EPA-450/3-74-003-e
November 1973
VEHICLE BEHAVIOR
IN AND AROUND
COMPLEX SOURCES
AND RELATED COMPLEX
SOURCE CHARACTERISTICS
[VOLUME V - AMUSEMENT PARKS
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Water Programs
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
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EPA-450/3-74-003-e
VEHICLE BEHAVIOR
IN AND AROUND
COMPLEX SOURCES
AND RELATED COMPLEX
SOURCE CHARACTERISTICS
VOLUME V - AMUSEMENT PARKS
by
Kenneth Axtell, Jr . and Scott D . Thayer
Geomet, Inc.
50 Monroe Street
Rockville, Maryland 20850
Contract No. 68-02-1094
Task Order No. 3
EPA Project Officer: Edwin Meyer
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Water Programs
Office of Air Quality Planning and Standards
Research Triangle Park, N. C. 27711
November 1973
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This report is issued by the Environmental Protection Agency to report
technical data of interest to a limited number of readers. Copies are
available free of charge to Federal employees, current contractors and
grantees, and nonprofit organizations - as supplies permit - from the
Air Pollution Technical Information Center, Environmental Protection
Agency, Research Triangle Park, North Carolina 27711, or from the
National Technical Information Service, 5285 Port Royal Road, Springfield,
Virginia 22151.
This report was furnished to the Environmental Protection Agency by
Geomet, Inc. , 50 Monroe Street, Rockville, Maryland, in fulfillment
of Contract No. 68-02-1094. The contents of this report are reproduced
herein as received from Geomet, Inc. The opinions, findings, and con-
clusions expressed are those of the author and not necessarily those
of the Environmental Protection Agency. Mention of company or product
names is not to be considered as an endorsement by the Environmental
Protection Agency.
Publication No. EPA 450/3-74-003-e
11
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CONTENTS
Page
List of Figures iv
List of Tables v
Sections
I Conclusions 1
II Recommendations 2
III Introduction 3
IV Characteristics of Amusement Parks 7
V Amusement Park Parameters 10
VI Traffic Parameters 17
VII Analysis 25
VIII Results
IX References 41
iii
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FIGURES
No. Page
1 Schematic Representation of Vehicle Operating Modes at 21
Amusement Parks
2 General Relationship Between Traffic Volume and Toatl 24
Running Time
3 Vehicle Accumulation by Hour for Peak Attendance Days at 29
Major Theme Parks
4 Generalized Methodology ' 32
5 Generalized Methodology Applied to Amusement Parks 33
6 Isopleths (m x 10^) of Mean Summer Afternoon Mixing Heights 37
7 Isopleths (m sec'1) of Mean Summer Wind Speed Averaged 38
Through Afternoon Mixing Layer ,
iv
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TABLES
No. . Page
1 General Information on Amusement Parks 8
2 Attendance, Employment, and Parking at Amusement Parks 11
3 Representative Distribution of Hourly Arrivals and Departures 13
at Major Theme Parks in the United States on a Normal Summer
Weekday ...... . .
4 Representative Dis'tribution'of Hourly Arrivals and Departures 14
at Major Theme Parks in the United States on a July or August
Weekend Day
5 Vehicle Exhaust Emissions at Idle in Grams per Minute 19
6 Example Queue Calculation when Gate Capacity is Exceeded 27
7 Key to Stability Categories (after Turner 1970) 36
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SECTION I
.•.;.;•;"•'" CONCLUSIONS
1. A general methodology has been developed which permits relating
parameters descriptive of traffic behavior associated with developments
(complex sources) to the available descriptive characteristics of the
complexes themselves. These relationships are subsequently to be used by
the sponsor to develop guidance for relating the complex's characteristics
to air quality.
2. The methodology has been successfully applied to the fifth (amusement
parks) of seven types of complexes, with quantitative results presented in
this task report.
3. It is now appropriate to proceed to the next type of complex (highways),
and apply the methodology appropriately.
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SECTION II
RECOMMENDATIONS
It is recommended that, as planned, the project officer employ this
methodology to develop guidance for relating the traffic characteristics
of amusement parks to typical and peak air pollution concentrations.
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SECTION III
INTRODUCTION
OBJECTIVE AND SCOPE
The ability to estimate traffic characteristics for proposed developments
and the resulting effects on air quality is an important prerequisite for
promulgating State Implementation Plans which adequately address themselves
to the maintenance of NAAQS. Prior to estimating the impact of a development
(complex source) on air quality, it is necessary that traffic characteristics
associated with the source be identified and related to parameters of the
development which can be readily identified by the developer a priori.
The purpose of this study is to identify traffic characteristics associated
with specified varieties of complex sources and to relate these characteristics
to readily identifiable parameters of the complexes. The end product of
this task will then be used to develop an Air Pollution Technical Document
which will provide guidance to enable control agencies to relate readily
Identifiable characteristics of complex sources to air quality.
The work is being performed 1n seven sub-tasks. Each sub-task is devoted
to examining vehicle behavior and its relationship to readily obtainable
parameters associated with a different variety of complex source. The
seven categories of complex sources are:
1. Shopping centers (Report EF-263)
2. Sports complexes (stadiums) (Report EF-265)
3. Amusement parks (Report EF-268 - the present report)
4. Major highways (Report EF-267 - in preparation)
5. Recreational areas (e.g., State and National Parks)
6. Parking lots (e.g., Municipal) (Report EF-266)
7. Airports (Report EF-264)
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This, the fifth task report, describes the methodology developed, and
the analysis and results of its application to amusement parks.
APPROACH
Due to internal constraints, the sponsor has been forced to impose a tight
schedule on this project, permitting only two to three weeks for the
analysis and reporting of each sub-task. Accordingly, the employment of
readily available traffic design information for each type of complex has
been suggested as the general approach.
The approach was designed to permit the development of answers to the
following questions posed by the sponsor, using available traffic design
and behavior data, and available data on parameters of the complex:
1. How much area is allotted or occupied by a single motor vehicle?
2. How much or what percentage of the land occupied by the complex
source (and the source's parking facilities) can potentially be occupied
by vehicles? What is the usual percentage?
3. What portion of the vehicles within the complex are likely to be
running at any given time during a 1-hour period? During an 8-hour
period? We are interested in both peak and typical circumstances here.
4. What is the typical and worst case (slowest) vehicle speed over
1-hour and 8-hour periods?
5. How are moving and parked vehicles distributed within the complex
property? (e.g., uniformly?)
6. What are the design parameters for each type of complex which are
likely to be known by the prospective developer beforehand?
7. Which ones of the design parameters in number 6 can be most success-
fully related to traffic and emissions generated by the complex?' What is
the best estimate for relationships between readily obtainable parameters
and emissions?
8. What are the relationships of parking "lot" design to parking densities
and vehicle circulation? What represents a typical design and/or a design
which has highest parking densities, lowest vehicle speeds, longest vehicle
operating times?
9. What meteorological conditions (i.e., atmospheric dilutive capacity)
are likely to occur during periods of peak use? What use level is likely to
occur during periods of worst meteorology (i.e., atmospheric dilutive
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The technical approach developed and implemented in this report consists of,
first, structuring a methodology for describing engine operating modes which
considers both the principal modes in automobile operation in and around
complexes, and the emission significance of each mode. In our analysis this
leads to an important emphasis on engine operating time, with only secondary
significance attached to operating speed and distance.
For the complex being studied, an analysis is made of the typical movements
of vehicles, and their movements under conditions of congestion, caused by
peak traffic loads or by awkward design elements of the complex, or both.
This highlights the traffic operational modes which have greatest effect
on running times, and assists in weeding out the elements or parameters of
the complex which influence these running times most.
The running times in critical modes are found to be dependent on the usage
rate of the complex as a percent of capacity. In addition, absolute values
of usage as a function of time are needed as direct input for estimating
emissions. Therefore, data on usage patterns of the complex by season,
day of the week, and hour of the day are collected and related to capacity
parameters. The results are used in two important ways:
1. To develop quantitative relationships between running times and
various percent-usage parameters; and
2. To provide general usage patterns from which the usage pattern for
a complex of interest can be inferred, if no measured data are available.
Basic parametric values are then derived which define typical base line
running times and use rates; these are used both to provide a point of
departure for the peak case calculations, and as input.to the estimate
of typical conditions.
For any parameter of capacity (e.g., parking, entrance, exit), resulting
increases in running time for each mode are estimated as they may be functions
of the exceedance of that capacity. The base running time is then used
1n conjunction with typical use rates to generate typical combinations of
running times and numbers of vehicles running. Finally, peak (1-hour and
8-hour) use rates are compared to capacities in order to calculate, using
the above derived functionalities, the associated peak values of number of
vehicles running, and running times.
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It may often be possible, in addition, to develop and provide qualitative
guidelines which can provide further insight into factors which may aggravate
or alleviate congestion. These are provided separately from the quantitative
relationships.
Finally, the meteorological conditions associated with the occurrence of
the peak "(vehicle number) (running time)" values are defined; in addition,
periods of the most adverse meteorological conditions are determined, and
the use rate data examined to determine associated use rates and running
times.
The methodology is considered to be completely general, and to apply to
all the complex sources of concern here, with the exception of "major
highway" case cited in Section III titled Objective and Scope. That
special case is recognized in the work statement as an unusual one requiring
different treatment in the context of the other six sources. In any event,
and in the words of that statement, "for highways it may simply be necessary
to tie existing guidelines into a concise package."
The remainder of this report covers special considerations required in the
case of amusement parks, and describes the implementation of this methodology
for these parks, and the results obtained.
Unlike most of the other complex sources investigated, amusement parks
are privately owned rather than municipal developments. Also, this
industry apparently is highly competitive. For these reasons, there is
a noticeable void in published information concerning the design and
operation of amusement parks; no technical or planning survey articles on
the industry were found in the literature. Only general information could
be obtained in telephone surveys of park managers.
Most of the data presented in this report were obtained from two sources:
news releases and articles appearing in the weekly trade newspaper
Amusement Business during the past three years; and general design data
compiled by Economics Research Associates, a leading consultant to amusement
park developers. One result of the data coming from these two sources is
that it is probably much more-,current than that used in task reports for
the other complex sources.
/
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SECTION IV
CHARACTERISTICS OF AMUSEMENT PARKS
Amusement parks can be classified into two general categories, each having
several distinguishing characteristics: (1) "theme" parks patterned after
the original idea of Disneyland, (2) and the traditional amusement parks .
with thrill rides and midway games. All new amusement parks in recent
years have been theme parks. The increasing popularity of theme parks
is attributed to their orientation to family groups and a single admission
charge for all attractions, rather than individual charges for each ride.
Theme parks also draw large numbers of tourists, whereas the traditional
amusement parks depend on local patronage for their revenue. Tourists
tend to come in family groups and prefer attractions that do not split
them up, i.e., sit-down shows and slower-paced fantasy rides. However,
according to C.V. Farman, Manager of Atlanta's Funtown Park, "rides are
what bring in the people."^
In number, theme parks now account for only 10 percent of amusement parks
in the U.S., but they garner 25 percent of the total attendance and 40
percent of the revenue.2 General information on several amusement parks
1s presented in Table 1. Most of these are theme parks, due to lack of
available data for traditional amusement parks. From the standpoint of
traffic, however, there do not appear to be any strong distinctions
between the two types of amusement parks. Therefore, both are considered
1n the traffic analyses in this task report.
Amusement parks are a slightly unusual complex source in one respect--
they are generally privately owned rather than municipal. The importance
of this fact is that much of the data on source parameters and traffic
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Table 1. GENERAL INFORMATION ON AMUSEMENT PARKS
Park
Location
Area of
Park, Acres
Annual
Attendance,
Millions
Cost,
Million $
00
I
Astroworld USA
Cedar Point
Carewinds
Disneyland
Disney World
Hersheypark
King's Island
Land of Oz
Magic Mountain
Opreyland
Playland
Riverside
Six Flags over Mid-America
Six Flags over Texas
Worlds of Fun
King's Dominion
(under const.)
Houston, Texas
Sandusky, Ohio
Charlotte, N.C.
Anaheim, Calif.
Orlando, Fla.
Hershey, Pa.
Cincinnati, Ohio
Beech Mtn., N.C.
Valencia, Calif.
Nashville, Tenn.
Rye, New York
Springfield, Mass,
St. Louis, Mo.
Dallas, Texas
Kansas City, Mo.
Richmond, Va.
60*
n.a.
203
n.a.
3,000
60*
n.a.
30*
200
n.a.
200
n.a.
200
145
500
800
1.2
2.3
1.5
9.5
11.2
0.9
2.2
0.4
1.3
1.5
1.2
1.0
1.4
2.1
1.1
1.6
(est.)
n.a.
27
30
n.a.
400
n.a.
40
n.a.
35
n.a.
n.a.
n.a.
n.a.
n.a.
21
40
n.a. = data not available
* for amusement area only
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at amusement parks cannot be obtained for competitive reasons. The scarcity
of published information applicable to the present investigation has already
been mentioned.
Another characteristic of amusement parks is their seasonal operation.
Most parks have a reduced operating schedule during the winter months,
and some are completely closed during this season. Amusement parks are
usually located either in popular vacation areas or in large metropolitan
areas.
In the past many patrons used public transit to travel to amusement parks
in large cities. However, most of these in-town parks, such as New Jersey's
Palisades and Olympic parks, Coney Island's Steeplechase Park, Baltimore's
Bay Shore Park, and Houston's Playland Park, have closed and the newer
parks are now reached almost exclusively by automobile.
The continuing success of the theme parks indicates that they are not
just a fad.
Announcements of theme parks to open in the next few years include three
$40 million parks planned by the Marriott Corporation, a $40 million park
in Richmond, Virginia planned by Taft Broadcasting, and one new park per
year (after 1975) planned by the Six Flags group. Nevertheless the anticipated
number of new parks per year - three or four — is relatively low in
comparison with the numbers of new complex sources in other categories.
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SECTION V
AMUSEMENT PARK PARAMETERS
The important parameters in characterizing amusement park traffic patterns
are attendance rates and temporal--daily, weekly and seasonal—variations
in attendance. Since these design-related values are not known prior to
the opening of a new amusement park, the developer must estimate attendance
rates and temporal variations based on the findings of feasibility or
market studies and/or the records of other amusement parks, respectively.
ATTENDANCE
Attendance generally is considered to be the best available parameter for
estimating traffic volumes. Annual attendance figures, which generally
are included in feasibility studies, are of limited use for the design of
facilities at amusement parks; however, they are useful for this study
since a typical day's attendance can be estimated by deviding annual
attendance by the number of annual operating days. The value of importance
to amusement park designers is the average attendance on the 10 to 15 busiest
days of the year, referred to as the capacity crowd. All park facilities,
including traffic and parking, are sized to adequately handle this number
of people.3 Average and capacity daily attendance figures for several
parks are shown in Table 2.
Amusement parks are probably the most flexible complex sources in terms of
layout and capacity. Their number of attractions and employees can be
readily expanded or reduced to meet attendance demands. Therefore, it is
incorrect to refer to the capacity of an amusement park as a permanent
fixed value. Rather, capacity is the maximum attendance that can be
accommodated with the existing park configuration.
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Table 2. ATTENDANCE, EMPLOYMENT, AND PARKING AT AMUSEMENT PARKS
Park
Cedar Point
Carowinds
Disney World
Hersheypark
King's Island
Land of Oz
Magic Mountain
^ Opryland
Playland-Rye
Six Flags Over Mid-America
Six Flags Over Texas
Worlds of Fun
Average
Daily
Attendance
16,500
11,000
35,000
7,800
17,600
2,500
7,200
10,300
9,000
9,000
13,000
8,000
Capacity
Daily
Attendance
46,000
Weekend 40,000
•70,000
22,000
38,000
10,100
30,000
27,000
40,000
30,000
40,800
23,000
Summer
Empl oyment
n.a.
1,300
11,000
n.a.
2,000
100
1,200
n.a.
n.a.
1,600
n.a.
1 ,200
Parking
Spaces
n.a.
12,000
Main lot 12,000
Overflow ?
8,000*
10,600
n.a.
9,000
4,600
n.a.
Guest 4,600
Employee 500
Overf 1 ow 500
n.a.
4,800
n.a. - data not available
* parking lot also used for sports stadium and other adjoining tourist attractions
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Like shopping center usage, amusement park attendance has definite seasonal
variations and differences between weekday and weekend crowds. However,
only limited data could be found to quantify these variations. The largest
crowds at almost all parks occur on Saturdays during July and August, and
the design capacity crowd described above is probably equivalent to the
normal July or August weekend-day's attendance. Reduced hours of operation
or closing of parks during winter months accentuates this seasonal variation.
The number of people and cars in a park at any specific time of day is
less than the total daily ticket sales, since some visitors do not arrive
until late afternoon or evening while others come in the morning and leave
in the afternoon. One developer who was questioned about this design
parameter indicated that 75 percent of the total daily attendance is in
a park at the most crowded time of the day.4 However, published survey
data indicate that this percentage may be too low, especially for weekend
days when the largest crowds usually are present. For example, attendance
at Opryland on the peak day in 1973 was 27,,74; at 5:00p.m., there were
25,892 persons, or 95 percent of the day's total attendance, at the peak.
At Carowinds, which admittedly has a typical attendance pattern, a survey
of arrivals by hour showed that 85 percent of the total patrons for the
day entered before noon.
While published data for arrival and departure by hour are sketchy, they
are readily available to amusement park developers for use in designing
their facilities.4 For this study, hourly arrival and departure data were
obtained from Economics Research Associates (ERA), the leading consultant
to the recreation industry on the feasibility and layout of amusement parks.
Composite arrival and departure data prepared by ERA for approximately
the same parks listed in Table 2 are presented for a summer weekday
(typical day) in Table 3 and for a peak or design summer weekend day in
Table 4.
Since arrival and departure patterns constitute a critical input to the
traffic analysis outlined in this report, data specific to the park under
review must be obtained from the developer. The data should be requested
in the same format as Tables 3 and 4.
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Table 3. REPRESENTATIVE DISTRIBUTION OF HOURLY ARRIVALS AND DEPARTURES
AT MAJOR THEMt PARKS IN THE UNITED STATES ON A NORMAL SUMMER WEEKDAY
Time Period Arrivals Departures
10 a.m. -11 a.m. 23%
11 a. m. - 1 2 noon 21
12 noon - 1 p.m. 19
1 p. m. - 2 p. m. 14 1%
2 p. m. - 3 p. m. 8 1
3 p. m. - 4 p. m. 5 3
4 p. m. - 5 p. m. 3 9
5 p.m. - 6 p.m. 3 10
6 p.m. - 7 p.m. 2 9
7 p. m. - 8 p. m. 1 7
8 p. m. - 9 p. m. 1 1.3
9 p. m. -10 p. m. - 21
10 p. m. -11 p. m. - 20
11 p. m. - 12 midnight -_ 6
Total 100% 100%
Source: Economics Research Associates.
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Table 4. REPRESENTATIVE DISTRIBUTION OF HOURLY ARRIVALS AND DEPARTURES
AT MAJOR THEME PARKS IN THE UNITED STATES ON A JULY OR AUGUST WEEKEND DAY
Time Period Arrivals Departures
10 a.m. -11 a.m. 17%
11 a. m. - 12 noon 24
12 noon - 1 p.m. 21 1%
1 p. m. - 2 p. m. 13 1
2 p. m. - 3 p. m. 9 1
3 p. m, - 4 p. m. 6 '4
4 p. m. - 5 p. m. 3 9
5 p. m. - 6 p. m. 3 11
6 p. m. - 7 p. m. 2 8
7 p.m. - 8 p. m. 1 8
8 p.m. - 9 p.m. 1 12
9 p.m. -10 p.m. - 20
10 p.m.'-11 p.m. - 18
11 p. m. - 12 midnight -_ 7_
Total 100% 100%
Source: Economics Research Associates.
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AVERAGE STAY
Another parameter of amusement parks which is related to the daily attendance
pattern is the average length of stay of patrons. Independent references
indicated that seven hours was the average stay for a well-run amusement
park.3»4 No data were found to substantiate that the average stay is
different for weekdays and weekends, but the evening entertainment attractions
which many parks promote during the week would certainly lead to that
conclusion.
If the 7-hour average stay is compared with the 12 hours of operation per
day common to many of the family amusement parks,5 it appears that more
than 75 percent of the days' attendance would be in the park at the peak
period. Therefore, the interpretation of the 7-hour and 75 percent values
that corresponds best with other collected data is as follows: the 7-hour
average stay is for the weekend periods with capacity crowds, when attendees
have an entire day to spend at the park, when the large crowds cause congestion
and longer waiting lines for rides and other attractions, and when more than
75 percent of the total attendees are at the park during the peak period.
In contrast, the weekday stay is probably less than 7 hours, and this is
the period for which the 75 percent of daily attendance at the peak period
is normally applicable.
EMPLOYMENT
A relatively large staff is required at an amusement park, especially at
a theme park with shows. Summer (peak) employment at several of the parks
is.jshown in Table 2. Employees average 15 percent of daily attendance for
the parks listed in Table 2, indicating that they are a significant park
of the traffic and parking volume at an amusement park.
SIZE
Amusement parks are often described by their size in acres. The acreages
of several parks are presented in Table 1. Except where noted, these values
Include parking, buffer, expansion, and other areas in addition to the
amusement park proper. Park acreage apparently is not a good indicator of
either park acitivity or related traffic volume. This is because large
portions of total park areas may be dedicated to such diverse activities as
man-made lakes, gardens, wildlife or conservation areas, picnicing, and
camping.
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PARKING CAPACITY
The number of available parking spaces is a critical parameter for any
complex source, and amusement parks are no exception. The total parking
spaces at several parks are shown in Table 2. In relation to maximum
daily attendance, the available parking spaces for a capacity crowd
average 0.24 spaces per patron for the eight parks having data, with a
range of 0.17 to 0.36 spaces per patron.
According to one amusement park designer, parking needs are determined by
dividing the projected peak attendance by an estimated average vehicle
occupancy, then adding 25 percent as a factor of safety.4 However, the
values reported above indicate that this excess capacity, or factor of
safety, is not found at the existing parks. Like other accomodations at
an amusement park, the parking facilities may be quite flexible in their
layout. Some of the required parking capacity can be obtained from unpaved
grass fields that normally surround the park. Also, remote overflow
parking lots are utilized in conjunction with shuttle bus service.
In the news articles and telephone interviews from which the data on
amusement parks were compiled, there were only a few references to
parking lot overflows during peak periods. In contrast, there were many
reports of incremental expansions of parking capacity in anticipation of
increased attendance.
Parking is generally supervised at large amusement parks, which should
result in higher densities of parked vehicles than with unsupervised parking.
Aisles must be maintained in the lots so that all vehicles are free to depart
at any time. Therefore, the average space per vehicle in parking areas is
usually limited to the range of 190 to 210 square feet per car.
The above discussion of parking requirements was for guest parking only.
At most parks, a separate parking facility is provided for employees.
Very little data was obtained on employee parking lots, but capacity analyses
for these lots are not relevant, since the overflow vehicles can use the
main parking lot.
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SECTION VI
TRAFFIC PARAMETERS
The methodology for describing traffic movement around this complex
source, as outlined in Section VII, requires estimates of the average
running time for the vehicles in and around the amusement park and the
volume of such traffic. Traffic parameters which should be used to
develop these two values are discussed in this section.
PARAMETERS TO ESTABLISH TRAFFIC VOLUMES
The estimated number of persons entering and leaving the park by hour
would be submitted by the developer. This data is converted to hourly
traffic volume by dividing by average vehicle occupancy. Although this
procedure for estimating traffic patterns places much emphasis on a
traffic parameter which is not very precise, it parallels a procedure
used by developers to estimate expected traffic volume for parking lot
design purposes. Also, no more accurate method of projecting traffic
volumes for a proposed park could be determined. As an example of the
effect of the average vehicle occupancy (A.V.O.) on traffic estimates,
a change in the assumed A.V.O. from 4.0 to 3.5 results in a 14.3 percent
Increase in estimated traffic volume.
No published data citing A.V.O. values were found. Economics Research
Associates reported that large theme parks such as those listed in
Table 2 have average vehicle occupancies in the order of 3.6, with a
range In this parameter of 3.2 to 4.0 for different parks. These data
are based on actual surveys by park personnel and on design values used
by ERA. An attempt should certainly be made to obtain an A.V.O. value
specifically for each park reviewed, and possibly even different values
for particular times of the day or week.
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This method of estimating traffic volume assumes that everyone arrives at
the park by automobile. If this assumption is incorrect, the number of
persons using other modes of transportation should be subtracted from the
total attendance before calculating the estimated traffic volumes.
The above procedure does not consider traffic volume generated by peak
employees. In most cases, employees do not use the same entrances or
parking facilities as the guests, nor is their pattern of arrival and
departure the same. Therefore, the entire traffic analysis should be
handled separately. The estimated number of employees entering and leaving
each hour should be easier to establish than the pattern for the park guests,
For employees, an average vehicle occupancy of 1.2 to 1.5 appears to be
appropriate.
PARAMETERS TO ESTABLISH RUNNING TIMES . . .
Concept of Emissions per^ Unit Time
In the immediate vicinity of amusement parks, maximum vehicle speeds rarely
exceed 10 or 15mph, and average speeds are much lower. The usual procedure
for estimating motor vehicle emissions as a function of venicle speed is
not very accurate at these low speeds due to:
a. Difficulty in estimating average operating speed; and
b. Variation in observed emission rates per mile with slight change
in average operating speed.
For amusement parks, analysis shows that traffic operations and their
related emissions are better considered in units of time (grams/minute)
rather than units of distance (grams/mile), for the following reasons:
1. The variations in emission per unit time at different speeds are
relatively insignificant at the lowest speeds;* and
2. Traffic movement in the vicinity of a park can be described more
accurately and more easily in terms of minutes of running time than in
terms of average speed, particularly when engine idling can predominate
during congested periods.
* Less than 10 percent increase in CO and hydrocarbon emissions per minute
from idle to 15 mph.
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Values for automotive pollutant emissions for 1972 in grams/minute at idle
are available from A Study of Emissions from Light Duty Vehicles in Six
Cities.5 They are summarized in Table 5. These test data compare well
with emission factors calculated from the current edition of AP-42,7
when converted to grams/minute at various speeds and then extrapolated
to zero speed.
Table 5. VEHICLE EXHAUST EMISSIONS AT IDLE IN
GRAMS PER MINUTE*
Pollutant
Carbon monoxide
Hydrocarbons
Oxides of Nitrogen
Emissions, gm/min
16.19
1.34
0.11
* These values do not include emissions due to the cold start of engines
or from evaporation of gasoline at the end of a trip ("hot soak"). If
subsequent investigation of the relative magnitude of these emissions,
compared to the totals generated by the methodology of this report,
indicates that they are significant, appropriate values for each cold
start and hot soak can be inserted as the total emissions for the start
and stop modes, respectively. Since data for cold start and hot soak
emissions would be reported per occurrence, there is no need to deter-
mine an associated running time or emission period for the modes.
In applying the recommended procedure of emission estimation, total
emissions from the amusement park at any time would be the product of
the number of vehicles, times average vehicle running time, times the
appropriate emission factor from Table 5.
ETotal = (V) (RT) (EF)' where
V = Traffic volume during period of concern
RT = Average running time, minutes
EF = Emission factor, grams/minute.
-19-
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Operational Modes at Amusement Parks
For purposes of analysis, traffic movement in the vicinity of an amusement
park has been divided into the same eight operational modes that were specified
for shopping centers, airports, and sports stadiums. These are summarized
below and shown schematically in Figure 1. The two major types of access
traffic have been distinguished from each other in the figure. The discussion
which follows is primarily applicable to travel by park guests rather than
employees.
Approach (A) - The time or distance along the immediate access road, usually
on park property, during which traffic movement is strongly affected by
vehicles entering or leaving the park.
Entrance (I) - Waiting and service time at the ticket gate or entranceway
to the parking facility.
Movement in (MI) - Driving time or distance to the designated parking space
(with supervised parking). This also includes waiting time in a queue within
the parking area or driving time to an overflow parking facility.
Stop (S) - Parking of the vehicle and shutoff of the engine.
Start (ST) - Starting of the engine and egress from the parking space.
Movement out (MO) - Driving time or distance from the parking space to the
preferred exitway.
Exit (E) - Movement through the exitway, including waiting time in a queue.
Departure (D) - The time or distance along the immediate access road that
movement continues to be influenced by traffic from the amusement park.
The average running time in each of these modes can be quantified for a
specific park as a function of its physical dimensions, traffic control
procedures, and traffic volume.
-20-
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FUTURE
EXPANSION
AREA
A MU SEMEN T
PARK
Entrance
T 'I- • 58S — —
©£)
1 x---x
(MM
V>l
t
I
Service
Road
_/MnY_^ (stTs j^
V_X x_xV-/ A^j
j
MA IN PARKIN
AREA
«f=
»J
^H
Parking Lot
—71 Ticket
j(ljj Booths
i
i
t
(A)
T
OVERFLOW
PARKING
IH^^B
MAIN ENTRANCE
ROAD
Motel I or
other auxiliary
facilities
LEGEND:
A, etc. = Guest movements
A1. etc. = Employee movements
Public Highway
Figure 1. SCHEMATIC REPRESENTATION OF VEHICLE OPERATING MODES AT
AMUSEMENT PARKS
-21-
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Base Running Time
There is an average minimum vehicle running time for each amusement park
that is associated with periods of low or zero traffic congestion. This
concept of a minimum or base running time is important because it usually
is the most common operating condition at the park and because at most
parks it is expected to be exceeded only during periods of relatively
high traffic volume. The base running time can be estimated from a plan
of the amusement park with an additional knowledge of its traffic control
procedures and probable driving patterns.
Due to the relatively low traffic volumes normally associated with employee
travel and the separate employee parking facilities, it has been assumed
for this analysis that employee traffic always moves with the same average,
or base, running time. This assumption appears reasonable because:
(1) employee peak travel times do not coincide with guest peak travel times;
(2) there are no ticket gates or other constraints to employee parking
lot ingress; and (3) the sizes of employee parking lots are small enough
that driving times within the lot would not increase significantly with
traffic volume.
Relationship Between Running Time and Traffic Volume
As traffic volume increases, running times become longer due to congestion.
Some of the constraints to movement that contribute to the longer running
times are:
e Queues at parking ticket booths, in the active parking
area as cars are directed into their assigned parking
spaces, and at other temporary or permanent traffic
control points.
e Queues created as vehicles attempt to exit onto uncontrolled
access roads.
• Traffic intersections and merging traffic lanes within the
parking area.
• Traffic aisles blocked by vehicles making dropoffs or pickups,
• Increased number of pedestrians in parking area.
-22-
-------
Generally, running time is related to traffic volume as shown in Figure 2.
The base running time (BRT) can be determined for a specific amusement
park as described above. The magnitude of increase above the BRT with in-
creased traffic can also be estimated from available traffic parameters,
by the procedures developed in Section VII.
Identification of Critical Modes at Amusement Parks
Examination of the eight operational modes that were identified indicates
that running times in some modes are relatively constant, but that times
in others may increase sharply under peak attendance/traffic conditions.
For amusement parks, the three modes whose times are greatly affected by
traffic congestion, in order of decreasing impact, are:
1. Entrance
2. Movement in
3. Exit
Time in the entrance mode is affected by the collection of parking fees
as the vehicles enter parking lots at most amusement parks.
Movement time into a parking space is a function of the maximum parking
rate that can be accomplished by park employees as they direct traffic
within the lot. If traffic flow into the lot is controlled by a ticket
gate, running times in the parking lot should not increase much with
increased traffic. However, sizeable queues form during these periods
in free parking lots. Time in the "movement in" mode expands incrementally
when the main parking lot is filled and incoming traffic must all drive
an additional distance to an overflow lot.
Exit time for a vehicle in a parking lot is a function of the egress
capacity of the lot. As this is approached or exceeded, running time
increases. Waiting times in the resulting queues contribute significantly
to total running times. Exit queue lengths are moderate compared to those
for the entrance mode by the departure of vehicles over a longer period of
time.
-23-
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I
ro
c
c
o;
BRT
Gate or
Parking Capacity
Traffic Volume
Figure 2, General Relationship Between Traffic Volume and Total Running Time
-------
SECTION VII
ANALYSIS
In this section, three analyses are developed for converting available
data into vehicle running times and numbers of vehicles running. The
final step of combining all these intermediate results into a quantitative
description of the amusement park traffic problem is then treated in
Section VIII, Results.
ENTRANCE OR PARKING TIME
Time spent entering a parking lot or waiting to be directed to a parking
space is a function of the rate at which vehicles are attempting to enter
the lot, the number of entrance lines, and the average time required to
collect the parking fee (service time). Running time can be quantified
with data on these three parameters by use of a methodology employing
queueing theory. The hourly inflow rate is obtained from the projected
traffic distribution pattern for the park. Average service time per
vehicle ranges from about 0.10 minute, where parking is free or the fee
is collected after the vehicle has parked, to 0.25 minutes in cases where
there are inadequate attendants or a poor entrance configuration. This
value is difficult to predict from design data, since it is much more
closely related to operational features of the parking facility. •
Estimates of running times for the entrance mode cannot be precise,
especially considering the available input data. The equations employed
here for waiting time in queue result from assumptions that vehicles are
reaching the gate randomly over the time increment of concern, and are
passing through the gate randomly; hence, their distribution conforms to
the negative exponential law, with the queue discipline the first-come-
first-served rule (classic basic queueing theory). Errors in the estimates
by use of these equations are thought to be relatively low.
-25-
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For periods when traffic flow is less than gate capacity, the average
running time (in minutes) in a queue is given by the equation:
RT = b y§— , where
a = utilization factor
_ (vehicle Inflow rate, veh/min) (b)
(no. of entrance lines)
b. = average service time, min.
For these periods when traffic flow exceeds gate capacity (a>1.0), the
queue continues to build during each time increment by the amount that
traffic volume exceeds capacity. Average running time for this situation
can best be estimated by the tabular calculation procedure exemplified
in Table 6. The procedure is illustrated with data for a two-hour peak
traffic period (3:00p.m. - 5:00p.m.) with vehicles existing as shown in
column 2, four entrance lanes, and an average service time of 0.1 minute.
EXIT TIME
Since guests leave the park over a period of several hours, as indicated
by the data in Tables 3 and 4, it is unusual for congestion and excessive
queueing to occur at the parking lot exits or on the access roads. However,
if inadequate exit capacity for peak crowds is suspected, the queueing
theory equation or tabular method presented above may also be used to
estimate running times in the exit mode.
Generally, it is more direct to describe the exit constraint in terms of
gate capacity rather than average service time. The "b" factor in the
equation can still be easily quantified, since it is the average outflow
time per vehicle or the number of exit gates divided by the total gate
capacity in vehicles per minute.
-26-
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Table 6. EXAMPLE QUEUE CALCULATION WHEN GATE CAPACITY IS EXCEEDED
1
Time Period
Starting Ending
2:30 3:00
3:00 3:30
3:30 4:00
4:00 4:30
4:30 5:00
5:00 5:30
5:30 6:00
6:00 6:30
2
Entering
Traffic
Volume
900
1220
1400
1600
1400
1100
980
750
3
Vehicles
Serviced
1200
1200
1200
1200
1200
1200
1200
1200
4
AN
col. 3-
col. 2
-
+ 20
+ 200
+ 400
+ 200
- 100
- 220
- 440
5
N at End
of Period
col. 4+
col. 5'
(line above)
-
20
220
620
820
720
500
60
6
NAV,
col. 5+col . 5'
2
-
10
120
420
720
770
610
280
7
RT, Win.
(b) (col. 6)
Divided by
No. of gates
(use equation)
.25
3.0
10.5
18.0
19.25
15.25
7.0
ro
N = queue length, in cars
RT = average running time, in minutes
= (av. inflow time per vehicle, min.) (av. queue length)
-------
MOVEMENT IN TIME
Running time spent in reaching a parking space increases as a function of
the number of vehicles already in the parking area, since the late arrivals
are directed to the more remote sections of the lot. The average running
time in this mode for a day, then, should be proportional to the daily
attendance. Actual values for a particular park are estimated from driving
distances as determined from a plan of the parking area.
For parking lots with no ticket booth, a queue may form at the point of
active parking during periods of high inflow rather than at the entranceway.
However, the same queueing theory equation is still applicable.
The largest increase in running time for the "movement in" mode occurs when
the capacity of the main parking lot is exceeded and incoming cars must
be diverted to an auxiliary or overflow area. Therefore, some quantitative
analysis of number of parked vehicles at any time of the day is desirable.
Vehicle accumulation can be derived simply from the hourly data on arrival
and departure of guests. After these data have been converted to equivalent
inflow/outflow of traffic, the number of vehicles in parking at any time is
the cumulative difference between these two hourly values. This is shown
graphically in Figure 3 on a percentage basis for the attendance data in
Table 4. At the time of day on a peak attendance day when the estimated
number of vehicles in parking exceeds the primary parking capacity, running
time is incrementally increased by an amount that accounts for driving
time to the overflow lot, plus any additional days associated with this
movement.
-28-
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100
100
UJ
eg
UJ
o.
o
UJ
o.
ID
O
(J3
a:
UJ
.^ACCUMULAT ION
10 11 Noon 1
UJ
OL
UJ
Q.
ft
UJ
_J
t—t
:n
UJ
I
o
o
1—t
§
•=>
ra
o
o
ca
i
23456789
HOUR OF DAY
10 11 12
Figure ^. VEHICLE ACCUMULATION BY HOUR FOR PEAK ATTENDANCE DAYS AT MAJOR THEME PARKS
-------
SECTION VIII
RESULTS
METHODOLOGY
In general terms, the methodology' proceeds as described in the next two
paragraphs which follow. It should be emphasized that this description
is of the technique, shown schematically in Figure 4, in its most general
form, which provides the starting for each of the seven types of complexes
investigated. Significant differences in implementation from this general
approach arose for each of the first three complexes, but the methodology
for. amusement parks follows the general approach closely with no peculiarities
or exceptions.
Starting from the physical, geographic, and demographic characteristics
of the complex, relationships are established for estimating typical and
peak traffic volumes. The concept of operational traffic modes is used
to generate best estimates of average running times for cars. The typical
traffic volumes and base running times provide the description of typical
conditions.
The parameters of the complex which significantly and adversely impact
traffic behavior are also defined. Quantitative relationships are proposed
or estimated for the controlling parameters of the complex with respect to
excess running times in critical traffic operating modes. These, in turn,
are superimposed on the base running times to generate peak running times.
The peak running times are then associated with peak traffic volumes to
create the required information on peak traffic conditions.
-30-
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In the case of amusement parks, as shown in Figure 5, the methodology proceeds
from basic information about a given park (see Section V), via traffic
behavior data and traffic volume projections (see Section VI), to generate
estimates of peak and typical numbers of vehicles and associated running
times by hour of the day. Typical and peak one-hour and eight-hour periods,
required end products, can then be extracted from this information.
The specifics of the procedure are presented below. First, the attendance
patterns associated with typical and peak days at the park are delineated.
These are converted into number of vehicles entering and leaving the park
per hour by dividing numbers of patrons and employees by their respective
average vehicle occupancies. Running times in the eight operating modes
are then determined. A schematic diagram similar to Figure 1 may be helpful
in analyzing the operating modes at the park under different traffic volume
situations. If the schematic is approximately to scale for the parking area
and access roads, it enables estimates of the base running times in each mode
to be made.
The access roads to most large amusement parks are private roads on park
property, so running times in the approach and departure modes are influenced
only by traffic to and from the park and by the configuration of the access
road. Running times in the stop and the start modes are probably always very
low--the value of 0.1 minute used in the first task report is still appropriate
here. Running times in the entrance and exit modes are estimated by the
procedures presented in Section VII, as functions of the traffic volume and
entrance and exit gate capacities. Because parking lots at amusement parks
generally have supervised parking, movement into a parking space is primarily
related to the size of the facility until the lot becomes filled.- Therefore,
the traffic volume estimates must be used in conjunction with parking lot
capacity to determine whether capacity is exceeded during peak periods, and
the number of vehicles that will have an additional running time to an
overflow parking area. Time for movement out appears to be just a function
of parking lot size, and relatively constant for all attendance rates.
-31-
-------
/Characteristic \.
-I Parameters 1-
V of Complex J
Peak
Trip
.Generation
Values
[ Exceedancej
V Values )
^
Exceedance
Depen-
dencies
k J
J '
/^TypicalX
( TriP )
veneration /
\JLalues ^/
Peak
Running
Times
Peak Values
of Number of
-**(Cars Running, ani
Base Running
Time
IBase
Running
Time
/Teak Values
/of Numbers of
ICars Running, and
V Peak Running
X^ Times
Typical Value:
of Numbers of
\Cars Running, -and
Base Running
Times
Figure 4. GENERALIZED METHODOLOGY
-32-
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Characteristic*1
of Amusement
Parks
Traffic I
Operational
Mode
Analysis
Peak Values of
dumber of Cars
Running and
Running Times
Typical Values
of Number of
Cars Running and
Running Times
Figure 5. GENERALIZED METHODOLOGY APPLIED TO AMUSEMENT PARKS
-33-
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The identity of each of the two traffic types (guest and employee) is
preserved through the calculation procedure because of differences in
the base running times and because of the differential impact of exceedances
on their running times. The base running times for each traffic type are
combined with typical traffic volumes for the same type to provide the
required values of total vehicles running and base running times. For
the peak case, diurnal variations of guest and employee traffic must be
examined to select the composite peak hour and eight hours. Typically,
the patrons' traffic, will overshadow employee travel, and their trips will
determine the peaking times.
In summary, the two main concerns for an amusement park are for adequate
parking lot entrance capacity and adequate parking spaces, or an efficient
means of directing and moving incoming traffic to an overflow parking area.
GEOGRAPHIC DISTRIBUTION
Running times, and hence emissions, from an amusement park complex can
usually be considered as being distributed fairly uniformly over the parking
areas during typical operating periods (base running times). Some con-
centration of vehicles may occur in the vicinity of the parking lot
entrance line. The added emissions attributed to this particular line
may be determined from the breakdown of running times by mode for a typical
period. It may also be desirable to simulate access road traffic as a
separate line source, depending on the orientation of the road (especially
if straight away from the park) and the distance of expected effect.
Under peak traffic conditions, the running time in the entrance mode is
greatly increased and the need to consider the entrance line as a special
source is accentuated. The area over which the other running times are
distributed may also increase, due to the utilization of secondary parking
areas.
-34-
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METEOROLOGICAL ASPECTS
The meteorological characteristics which most importantly affect atmospheric
dilutive capacity are mixing height, wind speed and atmospheric stability.
A convenient summary of mixing height and wind speed characteristics which
affect air pollution potential is given in the Office of Air Programs
Publication No. AP-101 (Holzworth 1972). Atmospheric stability may be
determined in terms of cloud cover, solar radiation and wind speed by a
method proposed by Pasquill and shown in Table 7. For ground level
sources, such as automobiles at amusement parks, the ground level concentrations
both in the vicinity and downwind of the sources will be inversely proportional
to wind speed and mixing height and directly proportional to atmospheric
stability (i.e., the more stable the atmosphere, the higher the concentration).
Peak use of amusement parks occurs during'summer, with the highest days of
the week usually being on the weekend. The peak hour use generally occurs
during the mid-day (somewhere from lla.m. to 1p.m.). The peak eight-hour
period is generally lla.m. to 7p.m. Holzworth (1972) has mixing height and
wind speed figures which are directly applicable to summer afternoon conditions
for locations in the contiguous United States, and these may be used directly
(Figures 6 and 7). For the weekend mid-day peak, atmospheric stability
classes B, C, and D may occur with classes C and D being the most prevalent.
The period when meteorological conditions are least favorable for diluting
pollutants is the period when amusement parks are essentially not in use.
This would be from very late in the evening until a few hours after sunrise.
It is most often during this period that mixing heights are lowest, wind
speeds are lowest, and atmospheric stability is greatest.
QUALITATIVE GUIDELINES
In addition to the quantitative guidelines developed above, the review
of amusement parks as complex emission sources should also include the
following considerations which are not presently reducible to quantitative
terms:
-35-
-------
Table 7. KEY TO STABILITY CATEGORIES (after Turner 1970)
Surface Wind
Speed (at 10 m) ,
m sec"1
<2
2-3
3-5
5-6
>6
Day
Incoming Solar Radiation
Strong
A
A-B
B
C
C
Moderate
A-B
B
B-C
C-D
C
Slight
B
C
C
D
D
Night
Thinly Overcast
or
>_ 4/8 Low Cloud
E ::.' , .. .
." ' \D-C:ff^.\''
-. D; ••-
. D
< 3/8
Cloud
F
E
D
D
The neutral class, Ds should be assumed for overcast conditions during
day or night.
NOTE: Class A is the most unstable, class F the most stable class. Night
refers to the period from 1-hour befor . sunset to 1-hour after sunrise.
Note that the neutral class, D, can be assumed for overcast conditions
during day or night, regardless of wind speed.
"Strong" incoming solar radiation corresponds to a solar altitude greater
than 60° with clear skies; "slight" insolation corresponds to a solar
altitude from 15° to 35° with clear skies. Table 170, Solar Altitude
and Azimuth, in the Smithsonian Meteorological Tables (List 1951) can be
used in determining the solar altitude. Cloudiness will decrease incoming
solar radiation and should be considered along with solar altitude in
determining solar radiation. Incoming radiation that would be strong with
clear skies can be expected to be reduced to moderate with broken (5/8 to
7/8 cloud cover) middle clouds and to slight with broken low clouds.
-36-
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Figure 6. ISOPLETHS (mxlO2) OF MEAN SUMMER AFTERNOON MIXING HEIGHTS
-------
Co
00
Figure 7. ISOPLETHS (m sec"1) OF MEAN SUMMER WIND SPEED AVERAGED THROUGH AFTERNOON MIXING LAYER (Figure 5;
-------
1. Since the layouts of amusement parks can usually be modified comparatively
easily to accommodate larger crowds or to alleviate traffic problems, the
amount of space available for expansion or modifications should be checked.
Specifically, the ease with which parking capacity and access roads could
be expanded should be reviewed.
2. The appropriate and adequate use of signs and markers to direct
motorists throughout the vehicular areas of the park is important, since
many of the guests are tourists visiting the facility for the first time.
3. The developer should demonstrate an effort to optimize traffic cir-
culation patterns in the park by such methods as:
• No left turn movements across the main access roads
• Maximum use of one-way and divided streets
e Markings that separate parking lot entrance lanes from
through traffic lanes, where appropriate
• Prohibition of on-street parking within the park.
4. In addition to the employees normally assigned to parking and traffic
control, the park's security personnel should be available to assist in
these areas during peak periods.
THE NINE QUESTIONS
While the specific information called for by the task work statement has
been provided in Sections V through VIII, the nine questions spelled out
as part of the work statement warrant specific response. This is given here,
with the questions abbreviated.
1. Area alloted to or occupied by a single vehicle? From 190 to 210 feet.
2. Percentage of land and parking spaces potentially occupied by vehicles?
The usual percentage? For the few parks for which data could be .obtained,
the acreage for parking varied from about half up to almost;the same amount
of land that was used for the amusement area proper. However, acreage
dedicated to such purposes as buffer areas, camping, gardens, lakes,
and expansion exceeded that for either the amusement or parking areas at
many of the parks.
-39-
-------
3. Typical and peak values (absolute or fractional) of vehicles running
for one- and eight-hour periods? The fractional values can be closely
approximated by the tabular summaries of number of guests arriving and
departing by hour, as shown in Tables 3 and 4.
4. Typical and worst case (slowest) vehicle speeds? In the context of
our approach, this question is only relevant to analysis of the "Major
Highway" complex source task. It will be dealt with in that task report.
5. Vehicle distribution within the complex? See subheading entitled
Geographic Distribution in Section VIII.
6. Design parameters of the complex likely to be known beforehand?
See Section V, Parameters for Amusement Parks.
7. Design parameters in question (6) which can be most successfully
related to traffic, and hence emissions? See Sections V through VII.
8. Relationships of parking lot design to parking densities and vehicle
circulation? What is typical design? Design with highest parking densities,
lowest vehicle speeds, longest vehicle operating times? To the extent
to which these questions are relevant to our methodology, they are answered
in Section V.
9. Meteorological conditions likely to occur during peak use? Use level
during periods of worst meteorology? See the subheading entitled Meteorological
Aspects in Section VIII.
-40-
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SECTION IX
REFERENCES
1. Amusement Parks Ride to Boom or Bust. Business Week. April 9, 1966.
pp. 32-33.
2. Sons of Disneyland. Newsweek. May 21, 1973. pp. 90-91
3. Enterprise: The Fun Formula. Newsweek. July 23, 1973. pp. 63-65.
4. Personal communication with Mr. William Lowe, Marriott Corporation.
October 9, 1973.
5. Information Extracted from several news articles in Amusement Business.
Cincinnati, Ohio. 1971-1973.
6. Data prepared by Economics Research Associates. McLean, Virginia.
October, 1973. .
7. Compilation of Air Pollutant Emission Factors. Environmental Protection
Agency Publication No. AP-42, Second Edition. April, 1973.
-41-
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-450/3-74-003-e
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
Vehicle Behavior In and Around Complex Sources and
Related Complex Source Characteristics
Volume V - Amusement Parks
5. REPORT DATE
November 1973 (Date of issue)
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Kenneth Axetell, Jr.
Scott D. Thayer
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORG 'XNIZATION NAME AND ADDRESS
Geomet, Inc.
50 Monroe Street
Rockville, MD 20850
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-02-1094
12. SPONSORING AGENCY NAME AND ADDRESS
13. TYPE OF REPORT AND PERIOD COVERED
Office of Air Quality Planning & Standards
Environmental Protection Agency
Research Triangle Park, North Carolina 27711
14. SPO
G AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
A general methodology is presented for relating parameters of traffic behavior
at amusement parks, including vehicle running time and traffic volume, to more
readily available characteristics of the parks, including attendance rates, temporal
variations in attendance, patrons' average length of stay and parking capacity.
Such relationships are to be used to relate amusement park characteristics to air
quality.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Air pollution, recreational facilities,
urban planning, urban development, urban
transportation, transportation management,
transportation models, land use, regional
planning, vehicular traffic, traffic
engineering, highway planning
Indirect sources
Indirect source review
13B
18. DISTRIBUTION STATEMENT
Release unlimited
19. SECURITY CLASS (ThisReport)
Unclassified
21. NO. OF PAGES
46
20. SECURITY CLASS (Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
-42-
-------
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15. SUPPLEMENTARY NOTES
Enter information not included elsewhere but useful, such as: Prepared in cooperation with, Translation of, Presented at conference of,
To be published in, Supersedes, Supplements, etc.
16. ABSTRACT
Include a brief (700 words or less) factual summary of the most significant information contained in the report. If the report contains a
significant bibliography or literature survey, mention it here.
17. KEY WORDS AND DOCUMENT ANALYSIS
(a) DESCRIPTORS • Select from the Thesaurus of Engineering and Scientific Terms the proper authorized terms that identify the major
concept of the research and are sufficiently specific and precise to be used as index entries for cataloging.
(b) IDENTIFIERS AND OPEN-ENDED TERMS - Use identifiers for project names, code names, equipment designators, etc. Use open-
ended terms written in descriptor form for those subjects for which no descriptor exists.
(c) COSATI FIELD GROUP - Field and group assignments are to be taken from the 1965 COSATI Subject Category List. Since the ma-
jority of documents are multidisciplinary in nature, the Primary Field/Group assignment(s) will be specific discipline, area of human
endeavor, or type of physical object. The application(s) will be cross-referenced with secondary Field/Group assignments that will follow
the primary posting(s).
18. DISTRIBUTION STATEMENT
Denote releasability to the public or limitation for reasons other than security for example "Release Unlimited." Cite any availability to
the public, with address and price. .'
19. &20. SECURITY CLASSIFICATION
DO NOT submit classified reports to the National Technical Information service.
21. NUMBER OF PAGES
Insert the total number of pages, including this one and unnumbered pages, but exclude distribution list, if any.
22. PRICE
Insert the price set by the National Technical Information Service or the Government Printing Office, if known.
EPA Form 2220-1 (9-73) (Reverse)
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