ML20137Z582

Evacuation Plan Update for Seabrook Station, Progress Rept 2

ML20137Z582
Person / Time
Site:	Seabrook
Issue date:	12/16/1985
From:	KLD ASSOCIATES, INC.
To:
Shared Package
ML20137Z542	List: ML20137Z540 ML20137Z554 ML20137Z582 ML20137Z611 ML20137Z615 ML20137Z629
References
KLD-TR-174A, NUDOCS 8603130072
Download: ML20137Z582 (60)

Text

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!!LD TR-174A  !

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EVACUATION PLAN UPDATE for ,

seabrook station Seabrook, New Hampshire i

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Preareas Renort No. 2  !

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Prepared for i' The Commonwealth of Massachusetts I O civi oea ^'a=v a*o"ic a'==rea=vPrarda"-

i by ,

KLD Associates, Inc.

, 300 Broadway '

Huntington Station, NY 11746  ;

1 i i 0 ,

December is, 1985 l 1 i i <O

p ' 988a q ,

TABLE OF CONTENTS

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em INTRODUCTION i SCOPE OF SECOND PROGPESS REPORT 1 ESTIMATION OF TRIP GENERATION TIME 3 Background 3 Fundamental Considerations 4 Estimated Time Distributions of Activities Preceding Event 5 7 i

Time Distr..bution for Preparing to Leave Work:

Activity 2 --> 3 10 Time Distribution of the Travel Time Homer Activity 3 --> 4 11 Time Distribution for Preparing to Leave Home Activity 2,4 --> 5 12 Distribution 4A 12 Distribution 48 13 Calculation of Trip Generation Time Distribution 14 Algorithm No. 1 (Dependent Events) e

, 15 Computed Time distribution of event k+1 16 Trip Generation Distributions for Week-end Scenarios 17 Trip Generation Distribution for Week-day Scenarios 19 Snow Clearance Time Distribution 19 EVACUATION OF EMPLOYEES 27 DEMAND ESTIMATION FOR OFF-SEASON AND MID-WEEK IN-SEASON SCENARIOS 36 Evacuation Voltimes for the Summer Mid-week, Mid-day Scenario 3a PRELIMINARY TRAFFIC CONTROL AND MANAGEMENT TACTICS 39 EVACUATION TIME ESTIMATES (ETE) 42 Future ETE Developments 42 APPENDIX I - Preliminary Traffic Control and '

Management Tec':ics I-1 S

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TABLE OF COkradTS (continued) .

LIST OF FIGURES h Title Ragg

18 Events and Activities Preceding the Evacuation 6 19 Comparison of Trip Generation Distributions 20 20 Elapsed Times from Start of Evacuation for Regions within Seabrook Station EPZ 46 21 Elapsed Times from Start of Evacuation for Regions within Seabrook Station EPZ 47 22 Elapsed Times from Start of Evacuation for Regions within Seabrook Station EPZ 48 23 Elapsed Times from Start of Evacuation for Regions within Seabrook Station EPZ

_ 49 24 Elapsed Times from Start of Evacuation for Regions within Seabrook Station EPZ 50 J

n U

25 Elapsed Times from Start of Evacuation for Regions within Seabrook Station EPZ 51 1 26 Elapsed Times from Start of Evacuation for Regions within Seabrook Station EPZ 52 1 27 Elapsed Times from Start of Evacuation for i

Regions within Seabrook Station EPZ 53 28 Map of EPZ Delineating all Emergency

{

Response Planning Areas (ERPA) 55 l

l LIST OF TABLIE I

i h Title Eagg l 2 Number of Sampled Vehicles 8

! 3 Computed Trip Generation Cumulative

! Distributions (percent) 18

! 4 Trip Generation Time Histograms for the i

Week-end Scenarios 21 I

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()

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F 1

TABLE OF con 1mnrs (concluded) ,

LIST OF TABTJS E2m Title Eagg l 5 Computed Trip Generation Time Distribution

for the Mid-week, Mid-day Scenario (Distribution F) 22 6 Trip Generation Time Histograms for the Week-day Scenarios (Dist. F) 23

, 7 Trip Generation Time Histograms for the i

Inclement Weather, Snow, Scenarios (Distributions G, H, I) 26 c 8 Year-round Employment Population Estimates

by Community 28 9 Employment Population Estimates by Community for the Months of July and October 29 i

l 10 Estimates of Evacuating Employees 33

11 Evacuating Employees for Various Scenarios,

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Expressed in Vehicles 35 i

, 12 Description of Evacuation Scenarios 1-10 43 1

i 13 ETE for Scenarios 1-10 44

! 14 Towns Included Within ERPA 56 I

111

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1. INTRODUCTION

() This is the second of a series of Progress Reports which document the activities performed, and the results obtained, in connection with a study to update the existing evacuation plan for the Seabrook Station.

, The practice of publishing progress reports for distribution

• departs, somewhat, from the conventional practice of completing the study before publishing a Final Report. We have chosen this approach for the following reasons:

1. It is hoped that the early publication of these reports would prove of value to other planning groups.

2. Hopefully, these reports will also stimulate responses from all involved public agencies, citizen planning committees and town officials.

3. The timing of these progress report publications will enable us to review all such responses -- both constructive and critical -- prior to the completion of the study. Any responses which are received in a timely manner and judged to contribute to the accuracy and/or reliability of the final study results, will be incorporated into the evacuation plan development, prior I to the publication of the Final Report.

This approach is endorsed by the Massachusetts civil Defense O Agency (MCDA), which is sponsoring this activity. ,

It is assumed that the reader also has a copy of the prior progress report, since many references are made thereto. Also, the section numbers of this report are a continuation of those of the prior report so thatt e continuity of text is preserved '

i e Reference by future Progress Reports to the earlier reports are clear and unambiguous.

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7. SCOPE OF SECOND PROGRESS REPORT

() This report describes the activities undertaken since the publication of the first Progress Report. Specificall*" ,

e The computation of the Trip Generation time distributions for different population groups and different emergency scenarios.

e The development of nreliminary traffic management policies which are designed to expedite the movement of evacuating vehicles routing.

in a manner which is consistent with the assigned e The acquisition of up-to-date information of current employment within the EPZ from State agencies.

e The computation of employment groups, stratified by town.

These groups include:

Those who work in the same town in which they live Thosethe within whoEPZ work within the EPZ but live in another town Those who work within the EPZ but live outside the EPZ. E The last employee group must be included in the population of evacuees. Those people in the'first two groups are .

residents ofgroups.

population the EPZ and evacuate as members of resident e The computation of evacuation routes and evacuation time estimates (ETE). These computations use the current i estimates of employment, the computed trip generation time distributions and apply the preliminary traffic management policies.

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The number of evacuation scenarios was expanded '

to includes

1. A rerun of the weekend summer mid-day, clear weather scenario, using the updated data which became available.

2. The weekend summer mid-day inclement weather scenario.

This scenario assumes that the beaches are crowded to capacity, that a sudden rain storm occurs almost instantaneously and that an alert is declared at Seabrook Station at precisely.that time. l

3. The mid-week, summer, mid-day, clear weather scenario.

It is assumed, based on available empirical data, that the tourist and beach area populations are about 75 percent of the weekend population.

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4. The mid-week, summer, mid-day, inclement weather scenario. This scenario also assumes a sudden rain

'( ) storm coincident with an accident at seabrook Station.

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5. The mid-week, off-season, mid-day, clear weather scenario. The tourist population is greatly reduced, relative to the summer scenarios.

6. The mid-week, off-season, mid-day, inclement weather (rain) scenario.

7. The mid-week, off-season, mid-day, inclement weather (snow) scenario.

8-10. Same as scenarios 5-7, respectively, except that the time is evening or weekend, rather than mid-day. For these scenarios, the number of employees is reduced to 25 percent of the number in scenarios 5-7.

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8. ESTIMATION OF TRIP GENERATION TIME i

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() Federal Government Guidelines (see NUREG 0654, Appendix 4) specify that the planner estimate the elapsed times associated with activities undertaken by the public in preparation for evacuation. We define the 125 of these elapsed times, to be defined later, as the Trip Generation Time.

Backaround In general, an accident at a nuclear power station attains one or more " classes" of Emergency Action Levels (see Appendix 1 of NUREG 0654 for details):  ;

1. Unusue.1 Event

2. Alert

3. Site Area Emergency

4. General Emergency At each level, the Federal Guidelines specify a set of

, , Actions to be undertaken by the Licensee, and by State and Local i offsite authorities. If we limit this discussion to the j

evacuation decision action, then the first off-site public

notification and response can occur at the time of the Site Area Emergency, as described subsequently.

There may be, however, an exception to this rule for the Seabrook Station. It is now contemplated that the public will be notified to clear the beaches at the Alert Level as a O precautionary action.

As a Plannina Bag 13, we will adopt a conservative posture, in

.l accord with Federal Regulations, that a rapidly escalating accident will be considered in calculating the Trip Generation Time. We will assumes e The accident escalates almost immediately to a site Area Emergency.

e That further escalation to a General Emergency occurs 15 minutes later.

e That the order to evacuate is transmitted to the public 10 l

minutes after the General Emergency is declared.

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, We emphasize that the adoption of this planning basis is ng_t 1 a representation that these events can occur at the Seabrook Station within the indicated time frame. Rather, these arsumptions are only necessary in order tot e Estaolish a temporal framework for estimating the Trip l Generation distribution in the format recommended in '

Appendix 4 of NUREG 0654.

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__-___ __- _ _ = .

l e Identify temporal points of reference for the purpose of

~N uniquely defining " clear Time" and Evacuation Time l (V Estimates (ETE).

I The notification process consists of two events:

. l e Transmittina information (e.g. using sirens, tone alerts, EBS broadcasts, loudspeakers).

i e Receivina and correctly intertretina the information that ,

is transmitted. t r

The population within the EPZ exceeds 140,000 persons who are deployed over an area of approximately 200 square miles, and engaged in a wide variety of activities. It must be anticipated that some time will elapse between the transmission and receipt of the internation advising the public of an accident.

!" The amount of elepsed time will vary from one individual to i i the next depending where that person is, what that person is '

doing, and related factors. Furthermore, persons who will be directly involved with the evacuation process may be outside the I EPZ at the time that the emergency is declared. These people may be commuters, shoppers and other travelers who reside within the i EPZ and who will return to join the other members in the hcunehold upon receiving notification of an emergency.

! As indicated in NUREG 0654, the estimated elapsed times fcr the receipt of notification can be expressed as a distributioD reflecting the different notification times for different people within, and outside, the EPZ. By using time distributions, it is i

also possible to distinguish between different population groups i

and different day-of-week and time-of-day scenarios, so that more accurate assessments may be obtained. i For example, persons on the beach areas will be alerted with I

loudspeakers; there will be little time lost between transmission

! and receipt of information. Other persons, located inland within the EPZ will be notified by siren, tone alert and ratio. Those

! well outside the EPZ will be notified by telephone, radio, TV and j word-of-mouth, with potentially longer time lags. -

) Furthermore, the spatial distribution of the EPZ population i

will differ with time of day -- families will be united in the evenings and at night, but dispersed during the day. In this respect, weekends will differ from weekdays. l Egndamental Considerations l The environment leading up to the time that people begin their evacuation trips, consists of a sequence of events and i activition. Each event (other than the first) occurs at an l inntant in time and is the outcomo of an activity.

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e Activities are undertaken over a period of time. Activities

() may be in " series" (i.e. to undertake an activity implies the completion'of all preceding events more autivities may take place over)the or may samebe in parallel period of time). (two or

.- . Activities conducted in series are functionally denendent on L

' the completion of prior activities; activities conducted in

, parallel are functionally ADdARADdent of one-another. The releve'at events associated with the public's preparation for evacuation are:

Event _ Number Event namerietion 1 No-accident condition 2

3 Awareness of accident situation Depart place of work 4 Arrive home 5

Imave home to evacuate the area Associated with each sequence of events are one or more activities, as outlined below:

Event sequence Activity 1 --> 2 2 --> 3 Public receives notification information Prepare to leave work 2,3 --> 4 Travel home 2,4 --> 5 Prepare to leave for evacuation trip These relationships may be depicted graphically as shown in figure 18.

(

Note that event 5, " Leave conditional either on event 2 grtoevent evacuate

4. the area" is That is, activities 2

--> 5 can be undertaken in parallel with activities 2 --> 3, 3

--> 4 and 4 --> 5, as shown in Figure is (a) and (c).

Specifically, it is possible that one adult member of a household can prepara to leave home (i.e. secure the home, pack clothing, etc.), while othere are travelling home from work. In this instance, the household members would be able to evacuate sooner than if such preparation had to be deferred until all household members had returned home. However, we will adopt the i

conservative posture that all activities will occur in sequence.

v It is seen from Figure 18, that the Trip Generation time (i.e. the total elapsed time from Event 1 to tvent 5) depends en the scenario and will vary from one household to the next.

/ Furthermore, Event 5 depends, in a complicated way, on the time distributions of all activities leading to that event.

Specifically, in order to estimate the time distribution of Event 5, we must somehow obtain estimates of the time distributions of all preceding events.

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5

._ m -

t s

1 2 3 4 5 .

1, z.: Inland and Residents

~ ~ _, ,_ __ __ ,

4 1 2 5 Beach area vacationers j

(a) Accident occurs during mid-wee)t, tat mid-day; summer season ',

1 2 5 ,

e  :: rc Inland and Residents 1 2 5 ~

==  :: Beach area vacationers I

(b) Accident occurs during week-dnd, at nid-day; summer season 1

1 '2 3 4 +

5

=- =  :: p

=% -

~ -

(c)

Accident occurs during mid-week, at mid-day;

(. non-summer season 1 2 5

== ==

(d) Accident occurs in the evening, non-summer season 1 2 3 ,

_ m. ..

(e) Employees who live outside of the EPZ

_ _____ _ __ _ _ % Time Increasing e Event

- *- Activity Figure 18. Events and Activities Preceding the Evacuation l (see text for definition)

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f Estimated Time Distributions of Activities Precedina Event 5

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The time distribution of an event is obtained by " summing" the time distributions of all prior, contributing activities.

' (This " summing" process is quite different than an algebraic sum since we are operating on distributions -- not numbers).

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i Time distribution of the Notification Process:

Activity 1 --> 2)

We know of no survey which has accumulated empirical information describing the rate at which notification information is received. Nevertheless, there is sufficient data to obtain a reasonable estimate of a notification time frame, based largely on the information obtained from the telephone survey. (See Appendices F and G). -

, Th's following information is relevant:

4 Estimated Population: 142,194 Average Household (HH) Size: 2.87 Estimate Number of HH: 142,194/2.87 = 49,545 Avg. Number of Commuters per HH: 1661/1300 = 1.28 Percentage of Residents who will be within the EPZ if accident occurs at mid-week, mid-day: -

0.582 (1.28) + (2.87-1.28) x 100 = 81.4 l 2.87 since 58.2 percent of all commuters work within the EPZ,

according to the survey results.

The population within the EPZ includes 81.4 percent of all residents, as computed above, and 100 percent of all tourists and employees, by definition.

The tourist population may be estimated by estimating an average value of persons per vehicle. The subject of vehicle occupancy has received much attention in past studies (see Appendix A, items 6, lo, 13; also the Costello Report referenced in item 16). Recently, a count of vehicle occupancy was conducted for KLD, as reported in item 18 of Appendix A. The results of this field count are presented in Table 2. These results for the major beach access roads may be summarized as follows:

1 Averace Vehicle Occucancy on Beach Access Roads Route Wednesday Sunday Overall 1A 2.18 2.21 2.20 286 1.91 2.12 2.07 51- 2.18 2.23 2.21

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. Table 2.- Number of Sampled Vehicles Major

• occupied by the indicated Mean Beach Location Day Time number of Dersons Occuo. Access.

L2 1 1 1 1 2t-

. Rt . 1 WED 10:00AM 33 30 17 8 0 0 2 2.13 Rt. 286 " 10:35AM 63 85 20 10 1 0 1 1.92 X Rt. 51 11:35AM 29 35 15 10 10 2 0 2.44 X Rt. 101C " 12:00PM 38 22 7 3 3 0 0 1.69 Rt. lA " 12:35PM 35 47 13 6 1 1 1 2.02 X Rt. 101E " 1:08PM 38 24 10 5 0 1 0 1.82 Rt. lA " 1:50PM 50 61 27 14 5 1 0 2.15 X Rt. 286 -" 2:25PM 20 32 8 1 1 0 0 1.88 X Rt. 51 " 2:56PM 41 42 19 10 5 0 0 2.11 X Rt. 101E "

3:25PM 25 34 17 7 2 0 0 2.14 Rt. 101C " 3:45PM 31 37 7*2 0 1 0 1.79 Rt. lA " 4:10PM 14 52 15 9 6 0 0 2.39 X Rt. 101C " 4:40PM 45 30 9 4 3 0 0 1.79 Rt. 101E 5:05PMT 68 54 12 6 2 0 0 1.79 Rt. 51 "

5:35PM -29 42 11 8 0 0 0 1.98 X ,

Rt. lA SUN 9:30AM 34 53 19 8 7 0 0 2.18 X '

Rt. 286 10:10AM 46 42 7 8 1 0 0 1.81 X Rt. 51 " 10:55AM 30 84 14 12 6 0 0 2.18 X Rt. 101E " 11:35AM

% 18 36 17 11 1 0 0 2.28 Rt. 101C " 12:00PM 22 29 13 6 1 0 0 2.08 Rt. lA " 12:25PM 14 40 14 10 1 2 0 2.37 X Rt. 101C " 12:50PM 25 27 15 11 3 0 0 2.25 Rt. 101E " 1:15PM 29 48 14 10 4 0 0 2.16 Rt. 51 " 1:40PM 9 42 8 10 0 2 0 2.38 X Rt. 286 " 2:30PM 36 65 13 16 3 2 1 2.23 X Rt. lA " 3:05PM 28 66 20 9 4 0 0 2.17 X Rt. 286 " 3:45PM 27 88 20 13 8 1 0 2.30 X Rt. 51 " 4:30PM 17 74 11 12 2 0 0 2.21 X Rt. 101E " 5:00PM 36 57 9 7 0 2 0 1.95 Rt. 101C " 5:30PM 35 56 13 16 5 1 0 2.23 Wednesday data is August 28, 1985 i

Sunday data is September 1, 1985 1

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• X indicates that route directly services the beach area l

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As is indicated, these data reveal a much lower vehicle occupancy than the values obtained in other surveys which yielded s values generally ranging from 2.7 to 3.5 persons per vehicle. The factors which could contribute to these disparate results are:

e Secular reduction in family size over the past decade.

e Increase in vehicle ownership per household, leading to fewer persons per car, over the past decade, e A change in the demographics of those attracted to the beach area, relative to prior years. Discussions with officials revealed that fewer families and a larger number of younger people were attracted to the beach in 1985.

o These data, collected over the last week and weekend of the season, may not be representative of the entire season.

In the absence of other definitive data compiled earlier in the 1985 season, we will adopt a " compromise" estimate of.2.8 persons per vehicle in the beach area. Any reasonable inaccuracy in this estimate will not meaningfully impact the~ calculations

{ of the notification time distribution.

In "round" figures, there are:

e 25,000 vehicles parked at the beach O e 10,000 vehicles at seasonal, or other, tourist locations located off the beach a 10,000 vehicles servicing employees who work on the weekend and who live outside the EPZ e 55,000 vehicles servicing residents, including those who will return home from work Thus,-the total estimated population which will be evacuating from within the EPZ is:

Tourists on the beach: 25,000 veh 0 2.8 = 70,000 l Tourists off the beach: 10,000 veh. 0 2.8 = 28,000 t

Employees off the beach: '10,000 veh. 0 1.16 = 11,600 Residents off the beach = 142.200 l

251,800 It is reasonable to expect that 90 percent of those within I the EPZ will be aware of the accident within 15 minutes with the l remainder notified within the following 15 minutes. The l commuters outside the EPZ will be notified somewhat later, say uniformly between 10 and 40 minutes, while the entire beach area population will be notified within 15 minutes. The resulting distributions for this' notification activity are given below:

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r Off the Beach: Distribution 1A

() Elapsed Time (min.)

Cum. Pct.

Notified 5 15 10 46 15 79 20 85 25 90

30 95 35 98 40 100 On the Beach: Distribution 1B Elapsed Cum. Pct.

Time (min.) Notified 5 20

'l 10 60 15 100 Time Distribution for PreDarina to Leave Work:

Activity 2 --> 3 It is reasonable to expect that'the vast majority of business enterprises within the EPZ will elect to shut down following notification. Most employees would take action to leave work r(-~ -

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quickly. Commuters who work outside the EPZ could, in all probability, also leave quickly since facilities outside the EPZ i sould remain open and other personnel would remain. Personnel

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responsible for equipment would require additional time to secure the facility. The distribution of Activity 2 --> 3 was obtained from data obtained by the telephone survey. This distribution is plotted in Figure 1 and listed below as Distribution 2.

Distribution 2 I

L Elapsed Cum. Pct, l

Time (min.) Leavina Work 5 66 10 77 15 84 20 '

86

, 25 87 30 93 35 95 40 95

, 45 95 1 50 96 55 96 l

O 10

7 Elapsed Cum. Pct.

Time (min.) Leavina Work 60 97 G5 97 70 98 75 98 80 98 85 98 90 99 95 99 100 99 105 99 t

110 100 NOTE: The survey data was normalized to distribute the

" Don't know" response Time Distribution of the Travel Time Homa: Activity 3 --> 4 This data is provided directly by the telephone survey. This distribution is plotted in Figure 1 and listed below:

Distribution 3 ~

i Elapsed Cum. Pct.

Time (min.) Returnina Home 5

O 10 15 16 33 49 20 60

=~ 25 66 30 75 35 78 40 81 45 87 50 89 55 89 60 95 65 95 70 96 75 97 80 97 i

i 85 98 90 98 l 95 98 100 98 105 99 110 99 '

115 100 NOTE: The survey data was normalized to distribute the

" Don't know" response O

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'~ Time Distribution for Precarina to Leave Home:

Activity 2.4 --> 5 -

This data is provided directly by the telephone survey. This distribution is plotted in Figure 1-and listed below:

Distribution 4A Elanned Time (min) Cum. Pet. Ready to Evacuate 5 8 10 16 15 24 20 34 25 44 30 53 35 56 40 58 45 61 50 65 55 70 60 74 65 78 70 81 75 7

~

85 80 86 l

85 86 l 90 87 95 87 p 100 87 v 105 87 110 88 115 90 120 91 125 92 130 94 135 95

140 95

! 145 96

[ 150 96

! 155 96

( 160 96 165 96 170 97 l 175 97 l- 180 98 l 185 98

( 190 98 l 195 99 l 200 99 205 99 210 100 NOTE: The original data was obtained in 15-minute increments.

The above figures were calculated by interpolation and normalized as before.

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Distribution 4B .

Distribution 4B describes the estimated preparation time to leave the beach area. While we hsve no empirical data to support this distribution, we do know the physical domain of the* beach area and the activities involved.

People on the beach or out walking would merely gather their belongings and walk to their respective cars, others who are lodged in overnight accommodations and in tourist facilities would return to pack their belongings and leave. Business people and permanent residents must secure their properites and then pack, before leaving.

Since we know that congestion will occur on the beach areas during the summer and that evacuation time will exceed Trip Generation time, any inaccuracies in the distribution will not influence the ETE. Thus, an approximate, reasonable distribution will satisfy our needs.

On a weekend, about half of all visitors are day-trippers.

These people should be able to access their respective cars within 40 minutes of the receipt of the notification information and be ready to depart.

About 80 percent of the remaining visitors (i.e. 40 percent of the total) should be able to access their respective cars within 1.5 hours5.787037e-5 days <br />0.00139 hours <br />8.267196e-6 weeks <br />1.9025e-6 months <br />. The remaining people are those who must take O' longer, say, from one hour, up to two hours.

The resulting distribution follows:

Elapsed Time (min) Cum. Pct. Ready to Evacuate 5 12 10 23 15 35 20 46 25 57 30 68 35 70 40 72 45 74 i 50 76 1 55 .

79 60 81 65 84 70 86 75 89 80 91 85 94 90 97 95 97 13

Elansed Time (mini Cum. Pct. Ready to Evacuate

! 100 98 105 98 110 99 115 99 120 100 Calculation of Trio Generation Time Distribution Associated with each event is a time distribution reflecting the range of time for the population to complete the preceding activity, and the time distribution of the preceding event.

When an event, k+1, deoends upon a prior event, k, then the time distribution of this event, k+1, can be calculated if:

e The time distribution of event, k, is known, and e The time distribution of the activity k->k+1, is known or can be estimated.

We now present the analytical treatment to compute the distribution of event, k+1. .

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Alacrithm No. 1 (Denendent Events)

(]) Computationally, all distributions are represented as histograms composed of elements (i.e. each element represents a percentage of the population). The following definitions apply:

Let T i(k) = Time at which the ith element of the histogram has completed event, k; i=1,2...,I .

tj = Time required for jth element of the histogram to perform the activity, k->k+1; j =1,2, . . . ,J Pi(k) = Percent of population represented by the'ith element of the histogram for event, k. That is, Pi(k) percent of the population has completed the event, k, at time, T (k) , over ' the interval, AT=Ti(k)-Ti_1 k).

Pj = Percent of population which requires tj minutes to complete activity, k ->k+1.

Tm(k+1) = Time at which' ath element of the histogram has completed event, k+1; m=1,2,...,1+j-1,...I+J-1 Pm(k+1) = Percent of population represented by the ath element of the histogram for event, k+1. That is, P m(k+1) percent of the population has completed the event, k+1, at time, Tm(k+1), over "

the time interval, AT=Ta (k+1) - T m-1(k+1)

Then, Pm(k+1) = I 1,j ->

Pi (k)pj /100 i+j-1=m Tm(k+1) =Ti(k)+tj where i+j-1=m I+J-l Note: I Pm(k+1) =1 i

m=1 Example: Dependent Events--Application of Algorithm No. 1 Time Distribution Time Distribution of of event. k activity. k->k+1 i Pi (k) Ti(k) j Pj tj [

1 30 10 1 50 20 l

2 50 20 2 30 30 3 10 30 3 20 40 4 10 40 15 l

f Let a ='l. Then i =.j = 1 .

P 1 (k+1) = (30) (50)/100 = 15 ;Ti(k+1) = 10+20=30 Let m.= 2. Then i=1, j=2 - ; i=2, j=1 P2 (k+1) = [(30) (30) + (50) (50) ]/100=34 T2 (k+1) = 10 + 30 = 40 Let a = 3. Then i = 1, j = 3 ; i = 2, j=2 ; i = 3, j =1 P3 (k+1) = [(30) (20) + (50) (30) + (10) (50)]/100 = 26 T3 (k+1) = 10 + 40 = 50 Let a = 4. Then i = 2, j=3 ; i = 3, j=2 ; i = 4, j = 1 P4 (k+1) = 18 , T4 (k+1) = 60

! Let a = 5. Then i = 3, j=3 ; i =.4, j = 2 P5(k+1) = 5, T5(k+1) = 70 Let a = 6. Then i = 4, j =3 ; P i(k+1) =2, Ti(k+1) = 80 ,

Comcuted Time distribution of event k+1 3 Pm(k+1) Ta(k+1) 1 15 30 l 2 34 40 3 26 50 4 18 60 5 5 70 6 2 80 i

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Definitially, the distribution for Event No 2 is identical to Distribution lA (or 1B), since Event No. 1 (the normal condition)

C_T/ is a continuum. To obtain the needed distributions run apply algorithm No. 1 repeatedly, as indicated below:

in order to which is Acolv Alcorithm No. 1 to Obtain Dist. for named Distribution Distributions lA and 2 Event No. 3 A Distributions A and 3 Event No. 4 B Distributions B and 4A Event No. 5 C Distributions.1A_and 4A Event No. 5 D Distributions 1B and 4B Event No. 5 E Table 3 lists the calcuated distributions.

Trio Generation Distributions for Week-end Scenarios For these scenarios it is assumed that the notification process for the beach populace begins at the Alert level, while that for the rest of the,EPZ begins 15 minutes later at the General Emergency levels ~ The trip generation time distribution for the beach is described by Distribution E. For residents and tourists who are inland, Distribution D applies, for employees within the EPZ (a topic discussed later), we apply Distribution A.

There is limited shelter capacity on the beach areas, relative to the number of people who could visit there on a week-end day. It is therefore reasonable to expect that the evacuation process will begin on the beach areas immediately following the notification that the beaches are closed, regardless of a formal request to evacuate.

The sirens will not be activated until the General Emergency i level is reached. This level is assumed to be reached 15 minutes L after the Site Area Emergency level. ~ We also postulate that the evacuation order is given 10 minutes after the General Emergency is declared. Thus, for a given worst-case accident scenario, we postulate two evacuation scenarios (beach area and inland) which are temporaly displaced with respect to one-another:

1. The Trip Generation time distribution for the beach areas has its origin point (i.e. timer zero) at the time of the

. announcement of the Site Area Emergency (assumed to be concurrent with the Alert level).

2. The Trip Generation time distribution for the remainder of the EPZ has its origin point (i.e. time zero) at the time of the issuance of the order to evacuate, which is 4

/~

i

(_)T I

17 i

L

Table 3. Computed Trip Generation cumulative Distributions (percent) .

~Elansed Time (Hr: Min) & H E D E 0:05 0 0 0 0 0 0:10 10 0 0 1 2 0:15 31 2 0 5 9 0:20 57 7 0 11 21 0:25 67 16 1 18 32 0:30 74 26 3 26 44 0:35 81 35 5 35 55 0:40 87 44 8 43 64 0:45 92 52 11 49 70 0:50 93 60 16 53 72 0:55 94 66 21 57 74 1:00 95

• 71 26 62 76 1:05 96 76 30 66 78 1:10 96 79 35 70 80 1:15 97 83 40 74 83 1:20 97 86 44 78 85 1:25 98 88 49 81 88 1:30 98 89 53 83 90 1:35 98 91 57 J5 93 1:40 .-

98 92 61 81 95 1:45 99 93 65 86 97 1:50 99 94 68 87 97 1:55 99 94 71 87 98 2:00 99 95 73 88 98

. Cs 2:05 100 96 75 89 99 2:10 97 77 90 99 2:15 97 79 91 100 2:20 98 81 92 2:25 99 82 94 2:30 100 84 94 2:35 86 95 2:40 87 96 2:45 88 96 2:50 90 96 2:55 91 96 3:00 92 96 3:05 93 97 3:10 93 97 3:15 94 98 3:20 95 98 3:25 95 98 3:30 96 99 3:35 96 99 3:40 97 100 3:45 97 3:50 98 3:55 98 4:00 99 4:05 99 4:10 100 t

18

- ,- , , . . , ~ . _ , - _ - , -- .--- - , - n - , - , -

7 assumed to take place 10 minutes after the General Emergency is declared, or 25 minutes after the

[} announcement of Site Area Emergency.

On this basis, reference to Dist. E of Table 3 indicates that an estimated 9 percent of the population in the beach area has been mobilized at the time the General Emergency is announced.

Also, about 32 percent of the beach area population is ready to evacuate to evacuate -- is andgiven.

has started to evacuate -- at the time the order On tho'other hand, only one percent of the inland resident and tourist population, and 10 percent of the employee population will be prepared to evacuate when the order to evacuate is issued. Figure 19 displays these distributions (A, D and E) on the same time scale, showing their relative temporal displacement.

The I-DYNEV model is designed to accept varying rates of trip generation for sach origin centroid, expressed in the form of histograms. We partition these centroids into three sets --

those for beach area traffic, for inland residents and inland employees. These histograms, which represent Distributions A, D and E, properly displaced with respect to one another, are tabulated in Table 4.

.These tabulations present the trips generated Juni the rates of trip-making within each indicated time period, both expressed as a percentage of the total number of trips to be generated at each' centroid. The rate of trip making is found by:

Rate = Tgfes cenerated in Time Period (nercent)

Duration of Time Period (hours)

Trin Generation Distribution for week-day scenarios

'The mid-day scenario produces a Trip Generation distribution which is a linear combination of Distributions C and D.

Distribution C applies to those households with at least one commuter, while Distribution D applies to those households with

' no commutars. This linear combination results in Distribution F, reflecting the fact that about 25 percent of the households

! within the EPZ has no commuters, according to the telephone survey (see Appendix G). Distribution F is listed in Table 5 and is also presented the IDYNEV system.

in Table 6 in a format suitable for input to Snow' Clearance Time Distribution Inclement weather scenarios involving snowfall must address the time lags associated with snow clearance. Discussions with local officials indicate that snow plowing equipment is mobilized and deployed during the snowfall to maintain passable roads. The O

19

________._._________..._________.._____.____._.___.n . . _ - _ _ - _ _ _ _ _ _ _ _ _ _ _ . . _ . = _ _ _ _ . _ . _ _ _ _ _ _ _ . _ _ _ . _ _ . _

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Table 4. Trip Generation Time Histograms O for the Week-end Scenarios Time Period Percent of Total Trips and Rates which are Relative to Generated During the Indicated Time Periods Time of Order to Evacuate Beach Areas Inland Residents Inland Empl.

(Hrs.: Min.)

(from Dist. E) (from Dist. D) (from Dist. A)

Trips Rate Trips Rate Trips Rate

-0:20 to -0:10 9 54 0 0 0 0

-0:10 to -0:00 23 138 0 0 0 0 0:00 to 0:15 32 128 18 72 31 124 0:15 to 0:30 10 40 25 100 43 172 0:30 to 0:45 6 24 14 56 18 72 0:45 to 1:15 15 30 24 48 5 10 1:15 to 1:45 5 10 6 12 3 6 1:45 to 2:30 0 0 9 12 0 0 2:30 to 3:30 0 0 4 4 0 0 3:30 onward 0 0 0 0 0 0 ,-

Units: Trips, percent of total trips at centroid during indicated. Time Period Rate, percent of total trips per hour during indicated Time Period i

Note: Time zero for Distribution E occurs 25 minutes prior to the Order to Evacuate, i.e. at the Site Emergency level. No one is ready to evacuate over the first 5 minutes, thus we show the time from -0:20 instead of

-0:25.

l l 21 l

(s Table 5. Computed Trip Generation Time. Distribution

() for the Mid-week, Mid-day Scenario (Distribution F)

Elapsed Time Cum. Pct. of Elapsed Time Cum. Pct of (Hrs: Mini Tries Generated (Hrs: Mini Tries Generated 0:05 0 2:05 79 0:10 0 2:10 80 0:15 1 2:15 02 0:20 3 2:20 84 0:25 5 2:25 85 0:30 9 2:30 87 0:35 23 2:35 88 0:40 17 2:40 89 0:45 21 2:45 90 ,

0:50 25 2:50 91 1 0:55 30 2:55 92 1:00 35 3:00 93 1:05 39 3:05 94 1:10 44 3:10 94 1:15 49 3:15 95 1:20 53 3:20 96 1:25 57 3:25 96 1:30 61 3:30 97

(' 1:35 64 3:35 97 s

1:40 67 3:40 98 1:45 70 3:45 98 l 1:50 73 3:50 99 1:55 75 3:55 99 2:00 77 4:00 100 9

(1) 22

Table 6. Trip Generation Time Histograms for the

() Week-day Scenarios (Dist. F)

Percent of Total Trips and Rates Time Period Relative to which are Generated During the Time of Order to Evacuate Indicated Time Periods fHrs.; Mini Trins Rate 0:00 to 0:15 5 20 0:15 to 0:30 12 48 0:30 to 0:45 13 52 0:45 to 1:15 27 54 1:15 to 1:45 18 36 1:45 to 2:30 14 18.7 2:30 to 3:30 9 9 3:30 to 3:50 2 6 3:50 to 13:50 0 0

? -

Units: Trips, percent of total trips at centroid Rate, percent of total trips, per hour Note: Time zero for Distribution F occurs 10 minutes prior O to the Order to Evacuate, i.e. at the General Emergency level.

l I

e l

l O

23 L

general consensus is that their efforts are generally successful for all but the most extreme blizzards when the rate of snow

((r's) accumulation exceeds that of snow clearance over a period of many hours.

Consequently, it is reasonable to assume that the highway system will remain passable -- albeit at a lower capacity --

under the vast majority of snow conditions. Nevertheless, for the vehiclec to gain access to the highway system, it is necessary for driveways and residential parking lots to be cleared to the extent needed. These clearance activities take time, and this time lag must be incorporated into the trip generation time distributions. Thus, we must postulate a separate distribution for the driveway snow clearance activity and then introduce this distribution into the procedure used to calculate the trip generation time distribution.

The time needed to clear a driveway depends on the depth of snow, the available equipment and the number of able-bodied personnel to perform the task. Since this area is accustomed to heavy recurring snowfalls, it is reasonable to expect that virtually all households have made provision for snow clearance by either owning some form of equipment or by contracting for 7 such service to be performed by others. The following distribution is postulated based on discussions with people in -

the area, for a heavy snowfall.

Elapsed Time Cum. Percent of

. ,r~T (min.) Cleared Driveways 15 5 30 10 45 25 60 40 90 70 120 90 150 100 It is recognized that the snow clearing activity can take place in parallel with other activities, e.g. preparing for evacuation. Nevertheless, we will adopt the conservative point of view that this activity follows the preparation activity, rather than proceeding in parallel with it. This posture will lengthen the temporal extent of the trip generation process.

The above distribution will be identified as Distribution 5.

The event " Driveways cleared of snow" will be identified as Event No. 5 and the event " Leave to Evacuate" is Event No. 6 for this scenario.

We must then perform the following additional operations to compute the trip generation distributions for the inclement weather, snow scenarios:

O 24 l

L

in order to which is Annly Alcorithm No. 1 to Obtain Dist. for . named Distribution O. Distributions A and 5 Event No. 6 G Distributions F and 5 Event No. 6 H Distributions D and 5 Event No. 6 I The results of these calculations are shown in Table 7 in a format consistent with the others. Note:

e Distribution G applies to employees e Distribution H applies to residents and transients during mid-day e Distribution I applies to residents and transients during the evening / weekend.

O I

e i

l

()

25 1

I

9( ) Tabla 7. Trip Generation Time Histograms for the Inclement Weather, Snow, Scenarios (Distributions G, H, I)

Time Period Relative Percent of Trips and Rates which are to Time of Order Generated During the Indicated to Evacuate Time Periods (Hrs.: Min.)

Dist. G Dist. H Dist. I i

Trips Rate Trips Rate Trips Rate 0:00 to 0:15 0 0 0 0 0

' 0 0:15 to 0:30 2 8 0 0 0 0 0:30 to 0:45 5 20 0 0 2 8 0:45 to 1:15 23 46 5 10 1:15 to 1:45 11 22 29 58 13 26 19 38 1:45 to 2:30 32 43 30 40 32 43 2:30 to 3:30 9 9 33 33 24 24 3:30 to 4:30 0 0 14 4:30 to 5:00 14 12 7 12 0 0 5 10 0 - 0 5:00 to 15:00 0 0 0 0 0 0 i

O Units: Trips, percent of total trips at centroid Rate, percent of total trips per hour Note: Time zero for Distributions G, H, I occurs at the General Emergency (sounding of sirens) which is assumed to be 10 minutes prior to the Order to Evacuate.

\ -

\.

26

9. EVAC ATION OF EMPLOYEES

( Table 8 lists the annual average employment figures for the years of 1980* and 1984, in the towns located within the Seabrook Station EPZ. We have also obtained employment figures for the months of July (in-season) and October (off-season). These figures, shown in Table 9, indicate that summer employment is significant in the Towns of Hampton and Rye, but not elsewhere.

As indicated in Table 8, the area within the EPZ has enjoyed a signifiant growth in employment over a period of four years:

about 20 percent increase in New Hampshire and more than doubling in Massachusetts. It is very tenuous to project employment figures for 1986 since employment is usually sensitive to the general health of the nation's economy and, of course, the regional economy. Nevertheless, we have projected these figures forward to 1986, using the growth rates in the 1984-1985 time frame for Massachusetts towns and the mean annual growth rate over 4 years, for the New Hampshire towns. These projections are also given in Table 8.

A careful analysis of the results of the survey taken of the population within the EPZ (see item 17, App. E and App. G) indicates that about 58.2 percent of commuters who live within the EPZ, also work within the EPZ.- Specifically, the survey also revealed that:

1300 Households were interviewed, representing

'3730 persons (i.e. 2.87 persons per household) and O' 1658 commuters (i.e. 0.445 commuters per resident) of whom 965 worked within the EPZ.

On this basis, the projected population (see Table 1) of 142,194 residents within the EPZ corresponds to 63,206 commuters.

Of these, 36,788 (58.2 percent) work within the EPZ. The remainder (68,084 - 36,660 = 31,424) who work within the EPZ, reside outside the EPZ. Thus, during a mid-week, mid-day scenario, these employees will be evacuating along with the other people within the EPZ.

(

For purposes of estimating evacuation traffic demand, we focus on those employees who work within the EPZ and who live l outside the EPZ. (Those who live within the EPZ have already been counted as part of the permanent population). It is therefore necessary to estimate the number of employees -- and l their vehicles -- who work within each town. We proceed as follows:

• The 1980 figures are taken from the Costello Report which cited the Census Bureau as the source. See item 16, Appendix E.

C:)

27 l

( Table 8. Year-round Employment Population Estimates by Community Annual Community Total Emnlovnent Rate 1980 1984 1986fProil (D0t)

New Hamoshire Brentwood 82 133 170 12.9 East Kingston 47 72 89 11.3 Exeter 5,309 5,387 5,430 0.4 Greenland 279 -

524 718 17.1 Hampton 2,845 3,636 4,109 6.3 Hampton Falls 173 296 387 14.4 Kensington 43 77 103 15.7 Kingston 384 670 885 14.9 New Castle 203 43 43 ~67.8 Newfields 678 824 908 5.0 Newton 88 123 145 8.7 North Hampton 599 962 1,218 12.5 Portsmouth 11,825 14,803 16,570 5.8 Rye 505 644 728 6.3 Seabrook 7,234 7,459 7,579 0.8 South Hampton 158 282 377 15.6 (g Stratham 510 947 1.290 16.7 l

(_/ New Hampshire Subtotals 30,962 36,882 40,749 4.5 Massachusetts Amesbury 3,954 7,463 7,880 2.6 Merrimac 496 2,414 2,543 2.6 Newbury 466 2,451 2,580 2.6 Newburyport 5,413 8,999 9,477 2.6 Salisbury 1,254 3,089 3,252 2.6 i West Newbury 411 1.522 1.603 2.6 Massachusetts Subtotals 11,994 25,958 27,335 2.6 TOTAL in EPZ 42,956 62,840 68,084 4.0 SOURCE: New Hampshire and Massachusetts Labor Services and Employment Bureaus for the 1984

. data, i

28

{

.(') Table 9. Employment Population Estimates by Community for the Months of' July and October July Oct.

Community 1984 1984 New Hameshire Brentwood 152 127 East Kingston 78 75 Exeter 5,634 5,508 Greenland 544 554 Hampton 5,213 3,232

.Hampton Falls 318 371 Kensington 79 . 70 Kingston 719 707 New Castle 54 55 Newfields 848 878 Newton 133 150 North Hampton 980 1,075 Portsmouth 15,233 15,103 Rye 862 643 Seabrook 5,116 6,005 South Hampton 361 367 Stratham 934 1.015 New Hampshire subtotals 37,258 35,935

() July 1985 Oct.

1985 Massachusetts

( Amesbury 7,707 7,715 Merrimac 2,486 2,489 Newbury 2,524 2,526 Newburyport 9,268 9,278 Salisbury 3,181 3,184 West Newbury 1,567 1.569 Massachusetts Subtotals 26,733 26,761 I

TOTAL in EPZ 63,991 62,696 i

SOURCE

New Hampshire and Massachusetts l Labor Services and Employment Bureaus.

[ .

l l

l

()

29

l J

Let:

Ei = Total number of employees within Town, i Ci = Total number of residents within Town, i, who commute ,

j to work * '

I Ni = Total number of residents within Town, i, who commute I to work in Town, i j Nzi = Total number of employees in Town i who commute there from another town Inside the EPZ NE i = Total number of employees in Town, i, who commute there from outside the EPZ.  !

Ri = Population of Town, i (i.e. Residents)

Pc = Percentage of residents in EPZ vho commute = 44.5 ,

)

Pi i = Percent of commuters in Town, i, who work in Town, 1 7

i Pei = Percentage of commuters who originate their trips ,

i i

within the EPZ and also work within the EPZ = 58.2 j By definition:  ;

1

• l

(() Ci = PcRi ; C= Ci L l

I Ri E=I Ei ;R=

! i i Ni = P 11Ci = Pii PcRi Nr . I (Ni + Nyi) = Per C i

1

N E=iI NEI = E - N I 1 e

Ei = Ni + NIi + NEi i where l 1

l E =. Total number of employees within the EPZ Nr = Total number of employees within the EPZ who also

live within the EPZ.

NE = Total number of employees within the EPZ who live  :

! outside the EPZ i .

30  ;

R = Total number of residents within the EPZ

(~' *

' )T

(_ C = Total number of residents within the EPZ who commute to work Given

1. Ei

2. Per and Pc

3. Ri

4. Ci=PRci Immediately, we get C, E, R, N I , NE using the expressions above.

The values of Pii for each town

• may be found from the 1980 census data (Appendix H). The values, N i , can then be calculated. Then, T l

NEi + Nzi = Ei - Ni where the right-hand side is known at this point. Summing both

{} sides over 1:

N E+iI Nzi = E-INi i

or NE = E - PcIC from the definition of N I , above and E Nzi = PcIC- iI Ni i

In the absence of any more definite data, it is reasonable to assume that the proportion of NEi to Nzi is the same for all towns, i. Specifically, define r = Nzi/NE i which is equivalent to r = I Nzi/NE l *The data for eight towns are not available, we will estimate these values, based on their respective population densities, I employment, and locations.

O 31

Then, for every town, i, the number of employees from outside the EPZ is estimated as:

O NEi = (Ei -Ni )/(1+r)

Table 10 presents the results.

In Progress Report 1, we accepted the NRC estimates of manufacturing and industrial employment since we had not yet obtained current estimates of total employment from the cognizant State agencies. Now that we have that information, we will replace the employment estimates used in Progress Report No. I with those in Table 10.

First, we must guard against double-counting those employees.

who work at the beach since their vehicles have already been ,

accounted for. Conservatively, it is reasonable to estimate that 25 percent of the employees in the Towns of Hampton and hye work at the beach areas and that 10 percent of employees in the Towns of Seabrook, Salisbury and Newbury work at the beach areas.

Second, the employment for Seabrook includes those working on Seabrook Station construction, based on 1984 figures. These figures reflect work on both-units, i.e. before the second unit was cancelled. We will estimate that some 4,000 employees at '

Seabrook Station are included in the employment at seabrook Town, ,

who will not be present after.the Station goes on-line. Of these, it is estimated that

( 4000 x (4,222/7579) = 2228 live external to the EPZ.

Third, employment over the week-end is some fraction of employment during aid week. This fraction will vary depending on the season and by location within the EPZ. Since we do not have data for this fraction, we will make some reasonable assumptions:

e For the tourist-oriented Towns of Hampton, Hampton Falls, New Castle, North Hampton, Rye, Seabrook, South Hampton, Salisburg and Newburg, we estimate that 70 percent of all employees work on the weekend, during the season.

e For the remaining towns, we will estimate that 40 percent (i of all employees work on the weekend, during the season.

ti e Off-season, we will estimate this fraction of weekend employment at 25 percent for all towns.

e During mid-week, all employees will be considered to be at l work.

4 32 i

s

._._---,--_r _ ._ , _ , .._r.. -

. - - . . , _ , . , _ - _ _ . . . _ , , . . , _ _ , . , , . _ _ - . _ _ _ _ _ - _ - , , - . , . _ - - - - . , _ - , - ,-.,.-,c-. --

i' I.

() Table 10. Estimates of Evacuating kaployees i

1986 Pii 1986 Employees

. / #

Population (pct) Emp1.

External Evac.

Sommunity from Town Empl. Empl.

New Hamnshire Ri El Ni NEi Vehicles Brentwood 2,039 10* 170 91 East Kingston 56 48 1,262 10* 89 56 23 i

Exeter 11,744 20 51.1 5,430 2,671 1,956 1,686 Greenland 2,225 40 718 396 228 Hampton 13,234 197 32.4 4,109 1,908 1,560 1,345

.Hampton Falls 1,474 25* 387 164 158 136

, Kensington 1,385 10* 103 62 29 Kingston 5,085 25 24.7 885 559 231 199 New Castle 621 10* 43 28 Newfields 11 9 868 40= 908 155 534 i

I Newton 3,744 460 8.3 145 138 5 North Hampton 3,638 16.5 1,218 267 4

i Portsmouth 26,881 674 581 61.2 16,570 7,321 6,556 5,652 i Rye 5,099 19.1 728

' 433 209 180 Seabrook 8,158 44.7 7,579 1,623 4,221 3,640 *

, South Hampton 699 25* 377 78 j Stratham 3,445 212 183 ,

22.1 1,290 339 674 581 '

l i

(:) Massachusetts j Amesbury 14,258 38.3 7,880 2,430 3,863 Merrimac 3,330 i

4,420 22.4 2,543 441 1,490 1,284

!- Mawbury 5,479 16.6 2,580 405 1,542 1,329 Newburyport 16,414 48.5 9,477 3,543 4,206 Salisbury 3,626 6,726 21.4 3,252 641 1,850 1,595 West Newbury 3,296 12.2 1,603 179 1,009 870 TOTAL in EPZ 142,194 68,084 23,928 31,298 26,980-f' t

f 4

I Nzi = 0.582 x 63,206 - 23,928 = 12,858 l i

NE = 68,084 - 0.582 x 63,206 = 31,298 r = 12,858/31,298 = 0.411 .

• Estimated 4

O 33

Fourth, it is necessary to recognize that the Trip Generation f <-

(,) time distributier. for employees differs markedly from that which is applicable for residents. The sequence of activities for employees is shown in Figure 18(e) . We must therefore apply Distribution A (see Table 3) to the employee trips.

' Table 11 presents the estimates of evacuating vehicles containing employees, for various scenarios, taking into account the comments made above. Table 4 presents the Trip Generation histograms for these employees.

a 4 O ,

I t

s i'

l' l

l i

i r

l 34 4

. ,g

() Table 11. Evacuating Employees for Various Scenarios, Expressed in Vehicles Community Summer Off-Season Off-Season Season Week-end Week-end Midweek Midweek (off-beach) (Total) (off-beach)

New Hamoshire t Brentwood 19 12 48 48 l East Kingston 7 5 20 20

Exeter 674 422 1,686 1,686 Greenland 79 49 197 197 Hampton 706 336 1,345 1,009 Hampton Falls 95 34 136 136 Kensington 10 6 25 25 Kingston 80 50 199 199 New Castle 4 2 9 9 Newfields 184 115 460 460 Newton 2 1 4 4 North Hampton 407 145 581 581 Portsmouth 2,261 1,413 5,652 5,652 i Rye- 95 45 180 135

~

Seabrook 1,083 430 1,719 1,547

' South Hampton 128 46 183 183 Stratham 232 145 581 581 O

Mapsachusetts Amesbury 1,332 833 3,330 3,330 Merrimac 514 321 1,284 1,284 Newbury 837 332 1,329 1,196 Newburyport 1,450 907 3,626 3,626 Salisbury 1,005 399 1,595 1,436 West Newbury 348 218 870 870 TOTAL in EPZ 11,553 6,266 25,059 24,214 f

6

~

i l

1 l

O

)

35 l

e

10. DEMAND ESTIMATION FOR OFF-SEASON AND MID-WEEK IN-SEASOU I

SCENARIOS .

t

, For off-season scenarios, it is necessary to estimate transient population. The number.of units available for overnight accommodations during the off-season is significantly less than during the: season. Furthermore, the occupancy rates of these rooms are also.significantly lower during the off-season.  ;

The NRC report (by Kaltman) presents the number of units available on a yearly basis and assigns one vehicle per unit.

We'believe this approach overstates the number of such l vehicles which can reasonably be expected to be within the EPZ in l the off season. Telephone inquiries with hotel / motel managers

( indicates an occupancy rate of about 50 percent.

We will retain the'NRC estimates for the vehicles parked in lots along Route 1 within the EPZ servicing persons who reside outside the EPZ.

i The permanent residents are the same as for the in-season t

scenarios. However, the number of vehicles used to evacuate the permanent residents may differ for a mid-day scenario since the school children will be transported separately. Thus, many

. . . households with multiple-car ownership who have children in school at the time of the accident, may use one vehicle to i evacuate, rather than the two vehicles they would otherwise use l to transport'the school children who would be at home.

() The rationale supporting the estimate of the number of vehicles used to evacuate the permanent residents, is given in Exhibit 2. The survey (see Appendix G) yields the number of school children in households of different size. We can then calculate the household sizes when the children in school are evacuated. separately. Refer to Exhibit 2 for the data used j below:

j 36 l

H.H. Size w/o No. of H.H. in No. of Cars Used children Survey Samole* Assumo. 1 Assumo. 2 0 1 216 192 192 (Note 1) 2 739 730 730 (Note 2) 3 242 242 242 4 92 92 129 5 18 32 32 6+ 13 23 23 1,311 1,348 Note 1: 163 + (216 - 187)

Note 2: 450 x 0.958 + (739 - 450 x 0.958)

The adoption of the estimate of 2.6 persons per vehicle for households containing school children, determined in Exhibit 2, results in a total of 1435 vehicles servicing the sampled 3,730 residents. If we apply Assumption 2 of Exhibit 2 to these households which are reduced in size due to the children being in school, then the number of vehicles used for evacuation is 1348, as shown above.

The children, which number 786 for this sample of households, would be transported in approximately 15 buses. A bus is

" equivalent" to two passenger cars, approximately. Thus, the total number of vehicles for the mid-day, mid-week scenario is 1378 vehicles, compared with 1,435 vehicles for the weekend. This represents a net reduction of about 4 percent in the number of

() evacuating vehicles, even after accounting for the school buses.

We will adopt the conservative posture that some households whose size is reduced to 4 or fewer persons when the children are in school, and who have access to more than one vehicle, will take two vehicles in anticipation of the eventual need to accommodate the children. Thus, we will not apply the indicated 4 percent reduction in vehicle demand, for the purpose of estimating evacuation travel times. Instead, the evacuating vehicle population will be the same as used for the in-season scenarios.

l *187 + 450 x 0.042 + 246 x 0.041 + 247 x.0.004 = 216 450 x 0,.958 + 246 x 0.429 + 247 x 0.498 + 206 x 0.358 + 64 x 0.333

= 730 246 x 0.53 + 247 x 0.255 + 106 x 0.321 + 64 x 0.231 = 242 247 x 0.247 +106 x 0.198 + 64 x 0.154 = 92 106 x 0.123 + 64 x 0.077 = 18 64 x 0.205 = 13 (Percents taken from page G-2) 37 i

Evacuatina volumes for the Summer Mid-week. Mid-day Scenario .

( For this scenario, it is assumed that:

1. Beach area population is 75 percent of capacity

2. Employment within the EPZ is at usual mid-week levels. That is, no allowance is made for the fact that some workers will be on vacation.

3. Commuters who live within the EPZ will return home, then evacuate with the other members of the household.

4. The Trip Generation distributions are:

e Distribution E for beach area e Distribution A for inland employees e

Distribution F for inland residents and tourists O

4 l

O i

38 l

11. PRELIMINARY TRAFFIC CONTROL AND MANAGEMENT TACTICS

() This section presents the Dreliminary set of traffic control and management tactics which are designed to expedite the movement of evacuating traffic. The resources _ required to implement these tactics include:

o Personnel with the capabilities of successfully performing the planned control functions of traffic guides, o Equipment to assist these personnel in the performance of their tasks:

Traffic Barriers Traffic Cones e A well-defined plan which defines all necessary details and is documented in a format which is easy to understand.

The functions to be performed in the field are:

1. Facilitate traffic movements which serve to expedite '

travel out of the EPZ along routes, which the analysis has found to be, most effective.

2. Discourace traffic movements which permit vehicles to travel in a direction which takes them significantly closer to the power station.

(")

(_/ 3. Discourace traffic movements which are non productive or which interfere with the efficient movement of other traffic streams. For example,' avoid traffic movements which focus demand on a limited number of highways while other highways are under-utilized.

We employ the terms " facilitate" and " discourage" rather than

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

e He/she may be traveling home from work or from another location, to join other family members preliminary to evacuating.

e The driver may be taking a detour from the evacuation route in order to pick up a relative.

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

The implementation of a plan must provide room for the application of sound judgment.

O 39

This set of control tactics is oreliminarv for the following reasons:

O

1. There is a need to survey these critical locations in the.

field in order to refine--or correct--the sketches presented herein. .

These' sketches are based on the data collected during previous field surveys and upon large-scale maps. We have found these maps to be less than accurate in some respects. Also, the previous surveys did not focus at great length on any particular set of locations, since we did not know which would be included in the set of Traffic Control Posts (TCP).

l

2. There is a need to review these tactics with the officials of the towns who will be implementing them: police and fire department personnel, specifically.-

Clearly, any control tactics should be reviewed by

. trained personnel who are experienced in controlling traffic and who are familiar with the likely traffic patterns. Also these personnel know which intersections' are probable bottlenecks under heavy traffic demand -

conditions. -

3. There is a need to prioritize these.TCP. Application of traffic control at some TCP will have a more pronounced influence on expediting traffic movements, than applying

?

(() control at other TCP. Thus, during the mobilization of personnel to respond to the emergency situation, those TCP which are assigned a higher priority, will be manned earlier than the others.

This setting of priorities should be undertaken with the concurrence of town police. These priorities should be compatible with the availability'of local manpower resources.

4. This set of recommended control tactics is incomplete. We have omitted some locations at the present time for the following reasons:

e There are locations were our existing knowledge of the

, geometrics is inadequate for this purpose. For example,

! the Hampton Interchange is an important TCP which must be

! carefully surveyed. The City of Portsmouth is another i

srea that must be surveyed in more detail prior to our

description of the TCP there.

e The sparsely populated towns to the west of I95 have limited personnel resources. We have therefore deferred

the development of control tactics in these towns until we j have reviewed our initial designs with local officials.

O 40 1

[.

It is our intent to perform these detailed surveys and

() discussions with local officials in the near future, so as to refine, revise and otherwise complete the descriptions of the traffic control policies presented on the following pages.

In each sketch which appears in Appendix I, the control policy is presented in a manner which is self-explanatory. Since this is a Procress Report, we would appreciate any comments which can assist us in improving these preliminary designs.

5 4

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1

12. EVACUATION TIME ESTIMATES (ETE)

( This section presents the results of the computer analyses to date using the IDYNEV System, for eight of the ten scenarios described in Section 7. Table 12 summarizes the factors defining the environment for each scenario.

Table 13 presents the ETE for 8 of the 10 scenarios to be considered for the full EPZ. The remaining two will be done-shortly. Figures 20 through 27 display these figures in graphical format. These estimates include the effects of realistic trip generation distributions, current employment figures, and the control policies of Appenidx I. Additional

' control policies for Portsmouth town and the western towns of the N.'H. EPZ may lead to some changes of these ETE, but such changes are expected to be limited.

Future ETE Develoements All of these scenarios address the case where the entire EPZ is evacuated. Given that an accident occurs, it is~unlikely that it will be necessary to evacuate..the entire population within the

.EPZ. It is therefore necessary to develop additional scenarios which consider the evacuation of a portion of the EPZ.

The Costello report displays an EPZ which is partitioned into seven "sub-zones" or Emergency Response Planning Areas (ERPA)*

identified by the letters A-G. They also identify three " quads" O- or portions of the EPZ labelled, respectively, Northeast, Northwest and Southwest. .

In general, we concur with that approach and suggest some small modifications:

1. Move the town of Stratham from ERPA F to ERPA G. A ray drawn from the Station which lies close to the Hampton Falls-Hampton border (which is also the border between ERPA C and D) extends into the western part of Stratham.

Thus, the 10-mile region which consists of ERPA A, D and G will also include the town of Stratham. Therefore, Stratham should be included in ERPA G. (Besides, ERPA F, is by far, the largest within the EPZ and can afford to be reduced in size.)

2. We suggest that the entire town of Hampton Falls be included within this ERPA A, since there is no boundary,

, .either natural (e.g. stream) or man-made (e.g. a highway) 4 which can effectively act as a dividing line.

, 3. Rename these regions, " North", " hest" and " South".

t L

l*

j *We will use the more common term, ERPA.

O 42 L -

O O v (m\

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Table 12. Description of Evacuation Scenarios 1-10 Scenario Season Day Time Wea ther Comments 1 Summer Weekend Mid-day Good Deach area population at capacity. Employees are at 70 pet. of mid-week in towns with beach areas, 40 pct.

in remaining towns. Tourists fill available seasonal and overnight facilities, with half of them at the beach areas.

2 Summer Weekend Mid-day Rain As above. Sudden rain occurs with beach population at capacity concurrent with accident at Seabrook Station.

3 Summer Mid-week Mid-day Good Beach area and tourist population at 75 pct. of capacity.

Employees are at 100 pct of mid-week work force.

4 Summer Mid-week Mid-day Rain As above. Sudden rain occurs, a

w 5 Of f-season Mid-week Mid-day Good Tourist' population at 50 pet. of yearly capacity (i.e.

facilities which remain open the entire year) . No beach area transients. Employees at 100 pct.

6 Off-Season Mid-week Mid-day Rair) As above, but for inclement (rain) weather.

7 Of f-Season Mid-week Mid-day Snow Conditions the same as for Scenario 5 except that there is inclement weather (snow). Evacuees must clear driveways.

8 Off-Season Mid-week Evening Good Tourist population at 50 pet. of yearly capacity.

• No Weekend All day beach area transients. Employees at 25 pet. o f mid-week, mid-day.

9 Off-Season Mid-week Evening Rain As .above, but for inclement (rain) weather.

Weekend All day 10 Off-Season Mid-week Evening Snow As above, but for inclement (snow) weather. Evacuees Weekend All day must clear driveways.

Table 13. ETE for Scenarios 1 - 10

() Distance from Elapsed Times from the Order to Evacuate at which Indicated Percent of Subarea Population Seabook Station is Evacuated (HR: MIN)

(Miles) Poculation M M M M 100%

Scenario 1 2 16,400 0:50 2:30 4:00 4:50 6:00 5 44,200 0:50 2:05 3:35 4:50 6:15 10 83,000 0:50 2:00 3:25 4:35 6:40 EPZ Bdry. 98,800 0:55 2:05 3:35 5:05 7:30 Scenario 2 i

2 16,400 1:20 3:25 5:20 6:25 8:00 5 44,200 1:05 2:40 4:35 6:10 8:10 10 83,000 1:10 2:35 4:45 6:30 9:00 EPZ Bdry. 98,800 1:10 2:35 4:45 6:30 9:00 Scenario 3 2 13,400 0:30 1:55 3:20 4:00 4:35 5 39,200 0:50 2:00 3:30 4:25 6:00

,10 82,500 0:55 2:05 3:30 4:40 7:10 EPZ Bdry. 101,900 1:00 2:15 3:55 5:10 8:00 3

Ecenario 4 1

2 13,400 0:45 2:35 4:25 5:15 6:00 5 39,200 1:00 2:35 4:30 5:40 7:30-10 82,500 1:10 2:40 4:30 6:00 8:45 EPZ Bdry. 101,900 1:10 2:50 4:55 6:40 9:20 Scenario 5 2 6,600 0:40 1:30 2:40 3:15 3:50 5 26,300 0:40 1:40 3:10 4:00 5:40 10 64,700 0:55 1:55 3:10 4:20 6:45

, EPZ Bdry. 82,100 1:05 2:10 3:30 4:50 7:40 Scenario 6

2 6,600 0 50 2

00 3:25 4:10 4:50 l 5 26,300 1:00 2:15 3:45 5:25 7:10 t 10 64,700 1:10 2:20 4:00 5:45 oB:20 EPZ Bdry. 82,100 1:15 2:40 4:35 6:20 9:00 g Scenario 7 2

5 In process i 10 EPZ Bdry.

(

44 f

1

i i Table 13. ETE for Scenarios 1.- 10

[- (} (concluded)

Elapsed Times from the Order to Evacuate at Distance from which Indicated Percent of Subarea Population Seabock Station is Evacuated (HR: MIN)

(Miles) Ponulation 21), gj21 211 igi 100%

Scenario 8 2 4,900 0:25 1:15 2:00 2:25 3:10 5 21,000 0:35 1:15 2:15 3:40 5:10 10 49,800 0:40 1:15 2:20- 3:25 6:05 EPZ Bdry. 62,200 0:45 1:30 2:40 4:00 6:15 i

scenario 9 2 4,900 0:40 1:30 2:40 3:05 3:20 5 21,000 0:40 1:35 2:40 4:40 6:40 10 49,800 0:50 1:55 3:20 5:00 7:35 f Scenario 10 ,-

2 5 In process 10 i EPZ Bdry.

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Figure 27. Elapsed Times from Start of Evacuation for Regions within Seabrook Station EPZ

g^s Figure 28 delineates these ERPA. -

\-) For analyzing scenarios wherein only a portion of the EPZ is evacuated, we identify the following regions (groups of ERPA):

Recion Radius ERPA Desianation 2

1 EPZ bdry. A-G Entire EPZ 2 EPZ bdry. A, D, G North Region 3 EPZ bdry. A, C, F West Region 4 EPZ bdry. A, B, E South Region 5 Five Miles A, B, C, D Entire Five-Mile Region 6 Five Miles A, D North Region 7 Five Miles A, C West Region 8 Five Miles A, B South Region [ ,

9 Two Miles A Entire Two-Mile Region Table 14 indicates the towns within each ERPA.

Note: All beach areas, are alvavs evacuated, including those outside of the Region ordered to evacuate.

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! Table 14. Towns Included Within ERPA ERPA Towns comorisine Indicated ERPA A Hampton Falls, Seabrook B Amesbury, Salisbury C Kensington, South Hampton D Hampton, North Hampton E Merrimac, Newbury, Newburyport, West Newbury F Brentwood, East Kingston, Exeter, Kingston, Newfields, Newton G , Greenland, New Castle, Portsmouth, Rye,

Stratham

.O 4

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