GCA-TR-79-22-G
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Idaho Operations Office
EPA Region X
Boise, Idaho
EPA Project: Officer
John Pfander
Contract No. 68-02-2539
Task Order No. 8
CARBON MONOXIDE EMISSION INVENTORY
AND ANALYSIS OF NONATTAINMENT
IN ADA COUNTY, IDAHO
Final Report
by
Frank H. Renesh
Kenneth W. Wiltsee, Jr.
May 1979
GCA CORPORATION
GCA/TECHNOLOGY DIVISION
Bedford, Massachusetts
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DISCLAIMER
This Final Report was furnished to the U.S. Environmental Protection
Agency by GCA Corporation, GCA/Technology Division, Burlington Road, Bedford,
Massachusetts 01730 in fulfillment of Contract No. 68-02-2539, Task-Order No. {
The opinions, findings, and conclusions expressed are those of the authors and
not necessarily those of the Environmental Protection Agency or of cooperating
agencies. Mention of company or product names is not to be considered as an
endorsement by the Environmental Protection Agency.
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CONTENTS
Sections Page
1 Introduction 1
Definition of the Nonattainment Area 1
Summary 2
2 Emission Inventory Development 4
APRAC-2 Methodology 4
APRAC-2 Methodology as Implemented in Ada County 5
Input Data 7
Emission Inventory 10
3 Parking Lot Emission Inventory 20
4 Worst Case 9th St. Modeling Analysis 26
Input Data 26
Modeling Results 27
Validation 27
5 Analysis of Critical Meteorological Conditions 29
Episode Analysis 29
Relationship of CO Emissions and Concentrations ....... 30
6 Projection of CO Concentrations 33
7 References 40
iii
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FIGURES
Number Page
1 1976 gridded emissions 11
2 1982 gridded emissions 12
3 1987 gridded emissions 13
4 1982 gridded emissions (with I/M) 14
5 1987 gridded emissions (with I/M) 15
6 Emissions inventory grid system 16
7 Emissions inventory grid system - Metropolitan Boise 17
8 Emissions inventory grid system - Boise urban area 18
9 ]MM validation results 28
10 1977 nonattainment area 34
11 1982 nonattainment area 35
12 1987 nonattainment area 36
13 1982 nonattainment area with Inspection/Maintenance 37
14 1987 nonattainment area with Inspection/Maintenance 38
xv
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TABLES
Number Page
1 Facility-Type Area-Type Matrix of Speed and Capacity . . . 6
2 Diurnal Distribution 8
3 Vehicle Age Distribution 9
A CO Emissions (kg/day) from Idling Vehicles in Parking Lots
in Boise, Idaho - 1977 '. 23
v
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SECTION 1
INTRODUCTION
DEFINITION OF THE NONATTA1NMENT AREA
The first task under this contract was a review of existing air quality
data in order to determine the extent of- the CO problem and to define the
area for which air quality modeling will be performed.
In performing this analysis, three data sources were utilized: (1) several
years of CO data recorded at the permanent monitor site on 9th Street; (2) a
study of CBD CO concentrations conducted by EPA during the winter of 1977-1978;
and (3) a study of the Boise urban area performed by the State of Idaho, also
during last winter. Data collected at a new permanent monitoring site located
on Orchard Street were not reviewed as the station was not operating during
the peak CO season (winter) and the State's urban analysis has already estab-
lished this as a nonattainment site.
A review of the 9th Street data indicated, for the most recent 1-yr period,
July 1977 through June 1978, a maximum 8-hr CO level of 18.4 ppm and a second-
high value of 15.9 ppm. During this 1-yr period, the 8-hr standard was exceeded
on 48 days, the majority (71 percent) occurring in November, December, and
January. Maximum 1-hr CO levels exceeded the 35 ppm standard twice during this
period; the highest level was 40.9 ppm and the second-highest 39.5. Review
of historical calendar year data for 1975 through 1978 indicate second-high
8-hr CO levels ranging from 17.5 ppm to 18.3 ppm.
The EPA study provided a high degree of resolution as to the variation
in CO levels throughout the CBD. About 40 monitors were operated for 10 to
20 days, 10 a.m. to 6 p.m., during November and December 1977; all were lo-
cnted wLthin about 10 blocks of the 9th Street monitor. The results of the
study showed 70 percent of the monitors exceeding 9 ppm at least once and
that on 19 of the 20 days, the standard was exceeded at at least one site.
The study also documented that the 9th Street station may not represent the
worst site in the city; a monitor located at Idaho and 8th Sts. recorded a
second-high 8-hr average of 16.5 ppm, 0.6 ppm greater than the second-high
value recorded at 9th Street. The short period-of-record for this monitoring
study suggests that second-high values even greater than 16.5 ppm may occur
at this site.
The CO study conducted by the State measured concentrations throughout
the urbanized area. A total of 46 sites, bounded roughly by 1-80 to the
south, Cole Road to the west, and the foothills to the north and east were
sampled for 1 week each. Exceedances of the standard were documented at all
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traffic corridor sites within the area bounded by I-80N, 1-180, and Broadway
Avenue. Eight-hour levels as high as 25 ppm were recorded. In addition, using
ratios of site-to-concurrent 9th Street concentrations, it was hypothesized
that virtually every traffic corridor and neighborhood site could potentially
exceed standards during the year.
The conclusion of this review is that the CO problem is widespread and
supports the expanded nonattainment area recommended by the Ada Planning
Association and approved by EPA in 1978. The study area of this analysis
should, hence, address this area to the greatest extent possible.
SUMMARY
Using assigned network traffic files supplied by the Idaho Transportation
Department, a wintertime motor vehicle'carbon monoxide emission inventory
was prepared for Ada County and gridded on 625 1-km grid squares. The total
emissions, presented below, indicate that only a sligh^ emission reduction
(4 percent)
Regional
Year vehicle
1982
1987
1976
1982
1987
with I/M
with I/M
(109
0.
0.
0.
0.
0.
CO motor Percent
emissions reduction
g/day)
223
215
167
193
133
(1976
3
25
13
40
base)
_
.6
.1
.5
.4
Urban core
grid emissions
(106
6
7
5
6
4
g/day)
.74
.06
.69
.34
.57
Percent
reduction
(1976
_
(4.
15.
5.
32.
base)
7)
6
9
2
is likely to occ'ur by 1982. A typical motor vehicle inspection/maintenance
(I/M) program can be expected to lead to a total emission reduction of 25
percent by 1982. By 1987, total reductions from 1976 levels are likely to
be 13 percent without I/M and 40 percent with an I/M program. Emission
reductions will be considerably less for a Boise urban area grid, presented in
this table for comparison.
An inventory of emissions from parking lots indicates that such emissions
are, on a regional basis, negligible (2 percent) though significant emissions
do occur in some CBD grids. Parking lot emissions are likely only to be
significant as localized sources, or CO hotspots.
A worst case modeling analysis of the 9th Street monitor, using the
Intersection/Midblock Model1 (IMM) and APRAC-2 dispersion models, indicates
that almost all of the ambient CO at the monitor location can be attributed
to traffic on 9th Street and Main Street. Approximately three-quarters of
this concentration is due to emissions from vehicles queuing at the traffic
signal:;. An attempt to validate the IMM model from 1 month of concurrent
ambicni CO, meteorological and 'traffic data was unsuccessful. Notwithstanding
the poor validation, it is still our opinion that the 9th Street monitor con-
centrations are predominately due to traffic on 9th Street. We also expect
tUat ot.her locations in the CBD will be similarly influenced by traffic on
nearby streets..
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A comparison of CO episodes with preceding nonviolating days suggests that
no major meteorological anomaly is causing the excursions above the standard.
Episodes are apparently caused by a combination of higher "per vehicle" emis-
sions, possible resulting from such factors as low ambient temperature and poor
traffic flow caused by fog, fewer hours of daylight, and reduction in road
capacity by snow; and by routine wintertime dispersion characteristics, in-
cluding low wind speed, low mixing height, and stable atmosphere (temperature
inversion).
Using a statistical relationship which uses traffic, emissions, and loca-
tion parameters to predict maximum CO levels, it is estimated that an additional
12 to 15 percent reduction in CO emissions, beyond that which will be achieved
through implementation of I/M, is necessary to meet the 8-hr standard in 1987.
This reduction represents a best estimate based upon the analysis presented in
this study. Several factors would result in a different range of needed reduc-
tion. Among these are:
• Failure to implement the I/M program described, both with
regard to timing and stringency,* will most likely require
a greater reduction from other control measures.
• The degree of emissions reduction ascribed to I/M has not been
fully proven, particularly at higher altitude.
• The use of a higher second-highest design 8-hr CO level than
the value 16.9 ppm (see Section 6 for further discussion)
would require greater emissions reductions.
• Implementation of the CBD Signal System, which was not
evaluated as a part of this study, will most likely reduce
the needed reductions to some extent.
• Variations in growth assumptions, project committments, and
parking strategies from those implicit in the traffic data
may change reduction estimates.
Evaluation of the possible variance in reduction estimates resulting from
these factors was not performed as a part of this study.
* All automobiles regularly traveling in the study area were assumed to be
subject to I/M.
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SECTION 2
EMISSION INVENTORY DEVELOPMENT
A gridded emissions inventory of motor vehicle carbon monoxide emissions
for the year 1976, and projections to 1982 and 1987 were prepared using a
modified version of the APRAC-2 model.* Projected emissions inventories for
1982 and 1987 were also prepared which assumed the implementation of a motor
vehicle inspection-maintenance program. In this section the standard method-
ology of emission calculation in the modified APRAC-2 model is first presented.
Then the changes in that methodology to calculate emissions in Ada County
are examined. Next the assumptions and input data are described and, finally,
the emission inventory is presented.
APRAC-2 METHODOLOGY2
The principal input data is the assigned traffic network. This is a
transportation planning forecasting model in which the metropolitan area high-
way system is described as a series of geographically coded links. Each link
has assigned to it an estimate of average daily traffic (ADT) and average
speed.
The emissions for a single 1-hr period are then calculated for each link
'.n the network. The hourly traffic on'the link is first calculated from the
ADT and a diurnal traffic distribution. The diurnal distribution describes
the proportion of the 24-hr traffic that occurs in each hour.' Different
diurna] distributions are input to the model for freeway and nonfreeway facili-
ties in each of the following locales: CBD; suburban and core city commercial;
residential; industrial; and rural or other. Thus, depending on the hour of
the day, the type of link, and the location of the link, an hourly traffic
volume is calculated from the assigned 24-hr traffic on the link.
The speed for that hour on the link can be either the average speed
provided on the assigned network or a speed calculated via the capacity-
restraint equation.
Two mode split distributions (i.e., proportion of VMT by light duty
vehicles (LDV), two classes of light duty trucks defined by weight (LDT1 and
LDT2), heavy-duty'gasoline powered trucks (HDV-G), heavy-duty diesel powered
trucks (HDV-D), and motorcycles (MC) are input, one for freeways and one for
nonfreeways. Each modal split for each link is thus designated depending on
the type of link.
* Tine A I'RAG-2 model modified to incorporate the MOBILE1 emission factors.
4
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Twelve cold-start hot-start mixes* are input to the model, describing
the vehicle operating states for four time periods (viz., 1800 to 0700, 0700
to 0900, 1000 to 1600, and 1600 to 1800) and three locales (viz., downtown,
suburban-commercial, and residential-other). Thus, depending on the time of
day and location of the link, a cold-start hot-start mix is assigned to each
link.
The remaining data necessary for the calculation of emissions do not vary
among links or depend on the time of day. They are input separately to the
model and are thus constant. These data include calendar year, ambient tem-
perature, the vehicle age distribution, the vehicle mileage accumulation dis-
tribution, and the optional correction factors for air-conditioning, loading,
trailer towing, humidity, heavy duty vehicle engine displacement and load,
and the parameters of an inspection-maintenance program.
All the necessary data for the calculation of emissions using the MOBILE1
emission factors is consequently available for each link for the hour of
interest. Once the emissions for each link are calculated, these emissions
are assigned to a grid square on the basis of the coordinates of the end-
points of each link. Links spanning grid square boundaries are apportioned
among the relevant grid squares on the basis of length of link in each grid
square.
APRAC-2 also provides for the calculation of emissions from vehicular
traffic that is not on the coded highway network. This is principally traffic
on minor streets that are too numerous to code individually. Two options are
provided. The first inflates the traffic in each grid square by a specified
percentage unique to each grid square. The second inflates the traffic in
cacli grid square by an amount that is a function of the locale of the grid
square (e.g., CBD, commercial, residential, industrial, and rural-other).
APRAC-2 METHODOLOGY AS IMPLEMENTED IN ADA COUNTY
t
Application of the Ada County traffic files required that several as-
sumptions be made concerning street locations and usage based upon APA's
facility/area type matrix as presented in Table 1. Area type 1 facility
type 1 corresponds to ramps. Area type 1, facility types 2 through 5 are
one-way streets. Area type 1, facility type 6 are interstates. Area type
2 are centroid connectors. Area types 3, 4, and 5 are two-way streets.
The lack of area-type index numbers impairs APRAC-2"s treatment of
diurnal distribution and the cold-start hot-start mix. This is especially
critical for the cold-start hot-start mix, since these proportions show
* Vehicles operating during the period from startup until the stabilized
engine temperature is reached emit CO at a greater rate than when stabilized.
Those vehicles starting with the engine temperature equal to the ambient are
said to be cold-starting. Those vehicles which have been not operating for
a short time and are, thus, still somewhat warm are said to be operating in
a hot-start mode. The mix of vehicles in the three classes (cold start, hot
start, and stabilized) is an important parameter In analyzing emissions.
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TABLE 1. FACILITY-TYPE AREA-TYPE MATRIX OF
SPEED AND CAPACITY
Facility type
1
25.0"
1 (550)f
2 15.0
10,000
Area 15.0
type (525)
30.0
4 (825)
, 45.0
(1,025)
2
20.0
(650)
17.5
(525)
32.5
(900)
47.5
(1,050)
3
25.0
(650)
20.0
(525)
35.0
(925)
50.0
(1,100)
4
30.0
(700)
22.5
(600)
37.5
(950)
52.5
(1,150)
5
35.0
(900)
25.0
(675)
40.0
(975)
(55.0)
(1,150)
6
53.0
(1,750)
27.5
(750)
42.5
(1,000)
57.5
(1,175)
t
Average speed (mph)
Lane capacity (vph)
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considerable variation by location, especially between the CBD and residential
areas. To preserve the discrimination between these areas in APRAC-2, it was
assumed that all of the one-way streets are located in the CBD and the two-way
streets are non-CBD. While this assumption is not totally accurate, it is our
judgment that it is preferable to the alternative of using a single cold-start
hot-start mix.
Consequently, area type 1, facility types 2 through 5 on Table 1 were
assumed to be located in the CBD. The remaining nonfreeway links were as-
sumed to be non-CBD. All freeway facilities were also assumed to be non-CBD.
The other significant change concerns the calculation of daily emissions.
The most rigorous method of calculating emissions for a 24-hr period would
be to calculate emissions for each hour and then sum over the entire 24-hr
period. The resources to perform this calculation were not available. Con-
sequently, APRAC-2 was executed once with the diurnal distribution factor
effectively set equal to 1.0. In other words, the entire 24-hr traffic volume
was treated as 1 hour's volume. (This was done only for the execution of
APRAC-2 for the preparation of the emission inventory; when executed as a-
dispersion model to predict intraurban background or mesoscale concentrations,
hourly traffic volumes were used.) The midday cold-start hot-start mix was
specified for the emission calculation.
INPUT DATA
Traffic assignment data used in this study were those supplied by the Ada
Planning Association (APA). These data represented the base planning network
plus, for projection years, those projects committed by the APA Advisory Com-
mittee. No modal split was assumed in these data; all trips were completed by
private vehicle with average occupancy of 1.2 persons. The impact of the CBD
sLgnalization improvement program was not reflected in this analysis.
The diurnal distributions shown on Table 2, based on data obtained from
the Idaho Transportation Department (ITD) permanent ATR stations, were used.
The vehicle age distribution shown on Table 3, provided by ITD, was used.
The national average mileage accumulations rates were used.
Based on the 0 and D classification data, obtained from ITD, the follow-
ing vehicle mixes were derived:
LDV LDT-1 LDT-2 HDV-G HDV-D MC
Freeway 68 .'0 8.6 8.6 14.6 0.2
Nonfreeway 67.5 12.9 12.9 5.7 0.9
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TABLE 2. DIURNAL DISTRIBUTION
Ending
hour
1
2.
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Freeway
Inbound Outbound
(%) (%)
0.7
0.5
0.3
0.3
0.8
2.0
3.2
4.1
3.2
2.3
1.6
1.8
1.8
1.8
2.5
3.2
3.6
3.6
2.7
2.2
2.0
1.7
1.4
1.2
0.8
0.5
0.2
0.2
0.7
1.5
2.8
2.9
2.8
2.2
1.9
2.2
2.7
2.2
3.0
3.8
4.4
4.4
3.3
2.3
2.0
1.8
1.6
1.3
Nonf reeway
0.84
0.53
0.25
0.16
0.17
0.40
1.58
6.70
6.06
4.82
5.14
6.42
7.61
7.08
6.95
7.34
8.67
9.22
5.58
4.21
3.22
3.07
2.40
1.62
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TABLE 3. VEHICLE AGE DISTRIBUTION
Vehicle age (years)
6 9 10 11 12 13 14 15 16 17 18 > 19
LDV 0.043 0.086 0.087 0.066 0.083 0.090 0.086 0.069 0.0b5 0.062 0.33- J.047 O.C~0 C.035 3.CCS 0.?:? ?.?!* 0.008 0.006 0.004
LDT-1 0.036 0.081 0.080 0.065 0.077 0.094 0.083 0.057 0.060 0.059 0.031 0.042 0.042 0.033 0.033 0.026 0.021 0.015 0.016 0.025
LPT-2 0.036 0.081 0.080 0.065 0.077 0.094 0.083 0.057 O.OoO 0.059 0.031 0.0,: 0.04: :."S 0.0:2 0.026 0.021 0.015 0.016 0.025
HDV-G 0.096 0.069 0.067 0.107 0.130 0.102 0.062 0.057 0.063 0.042 0.037 0.037 0.028 0.018 0.016 0.0i<. O.Oui 0.008 0.006 0.024
HDV-D 0.095 0.093 0.057 0.102 0.119 0.096 0.061 0.054 0.063 0.044 0.037 0.038 0.033 0.023 0.016 0.014 0.008 0.008 0.007 0.039
MC 0.030 0.074 0.079 0.134 0.135 0.144 0.108 0.094 0.075 0.050 0.030 0.024 0.023
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As discussed previously, the average speeds on each link were obtained
from Table 1, without further adjustment for capacity restraint.
Based on GCA's experience elsewhere, the following cold-start hot-start
were assumed:
CBD Non-CBD
Night
Morning peak
Day
15 /
10 /
5 °,
5 5
20 J
', C
1 H
I C
I H
I C
15 /
7 /
42 5
5 5
35 5
$ C
2 H
£ C
1 H
£ C
Evening peak 60 % C 13 % C
20 % H 7 % H
A linear interpolation between low and high altitude emission factors
was made, based on a low altitude reference of 500 ft, a high altitude refer-
ence of 5,500 ft, and Boise's altitude of 2,700 ft.
Consistent with the average January minimum daily temperature, an ambient
temperature of 22°F was used. However, the choice of a specific temperature
should not significantly affect any conclusions as to the degree of control
necessary for attainment of standards.
Where an inspection-maintenance program is assumed adopted, the following
parameters, typical of I/M programs presently being planned in the U.S. were
assumed: Implementation will begin in 1981, a mechanics training program will
be required, a stringency of 20 percent will be adopted, and new vehicles and
and vehicles over 12 years old will be exempted. The program will apply to
LDV, LDT1, 'LDT2 and MC.
All secondary traffic was assumed to be accounted for through the centroid
connect ors.
EMISSION INVENTORY
The emission inventory of traffic on the assigned network, based on the
assumptions detailed above, is presented below as regional totals and shown on
a gridded basis on the following five figures. Emissions in these figures are
in grams per day and are presented in scientific notation. Hence, an entry
0.170E-I-06 represents 0.17 x 106 g/day of CO from the grid. The gridded emis-
sion inventory is based on a 1 km by 1 km grid system whose origin is 319100,
660200 in the traffic network coordinate system. Maps of the grid square
network are presented as Figures 6, 7 and 8.
10
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-------
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-------
IDAHO TIAJBFOtTAttO* DZ?*.tTWIirr
N-Aj>miM co: i tow
co: i tow
BOISE MET1OTOLITAW TtAtSFOBTATION STUDY
ADA COUNTY WIOI
HIGHWAY M7TWOKK MAP
Figure 6. Emissions inventory grid system.
-------
HUM ini»ii iHII»
nAJimM MC-I
•czn MiTaorotmji TI imm
^
Figure 7. Emissions inventory grid system - Metropolitan Boise.
-------
OO
-•14
Figure 8. Emissions inventory grid system - Boise urban area.
-------
Regional CO motor Percent
Year vehicle emissions reduction
(109 g/day) (1976 base)
Urban core
grid emissions
(106 g/day)
Percent
reduction
(1976 base)
1976
1982
1987
1982 with I/M
1987 with I/M
0.223
0.215
0.167
0.193
0.133
3.6
25.1
13.5
40. A
6.74
7.06
5.69
6.34
4.57
(4.7)
15.6
5.9
32.2
19
-------
SECTION 3
PARKING LOT EMISSION INVENTORY
The VMT on the assigned network consists of trips between specific origins
and destinations. It does not consider the terminal times, that is the time
spent parking or unparking a car and walking to one's destination. Consequently,
it is of interest to estimate the quantity of CO emissions occurring in park-
ing lots, since these emissions are not adequately reflected in the network
based emission inventory.
Due to the interest in this subject, it is appropriate to identify the
appropriate use and limitations of this section. The emission inventory pre-
sented here was compiled to complement the regional emission inventory described
in the previous section. It may be used to estimate the total emissions from
parking lots in the region and, with less confidence, to identify those grid
squares in which parking lot emissions are a relatively larger proportion of
total emissions than other grid squares. Because of the data and methodological
limitations described in the following paragraph, these data cannot be confi-
dently used to estimate the magnitude of parking lot emissions in a single grid
and it would be entirely inappropriate to use the following data to estimate
the emissions from a single parking lot. The emissions from a single lot or
small number of lots can be estimated very adequately by using the Indirect
Source Guidelines (ISG), which is based on a more detailed methodology, or the
ISMAP model; a computer model based on the Indirect Source Guidelines. These
techniques also allow one to consider the impairment of traffic flow on adja-
cent streets by vehicles entering or exiting from a parking facility, a con-
sideration which is not addressed in this section. One may view the distinction
between the parking lot inventory presented in this section and the more de-
tailed techniques such as the ISG as similar to the distinction between meso-
scale CO models (e.g., APRAC-2) and raicroscale CO models (e.g., IMM).
Emissions from parking lots are principally a function of the time required
to enter the lot, search for an available stall, and park the vehicle plus the
time spent idling after starting, and then exiting from the lot. These times
are greatly influenced by the lot and entrance/exit capacity and demand. Other
important parameters affecting emissions include the speed of vehicles in the
lot and the proportion of vehicles in cold, hot, or stabilized running modes.
All of these parameters can be expected to display considerable variation among
different parking lots as well as with time of day. Almost all of these param-
eters were unavailable for this study; the only available information was the
total capacity and a single estimate of occupancy of the principal parking
20
-------
facilities in the Boise metropolitan area.* Consequently, a method was de-
vised, described below, to estimate the average vehicle's running time from
lot capacity and demand. Certain cold and hot start proportions are also
assumed. The resulting estimates should, as previously discussed, be viewed
as an approximation.
The methodology that was employed can briefly be summarized as follows.
Based on the number of parking spaces in a lot, the area of the lot was esti-
mated. The average travel distance from a parking stall to an exit or entrance
was then taken to be a function of area. With an assumed speed, this distance
can be converted to the amount of time a car is running in the lot. After
adjustments for near capacity situations, the time estimate can be converted
to an estimate of vehicle emissions. Total emissions are then estimated from
the average lot occupancy and the turnover of parking spaces.
Specifically, the area for the parking lot in square miles was estimated
by
C * 350
(5280)2
where C is the lot capacity in vehicles and an assumed 350 square feet of
stall and aisle area per vehicle.
The distance a vehicle travels from a stall to an exit or entrance is
then estimated as
C * 350
(5280)2
where the radical is the length of a side of a square whose area is equal to
the lot area. A vehicle is conservatively assumed to travel a distance equal
to two sides.
Assuming a vehicle speed of 15 miles per hour, the time between unparking
the car and exiting, in seconds is then
2 * 3600 .. 1C * 350
(5280)2
To account for congestion and delay because of near capacity, this expression
is adjusted by a factor which effectively doubles the time estimate at near
capacity situations,
2 * 3600 1C * 350 F, . /V \ 2
15 (5280,2
where V is the actual occupancy of the lot in vehicles.
* As supplied from the EPA project officer and derived from several CBD
parking studies and a survey of non-CBD facilities.
21
-------
Finally, 20 seconds io added as a estimate of idling time while parked
in the stall,
T . 20 + UL3600 /cZHr /y\2
15 T (5280)2 L \ / -
Total parking lot emissions are then estimated by
E=TFIVX+TF0VX
where T and V are defined as before, X is the turnover of parking spaces per
day and Fj and FQ are the idle emission factors for entering and exiting
vehicles, respectfully. Turnover is assumed to be related to lot use, viz.,
Lot Use X.
Employment 1
Shopping Centers 5
Fast Foods, Drug Stores, etc. 10
Miscellaneous 3
The emission factors vary between entering and exiting vehicles because of
varying hot/cold start assumptions, viz.,
Entering Vehicles 100% stabilized
Exiting Vehicles, Employment Lots 10,0% cold starts
Exiting Vehicles, Shopping Centers & Miscellaneous 50% cold/50% hot
Exiting Vehicles, Fast Foods, Drug Stores, etc. 100% hot starts
Following the above methodology, total CO emissions from the major off-
street lots is 5488 kg/day, as shown in Table 4. This a negligible amount on
a regional basis, since the parking lot emissions are 2,4 percent of the net-
work emissions, 0.223 x 109 g/day.* One may conclude that control measures
principally targeted at reducing emissions in parking lots do not have the
potential, on a regional basis, of significantly improving the ambient CO
concentrations in Ada County.
However, this statement must be-qualified by several significant con-
siderations. First, major parking facilities and associated congestion on
* After the completion of this study,, the EPA project officer determined that
a considerable number of CBD parking lots were not included in the original
data supplied to GCA. The emissions from these lots indicate that parking
lots may account for up to 20 percent of the emissions in the CBD.
22
-------
TABLE 4. CO EMISSIONS (kg/day) FROM IDLING VEHICLES IN PARKING LOTS
IN BOISE, IDAHO - 1977
to
u>
Xc.
la
c
d
e
t
g
h
i
j
2
3
4
5
6
7
8
9
lOa
lOb
11
12a
b
13
14
15
Locst ion
K-Mart
Shoreline Center
Post Office
Graybar Electrical Supply
State Liquor Store
Offstreet diagonal parking
Rocky Mountain Bank Note
Shoreline Plaza
European Health Spa
Franklin Shopping Center
Patti Plaza
Hillcrest Shopping Center
Uaretnart
Overland Park
Westgate Mall
Two Westgate Plaza
Collister Shopping Center
Albertson's customer
Albertson's employee
Hevlet t-Packard
Village Shopping (North)
Village Shopping (South)
Five mile plaza
Country Square
Bishop Kelly B.S.
CsDacity
(vehicles)
699
•. - 2
247
20
15
60
i3
34
63
462
252
1194
306
716
941
218
389
259
136
1100
185
657
ill
438
312
Volume
(vehicles)
260
172
247
15
5
30
i5
34
47
:S5
252
478
61
539
S47
218
350
233
122
1100
139
263
206
110
78
_ . Running Entering CO
Turnovers/ " r
Tine esisslon factor
y (sees) (g/sec)
5
1
3
3
10
1
1
1
3
5
5
5
5
5
5
1
5
5
1
1
5
5
5
5
1
^ i
14
64.
73.
31.
27.
36.
42.
39.
41.
62.
74.
88.
50.
91.
114.
70.
18
61
46
88
32
47
82
83
01
42
00
17
94
21
43
22
30.71
69.
55.
132.
56.
70.
63.
57.
51.
52
90
82
14
57
10
82
92
0
0
0.
0.
0,
0.
0
0,
0
n
0
0,
0.
0
0.
0.
0.
0.
0.
.43
.43
..3
.43
.43
.43
.43
.43
.43
.i?
.43
.43
.43
.3
.43
43
43
43
43
0.43
0.
0.
0.
0.
0.
43
43
43
43
43
Exiting CO
effllssion factor
(g/sec)
1.22
1 22
2.01
1.22
1.22
0.43 r
2.01
2.01
2.01
1.22
1.2?
1.22
1.22
1.22
1.22
1.22
2.01
1.22
1.22
2.01
2.01
1.22
1.22
1.22
1.22
1.22
Entering CO
emissions
(kg/day)
43.45
4.78
23.41
0.62
0.59
0.47
0 . S3
0.58
2.49
24.8?
40.09
90.61
6.68
105.70
208.38
6.58
60.74
34.83
2.93
62.82
16.78
39.90
27.95
13.67
1.74
Lilting CO
er-.i ssicns
(kg/day)
123.28
^ AQ
j . UO
66.41
1.75
0.59
2.20
0.47
2.72
7.05
70.44
113.75
257.09
18.96
299.88
591.23
30.77
172.33
98.81
13.71
293.67
47.61
113.21
79.29
38.80
4.94
Total CO
emissions
(kg/day)
166.73
6 87
27.12
89.82
2.37
1.18
2.67
1.30
3.30
9.54
95.27
153.84
347.70
25.64
405.56
799.61
37.35
233.07
133.64
16.64
356.49
64.38
153.12
107.24
52.47
6.68
(continued)
-------
TABLE 4 (continued).
::o.
16
17
18
19
20
"21
??
23
24a
24b
24c
25
26
27
28
29
30
31
32
IccaUc-
Borah K'.S.
Capital 'H.S.
But trey-Osco
Grand Central
Capitol Mall Cocplex
Federal Building
Boise City Hall
State Employment
Boise State 1*. reserved
Boise Par^it
Boise Stadium
5oi5i Casciii
tor r is-Knucson
Park Center Development
St Lake's Hospital
Idaho 1st STC Sldg.
Mountain Bell
Idaho Power
Sears
C-apaci t y
(vehicles)
650
"57
171
553
525
430
192
237
650
1000
2000
-Ij
600
S30
573
338
SI
137
428
Volume
(vehicles)
650
757
154
292
660
344
154
190
520
SCO
500
326
640
664
458
270
55
110
342
_ , Kunnine Entering CO
Turnovers/ 6 . *
Ti^e emission tactor
-av , , .
(sees; \^ • sec '
1 IIS
1 113
5 60
5 71
1 100
1 77
1 58
1 62.
1 91.
1 10S.
1 100.
1 73.
1 96 .
1 100.
1 86.
1 71.
1 45.
1 52.
5 77.
. 1 7
.59
.25
.33
.11
.84
.65
.94
.11
.20
.81
.io
69
36
77
28
10
65
70
0.
3
0.
0.
0.
0.
3.
0.
0.
j.
0.
j •
-J.
0.
0.
0.
Q
0.
.43
.43
43
43
43
43
43
43
.43
43
" J
-;•
- 5
43
43
43
43
43
43
Editing CO
emission factor
2
2
i
1
2
2
2
2
2
2
2
1
2 .
2 .
2
2.
2 .
2.
1,
.01
.01
.22
.22
.01
.01
.01
.01
.01
.01
.01
. 01
.01
.01
.01
.01
.01
.01
.22
Entering CO
emissions
-3
36
19
44
23
11
3
5
20
27
2i
1C
27.
28.
17.
6.
1.
2,
57.
.56
.97
.95
.73
.41
.51
.88
.13
.37
.22
.67 -
.79
. 21
.65
,09
.28
.-(•
49
,15
Exiting CO
emissions
(kg.'^ay)
203
172.
56.
127.
132
53
18.
23
95
173 .
101
5u
127.
133,
79.
38.
5.
11.
162.
.60
.33
.60
.06
.81
.82
.15
.99
. 23
.99
. =2
.,2
,21
94
,88
68
69
,64
12
Total CO
emissions
(kg/day;
247
209
76
171
161
65
22
29
115
211
122
61
154.
162.
96.
46.
7 .
14.
219.
. 16
.31
.55
.84
.22
.33
.04
.12
.60
.21
.19
.21
. 43
.59
.96
,96
15
13
27
1248.32
4239.47
5487.79
-------
adjacent streets can be and, in Ada County, likely are important localized
sources of CO emissions. As discussed in Section IV, a monitor located im-
mediately adjacent to a highway facility such as 9th Street can be heavily
influenced by emissions from vehicles on that street. Similarly, the con-
centration at a monitor placed near a major parking facility such as a shop-
ping center will often be mostly due to emissions from vehicles in and enter-
ing or leaving the lot. Existing and planned facilities suspected to be
significant localized sources should be analyzed with the ISG.*
A second and very important consideration is that the provision of park-
ing, especially for employment purposes in the CBD, can significantly influ-
ence the number of trips made into the CBD and the use of the public transit
system. CBD parking lots are of interest less because of the emissions oc- •'
curring within them but because of their ability to influence the travel
patterns in and out of the CBD and the resulting emissions. Public policy
on the availability and price of CBD parking can be an important air quality
planning tool. Parking restrictions and pricing are significant transporta-
tion control measures in major metropolitan areas, especially when combined
with improved public transit systems or carpooling programs. The potential
effectiveness of such measures can be analyzed by the combined use of the Ada
County transportation model chain and the APRAC-2 model, specifically in the
mode choice and auto occupancy models. Over the longer term, parking policy
can influence the relative attractiveness of the CBD versus outlying locations
for development and employment growth. This too influences a region's travel"
patterns.
* It is noted that, although EPA cannot require an indirect source regulation
as part of a SIP, states are free to adopt one. See section H0(a)(5) of
the Clean Air Act as amended August 1977.
25
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SECTION A
WORST CASE 9th St. MODELING ANALYSIS
The purpose of this task is to determine the geographical extent and
relative impact of emissions on CO concentrations measured at the 9th St.
monitor. The effort was carried out using design traffic, signalization, and
meteorological parameters and appropriate atmospheric dispersion models.
The combination of the Intersection/Midblock Model (IMM) and the APRAC-2
models were selected to best represent mobile source-entitled CO in the 9th
St. vicinity. These models are well described in EPA literature.1'2 IMM
includes a traffic submodel to estimate concentrations resulting from queue
and delay at intersections; the dispersion kernel of this model is EPA's
HIWAM model. APRAC-2 is a mesoscale model which was used to predict the im-
pact of non-adjacent roadways on 9th St. air quality.
INPUT DATA
Inputs to the model include traffic, signalization, and meteoroligical
conditions. Two intersections were chosen for representation by IMM: 9th
and Main and 9th and Idaho. Both intersections are controlled by fixed time
signals with 90 sec cycle times, 33 sec of which is green time to 9th St. and
49 sec of green time to the crossing road during the morning cycle. All
streets in this area are 3-lane and one-way.
Meteorological and traffic data were chosen as "worst-case," i.e., those
conditions which will result in highest predicted concentrations. The meteor-
ological conditions chosen are.:
wind speed 1.0 m/s
stability V*
mixing height 100 m
temperature 22°F
The wind direction was varied in order to determine maximum concentration.
Design traffic data were developed from a monitoring program conducted
during November of 1978. The maximum hourly traffic volume recorded on 9th
street ,md the concurrent counts on all other roads were used to represent
worst c.'ise.
"D" stability Is defined as a neutral atmosphere, the most stable conditions
typic;illy observed in an urban area.
26
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MODELING RESULTS
The results of this analysis indicate a maximum impact at the 9th St.
monitor of 73 ppm. This value can be considered the design 1-hour CO concen-
tration subject to the limitations discussed below. The disaggregation of the
impacts at the site indicated that almost all (72.5 ppm)'f of the CO results
from traffic on 9th St. (51 ppm) and Main St. (21 ppm) with 79 percent of the
emissions resulting from queuing at signals. Comparison of the magnitude of
these results with measured 1-hour CO concentrations is consistent with past
modeling efforts (i.e., a factor of 2 too great). This occurs due to the
extreme unlikelihood that tha worst case meteorological conditions, and, in
particular, the wind direction, will remain constant for an entire hour un-
der low wind speed conditions. Coupled with this degree of conservation is
the requirement that these meteorological conditions occur during the time of
peak traffic.
For control purposes, however, this analysis provides an indication of the
relative impacts of adjacent streets on CO levels and provides a basis for de-
signing control strategies. The .conclusion of this analysis is .that signifi-
cant improvements in CO levels can be achieved if efforts are focused on re-
duction in excess CO emissions caused by traffic delays.
VALIDATION
An attempt to validate the IMM model was made using meteorological and
traffic data collected at 9th St. during November 1978. A total of 48 hours
were chosen at random from the 10 days for which complete hourly data were,.
available for simulation by the IMM model.
The results of this analysis were very poor. Figure 9 presents a scatter
diagram of the modeling results. The correlation between predicted and observed
data was approximately zero, indicating that one or a combination of several of
the following conditions is occurring:
• The traffic data are incorrect.
• The monitoring data are incorrect.
• The meteorological data are incorrect,
incomplete, or not representative of
the 9th St. canyon.
• The model is unrepresentative of
the 9th Street area.
The amount of validation and theory which stand behind the IMM model suggest
that it is most likely properly representing the impacts of traffic on
air quality. The most likely source of this error is in the meteorological
data; the attempt to use winds recorded on top of a building to represent
conditions within a nearby street canyon can lead to errors in prediction.
iV
This concentration occurred with winds from the south-southwest.
27
-------
23
22
2\
20
19
16
ir
16
13
E
£ 14
j= 13
«t
a:
£ 12
in
v 10
Q
UJ
£ 9
UJ
CO
(26.2)
8
8
6
5
4
3
2
•
e
(19-2)
•
4 5 6 7 8 9 10 II 12
PREDICTED CO CONCENTRATION, ppm
13 14
27
Figure 9. IMM validation results.
28
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SECTION 5
ANALYSIS OF CRITICAL METEOROLOGICAL CONDITIONS
An analysis was performed to isolate the role of meteorology in excursions
of CO levels above ambient standards in Boise. This task was performed first
by analyzing a series of CO episodes in order to discern apparent effects and
then by using statistical techniques to develop relationships between CO
emissions and concentrations.
EPISODE ANALYSIS
Eight-hour CO concentrations recorded during 1976 were reviewed and all
excursions above the 9 ppm standard were tabulated. It was noted in this .
summary that no violations of the standard occurred between late spring and
early fall. A total of 77 violations occurred between January through April,
and September through December of 1976. This cold weather-violation pattern
corresponds with higher vehicle emission rates and poorer traffic flow during
winter time temperatures.
Those violations were first categorized by day-of-week with the following
results:
Weekdays Weekends
No. of Violations 73 4
Percent of Total 95 5
Mean 9th St. Traffic 406 208
This analysis indicates that 95 percent of all violations occur during the
weekdays. This table also presents mean hourly traffic counts on 9th St. for a
limited sampling period performed during November 1978. These data tend to
confirm a pattern which suggests that meteorology may aggregate high CO levels
but that high concentrations are caused by increases in source activity.
To further explore this point, wind speed and direction and surface pres-
sure data were collected for violation days, for each day preceding a viola-
tion, and for the months of September through April as an average.
It was found that the average sea level pressure on violating days was
1023 mb, as compared to an average of 1021 mb. The majority (58 percent) of
29
-------
observations were between 1020 mb and .1030 mb with none less than 1000 mb.
Wind speeds on violating days averaged 7.4 mph at 5 AM; this wind speed exactly
equals the annual 5 AM wind speed in Boise. All observations on violating
days were less than 17 mph and 97 percent were less than 11 mph; 6 percent
were calm. A review of the wind rose for violating days was also extremely
similar to that which is normally observed.
Comparison of each violation day with the preceding day's meteorology
again suggested that no major meteorological anomaly had occurred and led to
the violation. Mean 5 AM wind speed on preceding days was 7.5 mph and the
distribution of wind speed oy class and wind direction were almost identical.
Finally, comparison was made between mean and maximum CO levels on Mondays
(the day with most violations) and Sunday (no violations). These are as follows:
Sunday Monday
Mean 8-hr CO (ppm)
Std. Dev. of Mean CO
Max 8-hr CO (ppm)
Std. Dev. of Max CO
Ratio of Mean over Max
Ratio of Std. Dev. (Mean over Max)
2.8
0.8
7.3
2.9
0.38
0.28
7.5
1.5
21.5
5.2
0.35
0.29
The extreme similarity of these ratios suggests that the sources of CO
affecting the 9th St. monitor are located in the same geographic areas and
are being dispersed identically; only the magnitude of the emissions varies.
The conclusion of this analysis, coupled with the conclusion of the IMM
worst case analysis presented in Section IV, is as follows: high CO levels
result from a combination of typical wintertime meteorology — low wind speed
and mixing height — and high vehicle emissions caused by low ambient tempera-
tures and, most likely, poor traffic flow.
RELATIONSHIP OF CO EMISSIONS AND CONCENTRATIONS
With the knowledge that CO violations are related primarily to source
factors, the various combinations of these factors which may result in viola-
tions of the ambient standard can be identified. The goal of this effort
would be a relationship which can be used to predict maximum CO levels at a
site without resorting to monitoring.
Thi.s task was undertaken using source and concentration factors derived
from the TDI1W monitoring program conducted in the winter of 1977 and the emis-
sions inventory developed as a part of this contract. Approximately one week
30
-------
of monitor data was available at each sice. Factors, which were collected
for 28 sites included:
• Maximum 8-Ur CO concentration.
• Ratio of 8-hr CO to 9th St. CO during peak period.
e Traffic on adjacent roadway.
• Emissions in grid containing site.
• Emissions in 4 grids to the east and south of the monitor.
• Emissions in 4 grids to the west and north of the monitor.
and 2 dummy variables indicating:
• Location (valley or bench).
• Site type (traffic corridor or neighborhood).
Other variables which could have been considered in this analysis but which
were not available include queue and delay at each intersection, type of sig-
nalization and traffic flow on cross streets. The relatively short period pf
record also limits this effort as higher maximum CO levels could occur at other
times. These data were subjected to step-wise multiple regression analysis
with the following results:
• The best single predictor of maximum CO level is the average
traffic on the adjacent roadway.
• Other significant predictors include the emissions in the
grid, the location variable and the site type variable.
These variables provide the best model for prediction of maximum CO levels.
This is:
C = Gi + A (0.0015 V - 4.9 S - 2.8 L + 8.5)
where C = 8-hr maximum CO level (ppm)
V = Hourly traffic volume on nearby roadway (vph)
G. = Emissions from grid containing site for scenario i
(106 gr/day)
S = Site type (0 = traffic corridor, 1 = neighborhood)
L = Location code (1 = bench, 0 = valley)
A. = Projection factor to scenario/year i
31
-------
The conversion factors required co make predictions in "parts per million"
are implicit in each regression coefficient.
The projection factors, A., are as follows:
Scenario/year Fac tor
1978 0.99
1982 0.96
1982/IM 0.87
1987 0.75
1987/IM 0.60
These factors were developed from the regional emissions burden data
presented in Section 2. The fit of the data was significant at the 99 percent
level (r = 0.66).
These results confirm the analysis presented in Section I that most sites
in the valley will exceed the 8-hr standard.
These results also conform with the analysis presented in Section IV, as
well as experience and theory elsewhere, in that ambient concentrations of "
carbon monoxide are strongly influenced by the presence of nearby streets due
to carbon monoxide's inert nature and low elevation release.
This analysis implicitly includes all existing emissions associated
with parking, both on and off-street, inasmuch as these emissions had impact
at the IDHW and 9th Street monitoring sites. Growth in vehicle travel has
been accounted for as described in Section II. The emissions generated by
new parking facilities such as those associated with the proposed downtown
mall wei:e not included in this analysis.
32
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SECTION 6
PROJECTION OF CO CONCENTRATIONS
In order co determine the degree of control which will be needed to attain
the 8-hour standard by 1982 and 1987, the model described in Section 5 was
applied. Changes in grid emissions and regional emissions were used in combi-
nation to "roll-back" 1977 emissions taking into account growth in VMT and im-
plementation of Federal emissions controls.
The methodology applied was to make predictions of second-highest 8-hour
CO concentration at the 24 traffic corridor sites used to develop the regression
model for each of five scenarios/years. These are:
• 1977
• 1982
• 1987
• 1982 with Inspection/Maintenance
• 1987 with Inspection/Maintenance
Figures 10 through 14 present an estimate of the extent of the CO non-
atcainment problem for each of these scenarios. The area defined in each of
those figures provides a rough estimate of the area within which-traffic
corridor sites will exceed the 8-hr standard. Care should be taken in in-
terpreting these diagrams with respect to two points:
• Isolated hotspots most likely exist outside of the bounded
region, and
• Locations within the region but not adjacent to inter-
sections or roadways are not likely to exceed the
standard.
Review of these figures indicates that the nonattainment area is wide-
spread in 1977 and that only minor improvements will occur by 1982. Projec-
tion to 1987 indicates substantial reductions in the extent of nonattainment;
only the CBD and major access road corridors are expected to exceed 9 ppm.
Implementation of an Inspection/Maintenance program in 1981 will reduce
the nonattainment region slightly in 1982 and, in 1987, leave only the CBD
projected to be above standards. Based both on rollback and the model pre-
sented in Section 5, the second-highest 8-hr CO concentration at 9th Street
in 1987 with I/M in effect will be about 10.3 to 10.6 ppm. This indicates
33
-------
Figure 10. 1977 nonattainment area.
34
-------
4.
Figure 11. 1982 nonattainment area.
35
-------
Figure 12. 1987 nonattainment area.
-------
> l(
Figure 13, 1982 nonatealament area with Inspection/Maintenance.
37
-------
Figure 14. 1987 nonattainment area with Inspection/Maintenance,
38
-------
that an additional 12 to 15 percent reduction in emissions above that result-
ing from implementation of full Federal emission controls and I/M will be
necessary to attain standards by 1987. This reduction is based primarily
upon the monitor data recorded at 9th Street. As was noted earlier, the model
presented in Section 5 was based upon a second-highest value of 15.9 ppm for
this site. The model residual for this variable was +1.0 ppm, hence, resulting
in these strategies being based upon a design value of 16.9 ppm. The variance
of this value in relation to predicting needed reductions and in relation to
other sources of variance has been described in Section 1.
39
-------
SECTION 7
REFERENCES
1. lienesh, F. Carbon Monoxide Hot Spot Guidelines: Volume V: User's
Manual for Intersection Midblock Model. EPA-450/3-78-037.
August 1978.
2. Ludwig, F. L., et al. User's Manual for the APRAC-2 Emissions and
Diffusion Model. PB-275-479. June 1977.
-------
TECHNICAL REPORT DATA
rriiil /uiUriieiionx on tin' reverse he/<»/'<• C
I iu.i'OR'1 NO.
liTA .910/9-70-058
1. I 11 I. L ANUSUblMLL
Carbon Monoxide Emission Inventory and Analysis
of Nonattainment in Ada Councy, Idaho
7. AUTHOR(S)
Frank 11. Benesch
Kenneth W. Wiltsec, Jr.
J PERFORMING ORG AN I 2 A TI ON NAML AND ADDRESS
GCA Corporation, GCA/Technology Division
Burlington Road
Bedford, MA 01730
J. RECIPIENT'S ACCESSION-NO.
!>. REPOH F OATE
May 1979
li. PERFORMING ORGANIZATION CODE
8. PERFORMING ORGANIZATION REPORT NO.
GCA-TR-79-22-G
10. PROGRAM ELEMENT NO.
1. CONTRACT/GRANT NO.
K1 SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Idaho Operations Office
422 West Washington Street
Boise, Idaho
68-02-2539 Task Order No. -8
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING- AGENCY CODE
l[). S'JI'PLUMI NfAtlY NOThS
16. ABSTRACT
Using assigned network traffic files, a comprehensive wintertime motor vehicle
carbon monoxide emission inventory was prepared for Ada County, Idaho. The
Intersection Midblock Model (IMM) and APRAC-2 dispersion models modified to
include MOBiLEI emission factors was used in performing the analysis. As a
part of tliis study, CO episodes were compared with preceeding nonviolating
days to determine if meteorological anomalies may cause excursions above Che
standard, but it was found that episodes are apparently caused by a combination
of higher "per vehicle" emissions and routine wintertime dispersion characteristics,
Additional reductions in CO emissions beyond implementation of an inspection/
maintenance program were found to be necessary to meet the 8-hour standard in
1987.
17.
KEY WORDS AND DOCUMENT ANALYSIS
Air Pollution
Carbon Monoxide
APR'AC
Intersect ion/Midblock Model
b.lDENTII IERS/OPI..N L'NDED TERMS
c COSATI riclil/(irmi|>
l Hi I il', I III IIU I II )N :, 1 A I I Ml NT
19. SECUHITY CLASS (This Keport)
Unclassified
21. NO. OF PAGES
46
Unlimi ted
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
I I'A Form 2220-1 (9-7;))
41
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