EPA-450/3-74-058
NOVEMBER 1974
MONITORING AND ANALYSIS
OF CARBON MONOXIDE
AND TRAFFIC CHARACTERISTICS
AT OAKBROOK
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Wa^te Management
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
-------
ACKNOWLEDGMENTS
We wish to thank Dr. Edwin L. Meyer, Jr. for his close x^orking relation-
ship as Project Officer during this study.
We also wish to acknowledge the able assistance of Barton-Aschtnan
Associates, who performed the traffic monitoring and analysis phase of
this study, and Environmental Technology Assessment, Inc., who supplied
the carbon monoxide and meteorological data.
XI
-------
EPA-450/3-74-058
MONITORING AND ANALYSIS
OF CARBON MONOXIDE
AND TRAFFIC CHARACTERISTICS
AT OAKBROOK
by
R. M. Patterson and F. A. Record
GCA Corporation
GCA/Technology Division
Bedford, Massachusetts 01730
Contract No. 68-02-1376
Task Order 7
EPA Project Officer: Edwin L. Meyer, Jr.
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, N. C. 27711
November 1974
-------
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, for a fee, from the
National Technical Information Service, 5285 Port Royal Road, Springfield,
Virginia 22161.
This report was furnished to the Environmental Protection Agency by
the GCA Corporation, in fulfillment of Contract No. 68-02-1376. The contents
of this report are reproduced herein as received from the GCA Corporation.
The opinions, findings, and conclusions 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-450/3-74-058
11
-------
CONTENTS
List of
List of
Section
I
II
III
IV
V
Figures
Tables
Title
INTRODUCTION AND SUMMARY
SITE DESCRIPTION
CARBON MONOXIDE MONITORING PROGRAM
DATA COLLECTION
DATA ANALYSIS AND RESULTS
METEOROLOGICAL DATA
TRAFFIC MONITORING PROGRAM
MONITORING NETWORK
EVALUATION OF TRAFFIC OBSERVATIONS
MODEL DEVELOPMENT AND EVALUATION
V
viii
1
3
9
9
18
30
37
37
42
87
IV
ESTIMATION OF MISSION PROFILES FROM
QUEUING VEHICLES
COMPARISON OF OBSERVED AND CALCULATED
CONCENTRATIONS
EVALUATION OF AREA SOURCE MODEL
OUTLINE OF A "QUICK ESTIMATION" TECHNIQUE
REFERENCES
87
102
106
109
121
Appendix
A
B
CARBON MONOXIDE DATA
METEROLOGICAL STABILITY DATA
A-l
B-l
ill
-------
CONTENTS (Continued)
Appendix Title
C SHOPPING CENTER TRAFFIC AS PERCENT OF TOTAL TRAFFIC C-l
D COMPARISON TRIP GENERATION STUDY OF REGIONAL
CENTERS IN CHICAGO AREA D-l
E HOURLY AND DAILY TRIP GENERATION RATES--OAKBROOK
SHOPPING CENTER E-l
F TRIP DISTRIBUTION ANALYSES AND PROCEDURES F-l
DISTRIBUTION OF SHOPPING CENTER TRAFFIC F-l
G LEVEL OF SERVICE ANALYSES AND PROCEDURES G-l
LEVEL OF SERVICE G-l
H INTERSECTION LEVEL OF SERVICE BY HOUR OF DAY H-l
iv
-------
LIST OF FIGURES
No. Title
1 Proximity of Oakbrook to Chicago and Major
Expressways 4
2 Oakbrook Shopping Center Area Development 5
3 Oakbrook Shopping Center Building and Parking Lot
Locations 7
4 Location of Monitoring Sites in Relation to the
Shopping Center 10
5 Continuous Monitoring Sites at Route 83 and
22nd Street 13
6 Monitoring Station Schematic 14
7 Location of Bag Sample Sites 16
8 Bag Sample Apparatus 17
9 Diurnal Pattern - All Stations - Weekdays 23
10 Diurnal Pattern - All Stations - Saturday 24
11 Diurnal Pattern - All Stations - Sunday 26
12 Diurnal Pattern - Weekdays 27
13 Diurnal Pattern - Saturdays . 28
14 Diurnal Pattern - Sundays 29
15 Cumulative Frequency Distribution 31
16 Cumulative Frequency Distribution 32
17 Wind Speed Frequency Distribution 35
18 Route 83 - 22nd St. Intersection Configuration and
Existing Signal Phasing 38
19 Entrances 8 and 10 - Geometric Configurations and
Existing Signal Phasing 39
-------
LIST"OF FIGURES (Continued)
No. Title Page
20 Location of Intersection Counters 40
21 ' Location of Counters Within Shopping Center 41
22 Directional Distribution of Traffic on a Typical
Saturday 45
23 Directional Distribution of Traffic on a Typical
Weekday 46
24 Diurnal Pattern of Weekday Intersection Traffic 59
25 Diurnal Pattern of Weekday Intersection Traffic 60
26 Average Approach and Departure Speeds Versus Volume 71
27 Average Approach and Departure Speeds Versus Volume 72
28 Calculated Versus Observed Queue Length Using
Tollbooth Formula 73
29 Calculated Versus Observed Queue Length Using Red
Time Formula 81
30 Emission Profile for One Vehicle Decelerating From
35 mph at -2.75 mph/sec and Accelerating Back to
35 mph at 2.50 mph/sec With No Idle Emissions 89
31 Profile and Step Function Approximation of Excess
Emissions for a Queue of 10 Vehicles 90
32 Emission Profile and Step Function Approximation for
Excess and Cruise Emissions for a Queue of 10
Vehicles 96
33 Calculated Versus Observed Concentrations of Carbon
Monoxide 105
34 Locations of Receptors and Area Sources 108
35 Diagram of 20" Distances for Line Source Calculation 111
D-l Observed Hourly Generation Rates, Oakbrook, Illinois D-3
vi
-------
LIST OF FIGURES (Continued)
No. Title Pa%e
D-2 Observed Hourly Generation Rates, Oakbrook, Illinois D-4
D-3 Observed Hourly Generation Rates, Oakbrook, Illinois D-5
vii
-------
LIST OF TABLES
No.
1
2
3
4
5
6
7
8
Characteristics of the Three Highest "Episodes"
Frequency Distribution of Observed CO Concentrat iotas
Wind Speed Frequency Data
Distribution of Traffic Volumes by Entrance (Percent
of Total Volume) Oakbrook Shopping Center (1,250,000
Square Feet GLA) - Sears, Marshall Fields, Lord and
Taylor
Shopping Center Volumes as Percent of Total Traffic
Volumes
Directional Traffic Volumes - North Leg of Route 83
and 22nd Street Intersection
Directional Traffic Volumes - East Leg of Route 83
and 22nd Street Intersection
Daily Trip Generation Rates (One-Way Trips/1.000
Page
21
30
34
43
47
49
50
Square Feet GLA) Oakbrook Shopping Center 54
9 Maximum Eight-Hour Trip Generation Rates (One-Way
Trips/1,000 Square Feet GLA) Oakbrook Shopping
Center 55
10 Maximum One-Hour Trip Generation Rates (One-Way
Trips/1,000 Square Feel: GLA) Oakbrook Shopping
Center 56
11 Peak Twenty-Four Hour Two-Way Volumes 62
12 Peak Eight-Hour Two-Way Volumes ' 63
13 Peak One-Hour Two-Way Volumes 64
14 Observed Approach and Departure Speeds 70
15 Observed Acceleration and Deceleration Rates 75
\
16 Average Observed Vehicles Queued Per Signal Cycle 77
17 Vehicle Waiting Times and Estimated Red Time 80
viii
-------
LIST OF TABLES (Continued)
No. Title Page
18 Observed Cycle Length - Route 83 and 22nd Street
Intersection 86
19 Reference Data for Describing Emission Profile
Calculation 92
20 Emission Values for Use in Approximating Emission
Profiles 94
21 Observed and Calculated Carbon Monoxide Concentrations
Using the Composite Model 104
22 Cycle Lengths at the Intersection of Route 83 and
22nd Street 106
23 Area Source Upwind - Downwind CO Concentration
Differences ' 109
24 Roadway Locations and Distances Included in
± 2
-------
LIST OF TABLES (Continued)
No. Title
G-l Illinois Route 83-22nd Street Intersection Level of
Service - Existing Conditions, 9:00 a.m.,
March 13, 1974 G-7
G-2 Illinois Route 83-22nd Street Intersection Level of
Service - Proposed Conditions, 9:00 a.m.,
March 13, 1974 G-8
-------
SECTION I
INTRODUCTION AND SUMMARY
This document reports the results of a carbon monoxide and traffic mon-
itoring and analysis program conducted at Oakbrook Shopping Center in
the Village of Oak Brook, a Chicago suburb.
Following a description of the study site, this report falls into three
sections. The first section describes the details of the carbon monoxide
and meteorology monitoring techniques, and it gives a summary of the re-
sults. The full data listings are presented in Appendices A and B. The
next section presents a discussion of traffic monitoring locations, and
it evaluates the results in terms of the impact of the shopping center
on traffic loads at a nearby intersection, trip generation rates, and
vehicular operating modes at intersections.
The final section integrates the findings described in the other sec-
tions by developing a method for approximating emission profiles for
queuing vehicles, and testing the composite model formed by the ap-
proximated profiles and the HIWAY line source model against carbon mon-
oxide concentrations measured at the study site. Twenty-two of
twenty-seven calculated concentrations are within a factor of too of
those observed. Six comparisons agree exactly. The mean calculated
value is 3.5 ppm versus a mean 3.8 ppm observed value. The correla-
tion coefficient is 0.34, significant at better than the 10 percent
level. Less favorable agreement was found when concentrations were
calculated by (1) using a larger initial vertical diffusion parameter
and (2) assuming stability conditions one class less stable than those
-------
computed by the standard objective method. A suggested technique for
estimating carbon monoxide concentrations near intersections is also
presented. This technique involves examining the properties inherent
to the Gaussian diffusion equation compared v/ith receptor locations and
emission characteristics at intersections.
-------
SECTION II
SITE DESCRIPTION
Oakbrook Shopping Center is located in the Village of Oak Brook,
Illinois, a suburb located 12 miles west of the Chicago Loop. The
shopping center lies in an area of high accessibility being served
by the Tri-State Tollway, located two miles east of the center, and
the Eisenhower (East-West Tollway) Expressway, located 1/4
mile south of the center. The Oak Brook area is also served by three
major regional arterial roads: Roosevelt Road (Illinois Route 38),
Butterfield Road (Illinois Route 56), and Kingery Highway (Illinois
Route 83). Figure 1 illustrates the relationship of the center to
Chicago and the regional arterial roadway system.
There are substantial quantities of office space in the vicinity of
the shopping center (mostly to the east). The Oakbrook Association
of Commerce and Industry estimates that there are 2.5 million square
feet of office space in the Village of Oak Brook. In addition, there
are two theaters and several hotels and motels within 1/4 mile
of the site. Figure 2 illustrates the location of Oakbrook Shopping
Center with respect to adjacent developments and the roadway network.
Another major regional shopping center, Yorktown (approximately 1.5
million square feet of gross leasible area, or GLA) is located 2-1/2
miles west of Oak Brook in Lombard, Illinois.
Regional access to the center is provided by two major arterials,
Illinois Route 83 and 22nd Street. Interchanges with the East-West
Tollway are located on both these streets south of the center. Local
-------
Figure 1. Proximity of Oakbrook to Chicago and major expressways
-------
BUTLER
INTERNATIONAL
SPORTS
CORE
MAJOR OFFICE/EMPLOYMENT BUILDINGS
NORTH
Figure 2. Oakbrook Shopping Center area development
-------
access to the center is also provided by Spring Road (eastern site
boundary) and 16th Street (northern site boundary). The center has
six major access drives; tx^o each on 22nd Street and Illinois Route 83,
and one each on 16th Street and Spring Road. The entrances on
Illinois Route 83 and 22nd Street are controlled by actuated traffic
signals while the remaining two entrances are controlled by stop signs.
The shopping center has a parking lot capacity of approximately 7,200
spaces.
Oakbrook Shopping Center, completed in 1962, has a total GLA of
approximately 1,250,000 square feet. The prime tenants of the shop-
ping center are Marshall Field & Company (Building A), Sears, Roebuck
and Co. (Building B), and Lord & Taylor (Building C). The center con-
tains .60 smaller shops. Figure 3 illustrates the layout of the build-
ings, the parking lots, and the entrances. The prime trade area of
the center includes an area of over 180 square miles having a generally
more affluent population than other regional shopping centers in the
Chicago area.
-------
] PARKING LOTI
Figure 3. Oakbrook Shopping Center building and parking lot locations
-------
SECTION III
CARBON MONOXIDE MONITORING PROGRAM
DATA COLLECTION
Introduction
The study of air quality in the vicinity of the Oakbrook Shopping
Center was conducted using both bag sampling and continuous monitoring
techniques to measure carbon monoxide concentrations in the ambient
air. The study commenced Friday, March 22, and continued through
Saturday, April 13, 1974.
The locations of the monitoring sites relative to the shopping center
are shown in Figure 4. Sites 11 through 15 and 161 through 163 were
continuous monitors, and sites 181 through 184 were bag sampling
locations. Six of the eight continuous CO analyzers were located
near the intersection of Route 83 and 22nd Street. Meteorological
data were also collected near this intersection.
Instrumentation
Two types of CO analyzers were used during this study. One was the
"Ecolyzer", manufactured by Energetics Science, Inc. The analysis
performed by this instrument is based upon electrochemical oxidation
of the carbon monoxide. The instrument is portable and has a dual 0-100,
0-50 ppm range meter. Each analyzer was connected to a continuously re-
cording strip chart recorder throughout the study.
-------
Route 83
Figure 4. Location of monitoring sites in relation to the shopping center
10
-------
The second type of CO analyzer was the instrument used in the EPA stan-
dard reference method for the continuous measurement of carbon monoxide
in the atmosphere (Federal Register, April 30, 1971). This instrument, a
non-dispersive infrared (NDIR) unit, was manufactured by the Mine Safety
and Appliance Company. These units were also equipped with continuously
recording strip chart recorders. The measurement of CO by this instrument
is based upon the absorption of infrared radiation by carbon monoxide.
The range of the unit is 0 to 50 ppm.
Calibration
All of the CO analyzers were calibrated at least once daily throughout
the study. The "Ecolyzer" units were normally calibrated using a built-
in instrument zero setting and a span gas (48 ppm) which was almost full
scale on the 0 to 50 ppm range which was used. The instrument zero
settings were also verified at various times throughout the study with a
zero gas. These two zero techniques showed close agreement. In addition
to these end point calibrations, random low range checks were made on the
"Ecolyzers" using a certified 11.5 ppm CO gas.
Zero and span gas checks were also performed on the NDIR units on a daily
basis. The zero and span gases (0 and 37.8 ppm) were traceable standards,
as they had been calibrated against zero and span gases certified by the
National Bureau of Standards.
A multi-point calibration to check the instrument linearity was conducted
every week. This consisted of checking the instrument readings at five
different carbon monoxide concentrations across the 0 to 50 ppm scale.
These concentrations were made by combining the zero and span gas traceable
standards in various known proportions. The calibration procedures on the
NDIR instruments were performed by employees of the Quality Assurance and
Environmental Laboratory of the EPA.
11
-------
Similar linearity checks were also performed on the two "Ecolyzers" used
at Site 162. The reasons for changing units at this site are described
later.
All strip chart recorders were also checked daily to ensure that rea-
sonable data were being obtained and that the recorders were keeping
accurate time.
Continuous Monitoring Sites
As mentioned above, six of the eight continuous CO analyzers were located
in the immediate vicinity of the intersection of Route 33 and 22nd Street.
Figure 5 shows the exact location of these six monitors.
Sites 13, 14 and 15, located on the northeast corner of the intersection,
had "Ecolyzer" CO monitors. Each set of instruments was housed in a
fully enclosed utility trailer measuring approximately 6 feet long, 4
feet high and 4 feet wide. Each trailer was heated with a thermostatically
controlled electric heater, and the temperature within the trailer was
maintained at approximately 70°F. A 3/8 inch Teflon sampling line was
housed in a metal conduit which passed through the floor of the trailer,
attached to the side of the trailer, and extended above grade about 8 feet
with a U-shaped bend at the top. A one-gallon glass container was in-
serted into the sample gas line ahead of tha carbon monoxide analyzer to
act as an integrator to reduce the excessive scatter which normally occurs
on the strip chart without such a "surge tank." Figure 6 is a schematic
diagram of the sampling arrangement.
Three analyzers were located in a temperature controlled van at 75 ± 2 F,
situated on the southwest corner of the intersection. Analyzers 161 and
163 were NDIR units, and analyzer 162 was an "Ecolyzer." All three of
these analyzers were connected to the same sampling air manifold , and
hence the three received essentially identical samples. It was thus
12
-------
Rt. 83
~20 rat
. #13'
-40ir
#14
40m
20m
I
27m
22nd Street
KEY -
a
Van
Trailer
Wind Instrument
Figure 5. Continuous monitoring sites at
Route 83 and 22nd Street
13
-------
o
H
+J
d)
JS
o
0)
g
nJ
4-)
03
60
CS
O
vO
0)
*J
00
14
-------
possible to compare the readings obtained on the "Ecolyzer" with those
obtained by the EPA reference method. The results of this comparison will
be discussed in a later section.
NDIR unit 161 was used as a continuous monitor for sampling the ambient air
and contained a surge tank to reduce the scatter. NDIR unit 163 was used
as a continuous monitor as well, but it was also used to determine the con-
centration of the bag samples. For this reason, no surge tank was used on
this analyzer. "Ecolyzer" 162 was equipped with a 2 liter surge tank
instead of the one gallon glass container mentioned earlier. The 2 liter
container was sufficient to reduce the excessive scatter since some inte-
gration was accomplished in the sampling air manifold.
Two other "Ecolyzers" were used in the study. They were located at sites
11 and 12, shown in Figure 4. Site 11 was located on the shopping mall.
The analyzer was placed behind a locked door leading to a maintenance
storage area. A sampling line was connected to the outdoors and sampled
the air approximately 6 feet above grade. Site 12 had the sampling
arrangement shown in Figure 6. It was located in the parking area, inside
the ring road serving the interior of the shopping center.
Bag Sampling
There were four bag sampling locations at the intersection of the busier
shopping center gate on 22nd Street. These are shown in Figure 7. Eight
one-hour samples were collected each day using the apparatus shown,in
Figure 8. One of the four sites was selected each day depending upon the
wind direction. The site which would receive the maximum CO effect of the
intersection was chosen. For example, site 182 was chosen when the wind
was from the southwest. The eight-hour periods sampled each day differed
for weekends and weekdays. From Monday through Friday, bag samples were
taken between 2:00 p.m. and 10:00 p.m. Saturday samples were collected
from 11:00 a.m. through 7:00 p.m., and Sunday from 10:00 a.m. to 6:00 p.m.
15
-------
Shopping
Center
Gate
22nd Street
Um
Urn
Road leading to
Hotel parking
Figure 7. Location of bag sample sites
16
-------
W
PU
6
£
T3
V
-M
rt
ii
&
r-H
A
1
nl
*-<
O
l-i
0)
rt
PQ
o
rH
O
s
o
-JJ
3
co<
CO
0
bO
pq
o]
O
ffi
ri
Q)
^i bO
3 "43
3
CO
fl r-,
(U T3
h m
h «
^^
A H ^
O
.11 , TT
j niliyil j
CO
to
3
4-J
JO
VI
05
a.
Oi
cd
r-l
a.
B
cd
60
td
pq
oo
0)
n
3
00
r-l
17
-------
These hours were determined from the maximum daily 8-hour averages ob-
tained during a j
shopping center.'
tained during a previous carbon monoxide monitoring study conducted at the
2
The bag samples ware collected hourly, alternating between two 50 liter
"Tedlar" bags. Thus, one sample was being collected while the previous
one-hour sample was being analyzed. The samples were analyzed on both
"Ecolyzer" 162 and N'OIR 163. This afforded another controlled comparison
of the two instruments in analyzing identical sample gas. The bags were
properly flushed after each analysis so that there was no contamination
from previous samples.
DATA ANALYSIS AND RESULTS
Data Reduction
The data recorded on the strip charts were reduced manually by dividing
each one-hour period into four 15-minute increments, computing the ad-
justed average in each increment based on the zero and span calibrations,
and then averaging the four to produce a one-hour average. The NDIR data
were reduced and validated by the Quality Assurance and Environmental
Monitoring Laboratory, EPA. The data on the Ecolyzer strip charts were
averaged to the nearest ppm; the NDIR data were averaged to the nearest
0.5 ppm. The one-hour readings are the basic data for the study, and
these data have been keypunched and are. available in a computerized
system.
Ecolyzer - NDIR Comparison
As discussed earlier, the NDIR unit is used in the EPA standard reference
method for the determination of carbon monoxide in the atmosphere. The
"Ecolyzer" was used in several sampling sites in this study because of
the lesser expense, and the greater ease of operation and portability of
18
-------
this analyzer. It was necessary to compare the performance of the
"Ecolyzer" versus the NDIR unit. As described in a previous section,
two NDIR units (161 and 163) and an "Ecolyzer" (162) were connected to the
same air sampling manifold. To ensure that the "Ecolyzer" used in the
comparison was not unique, it was replaced on April 3 with a second unit.
The NDIR results for any given hour were averaged, or a single NDIR reading
was used if that was all that was available. A regression comparison of
the analyzer and NDIR data prior to April 3 yielded the relation
("Ecolyzer" reading) ppm = 1.053 (NDIR reading) ppm + 0.548 ppm and a
correlation coefficient of 0.945. A similar comparison of the data taken
after April 3 gave the result ("Ecolyzer" reading) ppm = 1.311 (NDIR
reading) ppm + 0.489 ppm with a correlation coefficient of 0.970. A
regression analysis of all the "Ecolyzer" and NDIR data was then made
using the least squares method. The regression analysis yielded the fol-
lowing equation:
("Ecolyzer" reading) ppm = 1.153 (NDIR reading) ppm + 0.546 ppm
This equation had a correlation coefficient of 0.947. Several other
regression studies were made using data greater than 6 ppm, less than
3 ppm, and other data comparisons. None of these, however, yielded a
correlation coefficient as high as the one found using all data. All
"Ecolyzer" data obtained throughout the study were corrected using the
above regression equation. It should be noted that this equation was
obtained from the results of this study only, and that it is not neces-
sarily generally applicable as presented.
Continuous Monitoring Data
Time series plots of the continuous monitoring data are given in Ap-
pendix A, Tables Al and A2. The "Ecolyzer" data have been corrected
using the regression equation, and all values ending in 0.50 through 0.99
have been rounded up to the next highest integer. The corrected one-hour
19
-------
and eight-hour averages for all of the continuous monitoring sites are
listed in Tables A3 and A4 in Appendix A.
Bag Sampling Data
The one-hour and eight-hour averages obtained by bag sampling are listed
in Table A5, Appendix A. The NDIR unit was used to analyze all bag
samples until the NDIR units were removed on April 10th. Data collection
continued until April 13, and an "Ecolyzer" was used to determine the CO
concentration of the bag samples for the three remaining days. The data
obtained during these three days have been corrected by the regression
equation discussed above.
Episodes
The data listing in Tables A3 and A4, Appendix A, shows that neither the
one-hour nor the eight-hour standards were exceeded during the study. The
highest one-hour reading of 11.7 ppm occurred at two different stations
during the evening of Wednesday, April 3, 1974. Station 12 recorded the
reading between 8:00 and 9:00 p.m., and station 15 recorded it between
9:00 and 10:00 p.m. The wind speed was 2 to 3 mph and the winds were from
the east-southeast.
The highest eight-hour average recorded was 8.5 ppm, and it occurred at
station 12 in the eight-hour period from 9:00 p.m. on Friday, April 5 to
5:00 a.m. on April 6.
Table 1 gives a listing of the three highest non-overlapping episodes.
There is no definite trend evident from this table. The highest episode
occurred during the early morning hours when the concentration is usually
the lowest. It also occurred in the parking lot when traffic near the
station would be minimal. The wind speed was very low, however, and all
eight analyzers recorded eight-hour averages above 6.0 ppm during this
episode.
20
-------
H
'-O
a
o
--
H
en
o
M
H
co
s
O
O
6
CJ
to
d
H
r-l "O
M d
Oj 'rH
o
PH
O 01
to ,
D* T-I co r! i I
4J f-i !-i
r\j ty I-j ^j O D
-W O O £ O
CO co '-"' JS H J^
readings
(11.7 ppm)
O
0
CM 1
5 r* o
r-l O O
ra i o <)
-------
The second highest episode had an eight-hour average of 8.1.ppm. The
prevailing wind direction was from the east, and under these conditions
the analyzers in the van should have recorded the effects of the inter-
section. This was indeed the case and stations 161, 162, and 163 all
recorded eight-hour averages over 7 ppm during this episode, including
the high value of 8.1 ppm at 163.
The third highest episode recorded occurred on Wednesday, April 3, when
the eight-hour average reached 7.9 ppm. The two highest hourly averages
(11.7 ppm) were recorded during this episode.
Diurnal Patterns
The diurnal patterns for weekdays, Saturdays and Sundays were determ-
ined by averaging the readings from all of the continuous monitoring
analyzers for each hour of the day.
The diurnal pattern for weekdays, shown in Figure 9, indicates three
discernible peaks. The first peak, between 7:00 and 8:00 a.m., is
probably due to the morning rush period and the second peak, between
5:00 and 6:00 p.m., is the evening rush period. The third peak,
between 9:00 and 10:00 p.m., occurs at the shopping center closing
time.
The diurnal pattern for Saturday (Figure 10) shows that the early
morning hours have the highest CO readings. This is questionable and
can be explained by the fact that only three days of data were used
to determine the diurnal pattern. This included Saturday, April 6,
which had the highest eight-hour average recorded during the entire
survey. The diurnal pattern does show a definite peak during the
early afternoon shopping hours. There is also a peak between 5:00
and 6:00 p.m., which would include the shopping center closing time,
followed by a sharp reduction.
22
-------
i i i t i r i I i i i
CO
3
03
g
cd
(a
t-i
I-H
nl
I
nj '
c
M
0)
NOLLVH.LN3DMOO OO
23
-------
i i I1 t i i i I i i
4J
c«
CO
I
CO
§
rl
CO
J-l
1)
4-1
.(J
nj
CU
O
r-H
-------
Sunday's diurnal pattern, shown in Figure 11, also includes only
three days of data. It shows a very similar afternoon pattern with
a pronounced peak during the early afternoon, a second peak at closing
time and a sharp reduction after closing. The early morning hours
are much lower, however. Diurnal patterns based on the bag sampling
data were also determined, and these were compared to the continuous
monitoring diurnal patterns for the sfine eight-hour periods. These
comparisons are shown in Figures 12, 13 and 14.
The weekday bag sampling pattern shows a strong similarity to the
continuous monitoring pattern, as shown in Figure 12. The evening rush
peak on the bag sampling data is much more pronounced, but the timing
is very similar, as is the peak at the shopping center closing time.
The higher peak is due in part to the location of the receptors, as
shown in Figures 5 and 7. The closest continuous monitors were
located twice as far from the road edge as the bag sampling locations.
The effect of this distance can be seen in all three bag sampling
diurnal patterns.
The Saturday bag sampling diurnal pattern is also similar to the con-
tinuous monitoring pattern for the same time period, as shown in
Figure 13. The shopping center closing time (5:30 p.m.) produces a
peak on both curves, followed by a very sharp drop in CO concentra-
tion during the following hours. The early afternoon patterns are
not so similar, but both show a sharp increase in the very early
afternoon and a decrease in the hour prior to closing.
Sunday's diurnal pattern comparison, shown in Figure 14, shows a
sharp increase in the early afternoon concentrations with a peak
between 3:00 and 4:00 p.m. on both curves.
25
-------
I I } I 1
§
UJ
s:
ca
§
H
4J
OJ
W
CO
r-t
tt
fx.
<-(
0)
00
(Hdd)
03
-------
£
ex
a.
c:
o
o
o
c.
o
O
O
O
BAG
SAMPLING
CONTINUOUS
MONITORING
I I I I I I
14 15 16 17 18 19 20 21 22
Jims of Day
Figure 12. Diurnal pattern - weekdays
27
-------
CONTINUOUS
MONITORING
II 12 13 14 15 16 17 18 |9
Time of Day
Figure 13. Diurnal pattern - Saturdays
28
-------
6
Q.
CL
c
o
o
c
o
o
O
O
BAG
SAMPLING ~?
CONTINUOUS
MONITORING
I I I I I I 'l
10 H 12 B 14 S5 !6 17 13
Time of Day
Figure 14. Diurnal pattern - Sundays
29
-------
Frequency D is t r ibutions
The cumulative frequency distribution of one-hour and eight-hour CO
concentrations is shown in Figure 15. Figure 16 is a similar plot on
log-probability paper, used to test the hypothesis that the distribu-
tion is log normal.
These curves were used to determine the frequency distribution values
listed in Table 2.
Table 2. FREQUENCY DISTRIBUTION OF OBSERVED CO CONCENTRATIONS
Percentile
1 hour
8 hour
40
0.6
0.6
50
1.1
0.9
70
2.1
1.8
90
4.0
3.5
99
8.0
6.4
METEOROLOGICAL DATA
Wind Speed and Direction
Wind speed and direction data were collected at the site shown in
Figure 5 in the immediate vicinity of the intersection of Route 83 and
22nd Street. The wind sensing instrument used was a "W101-P Skyvane
1 Wind Sensor" from Weather Measure Corporation, mounted at the top of
a 20-foot pole. The data rere recorded on a "W123 Wind Recorder,"
manufactured by the same firm. The recorder was housed in the van
containing the two NDIR CO analyzers and the "Ecolyzer."
The strip charts were checked daily to ensure that reasonable data
were being obtained and that the chart drive was maintaining accurate
time.
30
-------
o
a:
n.
ui
100
90
80 L
70
60
50
40
30
20
10
01 2 3 45 67 8 9 10 11 12
CO CONCENTRATION (ppm).
Figure 15. Cumulative frequency distribution
31
-------
LU
CJ
99.9 -
99
98
95
90
80
70
60
50
40
30
20 _
10
5
2
10
CO CONCENTRATION (ppm)
Figure 16. Cumulative frequency distribution
32
-------
The data on the strip charts were reduced manually by dividing each one-
hour period into four 15-minute increments, computing the average in each
increment, and then averaging the four to produce a one-hour average.
The wind speed was averaged to the nearest mph, and the wind direction
was averaged to the nearest 10 degrees.
The wind speed is plotted in Tables Al and A2, Appendix A, and the wind
direction is listed in these tables also. Both are also listed in
Tables A3 and A4. The number of occurrences of each wind speed obtained
during the survey is listed in Table 3, along with the percent of each
occurrence and the cumulative percent. This information was used to
derive the frequency distribution curve shown in Figure 17.
Stability Class
The stability class for each hour of the survey was determined by an
3
objective method from the month, date, hour of day, cloud cover,
cloud ceiling, and wind speed of each hour. All of these data were
either known or collected on-site, with the exception of cloud cover
and cloud ceiling. Data for th^se two parameters were obtained from
the National Weather Service. Two sets of data, one measured at
Midway Airport and the second at 0'Hare Airport, were obtained, and
the stability classes were calculated using each set of data. A com-
parison of the stability classes showed that they were very similar.
The O'Hare stability classes were then chosen, because O'Hare is
slightly closer to the monitoring site than Midway (approximately
9 miles versus 11 miles).
Temperature readings at different heights were obtained from the
Meteorological Station at Argonne National Laboratory, which is
located approximately nine miles to the south of the monitoring site.
33
-------
Table 3. WIND SPEED FREQUENCY DATA
Wind speed
(mph)
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
# of
Occurrences
18
19
17
31
22
36
38
37
31
40
40
29
25
16
00
21
13
15
13
14
16
3
4
2
4
4
2
3
1
2
2
1
7, of
Occurrences
3.3
3.5
3.1
5.7
4.1
6.6
7.0
6.8
5.7
7.4
7.4
5.4
4.6
3.0
4.1
3.9
2.4
2.8
2.4
2.6
3.0
0.5
0.7
0.4
0.7
0.7
0.4
0.5
0.2
0.4
0.4
0.2
Cumulative %
3.3
6.8
10.0
15.7
19.8
26.4
33.4
40.3
46.0
53.4
60.8
66.2
70.8
73.7
77.8
81.7
84.1
86.9
89.3
91.8
94.8
95.4
96.1
96.5
97.2
97.9
98.3
98.9
99.0
99.4
99.8
100.0
34
-------
|OO
iir~iiii
12 13 14 15
Wind Speed (m/sec)
_» t t t
i t i I
10
20
30
(mph)
Figure 17. Wind speed frequency distribution
35
-------
The standard deviation of the wind direction strip charts data was also
determined for each hour.
The input data to these alternate methods for determining stability class
are available for validation of the calculated values listed in Ap-
pendix B.
36
-------
SECTION IV
TRAFFIC MONITORING PROGRAM
MONITORING NETWORK
The basic geometric and lane-use configuration at the intersection of
Route 83 and 22nd Street is illustrated in Figure 18. The intersection
is controlled by a four-phase, fully-actuated traffic signal, with
phasing as illustrated in Figure 18, In addition, traffic conditions
were also analyzed at the two shopping center entrances nearest the
intersection (one north of the intersection on Illinois Route 83 and
one east of the intersection on 22nd Street) . Both of these two
entrances are controlled by fully-actuated, three-phpse traffic signals.
The basic geometries for these tx^o entrances and their signal phasing
are illustrated in Figure 19.
The monitoring of traffic volumes at the two entrances and at the inter-
section of Illinois Route 83 and 22nd Street was performed continuously
from March 13 through April 13, 1974. Automatic traffic counters were
placed at the intersection to enable all turning and through movements
to be monitored. The counters recorded the traffic volumes occurring
each 15-minute and hourly interval. Figure 20 illustrates the location
of the traffic counters at the intersection. In addition, automatic
traffic counters were also located to monitor inbound and outbound
traffic at the two nearby entrances and on the shopping center circula-
tion road. Figure 21 illustrates the approximate locations of these
counters.
37
-------
Figure 18. Route 83 - 22nd St. intersection configuration
and existing signal phasing
38
-------
ENTRANCE 10
mut UOVCHCNT
hill
ENTRANCES
UOVEMCMT
JL
ir
hit-
Figure 19. Entrances 8 and 10 - geometric configurations
and existing signal phasing
39
-------
RTE. 83
AUTOMATIC TRAFFIC COUNTER
Figure 20. Location of intersection counters
40
-------
"S X"
4
22ND ST
c:
NORTH
OAKBROOK
SHOPPING CENTER
B-
-fi
V
CI
^\ x^
H- AUTOMATIC TRAFFIC COUNTER
Figure 21. Location of counters within shopping center
41
-------
At various times during the monitoring process, additional field
studies were performed to obtain data on the average operating char-
acteristics of the vehicles traveling through the intersection.
Utilizing "test" vehicles, data on queue lengths/cycle, intersection
delay/stopped time, and acceleration and deceleration rates were
obtained.
The "test" vehicles were staffed by one driver and one observer-data re-
corder in each auto. On each of 5 days, while the traffic volumes were
being monitored by the automatic counters, two vehicles were continu-
ously driven through the intersection. The vehicles were driven as
closely as possible to the same pace as the traffic stream. For each
run through the intersection, approach speeds (approximately free-flow),
deceleration times, queue times, queue lengths, acceleration times, and
departure speeds were' recorded. The beginning time and direction of
each run was recorded as well as the type of movement being performed
(right turn, left turn, or through). These queuing studies were per-
formed on weekdays on March 15, 21, and 22 from 9:00 a.m. through
6:00 p.m. and on April 7 and 8 from 7:00 a.m. through 7:00 p.m. In
addition to these studies, manual traffic counts at the intersection
were performed to determine the accuracy of the machine counters and
to determine the distribution of traffic by lane. Field surveys were
also performed to determine signal phasing and timing at the intersec-
tion and intersection geometry.
EVALUATION OF TRAFFIC OBSERVATIONS
Impact of Shopping Center on Local Volumes at Intersection
From the analysis of additional traffic counts taken at Oakbrook Shop-
2
ping Center during the month of December, 1973, and from previous
counts taken in 1972, it was determined that the distribution of shop-
ping center traffic volumes by entrance (and turning movement) does not
fluctuate significantly from one day (or hour) to another. Table 4
42
-------
§
M
rXl
PL.
§
co
^
8
gg
^g
o <
H
/\
W P
1s
5 o
>g
r.
83
P4 W
O M
Pn
W J
u
O Pi
M
r-l
r-4
CO
P
r-H CM O ON « i (""") CO i t CD ON O CQ o\ f O r-l o*\ cr\ i i CD CO CD
i-H rH i-i rH -H r~«] r-l r-4 r-H rH t-4 r-4
rHrHCNCMCMCMrHCMrHrHrH.-.^rHrHrHrHr-lSr-.rH
CMCMr-li 4r-4r-4r-4r-4i 4r Ir-li lr-4i 4 r-l rH r-4 I 4 t 1 i lt1
r-ICMr-lr-lr-lr-ICMr-lCMCMr-ICMr-l- c ^! r-^ r^* '^^^ CM p*** r^^ o** r^- r~* i%- 1" ^^-« r^ r^ *J~
i 1 CM ^"- CM "* "^~^ UO " ^ CM ~v CM ~*~^ "^-^ r*- CM "~*^. J ^- co ^~- O r-i ~^~ co r-» LPI i r-~ .
CM CM CN CM '"'j O-i "^-, i 1 CM CM CM CO CO H i 1 "^ ^ "~^ "^^s ""^- CO
r-l 1 1 ~~ i 1 "~-. ^-. CM II »-, r- 1 ~^~- *~^ --. i f vj" r-H ^D t^ .
CM CM CM r-l » CM CMCMr-l« ~^- -^,-^.rH
f\ ^ ^-1 rt f 1 | i ^^ ft f 1 r. , 1 ! 1 p>s, ft , ( « p- ( f^
r*\ r**i K^ " Cil r*1 '^t ** CO £""> ^*1 "
CO CO ^ CO «\ *\ ^ -^J r^J n K$ 11 r\ ^ -£} rfj " Q N " ^-j
!-i U) ro S-J W TO T3 CD CO n3 !J eg ct) ''O CU w CO !-i co CO TJ
4-1 3 -H u ti a d> 73 3 T-I 4-1 c a a 'a 3 <-> w fi c: CM
r-l r-H
CO CM -3- P>.
r^- CM r-. r-i
r-4 r-H
O VQ LO vO
O CM CO CM
CM CO r-l
in a-\ r^- o
CM
rH r 1
CM X! X
C^J CO QJ Qj
OJ
W CO W 10 W
>,>->>. co ;>.
C3 co CO S-t CO
rO *O *"O QJ T3 *
,-1 > -i-l CM
r-4 14 il Cfl r-l C/1
r-l i-l O O
<; <; a! K
43
-------
indicates the distribution of shopping center traffic by entrance
during the December, 1973 study. Figures 22 and 23 illustrate the
distribution of shopping center traffic volumes at the various en-
trances and roadways adjacent to the site on a typical Saturday and a
typical weekday, respectively, during the previous study. The per-
cents of right turns and left turns at each entrance are also indicated.
The large solid arrows are the principal outbound directions of depar-
ture. The small solid arrows show the breakdown of the principal depar-
parting traffic into the turning movements at the various intersections
and entrances. The large striped arrows are the principal inbound
directions of approach. The smaller dashed arrows are a breakdown of
the inbound traffic by turning movement at the intersections and en-
trances .
For example, in Figure 22, 20 percent of the total site traffic ap-
proached the center from the east on 22nd Street. Of this 20 percent,
1 percent turns right on Spring Road and enters on Hargar Road (entrance
off of Spring Road). The remaining 19 percent continues eastbound on
22nd Street to the next entrance where 16 percent turns right into the
site and 3 percent continues westbound and turns right into the site at
the next entrance. As shown, the shopping center percent of total ap-
proaching and departing traffic that passes through the intersection of
22nd Street and Illinois Route 83 varies by direction. The north leg
(the section of roadway north of the intersection including approach
and departure lanes) accommodates approximately 19 percent of departing
shopping center traffic and 16 percent of approaching shopping center
traffic, averaged from both Figures 22 and 23. The south leg accommo-
dates approximately 15 percent and 16 percent departing and approaching
traffic, respectively; the east leg 16 percent and 20 percent; and the
west leg 20 percent both departing and approaching. Assuming this dis-
tribution of shopping center traffic to be a constant function over time,
the impact of shopping center traffic on the intersection was determined
using the additional data collected during March and April. Table 5
indicates the impact of shopping center traffic volumes on the north
44
-------
* CO
r-j
1
V" T '
X X '
o to
1 !
^^ IU-
2% eci^c^^i^
XX i
M i
*S
I
1
XX
Jlj
^
CD
£i
«
C - J20% . . ,
X- ' JJJ
-'- '
'inVrrtK "i
20% L> 20* --«'
' " y « .
' ^f£\. ** '^
' . ^4 >** ' . *\^
" i II ' ! 1
fc | ! i I n
'^r n r-H ... - -^---^
1 1 __j-^ i ~^ "' -\
-"^r'"'7"^^'^"
1 1 l»s-^-, ---~~ -
i i <'"<*.:
" .-'/'
t-« /" ;;
; r7% . .--- ' - -
^-^/^:^^: , .. J
! ^ - : ^< \ . > .-- - -.-:-
Jx .' -!\ > "-- «-3'
'SS x-'xN^ ^ " ' s< ^
-xX\Vy\ »-l
! / -:-><> x\ -,^ ^
^; ///^'r '
^~ :~ . ^S "i ' \ -\
; / , - : --^--'OAKBROOK - \. .
.' { p; '-""- \ SHOPPiNGCCNTER _x .- ,
i *; »' NA'V"' \v-/X \
" \ |!v ?^X - '
L ' \ ^J~^ ^ ^ 1
^ __. \ \ \^. \ *^ -' , ' *C ]* *
,X\\ \/ . , '/ NORTH |
' \ '/ ' '
, \ > \ '/ ' , ' ,- s^.^
1 i'' '-:':v-": ~~r ----"' x ' . tf
I i =g . L_«. £2 L_16X ,]
"* . JL ;*~" ju: i*-" IU
, -- ^ - j>\, ^ -" - ^ - - - 22'.OST J
~- r~ -j -- _-_------ -j , ---..--- _.,_.
t t 18X - J if 7X -^ 1 !
! i 3% --* i i »x -* i i :i% zr
lA ^
^ ^
>v
\
i
'
-, 5%^
1
>!
n
i
' rt
. L_,N S\V
"~"'"xl.L >0%
Nj
. .-. .'. '.-. . .'..'.. ;.;..
J21%|"^"\
1 je
' 1ft
Figure 22. Directional distribution of traffic on a typical Saturday
45
-------
Figure 23. Directional distribution of traffic on a typical weekday
46
-------
H
O
H
w
I
co
,
CO
T3
r-l
r-J
fe
Thursday
Wednesday
Tuesday
>>
CO
T3
c
O
s
>^
TO
T3
C
^!
W
Week
beginning
B>S
cr\ c^ cy> ro ro
C^l r^ r-l r-l rH
co o! ro ro ro
S~S
o\ co S
CM r-l r-l CO
ro ro r-i in
ro ro ro O
3-9
m co o
r . .
T)
CM a
CM
CM
V f
M
<} r-l CO OO
ro co ro ro CO
S-S
ro m si- ^J- m
r~~ vo in oo m
CM CM CM CM CO
B-S
ro oo vo o~v r- 1
c^ vo oo o
CM CM CM CM CO
B-S
* CO f^ r-l
CM C-4 CM rO
5^
oo in VQ GX
1 ....
m co oo o
CM CM CM ro
B^
!-4 -O- OO O
1 ....
CO r-l r^ r-l
CM ro CM ro
s^
O ^O MD CO
CM CM r-l CM
ro ro co ro
6-5
CM
O
CO
5^
OO
-------
and east legs of the intersection (in terms of percent of two-way,
24-hour volumes) by day of the week. The impact of the shopping center
traffic volumes on the total two-way hourly volumes at the intersec-
tion varies considerably throughout the day. At Oakbrook Shopping
Center, the peak impact of the shopping center traffic (in terms of
percent of total traffic) occurs during the midafternoon hours on both
weekdays and weekends when as much as 50 to 60 percent of the total
intersection traffic is destined to or departing from Oakbrook Shopping
Center. During the morning weekday rush hours (approximately 7:00 a.m.
to 9:00 a.m0) only 18 percent of the traffic at the intersection is at-
tributable to the shopping center. This shopping center traffic is
basically the employee traffic. Thirty-two percent of the traffic of
the intersection is attributable to the shopping center during the
afternoon rush hours (approximately 4:00 p.m0 to 6;00 p.m.). The exact
percentage is a function of both the shopping center activity and the
activity of the surrounding traffic generating land-uses. A complete
analysis of the hourly fluctuations in shopping center traffic as com-
pared to total traffic for all the days surveyed in March and April is
presented in Appendix C by intersection leg for two-way traffic.
Tables 6 and 7 present 1- and 8-hour traffic volumes for each direction
of travel on the north and east legs of the intersection. These vol-
umes are broken down as through, shopping center, and total volumes;
and the percent of the total volume comprised of shopping center
traffic is presented.
Guidelines for Relating Operating and_Design Characteristics to
Selected Key Parameters for Emission Estimation
The estimation of emissions generated by traffic in the vicinity of
a proposed indirect source such as a regional shopping center is de-
pendent upon two principal traffic parameters: the total volumes of
traffic occurring on adjacent roadways in the vicinity of the site and
some measure of congestion such as the "level of service" at which the
volume of traffic is operating.
48
-------
Table 6. DIRECTIONAL TRAFFIC VOLUMES - NORTH LEG OF ROUTE 83 AND
22ND STREET INTERSECTION
Pate
3/22//A
3/22/74
3/22/74
3/22/74
3/22/74
3/22/74
3/22/74
3/22/74
total
4/ 5/74
4/ 5/74
47 5/74
4/ 5/74
47 5/74
4/ 5/74
4/ 5/74
47 5/74
total
4/ 6/74
4/ 6/74
4/ 6/74
4/ 6/74
47 6/74
4/ 6/74
4/ 6/74
4/ 6/74
total
4/10/74
4/10/74
4/10/74
4/10/74
4/10/74
4/10/74
4/10/74
4/10/7.':
8-hour
total
4/12/74
4/12/74
4/12/74
4/12/74
4/12/74
4/12/>4
4/12/7'.
4/12/74
total
of
veoV
Fr i .
Fri.
Fri.
Fri.
iv i.
Fri .
Fri.
Fri.
Fi j .
Fri.
Fri .
Fri.
rri.
Fri.
Fri.
Fri.
Sat.
Sat.
S.It.
Sat.
Sat.
Sat.
Sat.
Sal.
Wed .
Wed .
Wed .
Wed.
t.'oJ .
Wed.
Wed .
Wed .
Fri.
Fri.
Fri.
Fri.
Fri.
Fri.
rri .
Fri.
01
day
12
13
14
U
If,
17
16
19
12
13
14
15
16
17
18
19
12
13
14
15
JO
\7
18
19
12
13
14
15
16
17
18
19
12
13
14
15
16
]7
13
ID
Southbound direction ol" tr.iwl
Through
valim.cs
494
51S
387
500
695
9S3
847
580
5,015
380
312
491
391
667
951
721
708
4,621
450
575
677
524
6S1
535
425
612
4,479
--
--
712
590
818
820
674
586
5'tO
:>03
547
6/9
599
524
550
4, 53 3
.S!iO|'pin4'
ce-.'ler
86
167
195
3 2 '<
338
437
517
187
2,251
226
240
274
319
377
513
562
204
2,715
335
450
446
510
576
568
623
88
3,596
--
130
417
566
556
231
2SS
464
419
505
541
595
514
251
3,587
ToL.il
vo 1 u . c ;
Si'O
r,;-5
5S?
330
1,033
1,425
1,3(.4
767
7 ,266
606
552
765
710
1,0 '(4
1,464
1 , 283
912
7,336
785
1,025
1,123
1 , 034
1,257
1,103
1,048
700
U.075
714
786
837
842
1 , 007
1,38't
1,376
905
832
1 , 004
927
1,032
1,220
1,194
1,038
801
3,120
!vi cent
3 .C .
15
24
33
3')
33
30
38
24
31
37
44
36
45
36
35
44
22
37
43
44
40
49
46
51
59
13
45
--
--
15
41
41
40
26
34
46
45
46
44
50
50
31
44
;;orthhound direction of travel
jl.i..n,,'i
\oU'..es
327
287
103
383
379
577
486
215
2.762
231
180
409
494
473
613
507
459
3,366
388
421
393
407
431
559
442
443
3,^84
i^4
327
'03
395
475
641
513
225
,
3.403
3:> 3
309
305
425
494
309
5'.0
J53
3,21)8
>ho;y in.;
o t n 1 i i'
368
350
385
296
233
2S1
302
3?1
2,533
254
29;!
290
214
1S7
217
242
257
1,959
473
462
468
457
374
246
112
58
2,650
23h
316
2 04
177
201
201
2] 9
263
1,876
402
402
431
432
322
23o
123
30
2,330
Tot.il
vol vines
695
637
4 S3
u84
612
S58
788
536
5,298
485
478
699
703
660
830
749
716
5,325
361
883
861
364
805
705
554
491
i,13'(
662
643
667
672
6/6
S'42
732
483
5,279
735
711
735
357
816
547
&03
r>83
5,i>48
I'erccnt
s . c .
53
55
79
43
33
33
38
60
48
52
62
41
30
29
26
32
36
37
55
52
54
53
46
35
20
12
43
36
49
40
26
30
24
30
54
36
55
57
59
50
39
44
19
5
42
49
-------
Table 7. DIRECTIONAL TRAFFIC VOLUMES - EAST LEG OF ROUTE 83 AND
22ND STREET INTERSECTION
Date
3/22/74
3/22/74
3/22/76
3/22/74
3/22/74
3/22/74
3/22/74
3/22/74
total
4/ 5/74
4/ 5/74
4/ 5/74
4/ 5/74
4/ 5/74
4/ 5/74
4/ 5/74
4/ 5/74
total
4/ 6/7 4
4/ 6/74
4/ 6/74
4/ 6/74
4/ 6/74
4/ o//4
4/ 6//4
4/ 0/74
total
4/10/74
4/10/7V
4/10/7^
4/10//4
4/10/74
4/10/7*
4/10//4
4/10/74
8-hour
total
4/12/74
4/12/74
4/12/74
4/L2./74
4/12/74
4/J2/74
4/12//4
4/12/74
8-hour
total
>>
of
week
Fri.
Fri.
Fri.
Fri.
Fri.
Fri.
Fri.
Frl.
Fri.
Fri.
Fri.
F r 1 .
Fri.
Fri.
Fri.
Fri.
S..C.
Sat.
oat.
S u I- .
S.]i:.
Sat.
Sat.
Sat.
Wr;l
'Jed.
'.:oJ.
',.Yd.
'led.
;,'ed.
Wed .
'..Yd .
Fri.
Fri.
Fri.
Fri.
Fri.
Fri.
Fri.
Fri.
of
Jjy
12
13
14
15
16
17
13
19
12
13
14
15
16
17
18
19
12
13
14
15
16
17
18
19
12
13
14
15
16
17
18
19
12
13
14
lr>
16
17
13
19
Uo.tt hound direction of travel
Through
volumes
637
59(>
483
503
627
833
773
546
5,003
636
576
483
432
611
774
761
552
4,325
399
A 59
470
408
395
272
306
714
3,423
68'
431
447
313
431
777
732
47-'i
4, 337
570
737
537
'.77
474
549
487
345
4,1/6
Shopping
center
141
181
202
230
260
241
255
163
1,673
161
195
203
245
277
264
283
213
1,841
227
300
299
374
396
416
450
55
2,517
169
255
263
2/7
. 319
' 257
278
214
2,032
213
296
299
375
360
326
325
205
2,399
Total
volumes
778
777
635
733
887
1 , 074
1,023
709
6,676
797
771
868
677
8S3
1,038
1,044
755
6,666
626
759
769
782
7
-------
Traffic Volumes - The volume of traffic in the vicinity of the shop-
ping center can be separated into two parts: through traffic volumes
and site-generated (shopping center) traffic volumes. Each should be
treated as an independent phenomenon having distinguishable diurnal,
weekly, and seasonal patterns.
The volume of through traffic on any section of roadway in the vicinity
of the site at a given hour depends on several factors such as the type
of roadway (function, capacity) and the intensity of development in
the area to which the roadway provides access. As stated previously,
Oakbrook Shopping Center is located adjacent to two major regional
arterial roadways. These two routes serve as feeder routes to the
expressway system and as principal access routes to the major office/
employment areas east of the center. As is typical of roadways of
this nature, several diurnal weekday patterns of through traffic occur:
1. Highly directional patterns (approximately 70/30
directional splits) of traffic during morning and
evening rush hours. These are northbound and east-
bound in the morning and southbound and westbound
in the afternoon.
2. High peaking characteristics. Peak morning and evening
rush hour traffic is 10 to 12 percent of the total 24-
hour traffic volumes.
The projection of through traffic volumes in the vicinity of a pro-
posed shopping center is at best an "inexact science." The general
lack of substantial data on diurnal, weekly, seasonal, and annual
patterns at most locations requires several simplifying assumptions
to be made. The following procedure is presented as a method for
determining future 1-hour and 8-hour through traffic volumes
on the roadways adjacent to the site:
1. Determine the existing 1-hour and 8-hour traffic
volumes. Perform 24-hour (or 12-hour, minimum) traffic
counts at the major intersections in the vicinity of
the site. Manual counts, including all turning move-
merits, should be made during morning and evening rush
51
-------
hours, if possible. An analysis of these data will
provide a basis for estimating the existing peak
1-hour and 8-hour periods of traffic.*
2. Obtain adjustment factors to account for weekly and
seasonal fluctuations. These estimates can usually
be obtained from state or local highway agencies or
from consultants familiar with traffic patterns in
the site vicinity. Weekly and seasonal adjustment
factors can vary considerably with the geographical
location and urban, suburban, or rural environments.
3. Determine the annual growth rate. The future through
traffic volumes on the highway are highly dependent
upon the potential for growth in the area surrounding
the center (other than the center itself). A trend
analysis of traffic volumes (or population growth) is
perhaps the best method for determining future growth
rates on roadways. Of course, consideration must be
given to the amount of potentially undevelopable land
in the vicinity of the site, other proposed new devel-
opments adjacent to the site and future programmed im-
provements to the roadway network (new or improved
roadways). Typical annual growth rates for through
traffic volumes range from 0 to 1 percent for built-
up urban areas to 5 percent or more for rural areas
on the fringe of growing -metropolitan areas. Again,
local and state highway officials and appropriate
planning agencies should be consulted to determine
localized factors for annual growth rates.
4. Estimate 24-hour, 8-hour and 1-hour traffic volumes
for air quality design year(s). Existing traffic
counts should be adjusted by weekly and seasonal
factors and a growth factor to determine maximum,
average, and minimum traffic volumes on a daily
basis.
The traffic volumes generated by regional shopping centers depend on
several factors. Among these are size, tenant mix, operation of
center (opening times, special sales, etc.), trade area demographics,
transit usage, and regional geographical location within the United
k»-
"A second method for determining through traffic volumes which is con-
siderably less precise is to use AADT maps (usually available from
state or local highway agencies). Typically, the 1-hour peak is
8 to 10 percent of the AADT and the 8-hour peak is 50 to 60 percent
of the AADT.
52
-------
States. The most important factor singled out in the present state-
of-the-art is size in square feet of gross leasable floor area (GLA).
Although a great deal of research work has gone into determining
volumes generated by regional centers, there are still numerous
variables xvhose effects have not yet been quantified. A study of
2
six regional centers in the Chicago metropolitan area indicates
substantial variations which appear to be attributable to factors
other than size. Appendix D summarizes the results of the December
traffic counts at these six regional centers.
The analysis of traffic generated by Oakbrook Shopping Center during
December, 1973, and January, March, and April, 1974, is summarized in
Tables 8, 9, and 10. More detailed information on the observed hourly
and daily trip generation rates is presented in Appendix E.
The peak single day for traffic at Oakbrook Shopping Center during
the two periods surveyed was the Saturday before Christmas with the
Wednesday after Christmas a close second. The 24-hour, 8-hour5
and 1-hour volumes generated on these two days were 150 to 170 per-
cent greater than the averages for all the days surveyed (excluding
holidays when the center was closed). The lowest single day of shop-
ping center traffic was the Sunday after New Years. The lowest
weekday observed was Monday, January 7, 1974. As anticipated, Satur-
day is the typical peak day for shopping center traffic. The average
24-hour generation rate for all Saturdays observed was 35.5 trips/
1,000 square feet compared to 32.0 for all weekdays. Friday was the
second highest day of the week for shopping center traffic activity,
averaging 34.9 trips/I,000 square feet daily. Sunday was the lowest
day of shopping activity averaging 23.5 trips/1,000 square feet over
all the days surveyed.
As indicated by the data in the tables, the average 24-hour, 8-hour,
and 1-hour traffic generation rates for the center during the peak
Christmas period are approximately 20 to 30 percent higher than the
53
-------
O
B
w
fK
p
o*
CO
o
o
o
CO
ft
pi
H
5
?
w
g
CO
w
is
H
§ §
H O
<3 O
^9
^ P^
W p i
°g
co
ft
£g
§
>
0) 0) X 60 trj
<1> > CJ C T3
CO
'XJ
d
3
co
CO
13
3
4J
CO
co
CO
rl
5-4
CO
w
5-1
d
H
CO
01
CJ
CJ
13
CJ
CO
TJ
01
CJ
d
H
cfl
a
d
o
60
a
H
d
d
0) 60
d) 0)
OS CO 1
CO CM r-4
cO p^ p**
cr» o CT» i
*vt" *vf C*"}
0 >fr CO
" 1
in r-4 in i
» I*"*** r*** r*^*
*^*^ ***^ ~^^. *^-^.
r*^« vj* i"~i r^«
r-l CM CO O
"^^ "^** "* ^ .
CM CM CM r-4
r-l r-4 i 1 O
vO
VA
CO
in
.
in
CM
CM
CO
^j-
VO
O
^
f^
oo
CO
^j-
.
i i
^j-
r-4
.
-,
S 60 d CO
1 n) i 1 T3
IH s-i o -1-1
O CJ X r-J
I > , co v^^a
Q
r-i oo m CM co
oo r~~ oo ON CM
CM 01 CM CM CO
v£l 00 CM VO
.... I
O O CO CO 1
CM CM CM CM
00 CM r-l r~- vD
CM vD r-l CO O
CO CM CO CO CO
in in i^* r^ co
ON O 00 CM in
CM CO CM CO CO
ON OS \O ON CM
CM CM CM CM CO
r-4 i-l CM ON
1 ....
1 O O r^. CT>
CO CO CM CM
oo co in co
1 ....
1 OO O ON CM
CM CO CM CO
CO CJ> vO
> CO
to
Q
^
«J
13
r-l
O
M
4->
CJ
CJ
CJ
d
a1
CO
O
o
o
*l
r-4
CO
cx
rl
4J
^0
r-4
CO
Ol
cO
d
CJ1
CJ
CO
c?
T)
1
r-l
CO
O
M-l
CJ
4-)
C|J
a
CJ
O]
a.
-rl
rl
4J
>,
H
CO
CJ
60
CO
a)
>>
<$
4-J
a)
0)
cu
3
a*
01
o
o
o
fV
r-l
01
a,
rl
^
4-1
-------
1 1
CD T3 r-l
60 3 O s~*
(0 i 1 .JU CO
^£ to U >,
(1) 0) X 60 (0
CU > 0) 0 TI
J5 CO ' ' <-! -H
>,
r^
rj
(y^
c$
i ,
M
3
4J
CO
£
T3
H
J_j
fn
tO
CiO
M
3
rC
H
>»
CO
tJ
to
0)
fl
T3
(!)
&
CO
to
CU
3
H
tfl
t)
C5
O
a
60
d
r4
M
u
^ -rl
CU 60
0) 0)
rs .a
v£> en co co CM
OO O OO CO vo
CM CO CM CM t-l
CM oo m
1 ... 1
i co v£> i I
CO r-4 r-4
^Q CM i-- r-l
00 CO r-4 O 1
CM CO CO CO
CO O CO
1 ... 1
1 00 ^O CM 1
CM CM CM
en r-. i
3 60 3 (0
i to 1-4 -a
m s-i o -H
O 0) X r-t
1 > . CO v-- 4^
CO
P
oo .
oo en r-. o m
r-4 r-l II CM CM
CM . r^. r^^ f- . f-^
^ ^-^ Sv^- ^"^ "^ .
r-t 00 m r-l 00
r-l r-t CM O O
~~-* ~-^ ~^~ ** ^-*.
n ro co vt"
>. CO
cO
a
»>,
cO
H
r-l
O
ffi
(U
3
0*
CO
o
O
O
1
r~i
CO
a
H
M
4J
m
CM
CM
CO
r-4
3
CP
0)
to
cfl
_1
t^
r-l
O
M-l
0)
^
3
O
A
i
J~
60
H
0.1
r-l
O
(X
n
CU
CO
f-1
CU
c
CU
60
to
a
H
S-l
I-1
g
^J
g
r-l
CO
g
(jj
60
M 4J
CU Q)
> Q)
0)
I-l
3
0*
to
o
O
O
J
r^
to
a
r4
r-l
4J
m
CM
CM
CO
r-l
3
cr
0)
CO
CO
T)
r i
o
IW
to
r-l
3
O
^
1
rC
60
r-4
a)
M
cu
Pu
T)
QJ
1 J
CO
M
cu
a
CU
60
to
ex.
r-l
r-l
4->
g
3
g
H
X
g
Q)
60
M 4J
(11 CU
> a)
-------
I
01 QJ X 00 CO
d) ^ QJ pi rO
J3 CO v_/ >H T-I
-a
a
3
as
co
t>
M
CO
CO
.,_!
(-1
CO
13
CO
Ij
M
>.
CO
TJ
03
CU
c
T3
CU
p:
tO
O
CO
cu
3
H
tO
tJ
C
O
00
C
r-l
a
c
^5 -<
cu oo
cu cu
p£ rQ
t4 in co v«o m cr>
1 1 1
»
rocoroco-^f 5W)3cd
r-- r**^ r^« r^** i^* i c\J r i "xu
""*- ^. ^»^. -^^, -^. m J_j Q .^
OJ r**» * ^ nJ ^ ' ^
^*-~ *^* ^ . ** . ^ ^>\ tO
CO CO CO
-------
generation rates during the pre-Easter period. Past observations of
seasonal patterns at other centers in the Chicago metropolitan area
indicate that traffic during both of these periods is higher than the
average for all days during the year. It is estimated that at Oakbrook
Shopping Center, the peak 3 or 4 pre-Christmas days have traffic genera-
tion rates approximately 200 percent of the overall average, while the
pre-Easter days' rate is approximately 130 percent of the overall average.
The average maximum 8-hour volume generated by Oakbrook Shopping Center
for all days surveyed was approximately 70 percent of the average 24-
hour volumes. The weekday maximum 8-hour volumes averaged 67 percent
of the weekday 24-hour volumes, while the weekend maximum 8-hour volumes
averaged 83 percent of the weekend 24-hour volumes. The average maxi-
mum 1-hour volumes on a weekday were approximately 10 percent of the
average 24-hour volumes, while the average maximum 1-hour volumes on a
weekend were approximately 14 percent of the average weekend 24-hour
volumes. The relatively high-peaking characteristics of weekend shop-
ping center traffic is a reflection of the shorter hours of operation
during those days.
The volume of shopping center traffic on any single section of roadway
in the vicinity of a proposed shopping center depends on (1) the volume
of traffic generated by the shopping center during the period under
analysis (1-hour, 8-hour, or 24-hour), and (2) the direction of approach
and departure for the traffic generated by the center.
In view of the possible variation of generation rates from one center
to another and the lack of substantive information on regional centers
throughout the United States, the following procedure is recommended
for the best estimate of the generation rate for a proposed shopping
center.
1. Select an existing center of equivalent size (and, if
possible, tenant mix arid trade area demographics) in the
same region as- the proposed center.
57
-------
2. Monitor traffic-volumes on several peak days (such as the
Saturday before Christmas, the weekday before Christmas,
or the Friday after Thanksgiving) as well as several
average days (non-special sale days in May or September).
These days can be selected by using daily sales indices
for existing regional centers in the area.
3. Estimate maximum 24-hour, 8-hour, and 1-hour volumes
from the peak pre-Christmas day(s) and the average
24-hour, 8-hour, and 1-hour volumes from the observa-
tions on the average day.
The distribution of indirect source generated traffic should be cal-
culated on the basis of a detailed analysis of the distribution of trip
origins and destinations within the area of influence of the develop-
ment. For commercial and industrial/office land-uses, the home is the
primary origin-destination and, therefore, the distribution of popula-
tion should provide a good estimate. For residential land-uses, the
place of work is the primary origin-destination and, therefore, the
place of employment should provide a good estimate. The net new trips
attracted to an indirect source originating from or destined to a
specific area should be assigned to the roadway network on the basis
of the relative efficiency of the alternate routes available. The
distribution of traffic at the entrances to the center is determined
by relative attractiveness of the entrances, which is in turn a func-
tion of distance and congestion (or expected delay). Appendix F pre-
sents a more detailed description of a suggested procedure for de-
termining the distribution of shopping center traffic on the adjacent
roadways and entrances.
Estimating the total maximum 24-hour, 8-hour, and 1-hour volumes in
the vicinity of the proposed shopping center requires a joint analysis
of the diurnal, weekly, and seasonal patterns of both through traffic
and shopping center traffic. The analysis of the data collected at
Oakbrook Shopping Center illustrates the impact that these fluctua-
tions can have on the peak volumes occurring on any section of road-
way. Figures 24 and 25 present the weekday diurnal patterns of
through and shopping center traffic volumes at the intersection of
22nd Street and Illinois Route 83. The diurnal pattern represents
58
-------
3400 T
3200
3000
2800
2600
2400
2200
2000
1800
1600
1400
1200
1000 '
800
O 600
to
ui
9 400
I
200.
NOTE:
DATA FROM SURVEY
TAKEN DECEMBER 20, 1973
THROUGH JANUARY 8. 1974
(EXCLUDING HOLIDAYS]
TOTAL
THROUGH
SHOPPING CENTER
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HOUR (ENDING) OF DAY
PEAK 8-HOUR PFRIOD
Figure 24. Diurnal pattern of weekday intersection traffic
59
-------
3800 T
3600
3400
3200
3000
2800
2600
2400
2200
2000
1800
1600
1400
1200 -
1000 -
800
600
400
LU
200
O
>
NOTE:
DATA FROM SURVEY
TAKEN MARCH 13, 1974
THROUGH APRIL 13. 1974
TOTAL
THROUGH
SHOPPING CENTEH
/
I -4 1 1 1 -t
1234587
HOUR (ENDING) OT DAY
8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
PEAK 8 HOUR PERIOD
Figure 25. Diurnal pattern of weekday intersection traffic
60
-------
the average of all the weekdays during the period surveyed. Several
observations can be noted from the analysis of these two patterns.
First, the diurnal pattern for through traffic remained stable between
the Christinas and pre-Easter seasons except for an overall increase
of approximately 10 percent in the volumes. Second, the peak period
for shopping center traffic shifted from the 12:00 p.m. to 2;00 p.m.
period during the Christmas season to 4:00 p.m. to 6:00 p.m. during
the pre-Easter season. Finally, an overall decrease in weekday shopping
center traffic of approximately 8 percent was recorded. The net
effect of these three "seasonal" shifts on total weekday traffic
volumes at the intersection was an overall increase in the 24-hour
intersection volumes of approximately 4 percent from December to
March, but an increase of approximately 27 percent in the afternoon
4:00 p.m. to 6:00 p.m. peak period.
From the combined Christinas and pre-Easter data, the 24-hour, 8-hour,
and 1-hour periods of maximum intersection volumes have been identified.
These are summarized in Tables 11, 12, and 13.
During the two periods surveyed, 24-hour, two-way volumes in excess of
48,000 vehicles occurred on only four days, three of which were the
days immediately after Christmas day. On all of these peak days, 8-
hour volumes in excess of 26,000 vehicles occurred. Out of all the days
surveyed, 8-hour volumes in excess of 26,000 vehicles occurred on
only eight. Except for'the Thursday after Christmas, maximum intersec-
tion 1-hour volumes in excess of 4,000 vehicles occurred on all of'the
four peak days. These four days of peak intersection traffic occurred
as a result of both high through traffic volumes and high shopping
center volumes. During these four peak days, the average through
traffic volumes were 19 percent higher than the average volumes for all
the days surveyed. It is expected that much of this increased through
traffic on these days is attributable to the nearby competing Yorktown
Shopping Center, thus causing through traffic and Oakbrook Shopping
61
-------
>
to
O
<) C4 C^l O>
r^ co oo r-. r--
U~l OO CO C"J Cvl
n A r> * *\
r-l O O> CTi O
in in o^i r^.
r^. r~- r i i ) cr>
O\ CO CTN f-» -)
CTl lO r-< o r^- 10 oo
m m i
1-1 m co co
.-< ON CO --t t~~
00 r-l CO CO i-l
r\ ft f* ** A
in vo CM vO O4 ON
O O cr\ co u">
i-l O vO O O\
iH i-l r-l
CTi r-4
n r\ r* n A
"» o
CT> CO O"1 CO ^o t~.
o vt r--. co oo
in co cr>
oo co o m o
t\ A ** * A
vo co r^ co r-.
r-l r-4 r-l r-l r-l
CO CO
r-4 r-l O r-4 <
nj >,
d to
W >, >» TJ
o) ni to w
a t> -a n
T) -H -r4 3
Q) H rl J3
& fH f^4 H
62
-------
CO
60
Q)
td
u
O
H
oo
d
cfl
,e
4J
S-i
o
3
bO
d s-i
H (D
CU 4-1
cx d
o ,
OJ
o
5
H
60
o
M
o
o
1/1
co
oo
CO
F4
ft
cfl
H
60
QJ
r-l
C8
J-)
O
H
60
d M
H Q)
p, jj
a d
o a)
f. o
co
oo
*\
en
LO
r~-
-------
CO
r-l
cu
0}
H
a)
B
J
i i
0
0)'
S
i
0
H
60
0)
4J
C/3
(U
T3
£3
CO
4-J
O
13
60
01
i 1
cd
w
60
0)
i I
4-i
rJ
o
Shopping
Shopping
Shopping
i i
4J
H
center
60
O
H
1-4
cd
H
center
60
O
^3
H
r-4
cfl
H
center
60
0
EH
CU
U
03
0
P
CM
VO
CM
*
CO
0
m
CM
g
r-4
CO
OX
i 1
in
o
r,
r-4
CM
m
Ox
CM
CO
CM
CO
O
r-l
r-l
CO
CM
r-l
CM
CM
CM
1
CM
r-l
Saturday
ox
o
**
o
CM
tn
r-4
OX
in
00
CM
un
o
oo
r-l
r-4
m
VD
CM
1 1
CM
CM
vO
m
m
ii
i
m
o
- o
-i
f*
CM
O
**
m
o
o
CM
00
OX
r-
i i
oo
r-.
CM
O
CM
m
r-4
r-l
CO
CM
CM
r-l
00
O
in
r-l
1
ON
O
o
Tuesday
i i
0
**
CM
OO
r-.
r-i
CM
CO
CM
CM
VO
r-l
i4
CO
m
o
i-H
00
m
O
CM
r-l
m
CO
oo
r-4
*-*
-------
Center traffic to reach peaks at the same time. The average traffic
volume generated by the 'shopping center on these four peak days was 30
percent higher than the average for all days surveyed.
As indicated by the data collected at the Oakbrook Shopping Center,
identification of the maximum 8-hour and 1-hour traffic periods
for a proposed shopping center is not a simple process. However, the
following guidelines should be used to determine when these periods are
most likely to occur.
1. The peak periods of total traffic are highly dependent
upon the ratio of through traffic to shopping center
traffic. Typically, this ratio is approximately 2:1
for suburban regional centers.-'-" With this ratio, fluc-
tuations in through traffic have twice the impact that
the same percentage fluctuations in shopping center
traffic would have.
2. The most likely periods of maximum traffic are:
a. Preschool sale days in August and September
or spring sale days (pre-Easter) when (1)
through traffic is generally at its peak (as
high as 120 percent of the average day on a
Friday), and (2) shopping center traffic is
close to its design level (approximately 140
percent of the average day).
b. Pre-Christmas Saturdays when through traffic
(in an area that does not contain intense
commercial development) is approximately 80
percent of the annual average daily volumes
and shopping center traffic is approximately
180 to 200 percent of the average day.
c. Post-Christmas (day after) exchange and sale
days when through traffic on a Friday may be
100 to 110 percent of the average annual day
and shopping center traffic is approximately
150 to 160 percent of the average day.
3. The maximum 8-hour period in the vicinity of a
regional shopping center (through traffic plus shop-
ping center traffic) typically occurs between 11:00
a.m. and 7:00 p.m. on weekdays and between 10:00 a.m.
and 6:00 p.m. on Saturdays and Sundays. The peak
65
-------
1-hour of traffic occurs simultaneously with the
peak period of through traffic (usually 4:00 p.m. to
5:00 p.m.).
4. The following set of calculations illustrates a sug-
gested methodology for analyzing the maximum traffic
flows on any critical section of roadway:
Given; Projections of through traffic
indicate that a section of roadway adja-
cent to the site will carry annual aver-
age daily traffic (AADT) volume of 10,000
vehicles. Traffic counts indicate the
evening peak hour is 10 percent of AADT
and the 8-hour period (11: a.m. to
7:00 p.m.) is 50 percent of AADT.
Information from the State Highway Depart-
ment indicates December traffic flows are
90 percent of AADT, April and September
flows are 110 percent of AADT, Fridays are
110 percent and Saturdays are 90 percent
of the average day.
Trip generation and direction of approach
analyses indicate 4,000 shopping center
vehicles utilize the section of road on an
average day.
Find ;
a. Total 8-hour and 1-hour traffic
volumes on a Friday preschool sale day
in August:
24-hour maximum through traffic = 10,000
x 1.10 (month factor) x 1.10 (day of
week factor) = 10,000 (1.21) = 12,100
vehicles.
8-hour maximum through traffic = 12,100
x 0.50 (8-hour factor) = 6,050 vehicles.
1-hour maximum through traffic = 12,100
x 0.10 (1-hour factor) = 1,210 vehicles.
e 24-hour maximum shopping center traffic =
4,000 x 1.40 (sale day factor) = 5,600
vehicles.
66
-------
8-hour maximum shopping center traffic =
5,600x 0.70 (8-hour factor) = 3,930
vehicles.
1-hour maximum shopping center traffic =
5,600 x 0.12 (1-hour factor) = 672
vehicles.
Total maximum 24-hour volume = 12,100 +
5,600 = 17,700 vehicles.
Total maximum 8-hour volume = 6,050 +
3,930 = 9,980 vehicles.
Total maximum 1-hour volume = 1,210 +
672 = 1,882 vehicles.
b. Total traffic volumes on a pre-Christmas Saturday:
24-hour maximum through traffic = 10,000
x 0.90 x 0.90 = 8,100 vehicles.
8-hour maximum through traffic = 8,100 x
0.50 = 4,050 vehicles.
1-hour maximum through traffic = 8,100 x
0.10 = 810 vehicles.
24-hour maximum shopping center
traffic = 4,000 x 1.80 = 7,200
vehicles.
8-hour maximum shopping center
traffic = 7,200 x 0.80 = 5,760
vehicles.
1-hour maximum shopping center
traffic = 7,200 x 0.12 = 864
vehicles.
o Total 24-hour maximum traffic =
8,100 + 7,200 = 15,300 vehicles.
» Total 8-hour maximum traffic =
4,050 + 5,760 = 9,810 vehicles.
9 Total 1-hour maximum traffic =
810 + 864 = 1,674.
67
-------
c. Total traffic on a post-Christmas Friday:
24-hour maximum through traffic =
10,000 x 0.90 x 1.10 = 10,000
vehicles.
8-hour maximum through traffic =
10,000 x 0.50 = 5,000 vehicles.
1-hour maximum through traffic =
10,000 x 0.10 = 1,000 vehicles.
24-hour maximum shopping center
traffic = 4,000 x 1.50 = 6,000
vehicles.
8-hour maximum shopping center
traffic = 6,000 x 0.80 = 4,800
vehicles.
« 1-hour maximum shopping center
traffic = 6,000 x 0.12 = 720
vehicles.
Total 24-hour maximum traffic =
10,000 + 6,000 = 16,000 vehicles.
Total 8-hour maximum traffic =
5,000 + 4,800 = 9,800 vehicles.
o Total 1-hour maximum traffic =
1,000 + 720 = 1,720 vehicles.
For this section of roadway, the maximum 24-hour, 8-
hour, and 1-hour volumes are most likely to occur on
the special preschool or spring sale days on a Friday
in April or August.
Level of Service - The term "level of service" is a broadly defined
measure of traffic operating conditions at intersections and continuous
segments of roadways.
Of critical concern to the estimation of vehicle emissions at inter-
sections is the determination of the vehicular operating modes (i.e.,
approach speeds, deceleration, queueing, and acceleration modes).
68
-------
Although a level of service condition at an intersection cannot directly
be used to predict the vehicle operating modes (i.e., a given level of
service does not correspond to a single condition of approach speeds,
deceleration, etc.), the level of service function provides a framework
for estimating these parameters. Therefore, it is necessary to under-
stand the process for determining intersection capacity, service
volumes, and level of service at signalized intersections as part of
the process for estimating operating modes. The level of service
terminology and procedures are outlined in more detail in Appendix G.
The process for estimating operating modes is presented in the following
section of this report.
Methodology for Estimating Vehicular Operating Modes at Intersections
As stated previously, the critical elements of traffic operating con-
ditions at intersections are the vehicular operating modes. The esti-
mation of the vehicular approach and departure speeds, acceleration and
deceleration rates, and queuing characteristics is essential for the
determination of carbon monoxide emissions.
Approach and Departure Speeds - For this study, the approach and
departure speeds were defined as the vehicle speeds experienced outside
of the influence zone of the signalized intersection, (i.e., the free-
flow speeds prior to deceleration and after acceleration at the
signal). The average approach and departure speeds observed at the
intersection of Illinois Route 83 and 22nd Street are presented in
Table 14. Except on the south leg, where approach and departure
speeds are close to constant, there is a discernable pattern of lower
speeds during the morning (7:00 a.m. to 9:00 a.m.) and evening
(4:00 p.m. to 6:00 p.m.) rush hours. Midday speeds are approximately
5 to 10 miles per hour below the existing speed limits (50 miles per
hour on Illinois Route 83 and 40 miles per hour on 22nd Street),
while peak-hour speeds are 15 to 20 miles per hour below the existing
speed limits. Figures 26 and 27 illustrate the relationship between
69
-------
Table 14. OBSERVED APPROACH AND DEPARTURE SPEEDS
Hour ending
8
9
10
11
12
13
14
15
16
17
18
19
Average:
Approach speeds
North leg
southbound
39
36
39
41
38
38
41
38
35
32
32
38
37.3
South leg
northbound
48
48
49
50
50
50
51
49
50
49
49
50
49.6
East leg
we s tb ound
38
39
38
37
35
33
34
32
32
24
26
37
33.3
West leg
eastbound
32
33
41
45
42
39
37
40
42
38
42
44
39.4
Hour ending
8
9
10
11
12
13
14
15
16
17
18
19
Average:
Departure speeds
South leg
southbound
42
44
44
45
45
43
43
44
41
43
43
43
43.3
North leg
northbound
35
37
37
38
36
36
40
37
39
35
40
39
37.4
West leg
westbound
40
42
39
38
36
35
39
36
37
33
33
36
36.4
East leg
eastbound
32
31
36
36
35
35
34
36
35
34
35
37
34.6
70
-------
o o u o
u -; iJ u
- -> J -I
r 5 I i
*- >- i- t-
cc cr -> 3
O Og o
2 Z b) «
3
rH
O
CO
3
CO
w
T3
0)
8UJ
Z
X
uj
o.
O
IIMW) Q33dS 3TOIH3A 30WU3AV
71
-------
o o
ill!
< * < £
o ct o i
a < cc <
a. a a. a.
a m a. u
< Q < Q
O O O O
Ul Ul
J 5 3
O
(U
0)
a,
CO
cu
4J
Vi
rt
a,
cu
-o
a,
a.
to
cd
M
0)
CM
Q)
I
H
(HdVNI 033dS 313IH9A 30VU3AW
72
-------
the average observed approach and departure speeds versus the
average volumes per lane on the intersection legs. Assuming the
single-lane capacity for each leg is constant, a pattern similar
to the relationships between volume and average speeds for rural
higtways indicated in Chapter 3 of reference 4 would be indicated.
The lower overall speeds (5 to 10 miles per hour) on the east and north
legs is most likely caused by disruption from adjacent signalized
intersections. The east leg approach speeds appear to be more signif-
icantly impacted by the higher volumes per lane. This is most likely
due to excessive congestion at the intersection of Illinois Route 83
and 22nd Street, itself, during the peak hours. The posted speed
limit appears to provide the upper boundary for all the approach and
departure speeds as no average single observed speed of more than
5 miles per hour over the posted speed limit was recorded on either
roadway during the study period.
The reasonable estimation of approach and departure speeds for inter-
sections in the vicinity of a proposed indirect source is difficult.
Approaching and departing flow conditions can vary from uninterrupted
(free-flow) conditions to interrupted conditions for numerous reasons.
Speed limits may vary from 55 miles per hour to below 25 miles per hour.
The limitations on vehicular acceleration and deceleration rates also
influence the speeds that can be obtained between consecutive signal-
ized intersections. The influence of decelerating and accelerating
vehicles may be experienced at distances of up to 400 feet upstream
or doxmstream from a signalized intersection. Thus, midblock unin-
terrupted flow conditions (average speeds > 30 miles per hour) are
unlikely to exist if signal spacing is less than 800 feet. Where
signal spacings of 800 feet or greater exist, the approaching and
departing speeds can be approximated by uninterrupted rural conditions,
and the curves relating volume to average speeds as found in Figures
3.41-3.43 of reference 4 should be applicable. However, for road-
ways in the vicinity of an indirect source, the posted speed limit-
should be used in place of the average highway speed.
73
-------
For signal spacings of 800 feet or less, the relationship of V/C to
average speeds for urban and suburban arterials indicated by Figure
10.3 of reference 4 can be used. However, the V/C ratio shown in
the graph reflects the midblock V/C and not the typical controlling
intersection V/C condition.
The speeds found from the various curves presented in reference 4 are
only approximations. Results should be compared with any available
recent studies. Wherever possible, local conditions should be analyzed
and appropriate adjustments made. Field measurements of existing
conditions in the vicinity of a proposed regional shopping center or
at locations having conditions equivalent to future proposed condi-
tions would provide the best measure.
Acceleration and Deceleration Rates - The average acceleration and
deceleration rates observed at the intersection by hour of the day are
shown in Table 15. Peak-hour congestion does not appear to have any
significant effect on these events. The average observed rates for
this study agree well with typical roadway deceleration and accelera-
tion performances recorded in several other traffic engineering
studies. For the purpose of emission estimation, it is suggested
that deceleration rates of between 2.5 and 3.0 mph/sec and acceleration
rates of 2.25 to 2.75 mph/sec be used. More applicable data should
be substituted if available.
Queuing Characteristics - The third critical element of the traffic
operating conditions at signalized intersections is queuing. The
number of vehicles waiting and the average waiting time per queued
vehicle are important parameters for the estimation of emission in-
tensities at intersections because of the high density emission rates
of idling vehicles.
74
-------
Table 15. OBSERVED ACCELERATION AND DECELERATION RATES
Hour ending
8
9
10
11
12
13
14
15
16
17
18
19
Average :
Average deceleration rates (mph/sec)
North leg
southbound
2.5
2.4
2.5
3.1
2.4
2.5
-
2.6
2.6
2.2
2.2
2.0
2.45
South leg
northbound
2.7
2.7
3.0
3.1
2.8
2.9
-
3.0
2.4
3.1
2.9
2.8
2.85
East leg
westbound
3.0
2.6
3.7
3.4
3.1
2.9
-
2.5
2.4
2.1
2.0
3.6
2.85
West leg
eastbound
2.0
2.9
2.8
2.8
2.2
3.1
-
2.9
2.8
3.6
3.2
3.1
2.85
Hour ending
8
9
10
11
12
13
14
15
16
17
18
19
Average:
Average acceleration rates (mph/sec)
South leg
southbound
3.0
2.7
2.7
3.1
2.4
2.4
-
2.4
2.1
2.0
2.2
2.2
2.47
North leg
northbound
3.0
3.1
2.1
2.8
2.2
2.8
-
2.8
3.0
2.5
2.5
1±1
2.70
East leg
eastbound
2.2
2.5
2.8
2.4
2.4
1.9
-
2.2
2.4
1.8
1.9
2.2
2.24
West leg
westbound
2.2
2.5
2.7
2.4
1.9
2.2
.
2.4
2.4
2.7
2.3
lil
2.45
75
-------
The hourly averages of the maximum queue lengths (in vehicles) observed
per signal cycle at the intersection of Illinois Route 83 and 22nd Street
are presented in Table 16. The data indicate an increase in the number
of queued vehicles per cycle as volumes on the approach increase.
Several mathematical models for predicting queue lengths have been
developed. As part of the analysis of queue formation, two different
models were analyzed. The first model investigated is frequently
used in operations research problems, and it is also used by traffic
engineers for the design of toll booth or drive-in bank storage areas.
The model, or the "Toll Booth Formula," assumes a Poisson distribution
of arrivals and an exponential distribution of service time. The
average number of vehicles in the queue is given as:
N =
where: N = expected number of vehicles waiting.
V = expected number of arrivals per unit time (equivalent
to approach demand volume) .
C = expected number of units departing per unit time
(equivalent approach capacity).
The time unit of the volume and capacity variables has no effect on
the number of expected vehicles in the queue as long as the volume
demand to capacity ratio is constant over each unit of time. Using
the observed hourly data on approach volumes, and the hourly capacity
calculations (based on the level of service calculations presented in
Appendices G and H) , the expected number of waiting vehicles was cal-
culated. This calculated queue length was then plotted against the
observed values. These plots are shown in Figure 28. The graphs
indicate the Toll Booth Formula almost consistently underestimates the
queue length by a factor of two or greater. Some inconsistency is
due to the Toll Booth Formula averaging the queue over both the green
and red signal phases. Corrections for this discrepancy would increase
76
-------
Table 16. AVERAGE OBSERVED VEHICLES QUEUED PER SIGNAL CYCLE
Hour
of
day
8
9
10
11
12
13
14
15
16
17
18
19
Number of vehicles queued
North leg
Left-
turn lane
(1)
1.0
5.5
2.0
3.0
1.0
2.0
1.3
3.4
3.0
2.8
2.8
1.0
Through
lanes
(2)
4.0
8.0
7.2
6.3
7.5
10.5
8.3
11.8
16.8
23.3
28.4
11.5
South leg
Left-
turn lane
(1)
6.0
3.0
3.0
3.0
2.0
2.3
1.5
1.5
2.9
3.0
3.0
2.0
Through
lanes
(2)
19.9
13.3
9.0
5.3
7.8
8.4
8.9
10.4
10.9
12.7
10.6
6.5
East leg
Through
lanes
(2)
4.4
5.9
6.6
8.3
12.2
20.6
16.8
10,6
16.5
33.4
33.1
15.0
West leg
Through
lanes
(2)
18.4
24.5
13.2
11.0
16.5
20.8
32.6
1.3.5
13.0
17.2
16.4
10.9
the calculated values by only a factor of between 1.10 and 1.70. This
would not improve the performance of this formula significantly.
The second model tested was a modification of the "Red Time Formula"
which is typically used by traffic engineers to calculate storage
length requirements for intersection approaches. This modified
formula is given by:
N =
(V) (l-G'/GO
CPH
where N = expected number of vehicles queued per signal cycle.
V = expected number of arrivals per hour (hourly volume
demand).
G'/C'
CPH = number of signal cycles per hour.
(2)
green time provided the approach as percent of total
cycle time ( (1-G/C/) is the red time plus amber time).
77
-------
NoRfH APPROACH
5 10
OeSERVED QUEUE LENGTH IN VEHICLES
SOUTH APPROACH
10-v>
CALCULATED QUEUE LEWiTH IN VSHICLEJ
NOTE : TOLL BOOTH FORMULA
Figure 28. Calculated versus observed queue length using tollbooth
formula
78
-------
EAST APPROACH
5 050-f-
2
0 020-
O
5 o 10 - * . ' .
5
10 JO 30
OOSIKVID QUEUE LENGTH IN VEHICLE!
WEST APPROACH
I 10-
o
8 5-
ra 20 30
OBSERVED QUEUE LENGTH IN VEHICLES
MOTE . TOLL OOOTH FORMULA
N.-J*L
CIC V|
Figure 28 (continued).
Calculated versus observed queue length using
tollbooth formula
79
-------
Using the data on hourly volumes and average cycle length observed
at the intersection, and'the calculated G'/C' ratios (see Appendix G
for a discussion of provided G//C/ ratio calculations), the queue
lengths predicted by the Red Time Formula were also plotted against
the observed values. The results are displayed in Figure 29. The
graphs indicate that although the Red Time Formula in most cases
slightly over predicts the queue length, it estimates the queue length
much better than the Toll Booth Formula.
Further refinements of the simple Red Time Formula can easily be made.
A factor to account for a Poisson distribution of arrivals can be
used along with a desired confidence level to determine more accurately
the expected number of arrivals. Also, the (l-C'/C') factor can be
modified to account for first vehicle and overall queue delay times
which result from delayed driver reactions to the green indication.
Several additional studies using these refinements should be consulted
for more detailed information. ' '
Another important aspect of queue formation is the average waiting
time per vehicle in the queue. Table 17 summarizes the waiting times
of vehicles queued at the intersection of Route 83 and 22nd Street.
Table 17. VEHICLE WAITING TIMES AND ESTIMATED RED TIME
Minimum time (seconds)
Maximum time (seconds)
Average time (seconds)
Standard deviation
Average red plus amber
time (estimated)
North leg
Left
turn
2.0
121.0
36.9
28.6
144
Through
3.0
180.0
27.2
27.5
104
South leg
Left
turn
1.0
84.0
36.9
22.6
144
Through
2.0
138.0
30.9
23.0
104
East leg
All
move-
ments
2.0
191.0
47.8
40.6
88
West leg
All
move-
ments
2.0
128.0
40.5
28.3
104
80
-------
NORTH APf-ROACH
M Of
g
;
X
I JOO
I
10 0 30.0 30.0
OSSEBVtO QUEUE LENGTH IH VEHICLE!
40.0 500
SOUTH APPROACH
50.0 -r
200- - *
. 10.0 50.0 300
OBSERVED QUEUE LENGTH IN VEHICLES
WO 50.0
NOTE: RED TIME FORMULA
N _ Hi^i/ci)
CPH
Figure 29. Calculated versus observed queue length using red time
formula
81
-------
EAST APPHOACH
MO T
100 20 0 30 0
O6SERVED QUEUE LENGTH IN VEHICLES
400 500
WEST APPROACH
3
w
O 100-
a
20M)
10 0 20.0 30.0
OBSERVED QUEUE LEKGTH IN VEHICLE*
NOTE: RED TIME FORMULA.
N = -^
CPU
Figure 29 (continued). Calculated versus observed queue length using
red time formula
82
-------
An analysis of queue time versus queue position was inconclusive. The
major east and west through movements experienced significantly more
delay than the north and south through movements. The estimated
average red plus amber times (cycle time minus green time) for the
approaches is also given in Table 17. The average waiting time per
vehicle varies from 25 to 55 percent of the estimated red plus amber
time for the approaches.
The estimation of emission intensities at intersections requires a
detailed evaluation of all vehicle operating modes. The approach
speeds, being a function of the midblock V/C ratio, are sensitive to
the capacity of the roadways. Roadway width and surging characteristics
are key determinants of the capacity of a roadway. Increased roadway
widths (number of lanes) can significantly reduce the V/C ratio and
thus allow for higher average speeds. However, for most urban and
suburban conditions, increases beyond level of service C will not
generally yield significantly increased average speeds. In many cases,
the posted speed limit will restrict the maximum speeds.
The acceleration, deceleration, and queuing characteristics are related
to the intersection control. The total number of vehicles having to
stop at a signalized intersection depends on the arrival pattern of the
traffic and the G//C/ ratio provided by the signal control. Assuming
an uncontrolled (random) arrival rate, the number of vehicles queued
during an hour is approximately equal to the volume demand times the
hourly percent cycle time given to red and amber time (or V x (1-G//C/).
As the green time per cycle for an approach increases, the number of
vehicles queued decreases. However, the green time given to one approach
is usually limited by the green time required by an opposing leg. In-
creasing the G//C/ ratio will thus have a limited effect in reducing
the queuing at the intersection as a whole, although queue lengths
could be "traded" among approaches.
83
-------
A more promising measure to reduce queuing is to modify the vehicle
arrival pattern. This can be done by progressive signal systems. A
progressive signal system times the release of traffic at signal-con-
trolled intersections so that vehicles arrive at succeeding intersec-
tions during the green phase, provided they travel at the proper speed.
Such a coordinated signal system will maximize the use of green time
for the direction of travel being progressed, and it will reduce the
vehicle start-up and queue delays. The successive intersections must
be free of queues when the progressed vehicles arrive.
To determine the effect of signal progression on queuing at an inter-
section, the designer must provide an estimate of the percent of total
approach traffic which has been progressed. The percent of vehicles
progressed is essentially the progression bandwidth divided by the
cycle length, and the bandwidth is the width (seconds) of the "window"
of green in a given direction which allows the vehicles to proceed
unopposed through the succeeding intersection. This information is
generally available from the analysis of the traffic distribution at a
regional center. This percent/100 can be designated as P, the pro-
gression factor. The through traffic adjacent to a shopping center
will often be progressed since it represents the majority of traffic
flow, and the value of P may vary from 0.40 to 0.70. Assuming this
platooned traffic proceeds through the intersection with only minor
disruptions due to turning movements, the emissions generated by the
progressed traffic can be estimated by the cruise emission strength.
The volume of progressed traffic is simply V = P (V total) and the
speed is the design progression speed. Techniques to model the effects
of a progression on emissions have been developed.
The remaining nonprogressed traffic (V-V ) should be analyzed according
to the following procedures developed for determining the operating cha-
racteristics of vehicles at intersections.
84
-------
1, Determine maximum 8-hour and 1-hour volumes by approach
according to procedures outlined in Section IV.
2. Determine the approach speed by calculating the midblock
V/C ratio and using the appropriate chart relating V/C
to average speeds,, Capacity should be based on analysis
of a continuous roadway section using factors for road-
way width and trucks.
3. Calculate the provided G' /C> ratio for each approach ac-
cording to the procedure described in Appendix G. The
total (G + Y)/C ratio for all approaches should be
< 1,00 at level of service D for worst conditions.
(Y represents amber time).
40 The number of vehicles decelerating, accelerating and
idling during a given hour (by approach) is calculated
by NIJQ = V x (1-G'/C')« The average number of vehicles
queued per cycle length is given by the Red Time Formula.
5, The volume of vehicles passing through the intersection
during an hour (at a constant speed equal to approach
speeds) is given by V-N^.
The cycle length for a traffic actuated signal varies with demand simi-
larly to the G/C ratio. Typical cycle lengths can vary from 60 seconds
to 180 seconds for arterial roads. At Oakbrook Shopping Center, the
cycle length at Route 83 and 22nd Street intersection varied from 140 to
210 seconds throughout the day. Table 18 indicates average cycle lengths
observed at Oakbrook Shopping Center by hour of the day.
The determination of cycle length (existing or proposed) is not a diffi-
cult process. The estimation of the existing cycle length required only
a brief field observation of the intersection during peak conditions,
In predicting future conditions, the designer usually selects the optimal
cycle lengths based on the approach speeds and the phasing necessary to
accommodate traffic at the desired level of service. Several methods for
determining optimal cycle lengths for fixed time or actuated signals are
available. \
' \
Cycle lengths for fixed-time signals are limited between 60 and 120
seconds due to equipment restrictions. Good estimates would be 60-,
85
-------
Table 18. OBSERVED CYCLE LENGTH - ROUTE 83 AND
22ND STREET INTERSECTION
Date
6/13/74
6/13/74
6/13/74
6/13/74
6/13/74
6/13/74
6/17/74
6/17/74
6/17/74
6/17/74
6/17/74
6/17/74
Day
Thursday
Thursday
Thursday
Thursday
Thursday
Thursday
Monday
Monday
Monday
Monday
Monday
Monday
Hour of
day
8
9
10
11
12
13
14
15
16
17
18
19
Average cycle
length (sees)
174
170
133
147
152
160
191
181
177
179
174
166
Cycles/
hour
20.7
21.2
27.1
24.5
*
23.7
22.1
18.8
19.9
20.3
20.1
20.7
21.7
75-, or 90-second cycle lengths for fixed time, depending upon the
progressive system (if any). Fixed-time signals are usually found only
in urban conditions where the signal coordination is essential.
Actuated signals are usually found in suburban and rural conditions,
where most signals are isolated, due to the great expense to coordinate
actuated signals. Cycle lengths for actuated equipment are highly
variable. However, cycle lengths of 90 or 120 seconds would be good
estimates. In all cases, local data should take precedence over these
estimates.
86
-------
SECTION V
MODEL DEVELOPMENT AND EVALUATION
This section describes a technique for estimating emission profiles at
intersections. Estimated profiles are then used as inputs to the HIWAY
model for comparison of calculated and observed carbon monoxide con-
centrations. A discussion of area source evaluation follows this. The
section concludes with the presentation of a methodology for estimating
concentrations near intersections.
ESTIMATION OF EMISSION PROFILES FROM QUEUING VEHICLES
A signalized intersection resolves conflicts between opposing streams
of traffic by alternately "blocking" and then allowing free passage of
vehicles on intersecting approaches. This feature, plus the relatively
fine detail in emission strength variations which must be known to
assess nearby concentrations adequately, imply that the widely used
"average route speed" method of computing emission strengths is not
suitable in this case. A detailed knowledge must be provided of the
emission variations from a vehicle undergoing mode changes from cruise
through deceleration to idle, and acceleration back to cruise. The
recentl;
detail.
9
recently developed "Modal Analysis Model" supplies this emission
The Modal Analysis Model computes total emissions of hydrocarbons, car-
bon monoxide, and oxides of nitrogen from a user-specified vehicle mix
through 1971. Any desired driving sequence falling within the range of
model applicability may be used. The model was modified for this study
87
-------
to calculate emissions at equal length intervals for a given "approach"
cruise speed, rate of deceleration, rate of acceleration, and "departure"
speed for an "average" vehicle representing a 1974 low altitude mix. A
1974 mix was obtained by calculating emissions for a 1971 mix using
Table 3.1.2.7 of AP-4210 and multiplying the results by the ratio of 1974
to 1971 test results. For carbon monoxide this ratio is 39/47. The
length interval was chosen as 8 meters, since this is the average distance
occupied by queued vehicles (front bumper to front bumper) used in the pro-
18
posed interim guidelines. Figure 30 shows the carbon monoxide emission .
profile calculated by the modified Modal Analysis Model for one vehicle
decelerating from 35 mph/sec at -2.75 mph/sec and accelerating from 0 back
to 35 mph at 2.50 mph/sec with no idle time. These values of speed, decel-
eration, and acceleration are representative of the values observed at
Oakbrook as described in Section IV. The units on the abscissa are meters
upstream (negative values) and downstream (positive values) from the inter-
section stop line which, for the single vehicle depicted here, is approxi-
mately the location of the front bumper when the vehicle is stopped. The
vehicle moves from left to right. The ordinate units are grams/8 meters -
time is not included here, but it will be later in the discussion of queu-
ing and signal cycle lengths. All that is of interest at this point is
the mass of CO emitted in each 8 meter length interval by a stopping and
starting (but not idling) vehicle.
The modeling of traffic flow requires simplifying assumptions to keep the
analysis tractable, and an idealized model of the behavior of queuing ve-
hicles was used in calculating emission profiles at intersections. All
vehicles which stop are assumed to decelerate at a constant rate from a
constant cruise speed. They queue up with each vehicle occupying an
8 meter interval, and then they accelerate at a constant rate back to
cruise speed. The emission profile is calculated by adding the emissions
from each vehicle in each interval according to the vehicle's speed and .
mode in the interval. It consists essentially of adding up 10 of the
curves shown in Figure 30, with each successive curve displaced -8 meters
from the previous curve; i.e., 8 meters upstream, and then subtracting out
the cruise emission component. Figure 31 shows the excess emission profile
88
-------
CN
fx
CO
^4
C4
O
/--N
5-1
CD
4J
CU
g
x_/
w
H
t-1
Pu
O
H
en
J2^
O
H
H
a
w
en
w
H
H
e
o
iJ
to
r<
JUI
Cd
^
O
o
o
r.°
CO
t-l
o
r-t
X
CJ
C
o
^
p
CJ
r 1
i-l
O
4J
a o
rQ -M
CO
60 CO
G -r;)
4J CU
cd
jj a)
a) i-i
rH rC3
-------
-144 -96 -48 0 48 96
DISTANCE FROM THE INTERSECTION STOP LINE (meters)
\
Figure 31. Profile and step function approximation of excess emis-
sions for a queue of 10 vehicles
90
-------
due to stopping and starting only for a queue of 10 vehicles having approach
and departure speeds both equal to 35 inph, deceleration of -2.75 mph/sec,
and acceleration of 2.50 raph/sec. Note that the scales on the ordinate and
the abscissa are different from those of Figure 30. The emission profile
pictured in Figure 31 does not include idle or cruise emissions, but only
the emissions in excess of cruise emissions occurring for stops and starts.
The step function also shown on Figure 31 depicts the approximation to the
profile of excess emissions. The amplitude equals the average emissions
over the queue length of 10 vehicles, or 4.5 grams. This average amplitude
is 79 percent of the peak value of 5.7 grams of carbon monoxide, and the
area contained within the step function is 56 percent of the total excess
emissions attributable to deceleration and acceleration.
It is important to note that the excess emissions described here are re-
lated to a spatial scale rather than to a temporal scale directly. They
arise from two effects. The first is an increase in the calculated emis-
sion rate, during both deceleration and acceleration compared to the emis-
sion rate at cruise speed. The second is an increase in the time for a
vehicle to travel 8 meters during deceleration and acceleration compared
to the time to travel 8 meters at cruise speed. The emission profiles
show the product of these too effects.
The method of constructing the emission profile for the 10 queuing vehicles
and the calculation of the amplitude of the step function approximation is
further explained by reference to Table 19. This table lists the emissions
calculated by the Modal Model from each of the 10 vehicles in each of the
8 meter scale lengths through which the vehicles decelerate and accelerate.
The distances from the intersection stop line which are listed represent
the mid-points of the scale lengths, so that the first queuing vehicle
occupies the scale length having its mid-point -4 meters from the inter-
section stop line." Cruise emissions are 0.119 grams/8 meters.
Looking at the column for vehicle number 1 (column 11), it is seen that
this vehicle is at cruise speed until it reaches the scale length with mid-
point -108 meters from the intersection stop line, then it begins to
91
-------
I
c
i
o
M
H
oO(^^?vDoeNia3*^o^(^r--OOO«-<^yocoOcGOCNC^ooOcO^jri^.o.u^c*locT\vJ3CsicO'-JOiOr^ov'OeNO
X-»^ 60 oOOOOOOOOOOOO^C>IOJr4r-4,-4OOOO
u
u
M
ri
fn
§
PM
I
en
41 O E
W C CO
^ o --.
3 O. E
.H o 'E
O «> 6
"e >2
oooooooooooooooooooooooooooooooooooooo
OOOOOOOOOOOOOOOOOOOOOOOi-(OOOOOOOOOOOOOO
o
§
H
o
CO
H
o
OOOOOOOOOOOOOOOOOOOOOOfHOOOOOOOOOOOOOOO
OOOOOOOOOOOOOOOOOOOOOrHOOOOOOOOOOOOOOOO.
oooooooooooooooooooo«-«ooooooooooooooooo
o
u
fn
&
ooooooooooooooooooo^oooooooooooooooooo
OOOOOOOOOOOOOCSOOOO^-tOOOOOOOOOOOOOOOOOOO
ooooooooooooooooo^oooooooooooooooooooo
-------
decelerate and the mass emissions per 8 meters increase. Acceleration emis-
sions from this vehicle begin in the scale length with mid-point -4 meters;
cruising speed is attained again in the scale length having its mid-point at
108 meters. Looking now at the column for vehicle number 2, it is seen that
the emissions are displaced one scale length upstream (negative direction)
from the intersection compared to vehicle 1 because this vehicle must begin
decelerating one scale length earlier to come to a stop in the scale length
immediately behind vehicle 1. Likewise, vehicle 3 begins decelerating one
scale length earlier than vehicle 2 and so on for the remaining vehicles.
Each row represents a scale length and each column gives the emissions
from each vehicle in each row, or scale length. Adding across each row
gives the total emissions of all vehicles in each scale length. These
total emissions are presented in the twelfth column. The next column is
simply the total cruise component from all 10 vehicles for each scale
length. The final column is obtained by subtracting the cruise component
from the total emissions, and it thus represents the excess emissions due
to deceleration and acceleration without idle emissions or the emissions
which would have been obtained if all vehicles had remained at cruise
speed. These are the emissions represented in Figure 31. On this column
of excess emissions are shown the 10 emissions from the 10 queue posi-
tions which are used to calculate the average emissions for the step
function approximation to the emission profile.
Table 20, column 3, lists the average excess emissions occurring over the
distance occupied by queues of 5, 10, ..., and 30 vehicles for approach
and departure cruising speeds of 15, 20, ,.., and 50 mph. The fourth
column lists the standard deviation for each of the average excess emis-
sion values to indicate the range of emission values which are used to
compute the average. For example, at the far right of Table 19 are shown
the emission values used to calculate the average va.lue of 4,504 grams/
8 meters. These can be compared with the information on Table 20 which
lists, for a cruise speed of 35 mph and a queue of 10 vehicles, an average
excess emission value of 4.504 grams/8 meters with a standard deviation of
1.077 grams/8 meters. The fifth column lists the percent of the total
excess emissions (defined by the entire excess emission profile) contained
93
-------
Table 20. EMISSION VALUES FOR USE IN APPROXIMATING
EMISSION PROFILES
DECELERATION = 2.75 mph/sec
ACCELERATION =2.50 mph/sec
1
Speed
(raph)
15
20
25
30
35
40
45
50
2
Queue length
(vehicles)
5
10
15
20
25
30
5
10
15
20
25
30
5
10
15
20
25
30
5
10
15
20
25
30
5
10
15
20
25
30
5
10
15
20
25
30
5
10
15
20
25
30
5
10
15
20
25
30
3
Average excess
emissions
(gtn/8ra)
2.297
2.436
2.482
2.505
2.519
2.528
2.860
3.282
3.422
3.492
3.535
3.563
3.066
3.984
4.315
4.481
4.581
4.647
3.163
4.389
5.061
5.397
5.599
5.733
3.221
4.504
5.541
6.154
6.522
6.767
3.253
4.569
5.679
6.645
7.265
7.678
3.269
4.601
5.727
6.773
7.719
8.378
3.273
4.610
5.740
6.790
7.806
8.764
4
Standard deviation
-------
within the step function approximation. Referring again to Table 19,
the last column, Excess Emissions, totals to 79,930 grams. Of this,
45.040 grams or 56 percent is accounted for over the 10 queue positions.
This percent is basically a function of the queue length and the distance
required to stop and start. The greater the ratio of the queue length to
the stop and start distance the greater will be the percent of the total
excess emissions contained within the step function. The next column is
included to show the total excess emissions (grams) per vehicle stopping
and starting from each of the cruise speeds in column 1, and the final
column indicates the cruise emissions (grams/8 meters) for each of the
cruise speeds.
Emissions from cruise and idle modes must be added to those due to stop-
ping and starting to develop the full emission profile. Cruise emissions
are included simply by adding the cruise emissions from each vehicle in
each 8 meter interval. Figure 32 shows the result of adding cruise emis-
sions to the emission profile and to the step function approximation for
a queue of 10 vehicles. The profile approximation now contains 68 per-
cent of the total emissions, and the approximated peak of 5.69 grams is
83 percent of the peak of 6.90 grams.
The signal phases and phase times are needed to calculate idle emissions
and mean expected queue lengths. The method for finding the mean queue
length will be discussed first; idle emissions are found by a simple
calculation following this.
Let the length of the red (plus amber) phase of a traffic signal be R,
let the vehicle arrival rate be q, let N be the number of vehicles queued
at the end of the red phase, and M be the number waiting at the beginning
of the red phase. Then, assuming random arrivals and no service during
12
R, the distribution of the quantity N-M is
(qR)k e"qR , k=0,l,... (3)
k!
where k equals N-M.
95
-------
7r-
-144 -96 -48 0 48
DISTANCE FROM THE INTERSECTION STOP LINE (meters)
96
Figure 32. Emission profile and step function approximation for excess
and cruise emissions for a queue of 10 vehicles.
96
-------
This is a Poisson distribution with mean qR. Making the assumption that
M = 0, the mean queue length per cycle is
N = q(veh/sec) R (sec/cycle) (4)
This is the origin of the Red Time Formula described earlier in
this report.
This formula neglects the possibility of additional queuing during the
green phase before the initial queue clears the intersection. This can
be accounted for as follows to provide a conservative estimate of the
total queue length during a signal cycle. Given that N vehicles are
queued at the beginning of the green phase, the distribution of the
total number of vehicles, N', which will queue up during the red and
green phases before the queue disappears, is given by^-2
.. -N'p ,.., .N'-N
N e ^ (N'p) M/ - M
f " , N' - N.,
iN (N'-N)!
The mean of this distribution is
I/ - . (6)
The parameter p is the traffic intensity, which equals the mean arrival
rate, q, divided by the mean service rate, s, during the green phase.
Since N = qR, the mean total number of vehicles queued during a cycle
is given by
The service rate, s (veh/sec) during green, is nearly equivalent to the
denominator used to compute G/C as described in Appendix G. (Actually
it will be slightly less, since there is some delay associated with get-
ting the queue in motion. This leads to a tendency to underestimate
97
-------
N'.) Hie volume parameter q(veh/sec) is the actual volume using the
roadway, and it is equivalent to the numerator used to calculate G/C.
Hence at level of service E (capacity), 1-G/C can be used for 1-q/s.
The length of the red (plus amber) phase, R, is given by R(seconds) -
(l-G'/C') Cycle Length (seconds). The quantity G' /C' is the actual green
time to cycle length ratio provided at an approach to an intersection,
as opposed to G/G, which is the green time to cycle length ratio
required to accommodate traffic on an approach. G'/C7 is computed for
an individual approach by dividing G/C for that approach by the sum of
the G/C for all approaches plus the amber time of the signal cycle:
G'/C' = (G/C) ()f (8)
f\t V-
where r- is the sum of the G/C for all approaches plus the amber time
(j
for the signal cycle. This calculation for demand actuated signals is
presented in detail in Appendix G. Thus, the mean total queue length
can be computed by
-/ (V veh/hr) (1-G//CQ (cycle length)
N = (3600 sec/hr) (1-G/C)
Including the amber time with the red time as l-G'/C' is a conservative
estimate which assumes nonagressive driver behavior.
s
This particular formulation for N' applies to demand actuated traffic
signals, for which the G/C calculations described in Appendix G must be
made to determine the signal phase times. For a fixed- time signal, G/C
will be constant for an approach, and this is used in place of G'/C'
used above to compute the length of the red (plus amber) phase. For
this case
-, (V veh/hr) (1-G/C) (cycle length)
green
98
,_,,.-. /, N , V veh/hr
(3600 sec/hr) 1 - - - prr - -
v ' I C veh/hr of
-------
As an example, consider an approach to an intersection with a volume of
G4-Y
215 veh/hr, G/C equal to 0.18, a cycle length of 180 seconds, ^r of
C
0.86, and G'/C7 of 0.18/0.86, or 0.21. The mean total queue length
per cycle is then
- _ (215) (1-0.21) (180)
N ~ (3600) (1-0.18)
= 10 veh/cycle
The length of the red (plus amber) phase for this example is 142 seconds.
On the average, a stopped vehicle waits 1/2 the red phase, or 71 seconds
for this case. The idle emission rate of carbon monoxide calculated by
the Modal Analysis Model is 0.234 gm/sec. This is assumed to occur in
each of the queue positions an average of 71 out of every 180 seconds,
that is, (1 - GVCO/2, or 0.39 of the time. Hence the idle emissions
average 0.092 gm/sec for each queue position for this example. This
tends to underestimate emissions in the lead queue positions, where
vehicles wait longer than 1/2 R, and to overestimate emissions for the
rear positions.
The HIWAY Model calls for emissions in units of grams/m-sec, and now
that volume and signal parameters have been specified, these will be
calculated for approach and departure speeds of 35 mph, deceleration
of -2.75 mph/sec, and acceleration of 2.50 mph/sec. Since N7 = 10
veh/cycle, the excess emissions due only to stopping and starting are
4.504 gm/8m/cycle, or 0.563 gm/m/cycle. But the signal cycle is 180
sec, so this becomes 0.563/180 = 0.00313 gm/m-sec due to stopping and
starting. The volume of 215 veh/hr equals 10.75 veh/cycle from which
cruise emissions must be added. The cruise emission rate is 0.119
gm/8m (Table 20), or
(0.119 sm) (10.75 veh/cycle) _ _ nnnRQ 0 ,
* ,- " ff.^n 7 :t * - U.UUUoy gm/m-sec
(8m) (180 sec/cycle) **
99
-------
cruise emissions. The idle emissions were found earlier to be 0.092
gm/sec for each 8 meter queue position, so the idle contribution is
0.01150 gm/m-sec from idle. The approximation of the emission profile
is then
0.00313 gm/m-sec from stopping and starting
0.00089 gm/m-sec from cruise
0.01150 gm/m-sec from idle
or 0.01552 gm/m-sec over the 10 queue positions, and 0.00089
gm/m-sec elsewhere. The approximated peak is 95 percent of the peak
calculated using the Modal Analysis Model, and the total approximated
emissions are -94 percent of the total. This arises from the large con-
tribution by idle emissions which are computed in the same manner for
both cases.
It is suggested that the following technique be used to estimate emis-
sion profiles from queuing vehicles using the factors presented in
Table 20.
1. Identify the parameters necessary for calculating the
expected mean total queue length. These parameters are
a. V = hourly demand volume
b. Cycle length
c. G/C = required G/C ratio (see Appendix G)
d. G//C/ = actual G/C ratio provided
or if the signal is fixed time,
c. G//C/ = actual G/C ratio provided
d. Capacity per hour of green
2. Compute the expected mean total queue length using
equation 9 for a demand actuated signal or equation 10
for a fixed time signal.
3. If the queue length is less than 5, assume it equals 5.
If it is less than a multiple of 5 plus 3, round down
to a multiple of 5, otherwise round up. Thus, both 8
and 12 would become 10. If average emission factors
are known for the exact queue length, these should be
used and it would not be necessary to round off the
queue length to a multiple of 5.
100
-------
4. Identify the approach and departure speeds. If they
are unequal, assume both equal the departure speed.
If the average emission factors are known for the
given approach and departure speed combination,
these should be used and it would not be necessary
to make the assumption that both equal the departure
speed.
5. Using Table 20 find the mean emissions per 8 meters
due to stopping and starting for the queue length-
speed combination.
6. Calculate the emission strength (gm/m-sec) over the
distance occupied by the queue by adding:
^mean stopping and starting emissions gm/8m) .
(8m) (cycle length sec)
(cruise emissions gm/8m) (V yeh/hr) (cycle length sec)
(8m) (3600 sec/hr)
(idle emission rate gm/sec) (1/2 the length of the red
(8m)
phase sec)
= emission strength over the queue length (gm/m-sec)
7. Assume that only the cruise speed emission strength exists
upstream and downstream of the queue (excluding the center
of the intersection).
8. After the emission strengths are found over the queue
lengths for all approaches, average them and assume this
emission strength for lanes in the center of the inter-
section.
Figures 31 and 32 show that the profile actually maintains high emis-
sion values downstream of the intersection. Step 8 tends to include
these high values through the intersection, although further down-
stream they are not included. This discrepancy becomes more pro-
nounced at higher speeds when the ratio of the deceleration-accelera-
tion distance to the queue length is increased. This is counteracted
somewhat by the approximate profile being higher at the upstream end
of the queue.
101
-------
COMPARISON OF OBSERVED AND CALCULATED CONCENTRATIONS
The Modal Analysis Model and the EPA HIWAY Model are designed to esti-
mate emissions and concentrations, respectively. To test the compati-
bility of the two models in translating traffic and meteorological
parameters into concentrations of carbon monoxide, a composite model
was used to predict concentrations at Oakbrook for comparison with
observed values.
An exact analysis would include emission strengths calculated for each
8-meter section of roadway, application of the HIWAY Model to each 8-
meter section, and addition of the individual section contributions to
find the calculated concentration at a receptor. An exact analysis,
however, is quite consuming of both manpower and computer time, and
the "improvement" in calculated values is probably of marginal benefit.
Because of this, and because it was necessary to evaluate the effective-
ness of the emission profile approximations as inputs-to concentration
estimates, the technique described previously for approximating emission
profiles was used to generate inputs to the HIWAY Model.
Twelve cases were chosen for analysis based on relatively low wind speed,
a wind angle suitable for defining concentrations upwind and downwind of
the intersection of Route 83 and 22nd Street, and completeness of the
input data set for the hour under study. In four of these cases the
wind was from the northeast quadrant, and concentrations were calculated
for the monitor in the southwest quadrant (station 162). In the other
eight cases the wind direction was reversed, and concentrations were
calculated for each of the three monitors in the northeast quadrant
(stations 13, 14, and 15). Missing data occurred for one case at
station 13 so that there are a total of 27 comparisons of observed and
calculated values. Concentrations recorded by the Ecolyzer were used
for the southwest location unless it was not operating for the partic-
ular hour under study. In these cases the average of the NDIR values
(stations 161 and 163) was used.
102
-------
Table 21 displays the dates, hours, and applicable meteorological con-
ditions chosen for the comparisons. The traffic parameters are listed
in Appendix H for Level of Service E, The higher G/C and G//C' for each
Ql Y
phase was used (where Gf /Cf = G/C « -~r-~). The volumes were taken from
C
the tables of V/C. The signal cycle lengths are given in Table 22.
Table 21 also shows the calculated and observed concentrations for the
periods studied, where the observed concentrations equal the difference
between downwind and upwind readings. Two sets of calculated concentra-
tions are given: (1) those based on an initial vertical diffusion param-
eter °"zo = 1.5 m, and (2) those based on °"zo = 3,0 m. The average of
all calculated concentrations is 3.5 ppm versus 3.8 ppm for the average
observed with o~zo = 1.5 m. The correlation coefficient is r = 0.34,
which indicates less than a 10 percent probability that the linear rela-
tionship between calculated and observed values has occurred by chance.
The correlation coefficient obtained using o"zo = 3,0. m is r = 0.29. Fig-
ure 33 is a plot of the data pairs. Concentric circles indicate more
than one point. Twenty-two calculated values are within a. factor of
two of those observed, while five vary by more than a factor of two.
Six of the calculated values agree exactly with the observed values.
The good agreement of the mean calculated and observed concentrations
is encouraging but there is a tendency for the composite model to under-
predict. Fifteen of the twenty-seven calculated values are less than
those observed, while only six are greater.
When the values are normalized for wind speed the mean calculated XU
is 11.7 ppm-m/sec compared to 13.7 ppm-m/sec observed. The correlation
coefficient is 0.44. This is significant at the 2 percent level, and
more of the variance is explained. The linear regression equation is
XU calculated = 8.2 + 0.25XU observed (13)
Predicted concentrations tend to be overestimated at low wind speeds and
underestimated at high wind speeds. The crossover occurs at wind speeds of
approximately 3.5 m/sec.
103
-------
^
§
s
H
M
W
O
I
O
CO
t3
g
O
&
o
t>
§
M
I
i
^^
s
S
a
S
OJ
r-*
U
U
O.
w
w
0
.U
D.
41
a
(4
O
JJ
ft.
o
u
ctf
8
ft.
0)
£
D
C
"-1
t £
o «*
,;?
SS
.-a
'.7
*-4 ft,
V &
jsl
.7
35
".7
5&
i!
<~l ^!
t-4 O,
sa
i!
o ^^
Stability
n o
o o
o in
0,-^
C s->
O a
J U
S3
3
O
X
«*> C* M M r-4 ft C4
«-« o-
_ , , X , ,
^ C*l fO *O ^ W C4
« ^ « «
-««*
(>* cO "^ *A
w a Q n 0 u U a « « c,
-.««'^^o««««o
ooooooooooo
IN CM CM N N C4 N
OOOOOOOOOOO
ooooooooooo
It.lflltllll
-
ot
«
-
o o 3
C1 r< «3
CO CO
rt -!
in act <<%
rt fH o
« Ix
N
8
1
104
-------
E
a
a
z 6
O
I s
Z
UJ
U
§ «
u
u
u
234567
OBSERVED CONCENTRATION, ppm
8
Figure 33. Calculated versus observed concentrations of carbon
monoxide .
105
-------
Table 22. CYCLE LENGTHS AT THE INTERSECTION OF
ROUTE 83 AND 22nd STREET '
Hour ending
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
Cycle length
(sec)
174
170
133
147
152
163
191
181
177
179
174
166
EVALUATION OF AREA SOURCE MODEL
18
Evaluation of the area source model of the interim guidelines requires
the calculation of the carbon monoxide concentration at a receptor site
based upon the location of the receptor with respect to the area source,
the size of the area source, and its emission density. These calculated
values are then compared with observed carbon monoxide concentrations
to determine the effectiveness of the model.
A carbon monoxide monitoring study conducted at the Oakbrook Shopping
Center for a 3-week period in December 1973, through January, 1974, was
used for the evaluation. Traffic volumes, base running times, area
source size and receptor locations are known from this study so that
concentrations can be calculated for comparison with the carbon monoxide
concentrations actually measured at the receptors.
106
-------
Figure 34 shows the receptor locations, the layout of the buildings,
the parking areas, the entrances and exits, and the ring road serving
the interior of the shopping center. The monitor at site 3 was moved
to site 3-A during the study because of difficulties with electrical
service. The (monitor was shut down at site 3 on December 31, and com-
menced operation at site 3-A on January 4.
\
The parking areas between two receptor sites were considered as area
sources for this evaluation, as shown in Figure 34. This meant that
one receptor was at the upwind edge of the area source and the second
was at the downwind edge. If the wind was in the proper direction,
the difference in carbon monoxide concentration was due solely to the
area sources between the receptors.
A 30 wind sector was used in the evaluation. A line was drawn between
the two receptors and the closest 30 wind sector (the wind direction
was recorded in 10 increments during the study) was used. For sim-
plicity, Figure 34 shows area sources between sites 2 and 3 and also
between sites 3-A and 4. Data between sites 2 and 3-A and sites 3 and 4
were also considered, but this is not shown on Figure 34.
Appendix Table A-6 lists the observed carbon monoxide concentrations at the
upwind and downwind receptors and the concentration difference between
the receptors for each area source. A summary of these data is shown
in. Table 23. Ibis table includes only hours when the shopping center
was open. The results show that 30 percent of the observations yielded
no change in concentration due to the area source and 30 percent showed
a decrease in die concentration. This is probably due to the influence
of the ring road. The remaining 40 percent show an increase in concen-
tration downwind of the area source.
107
-------
Figure 34. Locations of receptors and area sources
108
-------
Table 23. AREA SOURCE UPWIND - DOWNWIND CO CONCENTRATION DIFFERENCES
Area source
between
receptors
1 and 4
3 and 4
3A and 4
1 and 2
2 and 3
2 and 3A
Total
Percent of
all cases
Downwind
CO concentration
less than
upwind
(number of hours)
3
4
0
6
6
3
22
28.6
No difference
in
CO concentration
(number of hours)
3
5
1
5
9
0
23
29.9
Downwind
CO concentration
greater than
upwind
(number of hours)
5
8
2
5
12
0
32
41.6
OUTLINE OF A "QUICK ESTIMATION" TECHNIQUE
For nearby receptors, examination of the actual length of roadway which
contributes most of the pollution concentration shows the emission pro-
file approximation to be reasonably adequate. Assuming a normal dis-
tribution of downwind pollutant concentrations in the horizontal and
vertical directions, approximately 95 percent of the horizontal dis-
tribution lies within + 2 a . If the receptor is taken to be a point
source, and the roadway is taken as a line along which concentrations
are to be calculated, then 95 percent of the total contribution of the
point source to the receptor line lies along the line within + 2 a of
the intercept of the point source plume axis with the line receptor.
If now the roadway is the source and the point becomes the receptor,
95 percent of the total line source contribution will lie within the
same + 2 a distance. The HIWAY model reduces the length of a line
source to approximately + 4 a to reduce computation time. This dis-
- y
tance includes essentially all of the line source contribution to concen-
trations at a receptor point.
109
-------
The method used to calculate the + 2 a line source distances is explained
. y
with reference to Figure 35. The coordinate axes are noted_on the Figure.
The X axis lies along the roadway, and the X' axis lies along the wind
direction at an angle 0 to the X axis. Numerical subscripts indicate a
distance, while alphabetic subscripts refer to positions on the X and
X7 axes. The receptor is located at a perpendicular distance y from the
origin of the X axis. The horizontal dispersion parameter is a function
of the downwind distance, x7 , of the form a (x7) = a x7 , where a and b
are functions of atmospheric stability and the roughness of the area.
The lengths x.. and x? are the projections on the line source of the two
distances 2cr (x') and 2cr (x72) which lie perpendicular to the wind
direction. The sum of x, and x» is then the length of the line source
contributing 95 percent of the total concentration at the receptor. These
are found from the relations:
2o (x7
X2 ' -
The distances x7., and x72 are found from
- xi cos e>
+ x cos 0. (17)
sin d 2.
For Pasquill-Gifford Stability Class D, the parameters a and b are 0.13
13
and 0.903. An initial dispersion coefficient a =3 meters is assumed
yo
on roadways because of the mixing caused by moving traffic. This leads
to the addition of 32 meters to the downwind distance used to compute a :
y
110
-------
ti
o
1-1
u
o
r-l
0)
u
M
O
CO
0)
(U
U
co
rl
"0
CO
H
Q
CO
<0
M
60
rl
111
-------
c = a (32) = 3 meters.
yo yoN
The roadway lengths can now be calculated from:
°'903
(2) (0.13)
xi '
(2) (0.13) (-rj-g- + x cos B + 32)°'903
O 1. II ^ £. ^ ^ v
and x2 = - - . (19)
Values of x.. and x- were found by Newton's method for y = 10, 15, ..., 50
meters and 0 = 10, 20, ..., 90 degrees for stability class D. The
results are listed in Table 24, where x and x, are the distances from
a b
the origin as shown on Figure 35. Also listed are the total distance
x, - x and the equivalent queue length N.
D 3
Table 24 shows that except for wind angles less than 20 degrees, the
maximum length of roadway contributing 95 percent to a receptor not
more than 50 meters away is no more than 192 meters. This is equivalent
to a 24-vehicle queue assuming each vehicle occupies at least 8 meters.
For wind angles of 30 degrees or greater, a roadway length approximately
equal to a 10-vehicle queue will contribute 95 percent.
Concentrations due to an infinite line source at receptor locations
from 10 to 50 meters were calculated from
(20)
Jf Q exp -
V
H2 1
2 a 2 (y/sin 6)
_ z j
which is equivalent to equation 9 of reference 14. These calculations
were made using unit wind speed and source strength, a ground level
source, a receptor height of 2.0 meters, and Stability Class D. Table 25
lists the results. At a given receptor distance the highest concentra-
tions occur with small wind angles to a single roadway. For an
112
-------
e
CO
o
CM
+ 1
&
M
Q
W
h4
g
H
CO
8
H
co
z
g
I
cS
s
^
§
(U
co r^* i i *^
cMcococo-sT^inin
rHinO in vo o> o o*\
r*^ o r^ in -J" co co rH
\o r^ in r^* co o^ O «H
rH rH
1 1 1 1 1 1 1 1
o
(H
\
omomoinoin
rHrHCMCMCOCOvl-vt
r-
CO
m
vo
CO
i
CJ\
1
r-
O
rH
o
rH
O
CM
rH
1
0
m
co co co ^ --
CM
i
co
o
vO
rH
CM
'
rH
CO
1
m
CM
CO
CM
in
i
CM
CO
CO
vO
VO
CO
CM
1
o->
1
0
co
-------
s
n
II
b
CM
+1
H
Q
W
^
O
£5
H
CO
W
CJ
a
£
co
co
13
O
H
<
o
9
><
<
"O
CJ
D
a
r^
4J
O
O
CN
(U
iH
,£>
co
H
N
vehicles
to e
e
degrees
N
vehicles
9
egrees
i-ll-(r-!CSl
-------
(fH
Table 25. RECEPTOR CONCENTRATIONS [ ~) FOR AN INFINITE LINE SOURCE,
2 \ *< '
ppm-m /grn. HIND SPEED = 1 m/scc. SOURCE STRENGTH = 1
gm/m-sec. STABILITY CLASS D- RECEPTOR HEIGHT = 2.0m.
Source Height = 0.0m.
Perpendicular
distance
from the
roadway
(m)
10
15
20
25
30
35
40
45
50
Angle to the roadway
10°
886
723
609
527
465
416
377
345
318
20°
562
501
447
401
364
333
306
284
265
30°
409
382
353
326
302
281
262
245
231
40°
325
312
295
277
261
245
231
218
207
50°
274
268
257
245
232
220
209
199
190
60°
243
239
232
223
213
203
194
186
177
70°
224
222
216
209
201
192
184
177
169
80°
214
212
207
201
194
186
179
171
165
90°
210
209
2.05
198
191
184
177
170
163
orthogonal intersection the maximum values still occur when the wind
angle to one of the roadways is small, as can be seen by adding the
results listed in Table 25 for complementary angles.
A complication is added by the variations in emission strengths at
intersections: the section of roadway with the highest emission strength
will not necessarily coincide with the section having the greatest (unit
strength) impact at a receptor point. Calculation of maximum expected
concentrations must be optimized for both roadways together. This has
not been thoroughly investigated.
The difference in emission strengths at an intersection, and upstream
or downstream of an intersection, can vary by a factor of about 7 up to
a factor of 50 or more when traffic is light. Thus, emissions calculated
for a queue of 10 vehicles probably account for almost all of the
115
-------
concentration at a receptor for wind angles of 20 degrees or greater as
long as the queue occurs on the roadway section having maximum impact.
Shorter queues suffice at larger wind angles.
Greater lengths of roadway are involved at small wind angles, and it is
necessary to examine concentration contributions on a finer scale. The
contributions of 40 meter lengths of roadway were calculated for wind
angles of 10 and 20 degrees. The 40 meter length interval was chosen
since it is equivalent to the five vehicle queue lengths used in the emis-
sion profile approximations. Table 26 shows the results of the calcula-
o
tions. The concentrations are listed as XU/Q (ppm-m /gm). The wind
speed is 1.0 m/sec, the source strength is 1 gm/m-sec, the source height
is 0.0 m, the receptor height is 2.0 m, and Pasquill-Gifford Stability
Class D is assumed,, Concentrations were calculated for receptors located
at distances of 10, 15, . . . , and 50 meters from the roadway. Under
each receptor distance, the column labeled x , x, lists the end points of
the 40 meter roadway interval relative to the intercept of the roadway
with the normal from the receptor. This is the same notation used in
Figure 35, except in that case Xa and X^, denoted the end points of the
roadway length contributing 95 percent of the total concentration at the
receptor. The next column, labeled XU/Q, under each receptor distance
gives the concentrations contributed for each of the 40 meter intervals.
For example, for a wind angle of 10 degrees to the roadway, the roadway
length with end points (- 17, 23) contributes a concentration of
2
39.3 ppm-m /gm at the receptor. The dotted lines on Table 26 indicate
the approximate location of the intercept on the roadway of the line
lying along the wind direction which connects the roadway and the receptor.
It is interesting to note that for a queue of 10 vehicles, a wind angle of
10 degrees (and complement 80 degrees) still leads to a maximum concentra-
tion at 10 meters, but it no longer does so at a receptor located 50
meters from the roadway. Table 26 shows that for a wind angle of 10
degrees, the maximum concentration from 10 vehicles occurs when they are
queued in the roadway lengths (-57, -17) and (-97, -57) relative to the
116
-------
g
60
1
P<
ft
*\
13
1
Cu
O
CO
2;
o
M
H
O
w
g
c^
H
CO
CO
H
O
P
co
Pn
co
a
H
^
fq
H
g
H
a
o
o
g
o
B
^
&
w
o
&
o
vO
CN
0}
r-l
"ra
CO
M
CJ
£
roadwa
£.
istanc
o
u
a
D
O
c
o.
-a- '
x
^D E &
X ^
- H
X
*1^
X
CM
a.
- G
X
O t-4
a DO
b-4 ft
1
a 5 5 s R a 2 s a
3 « 33 33 53 ;V^ 3 ?5 rf 2 5 S £ 5 33 3 3
ll II II II Ii II It II II II 11
co* « -*' oo* =0* m ^' J <» rZ
^'" ^S IS1" £2 £S " 1! " ^ 21" ^2 SIS SS
1 II II II II II II II II II II
lnr,0^r,«r>r.-.tO«
2SS£3S5;S20'r-
SS 55 55 55 55 S5 So 55 55 55 85
1 tl ll ll Ii ll il ll 11 11 II
l/t vO OjON O> t~4 CM CO <-< sO CO
I
1
2^ SS S S I S S S^ ^^ S2 S 51 S S ^^ S0
i ii ii ti ii ii ii ii ii ii 11
i
i
OO OO OOjOO OO OO OO OO OO OO OO
I II, If II II 11 II II II 11
CM ^ CM (O 1 1 II II l' 1 II II II II
LA CM|O cr* .-i CM co r-. so *r\ CM
i
i
1 ' t^'.ft V-T 7-r 77 77 77 77 ?7 tf
t
CM »-l
1
(1 II II II ft tl II II II
1
Cl wil(M ON
-------
00
g
e
E
01
25
O
M
H
w
>
H
CO
CO
w
o
u
P
CO
o
CO
a
o
pq
a
o
u
&
o
s
w
g
T3
AJ
oj
o
V
U
stance
«
r-l
3
O
C
O
cu
CD
0
in
o
o
CM
o
CM
10
O
r-t
CM
ska
ex
.0'
- a
x
^
O1 B
-*- 1 x-s
3 n G
x o. So
o.
X
CM
5" 6 'a
x & °o
o.
J3
X
o* a
x |§>
-Q
X
E> B "S*
X c- oo
P.
.Q
-"» 1 s~*
Is
CM
0* S
=3 B S
X (X oO
(X
^-s-
x
CM
o- a
X o. w
o.
j3
X-g
X
CM
o a
» a B
x o. a
o.
.0
is
X
if
f-i *-4 oi> r^ o oo */i
00 r-4 CO o^ m x± O
rH C4
1 I « 1 r-*t-< CM^H rMCM CMCM
1 1 1 1 1 I 1 I I
CM r-t CO C"l »-* 00
^-4 (M
1 1 t 1 1 1 1 1 1
CTV vD -^ CO vtf f-«. O
ON O O %O ^* tn <*^
c?o oo oo oo oo oo
|| ,-H t r^^-tr-t^rJrHCMCM
I i i I i 1 I i i
r-» i-* co O r^> CM »A
o"^ o"j3 ^".0
II II r-< 1 rHr-trNf-HCMCM
1 1 1 1 1 1 t
»
r^« r^ *o co O^ cM O
1 II *-« 1 i-< f-t CM r-t CM CM
1 1 1 1 1 1 1
r4 e*l ^ *^ O vO CM
CM i/l ?>* 00 £M O irt
»-* r-« CO
1 1 ^Hl r-lr-t r-lr-* CMf~l CMCM
1 1 1 1 1 1 1 1 1
O \f} t^ \O \f\ *$ r**
«+ co en «sf
CM t-l -J
^"10 ^"un ^^ ^^ ^^ ^^
11 II r-t I r^r-tCMr-4CM;CM
1 1 t 1 -I 1 1
m r^ r>. O O n CM
CM ^J (M tf> «H O *O
CM CM . -*
1 II r-t t <-li-4(Mr-4CMCM
1 1 I 1 1 1 1
«. - ^ -* «>. «? *
-------
point at which the normal from the receptor intersects the roadway, for
a receptor located 10 meters away. This concentration is 359.5 + 223.4 =
2
582.9 ppm-m /gm. If the wind angle were 20 degrees the concentration
2
would be 247.8 + 275.7 = 523.5 ppm-m /gm. Looking across the table to
a receptor distance equal to 50 meters, the concentration with a wind
2
angle of 10 degrees would be 40.8 + 33.0 = 73.8 ppm-m /gm, while if the
wind made an angle of 20 degrees to the roadway the concentration would be
2
101.1 + 78.8 = 179.9 ppm-m /gm.
This brief investigation into the effects of queue length and wind angle
on concentrations at nearby receptors suggests the following approach for
estimating expected concentrations.
10 Determine the wind angle likely to lead to the highest
concentrations for each of a number of queue lengths
(e.g., 5j 10, . . ) at each of a number of receptor
locations. This is likely to be a small wind angle
to one of a pair of intersecting roadxvays.
20 List the XU/Q concentrations calculated for each 40
meter section of roadway for each receptor location.
Since large sections of roadway contribute at small
wind angles, approximately 8 to 10 values might be
listed.
To estimate actual expected concentrations the following three steps
might be implemented.
3. Multiply the values of step 2 by the emission profile
source strength estimate.
4. Subtract the sum of the values in step 2 from the
value calculated for an infinite line source (e,g.,
Table 25), and multiply the result by the cruise
emission strength.
5. The concentration (for a 1 m/sec wind) is given by
the sum of the results of steps 3 and 4.
119
-------
SECTION VI
REFERENCES
1. Chicago Tribune/Chicago Today Research Division. Chicagoland
Shopping Centers. October 1970.
2. Barton Aschman Associates, Inc. and Environmental Technology
Assessment, Inc. Unpublished study of Oakbrook Shopping Center
for the International Council of Shopping Centers.
3. Turner, D.B. A Diffusion Model for an Urban Area. Journal of
Applied Meteorology. Vol. 3, No. 1, February 1964.
4. Highway Research Board. Highway Capacity Manual - 1965.
Special Report 87.
5. Baerwald, J.E. (ed.) Traffic Engineering Handbook. Washington,
D.C., Institute of Traffic Engineers, 1965.
6. Barton Aschman Associates, Inc. Storage Requirements for
Frontage Roads.
7. Pignataro, L.J. et al. Oversaturation Terms and Measurements
Seem Adequate After Field Validation. Traffic Engineering.
Vol. 44, No. 9, June 1974.
8. Traffic Institute. Capacity Analysis Procedures for Signalized
Intersections. Northwestern University.
9. Environmental Protection Agency. Automobile Exhaust Emission
Modal Analysis Model. Report No. EPA-460/3-74-005. Environ-
mental Protection Agency. January 1974.
10. Environmental Protection Agency. Compilation of Air Pollutant
Emission Factors, Second Edition. Report No. AP-42. Environ-
mental Protection Agency. April 1973.
11. Mr. D. Kimball through Dr. Edwin L. Meyer, Jr. Personal
communication.
121
-------
12. Haight, F.A. Mathematical Theories of Traffic Flow. New York,
Academic Press, 1963.
13. Environmental Protection Agency. HIWAY: A Highway Air Pollution.
Model. Draft report. Environmental Protection Agency. December
1973.
14. Calder, K.L. On Estimating Air Pollution Concentrations From a
Highway in an Oblique Wind. Atmospheric Environment. Vol. 7:
863-868, 1973.
15. Thayer, S.D. and K. Axetell. Vehicle Behavior in and Around
Complex Sources and Related Complex Source Characteristics:
Subtask IShopping Centers. GEOMET Report No. EF-263, Prepared
under Contract No. 68-02-1094 Task Order 1 for EPA. August 1973.
16. Barton-Aschman Associates, Inc. Personnal communications.
17. Pignataro, Louis J., Traffic Engineering Theory and Practice.
Prentice Hall Inc. Englexrood Cliffs, New Jersey, 1973.
18. Environmental. Protection Agency Interim Guidelines for the
Review of the Impact of Indirect Sources on Ambient Air Quality.
1974 Draft.
19. Patterson, R.M. and J.R. Mahoney. Traffic Motion Controls as an
Emission Control Technique. Paper 74-3, 67th Annual Meeting of
the Air Pollution Control Association, Denver, Colorado,
June 1974.
122
-------
APPENDIX A
CARBON MONOXIDE DATA
A-l
-------
Table A-l. PLOT OF CARBON MONOXIDE AVERAGES FOR STATIONS
11, 12, 13 AND 14; AND PLOT OF WIND DIRECTION
AND SPEED.
Note:
Table A-l has been presented in 11 individual pages. These
pages may be connected together to form one large time series
plot, giving an overview of the entire monitoring study.
Weekday: Sunday = 1, Monday = 2, etc.
Hour: Midnight to 1:00 a.m. = 1, 1:00 a.m. to 2:00 a.m. = 2, etc.
For each station CO plot:
(0=0ppm, l=lppm, ..., 9=9ppm, 0-10ppm, l=llppm, ..., etc.)
For the wind speed plot, the same format was used with units of
mph instead of ppm.
An X on the right margin of the plot indicates that no data were
recorded except in the wind speed plots, where an X indicates
that the wind speed was greater than or equal to 19 mph.
A-2
-------
o
z a o
» o c
I
o
UJ
UJ I
a. I
in a.
a i
Z I
o x
o o.
>- o a.
< I
>-
ui
z i
o z
-t o a.
»- u c.
< I
>-
l/l
Z I
o z
« 00.
t- os.
< I
z i
« a ct
>- O O.
< I
in
jj 4
* o
r <
^- o
oooooooooooooaooooooooocooooooooooooooooooooooooo
^r »o 10 .-« ~< .-« cr «-« ioi/)ooGooo« « »H ^-t*^*«-»-,KIKI ^firi/itT'^KifOc^CT1 v£tr>inj .jcy-^oc oc c -c
X X X X X X X
-------
xxxxxxxxxx
in ui in
* *
a a a
010
CJ c* CM
jo in (O -o 10 n
(M O I
/ M
v-4
O O O C CO
in in
a- » * -f
>O "1 K> IO IO
I (VI -
A-4
-------
O O O c OOO COOCOO OO OOOOOOOGOOO C O C O o O o O OOOOOOOOC O O O OOOOOOO
'^'
fj CM CM CM
OOO'OOC OO C O O O O OOOOO
a a> f> tfs in m * >
m 4«4 r* **t .4^4^. .4 ^4«-4 ,-«v«.4««
CCCO COCCOGC3COO
xxxxxxxxxxxxxxxxxxxxxxxxxx
ro 1010 10 10
CM CM
X X X X
A-5
-------
O OOOCOOOOOOOOOOOOOOOOOOOOOOOGOOOOGOOOOOOOOOOOOOGOOOOOO
sc ocr^oo.r-osccrr-«oao 0*0 oc-ootv»o
-
10
(V CO
r- r- ^ r>
>CNO -o-o >o *o >c
in in in ifl u> to
* a ;* a
n nn
cu
vO J3 -O
in
jr^jd-j3-»» 3- »»
o n rt 10
CM (VI 10 fO 10 in
CM . CM CM CM CM CJ
-*« ^-^^i-^ ^4^4*4^^
OOOC3O ' C5OOC (SCOCCCOOOOOO
\a -a >c >o >c
in in >o m IT in in
3- » » 3-
rt
CM1M
OOOO33OOOO3O
jj a
^i ji
10
A-6
-------
oooooooooooooooooooooooooooooooccooooooooooooooooooooo
~ o- c ,0 <\, ,0 o <£ o o a:
ffl
100
CM
J>
10
CM«<\I
ocoooooooooooo
ocoaoooo
c «o
-------
O OOOOGOOOOOOOOOOOOOCCOOO OCOOOC COOC COO CTOOOOOOOG OCOOOOOO
10 j-^-. rg^^oacr
co a
r- r- r-
>O \O so va
U1
» *
IO 10 10
o 10
-------
O OOOOOOOOOOOOOOOOOOOOOOOOOOOCOOOGOOOOGOOOOCOOOOOOOOOOO
*^. < K-. i^< fr K*. ir K: in rsj t\j c\. o* c\. o. f\. <\* c. f^ IO IO I
CM ru oj CM
1 -** «^n in \n ui
10 M l>!
oococacooooc;
O* 3* 3"
33
I O
10
10 o 10 o
.NJ ,M OJ CM
-------
G OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOGOOOOOOOOOOOOOOOO
c c -^<\.crf^^c»iFi^^j3-K:mK!»^»o^'^-;'-JU"l'"w*rmirinir. ma-.j.jtf'O^cjoycyrMpj^ IT .o *n IT tn w. I
<\. cu o. c\< c\. t\. -. -, -. » r. r. f. r. r> f.
XX XXXXXXXX XX
CO v CO (O
?*-r- ^r^^p*- r*r*r*N
«0 ^
10 O
CM
! »4
o>
0>0>
t*
fin * n
~ C3OOOOOOC3OOOOOOOOOOOOOOCOOOOOOaOOC3OCC3OOOC2OC3CO OOOOC3O
10
10
O. CM (M CM (Vi
-------
O OOOGOOOOO'OOOOOOOOOOOOOGOOOOCOOOGGOCOOOOOCOOCOOOGOOOOO
"~
" o
,/) in- >fi
*
n n n 10 10
ca ev PJ eg
*^ *-« .-^H.-i«-««-l
c o o c. c o
CM
*4 ~* -«
O O O O
co 8)
10 ft >o 10 10
<\J OJ <\J CM CJ Ol
*«v4.^ V4«4^r4v^r^-' ^4^4*^^ ^t^-^^-^-^-^^ »*
OOO3OOO OO^O^OOOOOO
m in m
10 nio rtio 1010
CVIOI (MCMCVCM
-------
OCO COOO OOOOOOOO OOO COO OOOOOO O C. O OOOOOOOOOOO OOCC OOQOOOOO
GOO fft~*cr--r~r-r~r^r"-r-'C»£r~r~f'-cc.crc'<7cic:ocr'fxj»'~K*v/"i^:.£»£^ 10 ion
r- r^
« d
OOOCOOC3C3C3 ' OOOOOO
IOIOIO . IOIOIOIOIO
O. « O.CV.OICV.OjOIOJOJO.OiOl 01
-j -g dl OlOliM.-U.MOl'M OIO1 OlOIOIOlfdOirJ
A-12
-------
o o c o o
r- r- a. r- -a
o o c o
A-13
-------
Table A-2. PLOT OF CARBON MONOXIDE 1-HOUR AVERAGES FOR STATIONS
15, 161, 162 AND 163; AND PLOT OF WIND DIRECTION
AND SPEED.
Note:
Table A-2 has been presented in 11 individual pages. These
pages may be connected together to form one large time series
plot, giving an overview of the entire monitoring study.
Weekday: Sunday = 1, Monday = 2, etc.
Hour: Midnight to 1:00 a.m. = 1, 1:00 a.m. to 2:00 a.m. = 2, etc.
For each station CO plot:
(0=0ppm, l=lppm, ..., 9=9ppm, 0=10ppm, l=llppm, ..., etc.)
For the wind speed plot, the same format was used with mph
instead of ppm.
An X on the right margin of the plot indicates that no data were
recorded except in the wind speed plots, where an X indicates
that the wind speed was greater than or equal to 19 mph.
A-14
-------
X CO
I
ui i
a I
\J\ CL
Q I
Z I
o s:
- c a
I- (JO.
< i
i~
in
z i
O X
00.
t- O Q.
< I
I
in
Z I
2 OH:
> o a.
< i
I o!
*- O fi
< I
ir
xl -C
: O
z <
i: a
OOOOOOOOOOOOOOOOOC3OOCOOOOOOOOOOOOOOOOOOOOCTCDOOOOCJO
X X X X X X X
CM CM CM
O O
o> CT-
r»
o -o
m m in
X X X X
CM CM
-------
O OOOGOOOOOOOOOOOOOOOOOOOOOO O,O OOOOOOOOOOOOOOOOOOOOOOOOO
CM C C. » v* O ff %C vD *O Kl - CT r^ f» (T CJ* CT CT" O O* CT C5 ^* " ry «-* (V C\J f\J *^ O O *-« rvj OJ i^iioirjioK>
xxxxxxxxxx
a -a
\n in IT in m
10 10
CM CM IM CM
O O O
r-
c
m
>o 10 10
CM OJCM NCMCMCM
O O O O
XXXXX
Ol
ooocaccoc o ooc
XX
-------
o oooooooooooooooaooooooof-ooocooooooooooooooooooooooooo
o o oar~r^co«fcof^or>*»o(\j--«*-*<0
to co co
r- f-
\c in in trt ui
» J»
n n n n
IT. in
CM CM
X XXXXXXXXXXXXXXXXXXX
ft! CJ <\J
- ^1
C O O O x
o
a-
o o o
-v; «| ,-u .>, ,-j rtj f() y .-^ ;g ,v .\, y .v M .-J ;\l -\» M ,V :j J -V \J .g .-g M ca .\J .M V .\l ~V 1 .V .'» -V < JM
A-17
-------
O C OOOO O O O O O O O OGOOOOOO COOOOOOOOOOOOOO OOOOOOOOQOOOOOOOCO
«£ (Cr»o<^-O°O'f*a:o (Tioa'OOOc:fvK)a.-^»o^cccyFr;3«.^inu5^*\«--'--'----*'ir-. -* <\* f\i 10 K, »», ^^ ^-, ^ ^, ^ ^ ^ p,
xxxxxxxxxxxxxx
o- O- fl-
CC CO CO
C\)CJOJC\JOJCMjeMOJ
OC3COCOOOSOOOO
ococoooo
<\> n>
XXXXXXXXXXKXXXXXXXX
I/) ^) t/)
* 3- .» 3- »
rO j .g i
"J rj .M .g .<; <\. :\i .
\i >o o o o ^) .o -o -o -^ "i .1 i »i o /o >o ^o »>
A-18
-------
OOOCOOOOOOOOOOOOOOOOOOOOOOOOOOOCOOCOGOC5OOOOOOOOOOOOOOO
^oc^^crv0cuooccao*r^oo-crcrocrr~cro'0aa-c\«cvu*croi^.ijr~r^ttccoocc7crr--inir. jra-cvcvojcMcx;
KS c\* i*. .-..-« .-t ^ -*« .^ ««c^c^cvcv.cs.c\.c\icx»'.»'.r\eN.c\.c^(\c\iC\.c>,c\.o.r»4c\i
10 10
o1
a>
r-
K> n ft
CV. OJ CM
10 JO 10
(MCJCM (MM C\JOJo a
» -> *
IOIO (OJOiOOiOiOO iO>OlO "
fM CM CM OJ (M CM CM CM CM CM fM CM
-------
oocoooooooooooooooooooooooocooooocoooooooooooooooooooo
n :r 10 a
in Ift in in
a- ' »
01 (M
o» o
CD CD
^ f» t»
*O - »~
sO J3
in
» » »
rt 10 10
CMC\JCMCMCMC\J (M (M CM
CM CM (M CM CM
-*»*i»-lw* «-l"*H«-t -« P^.^^tlH
ccoocco ococo ooccoooooco
XX X
CC
a
IT
a
i«l
CM CM CM
3 333
* *
A-20
-------
r. r>f. r. « K. r ,. r.
x
a
1/1 IT) u">
'"
OJ
«
oocrc-ceccco
.«__. __._«_
>A
m m in
to to rt
OOC5CCOOCOCCCOOO
3 CC X 03
p- r-
X
in in
« KJ*
in in in
% .4 .k tf %
A-21
-------
OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOGOOOOOOOOOOOOOOOOOOOOO
o o -« itvo-r-^raioja ^JIOIOKI^.KIJK-J ;r in IT >r> «~ U"' «" inifiir, aa j j«otocurjpjru in ir>
<\. IN* o« rw ou c\- ^^ ^» -* ^« i?, f. V, r* f. r. r.
XX XXXXXXXX XX
CO O
10 10
CM o;
x x x x x x
vO
m
j a- » ay
10 10 to 10 1
CMCM NCMCU
-------
C OOOOOOOOOOOOOCOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO
K- .-..-«;jr~~-of>»Of"-*oir. o o err~r*r~o\i}u3unioj:j:rir. \OF~r-ffa:r~r~«o»£>u'>j:jir. JIT> f-^ioof^r-oirrfiri
r-
C
o o o o
K>KJ>OK>IO
CVCMCMOJ O
in
* a- a- a- a-
10 o n n 10 io 10
C. <\J IM CM (M CM «J CM CM CM
OOO C \ COOOOCC
XX XX XXXXXXXXXXXX
10 K; K> o 10
CMCM (Ni(\.CM (V.
o
r-
m
rO
-------
C OOOOOOOOOOOOOOOOOOOOOOO OOOOQOOOOOOOOOOOOCOOOOOOGOOOOO
XXX XX XXXXXXXXXXX
CC ft
f<* CM (M
o o o o
CO 09
o
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
X X X X X X
01 CJ
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx>cxxxxxxxxxxxxxxxxx
-n .1 n Ji -n in n -n * -3 o 3 J) o 33 00-3-0
A-24
-------
o o c o c o
a; r- r- O -H -W O
A~25
-------
Table A-3. LISTING OF CARBON MONOXIDE 1-HOUR AND 8-HOUR
AVERAGES FOR STATIONS 11, 12, 13 AND 14; AND
LISTING OF WIND DIRECTION AND SPEED.
Note:
MON = Month
DW = Day of Week (Sunday = 1, Monday - 2, etc,)
HR = Hour (Midnight to 1:00 a.m. = 1, 1:00 a.m. to 2:00 a.m. = 2,
etc.)
WD = Wind Direction (degrees)
W3 = Wind Spaed (mph)
* The 8-hour average listed for any given hour is calculated by using
that given hour and the previous 7 hours.
A "999.0" reading on the 1-hour average indicates that no data were
recorded.
A "*&****" reading on the 8-hour average indicates that there were not
sufficient data to calculate an 8-hour average.
A-26
-------
000000000000 00 00000000000000000000000000000000 000000
***"***^*******'**'-''!
QOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO
"-----
cat
0000000
o>OcOOlOrtlO'O'^'^'O'O'Or
o
A-27
-------
O OOOOOOOOOOOOQOOOOOOOOOOOOOOCDOO OOOOOOOOQOOOOOOOOOQ OOOO
o or^^^^^^^^^^^^^^^^oou">i/}r^r-r--^r(\i^tnj'--i -H^ririvO trjijin.-oj-cvojcg^oa^vomr-r^-j^-^
OOOOOOOOOOOOOOOOQOOOOOOOOOQ OOOO OOOOOOOOOOOOQOOOOOOOOOO
O OOCDr^OOOOO OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOQOOOO
--4 4 -4 o CO O v£> f) -O -4 ;> I*- i-- -O CJ> C* G"1 ^ J% L.~> O --« « ^ -* ,M *M -"NJ 1 O O -* ' <\J 'NJ ') "J CM C\J .J" J -O k> AJ Jl r> >") -^ J- r- -X) O O O
KiK)r^KiiOK>r^c^^^ocLcfoa^o»-*o---t^^)^-^'^^'fOoaorOi-^'jr^r^>^'K)^<^-io-H
-I^H -H<\iOJKinc\Jr-»^« *HC^i-^^^^-4-^c^OJlOr^rOfO'OiO(^J^OOJ»-^^-^ *H i
O
^t>
'^CT'.7^iJ^C^CT>C^^^fT*^rJ1^'^Cv'Cr»^7*O^'J>C^Cr-^
cri;>(7*.7v jr^j^,^ij'Ocr«Lr'cr'^cr>J^j>c^JvC7viT»oiT't7*JvCT'
O^C^O^O^Oy^CAO CTvOC»OC"'OC'C1Cr'ONCT>G>Q>O*C^C1*CTv
* > » * * o- * * ^* 3-^-^rfOroojcu^runuTui'i)r-*a3* * * »*
<»^»**-**-K-4 -***»»
«->1».»4»>«.*^«. *-»-+**
^:c_'oor>j^3-^rj-irj-^- jf»OK)^-jroooooooa
^c-a^cr-c^ 300 « -
J^^OO^C* J*OO^7>J*iJvO>
IT'C^OO^O^ CT'CnO%ONO^O^C7'
AJ^^iOOf^O<>C3'^OJrO^^^fNJrO*U1vOr*>o3O>O'~«-"vJ'^>-;^l^'^i
iO'')'O'OfOrOfOfn'O^l
o^jD^^o
A-28
-------
O O OOOOOaOOOOOOOOOOOQOOOOOOOQOOOoaOOOOOOOOOOOOOQOO O O O O O
arjo^ooo^<\j.-*ooc>^ooo'Moa3\3;n a* 03 :o eg f*
O OOOOOOOOCDO OOOOOaOOOOOOOOOOOOOOOOOOOOOOOOOOOO CXO O O OOOOO
O ^3 OGOOQOQOOQOOOOOOOOOOOOOOOOOOOCraOOOOOOOOOOOOOO'rJO O O O O O
A-29
-------
000-3000000000000 OOOOOOOOOOOOOOOOOOOOOOOOOOOQOOCDOQOOOO
;*in^'OuT\or^a^xO^^uir~r\j(>vi)jiroKif^o.j:f^c\j^^^r^^c^
o ooooooooooooooo ooooooo oooooo ooooooooooooooooooooooooo
ocooooooooooooocjoooo-^oooooaooooooooooG^coooooooQoooooo
O\ i3^-^OO^r-u3OOO»C7'CxOOOCM-O'.O^*-Oj-aD^V'n3-^ T »"» O r "0 -<-* 4 .~t CM O *O :r:T"~>'1')-Of~>'-t:NJ>.'\j;\J:\J'O.-iOo
*-, ^ r-4 *-« - t ^« *n I.M (^ cu C\i r'j r~j i^} lO "T O TO rl p ) r') KJ rl f") n rO fO rO rO fO K) fO rl r> O fO fO rO "O (O f-J (O
vOuiLOr^oino^'OcociL^aDC^ofOi^r^r-in^^rOxOorootTr^^^r^^c^cj^inr^cj^
-'''' ~--
C OO
j^
Kio
^
A-30
-------
OOOOOOOOOOOOOOOOOOQOOOOOC3OOOOOOOOOOOOOOOOOOOOOOOOOOOOO
jcj-**~4--«<'-4 ^ ^^..(.-^p^.-t.H.H.H --I -* .H C\J C\J OJ o ^rOooruociO3^mr^a*c^<>^cr»cr«r-o^c^o%cr»*.'j^cjl.Tt3O'n^r~r- tJc3->oocr^cDr-j^inj-a-r\jr\)ojruoj/oj-n
^-~*«-*«~<-^»-«< «- -^^^^ir\j(\jf\
'-*-<-<-<«*»H CD a-ttrvjcyajOJCMOJCMOsl-H -*(\JCJCJKllO/OfO
rf^-j-ionKi^t^t-H^-^-^-crj- ^-'lOfOroa-io-r-^orornncr =rJ-^-cfrr*oofOvOo^-(^«^OLnfOO(Of**<^in^'inrii*o^j-f^CTvoro co^o^o^o^cco vO< c\j\oor"**otD ^3"coj3-^c\jK>^-i/^\O3'
^-t^^t^H^i^^^^,^,,^ *^'^rOnK)(lO
j- ^3-j3- oiOpr>-4--4--<'OrOfOfOj}-j-.-t ct-^j-J ^^rK^^^oc3o^K^ofN.Ln^a^-^'^-^'^^^'*^K>'O'Of^--
o^to^ofO^^iriui^cjr^ai^^roK>fNjcsjwrOvr>oK5ui^0^^cj^oo^c\j^oaxa3r^ui^rOfo
*-I.H.~4r-<-'««-t--t-~l ^«^|»-l^*^-»CJC\JCyCJfU<^OJOJCg-H4^I i~4*~4_t.~«*..«.~4.-4_|_4,P4
zfK>*-*OtO^-cTJ^-ir^TifzfJ- ^P^OOOr^K)-^--^--^^«^^o-^-''OrOlO^o^^f'Sr^FO^O^^--^»-^o--l-^p^
o t ry o ro t oooo^ ^^fOo^*^<\joaojra^K><\jr\j»^'^^-^^H'M^«-H--*^4Cjrjro^jc\i»-4-^--i--i
j^ooooCT^o^r^-in^^r ^ ^cr^^cocuLni£jsOvOvoji'^oin^^^3's-^-trtc\j(7^r*-JifO^H^(r4jj-inio o ^o '-o
-H^fOj^-3'^-3"^r^-j-3-j--rj-^r^.-*ooTOj*s--<^^-H'0-^fOjj ^rrnz-xsra-x
OJO-OiO^>K5POrt*O
U-NJ CM rj rj eg AJ rj eg
A-31
-------
0000000000000000000000000000 0000000000000000000000000
......... »..»»....................,,...IIB^-v^v-'*-'»
?1 °i P, 2J"i^^^^^^N"*J^a*M^olo<0'1ia^l^OK1<^rv'J'0N--'0>'l"-rtc>c>I='-oouio>inor~i~.i-!r^in^1n
C\JCVC\IC\J-.-<.-..-I.-I.-..-,(\)-I-I-.-H.-< -.____ -.^^cM-.-.-.rvj^rjojrjrjcyrvj^Mojojru 10^ ft n n in n n n
o -.cvjroo-t ooo ^4-1 ^,<\j n n oj oaooo -i-. 10 rj
-i ca
ooooooooc __«_,,*(.,, rt^^-r-,
...... ......... *'7T:*'i*;*;'';''"or-13'1S^^ 2 222^223 J3
nj.3.3.a.3.j. 3.3.^.3. 3.3.., 3.^.^.^. 3.3.^^. a-a-a.tn*>stjtayftfi\t»n\n\njMr>-Jt\n
-------
OOOOOOOOOOOOOOOOQOOOOOOOO OOOOOOOOOOOOOC3OOOOO
uiK>uo*/)v0vD^r^^ui^^>oea
-------
OOOC>OOOC3OC3OO O O O O O
o oooooooooooooooooooooooooooooooooooooooooo oooooooooo
oooooooooooooooooooooooooooooooooooooooooooooooooooooo
'
OOCOOOOO
CDOOOOOOOO
OCDC3CDOOOC3
OOOOOC3CDOO
OOOOOOGOOOOOOOOO
OOOOOOOOO
OOOOOOOOOOOOOOOOOOOOOOO
^
A-34
-------
,-,,-. r^ r-» r~i -3oaoaOOOOOOOOOOO
O 0000-000 C_> 00 000^00000000^<-
^^-^
ooooooo^^
- 10 K1 K7 n 10 d' O f 1 O O -< '
A-35
-------
oooooooooooooooooooaoooooooooooooooooooooooooooooooo
o- cr*r--:cr\jfOU")O IOC^ODO « ao o oo
« .H ,- « .-* I f\» <\J I 4<\JCVj-*f\JC\J<\J
O " C3OOOOCDOOOC3OOOOOCJC3C3aC3OOOOOOOOOOOOOao
C;C^OOOOOCDOOOOOOOOOOOOOCDOC3OOOOOOOOOOOOo
or^r-'ar-r^-r-r^-r-r-r- o Dr-r-r-'Tt^a>c^ocioo-^'M^KT-^v"> O^J-^-iioooj
^«^«^^, ^^^^rjcucy»%jfOfO-H3-3-i-
oooo i^-*»HfOfOf')co--i»^»-*.-<«-t(\i
V^fOOcQiiJ^
ojcyoj^t»H*-«-<«
mo^«K>^-
- ro cu -^ i oj ooooaoo c\a(\jio
^^JOJf\JC4-^«-t
o-*Kid--.cr-
oooooooao
^-
ooo oooooooooocaoocaoo
^^
A-36
-------
000
H O f^
o o o
aj r- -o
*^ CO I
CJ /-i
tM 10 *
<\j rj
-------
Table A-4. LISTING OF CARBON MONOXIDE 1-HOUR AND 8-HOUR
AVERAGES FOR STATIONS 15, 161, 162 AND 14;
AND LISTING OF WIND DIRECTION AND SPEED.
Note:
MON = Month
DW = Day of Week (Sunday = 1, Monday = 2, etc.)
HR = Hour (Midnight to 1:00 a.m. = 1, 1:00 a.m. to 2:00 a.m. =
2, etc.)
WD = Wind Direction (degrees)
WS - Wind Speed (mph)
* The 8-hour average listed for any given hour is calculated by using
that given hour and the previous 7 hours.
A "999.0" reading on the 1-hour average indicates that no data were
recorded.
A "***#**" reading on the 8-hour average indicates that there were not
sufficient data to calculate an 8-hour average.
A-38
-------
m^ooooooooooooooooooooooooooooooooooooooooooooooooooo
i . ******<..».»..*«»*.*,.. »»,..«...»...
KifMrjoou^ooiOKi^i>jao^c^^oaacr'^acococoovi)^r->ouirOK>a-Ki^o^r-^^r^OfOoj(\j*^incJo^i^
Coooaoooooooooooooooooooooooooooooooooooooooaoooooooo
OOOOOOOO O O 0 O O OOOOOOOOOOO OOOOOOOOOC?OOaOOOO:DOOCDaaoa<"^rtr5
TTO^-H^io^nj^oooooo^^^i^i^^i^^-or5j--.OLni.TO'0'OAio^^y>ji3-j-u*-iaoooo-JoSoo
i^
l/i C- 0> C7* C^ CT*
Cf-HCJ'OfOfOKJrO-HCNJw-l-H*-! *
r-f-r^-^r-r'-r^r^r1-'
K>^K>^fO^rOOfOlOK>^^J^^^
^
A-39
-------
00000000000000000000000000000000000000000000
00 000000000 00000 OOOOOOOOOOOOOOOOOCOOOOOOOOOOOOOOOOOOOO
o*
co*#
C^ t> C* O* tjv O»
\o \o r*~ r** r^ i
. . , ininoooooooomom
ooo ".-;j;^^4J;j;4 *^^ " " "oooooo " "
A-40
-------
OOOGOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOQOOOQOOOO
OOOOOOOOQOOOOOQOOOOOOOO OOOOOOOOO OOOOOOOOOOOOOOOOOO OOOO
OOOOOOOOOOOOOOOOOOOOC2OOOOOOOQOOOQQOOOOOOOOOOOOOOOQOOOO
^oroo^jfOiv-H-- i.-i;7*;o;>c7*a^co;3r-r--r-f r*-r- 0 r-- cj -t) OJ»;7%oj*\ovj3.a.^3~O33c*a3.or-or-r-:Of>-;o:ai'1-
c i/:inoinoinau")c: c c vn ui in u~ ^ooininoooiniriLOinoinoinoooinooooc o o o o o m o o
»*»<»»»»*»»»»*»»**»** » * * »*
* **»»»*»***»****>#**»
x3tn«^irK>^jun^(M^4r^^o^^or^^^r^cNj^«^^'^fOui^xa-^o1irojrg.\jtNjrjfsif\i
A-41
-------
OOOOOOOOOOOOOOOOOOQOOOOOOOOOOOOOOOOOOOQOOOOOOOOOOOOOOO
OOOOGOOOOOOOOOOOOOOOOOOOOOOaoaoGOOOOOOOOOOOOOOOOOOOO
o oocmmoooifiiT. ctnificrLTinoir»oooc.oc: ooc. cz
'^rtrt
ica »-H
ooooo
A-42
-------
O OC3O DOOOOOOOOOOQOOQOOOOOOCOOOQOOOOOQOOOOOOOOOOOOOOOOOOO
j-f\jcafO^iOi/>coo^'OO^o*c3ao»-*ojfO-3'jpj'io^r*-»ot>(7^o-HC7*»-« c^J*i*3Ln\O'j^(/i*Hr*>'£jcJx.'O
*-«.-««-(-»4 .-««"« «"I«H «H *-t*~1.-t»"l.~l.-«l1~4.-t.-t *-i -4 4 CvJ CSJ C^ ttj
»
C3C3OOOOOOOOOOOC3OOOOOOOC3OC3OOOOOOOO<3OOOOOOOOOao'oOOOOOOOOO
OOOOO
(\if\j'«')-rfO
rgo4OjcjOj
^« -^^fiv^cacwvooj ^r^-H-^iT^uo-^^njtT^^ojr^r^f^oA/L^o^yKjr^rjLO^^o^^rjrH^^rDoocjo^^-^c^cr^to
^i ^i»-«^i^«^cj<\ifOioio^r^-roroK)CMoji^i^n^t .Hc\ic\jion^.^-jfonajcy»H^4-H*-«^-^»H«»-<i^4^<^*-irH*^
in cvninccinociooouiou^coocootnLncu^oococrou^u'iinooocjoooooofoctnooinio in
*~4 ^^^rouioio^cf^^
^4<-fcjcvr^y^ir3M*^-<-^fya;Kj?Of*3ronjoj*-i*-*
zt- ca^-jrKioc^C* vO^^t^o^^fO3^r ^cr^-^-cJ-ior-r-'^cr^O'O^-o^^- cr $ -x cfa-^r-^-cr^r^^-a-iOjO'-tfO^j^f'-^ir*
a* ^(O.-oninwnrooj^ ^^^riD/on^cT* -^^cy^
^. ^
cr- <^
oou^inoomin
oooooo--*-* O
i*
O*
A-43
-------
OOOOOOOOOOOOOOOOOOOOOOQOOOOO OOOOOOOOOOOZDOOipOOOOOOOCSOO
cyooo;rrvif^^vDr^o*vOJ^
c ooooooooooooooo OOQQOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO oooo
o oooo^oooo oac^ooooocjooQooooaooooooooooooooooooooaooooo
oj^^o3*(^or^r^r^c^or^^/O-Tro^r^ji^Lo:n^:*j^j3:D;T"ji\JO^^">^^^^^
oc c-ocDi^omoinominmoc^'j^tn cirtLninminminLiincomcmji ooom
c*
O"
ooouomc^omomaoooininou^ ir» i/*
ao -H ooooooorvitnj- o-^^wo^a-cgor-var-^oo ooo
A-44
-------
OOQOOOOOOOOOOOOOOQOOOOOOO OOOOOOOOOOOOOOOOOOO
roeM-HOooooooooocu'Ji oa*o* ^ in -< ^ r-
OOCaOOOOOOOOOOQOOOOOOOOOOOOOOOOOOOOOOOOOOOOofaOQOQOOOOOO
»*...».»»»*«.**.»
aoCDooooooooooQQQOOooooooooQooooaoooooooooooaQsooooQtaoo
in 3--na-'Oj^)'jr)ir»Ln'Oj-Ji -
ooo foCMC\j«-4*-*^i--t^-»cjrovOcocor^*O'r7^-inCT^^OT»injK)c\j^H^4^o ooo
c^
o\
fo-^^^o^^oa'^uia»^
eg *-» i .-« -*
a*
^*3-*o(Nj
-------
oooooooooaooooooooooaoooooooooooooooooooooooQooo ooooo
OOOOOOOOOOOCJOOOOOOOOCIOOOOOOOOOOOOOOOOOOOOOO OOOOOOOOOO
00000000000000000:^00000000000000000^000000000000000000
' ~ " - ~ ».o *) ,<> + ,o j- j >/j -ji m m j^ sO LI m *n ^ ^- j- ^- »> -o CM CM CM ^M rj cv ui o /« -.o .n tn ai 10 -4 -H
* o^ o* o* cr*
FO t\J CM *~t -* ^4 «H «H -* vi CM (M CM CM K) fO lO fO -3" ^ fO (O CM (M <^4 «-4 ^4 v-l
' ^ *^ O* O
ooaooou^omoomoinotn tnu^amoooootnoooiotninin o o o
»
-------
ooooaooooooo
oooooooooooooooooooooooooooooooooooo
OOOOOOOOOOOOGOOOOOOOOOOOOOOOOOOOOOOOGOOOOOOOOOOOOOOOOO
OOOOOOOOaOOOOOOOOOOOOOOOOaaoOGOOOOCGOOOOOOOOOOOOOOOOOO
» * » *
» * » »
cr o- (3- c- c> o<
A-47
-------
o o o cs oooooooooooooooooooooooooooooooooooooooooooaoooooo
jKicii'*or-ri-cor»o^-4<-4^4a%a*oooo^raro^uiu^^^^;3oo^."\j«\j.3-j-i'"> T-nj'^ro.-orgv-Mocor^f-
^^^^^^^-H^^^^^^^^.*^^^ojc\j(\jCN4CMfjrgcvojr»jc\j(Njoj^O^CTvOvCr'CrC*CT»C*G*C^C^C^
* * »*o^^c^i^^in^^^^^^^j^^^^*rrj^
»»*»********<*»»**
>-»-»v4*4«Hl
»**
»*»
o o c>cs»-*fOrr>fOj3ta'^J5r^*a- *=f ^^^t-crd-^^
a*a*c*»ocu»-i»H»H * i *-i c\j 10 ro *«-^**#»***»***»*»»****-*»*»*»
fr*^-*****^***^**-*** ******* »****** ft ** »*» ^-* -*»»*****#*# »^H
^*-*»*»*****^ *"*'***'**** *-*<(- f> * * V * » * * * **»**-fr1t»'*-^-f!>**»**«fc>^J^
C^CIsOsCvO^O^^O»O*C7sC^O^^^
33Olrtl*>^*C>Or*U1>{MOiO«-*rO3-J-O^ COvMf^fO O3
i^cuKi^fcfinintnirta-a-iorocjojcy
j^iOrO<^-^oc:!OtnrltnvOCtCtO--K)»nK
o o o ^^P4ruKirisO^r
ii>^o*-fJMro zrinjsr'-.'Ba^
--«»-*--«-H-H^t»^^ii-4
vOtO%<2>o^«a>o^>«o^a<>oo
A-48
-------
o o o
CO f- vO
» » *
* * *
tp c> o>
CO O» O»
* » »
* * *
o> o> o>
CMO O
<\J OJ -1
-< lO *
CM*-!
A-49
-------
Table A-5. CARBON MONOXIDE BAG SAMPLING DATA
Note:
Day of Week: Sunday = 1, Monday = 2, etc.
Hours: Midnight to 1:00 a.m. = 1, 1:00 a.m. to 2:00 a.m. = 2, etc.
A-50
-------
x >
I «:
1C
5:
oa
o
I
^, a, ,* _ ^
o »H^ojcM
-------
Table A-6. AREA SOURCE EVALUATION DATA
Note:
Wind speed is listed in raph.
Wind direction is listed in degrees. North = 0
The receptor concentrations are listed in ppm CO.
A difference is listed only in those cases where the downwind receptor
CO concentration is equal to or higher than the upwind receptor CO
concentration.
A-52
-------
" Station,' 1 Station .'2
Upwind . Upwind
Wird Direction Wind Direction
, .{40°, 50? r6_Q.°.) t (220°', 230% 240°)
Month Day Hour Speed Direction £]_ ' .#£ . Diff. JH -J[2. Diff.
12 17 22 . 1 230 4 10
12 19 23 . 10 40 . 110
24' 8 40 0 1 . 1
12 22 19 12 220 " 330
20 9 .240 . ' 2 2 0
21 10 240 2.2-0
12'. 23 62 60 11 0
7 3 60 .1 21 ' '
82 50 1 2 1
12 .25 14 16 230 1.10
.' ' 16 13 240 1 1 0
17 10 240 110
' . . 19 10 240 211
20 12 - 240 . 2 1 1
21 8-220 2 11
22 11 240 - 211'
12 26 10 2 60 6 5
11 3 50 76.
12 4 60 451.
15 6 ' 50- 462
16 7 60 4'5 1 " ' .
17 8 60 4 5 1 . . .
18 . 7 40 5 4
12 27 4 8 240 . - 0 2
5 7 240 ' 0 2
8 7 240 ' 2 1 1
9.8. 240 ' - ' .2 20
- 12 10 230 321
20 13 240 ' . -'2-20
12 28 . 3 5 220 . . 1 0 ' 1
''.' 19 9 220 2 3
- :-' 20: 8 .. 240 -' - 3 30
. 23 6 240 ' 1 2
A-53
-------
Station #4
Upwind
Month
12
12
12
12
12
12
12
1
Day
17
18
20
25
26
29
30
3
Hour
21
1
2
14
8
14
15
16
17
19
1
2
3
6
19
23
6
7
16
16
Wind
Speed
0
1
1
4
10
12
10
10
10
9
12
8
7
1
4
2
5
6
3
4
Wind Direction
Wind (150° 160° 170°)
Direction '#1
160 5
160 1
150 1
150 2
350
340
350
350
350
350
160 2
160 1
170 1
150 1
340
350
340
350
350
330
#4 Diff.
6
3
2
4
1 1
0 1
1 0
1 0
Station #1
Upwind
Wind Direction
(330° '340° 350°)
#4
2
3
3
3
3
4
3
3
1
2
2
2
#1
3
1
1
2
3
4
4
4
0
0
2
7
Diff.
2
2
1
0
0
1
2
0
A-54
-------
Station #3
Upwind
Wind Direction
Month
12
12
12
12
12
12
12
12
12
12
12
12
Day
17
19
21
22
23
24
25
26
27
28
29
. 30
Hour
23
1
2
9
10
11
12
13
11
12
14
16
18
22
23
9
10
17
23
24
3
18
24
9
1
2
3
6
7
10
13
14
16
21
22
24
1
20
10
13
Wind
.Speed
1
6
6
3
6
6
10
9
4
6
5
5
3
10
10
1
3
12
10
10
9
11
4
0
7
7
7
9
8
9
14
14
18
7
7
6
7
8
7
4
Wind
Direction
250
80
90
90
80
80
70
70
270
270
270
270
270
250
250
90
90
90
90
80
90
250
250
. 80
250
260
250
260
250
250
250
270
270
250
250
250
260
270
250
270
(250,
#3
4
5
5
6
8
12
2
1
2
1
2
2
2
2
2'
3
4
3
4
3
6
2
1
3
2
3
260.
//4
4
4
3
4
5
9
2
1
1
1
2
2
1
1
1
2
3
3
2
4
8
4
2
4
0
1
270 )
Diff.
0
0
0
0
0
0
0
1
2
2
1
li
1
Station #4
Up\vind
"Wind Direction
(70° 80*? 90°)
#4 if 3 Diff.
2
2
4
3
a
2
2
4
1
2
1
0
2
3
3
3
3
3
2
3
3
1
1
1
0
1
0
0
0
1
0
1
A-55
-------
Month
12
12
12
.12
12
12
12
12
12
Day Hour
20 3
4
5
6
7
8
9
10
11
12
13
15
16
17
18
19
21 3
5
9
10
23 5
25 3
4
5
12
13
26 8
23
27 11
28 6
7
8
9
10
11
12
13
14
29 7
30 16
17
18
23
24
Speed
11
11
12
12
11
10
11
12
14
11
13
12
10
10
10
13
4
3
7
1
1
7
9
7
2
7
2
2
8
5
5
5
8
11
12
14
13
13
6
3
2
5
9
9
Direction
10
360
360
360
360
350
360
360
350
360
10
350
350
350
360
350
10
360
360
350
10
170
180
190
180
190
360
350
180
190
180
-170
170
180
180
190
190
190
350
350
360
10
10
360
Station 2 Station 3 .
Upwind Upwind
Wind Direction Wind Direction
(350°..360°. 10°). (170°, .180°. 19Q°)
12 £L 2i£ii I! O- Diff-
1 2 1
1 1 0
1 1 0
2 10
2 1
3 2
3 2
3 2
4 3
440
440
440
550
7 6
7 5
550
121
1 2 1
4 5 1
550
1 1 0
0 1
0 1
0 1
1 2
2 1.1
3 4 1
4 3
2 4
1 10'
1 2
1 . 2
1 2
22 0
220
2 3
2 3
2 4
0 1 1
2 3 1
2 3 1
3 3 0
033
033
(continued)
A-56
-------
(continued)
Month Day Hour Speed Direction
12
31
1
2
3
4
6
8
9
8
9
7
8
6
6
6
350
360
360
10
10
360
350
Station 2
UpNvind
Wind Direction
0
0
0
0
0
1
2
2
2
2
2
3
4
4
2
2
2
2
3
3
2
Station 3
Upwind
Wind Direction
(170°. 180°. 190")
#2 #3 Diff.
Month
1
1
Hour
12
13
16
1
2
6
3
6
4
5
6
3
Direction
350
330
330
330
330
330
Station .2.
Upwind
Wind
(330.°.,.
J2_
3
3
3
0
0
0
Direction
340°,.
11A
4
5
5
1
1 .
1
350° ),
Diff.
1
2
2
1
1
1
Station 3A
Upwind
Wind Direction
(150°. TCP0. 170°)
Diff.
Month Day Ho\ir
4
5
19
2
10
0
1
1
1
2-
Direction
250
250
250
250
250
Station 3A
Upwind
"Wind Direction
(230°..240°. 2501).
£A_ £4 Diff._
1
1
9
5
3
3
3
8
9
3
2
2
4
0
Station #4
Upwind
Wind Direction
(50°. 60°. 70°1
IA
A-57
-------
APPENDIX B
METEROLCGICAL STABILITY DATA
B-l
-------
/
3
3
^
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
..J
3
3
3
T(
3
3
3
^
3
3
3
3
»
}
3
3
3
3
3
;j
3
3
3
. 3
3
3
t
*/ <&/
<$r
22
22
22
^^
22
22
^2
22
22
22
22
22
22
23
23
23
23
23
23
2 1
23
£ O
23
23
^3
i.3
23
2j
23
23
23
23
23
^J
«i J
., \
C. J
i-»
<:4
2s
2'H
*T ^
2<«
2'V
«:+
2w
24
24
24
2'1
24
24
2:»
2M
24
1
2
3
«t
5
I)
7
0
9
'10
11
1?
13
)4
10
lb
17
3*
17
17
17
17
2tt
20
20
20
20
20
20
20
20
3D
3 H
3n
7
P
l!
17
13
13
1?
12
1^
!«*
lf>
J2
10
U
ll
10
10
o
S
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
4
4
3
4
2
2
2
2
2
3
3
4
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
3
.T
3
4
3
4
"A "999" indicates
unlimited ceiling.
B-2
-------
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
24
24
«:4
24
24
24
24
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
25
2?
25
25
26
26
26
26
26
26
26
26
26
26
26
26
26
26
26
26
2o
26
26
26
26
26
26
IB
19
20
21
22
?3
24
1
2
3
4
5
6
7
B
9
10
11
12
13
14
15
1'J
17
Itt
19
20
21
22
23
?4
1
2
3
4
5
6
7
3
9
10
U
12
13
1^
\5
16
1?
Ifl
19
^0
21
22
?3
300
999
M99
090
999
t)9u
99u
999
999
999
120
46
46
200
999
200
2UO
200
200
200
HO
200
200
2UO
2'30
250
250
250
250
2 5 1!
2bO
60
60
250
250
250
60
100
60
250
20
250
25
250
250
2bO
250
250
250
14
lb
14
15
13
14
12
12
12
ll
10
9
6
5
7
7
4
4
4
4
5
1
0
0
0
0
0
0
0
0
0
3
e
2
2
0
6
6
7
7
5
6
7
5
7
7
6
10
10
10
10
in
10
JO
10
10
10
10
u
9
f>
6
6
5
4
P
9
9
9
9
Q
10
a
10
10
5
5
5
5
5
5
5
5
5
5
5
5
u
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
3
3
3
5
3
4
5
5
5
5
5
5
E-3
-------
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2b
27
27
27
27
27
27
27
27
27
27
27
27
27
27
27
27
27
27
27
2'~>0
25U
70
70
bf)
55
45
45
45
45
25
2<4
2°
20
bO
bo
Hi)
flo
3»
33
33
33
45
45
45
45
45
45
3H
33
17
lo
12
0
6
o
5
4
4
5
5
4
4
4
4
4
4
U
3
3
3
3
2
5
f-.
7
4
5
4
2
3
3
3
1
h>
5
8
in
10
10
q
10
10
10
ll
12
ll
10
10
9
ll
10
10
in
H
10
3
6
5
7
in
12
12
13
12
in
10
10
9
10
10
9
fl
>\
8
7
7
5
10
in
10
10
10
10
10
10
10
10
10
10
10
10
in
10
10
o
10
10
10
10
9
o
10
10
in
7
10
10.
10
10
10
10
10
10
in
in
10
in
10
10
10
10
10
10
10
10
10
10
10
10
10
10
5
5
5
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
B-4
-------
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
- 3
3
3
3
3
3
3
3
3
3
29
29
29
2V
29
29
29
29
29
29
29
29
29
29
29
29
29
2y
29
30
30
30
30
30
30
30
3U
30
30
30
30
3u
30
30
30
30
30
30
30
30
30
30
3u
31
31
31
31
31
31
31
31
31
31
31
6
7
4
4
10
Jl
12
13
I1*
3&
16
17
lb
19
20
21
22
23
24
1
2
3
4
5
6
7
3
Q
10
U
12
. X
1 J
I1*
lb
16
17
. &
1"
19
?0
21
22
23
'-ill
<1 *
1
2
3
4
5
&
7
n
9
10
U
1
1
2
2
2
3
3
4
2
3
3
3
4
12
5"S
10
10
il
r-,
7
4
2
1
0
2
7
11
R
5
5
5
c
T
7
6
17
lo
0 C
C ^
24
36
3H
29
25
?s
C J
29
29
2S
23
21
IQ
13
2bO
2bO
250
250
ft
(>
4
4
5
b
6
b
6
7
9
6
4
5
5
7
12
o
6
5
3
3
3
2
4
U
12
11
11
13
7
6
7
9
Q
9
U
o
9
30
10
q
Jl
6
6
6
8
5
3
2
3
3
4
2
10
10
10
10
10
10
10
10
10
10
1'J
10
10
10
10
10
10
10
10
10
10
10
Ifl
10
10
10
10
10
10
in
10
10
10
10
10
iO
10
10
10
10
10
10
10
10
10
10
10
U
7
a
7
7
5
4
4
4
4
4
4
4
4
4
4
4
4
4
4
U
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
. 4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
3
3
2
2
2
2
B-5
-------
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
« .
4
4
4
4
4
4
4
i .
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
31
31
31
31
31
31
31
31
31
.-51
31
31
31
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2 .
2
2
12
33
14
15
16
17
18
19
20
?1
^2
23
?4
1
2
3
4
5
t:
7
a
9
30
ll
1.2
33
I1*
15
16
17
38
19
i'O
21
<2
<>3
£4
1
2
3
4
5
b
7
a
9
i"
ii
12
13
14
15
16
17
250
2bn
2bO
250
250
120
120
250
250
170
170
100
1UO
50
bo
50
50
25il
250
250
100
40
250
250
250
250
2bO
23
ao
Olt
16
23
17
17
17
17
21
2bQ
} V°
o^Q
ogo
V9V
QOQ
SO
bO
220
Q9'J
2UO
200
20u
201}
200
200
200
2
3
4
5
5
8
9
6
9
9
fl
30
10
11
12
33
14
14
34
13
Q
7 '
6
9
9
9
31
9
31
34
39
3Q
36
35
16
15
35
31
7
6
9
8
7
7
6
1'*
17
19
?4
<-4
?5
?3
22
20
6
7
f,
10
10
10
10
R
10
10
Id
in
1" '
.10
10
10
10
4
7
fl
10
10
10
f>
7
10
10
10
10
10
10
10
10
10
10
10
u
2
o
0
0
0
o
2
4
3
0
4
3
5
5
3
R
9
2
f\
r.
0
r.,
3
3
t{
a
c,
4
4
4
4
4
4
4
4
4
[4
4
4
4
4
2
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
;j
^
4
3
4
4
4
4
4
14
4
4
4
B-6
-------
4
4
it
4
4
4
4
4
4
4
14
4
4
4
4
U
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
2
2
2
2
2
2
2
3
6
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
H
4
4
4
4
4
4
4'
1
i*
1
<4
I*
4
4
4
JH
19
?o
21
22
?J
;,"*
1
2
3
4
5
6
7
8
9
10
H
12
13
]4
15
16
17
!«'
19
20
?1
22
23
?4
1
2
3
4
5
6
7
a
9
10
ii
12
13
14
15
16
17
1«
19
.20
21
32
?3
2 'JO
2UO
2UO
2 Ui)
200.
20(j
200
100
200
200
2Ui)
200
200
100
1UO
JUt'l
100
60
13
IP
8
4
250
2bu
uo
36
50
&0
99Q
999
99Q
99^
99Q
23
23
10
o
12
12
12
11
9
12
15
15
16
16
11
10
11
11
6
£1
n
2>1
IP
3"
)2
7
6
6
7
Q
6
2
3
u
4
5
fl
1*»
12
16
J6
15
8
3
6
9
7
0
3
2
2
4
9
H
]2
15
15
?o
19
1"
16
If)
15
9
5
b
7
7
7
1
8
4
5
5
3
a
a
q
10
in
10
10
10
10
rt
9
fl
10
10
10
10
10
10
10
10
10
10
fl
4
o
Q
.3
2
n
0
0
0
0
6
10
10
10
10
10
1C
10
10
10
10
10
10
10
1C
10
10
10
10
10
10
4
'»
4
4
5
5
5
5
4
5
5
5
3
3
4
3
4
4
4
4
4
4
2
4
4
5
5
5
5
5
5
5
5
4
4
4
4
4
4
4
4
4
4
4
4
-------
4
4
4
It
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
U
4
4
4
4
i.
4
4
4
4
4
4
4
4
u
4
4
4
4
4
4
4
4
5
b
5
5
5
b
5
5
5
b
5
*>
b
5
b
b
5
b
5
b
b
r>
b
b
0
6
o
6
i)
f>
u
o
6
b
6
6
6
b
6
o
6
6
D
0
6
6
b
6
7
7
7
7
7
£4 11
1 1"
2 1-;
3 in
4 l«j
b lo
6 3-1
7 3/>
A 2.5
9 23
10 2b
1 1 i."^-
)2 35
13 5-,
1 " S U i
1 i> 2^1
50 2l<>
17 ^.)
)rt 2!-"!
)S» 2b!J
;-'0 2b.i
,'i -*V<-
i 2 -#v-»
2 3 VV"-
>4 -^V'J
1 -»'.-
2 utju
3 W>-<
4 oV-i
fj (jf'j
fi <-i^^
7 --iV^
rt ^^o
n -)V '
ju uV-.
1 1 -><-"-
12 40
J J HO
J 4 4 ..'
Jb <-.'->.>
ifa ??>;i
17 23.-J
Jrf 23'l
l^1 23ti
iO 2JJ
;! 2b,)
i-2 2b.i
? 3 120
<* 2'jH
1 2Su
2 <;bj
3 33
4 3>
b 33
5
6
h
6
6
7
6
5
6
6
6
fi
0
ft
q
q
10
o
7
5
3
2
1
0
0
0
0
0
0
0
11
0
0
2
S
JO
9
q
12
J5
]7
1«
si
1H
JS
]7
IS
l'»
j5
11
l<*
17
11
H
JO
10
10
10
10
10
10
10
10
10
9
q
9
10
to
10
10
10
10
8
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
3
3
10
JO
10
10
10
10
10
10
10
J.O
iO
10
10
10
10
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
3
3
4
5
5
S
5
5
5
b
5
S
5
5
5
T
- 3
?
2
2
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
B-8
-------
u
i
u
u
4*
L.
c*
L,
li
U
L.
it
L,
<»
U
4
L,
Ll
4
fc
LI
L,
L,
1.
L,
t;
'*
14
(4
U
1.
U
L.
L,
L>
LJ
1,
t.
I.
t.
U
L.
U
U
I-
L,
U
U
u
c,
u
1,
(4
4
7
7
7
7
7
/
7
7
7
. 7
/
/
7
7
7
7
7
i
7
j
i.
6
i
-t
,\
,t
f.
ii
0
.i
t>
,J
j
o
j
H
b
Ij
O
rt
t)
21
19 21
?Q 2 '\
f 1 9S
IV. HO
;3 7.'i
,?t 7.J
1 7(i
f. 17
0 17
'» 1'*
t. 21
0 21
7 21
/l d i
V 2 -> 0
) u 2bi)
U ;>'->()
1 2 2 b il
13 40
I1- 40
IS 40
)O 2b
1 7 33
1'i 2 bO
1 ^ 2b )
?' 2bif
i:l i'bj
iri; ?E>0
? 3 2 b il
i!14 ^bfl
1 2 bO
2 2b'»
3 w99
'( o 9 'J
D 60
6 70
7 *>^9
Jl >-)9o
9 ^0
iu tni
1 1 IbQ
H
5
3
?
H
I'1
1 "*
!-3
in
1?
J"/
] .'
1°
1(<
) 7
] f ,
37
17
17
!'
lu-
1°
?fl
f ;>
]<-
]H
lu
Jf*
jil
1'-'
17
j 7
I1-*
1°
1?
17
j 3
1 '"?
U
o
7
^
2
1
1
1
0
5
1
2
2
1
3
.3
10
l-l
10
1')
1 ^
I '
10
!')
1 '
t'1
l-'l
1"
1"
10
JO
1 V
1-1
1 '"
'J
Ll
1"
1-1
1 fl
J ''
y
«<
,"
rt
i»
f-i
^
>)
Q
P -
')
'»
I1"'
I1""'
1')
I1'
1 "
1 "
i"
Is
(»
II
n
u
t,
0
(1
P.
.3
7
4
14
L)
U
4
a
u
u
u
4
(i
fi
4
n
>4
4
U
4
4
4
4
4
4
4
4
4
4
4
4
4
U
4
4
4
4
4
4
'V
b"
5
5
5
5
5
5
5
3
2
2
1
2
2
13-9
-------
u
u
u
1*
u
u
14
14
u
14
u
u
It
(4
14
u
u
4
(J
c.
u
u
4
14
(4
<4
14
4
<4
1+
4
u
u
1*
««
4
t.
u
14
u
4
u
u
u
4
9
V
V
9
9
y
y
9
9
9
9
u
9
lu
10
lit
lu
10
lu
10
10
lu
lu
lu
lu
10
10
10
10
lu
lu
10
1J
lu
lu
111
10
1 1
11
11
1 1
11
11
11
1 1
11
11
11
11
1 1
11
11
11
11
)2
13
I1*
15
IS
J7
J«
19
?o
?1
;>2
/3
t-«»
1
2
3
i*
b
6
7
8
9
10
ll
12
13
1<*
lb
16
17
Id
19
;0
,-1
^2
;-3
;*
1
2
3
t
5
6
7
o
9
10
U
J2
J3
. l'»
15
|t>
17
no
?b'J
^bn
2bi)
11
33
33
fao
fan
MO
00
h.)
oyo
\)9"
oM*-'
^90
uS'-4
uS1^
120
120
2t>0
2h.i
^bn
2 bO
2b,l
Sb'l
2b.)
^bO
2b:l
2bO
lu 1
1 0 '}
HM
H";
vo
Vil
fo
34
).)
nil
bi)
3n
3S
33
33
33
70
b.)
bo
b-»
h-J
bO
bii
bo
.5
S
7
U
6
a
a
5
3
i
0
0
0
0
0
0
1
1
1
1
1
1
?
?
3
5
7
12
1"
31
U
h
fi
s
s
f-
5
<4
K
3
S
n
1'J
10
10
U
JO
JO
<-!
ll
l«
10
l'»
Q
I1
S
u
10
10 .
10
1"
H
4
?
i?
M
|l
II
tj
0
0
1)
1
3
fi
ll'
10
10
l->
I1'1
I1'
JO
I'1
!'.
1!'
)'
J "
1"
1-'
1 "
I1'
I-'
!'-
10
J1'
1'
1"
l-'1
J'l
10
l1-1
J"
1"
i<
u
10
10
10
if
2
2
2
4
H
H
S
5
5
5
5
5
5
b
5
5
S
3
2
2
1
2
2
?.
2
2
3
«4
4
i»
tt
r>
b
5
5
5
4
3
5
5
4
4
(4
4
4
3
4
U
4
4
i*
4
4
B-10
-------
It
u
u
14
14
4
14
U
4
U
U
H
U.
4
I*
u
1,
<*
u
14
14
1+
«4
U
t.
14
U
tt
U
14
14
n
14
14
1*
4
U
t.
14
U
M
U
4
U
u
1*
I;
'4
't
U
<4
M
i*
<»
u
11
11
U
11
11
11
11
12
12
12
12
12
12
12
!«:
12
12
12
12
12
l«i
12
\t
12
12
12
12'
14
12
12
1^
13
13
1 3
13
13
13
13
1 5
13
1 3
13
13
13
13
1 J
13
13
1 5
13
13
13
13
13
13
JH ')0
19 b5
^.j (.0
i-J t>0
22 60
23 70
?'t 70
1 bb
2 33
3 23
<* 21
5 17
h 13
7 13
A 13
4 13
j.i 17
ll 2S
j2 3-3
1 > 3&
1 u 14 1)
1 !> 'i 0
jo HO
1? ul.0
l'i >~'0
J4 230
J-0 230
^1 <4S>'-»
?-2 '-tj"
i-3 99^
i-'» y')Q
1 ')SH
2 S>^9
.> OMQ
u oOq
t, &UQ
o -i y v
7 o-JM
.i -1S)-,I
'} ? b 0
if, 12 ;
ll 1^0
]2 120
i3 2V1
14 2r>'l
llo 2'JO
lo 2'~>0
17 b5
11 10 '»
)rt 10 'I
ro 10 ^
,-o 10 «*
?0 10 'i
pi 9 'i
i 4 6 '*
oq o H
30 9 U
C'4 9 ^
M ^ *
;>6 7 4
^674
18 « <*
15 6 4
]4 2 H
13 0 '»
1304
90S
605
7 U '.>
70S
a o s
705
9 n s
12 0 4
JO 0 3
13 0 4
t5 2 «*
1U 2 4
13 u 3
1333
12 ? 3
jo & 3
10 3 i
9 f> 3
f o n
3 ^ S
7 10 «t
) 4 10 '*
j2 in '»
11 H' '»
10 iu u
7 10 i»
-------
APPENDIX C
SHOPPING CENTER TRAFFIC
AS PERCENT OF TOTAL TRAFFIC
C-l
-------
vD
CO
CO
>-
_J >-
fT ^"f
*4. *-i
H: a
< CO
I U
t > *"/Y ^
n a
'a. a UJ
u. 2: 3
ej CM
c: cvj u
H- V
^H UJ
K Z. UJ
III *"f "" 2
uJ *-L -S
^ try u.
LJ CO O
U
1- >-
o cc «t
2 a
H U.
QL O
CL *
O 2 t*-
X O 1
CO »-i tO
O UJ K>
0 CO
a: cc: u
miii
*lJ UJ
X > H-
< z: <
o n a
>-
a
u.
o
/y
LL.
0
X
>_
3)
CO
UJ
s:
3
2T
O
n
»-
O
UJ
CO
JC
aJ
H-
2
>-i
j_
<^
O
3
»
U. t-*K)rOfOIOK)CM
O
»_,-
r^
^
UJ
o
o:
u
a.
o
CO
I
13
ID
C£ rH K3 lO t-4 CO CM r^ ^" vD r^ d" 0^LOcfrr-lG^ COO^ lO dh f^- vD ^ rH
zc IT* co r** ^ r^* r-iLfiinv£)LOoK)c\i^j*'r-t^cQorO30 r^ct"^ f^
> »-l C\jai)c3'T-lO^OCMrHh">^"K>C\ir-iOr^-irj\i}ir?O
Q£
uJ
1-
J K3 vO t*- ^" d" K) CM
ca
X 2
h- l-«
a: a.
0 Q-
z o
X
CO
-J
^r-tromr-isjc\j[^d-vo^-cj-a\j?±-^r~vD^-r-vDtnoror-
OCT*fiJIV;fl>~i-4.r>;n>j3ifJG:'O.'v:".-r-irOC\lrOff*^l"OCT»cOCO
~»2^"S3^55^SS32;"'0'K>
X.
H)T-)
-------
u.
o
CVIK)C\ICJKJfOct«H
LU
U
cc
Ul
0.
o
c/j
{^
fc J
f^
CO
J >-
2! Q
2
i-t C3
0. Q *d
U. 2. 3.
< C\J
a: c\j u
K~ i£
CD UJ
fy ^"* *jj
t 1 «~r *T?
Ul *-i _s
t-
2 KJ LL
U 03 O
0
t- >-
o c; <
2 Q
1-1 U.
Q. O
Q. d-
O Z !*-
X O 1
W »-l fO
:*: o »
O UJ IO
O CO
c: OL u
fT^ 1 I 1
UJ UJ Ul
^^ J^ i-^
-
d"Occ'«--1r-'OcMr-i cr*
K)d"d"d"K)tOfO«-i cr*
CM
-tJ^o^ou^u^c^'^od-^D^)^-^^c^fO 10
-tc'>c!oj'ji:j-^-(v;r>>-»j3oi'O<7>>-* in
O « Q
c\j
jy
Z: r-
-------
_J
<£
u.
o
ro
Ld
o
a:
ui
Q.
O
CO
CO
n
co
Q
U.
O
o
t-t
u.
U.
a:
UJ
aJ
O
Q-
a.
o
X
an
a r
z H-
CM
CM II
O uJ
Z LJ
< 3
K) U_
CO O
cc <
a
u.
o
o i
O
X
O)
Ui
s:
CJ
LJ
CO
ce
T-! ^ f-l
-o
ON
in
a:
uJ
O LJrOK>r-IOOr~-cOI^-OCMcOr-IOvaOJvD«-lOtO
CVI
K)
i£ O I
o UJ ro
O co
IT IX II
03 jj uJ
O 1-1 Q
I
o
Ji
.
to
CM r-t -H t-4 iH
in
CM
o
CM
ce
Z. «-i C.
O
r-lcH «-lf-tt-tt-lT-li-lf-lCMCM
-------
U.
o
to
o>
CM
cc
Ul
0.
o
00
CO
hi
CO
u
o
X
UJ
X
o
rt rH
2 rO U_
UJ -
O. O
CL *
O 2 ^-
X O I
CM
3-
l-<
vfl
Ul
00
cc
ui
Q.
Q.
o
X
iO
O Ul W >-
O CO
-------
CT»
U.
o
O
ro
U)
O
tr
Ul
a.
o
w
t- <
c/3 a
a.
U-
<
a:
Z U.
Ovi
cc ii
a.
o
o:
ID
O
OQ
W
UJ
in
^>
mvOI^-cOO
rSIO^O«HcOOinr-»ct-
O\D!r>O\DKid-
C\JfOr-lC\l3-CQd-
O
sn
in
*: o i
O Ul K)
O 0-)
a: tr ii
D uJ uJ
X h- t-
-« a
I
O
CVI
d-
f
M
o
X
r-l <\1 IT J
<\j *.\j CM CM
G-6
-------
_J
f<3fOK>rOr<>tOC\JIOCMrOfOrOi-«
r-
CVJ
u
CJ
o:
Ul
a.
o
CO
U.
Ul CO O
U
to
2:
CL
a_
o
X
o
o
c:
x
ui
OT
ce
r>- ui
I H-
m ^
o
ui
en
Ui
i
o
tr
ui
u
o
z.
M
Q.
CL
O
X
to
O 0^
I- r-i
r-t t-l
03
O
vfl
ro
>0
o
vO
CM
CM
3 -
ro * a:
r-l f-l rH
C-7
-------
w
CO
>-
_J
2 -
ID £H
u
LJ
V)
Q£
Ul
^
l-t
^
O « *
o cj~ or> «-f j*
i- d- ca CM
2:
o
X
r-i fO IO LT) UD tO IO lO ^* ^" fO tH tH fO
10 cst vO r^ ^f~ ^o co CD c\i cMd-iO'Oooc\joou3co to
lf>IOi-*C\!(7^OOtr»f~-t-lvOvQCr^^-cOct'CM cM^'a>'Cv-i-";x)ff>d'T^insoc\j^ cr*
\^^* -OO^rOlO^CT^ O' r-"* ^^'OOT4 ^CM^**^" fO CM ?O
«~f CM zj" vfl 0^ O kf) CO i* CO CM F~ vD *-< C\! (Tv ^- IT) vO O
^HH^NHHHH 3
^ i^ ^ ^j ,-4 ,-i «H ^ rt ,_! ^' l*^ CM .M CM
C-8
-------
ro
UJ
o
cr
u
Q.
o
GO
co
n
co
CJ CO
o
CC
UL
O
cn
o
o
x
Z)
o
c\i j- in
cr>
o in in
o
r*-
o
U. 2 00
< CVJ
tr co n
t ^*
O UJ
CC 2 oJ
UJ <£ IS
t-
2 tO U_
U 03 O
O
H- >-
o cr -« LL
O. O
0. d-
o 2 r^-
X O 1
CO i-t vD
o ui ro
O 00
EC QC II
i-O I i 1
ij 1 . 1 f \^l
*: t »
4 3i <
CD >- i *~^
CO
LJ
g;
3
_J
>
^
0
n
H-
O
UJ
CO
Q£
oJ
H-
s
>_
CC
3
I
O
:s
^_
o:
UJ
i-
UJ ^ fO O
ID S_>
Ui
_1 tD
2.
t- >-t
oo a.
?)r-r^=sov)^,j'Vo <\j
-inc\)j'r-H-j'cr>vCc\ioj^'X)«H4"cr>x>oj-^>j\oLn ^Q
r-iojinc3r-ifoi^-u")iOct-c\jtscoojr^«HvDiri CT*
i-tr-lr-l tr-«t-J,-»r-l t-« r-l 3J
a:
5
r-t -! r-l r-l rH rH r-i r-l
A! C\J CM
G-9
-------
vO
f-
CM
,
U
(_>
CC
Ul
a.
u
CO
CO
n
00
u.
o
u oo
<
a
U.
u.
<.
a:
a:
LJ
c\j
cy
a
z
<
u
o
»-
CD ac
LL
o
<;
a
Q.
CL
o
X
co
u.
o
O I
Z3
O
X
to
UJ
s:
^
_»
o
L>
Ul
ro
fO
o
_J
X
1--
Et:
o
ui ro
O CM
CB
n
O.
Q.
O
X
in
CM
«-4
in
o
o
a:
ea
s;
.M C\l CM CM CM
C-10
-------
u.
o
o
»
CM
ro
Ul
o
oc
Ui
a.
o
V)
to
>-l
to
>
_1
<
z
-
»- <
U C/) a
U.
U-
<
a:
CC
U
U!
O
Q-
OL
o
CO
OJ
o
-------
U.
o
»HOjinc\;oroc\itnror--ofOtnin«-«in
UJ
U
en
LJ
0.
o
CO
n
CO
o
t-l
U,
cc
a:
UJ
u
CD
a.
Q.
o
X
CO
09
<
a
CM
CM
Q
-
<.
a
UL
O
O
O
-------
_J
K)K>Cf;rC\J
03
CM
w
o c/3 a
u.
o
o
X
LU
o
a:
LU
a.
o
O
r*
f
r-i r-1
UL a o
U. 2 £
~z
o
t-H
1-
L>
UJ
oo
a:
LlJ
t-
2
>-
e^
O
13.
*-
a:
UJ
t-
li i cO ^^ CD fl CM fO CO iT] (" cj"
CD o in in 3" cr>
U! t-H CM CM
_j (j>
z
f- »-*
00 Q.
< OL
UJ o
X
VI
-J
!-J>»-«CMtnK)^^J5fOsO
OOfOC\JCM«-I^Od' HC\i»H
t CM if vD f O
«H r-i r-4
fo vD r*^ cf^ ro r^- co vo o co CD ^*- o^ C3 CM
vfl J\ {J\ cO ^0 c} o CO fO 0^ fO <~i «t f^ h^
CMfO;}~;J".d".d-tncJ-cJ~K)fOCM r~
ID
[^.Kj^^i^^irj^jxaajoroio d-
O C3 C3 C3 O CJ^ r**~ rH CO r*~ 4j" Ct" vD r4 CD
o K} JD ^* ?o c\* in ,0 c\f cr^ r^ r** to CNJ 10
i Ir-liHi (i IrHMrSiH O
^J
O
X
d- ir- vr, r»-
H r-»
C\J CM
C-13
-------
U.
o
K>
ro
Ui
o
cc
UJ
a.
o
CO
CO
n
co
_J
-
<
Q
CO
UJ
II
UJ
u.
o
>-
CD
UJ
2 _J
O
a:
o
UJ
O
Q-
CL
O
CO
iC CJ I
o UJ ro
o oo
a: tn u
CD UJ UJ
X I- I-
-------
Lu
o
K> (T* -
<£ -« US
U. Q O
U. Z I-
et CM
c: CM ii
H- it:
O LU
a: z u
Ul U.
UJ -
CD o; <
z: o
>-« u.
Q- O
Q- *
O 2 h-
X O I
CO n {^
U.
O
a:
r>
o
X
>-
31
UJ
sr
U
u
V)
x.
uJ
X
o
o
o
LJ
ex:
ui
ID
Q-
O
X
03
X)
O LU KJ
O 00
CZ OC II
CD -U Ul
I
O
o
jC\JCVICMC\J
C-15
-------
cr>
u_
o
CM
cvi
ro
ro
2.
Ul
O
IX
La
a.
u
w
-
cr>cMtoc\jtor;-«-«oro-^o3-ro
OD
CO
fO
10
vO
in
vO
in
CM
CM
o
X
-------
u.
o
*
ON
CM
u
u
a:
UJ
a.
o
00
00
l-l
w
>-
_J
<
2
<
O V)
CO
cu
UL 2 3
< CM
a:
UJ
uJ
u
3
oo
UJ
s:
o
_i
o
Ul
H-
UJ 00 O
u
O (X - u.
CL 0
O. *
O 2 (*-
X O 1
00 >- 0
t- CM
X 0 1
0 UJ fO
O 00
ct ex: it
CD uJ LJ
>-
iJ
UJ
00
a:
i
»-
z
n
>-
-------
U.
O
ID in
CVJ
T-l»OOJK>K)tOK>tHt-lt-«i-4C\]CM«-<
o
CM
UJ
o
(£.
U
a.
o
CO
CO
< Q
t- CO
o co a:
»-» 1}
a. 3 X
Ll_ 2 K-
< CM
Ct CM II
ui
U
2 ro U,
U CO O
O
U.
o
ID
O
V
03
CO
u
UJ
X
13
O
C£ K) CD
x in f**
f- CM t-{
cc
uJ
C\!r~K)OCO^DOvDvDr-{
«-<«-« r-l
^ S^. f-
i-i r-i r-i
CM
\D
O
C3
ro CM
rl
O
O
in
1- >-
CD CC <
2 a
M U.
CU 0
a. *
O 2 h-
X 0 »
CO 1-4 «-l
1- CVJ
^r o t
O Uf K)
O CO
a, cc it
33 u) uJ
X H- 1-
1-1
I
U
UJ
CO
a£
jj
K-
"Z.
>H
>»
<;
3
1
0
X
^~
cr
o
2
2
t-i
0-
0.
O
X
CO
_J
<.
H-
o i-t a
vO
3D
tO
C t-» CV IO ^~
T-l CM (AJ CNJ C\l v\J
C-18
-------
ro
co
co
_i
<
2:
- cc
Q O
co x
X
»-
II
a:
U
UJ
CJ
a.
a.
o
X
CO
o
o
a:
OQ
.-o
CO
a:
u.
o
z.
O
o
CJ
I
U!
!T.
Q
03
00
Ul
_J
O
O
Ul
C/3
I
O
LJ
u.
o
U)
u
o:
LJ
a.
u
CO
X
CO
13
ce.
ui
U CO CU
5J
CD
a.
u.
o
X
* if) so (T> * tH CO
«-l r-« Lfl If) O 3" rl
IO ^- d- K) KJ
vO
o
CM
o
X
C-19
-------
a*
U-
O
t-»K>CMCNJCMCMK>T-lr-»«-«t-«CMC\J«S
CO
v-i
U
U
oi
LJ
o.
o
C/J
co
l-l
CO
U.
O
x
o
o
u_
o
2
CM
U.
II
UJ
Ul
O
ro
CO
to cc
j-
o
Q.
a.
o
X
rH CM
fO rH t-t
O
(M
vfl
< .
H- rH CO d-
O X) in vD
t- CM «-<
i-ltHr-IHr-JCMrVJr-lrHt-i.-l
ca
-M
or
o
X
CVKia-lTvif-CCCT O^CMKld-
r-« rH rH rH r-4 rH rH t-« ^M CM CM CM CM
C-20
-------
CM
U_
o
rt r\
«~tC\irOCMCM»OK>rOC\lrOCMtOWCMH
CM
uf
o
a:
Ul
a.
o
CO
CO
n
oo
<£
Q
U.
O
U tO Q
U- a
u. s
< CM
Gi CM
t-
Q
or z
UI <
l~
^ K)
UJ 03
CD o"
t-t UL
Q. O
Q.
O 2
X O
CO k-«
I-
*: o
o LU
o to
cc 3:
XI
U.
II
^
uJ
Ul
u.
o
O
X
00
CO
5
_l
o
u
d- X.
t- uJ
I »-
CM 2
CM n
I
fO >-
II ~3.
Ul I
t- O
< 3
Q I-
cv
r-
»-{
r-« r-t
Ul
_l
I-
co
Ul
o:
t-
o
CD
a_
OL
O
X
C/J
UJ
03
o
r-l r<
O
03
CO
CM
,-M
tr
i: «- <\
o
x
if .
O «- CV K-.
«H <-) rH t-l
^- ST. \T
cc cr-
O «-* C\, K) d-
v\J CM CM CM CM
C-21
-------
u.
o
rHt-iinininin.3-rOr-i»H
CM
U
cr
u
a.
2 <
< Q
H- a:
o co D
U. O et
U_ 2 CO
< CO
cr cy u
»- i£
O oJ
a: 2 ui
ui < 3
s: >o UL
U! «O O
O
o cr <
2 o
- u.
a. o
a. d-
021^
x o i
co »-i to
>- CM
£. O I
o ui to
O (/>
a: a: u
33 LJ Ul
o M a
a
u.
o
o
x
00
CO
LU
Ul
2 _l
O
i-t X
O
Ul
^
I
o
X
o
o
IO
vO
C3
a:
o
a:
i-
o
to
a.
a.
o
X
a>
K>
in
o
i-lr-li-lf-l
CU
CM
O
CM
a.
i: 1-1 cv »c
o
X
IT v£
cc
-------
CV)
K)
u
o
a:
ui
Q.
to
00
n
co
9-
_J
-
2 <
s o
o co
JL
U.
<.
ir
UJ
CM
H-
<
V)
u
c£
O
u_
o
cc
13
O
00
oo
ui
X
o
13
a:
u
in
ro
CM
2 fO U.
Ul CO O
0
t- >-
ts cc <
2 Q
t-i U.
£3- 0
0. d-
o 2 r-
X O J
V) M ro
1- 00
O UI K3
O CO
tx cr u
(V> 1 i 1
UJ -i-t LU
a: i H-
.
<£
3
O
3
O
UI
-J
1-
co
<
uJ
OC\I fOcOO>COOOiT)CVCr»?OOd"^'(T>lf)d'rO
-------
UJ
0
IX
LJ
a.
u
CO
o
»0
co
l~«
co
o to a
U_ 2 CO
< CM
a; oa it
H- i£
O -aJ
CC 2 aJ
LJ -H X
U
U
CO
QC
UJ
a:
o
X
o
in \o
in to
cc
a.
Q.
o
X
to
rO
-------
u.
o
rtojininmcs-d-3-oj
vO
»
to
UJ
u
tt
UJ
QL
O
CO
co
1-4
to
>-
_J
<
2:
< >-
H- <
<_> CO O
i-t ^
u. a 3
u_ 2 co
< CM
-
CD o: -l UL
0. O
Q. ;f
o 2 r-
X O I
c/J « d-
I- CM
iC U t
O UJ tO
O
en cr u
CD oJ UJ
it: t- i-
-i O
u.
o
o:
O
O
X
CO
UJ
X
CD
cr>
cr
UJ
U
UI
CO
OS
aJ
3
I
O
UJ
*-
CO
ut
to
in
ro
a.
a.
O
X
CO
CM
iO
»O
O
X
r-l CJ tC CT
C-25
-------
u.
o
2
UJ
o
UJ
0.
o
CO
CO
l-l
to
J-
co
u. o
u. 2:
<
a
2
o
s:
CJ II
QC 2
UJ <
»-
2 K>
UJ -i
<
o
to
UJ
2 -I
o
n X
»- H-
cj
ui
K)
O
a:
o
2:
o:
ui
in
CM
i
<£
Q
i
o
Ct
UI
UI
o
U)
a.
a.
o
X
CO
co
vD
r-l l-t --I r-l
vD
CM
in
1-1
a:
r «- cv
o
if. vCP-«.cr>c3i-ict,lro.3-invcr>-e
cr e
rH tM
CV ro
C-26
-------
u.
o
;*
»
r-i
K>
CO
< * >-
I- -
-
O <£. *Z
S Q
M LL.
OL o
a. =r
0 2 f^
X O 1
o
r^*
0
f-l
H-
U
UJ
C/3
cr
ui
t
IS
U
_J
»-
CO
4
UJ
t^ f~j T^ to co ^^ ^*^ vD c\j co vO cr^ *^ -^~ ^o ^* co ^o ^H
T~^ C\J CM PO fO l/^ LO ^^ ^* ij" l^i ^^ zt" fO CM
CD
zr
w
CL
a.
o
X
co
-t -4
r-« CU f. -3- !T,
r- c cr c; -< a
-r if. >x
c/~ o
ex
C-27
-------
u.
o
in
»
K>
UJ
l_)
oc.
UJ
Q.
o
CO
to
co
u.
o
X
o
I- O
U 00 CO
H UJ
U- CJ Z>
U. 2 H-
< CM
o: CM ii
t- X.
Q UJ
K ^ Ul
2 ro u.
Lu! 03 O
u
o a: w- **^_ t> tf~t -*-. /% i
co
in
t~-
CM
CM
vfl
a:
Z.
O
X
cv rr :?
v-lr^«-*r^»-4
c; cr c 1-1 cv re
IM OJ SM CM
C-28
-------
IO CJ
u.
o
CM
o
a:
co
I O
O CO CO
t-l UJ
U. Q O
U. 2 H-
< CM
ce CM ii
I- it
a bJ
X. 2 U
U < 3:
H-
2 fO U.
LJ CO O
O
H- >-
CD cr
_!
O
>
r-t rt
r-l r-t
eo
vO
m
in
to
an
UJ
<
UJ
ce
UJ
o
a.
a.
O
X
in
«
CM
sO
CM
03
cr
ID
O
K; r- in
c;
-------
U.
o
ro
IO
UJ
CJ
(X
U
CL
U
CO
1-1
<
<=C
I-
O 00 2
H ^3
u. a jj
U- 2 3
< CM
a: cj u
s- is:
O
00
U
UJ
H-
2 rO
UJ CO
U
uJ
U.
O
>-
Q
a. o
a.
o 2
x o
:*: o
o uj
O i/)
cc CE.
ZQ uJ
I
r-
CV4
i
fO
u
O »-i O
o
UL
O
O
X
CO
CO
UJ
s:
CJ
UJ
OT
a:
UJ
x
rs
o
CM
in
n x
c:
o
U
o
CD
>-4
a.
a.
o
X
CM
f-
t
O
CO
£0
CM
CM
cv;
in
o
X
c cr o ^ cv fO a-
-t
-------
«-««-ir-it-iC\irOfOrofOiOfOc\)K}rOfOtOfO
CM
LJ
O
K
UJ
a.
CO
l-l
co
_j
o
r-
co
U. Q
U-
-
<.
o
0 I
CO i-l
>-
CJ
UJ
is:
o
o
B£
33
DC
CM
t
KJ
II
Ld
>-
a
u.
o
a:
o
x
33
CO
U!
CO
ID
O
CM
O
UJ
UJ
co
I
o
3
o:
UJ
u
o
a.
a.
o
X
CO
«crrocofs-ot-icococr>«-icr>coh--in\£ifoc\i
o
o
in
\o
a
O t-i
I- CM
rH Cl d" C\J
rO fO CM £
>O X) rO J1
X)
O.
C-
. ->JL
33
CM
- (\J JTi
3- ."
fl
>T>
o
X
IT. v£ f- CC
C r
CM T
CX.
'.\J
G-31
-------
u_
o
u
a:
u
a.
o
v>
to
c/>
< >-
^i ff f"*i
. h~ CO
o o> a:
UL o r
u. z t-
-
ID C£ <
2 Q
»-» U.
Q. O
Q. d-
X O I
CO -« to
H- CM
*: o i
O UJ I<1
O CO
oi a; u
23 jJ UJ
x: i >-
< 2 <
O >-« Q
V-
a
u.
o
13
O
aa
CO
UJ
s:
UJ
CO
cc
aJ
LU
X
O
X
CO
UJ
H-
e
O
o
a.
a.
o
X
-1
<
£T>
LO
in
CM
J--
vO
d"Oin«Hi-li-l'H
3" d'
CVjJx
CM
o
fO
CM
M
O
X
c
iH!
c\j
IT, c: c- cr a- cj r-. cv tf. a
^I rH r-t f-i t-l CM CM CM CM O
C-32
-------
vfl
CO
CO
>-
-J
2 <
-
< C\J
a: cv u
^ ^^
Q aJ
oi -z. u
ill «*r" "~?
LU ^*. _5
I
^ K> u.
liJ CO O
0
I ^_
CD IX -
Q
UL
O
f^?
u.
O
X
03
CO
Ld
5-
IC_.
^
-I
>
"Z.
o
>__!
H-
U
Ul
00
a:
jj
(-
2:
n
>»
r
>
U. T-l i-»»-{r-«CV!<)£\Jf<)IOlOK>{\lfOfOrOfOCa
o
2
u
o
QC
LU
a.
o
CO
X
CD
13
^ f*. fw ?o ^ CS2 CO w^- ^i" O O »^J ,V) r<") 0% CO ^0 ft ^S" cf fO O r-l CM ?O
r~ r-t WK)^~COvOO^Cr^^t-.<^T^'^"^"K)^t*C\JCM
_J CO
5?
A.
> M
co a.
< CL
Ul 0
X
co
_j
j-jOvo^ocMoosOcnoaN'004).. '".-» ^rvi^-criCMj-roincJ-
OU3r^*rOCVJi"OG>/'OJ^J^CrvuTvOXJ ^.vtHOcOr^CM^ OrO *O tD
H «-< ct-^-vOocr^cvjtorocM/OinfOrHfHtocatOro
H r-l r-4 r-l r-i Y-! 4 'H r*4 fH r-f r-l
9
CM
CM
f>-
r*-
i
T^
?
IO
in
in
r-
iH
O
CM
SX.
E>
J to ^
.-* «-*
a c-
c:
ivj
cv rC
oa CM
C-33
-------
u.
o
»-«K5fOd-;i-;i-:±foc\jrOK)fOi
vO
O
ro
u
CJ
C£.
UJ
Q.
u
CO
C/J
l~«
C/J
O C/5 Q
-
CD (X H cr^
t- CM
ii O 1
O UJ K)
O 00
a: ac. u
CD uj aJ
x: >- i-
«=C 2 <
O i-« Q
CO
LJ
S.
D
2
0
>-«
1
o
UJ
to
o:
UJ
h-
2
n
>-
c£
3
t
1-
o:
UJ
t-
uj C-J ^o »j^ ^i~ r**- o o r*- r** »H o t/^ CD cr^ t~t 03 ^* *o CM ^*>
_i «-*mrOij"Uiir)3"ioif)vOf^fOd-(OfO t-i
CD t^-
X 2
H- »-
a: CL
0 CL
2 O
X
to
_
_J
1 CM TH C\lcoin^ocCC\jro»-iK)r^»HcoC\irocoovDtn «-*
10
o:
fl CV
IT vD
CV Ki
IT. vC
cC
CV K)
C-34
-------
in^K>inc\jtr>«-ir>-h-cvjood-
U. r-i r-t «H «HCVJK5OJCJtOrOK)CMfOC\lCMtOK)rH
in
CM
UJ
o
a:
o
w
to
CO
-i
-«
2:
u.
LJ
u
u.
O
et
O
Q.
a.
0
X
CO
:«:
O
o
cr
03
5C
U.
O
O I
CM
i
fO
-
21
CO
UJ
s:
CVI
03
u
UJ
CO
ce
-------
u.
o
to
u
u
C£
Ul
a.
u
w
CO
CO
-f
u.
a:
o
u.
o
>- tr
-
o
U-
O
o i
»-l O
t- fO
o i
UJ tO
en
££ II
CD
LJ
§:
O
n
V-
o
Ul
C/J
a:
X
ID
to
r-t
tr
ui
tD
Ul
a:
o
O >H
I
O
J3
H-
Uia»lf)C\Jr-4K5d-a3(OirirOOCOCOC\JrOlf)rHi-irOaDcOvflOCO
a.
o.
O
X
CO
»- r- rH ro
o in 25 CM
H- d- CM CM
f-i i-l H rH
r-
r-
CM
a:
r* <\ NT 3
O
.-» <-\ r-t 'M CVJ CM CM
C-36
-------
cy
u.
o
UJ
U
a:
ui
a.
o
03
CO
co
-
Q
I
O
ro
i
Q
Lu
O
Z3
O
X
03
CO
UJ
3~
O
CM
O
U
2
I
O
CO
_J
£E
LJ
CD
OL
O
CO
CO
r-
\O
O «~l Q
o ai r~ IH co
o^ .-o
o r- .-o o xi o r- ro
sr> o
K)
o
X
C-37
-------
U.
o
CM
CM
LU
o
K.
U
a.
o
CO
00
i-l
CO
>-
_I
(_> CO 3
u. o z>
U. 2 CO
< CM
a: CM u
i- ic:
Q jJ
CE 2 jJ
UJ «5 3
H-
2 rO U.
Ul CO O
O
J >-
CD QC <
z. a
M U.
CL O
Q. *
o 2 r~
X O I
CO «-H rt
t- ro
it U I
O LiJ fO
o to
tr
-------
vO
u_
o
c\i
ro vfl to LU
UJ CO O
J- >-
O Qi «S
2 O
-4 U-
o. o
Q- rf-
a z. t*-
X O 1
C/3 i-l t-l
»- ro
O LJ ro
O CQ
a: cr: u
CD uJ LJ
O
u.
o
a:
13
O
X
U
s:
CJ
LJ
00
a:
UJ
<£
3
I
O
3:
V-
o
13
CD
LJ
a:
LJ
O
oo a.
CV1 t
OJ C\i JD
*.
J-^0
UD K3
tO
o
X
(O J IT
t cr o tH c\j rr *
tH »-» CM CJ CVJ i
C-39
-------
in
UL
O
cvj
»O
UJ
o
en
UJ
a.
o
V)
O C/D O
u. n
u. H
< CM
a: cv
\r-
I-
H K>
bJ CO
U
ID OC
»-« U.
QL O
CL
O 2
X O
CO i-«
^-
id O
O Ul
o to
a: a:
03 jJ
s:
ii
u.
O
a
u.
o
O
X
u
s:
r>
_j
o
>
X
o
13
m
m
S3
Ul
i-« X
U3
* P1
I I'-
ll 3:
UJ I
K- O
a:
uJ
CD
a.
CL
O
X
C/J
O M O
CNJ
r-
o
CM
M
Q£
~ «-l CVJ tf.
O
X
IT. vC
(\( I*)
IT
r-» r-t l\l V\J CM OU
C-40
-------
d-inmc\j
LJ
O
Q.
w
X
to
K)K>:d-r~vDcO
r-< r-i
«-l«-oa3vOincOK><\J
r-t
CM
in
u. a o
u- 2 s:
< c\i
a: CM u
t- i£
O UJ
IV P" tjl
1 1 J wf »
Lu *A J£
>-
2 "> U.
UJ 00 O
O
1- >-
O ££ -t r-t
it U 1
O (jj d-
O W
cr cc n
rVN 111
UJ ^J uJ
-
J
LU «
_j ID
2
1 »-«
00 Q.
-------
U.
o
r-»rOC\lrOfO3-d-K>C\JKJK5K>;l-»OK)rH
K)
Id
o
t£.
ui
a.
o
CO
l-l
CO
U.
o
X
C3
o oo
»-«
u. o
u. s
< CM
a: -
<.
O
I
CM
o
X
21
CO
LU
o
>
t-i X
vO
o
rH r-l
a:
u
to ujvoroc\ii-ioc\jvOd-od-
u>
z.
K5
CTi
cy
Ul
CO
-J
»
2
ce Q.
o a.
2 o
x
co
O IU
O C/3
£t QC
CD LJ
iil t-
< 2
O >-<
II
UJ
H-
<
O
t
o
C\J t-l
CX3
fO
O
CM
c£
o
x
cv K. ;* in vc
co cr- c. r-< t\' K> ^
C!
vM
-------
vO
U.
o
CO
CM
Ld
(J
ce
O
c/j
GO
>-
_l
<
2
1
o
t-4
u.
UL
a:
LJ
co
o
2
CM
CV
Q
2
G3
>
-
Q
U.
O
<£.
O
X
to
Ul
UJ
O
I-
o ce
a.
a.
o
x
co
O
O
cr
03
U.
o
U.
O
>-
<
Q
i
CM
O
LJ
U
CJ
1
O
O -« Q
o
LJ
13
O
to
K>
fO
T-i .-I
a:
ui
CM tn 1-1
I- J- M
t_> to a.
LJ
-------
U.
o
CM
U
o
(X
Ul
Q.
o
CO
00
I-
o
CO
in
CVJ
CVJ * tO fO
vfl
-------
U.
o
rH«-l«-«HlOrOtO>O*K>rOC\llOfOKJfOCM
CO
CM
U
ce.
UJ
a.
o
CO
CO
CO
>-
_l >-
*T «-r
-
2 ro U.
UJ co o
CJ
K- >-
CD or -
2)
CO
UJ
s:
^>
>
2
o
»-i
H-
<_)
UJ
CO
cc
jj
>-
2.
>-l
j_
<$
O
3
1
X
o
^>
/y pc^ ^*j \Q ^^ (^ f^5 ^J~ rO v£l C5 *~l CJ CM ^^ *^ fO ?~ 4 r*4 ^Vl ^!J ^^ ^^ ci* vO
J^L vp \Q ^^ K^J | ^ ^-. f-"4 ^i co ro ^o ^o fo ^^* co T1^ wO c\j ^jt* C5 j* »o ^o ^y
f r-f cf^"^**r^\DQ^OsDlDP^-?HOcOO^tn\D^OrO
t-i r* fH rH r-4
^._,
cc
UJ
i-
CD o in >J> 'X> fo o *o ro in »o ?o ;* cf o in «-i f- KJ t-i
i.l t-!CMfOd'^-ininfOK)K)^iOd"(OCM
_J 10
z
1 n
co a.
cMcr'>ocr>rvif^33oj>. j-^-ocMfOj- r-io«-ijia)incr»o
o^fs-r c\j^-3-y)f^io^oa")'n\iJd'
> rH d"a")I^OOfOmCM3^OlT(a"C\JKJCO{r>K)(O
00
in
CO
to
V0
O
M
a:
o
x
C-45
-------
Or-ii~«cocMromcT\;j-c\jcMcrkr-cor-;»-»-i»-iroLn-
CD QC -i d-
H-
i; o »
o LJ a-
o co
a: cc: u
CQ jJ bJ
O -« Q
u
LJ
GO
a:
Ul
ae.
o
or
ui
O
in
3.
a.
o
X
V)
CO
«-f
r*-
I
O
fO
O
CM
M
cr
O
X
T-I CV tO 3-
CVJ OJ «.M CM
G-46
-------
u.
o
H-
2:
U
o
C\JK>fOtOrOC\lfOrOOJK>fOfOI'OtO«-l
03
CM
GO
»-i
GO
>-
_J
oo
LL
U.
<
cc
a:
ui
<
o
or
X
CM
CM
O
2
-
Q
*
I
<£
a
O
o:
o
X
00
UJ
_J
o
o
LU
CO
C£
X
o
CM
a:
ui
-------
UL
o
^
ro
(O
M
CO
a
O
U.
o
oc
ID
O
I
ui
u
(£.
ui
a.
o
CO
X
CD
r-
*
o
t-l r-l i-l t-4
UL CD ai
U. 2 U.
< CM
o: -
O Q£ -
S
VJ
r^
>
<
3
O
3.
^-
CD
UI
-1
X
1
cc
o
2
d" d" CM ^0 ^5 t~4 *O CM ?O CJ^
OJJvO^xijUjj-^rOJIJ'd >'»:. "j »-l O J* fO CM 1*5 O i.\l »-l O 3^
H-cMrH cMcr>mcMCT'T-»uii_i^3-f*-cMovjD^cJ"forN-in cr>
o
X
O r-l CO K> 3-
vM CM C\i «.\J C\|
C-48
-------
«Hr-l*-»»-iK)rOC\iK>K)»OK)CMK)rOfO:3-»OTH
o
CO
CO
UJ
s:
X
O
o
Ctvfl
Xin
» CM
o:
UJ
CVI
r--
<
Q
UJ
CO
o
H-
co
-------
co
u.
o
UJ
o
t£
Ui
Q.
w
oo
H-l
00
-
c«> a <
2 a
"-I U-
OL o
Q. *
o z r-
x o i
V) -< \O
i-
s: o i
o LJ 4-
o co
a: cr u
£3 uJ UJ
O M Q
W
UJ
_J
O
IU
00
2:
uJ
<
3
I
O
ce
O
o:
u
o
a.
Qu
O
X
in
V0
TH
CO
t\»
O
X
i-l -» r-t CVJ >.\4 CU OU CM
C-50
-------
Oa3K}r-cOCMvCr--tOvO«-l:}-Cr>.dhr-ICOCVIOinr-IO
!_.... ....................
o
in
K>
ro
UJ
o
o:
UJ
Q.
O
c/i
<
Q
O
v-i
U.
U.
<£
c:
a:
UJ
LJ
O
C/J
O
2
CM
c\i
CO
u
i«:
uJ
< 3
10
O
a.
O
o
ce:
33
O
X
33
LJ
X
CD
O
x r-
vO
in
a:
uJ
CD
fO
o
CVJ
Q.
a.
O
X
U-
O
t*-
I
o
LJ
c/3
-
<. z. <
o >-t a
i
o
OJ
in CM
cr
o
ID v£
O «H CV fO
If ; vC
CT C
CX K)
C-51
-------
u.
o
CM
10
LJ
O
a:
LJ
OL
C/l
CO
i-«
V)
00 Q
Q
U.
O
ce
^
o
X
X
CD
13
O
o >- a
en
f-i
o
». .&
H-
2 to U-
uJ CO O
O
t X-
o a: <
2: Q
-I U.
Q. O
a. *
o 2 r-
x o r
CO >-l (^
r^
iC CJ 1
0 UJ Sf
o to
cr cr u
m i l t l
uj uJ UJ
:£ > t
CO
Ul
5Z
^
-J
2
O
n
1-
o
UJ
y)
cr
uJ
t-
z
K^
>-
*z
3.
0
o:
uJ
\-
'jj CJCJ C\JCCb-OJlv£)K)ocO\Od-C\ICM \O
_J rHlOCOCT'OCT'h-K) CO
CD t-l lO
X 2
»- M
Q^ QL
0 Q.
2 0
X
00
_1
1-1 c\) 1-1 r\j o r- cu
r-i ^S r-« i-l ^ ^t r-i fH J\J >.\| CM
C-52
-------
CO
U-
o
CM
tO
ut
o
IX
bJ
Q.
«t
U
O
U.
o
o
X
X
o
\O CM CM
U_
££
o:
UJ
U
Q-
0-
O
X
co
I II
iC
UJ
U.
o
>-
o
co
UJ
_J
o
U
U
C/3
UJ
tD
Ul
00
<
UJ
U
h-
O K)
o
0.
Q.
O
X
co
co
i£ O I
O Ul d-
O CO
a: a. ii
CQ UJ LJ
Jt I- »-
< «^ <
O >-i Q
I
O
O
O
IO
CO
i-l c-l c-l
a:
i; «-t ex jc 3- in
a
O «-! OS.' K3
v\J C\J C\J OJ
G-53
-------
a-o>vooirt;»-ror-or-i-<(r>;j-or-tod-r-co IJL
so O
on
o
UJ
00
a:
o
X
(0
r>
o
a:
x
\D CO
CM m
i
o
3
I-
a:
i-
2
U
ID
a.
a.
o
X
CO
h- r-l
rt
CO
^
.*
r-t
vO
CO
CO
TH
CM
ra
i£
~ rK CM
O
X
i" Ui
C rH O. K-. ^- IT. vf
o
i^J
OJ »O J-
C-54
-------
O
u.
O
.-i
u
O
f£.
Ui
0.
U
CO
00
_l
<
2:
«I >-
t-
o
X
2 >-
U.
U.
C\J
OJ II
co
UJ
s:
X
u>
:D
o
o:
UJ
a:
ul
u
3
Z KJ U.
UJ CO O
a
O Of. <.
*!. 0
»-« U.
Q. O
Q. d-
O 2 h-
X O I
00 1-1 CO
o
UJ
a:
UJ
oo
O T-( <\l K~i J-
t-» ^1 r-t rS r-* »-l rH CM CJ ^\J C\J CJ
C--55
-------
u.
o
inmcMi'O»-i»-«rMinvovflcr»tninoccir~«oini-i.3-
in
to
o
t£
Ul
CL
U
CO
CO
CO
_J
«=t
o
u.
c:
oc
U
CO
o
C/J
t\l
-t
H-
CO
Ul
O
CM
vn
iH
*
a:
u
CM
o
a>
or
o
Q.
a.
o
X
co
o i-i a
CM
CM CO IO O t-l
CM
CM
O
X
C- C «-<
C-56
-------
U-
O
«-!«« T-t«-t*-lfOK)KjrOK>:3-K>IOrOfOd-;»-rOrH
Ld
O
o:
Ui
a.
o
CO
00
t-l
oo
u co
u. o
u. z
< CO
IT CV1
a '.
IT 2 I
UI <£
a
co
(0
CO
U.
O
u
O CC
z
-< u.
a. o
a.
o 2
x o
C/J -
»-
itr o
o u
o oo
oi u:
CD uJ
U.
o
o
x
00
w
UJ
z.
o
o
u
00
CE
oJ
X
o
r>
o
JO
CM
o
to
ft
a:
Ld
ta
ui
CO
cQejd-i-i
to
m
r-
vD
Q.
o.
O
O i-« Q
I
o
3
O
O
CO
ZJ *H c.
O
X
cr (r
-------
u.
o
in
o d- o o to
(\l(MOO>OvBOrHtnCM;*-va
»S;l-tOCMCMCMC\iCMK>fOlOrO
;f;l-
f-3-
K>
I"-
CM
ui
o
a:
UI
a.
00
o oo
JX
£C
UI
o
oo
2
O
3
I
i U
uJ
U)
X
o
U.
o
C£
O
X
03
00
UI
X
O
o
cc o m d-
X ro t-« vo
vfl
vO
f-
a:
ui
H-
Ul
O
O Ct
U.
o
X-
<
o
tD UlrOCMOCMOCMtO
UI O rt CM
CM d-
CM in
CM tO
to lO
O IO i-*
CM IO tO
-»S to O 3-
p* r*- in in
to
d- »-i
vO
vO
vO
^^ JL.
a.
a.
o
x
U.
o
0 1
u
UI
00
tr
ui
o:
o
a.
a.
o
x
^ U I
O UJ &
O 00
CE. IX II
20 LJ ul
o »-« a
I
O
3
CM
CM CO
CM O
"O-O :3fO(n
.-.-:i)CMoaNo
--'' v/i CM rH IO K)
(T>
K)
IO
a:
IH
-------
u.
o
UJ
u
a.
ui
a.
o
to
CO
>-t
CO
< <£
2 0
< 5O
I- UJ
cj co ,2
-« O
UL 0 J
UL Z 3
-
O (£. -t o
I rt
^ O I
O UJ 3-
O CO
a: ix n
CQ UJ uJ
* »- h-
O I-H C
u.
o
cc
o
3D
CO
Ul
E:
x
C5>
^
O
«-l i-t
ro
vO
»o
in
u
UJ
CO
K
CD
UJ
CO
Ui
CC
UJ
u
(9
Q.
Q.
O
X
CO
co
vO
ON
vO
I
O
or^inin'Oco
CM
Qi
o
C n <\' K: xr LT O h- c: (T O »- <\i K5
C-59
-------
U.
o
K>
2
Ul
O
cc
ui
a.
o
00
to
M
CO
U-
o
X
O
2 -t Z3
U. C3 X
U. 2 H-
< CM
o: CM it
l~ *:
O uJ
CC 2 Ul
Ul U.
Ul CO O
O
H- >-
CD o: <
2 Q
Q. O
OL *
O 2 f»-
X O I
W ++ i-l
t- *-t
X. 0 I
o uj a-
o to
cr a; ii
O - O
o
X
CO
UJ
SI
3
_J
o
UJ
CO
o:
Ul
Ul
a:
o
2
vc
UJ
o
QL
Q.
O
X
CO
ca
JO
m
CO
I
O
<
I
to *-t
K)
K)
KJ
r>
CM
(X
z: «-< w KV d- u:
o
oc cr> o
IP
CM
C-60
-------
U.
o
iH»-ii-tc\ltOCMtOi-OrOfOCMfOK).3-:*-rOr-iTH
*
o
to
UJ
o
a:
LJ
CL
O
to
to
»-«
co
2 -
CD a: <
2 Q
M U.
Q- O
Q. *
o 2 r-
x o i
u.
o
a
to
u
X
o
t-4
co
K)
O
in
o
u
co
cc
UJ
o
UJ
CO
UJ
UJ I
o
CD
2
o.
a.
o
X
to
vO
^
in
vO
^ O I
o uj a-
o co
cr a: ii
33 .J UJ
XL »- H-
< ^ 4
O »-< Q
I
O
2
CM
in
«-i c\j to
in
in .\J
C-61
-------
vD
u.
o
to
ro
U
O
a:
ui
a.
o
co
CO
n
CO
>-
-
<
a
oi
u_
UJ
o
a.
a.
o
X
cr
u.
o
UJ
UJ
LU
O
>
o
h-
I
CM
ZJ
O
CO
UJ
CD
UJ
i-* X
CO
a:
UJ
ce
o
o
I- fO t-J
a:
uJ
CJt-i
a.
CL
o
X
to
rt r-t
r-S
vO
CO
o
o
a:
en
u
UJ
a:
uJ
it
LJ
o »-4 a
3
I
O
rocvj
Kl
CM
a:
rr r^ c.
r- c
c ir- C\. K> a- IT.
f-4 -« 1-4 r-t 1-t «-4
04 .
C-62
-------
in
U.
o
U
U
x.
Ui
a.
o
w
I- <
c_> 05 a
u. n :e
u. ^ u.
< CM
a: CM u
»- ^
O aj
EC Z Ul
u
2 K> U.
UJ CO O
o cr: <
z: Q
»- u.
Q. O
a. d-
o z h-
X O I
C/J -« CM
u.
o
cc.
r>
o
X
Ul
s:
D
_J
O
»- I
U CO
LJ <:
y) uJ
3:
x
o
vO
in
CM
CM
o
a.
a.
O
x
to
O Ul cr
O OT
a: 2: u
CD U J
>«:»-»-
<. z <.
o M a
<£
3
I
O
e£
O
03 r-
K)
CM
UT
d-
M
CM
C£
3
t-l «H r-i
CM
C-63
-------
c\)
u.
o
r-lr-ICVICMCMCMCMfO
UJ
o
t£.
UJ
a.
o
CO
co
u.
o
x
o
*z >-
2 <
< - a
i- a:
c_> to D
1^1 1 T
u. a <
U. Z to
< CM
K. CM II
»- id
Q UJ
K 2 UJ
u -
is 2:
0
X
y.
7^
&
to
UJ
s:
o
j
o
>
2
O
t-i
V-
o
LJ
to
a:
UJ
t-
2
n
>-
<
3
1
O
o:
X
t-
cc.
ul
H-
2
12 UJ
UJ (->
_1
to
X 2
» i-«
CC CL
0 0.
2 O
X
to
_l
*
o
CM
C-64
-------
CM CO
O
t-
Z
Ul
u
h-
«£
U.
O
O
X
03
CO
LJ
£
X
CD
a:
UJ
K.
Ul
O
o
fO
CO
U_
O
u.
o
2i
O
a
I
ro
a.
Q.
O
X
OT
O
o
a:
to
O - Q
O
UJ
CO
DC
UJ
CD
ua
oo
c\j;fr
-------
APPENDIX D
COMPARISON TRIP GENERATION STUDY OF
REGIONAL CENTERS IN CHICAGO AREA
During December, 1973, the traffic volumes at five regional centers in
2
the Chicago metropolitan area were monitored. These five centers
and the days they were monitored are:
Deerbrook Shopping Center, December 15 and 20
Lincoln Mall, December 15
« Old Orchard Shopping Center, December 15 and 26
Randhurst Shopping Center, December 19 and 22
River Oaks Shopping Center, December 28 and 29
The days selected were anticipated to be among the peak days of sales
activity and thus also the highest days of shopping center traffic
generation.
The purpose of the study was to provide an additional data base for
estimating the effect of tenant mix, operating hours and demographic
characteristics on the trip generation rates of regional shopping centers,
The five centers (plus Oakbrook Shopping Center) were selected to pro-
vide a representative sample of regional shopping centers in the Chicago
area.
The location, GLA, tenant mix and mall characteristics of each of
the centers monitored are listed below.
D-l
-------
Deerbrook Shopping Center
Deerfield, Illinois
(Enclosed Mall)
Lincoln Mall
Matteson, Illinois
(Enclosed Mall)
Old Orchard Shopping Center
Skokie, Illinois
(Open Mall)
Randhurst Shopping Center
Mount Prospect, Illinois
(Enclosed Mall)
River Oaks Shopping Center
Calumet City, Illinois
(Open Mall)
GLA:
500,000 square feet
Major Tenants: Montgomery Ward
Turnstyle
Date Opened: 1969
GLA:
Major Tenants:
Date Opened:
GLA:
Major Tenants:
Date Opened:
GLA:
Major Tenants:
Date Opened:
GLA:
Major Tenants;
Date Opened:
1,003,462 square feet
Carson Pirie Scott
J.C. Penney
Montgomery Ward
Wieboldt's
1973
1,123,144 square feet
Montgomery Ward
Marshall Field's
1956
1,096,310 square feet
Carson Pirie Scott
Montgomery Ward
Wieboldt's
1962
1,328,978 square feet
Marshall Field's
Sears, Roebuck
1966
Figures D-l, D~2, and B-3 compare the trip generation rates for the
various centers (including Oakbrook Shopping Center). The centers are
compared only for the days when counts were taken at two or more centers.
The data indicate a wide variation in trip generation rates from
center-to-center even on the same day in the same metropolitan area.
The trip generation rates for the four centers monitored on Saturday,
December 15, varied from 20.38 to 30.18 with Deerbrook Shopping Center
having the highest generation rate. For the two days monitored, Deer-
brook's generation rate averaged 15 percent higher than Oakbrook1s.
Randhurst Shopping Center's daily generation rate was only 6 percent
higher than Oakbrook's but the peak one-hour rate was 21 percent higher
on the day surveyed. Some similarity in the diurnal patterns of these
two centers could be seen. Old Orchard Shopping Center and Oakbrook
Shopping Center exhibited almost identical generation rates, and very
similar diurnal patterns of trip generation. River Oaks and Oakbrook
Shopping Centers had similar diurnal traffic patterns. However, a
D-2
-------
DEERBHOOK
TOTAL
TRIP
GENERATION
RATE
2667
30 IB
OLD ORCHARD 24.25
LINCOLN
JO. 38
SATURDAY DECEMBER 15, 1973
1.00 10.00 11:00 12:00 13:00 1400 16.00 16:00 1700 11.00 1» 00 20:00 21.00 Z2 00 23:00
HOUR I ENDING I OF DAY
o
5
IU
X
w
<3
TOTAL
TRIP
GENERA TOM
RATE
06ERBROOK 3S.99
- OAKBROOK 33.06
THURSDAY DECEMBER 20. 1973
00 10.00 11:00 12-00 1300 14:00 11:00 li.OO 17:00 11.00 1«.00 10:00 21:00 22:00 2300
HOUR I ENDING I Of BAY
Figure D-l. Observed hourly generation rates, Oakbrook, Illinois
D-3
-------
"» 30
TOTAl
TRIP
GENEHATION
RATE
RANOHURST 6O.1I
OAKSHOOK 47.18
SATURDAY DECEMBER 22, 1973
« 00 1000 1100 12.00 1300 It.OO IIOO 16:00 17.00 II 00 l».00 M.OO 21:00 72.00 2J.-OJ
HOUR ( ENDING ) OF DAY
...
TOTAL
TRIP
GENERATION
RATE
OLD ORCHARD 43.23
OAKBFIOOK 4J.74
WEDNSDAY - DECEMBER 26. 1973
tOO 1000 11.00 1200 1100 14.00 15 00 1100 1700 1900 1*00 TO'OO 21.00 Z2.00 i3:00
HOUR I ENDING I OF DAY
Figure D-2. Observed hourly generation rates, Oakbrook, Illinois
D-4
-------
C 1.0
to.,
TOTAL
TRIP
GENERATION
RATE
RIVER OAKS 20.49
OAKBROOK 33.76
FRIDAY DECEMBER 28. 1973
tOO 1000 11.00 1200 13.00 1400 1500 IS.00 17:*0 11-00 H 00 20.00 21.00 22:00 1300
HOUR I ENDING I OF DAY
C 1.0-
- RIVER OAKS
OAKIROOK
TOTAL
TRIP
GENERATION
RATE
46.60
36.70
SATURDA Y.DECEMBER 29.1973
t-00 10:00 11.00 1200 13.00 14.00 1(00 1100 1700 1(00 1»:0» 2000 7100 22:00 23.00
HOUR ( ENDING I Of OAT
Figure D-3. Observed hourly generation rates, Oakbrook, Illinois
D-5
-------
marked disimilarity between generation rates was observed. Oakbrook
Shopping Center had a substantially higher trip generation, rate on
Friday while River Oaks Shopping Center had a higher generation rate
on Saturday.
Without examining potential interactions among operating hours, demo-
graphic characteristics, and tenant mix it is impossible to make exact
quantitative statements on the varying generation rates. However, when
the centers are stratified by GLA, the generation rates are seen to
follow a pattern described previously. Deerbrook, with a GLA about
half that of the other centers, has a higher generation rate. The
remaining centers fall in the same range about a mean value (+ 20 per-
cent about the mean ) when compared on any given day, with the
exception of River Oaks and Oakbrook on Friday, December 28. (See
Figure D-3). The average trip generation rate for Oakbrook during the
March and April period up to the week before Easter is 30 trips per
2
1000 ft GLA, which is the mean value given in reference 15 for centers
of similar size.
D-6
-------
APPENDIX E
HOURLY AND DAILY TRIP GENERATION RATES-
OAKBROOK SHOPPING CENTER
E-l
-------
m
a
r-
in
to
V) <
W I-J~
z 3 o
M O »-
II II II
X >-
10
-
<
u.
O
IO
° s
<
I-
QQ
w
Ul
a:
uj
2
Q
tr
O
-I
o:
UJ
t- tO
z Q
Ul _l
u < ui
-!>-«
_
a. u. _i
a. OC
-
O
t
U.
O -!
a
o
rt
X
w
a.
M
cs
X X X
X
X
CO _
* o
>& ..
-< \O
_
2
*"^
u
OT
U_
o
O
cc o co
CD m en
sc cv «*
< -UJ
o
O
I
t-l»-li-l«~t«-l«-4»-i.-l»-l.-lc\J{\!OJ.
I
CM
CM
aw
«o
E-2
-------
o
vO
10
w <
tn\-\-
ZI30
MO I-
ii ii it
X -I-
,.
in
o
u.
o
<
0
u.
o
s
O
x
60
u
f-
- W
2 O
lU_|
ID e> u.
H
IH H- J
a. u. _i
a. <
o o x
IW40
«/3 3C
O =t
^: o s:
oo
O
K O W)
co in cc
s«: c\ «*
< Ul
O rt W
«M
-J
u
u.
a
Oc-«
o
O
CO
a.
«n
o
VU
i 3
a
xxx
»X
xxxx
II <
OT
<
X »-»-
X O
O
I
KJ
-r~
Ul I
I- O
XCVI
a i
CM
»-t«"t"-l«-*»-Jf-»«-l»-t«-»t-ICMOJOJClJ
-r»
I
O
CM
i
-------
10
CM
CM
«O
10
C/J -
<
0
U.
O
O
I
OT
bJ
<
CC
CC
UJ
n:
O
>-
4
Q
2
CD in a:
jc cv t X M
-» X rt
x x x x «- »-«
<«
a u.
OS
u.
E-4
-------
10
r-
in
T*
vO
-I
W <
w«-»-
H =) O
M O t-
II II II
X »t-
"
E
^
W
O
I-
l-l-
in
I-
O
IO
II
*~
IO
u.
o
J
<
»-
O
u.
O
ce
13
H-
o
XX
>-
CO
uj
i-
«s
ee
t-
O -
o: o 01
CD in ct
it tV <
< LJ
O ^1 W
U-
a
w
o
o
o
w
O-
o:
H-
x
x
x
x
o>
o
n
w
2
a.
o
X K-
XO
O
X
K)
Is-
LJ I
I- -lfHr-lT-<(M(M(M>-
«
aw
E-5
-------
CO
*4
\a
c/> -
<£
H
O
o:
r>
O
I
CD
oo
ui
a:
z
O
o
a:
o
a:
ui
z o
ui _i
-------
to
o
o
ON
o <
OT 1-1-
ZOO
»-l O H-
II II II
X J-
II
sc
U.
O
-
ca
co
u
i-
<
a:
Z
O
CC
U
2
ac
o
H
a
'z
<
o
o:
o
z Q
ui _i
o
-------
in
ro
in
co - a: H-
«t o o
o -I v-
>-
u. <
O I-
C£ Q
r> 2
o < < - a:
on o »-
-I U.
OT o:
LJ U - O
H- >- w w
*t 2: Q II
Of U _l O r* W
<_) i
CD in a: to 10
ic ul UI I I
o <-< co t- in in
< oa cvj
o i i
-------
CM
CO
_J
V) t
V) t- H-
H 3 O
>- O I'-
ll II II
X I-
II
£
3
C/J
U.
O
cr»
.a-
in
o
10
u.
O
<
o
ac
o
IO
<
i~
o
0
OC
3
O
X
>-
m
OT
u
h-
<
a:
2
O
IH
h-
i/)o:
o ec
*: o s:
oo
O
a: o co
a m a:
ic <\ <
X
X »X
X
X)
K>
x
u.
o
o
o
M
a.
x
x
X
O
x
ui i
i- o
< CM
a i
o
< ui
a 3t
a
ui
E-9
-------
CO
vD
in
CM
in
23 O
H O >-
II II II
X -V-
it
JC
3
CO
U,
O
in
<
»~
o
o
o\
CM
Ml
CM
O
U.
O
>-
-_J
o. u- _i
a. <
o o x
XWW
COX
s <
£ o z.
os
O
OC O W
CO in CC
it-<\ <
< »UJ
O t-l W
«M
C»
W
O
O
O
a.
»«
a:
X X X
X
- t^
«t CM
a i
CM
M
U.
l-O
x»
jj
<
X.h*t-
X O
t-
IO
r^
I
l»-
CM
i
CM
O t~
E-10
-------
!O
0*
vO
r-4
in
Z ZDO
M o ^
II It II
x «K-
in
>-
<
0
u.
O
cr
^3
O
X
>-
m
w
a:
o
-1
Q
Z
-------
o
K)
CO
O
in
w <
w t- »-
z u o
MO V-
II II II
x >-
a:
D
oo
U.
o
«t
o
in
\a
VO
Kl
in
01
it
U.
o
>-
<
O
U.
O
O
X
CD
UJ
<£.
O
Q
z
<
Q
«
O
x
10
»-
U I
K- ff>
< CM
a i
CM
<
»-
O
t-
VO
in
CM
ii
CO
t-»x
X »- U.
>« O
x <
h-
O
K>
N
I
CM
i
CM
t/i
E-12
-------
o
in
in
.
<
Q
U.
O
er:
^
O
:=
>-
m
OT
IO
<
Q
o:
o
xx
H I- _J
a. u. _J
CL<
ooi
i -«
o:
X X
to
»O
>ix<
H« >-
xxo
O »
(TOW
cn in o:
i: «\ <
< -LJ
O ->(/}
O
X
r-t-l<-4>-<<-lr-l>H>-ICMC\lC\JCMCM
10
Ul I
t- O
Q I
CM
10
O
I
-------
- X
X
X
o
a:
o
_j
a:
u
fr- W
z: a
u -i
«_>< ui
_i i-«
CO CD U.
fr-
ee
cc
LJ
z
u
i3
M fr- _l
Q_ U. _l
Q- <
o o i
X to CO
W X
~* ff
-J c^
x. o s:
o o
0 -
EC 0 W)
CQ in ce
5C O. <
< . u
O ^ CO
(3
O
CO
O
o
a
T-l
X fr-
X
X X
0*
CO
n
ca
zr
U.
O
X
X »fr- «-<
>» x fr» fr-
X X O
OL
u «
O
X
K)
r-
Ul I
fr- ^
< to
a i
01
d-J>^)r-a3J»oi-«M"O*
i<-«>-liH>-l>-ii-«CMCMOlOlOI
K)
I*-
i
f-l
IO
I
01
>- z
< o
O £
E-14
-------
CM
IO
to <
O t- }-
200
M O >-
II II II
X >-
II
co
UL
o
_l
in
in
OL
O
u.
o
t-
o
h-
UL
O
o
X
>_
CO
co
111
l~
«£
ce
2^
o
w
»-
to
z a
Ul -J
0
»-
U.
C9
to
0 f-l
o
o
«-|
X
co
CL
M
X.
»
o
a:
^
o
X
UJ
1-
>«>»>4>«>1>4>4 XX
IO
in
n
to
u.
o
<
»-
rH OJ CM CM OJ CM
>- u
< a
o >-
UJ
E-15
-------
-
to
u.
o
in
<
»-
o
to
10
CM
II
h-
O
U.
O
a:
o
to
1- »-
<
o
u.
o
a:
o
i
CO
CO
ia
^
o:
2»
o
i-
«s
ce
u
.j
o
or
o
^J
oc.
UI -
h- CO
Z O
U -J
O - Q
< U
Q 3t
E-16
-------
IO
CM
«M
2: z> o
M O H-
II II II
X J
c/j
U.
O
in
o
*4
CM
o
u.
o
-
03
m
ui
H-
-t
tO U-
fO
-
0
a:
3
O
X
X
X
-X
CM
»-x
x
a *
x
x n
xx co
U.
O
<
M Ml-f-
H* XXO
>-4r-4T-<«-4HiM>-1>-lr-IC\JOJC\jr>JCM
d-
r-
»
Kl
i
< X
OH-
I
I-
E-17
-------
in
W < E
V) t~t- 3
2 r> o w
»-« O h-
II II II U.
X »l- O
in
r-
o
CM
CM
U.
O
I- t~
-I
IO H- <
>- K. I- V-
< O 1-0
O _J I- >-
>-
U. < t-
01- I-
>-
0:0-
^ Z I-
O < < CJ vO
n: _i i- \o
Q o v- o
>- o: 01
CO O I- XXX 04
_J U. I- X
V) X >- X
ui u» a x
H- t- OT W « X
< z a x x x 11
o:u_jorf» -x x w
O «S U O 2
Z _l 1-4 O X M
o o o u. ^
t-t -z. -^ xi- a.
»- M t- _i w . o
- .
a: a. < M x i-_j
tuooxo: . x«<
ZIWCOI- M« XH
jj w a: o M M M >* M M o
U> 9 4 *
ie o s: o:
oo 3 r4'CM>o:r:nvor-flr-:o:r»oi-»:\j-o:j'
O O v4i-tr4r4TH»-li~lv-l>-I^OiCMCVtCVJOt
C£ o W I
CQ in o: * *
ic <\ «j r« i^
UJ Ul I »
O «H W I- * =t
-------
vfl
in
GO H- >-
23 O
n O »-
II II II
X »-
z:
U-
O
m
in
o*
M>
*
u.
O
<
Q
U.
0
O
X
>-
m
VI
Ul
CC
U
t-
2:
U
O
C9
cc
o
1-
a
z
»
a. u. _i
a. <
oox
«
u.
O
M o s:
OO
O
a: o w
CD in at
ic cv <
«* - LJ
o
a:
3
O
i
d-
l>-
u i
t- \n
<
a i
«-i»-«»-l«-l«-»'v-l.~l»-lt"
E-19
-------
CM
*
- 3
Z U O W
w O t-
II II II U-
X !- O
O
tt>
- ce »-
to o
O -I >-
U.
o
Q
O - O*
o e> x o
>- tC ----- "X CM
CO O >- H- »H
_l U. X
c/> o:
U U O X
H- »- CO C/> h-
< Z Q II
Qi Ul _1 O ^ « X -t Z ^ » >- U.
i- »-t i- j co ' o
ci Q. UL -I O. X t-
OiO.- M»-_JI
UOOX CCh»' X» >* I- «t
Z X CO CO h- H X X h» K I-
LJ COX 0»XMMKMKM>4» XXMO
j> a tt h-
sc o s: oe
OO a r«CMlO*J»«Or-JO3»Or<-.-«>*JJJ)l^»J»Of-ICMtO*
O - O «-1r4«H<-t>-«rH<-lT-«l-lf-IC\ICMCM
-------
in
vO
in
oo <
co h-H-
Z r> o
n o t~
II il II
x >-
in
a: . »-
< o o
Q -J t-
U. < I-
O H- K
a: o
32 I-H- I-
O < < 01 ' ?»
I _I rl
a o a%
>- ix H *
01 O I- rl
-1 U. X h-
w a:
u ui o i- x
i- t- w w . i-
< ~z. a x x - it
trui-iori* x sa
o < u o x x x z
2 -i »-« o »-i- x>- »-
O 13 19 U. rt X »-
nz "-_JW X»O
!!«(_
.J tna: o » >-» M t* >t w w x M o
J) C3 < j_
i: os: a:
OO rj r4CH(O*invO.^tO3^0rfro-OJ-/lvOS3^0i-l(\JiO*
O-» O rt^tirl^rirl^l^l^OJCVlCMOJCM
o: o co x
en in cc ^r 3.
>t CV. < f- f^
<. « uj u » t
o ^ w >- r~ . r»
<£
01" I
«c o
a 3E
E-21
-------
J
O <
00 >- i-
2 :3 o
M o i-
II It II
x §-
r>
c/j
U.
o
in
o
h-
10
0*
o
*
II
I-
U.
o
>-
-«
ID 13 U.
a. u. _i
Q- <
OOX
:/)
!£
-«
OC
O
x
Ul t
I- <0
<
at
»-xx»
XXX
x >» x
xx
o
LJ
«0
O K-
Ul
E-22
-------
o
in
CM
vO
vt
a.
oc.
oo
C/J
^~
t ^_
«t <£
Z. Q
-
10 a: «
2 Q
»-* u.
Q. O
Q. d-
o z r-
X O 1
00 t-t ro
h" v~l
X. u 1
O LJ >O
O 1/3
ix a: ll
S3 .x! UJ
iC t »
-
2 CO
U) 1
0 2
^}l
o o
2 0
> 1
a. s:
a. o
o a:
x u.
00
Q
2
Z3
O
m
K-
^
O
II
O
^
13
0
ca
2.
K4
u
^
-i
cj
>~
O
t-
II
*
- o
^^ *
CM
0
^4
h-
^
o:
2!
O
n
J
«£
o:
UJ
2 O
UJ
O rH
a.
t*-t
cc
H*
# *
*
+
+
* *
-
in
u
o
o
CO
t|
s, ^
H
-g »
o
o
*»-»»
O
O
O
V-
a:
o
x
E-23
-------
CM
10
II
0.
OL
O
UJ
to
to
2 <
< . o
H CO
O CO K
n 13
u. a x
\i- ~Z.Y-
< CM
Ci CM II
1- ^
Q iblJ
a: 2: iJ
U < 3
z: to u.
U Q3 O
t- >-
CD Z -« Q
X
o
0;
0[ ^^X
a. -«
Q
H- O
-------
o
*
m
in
CO
vfl
»o
Q.
M
o:
o
ui
C/J
U C/i O
u. a 2:
u. 2 u.
-
O CC <£
z a
M U,
D. O
0. d-
o 2 r^
x o i
oo >-« in
f- ^
ii U t
o u ro
O
-------
o
*
in
ON
r-
O
Ul
V)
o.
1-4
ec
t-
>-
_i
n
a
(/)
n
to
>-
_J
<
2
-
<
a
01
3
i-
ct
co
II
'^
jj
s:
|_4
X
0
cc
c.
a.
-
o
o
y-l
O
^
<
CO
M
Ui
»
a
2
2^
O
CQ
1-
^)
O
II
c
H-
U.
«
0
C/3
O
o
c?
f-l
X
w
a.
Hf
fr"
H-
o
fO
o
cc 2 a
2 to U.
uj -
o tr <
23 O
t-\ d.
a. o
CL *
O Z. t~
x o t
W M \O
K- r<
iC O I
O LJ K3
O W
cc ce u
3D Ul ui
O >-i Q
U)
o
23
CM
-------
o
»
in
in
01
oo
CL
00
o oo a
M Z
LL a i>
U- 2 C/>
U.
Ul CO O
O
t~ >-
is a: <
.
Q- O
a. d-
O 2 Is-
X O I
if) n r-
i- ^
bi t_> i
O Ul IO
O If)
a: ac. ll
co ul UJ
o n a
a
UJ
x
o
a:
a o
UJ
I
- II
cc »-
Ul <
O
£Q
O
I-
LL ro
*
O
O
O
O
w
CL
o:
i- o
CM
O
-I
ft
t-
o
ui
* »
O
X
E-27
-------
o
m
r--
in
in
KJ
CO
Q.
co
n
co
o co a
u. o o
u. z s:
< oj
o: oj u
a <-d
a: z ui
ui U.
Ul CO O
U
O CC <
z a
M U.
Q- O
Q- *
o z r-
x o i
CO n =3
>- «-t
is: a «
o ui 10
O t/3
a: c: u
33 Ul uJ
5Z K- H-
O »-« Q
O
Ul
X
o
Q:
QL <=>
Q. rt
M «C
H* C9
o: i
O iU
a: -
O
o
X
E-28
-------
o
in
fO
to
o
\D
10
o
d-
C/J
O.
O
UJ
V)
t~t
to
2 >-
-
< CM
CC -
CD c: -
l-l <
(- O
<
a: K
Li] <
O U
X
a: <
j t-
ui i
U
0) O
Q. s: K-
O. Q O
o re >-
x u. u
U) *
Q
O
03
O
II
O
cn
s
H
II
t-
It.
a
w
o
o
o
ce.
»- o
* *
o
M
I-
OL
UJ
U)
13
a.
t-4
a:
CM
* ft
u
Q
13
O
I-
O
CM
in
r-
II
O
o
.a
o
*
o
h-
O
o
X
E-29
-------
o
0
in
a
in
r-
«o
a.
M
a:
o
LJ
>-
-1
- :*:
a ui
a: z UJ
u -
JZ rO U-
u -
o cc <
2 a
>~« u.
ex. o
Q. *
o z r~-
x o i
CO H< O
H- OJ
2£ U I
O Lj F)
O C/J
a: a: u
33 |