Text

an Independent Assessment of Evaluation Time Estimates for a Peak Population Scenario in the Emergency Planning Zone of the Seabrook Power Station
	ML20069N647
Person / Time
Site:	Seabrook
Issue date:	11/30/1982
From:	Desrosiers A, Mclean M, Moeller M, Urbanik T; Battelle Memorial Institute, PACIFIC NORTHWEST NATION
To:	; NRC OFFICE OF INSPECTION & ENFORCEMENT (IE)
References
	CON-FIN-B-2311 NUREG-CR-2903, PNL-4290, NUDOCS 8212060457
	Download: ML20069N647 (87)
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! NUREG/CR-2903 PNL-4290. ..

! An Independent Assessment of Evacuation Time Estimates for A Peak Population Scenario in

?the Emergency Planning Zone;of the; a l

'I Seabrook Nuclear Power: Station

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l Prepared by M.P. Moeller, T. Urbanik ll", M.A. McLean,- A.E. Desrosiers Pacific Northwest Laboratory Operated by Battelle Memorial Institute Prepsred for U.S. Nuclear Regulatory Commission

Texas Transportation Institute i

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NOTICE -

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This report was prepared as an account of work sponsored by an agency of the United Statest Government. Neither the . United States Government nor any agency thereof, or any of their I

employees,. makes ' any warranty,. expressad or implied, or . assumes any legal; liability of re-spo.nsibility for any third party's use, or the results of such use, of any information, apparatus,'

product or process disclosed in this report, or represents that its use by such third party would; not infringe privately owned rights. .

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Availability of Reference Mat'erials Cited in NRC Publications

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Most documents cited in N RC publications will be available from one of the following sourcesi

1. The NRC Public Document Room,1717_H Street, N.W. .

Washington, DC 20555 -

2. The NRC/GPO Sales Program, U.S. Nucleef Regulator [Cornmission,"

.M Washington, DC 20555 ~

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3. The National Technical Information Service, Springfield, .VA 22181 f Although the listing that follows represents the majority of document; cited in NRC publications, it is not intended to be exhaustive.

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Referenced documents available for inspection and copying for a fee from the NRC Public Docu.

' ment Room include NRC correspondence and ir.ternal NRC memoranda: NRC Office of Inspection ~.

and Enforcement bulletins, circulars, information notices, insoection and investigation notices; '

Licensee Event Reports; vendor reports and correspondence; Commission papers;and applicant and ~

licensee documents and correspondence.

The following documents in the NUREG series are availaole for purchase from the NRCIGPO Sales >

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Program: formal NRC staff and contractor reports..NRC-sponsored conference proceedings,~ and N RC booklets and brochures. Also available are Regulatory Guides, NRC regulations in the Code of Federal Regulations, and Nuclear Regulatory Commission issuances. -

Documents available from the National Technical information Service include NUHEG series reports and technical reports prepared by other federal agencies and reports prepared by the Atomic .

Energy Commission, forerunner agency to the Nuclear Regulatory Commission.1 Documents available from public and special-technical libraries include all open literature items, such as books, journal and periodical articles, and transactions. Federal Register notices, federal and .

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Documents such as theses, dissertations, foresgn reports and translations, and non-N RC conference proceedings are available for purchase f.om the organization sponsoring the publication cited.

Single copies of NRC draft reports are available free upon written request to the Division of Techc nical Information and Document Control, U.S. Nuclear Regulatory Commission, Washington, DC 20555.

Copies of industry codes and standards used in a substantive manner in the NRC regulatory process are maintained at the NRC Library, 7920 Norfolk Avenue, Bethesda, Maryland, and are available there for reference use by the public. Codes and standards are usually copyrighted and may be purchased from the originating organization or, if they are American Natir al Standards, from the American National Standards inttitute,1430 Broadway, New York, NY 10018.

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NUREG/CR-2903 PNL-4290 An Independent Assessment of Evacuation Time Estimates for A Peak Population Scenario in the Emergency Planning Zone of the Seabrook Nuclear Power Station Manuscript Completed: October 1982 Data Published: November 1982 M , oe Ier, T. Urbanik ll*, M.A. McLean, A.E. Desrosiers Pecific Northwest Laboratory Richland, WA 99352 Prsp: red for Division of Emergency Preparedness Offico of Inspection and Enforcement U.S. Nuclear Regulatory Commission W:shington, D.C. 20555 NRC FIN B2311

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,%ed ABSTRACT This study comprises two major tasks. First, it includes an independent assessment of the methods and assumptions used ir, calculating evacuation time estimates (ETEs) applicable to the general population for.a peak population scenario in the emergency planning zone (EPZ) of the-Seabrook Nuclear Power Station. This consists of a review and analysis of previous work by Public Service of New Hampshire (PSNH) and the Federal Emergency Managenent Agency (FEMA), as well as an independent calculation of evacuation times using the CLEAR model for the demographic data reported by PSNH. Secondly, this study includes independent estimations of evacuation time for the peak population scenario developed using demographic data prepared by'the U.S. Nuclear Regulatory Commission (NRC). These evacuation time estimates are approxi-mately 60% and 84% greater, respectively, than the estimate provided by PSNH for a simulataneous evacuation of the entire EPZ under peak conditions.

- The CLEAR model, which was developed by Pacific Northwest Laboratory (PNL) under the sponsorship of the.NRC, was also used for these latter calculations.

The results of this study reveal the importance of the assumptions used for calculating evacuation times. Because traffic routings and management plans have not been prepared for the area, the CLEAR calculations utilized indep-dently prepared traffic routings and assumptions. A detailed analysis of the results suggests that the ETEs submitted by PSNH are consistent with the methods and assumptions which provide-the bases for PSNH's evacuation time estimates. Differences among evacuation time estimates stem'largely.

from differences in the assumed size of the evacuating population and the estimated effectiveness of traffic controls.

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SUMMARY

This study is an independent assessment of the evacuation time estimate for the general population reported by PSNH, Public Service of New Hampshire, for a peak population scenario in the emergency planning zone of tne Seabrook Nuclear Power Station. The study consisted of two parts. First, the computer model CLEAR was used to calculate ETEs for the Seabrook peak population scenario based upon the demographic data and automobile demand estimates submitted by PSNH. Second, the CLEAR model was also used to calculate independently the ETEs for the same scenario based upon the demographic data and automobile demand estimates prepared by the U.S. Nuclear Regulatory Commission.

The results of this study reveal the importance of the assumptions used for calculating evacuation times. Analysis of the evacuation time estimates reported in this study suggest that the ETE computed by PSNH is consistent with the methods and assumptions used in their analysis. Their assumptions are optimistic and include implicitly attaining a high level of efficiency and utilization of the available transportation network.

In contrast to the 380 minute ETE reported by PSNH, a 610 minute ETE was calculated for the same demographic data using the computer model CLEAR.

Using equally realistic methods and assumptions, the CLEAR ETE is greater because the methods and assumptions used in the calculations are more conservative. Furthermore, because the demographic data and automobile demand estimates prepared by NRC were larger than those reported by PSNH, the CLEAR model calculated a 90 minute inc' ease in its ETE when using the NRC data.

The evacuation times reported in this study will remain gross estimates until the assumptions used in the calculations for this scenario are defined.

Specifically, when the detailed local evacuation plans have been prepared for the Seabrook EPZ, a more exact ETE can be calculated.

This last point identifies the significance of the detailed local evacuation plans in determining the time necessary to evacuate the Seabrook EPZ. As detailed in this report, the relative degree of evacuation planning and implementation of effective traffic management procedures will ultimately determine the time required to evacuate.

In conclusion, the results of this study emphasize the need to develop a detailed local evacuation plan for the Seabrook EPZ and the need to reexamine the ETEs after these plans are developed. The alternative traffic management schemes discussed in this report should aid in the optimization of the local traffic management portion of the offsite emergency plans, iv

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TABLE OF CONTENTS ARSTRACT.................................................................iii

SUMMARY

....................................................... ..........iV INTRODUCTION.............................................................. 1 DEMAND ESTIMATION......................................................... 2 TRAFFIC CAPACITY.......................................................... 9 ANALYSIS OF EVACUATION TIMES............................................. 15 METHODOLOGY......................................................... 15 RESULTS.................................................................. 16 DISCUSSION............................................................... 19 CONCLUSIONS.............................................................. 24 REFERENCES.............................................................REF-1 APPENDIX I - AUTOMORILE DEMAND ESTIMATES.................................I-1 APPENDIX II - EVACUATION TREES..........................................II-1 APPENDIX III - INPUT DATA..............................................III-1 APPENDIX IV - 0FF-SEASON SCENARIO EVACUATION TIME ESTIMATES.............IV-1 v

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INTRODUCTION This study is an evaluation e evacuation time estimates for the general population submitted by PSNH ' for a peak population scenario in the emergency planning zone of the Seabrook Nuclear Power Station. The purpose of this study is to independently assess the validity of the ETEs, as well as the methods and assumptions used by PSNH for estimating evacuation times. This independent verification of PSNH's time estimates for the Seabrook EPZ inclupes two independent calculations of evacuation time estimates using the CLEAR \ 11 model. Evacuation time estimates were prepared using both PSNH and '

NRC's demographic and vehicle demand estimates. Therefore, this study reflects an independent assessment of all variables, parameters and assumptions used in calculating evacuation time estimates for the Seabrook EPZ. In addition, an examination of the transportation network in the EPZ was perirrmed in order to establish assured evacuation routings.

A single scenario was selected as a basis of comparison. This scenario is an evacuation of the entire (360 ) EPZ surrounding Seabrook Station under .a peak population condition. The population is assumed to consist of the permanent, seasonal and peak transient residents of the EPZ. Institutionalized populations are not included.

The selection of this scenario does not imply that institutionalized populations should not be included in emergency preparedness plans or that a The simultaneous 370)should evacuation of an EPZ he consulted in is a preferred this protective regard. The action.

scenario was NRC's guidance selected as a means of comparing PSNH's ETEs with independent calculations under conditions that would highlight differences.

The calculations in this report are likewise not intended for use by decision makers during emergencies. The present estimates are based on assumptions by the authors regarding preferred evacuation routings and traffic management.

The recommendations of this report, other analyses of the Seabrook EPZ and the experiences of local officials should be reviewed and detailed local plans should be implemented. At that time, th9 qvacuation time estimates indicated in NRC's emergency preparedness criteria \71 should be prepared for the use of decision makers.

There are two other studies of evacuation times for the Seabrook site. One of these studies, by Wilbur Smith and Associates, was not reviewed as it is somewhat dated, yoyever, a more recent study by the Federal Emergency Management Agency \ 31 is discussed.

(a) Personal correspondence from John D. Vincentis, Public Service of New Hampshire to the U.S. Nuclear Regulatory Commission dated July 31, 1981.

(b) Parsonal correspondence from Arthur M. Shepard, Public Service of New Hampshire to the U.S. Nuclear Regulatory Commission dated August 4,1980.

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i l DEMAND ESTIMATION The objective of.this section is to provide an estimate of the number of vehicles participating in the evacuation. The autot* bile demand estimate is based upon three potential population groups. These .nclude: 1) permanent residents, 2) seasonal residents, and 3) daily transients. Permanent resioants are those who live in the area throughout the year, while seasonal residents live in the area during the tourist season. Daily transients include those in hotels, motels, and campgrounds,- daily visitors to beaches, and persons at the Seabrook Greyhound Park (a race track) and other facilities in the EPZ.

.. The automobile demand estimates used as input for the CLEAR calculations were those reported by PSNH and the NRC for the three population groups. Figures 1 and 2 and Table 1 are summaries of the automobile demand estimates for a peak population scenario in the Seabrook EPZ. These figures illustrate the total number of vehicles within the EPZ, as well as their spatial distribution in each sector. The total number of vehicles estimated to be in the Seabrook EPZ during this scenario was established as 87,996~ by PSNH and as 95,822 by the NRC. Additional information used to calculate the automobile demand estimates is illustrated in Appendix I. Table 2 shows the percentage differences q between PSNH's and NRC's estimates of automobile demand.

' The NRC's automobile demand estimates used in the CLEAR calculations for the f zero to ten mile radius area 43 (Summer Weekend Case:

of theDemand Vehicle Seabrook EPZofwere 1983.) thosereportt2 the NRC reportej in Table Excluded from this table are automobile demand estimates for the resident non-auto owning population group in the zero to ten mile area. In order to have a format consistent with PSNH's data, vehicle demand estimates were calculated for the resident non-auto owning population. It was assumed that the resident non-auto owning population would be evacuated by bus in an emergency situation. One bus was assumed to carry approximately forty residents and one bus was assumed to be the demand equivalent of two automobiles. Therefore, in the Seabrook EPZ the resulting automobile occupancy factor for the resident non-auto owning population is twenty residents per automobile. This occupancy factor was used in conjunction with Table Non-auto Owning Population 1983.) of the NRC report 2 to{6)(Summer determine theWeekendautomobile Case:

demand estimates for the entire EPZ of the Seabrook site.

The ETEs are not sensitive to these assunptions because the resulting demand is less than one percent'of the total demand estimate. In the 0-10 mile area of the EPZ, the resident non-auto owning population was estimated by NRC as

! 13,061. According to the formula mentioned above, this resulted in a i automobile demand estimate of 653. It is also reasonable to assume that, in I

reality, people without automobiles may be absorbed into neighbors' vehicles.

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AUTOMOBILE DEMAND ESTIMATES FOR A PEAK POPULATION SCENARIO IN THE SEABROOK EMERGENCY PLANNING ZONE N 492 e ,m .

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PSNH VEHICLE TOTALS RING RING TOTAL CUMULATIVE MILES VEHICLES MILES VEHICLES 02 14891 0- 2 14891 2-5 27201 0- 5 42092 5 10 33833 0-10 75925 10 EP2 12071 0-E P2 87996 FIGURE 1.

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AUTOMOBILE DEMAND ESTIMATES FOR A PEAK POPULATION SCENARIO IN THE SEABROOK .

EMERGENCY PLANNING ZONE !

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NRC VEHICLE TOTALS RING RING TOTAL CUMULATIVE i MILES VEHICLES MILES VEHICLES 0-2 17990 0-2 17990 25 31016 0-5 49006 6-10 35763 0-10 84769 10-E PZ 11053 0-E PZ 95822 FIGURE 2.

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TABLE 1. Automobile Gemand Estimates for a Peak Population Scenario In the Seabrook EPZ 0-2 mi. 2-5 mi. 5-10 mi. 10-EPZ Total Sector NRC PSNH NRC PSNH NRC PSNH NRC PSNH NRC PSNH N 93 37 2027 952 1685 2048 1908 492 5713 3529 NNW 170 151 280 268 1122 993 311 419 1883 1831 NW 126 94 724 486 4054 3953 283 293 5187 4826 WNW 59 28 285 321 717 800 759 1090 1820 2239 W 3277 2408 3514 3551 996 1333 833 898 8620 8190 WSW 369 322 1383 1551 4298 4840 187 222 6237 6935 SW 1335 334 1374 1491 1935 2235 123 153 4767 4213 SSW 177 271 641 518 3777 3941 276 291 4871 5021 S 244 236 1272 1149 3980 3258 0 0 5496 4643 SSE 44 39 5533 5482 6212 4822 0 0 11,789 10,343 SE 63 42 1443 1327 0 0 0 0 1506 1369 ESE 2225 1964 0 0 0 0 0 0 2225 1964 E 4304 4107 0 0 0 0 0 0 4304 4107 ENE 5279 4711 3910 3336 0 0 0 0 9189 8047 NE 200 147 6905 5056 4386 2771 175 0 11,666 7974 NNE 25 0 1725 1713 2601 2839 6198 8213 10,549 12,765 Total 17,990 14,891 31,016 27,201 35,763 33,833 11,053 12,071 95,822 87,966 TABLE 2. Percentage Differe..ce Retween PSNH and NRC Automchile Demand Estimates

0-2 mi. 2-5 mi. 5-10 mi. 10-EPZ Total Sector % % % % %

N +151 +113 -18 +288 +62 NNW + 13 + 4 +13 - 26 +3 NW + 34 + 49 +3 - 3 +7 WNW +111 - 11 -10 - 30 -19 W + 36 -

1 -25 - 7 +5 WSW + 15 - 11 -11 - 16 -10 SW +300 - 8 -13 - 20 +13 SSW - 35 + 24 -4 - 5 -3 S + 3 + 11 +22 0 +18 SSE + 13 + 1 +29 0 +14 SE + 50 + 9 0 0 +10 ESE + 13 0 0 0 +13 E + 5 0 0 0 +5 ENE + 12 + 17 0 0 +14 NE + 36 + 37 +58 +N/A +46 NNE +N/A + 1 -8 - 25 -17 TOTAL + 21 + 14 +6 - 8 +9

Percenta9e difference is calculated by NRC-PSNH gg, 5

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Two other population groups (medical related and institution related) i' identified in Table 46 of the NRC report were not included in determining i automobile demand estimates for the NRC's non-auto owning population group fnr a peak population scenario. This was consistent with PSNH's automobile demand

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estimates, which also did not include these institutional population groups.

Automobile demand estimates for populations in educational facilities were also not considered in determining ETEs for 50th PSNH's and NRC's data, since the peak population occurs on a summer weekend.

l This is not to say that evacuation time estimates should not be prepared for such groups. However, these groups were not selected for inclusion in the estimates generated for this comparison because the purpose of this study is

, to independently assest the methods for calculating evacuation times for the general population.l 101 NRC radiusautomobile were determineddemand fromestimates population for data the Seabrook reported EPZ in April, outside 1982 2 of In the(t$n mile the other report, NRC did not generate data for the area from the 10-mile radius to the EPZ boundary. To obtain this information, the NRC population i

estimates for towns beyond ten miles in the Seabrook EPZ, as shown in Table 3, were divided into two basic groups; a total population and an estimated population without automobiles. To determine the NRC automobile demand

, estimates in each town for this portion of the EPZ, the non-auto owning populations were subtracted from the NRC's total population groups. The resu}ti\ 4J'g n town populations These numberswere divided by represented thethe number average householdowning of households size for each automobiles in the Seabrook EPZ beyond ten miles. The vehicle occupancy factor used for these calculations was one household pet vehicle. This is the vehicle occupancy factor which the NRC study adopted.ts)

I The non-auto owning populations were divided by the vehicle occupancy factor of twenty residents per automobile equivalent (as previously discussed). 'Thi s determined the effective automobile demand estimates for these populations.

Estimates were summed to obtain the total automobile demand estimate for each town extending beyond the 10-mile radius.

The resulting demand estimates for each town in the EPZ beyond the ten mile radius are assumed to be distributed evenly over each town's area and divided into sectors (N, NNW, etc.) accordingly. For example, the town Brentwood has a total population of 1,984 outside of ten miles in the EPZ(o{. 2 However, 1,401 residents are in the WNW sector and 583 are in the NW sector. This procedure is performed for the auto-owning and non-auto owning population 4

groups in each town.

l In regard to Table 3, the data for the townships of Portsmouth and Kingston i have been readjusted from the original table received from the NRC. As i

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TABLE 3. Population Beyond 10 Miles in Towns Within the Seabrook EPZ NRC's PSNH's NRC's Revised Estimated 1983 1983 Population Town Sector Population Popul ation, Without Autjs Rye NE 604 465 11 Rye NNE 603 464 10 Portsmouth NNE 19,228 17,994 2,682 Portsmouth N 4,807 4,498 670 Greenland N 1,477 1,304 115 Stratham NNW 480 422 37 Newfields NNW 778 601 53 Newfields NW 247 191 17 Exeter NW 146 149 23 Brentwood WNW 1,756 1,401 123 Brentwood NW 731 583 51 Kingston WNW 1,207 1,047 70 Kingston W 2,817 2,242 163 Newton W 187 13d 11 Newton WSW 187 130 11 Merrimac WSW 480 477 56 West Newbury SW 459 479 89 Newbury SSW 872 852 60

These data are for total resident population which include those who have access to automobiles and those who do not.

indicated in the original table received from NRC, the outer boundaries of Portsmouth and Kingston are not indicated in Figure B-1 of PSN4's report, which the NRC demographers used to divide the population groups into their corresponding sectors. The original table indicates that the total population of Portsmouth is in the NNE sector and that approximately 38% of Kingston's total population is in the WNW and 62% in the W sector. The approDrtate sectors have been drawn on maps which do show the outer boundariesl61 It is found that Portsmouth's population beyond 10 miles in the EPZ lies in both the NNE and N sectors, with percentages of 80% and 20%, respectively. It is also found that approximatley 30% of Kingston's population is in the WNW sector and 70% is in the W sector.

These new data percentages have been calculated by dividing the towns' area within the ten mile radius and outside the ten mile radius into approximately triangular areas. The area in a specific sector is then divided by the appropriate total area beyond ten miles and multiplied by 100 in order to determine the percentage of the total population group that is in the >

particular sector. This is performed by assuming an even population distribution throughout these two towns.

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The automobile demand estimates for the entire Seabrook EPZ are assigned to the appropriate sectors and radial annuli. The sectors being N, NNW, NW, etc.

and the annuli being 0-2, 2-5, 5-10 miles and beyond 10 miles within the EPZ (10-EPZ). These evacuation trecs(estimates areinused 11 established as inputEPZ.

the Seabrook to the CLEAR The CLEARmodelmodel for the is used to calculate the ETE for each evacuation tree.

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TRAFFIC CAPACITY In order to assess the capacity of the transportation metwork, two on-site visits were made to the Seabrook EPZ. One was made during the last weekend of July 1981 and the other during Labor Day weekend, 1982. The first effort involved an overall examination of the entire transportation network in the Seabrook EPZ. This review included the collection of data detailing the capacity, speed, number of lanes, and intersecting routes for each road segment in the EPZ.

In addition to this effort, several special traffic studies were conducted in the Seabrook EPZ in order to establish psrameters used in calculating ETEs. These special studies involved the collection of travel time and speed data over several critical lengths of the Seabrook EPZ (see Figure 3).

The data analysis and determination of the various parameters were performed at the Texas Transportation Institute (TTI).

One special study involved the recording of the last three digits on vehicle license plates between two points on the major evacuation routes in the EPZ.

From these data, travel times were calculated for vehicles under a wide range of conditions. A total of four studies were made on two separate routes. Two of the studies were conducted on New Hampshire Route 286, between Washington Street and New Hampshire Route 1A. Although eastbound New Hampshire Route 286 would not be an evacuation route, the studies were conducted in both directions in order to detail traffic flow in the particular area. At each upstream survey point, the data collectors recorded on tape recorders both the last three digits on a vehicle license plate and the time at which the vehicle passed the survey point. Only the last three digits of the license plates were recorded because it was not necessary to match all license plates at both survey points. At each downstream point, the same data was collected; that is, the last three digits of each vehicle's license plant and the time at which the vehicle passed.the survey point. From these data, both the total number of vehicles involved and the average travel time between the two points were determined. It was apparent during the collection of the data that the critical points in the transportation system were the intersections downstream of the survey points. Based on observations at these critical points, such as outbound on New Hampshire Rout 286, it became apparent that part of the congestion was induced by downstream traffic signaling. The relationship of these studies to the assumed traffic capacities used in the CLEAR calculations will be discussed later in this report.

In order to establish road segment characteristics and develop evacuation routings, extensive field work was conducted which included driving the transportation network in the Seabrook EPZ in order to determine the number of lanes and free-flow velocity of each road segment (see Figure 4). In addition, aerial photographs were taken of the entire Seabrook EPZ which enabled verification of the field work and assisted in the development of evacuation routings. A total of eight maps showing those road segments used as evacuation routes are included in this report as Appendix II. Each map corresponds to an evacuation tree used to calculate an evacuation time 9

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FIGURE 3. Road Segments on Which Special Traffic Studies Were Conducted 10

TRANSPORTATION NETWORK IN THE SEABROOK EMERGENCY PLANNING ZONE

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estimate for the population in that area. An evacuation tree is a closed system of road segments which indicate the evacuation routings used for the i population in each area.

From the traffic studies, field work, and aerial photographs, characteristics for each road segment in the Seabrook EPZ were established. Characteristics j of each road segment are listed by evacuation tree in Appendix III. 'This j j appendix is actually the first part'of the output from the CLEAR model. The printout details the input characteristics of each road segment used to calculate the ETEs.

1 j One exception to the usual method of establishing an evacuation tree and planned routing was made for Interstate-95 (I-95). The southbound evacuation route for I-95 is split into two road segments with an imaginary divider from i the intersection with New Hampshire Route 107 to the off-ramp to Interstate-l 495 (I-495). The road segments are modeled in this manner because there is a

! reduction in capacity on southbound I-95 south of the I-495 off-ramp.

I Specifically, I-95 north of the I-495 off-ramp has four lanes, and south of the I-495 off-ramp it has three lanes. Therefore, the portion of Route 107 1

west of I-95 and up to and including Seabrook Greyhound Park was simulated as evacuating on a single lane of I-95 southbound and then routed via the off-l' ramp to I-495. The remaining three lanes of I-95 :;outhbound were assigned to another evacuation tree. Because I-95 did not reach its capacity during the CLEAR calculations, these assumptions do not distort the evacuation time estimates. Hence, it is not particularly important how traffic on I-95

southbound is split between I-95 and I-495, because the evacuation time is

! constrained by the capacity of the roads that feed onto I-95 and I-495.

]

l The process of assigning the vehicles to the transporta<;1gn network included

! the use of three independent special traffic generatorsL11 These three j generators included the Seabrook Nuclear Power Station, the Seabrook Greyhound i Park, and a campground south of New Hampshire Route 1A near Salisbury Beach.

i With one exception, the remaining traffic was assigned using the normal' CLEAR procedure of di t ibuting the traffic along all of the road segments of a

{

particular zone 1 Due to the limited access of southbound I-95 south of New

! Hampshire Route 1A, no population was assigned initially to that road i segment. This was accomplished by creating a special zone with zero

! population that included the relevant section of I-95 (see Appendix III).

i The road segment capacity used for this study is a critical (or limiting) lane

. volume of 1500 vehicles per hour. The 1500 vehicles per hour volume is a widely-used capacity figure and represents an attainable value for average-to-j good urban conditions. It should be noted that a critical lane volume of 1500 i vehicles per hour includes the sum of all movements approaching an intersection. Where two road segments merge into a single lane, the two

! contributing road segments cannot reach the 1500 vehicles per hour volume i because the downstream link would be controlling the volume.

i l The road segment capacity figure was chosen in consideration of several factors. Based on the traffic studies conducted in the EPZ, it is apparent j that congestion exists are due to a variety of factors. In some cases, it was

observed that traffic signals were not functioning in the most efficient i

I i 12 l-t I .. _._ .- .- __ _ -

manner. In others, there existed substantial side friction caused by vehicles entering and leaving the road segment in numerous areas; most notably in the commercial areas with restaurants.

The flow rates attainable on any particular road segment during the evacuation are also based on other factors. It is assumed that traffic control will be instituted at critical intersections and that traffic flows are routed in accordance with the evacuation trees developed in this model.

The observed congestion that exists in the EPZ during a typical summer weekend is not necessarily representative of events occurring during an evacuation.

For example, it is not expected that large numbers of people would be stopping at the local dining establishments during the evacuation. It is also expected that higher flow rates will be achieved on certain critical links due to the presence of traffic control at critical intersections and that efficient routing of traffic will be instituted to avoid unnecessary conflicts between competing traffic flows. This explains why the congestion which may exist over time periods as great as 6.5 hours5.787037e-5 days 0.00139 hours 8.267196e-6 weeks 1.9025e-6 months during a summer Sunday does not represent a minimum attainable evacuation time for that particular area. In other words, flow rates on particular road segments during an evacuation are anticipated to be higher and some traffic that would normally use a particular road segment could be rerouted over alternate routes in order to better utilize the available capacity within the entire transportation network.

An issue that was raised by residents in the Seabrook EPZ concerned potential delay problems caused by the French-speaking population present in the area.

It was alleged by some that up to 20 percent of the population were non-English-speaking people from Canada. In order to attain an estimate of the potential French-speaking population, two sets of data were collected in the EPZ. The study included the collection of license plate data on the Exeter/Hampton Expressway (Route 51). Approximately 350 vehicles were recorded inbound on Route 51 on a Sunday morning. Of this number, approximately 3 percent had Canadian license plates. This route was selected because it was the most likely route by which vehicles from the Province of Quebec would enter into the area. It seems unlikely that any other route would have a significantly larger number of vehicles from Canada. In addition, based on a survey cf vehicles parked near the beach area, NRC staff estimated that 3 percent of the vehicles were from Canada. Therefore, it appears reasonable to assume that 3 percent is the upper limit on the number of French-speaking residents of the area. This appears to be an upper limit because it is unlikely that all of those vehicles coming from Canada are occupied by people that speak or understand only French because Canada is a bilingual country.

The non-English speaking population should be considered under the general area of problems that might be addressed during an evacuation. Other such problems would include accidents, vehicles running out of gas, and vehicles that suffer mechanical failures. It is considered that these fact)rs are not a significant problem. Vehicles blocking traffic flow on a road segment for any of the above reasons would be isolated incidents that could generally be cleared in a reasonable amount of time, or otherwise bypassed. However, this is not to imply that provisions should not be made in the detailed planning 13

I for evacuation to provide a means of accommodating these limited problems. A few wrecker vehicles, tow trucks and other service vehicles needed to handle these emergencies could be deployed within the EPZ after a decision to evacuate had been made. In addition, an information program for the area could be implemented in a manner consistent with the fact that not all drivers speak English. It is common in Canada and other foreign countries to use symbolic signs to convey messages to drivers, for example. To repeat, this is a detailed planning requirement that should be addressed in the planning phase.

14

ANALYSIS OF EVACUATION TIMES This section of the report will discuss the methodology of the CLEAR model for loading and advancing vehicles on the transportation network and report the results of the analysis. The only scenario being evaluated in this report is the peak summer population during normal weather conditions. Normal summer conditions refer to clear weather, good visibility and dry pavement. Degraded weather conditions are inconsistent with the assumption of a peak transient population. This analysis is essentially a benchmark to compare studies and not a complete evaluation of all aspects of an evacuation time analysis.

METHODOLOGY The methodology used in CLEAR to load traffic onto the road segments utilizes the distribution function method allowed in NUREG-0554. The distribution function method involves determining the time distribution of loading, and the maximum loading time. It was determined in this study to use two separate loading functions. One loading function was used for the beach and another loading function was used for the general population. The loading function aforfew the beach areas was determined to be shorter belongings and get to their vehicles. because people need on y) pack The maximum departure time 1 was set at I hour, with 25% of the population loading during the first 15 minutes. Of the remaining population, 25% would depart during the next 15 minutes, 50% over the next 15 minutes, and last 25% would depart during the final 15 minutes.

For the remainder of the population, a different loading function with a longer time distribution was used. The maximum departure time was set at 90 minutes with only 10% of the population simulated to depart during the first 22.5 minutes. Of the remaining population, 25% would depart during the next 22.5 minutes, 50% over the next 22.5 minutes, and the last 25% would depart during the final 22.5 minutes.

Finally, please note that the total evacuation time includes 15 minutes for notification time. Thus, it is assumed that no vehicles will depart during the first 15 minutes after the decision to evacuate has been made. Therefore, a 15 minute time period is added to the time estimate calculated by the CLEAR model because the mathematical simulation begins when vehicles are ready to depart.

15

RESULTS The results reported in this paper are based on calculations using the CLEAR model. The preceding discussion details all of the assumptions incorporated in the model that were necessary to perform these calculations. No modifications were made to the model as it is described in NUREG/CR-2504 (PNL-3770).

The CLEAR ETEs are the result of an iterative process of analyzing the evacuation times. The first step in this process was the selection of traffic 4

routings (evacuation trees) that were perceived to be the most logical for the evacuees to exit the EPZ. The first set of CLEAR ETEs revealed that more efficient routings could be selected to reduce the evacuation time. This process provided additional information on the interactions of the transportation network and the evacuating traffic. No attempt was made to totally optimize the routings or to thereby minimize the evacuation time estimates. Therefore, the evacuation time estimates could be reduced by further optimization of traffic routings. It is not, however, advisable to select routings that would be considered unacceptable to evacuees or that would be unknown to evacuees unless a detailed traffic management plan and information program were in effect.

The results of the first computer processing (runs) using PSNH data for the eight evacuation trees are presented in Table 4. The results of these calculations indicate that evacuation tree No. 7A had the longest evacuation time. This evacuation tree includes traffic from both Salisbury Beach and Seabrook Beach, plus half of the traffic from Hampton Beach. As a result, some additional calculations were made which modified the distribution TABLE 4. Initial Evacuation Time Esimates Calculated Using the CLEAR Model for a Peak Population Scenario in the Seabrook EPZ (Initial Runs, PSNH Data).

Evacuation Evacuation Time Estimate

Tree (Hours: Minutes) (Minutes)

No. 1 8:55 535 No. 2A 4:10 250 No. 3 2:25 145 No. 4 6:00 360 No. 5 3:10 190 No. 6 4:15 255 No. 7A 12:00 720 No. 8 5:15 315

Includes 15 minute notification time.

16

of the evacuating traffic in this area. These additional calculations separated the evacuation trees at the Hampton Harbor drawbridge (see evacuation trees No. 28 and No. 78).

I In thu second run using PSNH data, all of the Hampton Beach traffic was routed north onto Route 51 which reduced the volume of traffic southbound on New Hampshire Route 1A by 8775 vehicles. The results of these reruns, shown in Table 5, indicate that by judiciously routing the traffic it is possible to reduce the evacuation time below the previous estimate. The resulting ETEs for evacuation trees No.1, No. 28 and No. 7R are all roughly equivalent ranging from nine to ten hours. The initial routings resulted in evacuation tree No. 7A, which included New Hampshire Route 286, having the most congestion.

TABLE 5. Recalculation of Evacuation Time Estimates Using the CLEAR Model for a Peak Population Scenario in the Seabrook EPZ (Rerun for No. 2 and No. 7, PSNH Data).

Evacuation Evacuation Time Estimate

Tree (Hours: Minutes) (Minutes)

No. 1 8:55 535 No. 2B 10:10 610 No. 3 2:25 145 No. 4 6:00 360 No. 5 3:10 190 No. 6 4:15 255 No. 7B 9:25 565 No. 8 5:15 315

Includes 15 minute notification time.

As a result of rerouting the Hampton Beach traffic, the ETE for evacuation tree No. 2 increased while the evacuation time estimate for evacuation tree No. 7 decreased. It should be noted that in evacuation tree No.1 the critical road segments are not within the EPZ. The bottleneck locations occur

in the Portsmouth area as traffic converges onto a reduced number of lanes.

Evacuation time estimates were also calculated for the NRC demographic data described previously using the CLEAR model. Evacuation times were calculated for the second iteration of evacuation trees (i.e., 2B and 7B). A summary of the ETEs is illustrated in Table 6.

17

TABLE 6. Calculation of Evacuation Time Estimates Using the CLEAR Model for a Peak Population Scenario in the Seabrook EPZ. (NRC's Demographic Data)

Evacuation Evacuation Time Estimates

Tree (Hours: Minutes) (Minutes)

No. 1 9:40 580 No. 2B 11:40 700 No. 3 2:20 140 No. 4 6:15 375 No. 5 2:45 165 No. 6 3:40 220 No. 7B 10:25 625 No. 8 6:25 385

Includes 15 minute notification time.

In order to determine the impact of using NRC's demographic data on the calculations, ETES were prepared using the CLEAR model and the same evacuation trees. A comparison of these results versus the results obtained using PSNH's demographic data is presented in Table 7.

TABLE 7. Comparison of Evacuation Time Estimates as Calculated by the CLEAR model for a Peak Population Scenario in the Seabrook EPZ Using Two Demograph Data Bases.

Evacuation ETE Using PSNH NRC Data ETE Time Difference Tree (Min) (Min) (NRC-PSNH, Min)

No. 1 535 580 +45 No. 28 610 700 +90 No. 3 145 140 -5 No. 4 360 375 +15 No. 5 190 165 -25 No. 6 255 2E0 -35 No. 78 565 625 +60 No. 8 315 385 +70 18

DISCUSSION In discussing the results of this study, it is desirable to compare and contrast the results with two other studies. One study was done by Allan M. '

Voorhees)andThe Associates for thewas second study Federal Emergency by PSNH, PublicManagement Agency Service of New Hampshire, and (FEMA){ 3 was initially submitted in August of 1980. The latter study uses the EVAC model developed by HMM and Associates. In addition, Public Service of New Hampshire submitted a supplement to the initial study ; n July,1981. A discussion of the results of this supplemental studyta< will also be included in this section.

There are several aspects of the FEMA study which make a comparison with the CLEAR results difficult. According to Table 7 on page 48 of the FEMA study, the total number of vehicle trips during the summer Sunday scenario was 65,227. This number is significantly less than the 87,996 vehicle total reported by PSNH and the 95,822 vehicle total developed by NRC. Therefore, the traffic voluaes used in the CLEAR calculations are 35% and 47% larger, respectively.

There are additional considerations that make it difficult to proportionately scale the FEMA analysis to the CLEAR calculations. The traffic routings outlined in the FEMA report utilized principally U.S. Route 1 southbound. The FEMA report did not utilize the I-95 expressway to its fullest potential. In addition, the FEMA report assumed that U.S. Route 1 southbound would be operated with the center left-turn lane as a continuous outbound lane for evacuating traffic. Consequently, it is difficult to scale any of the CLEAR calculations to those reported in the FEMA study.

It should also be noted that the FEMA report indicated that ineffective traffic control could increase the evacuation time estimate from six hours and 10 minutes to 14 hours1.62037e-4 days 0.00389 hours 2.314815e-5 weeks 5.327e-6 months and 40 minutes. A lack of documentation prevents an assessment of the rationale for this statement. It appears that the FEMA study may have assumed a reduced network capacity to account for traffic accidents or mismanagement. It is also not possible to determine whether the longer time estimate results from revisions to the assumed evacuation traffic routings.

One similarity between the FEMA results and the CLEAR results is, however, noteworthy. It was determined by the FEMA analysis that the maximum delay would occur due to the evacuation of the Salisbury Reach area, as indicated on page 62 of the FEMA report. This result is consistent with the CLEAR analysis, which indicates that the Salisbury Beach area would be one of the critical areas. It should be noted, however, that this does not suggest that the Hampton Beach area is not critical in the evacuation process. In fact, it is necessary to route much Hampton Beach traffic to the north in order to obtain the estimated evacuation time. This necessity is act completely (a) Personal correspondence from John D. Vincentis Public Service of New Hampshire to the U.S. Nuclear Regulatory Commission dated July 31, 1982.

19

consistent with the route which may be p:;rceived by motorists to be the most expedient evacuation route. In other words, motorists may perceive that they should evacuate to the south even though their most expeditious route is to the north. The effect of routing traffic to the south can be seen in the results of the initial run of evacuation tree No. 7A in Table 4.

The estimate for the 360 degree evacuation of the entire 10-mile EP7 for a peak summer weekend population reported by PSNH was 6 hours6.944444e-5 days 0.00167 hours 9.920635e-6 weeks 2.283e-6 months and 5 minutes. A notification time of 15 minutes should be added to this estimate to determine total evacuation time. Therefore, the time estimated by PSNH is 6 hours6.944444e-5 days 0.00167 hours 9.920635e-6 weeks 2.283e-6 months and 20 minutes.

There are several interesting aspects of PSNH's methodology. PSNH allowed a portion of the evacuating traffic to travel in a direction that was not consistent with general radial dispersion as suggested in NUREG-0654. The concept of general radial dispersion implies that traffic should be routed in a general direction away from the nuclear power plant site. The methodology used by PSNH allowed vehicles at some of the critical intersections to evacuate in a nonradial direction.

A portion of the traffic evacuating southbound out of Seabrook was allowed to turn right onto the entrance ramp to I-95 northbound. This means that a portion of the traffic that was initially evacuating in a radial direction to the south was allowed to change direction and evacuate on I-95 northbound.

Although non-radial evacuation routings could be desirable under certain circumstances, such routings were not used ni the CLEAR analysis in order to provide a more conservative estimate of the evacuation time. This difference was also observed when estimates performe yyPSNH'scontractorwerecompared with CLEAR calculations for another site. Si Nonradial dispersion was incorporated into PSNH's analysis at several critical intersections in the Seabrook EPZ, including one intersection in the Salisbury Beach area. Specifically, the intersection is at the junction of New Hampshire Route 1A and U.S. Route 1. Traffic westbound on New Hampshire Route 1A approaching U.~., Route 1 was allowed to turn left onto U.S. Route 1 south and proceed straight on to New Hampshire Route 110.

In addition, a portion of the traffic was allowed to turn northbound onto U.S.

Route 1 in the general direction of the plant. According to PSNH's methodology, this volume would increase as congestion in the vicinity of this critical intersection increased. The volume directed to the north ranged from 5 to 10 percent of the volume evacuating from the Seabrook Beach area. This dynamic routing algorithm utilized by PSNH would produce a lower evacuation time than that produced by the CLEAR model.

In summary, PSNH's approach to calculating ETEs allows for a greater optimization of the transportation network within the EPZ than that used in the CLEAR analysis. In order to achieve this optimization, a higher level of traffic control would be necessary than under the assumptions used in the CLEAR calculations. Whether or not this level of traffic control could be achieved would depend on the evacuation plans developed for the Seabrook EPZ.

20

The 610 minute and the 700 minute evacuation time estimates by the CLEAR model did not require the previously mentioned assumptions. This does assume, however, that there will be traffic control at the major bottleneck locations. Consequently, the time estimates are not the maximum evacuation time estimate that could be calculated for the Seabrook EPZ.

The point of this discussion is to emphasize that the evacuation time estimates are, in fact, estimates. Their value is in determining critical planning factors and needs. For example, the analysis reveals that there is a critical need for the planning of evacuation routes. Depending on the degree of refinement of these routes and the amount of traffic control that could be obtained during an actual evacuation, the time estimate can be reduced.

Alternatives are available to reduce evacuation times. Traffic signals could be operated in a manner that would maximize flow in the direction of the evacuation. In some instances, reversal of the normal flow of traffic could also be appropriate. For example, traffic outbound from the Salisbury Beach area approaching the intersection of U.S. Route 1 could be operated in a reverse flow manner such as to maximize the traffic flow out of the beach area. This would necessitate that some traffic, such as emergency vehicles, would have to use alternate routes to obtain access into the Salisbury Beach area. For example, New Hampshire Route 286 could remain in a two-way traffic flow mode if New Hampshire Route 1A westbound from the Salisbury Reach area is operated in a reverse flow manner. This would allow emergency vehicles access to the Salisbury Beach area using New Hampshire Route 286 into the Salisbury Beach area.

Other traffic management opportunities also exist for the area. For example, outbound traffic on the Exeter/Hampton Expressway (Route 51) could be operated in a one-way traffic flow mode on the bridge over the I-95 expressway. This would allow more efficient routing of traffic entering the area from Route 101C and from Route 51 to attain access onto the I-95 expressway. This special traffic management would require alternate routing of traffic eastbound into the area using Route 101C.

Still more traffic management opportunities for reducing evacuation time exist in the Seabrook EPZ. These include the rerouting of traffic northbound on U.S. Route 1 and New Hampshire Route 1A through the Stratham area. In addition, as indicated in the FEMA report it is possible to operate U.S. Route 1 in a two-lane traffic flow mode by utilizing the center turning lane as a second lane in the direction of evacuation.

As a final note, there are other opportunities for expediting the evacuation process in the area. For example, there are on-ramps to the I-95 expressway, just south of both the Exeter/Hampton Expressway (Route 51) and New Hampshire Route 101C, that are used currently only by maintenance vehicles. It is possible that these ramps could be utilized in the evacuation through the use of special traffic control.

It must be emphasized, however, that all of these special traffic management techniques require advance preparation. In some cases, it could involve the 21

deployment of traffic control personnel, the utilization of special signing, the deployment of traffic cones, or any of a number of other techniques in order to achieve the desired traffic flow.

In sunmary, the various calculations indicate that there is a wide range of .

evacuation times applicable to a peak population scenario in the Seabrook EPZ. The range of values appears to be from a lower estimate of slightly more than 6 hours6.944444e-5 days 0.00167 hours 9.920635e-6 weeks 2.283e-6 months to an upper estimate of 12 hours1.388889e-4 days 0.00333 hours 1.984127e-5 weeks 4.566e-6 months or more. The lower estimate requires extensive traffic control management and routing techniques while the upper limit reflects traffic conditions without the benefit of a sound traffic management plan. Furthermore, the upper limit of 12 hours1.388889e-4 days 0.00333 hours 1.984127e-5 weeks 4.566e-6 months does not represent an absolute maximum time. Without a traffic management plan, the potential for inefficient routings and disruptions is increased.

Although the calculations reported in this study deal only with normal weather conditions, it is unlikely that a severe adverse weather condition would exist during periods of peak population. The only likely adverse weather during a peak population scenario would be summer rain. There could be some minor reduction in roadway capacity due to such rain showers. It is unlikely that a major severe weather condition such as a hurricane or snow would exist during a peak population occurrence. The summer weekends that are represented in this study comprise 6% of a year's duration.

There are some miscellaneous considerations that should be addressed in this study. These factors primarily concern issues raised by some of the local residents during the preparation of this study. One concern was the drawbridge over the Hampton Harbor entrance. This concern was addressed in two ways.

The schedule and priority of operation for the bridge was investigated during an emergency situation. Here, the question is whether or not boats would be

able to preempt vehicular traffic. According to the New Hampshire Department of Civil Defense, the bridge would not be operated in a manner inconsistent with full utilization of the roadway transportation network during an evacuation.

In addition, the results of the CLEAR analysis indicate that it would not necessarily be desirable to evacuate any significant number of residents of the Hampton Beach area across the drawbridge to the south. This is due to the fact that a more efficient utilization of the road segments would be acheived by using the Hampton/Exeter Expressway (Route 51), as well as other routes to the north.

Another concern raised by the local residents was that on some summer weekends traffic congestion has been observed fcr periods up to 6.5 hours5.787037e-5 days 0.00139 hours 8.267196e-6 weeks 1.9025e-6 months along New Hampshire Route 1A southbound and along New Hampshire Route 286 westbound. As was previously indicated, there are two reasons why this traffic delay is not representative of evacuation conditions for the area. First, optimization of the traffic flow during an evacuation would route the Hampton Beach traffic to the north, thereby alleviating much of the observed traffic problems on New 22

Hampshire Rout? 1A and New Hampshire Route 286. The traffic leaving for home 4

observed normally on a summer weekend includes a large amount of traffic from the Hampton Beach area.

The second reason concerns flow rates attainable during an evacuation. The

! traffic delays and flow rates on some summer weekends are representative of j the current operation of traffic signals at the intersection of New Hamphire Route 286 and U.S. Route 1. This is not, however, indicative of achievable 4

traffic flow under a good traffic management plan. It was observed that the 4

congestion occurring along the route exists because people are not evacuating the area but rather gaining access to and from the numerous businesses along the route. This type of activity would be minimized during an emergency evacuation.

4 The evacuation times calculated for the peak population scenario described in this study are relatively long because the added transportation demand of the transient population cannot be rapidly accommodated by the transportation network. This situation does not exist throughout the year, but occurs primarily during the summer tourist season and is most acute on summer weekends when the weather is favorable. Therefore, evacuation time estimates reported in this study are representative of conditions that occur during a j small portion (6%) of the year.

Furthermore, evacuation time estimates for the peak population scenario are not indicative of the evacuation time expected for permanent residents of the area during the off-season. Calculations of evacuation times for an off-season case indicate that evacuation times are r estimates for the peak case in the Seabrook EPZ(educed to approximately

3) (see Appendix 60% of IV). Further discuss by FEMA 3 and PSNH o ofoff-pgk ases and associated time estimates have been prepared

. The effects of adverse conditions and peak i evacuation times for other sites have been summarized in previous work}ogds 91 on i The major traffic problems predicted for the Seabrook EPZ occur primarily in the areas east of the I-95 expressway. This is due to the scenario being evaluated which assumes that a very large population will exit from the beach area when the evacuation is declared. Areat located west of I-95 should experience essentially no significant traffic problems during the evacuation.

It should be emphasized that with a thorough traffic management plan, it is possible to attain more effective use of the traffic capacity readily available on I-95. For example, the Seabrook town population could be initially evacuated south on some of the local roads over to I-95 This would be effective because it would avoid hindering their northbound.

evacuation because of the evacuation of the Seabrook Beach population.

! (a) Personal correspondence from John O. Vincentis, Public Service of New Hampshire to the U.S. Nuclear Regulatory Commission dated July 31, 1981.

(b) Personal correspondence from Arthur M. Shepard, Public Service of New Hampshire to the U.S. Nuclear Regulatory Commission dated August 4,1980.

23

- -- .- - , , , n -,-,n- . . - - - - c, , , , ,-

i CONCLUSIONS According to the data available for the peak number of vehicles evacuating the l Seabrook EPZ, it appears that evacuation times ranging from 6 to 12 hours1.388889e-4 days 0.00333 hours 1.984127e-5 weeks 4.566e-6 months could be anticipated for the area. The range is a result of the assumptions and the demographic data bases that are used in the calculations. In general, the lower estimate represents a high level of utilization of the available transportation network. This could be achieved either by utilization of a high level of traffic control or through extensive education of the population as to alternative evacuation routes. The upper estimate represents a less optimistic assumption concerning the ability of the transportation network to be utilized to its maximum efficiency. Until the detailed local evacuation plans are developed, it is difficult to specify a smaller range of evacuation time estimates.

The evacuation time estimates computed by PSNH are consistent with the assumptions and demographic data base used in their analysis. The assumptions include implicitly attaining a high level of efficiency and utilization of the available transportation network. The appropriateness of these assumptions will ultimately be judged in the context of the local plans developed for the area. Furthermore, this study emphasizes the need to develop a detailed local evacuation plan for the Seabrook EPZ. Because it has been determined that the vehicle demand estimates for a peak population scenario used by PSNH are lower than those developed by NRC, PSNH's evacuation time estimates could be adjusted to reflect those differences. The percentage increase in PSNH's ETE using the NRC demographic data would probably not be greater than the percentage increase recorded in the comparative CLEAR ETEs. The basis for this statement involves the aforementioned methodology and assumptions used by PSNH in preparing an ETE.

The data presented in this report suggests that an evacuation time of 6 to 7 hours8.101852e-5 days 0.00194 hours 1.157407e-5 weeks 2.6635e-6 months is possible under peak conditions if a high level of effectiveness and traffic optimization are achieved. An evacuation time estimate in the range of 10 to 12 hours1.388889e-4 days 0.00333 hours 1.984127e-5 weeks 4.566e-6 months represents the time estimate for an evacuation under peak conditions if a relatively unimproved level of traffic control exists.

In conclusion, the results of this study emphasize the need to develop a detailed local evacuation plan for the Seabrook EPZ and the need to reexamine the ETEs af ter these plans are developed. The alternative traffice management schemes discussed in this report aid the optimization of the local evacuation plan.

24

REFERENCES

1. Moeller, M. P., T. Urbanik II, and A. E. Desrosiers,1982. CLEAR (Calculates Logical Evacuation and Response): A Generic Transportation Network Model for the Calculation of Evacuation Time Estimates, NUREG/CR-1534 (PNL-3770), Pacific Bbrthwest Laboratory, Richland, Washington.

2. Ka l tman , M. , 1982. Demographic and Vehicular Demand Estimates for An Evacuation Analysis of the Seabrook Station, U.S. Nuclear Regulatory Commission, Washington D.C. Docket No. 50-443, 50-444. Accession No.8206040382.

3. Federal Emergency Management Agency (FEMA). 1980. Seabrook Station Evacuation Analysis, Final Report, Estimate of Evacuation Times, Alan M.

Voorhees & Associates, McLean, Virginia.

4. These average household size factors were from Appendix B of reference 3.

5. This factor was for the resident population group from Table 42 of reference 3.

6. General Highway Map, Rockingham County, New Hampshire,1968, and Portsmouth Quadrangle 7.5 minute Series Topographic Map by the United States Department of the Interior Geological Survey, Photorevised 1972.

7. U.S. Nuclear Regulatory Commission, Federal Energency Management Agency, 1980. Criteria for Preparation and Evaluation of Radiological Emergency Res30nse Plans and Preparedness in Support of Nuclear Power Plants, NURIG-0654, FEMA-REP-1 Rev. 1, Washington, D.C.

8. U. S. Nuclear Regulatory Commission, Office of Nuclear Reactor Regulation, Safety Evaluation Report Related to the Construction of Pilgrim Nuclear Generating Station, Unit.th). 2, Docket No. 50-471 (Boston Edison Co., et al), NUREG-0022," Supplement No. S to NUREG-75/054." May 1981. Wash, D. C.

9. V. S. Nuclear Regulatory Commission, 1981. An Analysis of Evacuation Time Esimates Around 52 Nuclear Power Plant Sites, NUREG/CR-1856 (PNL-3662) Volume 1, Washington, D. C.

10. U. S. Nuclear Regulatory Commission, 1980. Analysis of Techniques for Estimating Evacuation Times for Emergency Planning Zones, NUREG/CR-1745 (BHARC-401/80-017), Washington, D. C.

REF-1

4

, I

APPENDIX I '

This appendix includes the component automobile demand estimates used to calculate the total automobile demand estimate for the peak population scenario for PSNH and NRC.

( ,e i

e i

a 4

i 4

1 d

l l

4 1-1 i

l l

AUTOMOBILE DEMAND ESTIMATES FOR AN ESTIMATED 1983 -

PERMANENT RESIDENT POPULATION

IN THE SEABROOK EMERGENCY PLANNING ZONE

\ N 492 [ ,.,.

4 . ,I <*

...'f 419 8213' #*** .*

NNW NNE '

.11,

~

,.i

c. * . , ' ' n :;. .,; ,11 f*

293 1704 / *

.g, f ,

NW '

$.** i N E fe f

'". . , .~.c ... 2 Y b., .b 843 2649 YE NOR BEACH

.c wa: .

.m

?*/ t ,,, - ,. h 3563 ( 1000+ / . . ,

, .* ,) 10 MILES

1090 an . RYE BEA. ~ , ' - .

WNW * * *. E5E "'

650 228 597 1535 .* -

' lIf s-

-n d ,, '

136 _ 1124 * .

I ,

@ m y - . {'.. , . .. ,

, f_ y 295 gsi ., ' 's. , # 5 MILES I <

g .( qt .

ca a ><*

MN. .+c ,

A C,H.'

W 1181 438 % so. . ,*" 2 M$LES

6

? ... ,. . :. -

>t

% 'v j a

2483

.. f N 4-E.W f. g . .. :. , ,

.. ^y gASSA 1343 . j 89 . - -

1,qi 4498 378 ,

ABR. K C'H .

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,,,, , y WSW - [- ..

t., '

. ESD

' w;;

222 .

I

't.'.,

. . .; .M;. . .i 2171 * **,...,I

. : Ia * -

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l 8 3556 '*

/SE ; -

), *

- ' n-

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. . ' 'F.. .

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2713 gt,

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0 1 2 3 ..* .

~

la'

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SS'Ei2 .

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MILES

[SSW 291 IS .

j l 36424l PSNH VEHICLE TOTALS TOTAL SEGMENT VEHICLES RING RING TOTAL CUMULATIVE o To to utts MILES VEHfCLES MILES VEHICLES 0-2 2169 02 2169 l

l 2-5 9275 0-5 11444 5 10 24980 0-10 36424 10-E PZ 12071 0-E PZ 46495 '

I-2 -

l i.

AUTOMOBlLE DEMAND ESTIMATES FOR AN ESTIMATED 1983 SEASONAL RESIDENT AND DAILY TRANSIENT POPULATION IN THE SEABROOK EMERGENCY PLANNING ZONE '

i 1

\ N [ @ ,5 j

NNW A .*

. .f h NNE ,

..* , ' . - ;J

/ :.".* ..

N 344 -

NW E 'I $d*J

' ']

150 190 k[YE NOR il$ACH I

, . ,m . ,

& 4*._.-

,390 ( #

17711 .

t..- * . ) 10 MILES,*

K * . RYE BEA .

WNW 355 '.**

'EEN .

150 40 '178 m ,., .

350 __3932 * .-

l e c.3 w: ..

26 '. .'" , . (5_M_lLES * - ,.

2984"

a m

s

. . A..C.H.-

W 152 3113 noa ,,, '; * '*,

~ h ,, ,'2ML- y:.- ,

. . . b, t

68 n* . ... /

:. :w~

7-ene.a.qC,"Ns 148

..g };;. ' -

g.. gASSA 41138,

. _ _d; 342 67 510 ** *

423 Q- g-g .. .

~

.g.

..'e....--

WSW - ..

.. ;e .,Y;

[ ,,. s ,

.p ,

sy-

t. .* . [* 7**. *

[ 64 . ** 3 (N. . ..N..*.

~~~

[. .' * = ,

b 215 '.4370;

= _.

,SW ,.-*. . . - f SE f. *

,. -m.-. s j 545 .:;:. -

l 0 1 2 3

.' ' . , . l.- * - - - * ^

4 N ST. . .' ..

MILES [SSW " ,, ( g -- , ,

IS .,., -

l 39501 l PSNH VEHICLE TOTALS I

TOTAL SEGMENT VEHICLES I

O TO 10 MILES RING RING TOFAL CUMULATIVE MILES VEHICLES MILES VEHICLES 0-2 12722 02 12722 25 17926 0-5 30648 5 10 8853 0-10 39501 1-3

i AUTOMOBILE DEMAND ESTIMATES FOR AN ESTIMATED 1983 PERMANENT RESIDENT POPULATION IN THE SEABROOK EMERGENCY PLANNING ZONE

\ @ Y I'

311 N 1908[ 7.

t ,

NNW I NNE 6198 ,

I

? ' . . -

1154

2334 *a 283 .

NW *$' - N E' 175 -

932 ,,g

,$-. ~ ~ . .

RYE NOR BEACH - - - - -

e. .

k E824 *

._._J_

; 10 MILES

3426 s 759 s7s cn . RYE BEA .

WNW 1545 g ,.f * . *.

229 ,

527 y9, ,

"3"- 1144 -

\ F ~>- * .

@l la , .

~

239 n ,, ..3 ,3 5 MlIES i ,

I i ,, ,

HA ACH 833 804 .

~'-

s'e *

W 36s % , i E-2 MLES;'.*:.-

~ - ~ - -

.- ,; 7 - ,,, ,,, u9: : . .

.* -a a p.* *

/ t:i;.

tw S."pgg1B

,,, ==g gSSACgstus 117e 5 3880 .ge g ABR K 'C'H * .- .

151 ;.

~y, 187 WSW h[ [

'f a

+

, ESES

f, ,.

1ess .

3246

' ,1

.** b *g.**.,**.

4 (r.)

SW

~

3s,4 - ., , g '"

'123 'U.**. .

2si. '.0: . ,.

0 1 2 3 ': * . ,

jSSW ~ . 5S'E . - = . ' .

MILES / 276 *. . .

IS

l 32980 l NRC VEHICLE TOTALS RING RING TOTAL CUMULATIVE TOTAL MILES VEHICLES MILES VEHICLES SEGMENT VEHICLES 02 2134 0-2 2134 2-5 8853 0-5 10987 5-10 21993 0-10 32980 10 EPZ 11053 0-E PZ 44033 I-4

AUTOMOBILE DEMAND ESTIMATES FOR AN ESTIMATED 1983 SEASONAL RESIDENT AND DAILY TRANSIENT POPULATION IN THE SEABROOK EMERGENCY PLANNING ZONE 1 N

/ .

NNW NNE .

S l ** . '

531 T - ***

267 **'

\ .

iEE'-

NW ,-l'@*'

190 ~g

. . . . . . , . . u . n.

J:. RYE,NO.R

~ n. ~

..BE.~AC,~H n

ra p

l *

\ ,3562. _ ._ %

428 ?.E ., 110 MILES *

"~ ~"

1452 .. . RYE BEA .

WNW 180 b ,V 51 l

. ,.; , {

190

613 -

5761

I .** * .

@ f9 l e

, vi

,3547, 2,5 3b, ,

. . . . = . .

192

W 3:46 % s.o rf .

.'.'.". 2 IdllLEh ;*.-*.,. *. *

$. b

.. ;,~~. -,,,,..,s

+ .

EW

- f. leE**hS gASSA g

19s

.*h .24s ,

,q 638 . 51 ,

521 '!,.

.T, .. ., . . , . .

WSW **' *

[ ,,. #

.. . (ESEt 7

. g,-l. .i.**,*,,~.,. .

47 .

. N

531 ..' * . * * * . * - *. **

- * ?.*,**..*** .*

SW

@' '.r572e .- .

a

's. . - S,E4.! .

/ 1466 * * * *

l 0 1 2 3 **..,

MILES

SY.' . . .

[SSW IS -:_.,

l51789l NRC VEHICLE TOTALS TOTAL SEGMENT RING RING TOTAL CUMULATIVE VEHICLES MILES VEHICLES MILES VEHICLES 0 TO 10 MILES O-2 15856 02 15856 2-5 22163 0-5 38019 5-10 13770 0-10 51789 I-5

i APPENDIX II l

This appendix illustrates the eight evacuation trees used in the initial runs and the two additional evacuation trees used to calculate the ETEs.

11-1

SEABROOK EVACUATION TREE NO.1 e._.e => -

,:,c,::. ,.,

N ,,

e' '=,* .

ro 69 I I8 79 84 d- ,

,, NNE 7 76 n .Q.I -

.,.y ,

=

4e .

. ; h,** * . *

4r

,, } ,:* .

so 52 e3 ,

3, ,

as se . .

4, ,,

- q

.o ,

41 63 6 4,*e*' ,

35 36 32 31 . 5.% . *

33 as 62 ,; * .

61 .

s'

29 34

8 60 * !*.'s'e* *

18 3, ao so *: ': ' ' .

26 97 61 69 **,

20 27 .

, ~

1 ,, .;*':. -

10 MILES *

[,*

y,.-

.a

l i.

.4 ENE

>> r. . -

,3 .

s . .

g l

s: -

5 MILES -

't.**.. . .

i.-

.r. . -

g

. ..~i

.. 2 MILES ' ! *,. . .

A- _

. x -, r II-2

AC ATION TREE 9

49

<a a '-:.

N "

NNW NNE ::.

l ..

.c. r 5.*

lt*

eo ,:

n .: . ..

..:.s.-

.,{Y .

....r: .

,, n

i, ,

.c. . . ... =

.? ,, n

. n (. -

>> * ,ov,. :. ; . .

> ,n ., 3 s..

1 .

s *$*

to ,, y 5 MILES

,1, ;!:

'....j: -

x

~. . .

. ,.:.- ."2 M!tes : . .. .,

W,- :

II-3

Ev CUATION TREE N0 49 4

f.

N

NNW ;;:'

NNE '

4, n 4.'N:..

.0

3. ?l .-

- i.

' se

.,[. . .

,o Iti 12 ::.

u. .. :

. c. . . , .

s I g: : .

5 M lle S

';, .. 2..:mu.es - : .. . , . .

A , ~- ...

^

11-4

1 SEABROOK EVACUATION TREE NO.3 2

n N 2, w 2. ,.-

28 24 27 17 23 16 12 21 gg 15 22 l

NW , ,

c

- ES ;. .

\ ~~.

5 MILES y.. . .*': '

...~:

," -M

.' . 5 2 MILES'

/

i II-5

a. -e as_--_w _a n_.us ..,a - a __- __,_t , _ -,, ,____w SEABROOK EVA UAHON M N

NNW

2 NW

27 u

26 26 22 3 32 40 39 24 34 30 33 18 16 23 20 16 WNW 12 17 10

, e 6

W '

so gtLES ' s I

h gtLES , , ,

\

2 gtLES

{,l-p . % .. ;.

\

~:- , , '

II-6

1 SEABROOK EVACUATION TREE NO.5 e .,

27 10 MILES WNW 33 3, w 1 5 MILES 1.

y(

1 n

20 3

2 MILES ,

W

i

.A.

5.Q WEk

'i

e 1 .

WSW W -

l II-7

l l

SEABROOK EVACUATION TREE NO.6 M ES ,

5 MILES ,,

W - -

" M 10 MILES ,

.. g ,

WHAMPbfSETTS

- "a ' *

,,, f.*$sf$u. ,.

14 1 y ,, , .

n WSW ,. ,,

,e 28

28 l

l i

l SW SSW _

S II-8

I

]

SEABROOK EVACUATION TREE NO.7A

,N. ::.:.::.;

g."

,, .. ' gy: .

.....,h..

n . .; 2 M.ILES

,, u "... ,

.# *

N., n .. . ..

HA U.

5 MILES '

afl h .

2. '. **

,g'. ; ,

's'sACHusEUS ,,

u ,. ,, n >= *i'.

3

,G,'! * ,

w - .

.p - ,.

10 MILES .

a sw ?.*. . .

z.* . , .

SO ;. . .

n .:. . .

SSW .

n '

S ::. . _ .

II-9

SEABROOK EVACUATION TREE NO.7B l

19 .I

?t. ' : -

, ! ,,i . . .

' 2 MILES

~ .. ..

a.

2a . * .

9, . 5 MILES . y/ ,, ,, .

SSA = . .

4g-:. . u

\Y,:,. :

i '.. . .

. 'l 10 MILES

\ ...

8 *

.9 .

SW . ;

so ..-.

,,SSW ...

S :':

11-10 l

1 - . . . . .

- _ __ .= __ __-

SEABROOK EVACUATION TREE i NO.8 1 1

l

t. ' -

.~.i 2 MILES. . .

l W..

.. ~ .. ! 1,

\PS ** 5 MILES .'.'.

s s ., ,. . . . . ,

ceu :;* .

. i

..i

+ s, :'. ..

io .. . . . . .

sa ,,

. .. , . . .. .s -

2s , . ;.', . ,

SW u

3. . '. '. .

O" 10 MILES i. ,

' i.: ' . '

SSW gg _ _ - - - - -

.. . S S E 2s fS II-11

APPENDIX III This appendix contains the input data for CLEAR code runs. This material

details the input . data for each road segment of the Seabrook EPZ.

l Pages III-1 through III-17 show the data inputs based on PSNH's demand

! estimates for the eight original evacuation trees and two revised evacuation l trees that were used in this study. Pages III-18 through III-29 give the input data for the eight evacuation trees that were analyzed using NRC's demographic data.

III-1

FVACUAT104 TREE huuSER OMF FOR SEARROOK 70.1 4 CLEAR WOFLLER CLfAR BATTELLE CLEAP MOELLER CLEAR LUs 3 DFLTs 12 TIPS 25 FRACTs 0.25 4AICFPs 3A00 POPVFHs 1 LGCODEs 4 FLopATs 1500 mI45PDs 35 E!hos 0 ZFIVs 3 7tFNs 6 ZEPZs 8 157Gs 0 FNs a5 FPZs 13 20SE 1 POPZas 952. NPDSa 3 LENp0$s 19800 Z4DD3 1 Limps 2 IEus 600 PADIsa 5 houvELs 45 WLANESs i NPSECs 3 7mR03 2 LINKS 16 LENS 60n RADISs 5 NomVELs 45 gLAhESs I hR5ECs 0 Z6pDs 3 LI4Fs 2 f.E%s 3no pADISs 5 wouvtLa 10 htA4E5a i usSECs t ZONE: 2 POPrks 171). upD$s 9 LENRDSs 22800 ZmRDt 4 LI4Fs A LENS ROO WADISs 5 40mWEL= 30 hLANESs 1 NRSECs 7 Zhp03 5 LINrs 7 LENS 600 kADi$a 4 40PVELs 30 hLANESm 1 4RSECs 6 Zuppt n LimFu 7 LLus 2000 PADISm 4 NOMVEta 30 hLAbfSu 1 NASECs 5 Zhpot 7 LIhKm e LEms 32n0 PAOISm 5 404VELs 30 NLANESm i NASLCs 4 7490 8 LINNs in LE4s 300 EADISs 5 houYFLs 30 KLANE$a 1 NR5FCs 0 7hDOS 9 LINKS 19 LENS 500 RADISs 9 40mVELs 3n htA%ES 1 NASECs 0 2490: 10 Linus 22 LE4s Ann RantSa % 40*VELs 30 48AhESs t NRSECs 0 Zepht 11 LIhFs 12 LLNu 3n0 RALI5m 4 h0mVELs 30 NLA4FSs 1 4RSECs 0 ZmPO 12 Lihrs 24 LF1s 1960 PADI5m 9 408vELs 30 hLA4L5s 1 N4 Secs 0 204t* 3 POPZhs 5056 MPD5s 3 LFhkDSs 10100.

249et 13 Lik's 15 I.LNs 300 RADISs % h04VELs 30 mL&4E5m t hRSECs 14 24RD 14 LikFs 15 094s 1300 PADISs 9 40=VELs 30 hLANE5a 1 NRSECs 13 Z4RPt 15 LT4es g4 tems 6no NADISs 5 40mVELs 30 ht&hFSm i NRSECs 0 70hEt 4 POPZhu 2046 %RD5s 3 fEhRD5s 36200 TN80s 16 LINKS 14 LE4s 600 98015s 6 N0mVELs 45 4LANL5s t NRSECs 17

- Zm403 17 LIhKa 19 LE4s 300 PAniSs 6 N04WELs 35 4 LANE $a 1 4RSECs 36

((

e 2N90 20*Et 19 LI4rs 5 POPZNs 2R39. hpDSs 28 f,E N s 1300 >AnISs 35 LENhD5m 473e0 6 404VELs 45 NLA4ESs 1 mRSEcs 6 DO Z4PD 19 LIhKm 21 LENS 400 RAD 15m 6 N0mVELs 30 mLAhES: 1 NRSECs @

Z%R03 20 LINrs 17 LE4a in00 RA0tSa 6 w0*Vrts 35 hLANESs 1 4RSECs 0 Zwett 21 Lfhts 26 EE4s 1200 PADISs 6 humVsLs 35 4L44L5m 1 NRSECs 22 24ent 22 Lf4Ks 24 LENS 500 PADIS 6 40mWFLs 30 NLAmESs 1 4RSECs 23 24R03 23 Lihus 25 LLuz non RADISs 6 houvrLa 30 me,A4ESs I hRSECs 24 Z%RO: 24 Likus 25 LE4s 400 RADISs 6 homVELs 35 hLANESs t 495ECs 23 ZWRnt 2% Ltuus 26 LF4s 1100 BADI$s 6 truYELs 35 mL4=E5s 1 NRSECs 22 24PD 26 LINKS 13 LENS 240n RAOI5s 6 N0mVFLs 30 4 LANE 5m 1 NRSECs 29 19P0: 27 LINWu 31 LF4s 2506 RADISs 6 404VFLs 30 WLANESs 1 4RSECs 30 Za80s 29 linum 32 Leks 900 PA0tSu 7 40=VFLs 45 kLANE5s 1 hpSFCs 0 ENEOs 29 LimKm 33 LEms 2300 RA018s 7 404WELs 30 FLANESs I hRSECs 26 Z490: 30 LihPa 31 f, ens 1000 RADISs 7 N0=vtLa 30 hLANESs t NRSECs 27 24 Rot 31 LI4Ks 33 LEps 1000 #A0!Su 7 houvELs in =Lautsu 1 NASECs 26 ZmRDt 32 LINrs 39 LE4s 2400 PADI5s R NO"VELs 45 4LA4E5s 1 NRSEra 35 ZhpDt 33 LfMFs 40 LFhe 2 ROC RADISs 9 N0mvELs 30 NLANE5s 1 NRSECs 36 Z4RD 34 LThWe 37 LE4s lion PADI$a R NOuyELs 30 4L44ESs t dRSECs 0 1980s 35 LihMa 39 f.E4 s 3300 RADISs 8 40mVEL= 30 *LAnr$a 1 WNSECs 32 24RD: 36 LiwKs 40 Leks 1700 PAD 15m 9 M0mvELs 30 4L&4Ess 1 4RSECs 33 Z4RD: 37 LINKS 41 LENS 1000 DADISs R N04WELs 30 NLA4ESs t hR$ECs 0 EMRD* 39 LINF3 6j g(Ng ggQ pap {$3 R NONVELs )@ MLANE$3 g 4R$r(3 ()

ZmRDt 39 Liens 4R LF4s 2500 RADISs 9 NouYELs 45 hLAWESm 1 NRSECs 47 Z4RDS 40 LinFs 42 LFNs 1900 NADISm 9 40mVELs 30 NLA4FSm i N# SECS 41 ZuRO: 41 LJNKs 42 LENS 1100 Rani $s 9 N0mVELs 30 mLA4E5s 1 hASECs 41 ZukD 42 LINFs 53 LLes 400 RADIsa to NOMVELs 30 hLANE5s 1 NRSECs 0 14RD: 43 L1hEs 63 LE4s 1000 PAD 15s 9 40mVELs 30 4LA4ESm i NesECs 0 Z4RDs 44 LThKs 46 LE4s 600 PADISs to NONVELs 30 hLANESs 1 WR5ECs 45 Z4PDs 45 LI4Rs 46 LENS 1600 PADISs to h0=VELs 30 4LA4ESs t NPSECs 44 24P08 46 LINKS 68 LENS 1000 NADI 5s to 404VELs 30 4LANESm I hWSECs 0 24RDt 47 LINKS 49 LE4s 2400 RA01Ss to N04WFLs 30 mLANE5s 1 4RSECs 39 ZNRD 48 L!nra 69 LE4s 1000 RADISs 10 40MVELs 35 NLA4ESs 1 4RSECs 0

1300 #ADISs 10 NOuvEI.s 30 WLAMESs 1 NRSECs 0 24003 49 LINES 52 LF4s t mRSECs 52 2 Nap to LINKS 71 Leks 1700 RADISs in 40mVrt 30 4.44ESs 900 PADISs to N3mVELs 30 *LANESs 1 4pSECs 0 2490 51 LINKS 53 LE4s 30 mLA4ESs 1 hpSECs 50 Zgpna 52 Lf4Fs 73 f. ens 1300 PADISs to Wo*VELs 500 PARISs 10 404VELs 30 4LA4ESs 1 N4 SECS 0 Zenos 53 linus 74 LE4s 20%Es 6 P08'24 s 2771. upDSs 13 LFbpD$s 13600 54 L14Ws 56 Leks 1 00 RADIEs 6 NOWWELs 30 ELAhESs 1 NRSECs 55 ZuRD 1 meSECs g4 i 2 gens 95 Lihus 56 Leks 1999 pan 18s 6 gomyrLa 35 mLANESs 60 LEta 2700 NADISs 7 60mVELs 30 NLANESs 1 NASECs $9 2neD 56 Lf4Ks 1 4pSECs 0 ZhpD 57 Liens 59 LE4s 500 9A015s 7 NOuvEts 30 %LAWFSs 1900 RADISs P N0"vELs 3D *LANFSs 1 4pSECs 0 24pnt 99 LINFs 34 LEPs 59 LihEs 6n fF4s 400 PADISs 7 NouvFt.s 30 4LA4ESs 1 heSrca 54 2NSDI t meSFCs 61 2%p0: 60 LfMEs 62 LL4s 160n pADgS e NOgVELs 30 hLANEsa 67 LF4s son DADISs a go4 vfl.s 30 WLANESs 1 mRSECs 60 74 ppt 61 LINES 63 24 ppt 62 LihFs 64 8.E k s 3200 KADIS =

40myrLa 30 " LAMES 1 Na4ECs se f.E4s 600 Rani $s e 40mVELs 10 *LA4ESs 1 NR$FCs 62 24RDr 63 LINrs 1 hpSECs 65 24RD: 64 LINFs 66 Leks 2000 PADISs 10 NOuvFLs 30 4LAuESs 65 LINKS 66 f. ens 5n0 pan 1Ss to houvELs 30 4LANESs 1 44SFCs 64 24ent 1 24908 66 LINFs R3 LE4s 70n RApl$s to N0mVELs 30 hLANESm 1 teSECs . 0 R213. 4WDSm 16 IFNkrss 2p700.

204F 7 90FZ4s 0

- 67 LIhns 44 LFNs 7n0 RAD 15s 11 NOuvELs 30 %LAuCSs 1 NRSECs i 2kDD 73 74e9: 69 LINES 7 2 f.E N s 3400 PAntSe 11 40sVFLs 30 NLA4ESs 1 NPSECs l (( 35 NLA4rss 1 NRSECs 70

] I 24RDt 69 Lf4Fs 71 LF4s 1960 RAn15s 11 MouvELs 24no pant $s 12 un4WEta 30 hLAut$s t mesrCs 69 1 LJ 249D: 70 LINKS 71 LENS 68 2VpDs 71 LINKS 72 LENS 1600 PADiss 12 wouYEts 35 Nf, A 4 E Ss 1 44 SECS 17 N0=VELs 49 NLAbrSa 1 mRSEcu 0 21RD: 72 LIN#m 95 LEts 1900 DADISs 79 LE%s 900 #AntSs 11 WO4VELs 30 hLA%ESm 1 WPSECs 75 ZapDe 73 LINKS 0 74 LIN's 76 LENS 2l00 PADISs it 40mvrLa 34 htAhEss 1 hRSrcs ZF4P 73 78 IEus 1000 #AntSa 11 ND4 VEL 30 4LA%ESs 1 4RSFCs j 2NeDt 75 LI4Na t 4RSFCs 77

, 24 ppt 76 L14km T o t,E4 s Sn3 paDISs 12 NouvFLs 30 4LA4Fss 24 ppt 77 LINFs 79 tEum 804 PADiss 12 4D4VELs 30 hLANE$a 1 4kSFCs 76 78 LTNKs 97 LE4s IR04 NAnt$s 12 hCuVELs 30 PLAbE$s 1 4WSECs ut 2490: g6 24pDt 79 blurs et (Ers 13nn eAntSa 12 NouvELs 3o 4LA4ESs 1 NaSECs EmpDs #1 LFra 2000 manISs 13 404WELs 30 hLA4ESs 1 hpSECs 79 PD Lista n2 LENS 1300 RADISs 12 404VFLs 38 WLANESs t unSFCs 70 2None at Links 0 24pnt n2 Lturs g5 '.E% s 700 Rant $s 12 40mVELs 30 %LAhESs 1 4RSECs ZOhEt a POP 7Ns $213. NPD$s 2 LENFD$s 74700 24kDs R3 LINNs 77 t.Eus 20C0 NACISs 11 NONVELs 30 WLA4ESs 1 NASFCs 0 90 f,FNs 240P RADISs 12 NO4VELs 30 4LA4ESa 1 NWSECs 0 74903 R4 LthKs EDgre 9 PDFZ4s n. NPOSs 1 LFwWDSs 999999, 15 NOuvELs 3 NLA4ESs 99999 NRSFCs 0 24PDt R5 LINF s 85 lANs 999999 Pali!Se

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ZNRDI 41 LINKS 42 LENS 1000 NADI 5s 11 N0mVELs 35 NLAhESs 1 mRSECs 0 10hEt 14 PDPZus 0. NRO5s 1 LEhRD5s 9999

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>* EmRD3 e Linus 9 LENS 1000 NAD15s 5 mJ4VtLa 30 4LAmESs 1 mRSECs 7 1 NRSLCs

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s ZmMD3 ZONE: 5 POPZum 9 Li%Rs 414 hRDSs th LLNs 3u0 NAplSa 2 Lt.NwDSs 9700 5 104VEbs 30 %LANL5s O hJ ZdWD3 lu LIhas 2 LLhz 4u0 NADI 5s 3 NJ4WELs 35 4LAhESs 1 NRSECs O Ch ggRos 11 LINns 7 LEhs 110u dAulsa 5 N0mVELs 30 mLAmL5s 1 NH5ECs 0 Zumi: 6 POPZum 1935. NRD$s 9 LE=hDSs 14600 ZukDs 12 LIhns 14 LENS 900 RADI5s 6 h04WELs 55 NLA4ESs 4 NRSECs 0 ZNkut 13 LISMs 15 LEms wou MADI5m 6 N0mVELs 55 NLAhE5s 2 Nk3ECs 0 ZmR03 14 LIhus Ib LENS 1400 HADI5m 6 h0mVELs 30 4(.A%ESs 1 NRSECs 16 ZNRD3 15 LINFs 19 LLhs 1900 NADISa 6 N04VELs 55 NLANE5s J NRSECs 17 ZhRD: 16 L1hns 18 LE%s 230u HADI5s 6 N04WELs 30 mLAmEas 1 an5ECs 14 ZNRD: 17 LINMs 19 LENS WOJ HADISs 7 N04WELs 30 NLANE5a 1 NRSECs 15 ZmRD: to LI%Ns 22 LLNs 1900 RADIss 7 hoeVELs 30 mLAhE5s 1 NRSECs 0 ZhW03 19 6 tens 20 LLas la00 NAdlSE 7 40mVELs 55 mLAmEbs 3 mRSECs 0 Z.4 H J 20 u!%ds 21 LL%s IbOu AAJ1hs 8 a0MVEI e 55 %LAhESs 3 NRSECs 0 204%2 7 PDPZ4s 429e. 4RDSs S LENRuss 13000 ZNMDI 21 L!hKs 26 LENS 2500 NADISs 10 N34WELs 55 NLAhE5s 3 NHSECs 0 24RD3 22 LlhKs 23 LENS 19u0 MADISs 8 N0gvgLa 30 NLAmE5s 1 mRSECs J ZmRot 23 Llens J4 LLms 2000 NApl5a 9 h34VELs 30 4 LANE 5s 1 mRSECs 0 ZNRD: 24 Ligga 27 LLNm 2000 RADI5s to NUMVELs 30 NLANLSs 1 NWSECs 0 ZNRDS 25 Liths b LLhs 500 NADISs 6 h0mVELs 30 9 LANE 5s 1 mRSCCs 0 ZONES b POPZ1s 197 NRDSs 2 LENWD5s 3500.

Zakos 26 L14Km 28 LENS 1000 NAD15m 11 N34WELs 55 4L44E5s 3 NRSECs 0 ZNkut 27 LINRu 28 LLNs 1000 WAD 15s 11 N3MVELs 30 4 LANE 5m 1 NRSECs 0 ZONE: 9 POPZNs 0 mHD5s 1 LEhn0Ss 9999 ZhMD 28 LINRs 28 LLNs 9999 RAD 15m 13 NQ4WELE 3 NLANE5s 999 NR$ECs 0

- 157G3 HOADs 10 LENSTGs 400 PDPstCs 3100 PVSIGs 3

EVZCu2710m 1REE NO. 7H F02 SEA 3200K= KIC DZTA 5 CLEAR m0ELLER CLEA3 BATTELLE CLEAR COELLER CLEA2 LUs 3 Dtbra 12 TYPs 25 FRACTs 0.25 441DEPs 3600 POPVENs 1 LGC0 des 5 FLORATs 1500 mINSPDs 15 ZTeos to ZFiva lh ZFENs le ZEPZa 19 ISTGs 2 EXs S3 EPZa 10 ZONE 1 POPZNs 4304 hRD$a 1 LEhMDSs 1400.

ZMAD 2 LImus 3 LENS 200 NADISs 2 NamWELs 35 NLAhESs 1 NRSECs 0 ZOhE: 2 POPZ4s 2225. hRDSs 3 LEnkDSm 1600 Em>D 3 LINKS S LENS 1000 NADISs 2 NONVELs 35 hLANESs 1 NRSECs 4 Z4RD: 4 LI4Ks 5 Leks 300 RADISs 2 N0mVLLs 20 NLANESs 1 mRSECs 3 ZmRbt S LINKS 22 LE9s 400 RADIS 2 h0mVELs 35 hLA4ESs 1 mRSECs 0 Z0tt: 3 PUPZ4s 63. hRDSs 1 LENRDSs 600.

Zampt 6 LINKS 4 LENS 600 RADISs 2 h0MVELs 20 4LA4ES: I hRSECs 0

, ZumE 4 POPZ4s 44 NRDSs 1 LEhRD$s 400 Z4kD 7 LINKS M Leks 400 BADISs 2 homWELs 35 hLANESs 1 NRSECs 0 ZohEs S POPZ4s 244 NWDSm 1 LEhWD$s 1300 ZNWD2 s LINKS 9 LENS 1300 RADISs 2 N0mVELs 35 NLAhESs 1 NRSECs 0 ZONE: 6 POPZ4s 177 NNDSs 2 LEhkDSs 1100 Z4h0: 9 Lives 33 LENS 600 RADISs 2 h0MVEbs 30 4LANESs 1 NRSECs 0 14kD: to LINKS 32 Leks 500 RADISs 2 h04WELs 30 % LANE $s 1 hRSECs 0 ZUNot 7 POPZ4s 1315. WhD$s 2 LFhkDSs 2000 Z4n0: 11 LIhKm 10 LENS 1500 NADISs 2 NOMVELs 35 NLANESs 1 NRSECs 0 Eikot 12 Lings 3R LENS 500 kADISs 2 NomVELs 35 NLANESs 1 hRSECs 0 ZumL: R POPZ4 369 NRDSs 2 LEhRDSs 3300 Zhkut 13 LINKS 11 LENS u00 NADISu 2 N0mWELs 35 NLANESm I hRSECs 0 Z%ho 14 bl4Ks 41 LEhs 1100 NADISs 2 h04WELs 55 mLAhESu 3 mRSECs 0 ZONE 9 POPZNs 1277 NWOSs 1 LENRD$s 3900.

ZmRD: 15 Li%Ks 17 LENS 1300 NADISs 2 MonVELs 35 NLANES 1 NRSECs 16 Z4RD to links 17 LtNa W00 RADISs 2 404WELs SS NLANESs 4 NRSECs 1$

21RDr 17 LINFs 14 LENS 300 RADISs 2 N0mWELs 55 NLANESs 3 hRSECs 0 ZumE: 10 POPZ4s $9 hRDSs 2 LENkDSr 3100 ZNNU: la LIhka 15 LENS 600 NADISs 1 homWELs 35 NLANESs 1 NRSECs 0 Z%RDI 19 LINns 16 LENS 900 kADiss 2 N0mVELE SS NLAhtSu 4 NASECs 0

- 20hEt 11 POPZNs 1443. 4HUSs 3 LEhWDSm 3000.

"[ ZhhD3 24R02 22 LINKS 23 LINKS 23 LENS 2S LENS 900 NADISs 800 NADISs 3 h0mVELs 3 N0mVELs 35 MLANESs SO NLANESs 1 NRSECs 0 0

e I hRSECs DO ZmRD: 24 LINKS 26 LENS 1300 RADISs 3 40mVELs 35 hLANESs 1 NRSECs 0

'd ZONL3 12 POPZ4m S533 %RDJs 6 LEhpDSs 7700 ZNkos 2S LINKS 7 LENS 1000 NADISs 3 NONVELs 50 NLANESs 1 NRSECs 0 ZhRO: 26 LIhFs 28 LENS 2J00 NAOISs 4 40mVEL= 40 hLAhESs 1 mRSECE 27 Zhku: 27 LINKS 2g LANs 1500 NADISs S N0mWELs 30 NLANESs 1 NRSECs 26 ZNRD: 28 LINKS 30 LENS 400 NADISs 5 NONVELs 3S hLANESs 1 NWSECs 29 ZvHas 29 links 30 LENS 1500 dADISs 5 N0mvELs 30 NLANESs 1 NRSECs 2e Zmunt 39 LImKa 31 LENS 1100 RADISs 5 NONVELs 40 NLANESs 1 NRSEcs 0 ZuNE: 13 POPZ4s 1272. hkDSs 1 LENkDSs 2200 ZmRos 31 LINKS 36 LENS 2200 RADISs 5 N0mVELs 40 NLANESu 1 NRSECs 35 ZONE: 14 POPZgs 641. NNDSm 6 LEhkDSs 10100.

ZhHn: 32 LINKS 34 LENS 300 RADI$a 3 NONVELs 30 NLANESs 1 NRSECs 33 ZhkD: 33 LIgKs 34 Lens 400 RADISs 3 NumVELs 30 hLANES 1 NRSECs 32 ZNkD 34 LINKS 39 LENS 700 MADism 3 N0mVFLs 30 NLANESs 1 NWSECs 0 ZhRD3 3S LInns 16 LENS 3500 MAUISs 4 nomVELu 40 NLANESs I hRSECs 31 ZhRot 36 Linus 37 LENS 309 RADISs S homWELs 30 hLAhESs 1 NNSECs 0 ZNND 37 LINKS 45 LENS 3300 RADISE 5 hDmVELs 40 NLANESs 1 NRSECs 42 ZONts 15 PDPZgs 1374 NRDSm 9 LEhhDSs 15400.

ZNkD3 Jo LIhKs 40 LENS 600 NADISs 3 N0mVELu 35 hL4hESs 1 NRSECs 39 ZNRD: 39 LI9Ks 40 LENS ROO RADISs 3 N0mVEL 35 NLANESs 1 NRSECs 30 ZNND 40 LIhka 43 LENS 700 NADISs 3 NumVELs 35 hLAhESs 1 NRSECs 41 ZNHO3 41 LINKS 43 LENS 1600 NADISs 3 NOMVELs 55 NLANESs 3 NRSECs 40 ZNRut 42 L14Ks 45 LENS 3000 NADISs 4 N04VELs 30 hLANESE 1 NRSECs 37 ZNRD3 43 LINKS 44 LENS 1000 RADISs 4 N04WELs 55 NLANESs 3 NRSECs 0

._ ._ _ _ _ . . _ . _. . _. .. . __ . ._. _ _m . _. _ _. .. _ _ . . . . . .

1 1

i I

I i (( ZmRO: 44 Links $2 LFNs 1700 NAD15s S hasVEbs SS %LA=E5s 4 %d5ECs 4S g ZakDs 4S LI1km 52 LLus 800 RAD 15s S h0aVELs 35 % Lane 5s 1 mRSECs 44 BJ Zumit 16 POPZ4s $242. NSD5s 1 LLukD5s 3000.

03 gneDi 46 Li4Ks 27 LENS SJO NAD15s 6 m3mVELs 25 hLanE5s 1 NRSECs 0 20hti 17 POPZ4s 0 NRD5s 4 LLhkD5s 7600

! Z% hot 47 L!hns 49 LEhs 1900 RADI5s 7 m34WELs SS %L4mL5s 4 Nd5ECs 0 Zhkut 4e binKs 49 LEhz 1900 NADI 5 8 husVELs SS hLAntSa 4 mR5ECs 0 ZhR02 4v Linna $0 Leks 1900 RAD 15s y m3mVELs SS %LANEsa 4 bd5ECs 0 ZhRD: $6 Lihas 52 LL4s 1940 RADI5s 10 humVLLs SS gLAmE5m 4 mRSECs b ,

20 hts le POPZvs 0, hRD5s 1 LEhMD5s 2$00 ZNRD St LIhRs 47 Leks 2500 RAD 15s 6 N0mVELs SS hLAhtSa 4 N#5ECs 0 ZONE 19 POPZ4s 276 4N05s 1 LENRDSu 3000 Z4ED: 52 LIhna S3 LEhs 1000 h4D15s 11 NDmVELs SS 4L4ht5s 4 hRSECs 0 Zahl 20 POPZgs 0 mkD5s 1 LEhhD5s 9999 j ZukD 53 L1hKs S3 LENS 9999 NAD15s 32 momVELs 3 mLAhE5s 999 NRSECs 0

e15fG3 R3 ads 15 LFmSTGs 600 PDPSTGs 2000 PVSTGs 3 estSTGt HJADs to LLn57Gs 800 PDPSTGs 970 PVSTGs t 4

1

- + - , . _ _ _ _ _ _ _ _ . _ _ . . _ _

LVACUATION TREE NO. 8 FOR SEAhR30K= hRC DATA 4 CLEAN m1ELLER CLEAR BATTELLE CLEAR mJELLER CLEAN Lys 3 delis 1J TYPs 25 FNACTs 0.25 MANDEPs 3600 PDPVEHs 1 LCC00Es 4 FLORAfs 1500 MIh5PDs 15 ZTuos 0 ZFIts 1 ITENs 5 ZEP4s W ISTGs O EXs 25 LPZa 11 ZONE: 1 PDPZhu (41 hRD5s 1 LENkD5s 10100 ZNRD I LINKS e LEhs 1600 RADISs 5 N0mVELs 40 NL4hE5s 1 NRSECs 0 ZONEt 2 POPZes 6212. NkDSs 2 LENRD$s 3800.

ENRDI 26 LINKS 2 LENS 1500 RADISs 6 h04WELs 30 %LANESs 1 NRSECs 0 ZNRO 2 LINKS 5 Leks 1500 NADISs 6 NQuvELs 10 NLAhEsa 1 NRSECs 3 ZONE 3 POPZNs 39NO. NRD5s 5 LENND?s 15000 ZNRD 3 LINKm 5 LENS 1600 NAD158 7 N0aWELs 30 NLAhESs 1 NRSECs 2 ZNRD: 4 LINKS 5 LENS 1200 RADI5s 7 N08tELs 30 NLANE$s 1 NRSECs 2 ENhD3 5 LINKS 9 LENS 4700 NAD15s 7 N04WELs 30 NLANESs 1 NRSECs 0 ZNRD 6 LINKS 7 LENS 4200 RADI5s 8 N0uvELs 30 NLAhESs 1 NRSECs 0

[2 Z1RDt 7 LIhKs 21 LENS 3300 RADI5m 10 NumVELs 30 NLAhESs 1 mRSECs 0

>* ZONE 4 PDPZum 3777. NRD5s 13 LEhPDSs 23600 8

ZNRot 8 LIhKs to LENS 2100 NADISs 6 NOMWELs 40 NLAhESs 1 NRSECs 9 h$ ZNRD 9 LINKm 10 LENS 1400 NAD15s 6 NONVELs 30 NLANESm 1 NRSECs 8 Zapos 10 LINKS 13 LEhs 500 RADI5s 7 N0mVELs 40 NLANE5s 1 NRSECs 11 ENRD 11 LINKS 13 LENS 2200 NADISs 7 NONVEL: 30 NLAhE$s 1 NRSECs 10 ZNRD 12 LINKS 6 LENS 1400 NADI 58 7 h04WELs 30 NLANES 1 NRSECs 0 ZNRD 13 LINKS 14 LENS !!00 NAD15s 7 N0aWELs 40 NLAhESs 1 NRSECs 0 ZNRD: 14 LINKS 15 LEhs 2700 RADISs 8 NONVELs 40 NLANESs 1 NRSECs 0 ZNRot 15 LINKS 22 LENS 2700 NADI $a 9 N04WELs 40 NLANESs 1 NR$FCs 0 ZNRD 16 LINKS 17 LENS 3500 NAD15s 8 NO4VELs 30 NLANESs 1 NRSECs 0 ZNRD 17 LINKS 23 LENS 3500 RADI5s 9 NONVELs 30 hLANE5m i NRSECs 0 ZNED le LINKS 19 LENS 2500 RAD 15s 6 NONVELs 30 NLAhESm i NRSECs 0 ZONE 5 PDPENs 1935 hRDSs 2 LENNDSs 18600 ZNRD3 19 LINKS 20 LEhe 2500 NADI 5s 7 NOMWELs 30 NLANE5s 1 NRSECs 0 ZNRD3 20 LINKS 24 LENS 2500 RADISE 8 N04WELs 30 hLAhE5s I hR5ECs 0 ZONE: 6 POPZNu 0 NND$s 1 LEhMDSs 1000 ZNRD 21 LINKS 25 LENS 1000 NAD15s 11 NDMWELE 30 NLAhESS 1 NRSECs 0 EUNEt 7 POPZNs 276 4RDSs 2 LENRDSs 3000 ZNRD 22 LINKS 25 LENS 1000 RAD 15m 11 ND4WELs 40 NLANESs 1 NRSECs 0 ZNkot 23 LINKS 25 LENS 1000 NAD15m 11 NDmWELs 30 NLANE5s 1 NRSECs 0 ZONE 8 POPZNs 123. NRD$a 1 LENRDSs 1000 FNRDI 24 LINKS 25 LENS 1000 RADI5s 11 N04VELs 30 NLANE5s 1 NRSECs 0 ZumEt 9 POPZNa 0. NRD5s 1 LEhWD5s 999 ZNRD 25 LINKS 25 LENS 999 RADiss 13 h0mWELs 3 NLANESs 999 NNSECs 0

4 i

t i APPENDIX IV

. This appendix contains off-season scenario evacuation time estimates and corresponding vehicle demand estimates for the Seabrook Nuclear Power Station.

t i

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IV-1 4

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Evacuation time estimates (ETEs) for an off-season scenario in the Seabrook Nuclear Power plant EPZ were calculated by PNL using the CLEAR model.

Following are the results and a discussion of both the vehicle demand estimates used as input data and the ETEs.

Most NRC'sof thedemand draft demand data used({The estimate. r the ETE calculations vehicle were taken demand estimates for thefrom off- the season scenario include contributions from permanent resident, schools, employment sources, recreation, shopping centers, seasonal housing and overnight acommodations. Table IV-1 shows the off-season vehicle demand j estimates for seasonal housing and for rooms in yearly overnight accommodations. Estimates from seasonal housing refer to units (houses, apartments, etc.) that are normally occupied during the summer season which are occasionally occupied during the off-season (non-summer) either by owners or renters. Rooms in yearly overnight accomodations refer to hotels, motels, and guest houses that are open during the entire year. In both instances, an estimate of 1 vehicle per unit was assumed. (Note that no data was available for distances greater than 10 miles.)

Table IV-2 shows the off-season vehicle demand estimates for U.S. Highway 1, manufacturing and industrial employment, and educational facilities. U.S.

Highway 1 is a major north-south artery in the Seabrook EPZ. The vehicle demand estimates ara based on 100 percent occupancy of the parking capacity of shopping centers, restaurants, municipal parking lots, and large stores found along it. An assumption of one auto per employee was used in determinng the vehicle demand estimates for employment. In addition, an estimate of 2,000 vehicles on the Seabrook station site was included in the employment category. A vehicle demand estimate factor of 20 students per vehicle was used for educational facilities. This factor is based upon the assumptions that these facilities would be evacuated by bus, with 40 students per bus, and one bus being equivalent to two vehicles. (This is the assumption used for non-autc owning residents. )

Table IV-3 shows the vehicle demand estimates for the permanent resident population of the Seabrook EPZ. These demand estimates are identified to those for a peak population scenario (summer weekend case). Table IV-3 contains data for the auto owning and non-auto owning population categories.

Table IV-4 shows the total vechicle demand estimates that were used to calculate ETEs for an off-season scenario in the Seabrook EPZ. Included in this table are demand estimates for the Seabrook Greyhound Park. Note that the demand estimates for the Greyhound Park differ from the NRC's draft. The NRC's report stated that the estimate of 3100 vehicles (which was for a 100 percent occupancy of the parking lot) could occur during a summer or a non-summer day. Instead an estimate of 873 vehicles is used in the present ETE calculations. This is based upon attendance data received from the Greyhound Park and an assumption of one vehicle pe- two people. Following is a description of this attendance data.

IV-2

Seabrook Greyhound Park Demand Estimate Yearly average attendance = 1813 people / performance June thru October average attendance = 1905 people / performance 8 performances per week at 52 weeks per year equals 416 performances / year June thru October equals 22 weeks times 8 performances per week equals 176 performances 1905 people x 176 performances = 335,280 people for June thru performance October 1813 people x (416) performances = 754,208 people for year performance 754,208

- 335,280 418,928 people for November thru May 418,928 people + (416 - 176 =) 240 performances for November thru May Equals 1746 people / performance for November thru May.

It is assumed November thru May is equivalent to the off-season and therefore:

1746 people + 2 people = 873 vehicles / performance performance vehicle Table IV-5 shows the ETEs calculated by the CLEAR model for each evacuation tree in the Seabrook EPZ. Table IV-6 shows comparison between the off-season and peak population scenarios in the Seabrook EPZ, using NRC's vehicle demand estimates as input data. The major results are large reductions in ETEs for evacuation trees no. 1, 2B, and 7B. These three trees include the main evacuation routes for the transient beach population of the peak population scenario. These results were expected since the vehicle demand estimates for the off-season scenario are significantly less than the peak population estimates for these evacuating trees. There was little or no reduction in ETEs of the remaining evacuation trees for the off-season scenario, mainly IV-3

l because the increase in vehicle demand estimates from the manuafacturing and i industrial employment category offset decreases in transient population

] estimates.

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TABLE IV-1 1

OFF-SEASON VEHICLE DEMAND ESTIPMTES FOR SEASONAL MUSING AND FOR ROOMS IN YEARLY OVERNIGHT ACCONTIONS 4

0-2 Mi le 2-5 Mile 5-10 Mile 10-EPZ 0-EPZ Seasonal Overnight: Seasonal Overnight: Seasonal Overnight: Seascnal Overnight: Seasonal Overnight:

Sector %usir.a Year Round musing Year Round musing Year Round %using Year Round musing Year Round N 1 0 5 196 17 0 0 0 23 196 NW 3 36 4 0 15 0 0 0 22 36 !

NW 1 0 5 0 16 90 0 0 22 90

! WW 0 0 3 0 15 0 0 0 18 0 W 2 136 4 0 16 0 9 0 22 136 WSW 3 46 7 0 10 0 0 0 20 46 SW 3 44 8 88 3 0 0 0 14 132 SSW 1 0 4 36 38 11 0 0 43 47 ;

< S 1 0 13 32 53 25 0 0 67 57 SSE 1 0 128 202 112 7 0 0 241 209 SE 3 0 44 0 0 0 0 0 47 0 i

ESE 72 0 0 0 0 0 0 0 72 0 E 69 208 0 0 0 0 0 0 69 208 ENE 95 740 120 54 0 0 0 0 0 215 1,280 NE 12 0 174 168 23 88 0 0 209 256 NNE O O 12 0 15 77 0 0 27 77 Total 267 1,210 531 1,262 333 298 0 0 1,131 2,770 t

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TABLE IV-3 VEHICLE DEMAND ESTIMATES FOR PERMANENT RESIDENT POPULATION 0-2 Mile 2-5 Mile 5-10 Mile 10-EPZ 0-EPZ Auto Non-auto Auto Non-auto Auto Non-auto Auto Non-auto Sector Auto Non-auto Total Own Own Own Own Own Own Own Own Own Own Resident N 22 0.3 571 4.4 1,144 10.1 1,868.6 39.3 3,605.6 54.1 3,659.7 NNW 76 1.1 227 2.0 920 12.2 306.9 4.5 1,529.9 19.8 1,549.7 NW 64 0.9 109 1.7 3,541 84.8 278.1 4.5 3,992.1 91.9 4,084 WNW 21 0.3 235 3.5 520 7.2 749.2 9.7 1,525.2 20.7 1,545.9 W 306 4.0 363 5.2 792 11.5 874.2 8.8 2,285.2 29.5 2,314.7 WSW 248 3.3 1,262 34.9 3,566 93.8 183.5 3.4 5,259.5 135.4 5,394.9 SW 276 3.7 1,141 35.1 1,835 52.8 118.0 4.6 3,370 96.2 3,466.2 SSW 160 2.1 455 14.0 3,155 91.0 273.1 3.0 4,0 13.1 110.1 4,153.2 32 S 149 2.0 731 20.1 2,459 55.4 0 0 3,3 39 77.5 3,416.5

, SSE 35 0.5 38 0 11.2 473 11.5 0 0 d88 23.2 911.2 SE 20 0.3 191 4.3 0 0 0 0 4.6 211 215.6 ESE 350 4.2 0 0 0 0 0 0 350 4.2 354.2 E 184 1.5 0 0 0 0 0 0 184 1.5 185.5 ENE 172 1.4 360 2.9 0 0 0 0 532 4.3 536.3 NE 25 0.2 1,135 8.8 821 2.8 174.6 0.6 2,155.6 12.4 2,168 NNE 0 0 1,533 11.8 2,299 35.1 6,063.9 134.6 9,895.9 181.5 10,077.4 Total 2,138 25.8 8,693 159.9 21,525 468.2 10,840.1 213 43,166.1 866.9 44,033

TABLE IV-4 VEHICLE DEMAND ESTIMATES FOR AN OFF-SEASON SCENARIO IN THE SEARR00K EPZ r

0-2 Mile 2-5 Mile 5-10 Mile 10-EPZ 0-EPZ Sector Total Total Total Total Total N 111 1,955 -1,427 1,908 5,401 ,

NNW 140 233 1,461 311 2,145 NW 129 116 5,635 283 6,163 WNW 56 250 551 759 1,616 W 3,811 1,267(a) 822 833 6,733 i WSW 1,267 1,595 3,956 187 7,005 SW 1,448 2,261 2,868 123 6,700 SSW 163 524 6,486 276 7,449 S 262 986 3,890 0 5,138 SSE 37 721 603 0 1,361 SE 23 239 0 0 262 ESE 426 0 0 0 426 E 463 0 0 0 463 ENE 1,009 1,023 0 0 2,032 NE 37 1,752 1,966 175 3,930 NNE 0 1,792 2,475 6,198 10,465 TOTAL 9,382 14,714 32,140 11,053 67,289 (a) Includes the vehicle demand estimate of 873 for the Seabrook Greyhound Park.

IV-8

TABLE IV-5 Calculation of Evacuation Time Estimates Using the CLEAR Model for an Off-Season population scenario in the Seabrook EPZ. (NRC Data)

Evacuation Evacuation Time Estimates

Tree (Hours: Minutes) (Minutes) 1 6:45 405 l

28 3:20 200 3 2:35 155 4 6:10 370 5 2:30 150 6 3:55 235 7B 2:55 175 8 4:25 265 Includes 15 minute notification time.

TABLE IV-6 Comparison of Evacuation Time Estimates as Calculated by the CLEAR Model for a Peak Pr,oulation and an Off-Season Population Scenario in the Seabrook EPZ.

(NRC Data)

Evacuation Peak Population ETE* Off-Season Population ETE*

Tree (Hours: Minutes) (Hours: Minutes) 1 9:40 6:45 2B 11:40 3:20 3 2:20 2:35 4 6:15 6:10 5 2:45 2:30 i

6 3:40 3:55 78 10:25 2:55

, 8 6:25 4:25 l

Includes 15 minute notification time.

IV-9

Nf.C roRu 335 g gg ggggg g 1. REPOST NUMBE R (Assigned by ODC/

BIBLIOGRAPHIC DATA SHEET 4 TlTLE AND SUBTITLE (Add VJaume No., of apprmeratel 2. (Leave blank)

An Ind: pendent Assessment of Evacuation Time Estimates for a Peak Population Scenario in the Emergency Planning Zone 1 RECIPIENT'S ACCESSION NO.

of the Seabrook Nuclear Power Station

7. AUTHOR (S) 5. DATE REPORT COMPLETED M. P. Moeller M. A. McLean uONTH lvEAR T. Urbanik II A. E. Desrosiers October 1982

9. PE RFORMING ORGANIZATION NAME AND MAILING ADDRESS (include lip Codel DATE REPORT ISSUED MONTH l YEAR Battelle Pacific Northwest Laboratories November 1982 P. O. Box 999 s (t ,,v,bianni Richland, WA 99352 8 (Leave blank)

12. SPONSORING ORGANIZATION N AME AND M AIL;NG ADDRESS I/nclude l<a Codel

10. PROJECT / TASK / WORK UNIT NO.

Division of Emergency Preparedness Office of Inspection and Enforcement ,i. nn no.

U. S. Nuclear Regulatory Commission Washington, D. C. 20555 NRC FIN 82311

13. TYPE OF REPOP T PE RIOD COVE RE D (inclusive dates /

, Technical

,15. SUPPLEME N TAHY NOTE S 14. (Leave o/m4J l$6. A 51 R ACT (200 words or less!

This study comprises two major tasks: (1) an assessment of the methods and assumptions us::d in calculating evacuation time estimates (ETEs) applicable to the general population for a peak population scenario in the emergency planning zone of the Seabrook Nuclear Power Station, consisting of a review and analysis of previous work by Public Service of New Hampshire (PSNH) and the Federal Emergency Management Agency (FEMA), as well as an independent calculation of ETEs using the CLEAR model for the demographic data reported by PSNH; (2) independent estimations of the ETEs for the peak population scenario, developed using demographic data prepared by the U. S. Nuclear Regulatory Commission (NRC) and the CLEAR model. The results of this study reveal the importance of the assumptions used for calculating ETEs. Because traffic routings and management plans have not been prepared for the area, the CLEAR calculations utilized independently prepared traffic routings and assumptions. A detailed analysis of the results suggests that the ETEs submitted by PSNH are consistent with the methods and assumptions which provid3 the bases for pSNH's ETEs. Differences among ETEs stem largely from differences in the assumed size of the evacuating population and the estimated effectiveness of traffic controls.

17. KE Y WORDS AND DOCUME NT AN ALYSIS 17a DESCRsPTORS Evacuation Time Estimates Indep1ndent Assessments S:abrook Nuclear Power Station 11b. IDEN TIFIE RS OPE N.EN DE D TE RYS 18 AV AIL ABILITY ST ATEVENT 19 SE CURITY CLASS (Th.s recorr/ 21 NO OF P AGES Unclassified Unlimited 20 -e CuaiTY CL AS$ (TNs parl 22 PRICE dnclassifiga s N OC F ORV 335 til sie

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". UNITED STATE 3 eoca ct Assmt . ~o

.. NUCLEAR REGULATORY COMMISSION f0DAGE H it$ pal 0'. -

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WASHINGTON D.C,205% '

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OFFICIAL SUSWESS PINALTY f OR PRIVATE USE,4300 _

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ML20069N647

Contents

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SUMMARY

SUMMARY

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ML20069N647

Text

SUMMARY

SUMMARY

==

===

=== = = m mm == mm m eM mW === mmmmm. = ====== ==

w# W 9 mN me eed e*WN 3 e8 5 # W W me a was A A A

=

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