267 1.00 20. 810 00 1681 0 .00 0. 0 .00 6 0 00 0.
81 SO 810 1200 28. 12 6. 2 1 4 3 F ll. 145 1.00 2000, 0 .00 1941. 0 .00 0. 0 00 0- 0 .00 6.
$9 11 10 400. 13, 33. 6, 1 3 4 3 F 10. 241 1.00 2000. 0 .00 1236. 410 .00 0 0 .00 0. 0 .00 6.
43 12 51 11440. 13. 12 6. I 1 7 4 F ll 163. 90 3000. 009 00 1624. 0 00 9 0 00 c. 0 .00 6.
63 il 8000. 13 12. 4. 1 1 7 4 F 10. 176. .30 2000. $6 . 00 16J4 . 0 .00 6. 0 .00 9. 0 00 0 64 5 3 tot 16280. 12. 12. 6. 1 1 1 4 F $1. 141. 1 00 2000. 0 .00 16J4. 0 .40 c. 0 .00 D. 0 .00 C.
69 54 ll 9640. 11. 11. 6. 1 2 7 4 F ll. 147 25 2000 0 .00 1912. 0 .00 0. le .00 6. 0 .00 0.
66 67 22440, 13. 13. 6. 1 1 7 4 F ll. 163 .75 2000 SOS .00 1434. 0 .00 0 0 .00 0 0 .00 4.
47 ll 16 9684 13. 12. 4. 1 1 7 4 F ll. 160. . 00 2000. 57 ,00 1824. 0 .00 0. 0 00 C. 0 .00 C.
68 44 SF 8400. 12. 13. 4 1 I 1 4 F $1 160, 1 00 2000. 0 .00 1624. SCO .00 6 0 .00 6. 0 .00 9 69 47 tot 12740. 12. 13. 4. 1 5 7 4 F ll .1 0 - 1 00 2000. 0 .00 1424. 0 .00 9 0 .00 0. 0 .00 0 10 la 60 6200. 2a. 12. 6 I 1 7 2 F 40. 234. 1,00 2000 61 .00 2000. 0 .00 0. 0 .00 6. 0 00 C.
11 ll 62 2800. 14. 14. 1. I 1 6 1 T to 420. 1 00 2000,
. 0 .00 810. 63 .00 C. 0 .00 4 O .00 9.
72 60 43 3310. 24. 12. O. 2 1 5 1 T 20. 376. 1.00 1980. 0 00 730, 6450.00 1200- 0 00 0, 0 .00 6.
73 41 64 2800. 21. ?). O. I 2 1 1 7 20 le4 1.00 1790 O <00 1241. 6150,00 1200. 0 .00 0. 0 .00 0 74 41 83 400 34 11 1. 2 1 4 1 F 20. 160. 1,00 18J0, 6460.00 1699. 0 .00 0. 3 00 0. 0 .00 0 7$ 63 to 800. 16. 11. O. 2 1 4 1 F 20. 356. 1.00 1780. 65 400 1651. 0 00 6. 0 .00 0 0 ,00 0.
76 64 $$ 2400. 34. 13. O. 2 1 4 1 F 30. 374. 1.00 1400. 126 00 1914. 0 .00 9 66 .00 0 0 .00 0.
?? 69 66 000 10. 14. 6. 1 1 1 1 F 20 283. 50 2000. 0 .00 1100 0 00 9 0 .00 0. 71 00 1500-78 124 284a. 24. 13. 4. 2 1 4 1 F 30, 247. .23 2000, 3550.00 1910 0 00 0 0 .00 C. 0 .GG 0.
79 46 11 11440. 24, 12- 6. 2 1 8 4 F 70. tit. 1 00 2000 807 00 2000. 0 .00 6. 0 .00 6. 0 .00 0-40 67 68 490 II, 13. 6, 1 1 1 1 T 20 420 1.00 2000, 0 .00 1285. 0 .00 0. 70 .00 0. 0 .00 0.
81 60 10 J400. 24. 12. 6. 2 1 4 1 F 20. 400- 1 00 3200 71 00 1970. 0 .00 6 0 .00 0, 0 .00 0.
82 49 48 800. J1. 13 6. 1 I b 1 7 20 420 1.00 2000 0 .00 1265. 10 00 0 0 .00 9 0 .00 c.
2
"\/ 43 70 71 9000 13. 12. 4. 1 2 4 3 P ll . 145 1 00 2000- 0 00 1234. 401 .00 1500 0 .00 0. 0 00 0.
v RulwayNetwork Listmg C-l 23627/metefinal
- - . . ~_ - ..-. - - . - . . - - ,
LIFE FBm TO LSW As Le 89 L F8 LT AT Ps $PD Jan PtF FCA) STS SPLT CAP SST SPLT CAP 1.FT SPLT CAF bl&S $ PLT CAF
$5 91 301 18536. 34 13, 6, 1 1 8 4 - F ? $ , 114 1.00 2000 0 .00 2000. 6 00 6- 0 .00 4. 0 .00 C.
46 13 91 840, 22. 12, 4. 1 1 1 4 F le 199. 1.00 2000 99 .00 3000 0 .00 9. 400 -00 9 0 .00- 6.
61 93 12 2649 39. 11. 6. 1 1 1 4 F St. 191, n=00 2000 97 00 2000 0 00 0. 0 .00 C. 0 .00 4 l SS 14- 93 1040 34. 13. 6 1 1 6 4 F 66.13L 15 2000. 93 00 2000, 0 ,00 9 0 .00 9. 0 . 00 1 It- 94 11500. 14. 12. 3. 1 11 4 7 80 114. ,25 3000. 89 00 1624. 0 00 4. 0 .00 .6. 0 .00 c.
90 ft 16 1940- 34. 13 4. 3 1 6 4 7 el. 123. 15 3s00. 19 .00 2000. 0 .00 P. 11 3 to 1200. 0 .00 8 91 123 3209. 24. 14. 4. 1 1 7 4 7 30. 391. 26 3009. 124 .00 1825 8 00 5, 4 .00 6. 0 .00 4.
93 ?6 17 3000. 13. 13. 6. 1 1 1 4 F 16. 163. .25 2000. 14 00 1626 0 .00 6. 0 .00 4.' O .00 9.
19 4400. 34- 13, 4. 3 1 6 4 F el. 133. ,71 3000 80 .00 2000. el 3.00 1300. 0 .00 0. 0 ,00 6.
91 94 _71 15 24640. 13. 12 4. 1 1 ? 4 F St. 163. 1.00 2000 017 .00 1624. O _00 9 3 .40 9, 8 .00 0, 98 10 Sit- 9409-. 12. 13 6. 1 1 ? 4 F Gl 141. 1.00 2000. 0 .00 1624. 0 .00 9. 0 .00 0. 0 .00 6.
96 19 90 *J40. 34. 4T. 6. I 1 6 4 F 65. 123, 75 2000, 41 =00 2000. 93 3 00 1200. 0 .00 6. 0 .0a 0.
71 85 19040 13. 13 6. 1 1 1 4 F 16. 163. .35 3000, 8Ja .00 1634 0 .00 C. 0 .00 0. 0 .00 0. .
94 40 en 12120 34. 13 6, 2 1 6 4 F 49,133 18 3000. 610 .00 2000. 62 3.00 1390. 0 .0. 0 0 .00 C.
99' On 14960- al . II . 4, 1 1 7 4 # 55. 161. .25 2000. 0 00 1634. 94 .00 6. 0 .00 0 0 .00 0 100 el 810 6800 it. 13 6 3 1 6 4 7 64, 113 11 2000. 0 00 2000< 0 .66 c. 0 .00 9. 0 .00 9.
101 82 5290. 11. 11 6. 1 1 1 4 F S t . 141 3% 3800. att .00 1813. 0 .60 6. 0 .00 4. 0 .00 6.
103 42 819 31000. 11. it. 6. 3 1 ? 4 F ll . 147. J A9 2000. 0 .00 1812. 0 00 0. 0 .00 Om 0 .00 0.
108 43 94 930. 12 11, 1 1 1 7 4 F 45.171> 1. 7f SP10. 0 .00 1624. $ .40 C. 420 .00 0, 0 .00 0, 104 *4 $29 10569 11 11, 6, 1 1 1 4 F 4 5.100.1. 67 J7t6 0 00 1912. 0 .70 6. 0 .00 6. 0 .00 0.
106 el 831 10140 12. 12- 4 1 1 7 4 F ll. 163. 1.06 1906 -4 4 leil. 9 90 6. 0 ,00 c. 0 .00 9 5 104 46 91 13320. 12. 12. 6. I 1 . 4 F ll. 163. 1 00 2000 931 00 1614 0 00 C. 0 .09 0. 0 .00 9.
Is't OT 012 13205.12.12, 64 1 1 1 4 F St. 161. 1.04 2000- 2 80 1629 F .00 0. 0 .30 0. 0 .00 4.
10s at 99 5280. 13. 13. 6. I 1 7 4 F S0.179. 1.00 3000. 90 .00 1634. 0 .00 0- 0 .00 6. O 00 c.
109 19 to 11300. 13. 13, 6, 1 1 7 4 F to - !?t. 1.00 1000. 91 00 1634, b .00 .O. 0 .00 9 0 .00 0, 110 90 91 7930. 13. 13 6. I 1 7 4 F to. lit 1.00 8000 801 00 1634. 0 .00 C. 0 00 0. 0 00 6.
111 91 tot 10130. 12. 13. 4. 1 1 ? 4 F St. 119. 1.00 2000. 0 .00 1634. 0 .00 0, 0 .00 6 0 .00 01 113 63 93 14a0. 14 13. 4. 2 1 6 4 F 66,123, 5.00 2000. 90 .00 2000. 8 .00 9, 94 2.00 1300, 0 .00 4.
113 el 94 1930, 13. 12 6. I 1 1 4 F 15. 254 .35 300%. 133 .00 1624, 0 00 C. o 00 0. 0 .00 9 1:4 to 4400 23 11. 6. 3 1 6 3 F ll. 141. 18 1960. 101 .00 1191. 0 .00 9. 0 .00 0. 0 .00 0.
118 94 133 14840 13. 13. 3. I 1 1 4 F ll. 187. 1.00 2000. 95 .00 1624. 0 .00 0. 0 .60 0, 0 .00 0, 116 95 96 11840 11, 11, 6 1 1 1 4 F $0.163.1s 00 3000 802 00 1913. e .00 9. 0 .00 0. 0 .00 9.
IIT to 6 3 1920, 12. 13 4. I 1 1 4 F 50 119. 1.00 2000 0 .01 1634. 0 .00 C. 0 00 6. 0 .00 0 118 97 100 13320. 13 13. 6. 1 1 1 4 F ll. 163. .50 3000. 101 00 1624 0 .00 0. 0 .00 9. 0 .00 0.
119 99 11440. 16. 12. 6. 1 1 1 4 F $0. 119. ~50 3000. 111 00 2000. 0 .00 9. 0 .00 9 O ~00 4.
135 99 101 2640. 32, ll- 4. 2 1 1 3 F 35, all. 1 00 2000. 103 .00 1391 0 .00 9 0 00 8. E .00 C.
- 12. 12 6= 1 1 1 4 F 55, 168. 1.00 2000. 115 .00 1824 0 .00 9. 0 00 9 0 00 0, 128 99 all 4400 123 100 nel 1160, 11 11. 4. 1 1 7 8 7 30. 269. 1.00 2000 *O allt. 103 00 0. 0 .00 01 0 .00 6.
123 101 102 440. 32. 11. 6. I 1 1 1 F 30, 269. 1.06 3004 1 1191 0 .e4 0. 101 .00 9 O < 00 6.
124 103 101 6140. 33 13. 6 I 1 1 1 F 35. 2nd. 35 to) c000, 0 .00 9. 0 00 1 0 .00 0 126 112 2649 34. 13. 4. 2 1 6 3 F ll 145. 16 20'. 4 iJ00. 0 00 9. 113 2.00 1200. 0 .00 9 134 103 104 10160. 23. 13. 3. 1 1 1 4 F ll,187. 1.00 300. 0 2000. 0 .00 0, 108 .00 0. 0 .00 8.
g 131 104 104 tese 10. 10 5 I 1 1 4 F 16, 30). .30 nies. nde 00 1400. 0 .00 9. 0 .00 3. 0 .00 9 124 101 10160. 12, 12. 6. 1 1 1 4 F ll. 141. .60 2000. 108 .05 1624. 0 .00 0. 0 .00 0, 0 .00 0.
129 105 106 11440. 10. 10. 6. 1 1 1 4 F 46. 154. 1.00 1780. 0 00 1400. 106 .00 0. 0 .00 0. 0 .00 0, 110 104 108 2640, 11. 11, 4 1 2 1 4 F SO, 162- 1,00 3000, 0 .00 1634. 0 .00 0. 109 .00 9. 0 .00 4 131 101 100 12320. 12. 12. 4, 1 3 1 4 F ll. 163, 1.00 2000 109 .00 1624. 0 .00 9. 0 .00 6. 0 .00 0.
til 108 109 7040. 33, 13. 6. I 1 1 4 F ll. 163 1.00 2000 110 00 1634 0 .00 6. 0 00 4 0 .00 0.
131 109 110 638c, 12. 12 6, 1 1 1 4 F ll, 163 1.00 2000. 803 .00 1424 P 00 0 0 .00 0. 0 .00 6.
134 110 Gol 3120. 12. 12. 6. I 1 1 4 F $0. 179. 1.00 2000. 0 00 14J4, 0 .00 0. 0 .00 6. 0 .0^.' O.
135111 All 141J0. 12. 11 6, 1 1 1 4 F ll. 141. 1.00 2000. 116 .00 1624 0 00 0. 0 .00 0. 0 .00 9.
134 112 113 14000, 13, 13, 6. 1 1 7 4 F 45 199. 35 3000. 114 00 1624. 0 .00 9 0 00 0 0 .00 4.
111 116 15340. 22. 11 4. 2 1 6 4 F El. 144 .it 1949. G0S .00 1391. 0 .00 0, all 3.00 1200. 0 .00 6.
lit 11) 114 13200 12. 13 4 1 2 1 4 F 44, 224. 1.00 3000. 0 .00 1634 0 00 C. 119 00 0, 0 ,00 4.
139 114 119 19160. 13. 12- 6 1 1 1 4 F ll. 143. 1.00 2000. 0 ,00 1634. 804 .00 6. 0 .00 4 0 00 5 140 lin 116 2440 12. 43 6. 1 2 ? 4 F ll . 163. 1.00 2000. 111 .00 1424. SOS 00 6. 0 00 6. 0 .00 0.
141 116 111 11200. 13= 12. 4. 1 1 1 4 F 55 161. 10 2000 138 00 1624. 0 .00 6. 0 00 0. 0 .00 9 142 005 4400, 33. 33. 6. I 1 6 4 F ll. 141. .90 2000, 0 00 1391. 0 .00 0, 0 00 0. 0 .00 0,
- 14) 111 lit in sa . 11. 11, 6. I 1 1 4 F ll. 141. 1.00 2000. 114 .00 1913 0 00 0 O C0 0 0 .06 6.
144 110 114 12130. 11. 11, 6. 1 1 1 4 F ll . 147 1.00 2000. 119 00 1912. 0 .00 0. b 00 0, 0 ,00 0.
nel 119 904 10160. 11. 11. 6. 1 1 1 4 F ll. 147. 1.00 3000, 0 .00 1813. O .00 9. 0 .00 0 0 .00 0, 146 130 131 14000. 34. 11 5. I 1 1 4 F ll. 145. 1.00 2000 606 .00 2000. 0 .00 4. 0 .00 0 0 .00 9.
149 121 604 6800. 13. 12. 4. 1 1 1 4 F ll . 143. 1.00 2000 4 .00 1624, 0 .00 4. 0 .00 0 0 .00 0, 148 132 139 2940. 24. 12. 6, 1 1 5 4 T 30. 261. 1.00 3000 86 00 1828 0 00 9. 0 .00 C. 0 .00 0.
149 1?) 95 17400. 13. 12. 6. 1 1 1 4 F 4 5, 199. 1.00 2000. 96 .00 16J4. 0 .00 C. 0 .00 0. O .00 0, 150 124 2n 19140.12 < 13, 6, 1 1 1 4 F 30. 299. 1,00 2000. 24 .00 1624 0 .00 0. 10 .00 0. 0 .00 0.
til 13% 06 12000. 12, 12, 2. 1 1 1 4 F ll. 151 1.00 2000 01 00 1624. 0 ,00 0, 0 .00 0. 0 .00 0, all k36 - 38 11000. 3 3. II. 6, 2 1 7 4 F 11.161 1.00 2000- 41 00 1397. 0 .00 6. 0 400 0. 0 .00 0.
64 131 120 11640. Lt. 12. S. 1 1 9 4 F ll, 161. 1~00 3000, 131 .00 1624. 0 .00 c. 0 .00 4. 0 ,00 A.
c s Roadwy Network Listmg C-2 23627/metefinal
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