EPA-AA SDSB 79-30
Technical Report
An Investigation of Future Ambient
Diesel Particulate Levels Occurring
In Large-Scale Urban Areas
By
Daniel P. Reiser
November, 1979
NOTICE
Technical Reports do not necessarily represent final EPA decisions
or positions. They are intended to present technical analysis of
issues using data which are currently available. The purpose in
the release of such reports is to facilitate the exchange of
technical information and to inform the public of technical devel-
opments which may form the basis for a final EPA decision, position
or regulatory action.
Standards Development and Support Branch
Emission Control Technology Division
Office of Mobile Source Air Pollution Control
Office of Air, Noise and Radiation
U.S. Environmental Protection Agency
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I. Introduction
EPA proposed a particulate standard for diesel-powered light-
duty vehicles in February, 1979, and is in the process of promul-
gating this standard. One of the prime inputs to this process is
the effect of diesel particulate emissions on air quality. The
purpose of this report is to determine the diesel's effect on
ambient particulate levels over large urban areas. Past studies
will be examined and combined with original projections to arrive
at the best estimate of ambient diesel particulate levels in U.S.
cities. A companion study is being conducted to determine the
diesel's impact in smaller, local areas where the impact may be
significantly larger (e.g., street canyons).
The original calculations of future regional impacts from
diesel particulate emissions will be based on past ambient lead
measurements in various urban areas. Almost all of ambient
lead prior to 1976 can be traced to lead-containing particulate
from automobile exhaust emissions. By relating future particulate
emissions from diesels to past lead emissions from gasoline-fueled
vehicles, ambient lead concentrations of the past can be used to
project ambient diesel particulate concentrations in the future.
General Motors (GM), in their comments to the proposed light-
duty diesel particulate standard, did just this, they projected
ambient levels of diesel particulate for the year 1990 using
ambient lead concentrations found in two major cities, Toledo and
Chicago. However, GM did not document their methodology to support
their calculations. Since it is desirable to project the ambient
impact of diesel particulate in as many cities as possible, GM's
work will be repeated to confirm their results and then expanded to
other cities using a documented methodology. The results from this
work will then be compared to two studies performed by PEDCo
Environmental examining the impact of diesel particulate emissions
in 1) Kansas City and 2) New York, Chicago, and Los Angeles.
The rest of this report has been divided into five sections.
The first section contains the development of a reasonable scenario
which includes future diesel sales, future traffic levels, and
diesel particulate emission factors. The second section contains
1) a survey of the three studies which have already examined the
air quality impact of the diesel and 2) modifies the results of
these studies to conform with the scenario developed in the pre-
vious section. In the third section, the lead surrogate approach
(GM) is outlined and extended to many other cities. The fourth
section contains a comparison of the results of the three studies
(including the extention) while the final, fifth section contains
the conclusions of the analysis.
II. Development of Scenario
Whenever two studies predicting the same phenomena are com-
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pared, differences can result because of two factors. One, the
input data may differ. Two, the methodology may differ. This
study is primarily concerned with differences in methodology. The
study's goal is to arrive at the best estimate of the ambient impact
of a specified level of diesel particulate emissions. In order to
compare methodologies from one study to another the same input data
must be used in every case. This input scenario will consist of
projected emission factors, growth rates for vehicular traffic
and the breakdown of this traffic by vehicle class.
EPA estimates that by 1990 the uncontrolled particulate
emission factor from light-duty diesels will be 1.0 gram per mile
(g/mi).J_/ This emission factor anticipates an increase in particu-
late exhaust emission due to a more stringent NOx emission standard
being implemented by 1985. The heavy-duty particulate emission
factor is presently estimated to be 2.0 g/mi.^/ It will be assumed
that these emission factors would not change by 1990 without
regulation. A summary of emission factors corresponding to vehicle
class is shown in Table 1. Because this report is only concerned
with diesel particulate emissions, particulate emissions from
future gasoline-fueled vehicles will be assumed to be zero.
The breakdown by vehicle class of total urban vehicle miles
traveled (VMT) by 1990 is also shown in Table 1. Two different
breakdowns are shown: a "low estimate" and a "high estimate" based
on a range of projected diesel sales. When engine type (gasoline
or diesel) is ignored, the breakdown by class is the same in both
cases and was based on DOT data.2/ EPA's latest projection of
diesel penetration into the 1990 light-duty vehicle and truck fleet
was the basis for the breakdown of the first two classes of Table
1._3/ That projection only included a single best estimate. To
indicate the error possible in such projections, a range of plus
and minus 25 percent of the best estimate was used. The estimate
of diesel penetration into the heavy-duty fleet was taken from the
Regulatory Analysis for EPA's proposed light-duty diesel particu-
late regulations.^/ Knowing the emission factors and the fraction
of VMT for each class, an average weighted emission factor of 0.17
g/mi for the "low estimate" case and 0.27 g/mi for the "high
estimate" case can be calculated. These figures were obtained by
summing the product of each urban VMT fraction and its correspon-
ding emission factor. From examining the contributions of each
class to these average emission factors it can be seen that light-
duty diesels contribute 56.7 percent and 60.6 percent of total
diesel particulate emissions, low and high estimates, respec-
tively.
Finally, an estimate of urban traffic growth is necessary to
obtain a complete picture of future vehicle emissions. An annual
growth rate of 1 percent will be used here. This should be suit-
able as it has been EPA's policy to use a 1 percent per year growth
rate for projections of CO emissions, which, along with diesel
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Table 1
Fraction of Urban VMT by Mobile Source
Category in 1990
Fraction VMT (1990)
Classification Low High
LDV-G
LDV-D
LDT-G
LDT-D
HDT-G
HDT-D
0.745
0.085
0.096
0.012
0.025
0.037
0.689
0.141
0.089
0.019
0.010
0.052
Emission Factor
0
1.0
0
1.0
0
2.0
LDV = Light-duty vehicles.
LDT = Light-duty trucks.
HDT = Heavy-duty trucks.
G = Gasoline.
D = Diesel.
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particulate, is primarily an urban core problem.^/ This increase
should be compounded between the last year of traffic or ambient
pollutant measurement and the year being examined (1990). In-
cluding traffic growth in future projections is necessary as it
alone will cause an increase in ambient particulate concentrations,
if other factors are left unchanged.
III. Survey and Modification of Previous Studies
A. PEDCo-Kansas City
PEDCo Environmental recently performed a study on the impact
of diesel particulate emissions on total suspended particulate
(TSP) concentrations in the atmosphere,2j Specifically, the Air
Quality Display Model (AQDM) was used to predict the diesel's
impact on the air quality of Kansas City, Missouri. The city was
broken down into 165 sections using a grid of 2 x 2 kilometer
squares. The average diesel particulate concentration in each
square was determined. EPA requested and examined PEDCo's grid
data sheet for one case and determined the fraction of the pop-
ulation exposed (by residence) to various levels of diesel part-
iculate in 1990._4/ These results are shown in the second column of
Table 2. ~
In calculating the impacts shown in the second column of Table
2, PEDCo used emission factors of 0.5 grams per mile (g/mi) for
light-duty diesels and 2.0 g/mi for heavy-duty diesels with a
traffic growth rate of 1.51 percent per year between 1974 and
1990. The traffic breakdown (percentage of total regional travel)
used was 19.1 percent for light-duty diesel vehicles, 2.4 percent
for light-duty diesel trucks, and 5.2 percent for heavy-duty diesel
trucks.
To convert these results to the scenario of Section II, two
converting factors must be determined. One is the ratio of the
traffic-weighted diesel particulate emission factors and the other
is the ratio of future traffic levels between 1974 and 1990. From
the figures shown in the preceding paragraph, PEDCo's weighted
emission factor was 0.21 g/mi and their overall estimate of traffic
growth was 27 percent. From Section II, EPA's weighted emission
factors are 0.17 g/mi (low) and 0.27 g/mi (high) and the estimate
of traffic growth is 17.3 percent (16 years). The ratios of
emission factors are then 0.81 (0.17/0.12) and 1.29 (0.27/0.21),
low and high diesel estimates, respectively. The ratio of future
traffic levels is 0.92 (1.173/1.27). Combining these two factors,
the PEDCo results need to be multiplied by 0.74 and 1.14 to be
converted to EPA's low and high diesel scenarios, respectively.
This has been done and the modified results are shown in the last
two columns of Table 2.
B. PEDCo-New York, Chicago, and Los Angeles
PEDCo performed a second study on the environmental impact of
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Table 2
Predicted Population Exposure to Ambient Particulate Levels
for Kansas City, Mo, in 1990
% of
to
Population Exposed
Estimated Ambient
Levels
2.1
5.9
13.2
17.8
28.6
32.8
Ambient Part. Level (ug/m^)
Diesels (Pedco, "Max Growth")
1.732
1.586
1.48
1.386
1.24
1.20
Ambient Part. Level (ug/m^)
Diesels (EPA, "Low Est.")
1.3
1.2
1.1
1.0
0.92
0.89
Ambient Part. Level (ug/m^)
Diesels (EPA, "High Est.")
2.0
1.9
1.7
1.6
1.5
1.4
i
ON
1
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diesel particulate emissions,5/ this time based on ambient total
suspended particulate (TSP) data taken at fifteen monitoring sites,
five each in New York, Chicago, and Los Angeles. TSP data collec-
ted from these SAROAD sites were converted to ambient diesel
particulate levels using the approximation that motor vehicles
contribute a fixed percentage of the TSP levels in each city.
PEDCo estimated that particulate emissions from motor vehicles in
1975 and 1976 contributed about 21 percent of the TSP in New York
City, 13 percent of TSP in Los Angeles, and 17 percent of TSP in
Chicago .j>y These percentages were the result of analyses examining
the amount of elemental lead in ambient TSP measurements. It is
uncertain whether these percentages as discussed in the original
references, refer to leaded exhaust particulate only or to all
particulate emissions associated with automobiles (e.g., tire
particulate emissions, reentrained dust, etc.). PEDCo assumed that
the percentages referred to leaded exhaust particulate. This
uncertainty will be analyzed in the Comparison section of this
report (V).
Via the above-mentioned percentages, PEDCo was able to deter-
mine the motor vehicle contribution to ambient TSP levels in
1975-1976. They then determined future ambient diesel particulate
levels by using 1) the ratio of the diesel particulate emission
factor to the leaded-gasoline particulate emission factor, 2) the
ratio of future diesel traffic to the existing traffic of leaded-
gasoline fueled vehicles, and 3) the future overall traffic growth.
Through the use of two or more different estimates of the above
three factors, PEDCo examined a total of six scenarios. As PEDCo"s
work involved the same basic assumption as that used in this
report, that the air quality impact of a source is proportional to
the emissions of that source, only one of PEDCo's scenarios need be
modified to the scenario of Section II.
PEDCo's scenario which assumed optimistic growth in diesel use
and traffic will be the one examined here (Scenario Tj D2 Ej). The
particulate emission factors used were 0.5 g/mi for light-duty
diesels and 2.0 g/mi for heavy-duty diesels. The breakdown of
traffic by vehicle and the traffic growth rates used were different
for each city and are shown in Table 3. The weighted emission
factors resulting from these growth rates and individual vehicle
emission factors for the year 1990 are also shown in Table 3. The
resulting ambient diesel particulate levels at all fifteen sites
are shown in Table 4 (first column). These results, modified to
the scenario outlined in Section II, are shown in the second column
of Table 4. The methodology used to modify these original PEDCo
results was the same as that used to modify the results of the
previous PEDCo-Kansas City study. The ratios of the weighted
emission factors and the future traffic levels were multiplied
against the original results to obtain the modified results. These
results are substantially higher than the PEDCo-Kansas City predic-
tion. An explanation of this will be discussed in Section V.
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Table 3
Input Parameters of PEDCo Three-City Study 5/
Tl, D2, El Scenario - 1990
New York Chicago Los Angeles
Overall Traffic Growth
(1976-1990)
10.!
Vehicular Traffic Breakdown by Class
Light-Duty*
Gasoline
Diesel
50.7%
40.5%
6.4%
47.8%
42.2%
22.7%
52.2%
41.6%
Heavy-Duty**
Gasoline
Diesel
0.3%
8.4%
o.:
4.1
0.
6.
Particulate Emission Factors
Light-Duty
Heavy-Duty
Diesel Particulate Weighted
Emission Factors
0.5 g/mi 0.5 g/mi 0.5 g/mi
2.0 g/mi 2.0 g/mi 2.0 g/mi
0.37g/mi 0.307g/mi 0.33 g/mi
* Light-duty includes autos and taxi's in PEDCo's terminology.
** Heavy-duty includes heavy-duty trucks and buses in PEDCo's
terminology.
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Table 4
Predicted Ambient Particulate Levels for 1990 from Diesels
EPA vs Pedco
City
New York
New York
New York
New York
New York
Torrance,
Los Angeles
Long Beach,
Los Angeles
Los Angeles
Pasadena
Pasadena
Chicago
Chicago
Chicago
Chicago
Chicago
Site Adress
EPA Scenario
PEDCo Scenario (ug/m3)
T1>D2»E1 (ug/m3) Low High
Steinman Hall ,W. 141 St.
and Convent Ave.
170 E. 121 St.
Central Park Arsonal,
5th Ave., and 64th St.
240 2nd Ave.
Pier 42, Morton St.
and Hudson River
2330 Carson St.
2655 Pine Ave.
434 S. Pedro
1196 East Walnut
Kech Laboratories,
Cal. Inst. of Tech.
3500 E. 114 St.
1947 W. Polk
9800 S. Torrence Ave,
538 S. Clark St.
4015 N. Ashland Ave.
20.50
19.78
20.45
24.90
20.72
22.59
46.91
22.91
25.07
23.82
19.64
9.8
9.6
10.0
12.0
10.1
11.0
28.1
13.7
15.0
14.3
11.8
15.1
21.62
19.97
25.62
24.82
10.3
9.5
12.2
11.8
16.0
14.7
18.9
18.7
15.0
15.4
18.7
15.6
17.1
43.6
21.3
23.3
22.1
18.3
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C. GM Study
In their response to EPA's proposed standards, GM submitted an
air quality impact section in which ambient particulate concentra-
tions from diesel vehicle emissions were calculated from a lead
tracer model.6J A methodology was not presented in this report,
but a scenario was given which included a particulate emission rate
of 0.2 g/mi with a light-duty vehicle (LDV) fleet of 25 percent
diesels for the year 1990. A 1 percent per year traffic growth
rate was also used. The GM results are shown in Table 5, as well
as the results modified to EPA's scenario. As the GM and EPA
traffic growth rates are the same in this case, no adjustment due
to this factor was necessary. The GM weighted diesel particulate
emission factor was simply 0.05 g/mi (0.25 x 0.2 g/mi), so the only
adjustment was converting this to the 0.17 g/mi and 0.27 g/mi
weighted emission factors, low and high diesel estimates, respec-
tively.
The regional annual means determined by GM were based on
annual lead measurements in Chicago and Toledo taken in 1970 and
1968, respectively. GM claimed that this lead surrogate method is
sensible and straightforward and can be reliably applied to major
U.S. cities as well.jji/ Because of this ease and applicability to
many urban areas, this lead surrogate work will be extended to more
cities below.
IV. Extension of Lead Surrogate Work to Other Cities
Although GM used the lead surrogate approach to predict future
particulate concentrations from light-duty diesels, the exact
methodology was not documented. As it would be helpful to extend
this work to other cities, a methodology will first be outlined
below and then extended using monitoring data similar to that used
by GM. This methodology should be very similar to that used by GM
and any differences will be examined in Section V.
The basic assumption involved in surrogate work of this type
is that the ratio of the ambient level to emissions of one pol-
lutant (in this case lead) is related to that of another pollutant
(in this case diesel particulate). Lead has the advantage of being
easily separable from other particulate components and the great
majority of it is emitted from motor vehicles. It is much more
difficult to distinguish diesel particulate from carbonaceous
particulate from other sources. Thus, the relationship between
ambient lead concentrations and lead emissions from motor vehicles
is first determined from actual measurements of both. Second, this
relationship for lead is modified as necessary to represent the
same relationship for diesel particulate. Finally, this relation-
ship for diesel particulate is coupled with diesel particulate
emission data to yield estimates of ambient diesel particulate
levels.
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Table 5
Results and
Modification of GM Study 6/
Ambient Diesel Impact
Regional Annual Mean (ug/m^)
GMEPA
Low High
Major Cities (Chicago) 3.2 10.9 17.3
Mid-size (Toledo) 0.9 3.1 4.9
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Th e first step in this process is to express the ambient
levels of both diesel particulate and lead in terms of their
respective emissions. These relationships are expressed in the
following two equations:
C(Pb) = E(Pb) • f(Pb) (1)
C(D) = E(D) • f(D) (2)
where:
C(Pb) = concentration of ambient lead levels from mobile
source emissions in a particular urban area.
E(Pb) = average motor vehicle emission factor for lead in a
particular urban area.
f(Pb) = a function which relates lead emissions to ambient
lead concentrations (constant for each monitoring
site).
C(D) = concentration of ambient diesel particulate levels
from diesel mobile source vehicles in a particular
urban area.
E(D) = average motor vehicle emission factor for diesel
particulate for a particular urban area.
f(D) = a function which relates diesel emissions to ambient
diesel particulate levels (constant for each moni-
toring site).
As can be seen, the ambient levels of both pollutants have been
assumed to be proportional to their emission factor. This is a
standard assumption when working with one source of a non-reactive
pollutant. Here we are working with many individual sources (i.e.,
vehicles). If the relative distribution of these vehicle through-
out the region were changing, then f(Pb) or f(D) could change if
the average emission factor changed. However, for the purposes of
this report, the relative distribution of vehicles throughout a
region will be assumed to remain constant. The overall breakdown
of traffic by class and engine type may change and the overall
traffic may increase, however, each subsection of the region is
assumed to have the same fraction of the region's total traffic as
it had when the lead studies were performed. Under this condition,
equations (1) and (2) are quite valid.
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Equation (2) can not be used alone to calculate concentrations
of ambient diesel particulate levels since f(D) is unknown.
However, if equation (2) is divided by equation (1), and solved for
C(D), C(D) then becomes a function of C(Pb) and two factors, one
related to emissions and one related to dispersion. It may be
possible to determine the ratio f(D)/f(Pb) where it would not have
been possible to determine f(D) alone. The equation is shown
below:
C(D) = E(D) ' f(D) • C(Pb)
E(Pb) f(Pb)
In the following three subsections, the three factors shown on
the right side of equation (3) will be determined. In the fourth
subsection, all three will be combined to yield estimates of
ambient diesel particulate levels in a large number of cities
throughout the U.S.
A. Lead and Diesel Particulate Emissions
The first factor of equation (3) to be determined will be that
relating to emissions, E(D)/E(Pb). The average emission factor for
diesel particulate has already been calculated in Section II and is
0.17 g/mi for the low diesel estimate case and 0.27 g/mi for the
high diesel estimate case. The average emission factor for lead
will be determined below.
Lead emission factors for light-duty vehicles (LDV), light-
duty trucks (LDT) and heavy-duty vehicles (HDV), can be determined
from three pieces of data; 1) the lead content of gasoline, 2)
the fraction of the lead entering the engine that is emitted from
the exhaust, and 3) the fuel economy of the vehicle. All of these
factors will be determined circa 1975, as this is the year of the
ambient lead measurements.
The (elemental) lead content of gasoline in 1975 was 1.9
grams per gallon. Tj Past studies have found that approximtely 75
percent of the lead in the fuel leaves through the exhaust.^/ The
rest is accumulated in the oil sump and exhaust system. The
average fuel economy of light-duty vehicles in 1975 was 13.5 miles
per gallon and that for trucks was 8.7 miles per gallon (based on
DOC data).jy No further breakdown was available on the fuel economy
of trucks into EPA's light-duty and heavy-duty categories so this
figure will be used as the average fuel economy for these two
classes.
Combining these figures, the lead emission factor for light-
duty vehicles is 0.105 g/mi and 0.164 g/mi for both light-duty
trucks and heavy-duty vehicles. These figures and the breakdown of
urban traffic in 1974 (assumed applicable in 1975)2/ are shown in
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Table 6. Combining the figures of Table 6 yields an average
1975 lead emission factor of 0.11 g/mi.
Only one step remains before the ratio E(D)/E(Pb) can be
determined. The average diesel particulate emission factor (0.17
and 0.27 g/mi) is in terms of 1990 miles, while the lead emission
factor is in terms of 1975 miles. Between these two years,
however, overall travel will increase by 16.1 percent (1.0 percent
annual growth compounded for 15 years). Thus, the average diesel
particulate emission factor should be increased by 16.1 percent to
be on an equivalent basis as the lead factor. With the incorpora-
tion of the 16.1 percent increase, the ratios of E(D)/E(Pb) are
calculated to be 1.8 (low estimate) and 2.8 (high estimate).
B. Lead and Diesel Particulate Dispersion Characteristics
Automotive lead and diesel particulate emissions have similar
properties that would imply that their dispersion would be very
similar. These properties are: a) both are emitted in particulate
form, b) both are emitted from ground level, and c) both are
emitted from vehicles of similar urban driving patterns. However,
a major difference between lead and diesel particulate is their
relative size. This section will discuss this difference and how it
affects the relative dispersion of the two types of particulate.
Diesel particulate is extremely small with well over 90
percent by mass being fine (less than 2.5 micrometers in dia-
meter). _8_/9_/ This is small enough for all of the particulate to be
considered suspendable.JjV Lead-containing particulate (lead salts
such as PbClBr), on the other hand, is much larger, only 43 percent
by mass being smaller than 9 micrometers in diameter ._10/ This same
study examined the particle size distributions of both ambient and
exhaust lead-containing particulate and concluded that only the 43
percent smaller than 9 micrometers was being suspended and the rest
was settling out rather quickly after emission._10_/ It appeared
somewhat simplistic to assume that the cutoff for suspension would
be so sharp. However, an examination of the size distributions of
both the ambient and exhaust particulate samples revealed that the
fraction of the mass smaller than 0.6 micrometer was approximately
2.5 times larger for the ambient sample than the exhaust sample.
If it is assumed that all of the particles less than 0.6 micro-
meters in diameter were suspended, this would imply that about 40
percent of the lead-containing particulates was suspended. As this
confirms the 43 percent figure cited above, 43 percent will be
used as the percentage of lead-containing particulate that is
suspended.
Given that all the other source characterisitics are the same
for lead and diesel particulate, the only differences between the
dispersion of the two pollutants is that 57 percent of the lead
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Table 6
Fraction of Urban VMT by Mobile Source Category
in 1974
Fraction of
Urban VMT
i
1
2
3
4
5
6
Classification
LDV-G
LDV-D
LDT-G
LDT-D
HDV-G
HDV-D
(1974) 2/
0
0
0
0
0
0
.826
.004
.107
.001
.036
.026
Pbi
0
0
0
0
0
0
(gr/mi)
.11
.11
.27
G = Gasoline.
D = Diesel.
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particulate does not stay aloft long enough to be measured by an
ambient air monitor. Thus, the ratio f(D)/f(Pb) is 1.0/0.43 or
2.32.
C. Ambient Lead Levels
The third and last parameter to be determined before equation
(3) can be used to predict ambient levels of diesel particulate is
the ambient level of lead (C(Pb)). Unlike the other two para-
meters, this parameter varies from city to city. For precisely
that reason, this approach is able to yield diesel impacts in many
cities while requiring a minimum of effort.
There are two primary sources of ambient lead data available;
that obtained by the National Air Surveillance Network (NASN) and
that contained in the National Aerometric Data Bank (NADB).JJ_/ The
NASN data will be used here because it has the greater likelihood
of being representative of large-scale urban areas and large
exposed populations. Many of the lead monitors submitting data to
NADB are special purpose monitors located near large sources of
lead emissions and would only be representative of locales near
those sources.
The NASN ambient lead data is shown in Table 7-A through 7-E
for cities divided into five population categories. Data from a
few cities known to have large stationary sources of lead emission
have been omitted. In general, the lead measured at sites shown in
Tables 7-A through 7-E should be nearly all due to motor vehicle
exhaust emissions. In 1975, motor vehicles accounted for 89
percent of the 142,000 metric tons emitted nationwide.^/ In
addition, much of the 11 percent due to stationary source emissions
is concentrated in those areas which have been avoided by this
study. However, to be conservative, it will be assumed that only
89 percent of the ambient lead concentrations shown in Table 7-A
through 7-E are due to motor vehicle emissions. Thus, these values
will be multiplied by 0.89 before being used in equation (3).
D. Calculation of Ambient Levels of Diesel Particulate
The necessary data is now available to calculate ambient
diesel particulate levels in 1990. Once again equation (3) is:
C(D) = E(D) ' f(D) . C(Pb) (3)
E(Pb) f(Pb)
The ratio E(D)/E(Pb) is 1.8 for the "low estimate" case, and 2.8
for the "high estimate" case. The ratio f(D)/f(Fb) is equal to
2.32 (1/0.43). C(Pb) for each city is equal to the value shown in
Table 7 (A through E) multiplied by 0.89. Using these figures,
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Table 7-A
Ambinet Lead Levels in Cities with a Population Greater Than 1,000,000 ll/
City
Chicago
Detroit
Houston
Los Angeles
New York
Philadelphia
AQCR #
67
67
123
216
24
43
45
45
Site Number
141220001
141220002
231180001
452560001
054180001
(Old #)
334680001
(New #)
334680014
397140002
397140004
Address
320 N. Clark St.
445 S. Plymouth Ct.
Public Library
810 Bagby St.
434 S. Pedro St.
170 E. 121st St.
2031 Race St.
1501 E. Lycoming Ave .
Station Type
Center City-
Commercial
Center City-
Commercial
Suburban-
Commercial
Center City-
Commerical
Center City-
Commercial
Center City-
Commercial
Center City
Residential
Suburban-
Residential
Elev. Above
Ground ( f t . )
10
10
9
50
100
75
15
17
Lead Concentration
(ug/m^)*
1.42
3.01
0.99
2.09
2.68
1.05
1.34
1.23
Annual Mean.
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Table 7-B
Ambient Lead Levels in Cities With a Population Between 500,000 and 1,000,000 ll/
City
Boston
Dallas
Denver
Kansas City,
New Orleans
Phoenix
Pittsburg
San Diego
St. Louis
AQCR #
119
215
36
36
MO 94
106
15
197
29
70
72
Site Number
220240001
451310002
060580001
060580002
262380002
192020002
030600002
397260001
056800001
264280001
264280002
Address
JFK Bldg.,
Cambridge St.
2100 Young St.
414 14th St.
2105 Broadway
Not available
421 Loyola Ave .
1845 F. Roosevelt
County Office Bldg.
Not available
1720 Market St.
215 S. 12th Blvd.
Station Type
Center City-
Commerical
Center City-
Commercial
Center City-
Commercial
Center City-
Commerical
Center City-
Commerical
Center City-
Commercial
Center City-
Commercial
Center City-
Commercial
Center City-
Commercial
Elev. Above
Ground ( f t . )
85
12
43
9
72
30
160
49
10
Lead Concentrations
(ug/m3)*
0.92
3.03
0.95
1.59
0.80
1.06
2.10
0.85
1.13
1.18
1.58
00
I
Annual Mean.
-------
Table 7-C
Ambient Lead Levels in Cities With a Population Between 250,000 and 500,000
City
Atlanta
Birmingham, AL
Cincinatti
Jersey City
Louisville
Oklahoma City
Portland
Sacramento
Tucson
Yonkers, NY
AQCR #
56
4
79
43
78
184
184
193
28
15
43
Site Number
110200001
010380003
361220001
(A01)
312320001
182380002
372200015
372200029
381460001
056580001
030860001
337620001
(A01)
Address
99 Butler St. SE
Not Available
Public Library,
Vine St.
Med. Ctr. Garage
2500 S. 3rd St.
428 W. California
Not available
State Office Bldg.
2221 Stokton Blvd.
24D & Palm
87 Hepperman Ave .
Station Type
Center City-
Commericial
Center City-
Commercial
Suburban-
Industrial
Center City-
Industrial
Center City-
Commerical
Center City-
Commerical
Center City-
Commerical
Center City-
Commerical
Center City-
Commerical
Elev. Above
Ground ( f t . )
20
550
45
80
15
170
11
47
100
Lead Concentrations
(ug/m3) *
1.05
1.22
0.81
1.03
0.96
•8.
H>
VD
1.66 '
1.02
0.81
1.05
0.75
1.16
Annual Mean.
-------
Table 7-D
Ambient Lead Levels in Cities With a Population Between 100,000 and 250,000
City AQCR #
Baton Rouge 106
Jackson, MS 5
Kansas City, KA 94
94
Mobile, AL 5
New Haven, CT 42
Salt Lake City 220
Spokane, WA 62
Torrance, CA 24
Trenton, NJ 45
Waterbury, CT 42
Site Number
190280001
251260002
171800002
171800012
012380001
070700001
460920001
492040001
058260001
315400001
071240001
Address
3142 Evangeline St.
424 N. State St.
Miami & Baltimore
EPA Lab 25-
Furston Rd .
O.K. Bicycle Shop
270 Orange St.
610 S. 2nd East
Spokan City Hall
2300 Carson St.
State House and
State St.
City Hall
235 Grand Ave .
Station Type
Center City-
Commercial
Center City-
Industrial
Center City-
Industrial
Center City-
Commercial
Center City-
Commercial
Center City-
Commercial
Center City-
Commercial
Center City-
Residential
Center City
Commercial
Center City-
Commercial
Elev. Above
Ground ( f t . )
5
12
14
19
15
72
30
84
4
40
55
Lead Concentrations
(ug/m3) *
0.93
0.80
0.60
0.43
0.96
1.15
0.98
0.58
2.35
0.88
1.88
o
Annual Mean.
-------
Table 7-E
Ambient Lead Levels in Cities With Population Under 100,000
Kiev. Above Lead Concentration
City
Anchorage,
Bethlehem,
Helena, MO
Jackson Co
AQCR #
AL 8
PA 151
142
. , MS 5
Site Number
020040003
39078002
270720001
251280001
Address
527 E. 4th Ave.
Public Safety Bldg.
Cogswell Bldg.
Jackson Co.
Health Dept.
Station Type
Center City-
Commercial
Suburban-
Commercial
Center City-
Residential
Rural-
Near Urban
Ground (ft.)
28
41
29
4
(ug/m3) *
1.00
0.57
0.29
0.47
I
NJ
Annual Mean.
-------
-22-
ambient diesel particulate levels in 1990 can be calculated and are
shown in Tables 8-A through 8-E. Now that all the previous studies
have been normalized to the same scenario and the GM work has been
extended to more cities, the last step of this analysis will be to
compare the results of the studies and determine what is the best
estimate available of the future ambient impact of diesel particu-
late emissions.
V. Comparison of Results
The normalized results of the various studies are contained in
Tables 2,4,6, and 8-A through 8-E. Because the projections con-
tained in Table 8 (A-E) include most of the cities examined by the
other studies, the Table 8 data will be used as a common ruler,
against which the results of the other studies will be compared.
The comparison will begin with the GM work, as it will be the
simplest comparison and will be followed by the PEDCo three city
study and the PEDCo-Kansas City study.
A. GM Study
This comparison is the simplest because the methodology used
in Section C is most near that of GM. The city examined both by GM
and in Section IV is Chicago. Under the low diesel estimate
scenario, GM would have projected a level of 10.9 micrograms per
cubic meter while Table 8-A shows 11.2 micrograms per cubic meter
(for the monitor examined by GM). As can be seen, these projec-
tions are less than 3 percent apart. A brief conversation with GM
revealed a few sources of the difference, some compensating
others.12/ One, GM used a higher average lead emission factor,
0.13 g/mi versus the 0.11 g/mi factor determined in Section IV-A.
Two, GM did not try to take into account sources of lead other than
motor vehicles. Thus, the 0.89 factor was not used. Three, their
original ambient lead level was slightly higher (3.2 versus 3.0
micrograms per cubic meter) as they used 1970 data_13_/ rather than
1975 data.7/
GM's higher lead emission factor may be due to the earlier
date examined, 1970. The lead content in fuel was decreasing in
that time frame .Tj The decision to take stationary source lead
emissions into account is really a decision to be conservative or
liberal and in this study the choice has generally been to be
conservative, if possible. In general, then, the methodologies
used by GM and in Section IV seem to be nearly identical and the GM
results tend to confirm the results of Section IV. As the latter
examines many more cities than the GM work, the results in Table 8
should be sufficient for future studies.
B. PEDCo-New York, Chicago, and Los Angeles Study
The basis of this PEDCo study, like that of Section IV, is the
-------
Table 8-A
Ambient Diesel Particulate Levels* for
Urban Areas With A Population Above 1,000,000
City
Chicago
Detroit
Houston
Los Angeles
New York
Philadelphia
AQCR #
67
67
123
216
24
43
45
45
Ambient Lead, 1975
(ug/m3)(All Sources)
1.42
3.01
0.99
2.09
2.68
1.05
1.34
1.23
Ambient Paticulate, 1990
(ug/m3) "Low Estimate"
5.29
11.22
3.70
7.76
9.96
3.90
4.99
4.56
Ambient Particulate, 1990
(ug/m3) "High Estimate"
8.36
17.73
5.83
12.32
15.80
6.19 i
S3
w
7.90 '
7.25
Annual Mean.
-------
Table 8-B
Ambient Diesel Particulate Levels* for
Urban Areas With A Population From 500,000 to 1,000,000
Ambient Lead, 1975
City AQCR # (ug/m3)(All Sources)
Boston
Dallas
Denver
Kansas City, MO
New Orleans
Phoenix
Pittsburgh
San Diego
St. Louis
119
215
36
36
94
106
15
197
29
70
70
0.92
3.03
0.95
1.59
0.80
1.06
2.10
0.85
1.13
1.18
1.58
Ambient Paticulate, 1990
(ug/m3) "Low Estimate"
3.41
11.27
3.53
5.91
2.61
3.92
7.81
3.15
4.21
4.38
5.88
Ambient Particulate, 1990
(ug/m3) "High Estimate"
5.42
17.86
5.60
9.37
4.13
6.24 i
N
*
12.38 '
5.01
6.67
6.95
9.32
Annual Mean.
-------
Table 8-C
Ambient Diesel Particulate Levels* for
Urban Areas With A Population From 250,000 to 500,000
City
Atlanta
Birmingham, AL
Cincinnati
Jersey City
Louisville
Oklahoma City
Portland
Sacramento
Tucson
Yonkers, NY
Ambient Lead, 1975
AQCR # (ug/m3)(All Sources)
56
4
79
43
78
184
184
193
28
15
43
1.05
1.22
0.81
1.03
0.96
1.66
1.02
0.81
1.05
0.75
1.16
Ambient Paticulate, 1990
(ug/m3) "Low Estimate"
3.90
4.54
3.02
3.83
3.57
6.16
3.78
3.02
3.90
2.80
4.31
Ambient Particulate, 1990
(ug/m3) "High Estimate"
6.18
7.19
4.77
6.07
5.65
9.78 &
6.00 '
4.77
6.19
4.42
6.83
Annual Mean.
-------
Table 8-D
Ambient Diesel Particulate Levels* for
Urban Areas With A Population From 100,000 to 250,000
Ambient Lead, 1975
City AQCR # (ug/m3)(All Sources)
Baton Rouge
Jackson MS
Kansas City, KA
Mobile, AL
New Haven, CT
Salt Lake City
Spokane , WA
Torrance , CA
Trenton, NJ
Waterbury, CT
106
5
94
94
5
42
220
62
24
45
42
0.93
0.80
0.60
0.43
0.96
1.15
0.98
0.58
2.35
0.88
1.88
Ambient Paticulate, 1990
(ug/m3) "Low Estimate"
3.46
2.97
2.24
1.60
3.57
4.28
3.65
2.15
8.74
3.27
6.70
Ambient Particulate, 1990
(ug/m3) "High Estimate"
5.48
4.71
3.46
2.54
5.65
6.78
5.78
3.42
13.85
5.19
11.08
I
NJ
Annual Mean.
-------
Table 8-E
Ambient Diesel Particulate Levels* for
Urban Areas With A Population Under 100,000
Ambient Lead, 1975 Ambient Paticulate, 1990
City AQCR # (ug/m3)(All Sources) (ug/m3) "Low Estimate"
Anchorage, AK 8 1.00 3.65
Bethlehem, PA 151 0.57 2.07
Helena, MO 142 0.29 1.06
Jackson 5 0.47 1.67
County, MS
Ambient Particulate, 1990
(ug/m3) "High Estimate"
4.44
2.52
1.29
2.76
i
N3
Annual Mean.
-------
-28-
use of lead as a surrogate. As such, one would expect the results
of the two studies to be similar. However, this is not the case.
The PEDCo results for New York are much higher (86-154 percent)
than those determined in Section IV as are PEDCo"s Chicago results
to a lesser extent. A possible reason for this might be the use of
different monitors within each city. However, an examination of
the actual sites modelled (Tables 6 and 8-A) reveals that two
sites, one in New York and one in Los Angeles, were modelled in
both studies. In both cases, the PEDCo results were higher, 154
percent (New York) and 18 percent (Los Angeles). The latter error
is not large given the type of projections being made here, but the
former was too large to ignore and PEDCo's methodology was examined
to identify possible sources of the differences.
One primary difference was found between PEDCo's metodology
and that used in Section IV. In Section IV, ambient lead levels
are modified by two factors, one related to emissions and one
related to dispersion characteristics. PEDCo used two similar
factors. However, the base ambient lead level was not measured,
but calculated from ambient levels of total suspended particulate
(TSP). A different constant fraction of TSP levels was assumed to
be lead (or lead salts) in each of the three cities, based on
referenced studies in New York and Los Angeles. Both of these
references were examined.
The Los Angeles study concluded that 13 percent of ambient TSP
levels in Los Angeles were automotive-related.14/ It appeared from
the wording of the report that this 13 percent only included leaded
exhaust particulate and not tire particulate or reentrained road
dust.JL4/ This was also PEDCo's interpretation judging from their
use of the 13 percent figure ,_5_/
The New York study, on the other hand, concluded that 20-25
percent of New York's TSP levels were automotive-related._15y A
statistical method was used to correlate ambient TSP levels with
ambient lead levels. Rather than express lead levels as a fraction
of TSP levels, however, the report's results were actually in terms
of an 'x' microgram per cubic meter increase in ambient elemental
lead levels coincides with a 'y' microgram per cubic meter increase
in TSP levels.15/ This type of analysis would definitely include
reentrained dust and other-than-exhaust automotive particulate.
However, PEDCo interpretted the report's conclusion to only refer
to exhaust (lead-salt) particulate and assumed that 21 percent of
ambient TSP levels were lead-containing particulate. This would
appear to be the source of the difference between the PEDCo New
York results and that of Section IV.
This error can be remedied by determining the actual percen-
tage of TSP levels due to "exhaust" particulate. A reexamination
of the original New York study revealed that about 8 percent of New
York TSP levels consisted of lead salts from motor vehicles.15/ As
-------
-29-
PEDCo used 21 percent, they overestimated the actual figure by a
factor of 2.66. PEDCo's New York results can simply be divided by
2.66 to remove the error and this has been done in Table 9. As can
be seen, the modified PEDCo result for the E. 121st St. site is now
6.0 microgram per cubic meter, which compares very well with the
Table 8-A result of 6.19 microgram per cubic meter.
Thus, the two studies now compare very well in New York and
moderately well in Los Angeles. However, the PEDCo results for
Chicago were partly based on the erroneous 21 percent figure used
for New York. As no similar study was available for Chicago, PEDCo
assumed that Chicago's motor vehicle contribution to TSP levels
would be halfway between that of New York and Los Angeles, or 17
percent. Given that the New York percentage is now 8, the same
assumption would yield 11 percent for Chicago or a reduction of 35
percent. Thus, the PEDCo results for Chicago should be multiplied
by 0.65 to adjust for this error. The adjusted Chicago results are
also shown in Table 9. As can be seen by comparing the Chicago
results in Tables 8-A and 9, four out of five of the PEDCo monitors
fall within the range of the two Table 8-A monitors and agreement
can be said to be quite good.
Because this PEDCo study examined a number of monitors in each
city, further analysis of the locations of these monitors was
performed to determine any possible localized effects due to heavy
traffic nearby. Since the modified PEDCo results agree very well
with the Section IV results, any conclusion made concerning the
PEDCo sites should also apply to the sites modelled in Section
IV.
Numerous calls were made to state, local, and EPA regional
offices to determine the location of the SAROAD sites modelled by
PEDCo. The results are shown in Table 10. EPA guidelines for TSP
monitors were published recently and contained minimum distances
that a monitor should be located from a road to be representative
of large-scale impact s .J_6_/ These minimum distances are 1) 15
meters above and 5 meters away from the road, 2) 2 meters above
and 25 meters away from the road, or 3) any point lying on a
straight line between these two positions. As can be seen for New
York, all five monitors lie well outside these limits. Also, while
the traffic counts of the nearest streets are significant, none can
be termed 'heavily—travelled' by New York standards. Thus, the
projected diesel particulate levels at these sites should be very
represenative of large-scale areas and not representative so-called
localized impacts.
The Los Angeles sites are generally closer to the road then
the New York sites. Two out of four sites for which locations
are available meet the EPA guidlines. Again as in New York, none
of the nearest roads are exceptionally busy. From an examination
of the ambient diesel impacts at these five sites, one finds that
-------
-30-
Table 9
Projected Ambient Diesel Particulate Concentrations in 1990
Revised PEDCo Results
City
New York
New York
New York
New York
New York
Torrance,
Los Angeles
Long Beach,
Los Angeles
Los Angeles
Pasadena
Pasadena
Chicago
Chicago
Chicago
Chicago
Chicago
Site Address
Steimnan Hall ,W. 141 St
and Convent Ave .
170 E. 121 St.
Central Park Arsonal,
5th Ave., and 64th St.
240 2nd Ave .
Pier 42, Morton St.
and Hudson River
2330 Carson St.
2655 Pine Ave.
434 S. Pedro
1196 East Walnut
Kech Laboratories,
Cal. Inst. of Tech.
3500 E. 114 St.
1947 W. Polk
9800 S. Torrence Ave.
538 S. Clark St.
4015 N. Ashland Ave.
EPA Scenario
Low
3.7
3.9
3.6
4.6
4.4
9.6
10.0
12.0
10.1
11.0
17.3
8.5
9.3
8.8
7.3
(ug/m3)
High
5.7
6.0
5.5
7.1
7.0
14.9
15.4
18.7
15.6
17.1
26.9
13.2
14.4
13.7
11.3
-------
Table 10
Saroad Monitoring Sites
City
New York
New York
New York
New York
New York
Torrance,
Los Angeles
Long Beach,
Los Angeles
Los Angeles,
Los Angeles
Pasadena,
Los Angeles
Site Address SAROAD Code
Steinman Hall 334680057F01
W. 141 St. , and
Convent Ave .
170 E. 121 St. 334680014P01
Central Park 334680005H01
Arsonal, 5th Ave.,
and 64th St.
240 2nd Ave. 334680010H01
Pier 42 ?
Morton St. , and
Hudson River
2330 Carson St. 058260001P01
2655 Pine Ave. 05410001F01
434 S. Pedro 054180001101
1196 East Walnut 055760004101
Elevation
Above Ground
22.9 m
(75 ft.)
22.9 m
(75 ft.)
13.73 m
(45 ft.)
18.3 m
(60 ft.)
7.63 m
(25 ft.)
1.22 m
(4 ft.)
7.63 m
(25 ft.)
27.4 m
(89.8 ft.)
5.5 m
(18 ft.)
Distance From
Large Road
91.5 m
(300 ft.)
30.5 m
(100 ft.)
30.5 m
(100 ft.)
15.25 m
(300 ft.)
91.5 m
(300 ft.)
Not
Available
1.83 m
(6 ft.)
5.0 m
(16.4 ft.)
17 m
(55.7 ft.)
Vehicle Count
(Vehicle/day) Comments
12,100
16,500
17,900
26,600 Air Resource Board
lists 27.45m (90
ft.) above ground, i
i — '
16,800 City lists 4.58m
(15 ft.) above
ground .
15,000
15,000
13,500
18,000
-------
Table 10 (con't)
PEDCo TSP Monitoring Sites
City
Lennox ,
Los Angeles
Chicago
Chicago
Chicago
Chicago
Chicago
Site Address
11408
Blvd.
3500
1947
9800
Ave .
538 S
4015
Ave .
La Cienega
E. 114 St.
E. Polk
S. Torrence
. Clark St.
N. Ashland
SAROAD Code
05390000101
14122002H01
141220033F01
141220005H01
141220005H01
141220004H01
Elevation
Above Ground
7.0 m
(23 ft.)
9.46 m
(31 ft.)
4.57 m
(15 ft.)
4.88 m
(16 ft.)
39.9 m
(133 ft.)
19.2 m
(64 ft.)
Distance From
Large Road
19 m
(62.3 ft.)
24.4 m
(80 ft.)
30.5 m
(100 ft.)
21.35 m
(70 ft.)
9.15 m
(30 ft.)
3.6 m
(12 ft.)
Vehicle Count
(Vehicle/day)
25,000
Not
Available
4,674
9,400
11,600
25,100
Comments
i
u>
KJ
1
-------
-33-
the largest impact is at the San Pedro site, which is the furthest
from the least-travelled road. From this observation, it would be
difficult to argue that the other sites were overly influenced by
heavy traffic. The result for Los Angeles, then, is the same as
that for New York, the monitors appear to be very representative of
large-scale impacts.
The Chicago monitors are slightly more difficult to analyze.
Four out of five are within the EPA guidelines, though two of
these four monitors (Polk and Torrence) are quite near lightly-
travelled streets. The Clark St. monitor, on the other hand, is
well away from a lightly-travelled street. The impact at this
monitor (Table 9) is no different than that at the three monitors
which are nearer the road. Only the 114th Street monitor has an
usually high impact associated with it. This monitor is actually
quite far from the street, though the exact traffic count of the
street is not known.As PEDCo' s methodology was based on TSP
levels, the TSP level at this site was twice that of the others in
Chicago and upon investigation was found to be 165 micrograms per
cubic meter.5/ It cannot be determined whether the motor vehicle
contribution at this monitor is also twice that at the other four
monitors. However, as the resulting diesel particulate level is
almost 50 percent higher than that at any other monitor in any
city, it appears likely that something unusual is occurring at that
monitor. The use of the 114th Street projection should therefore
be used with caution. Otherwise, the results of the other four
monitors appear to be free from local impacts like heavy traffic
nearby and should be representative of large-scale impacts.
Given that the great majority of the monitors examined by
PEDCo appear to be representative of large-scale impacts and the
modified PEDCo results closely match those of Section IV, it would
seem reasonable to assume that the great majority monitors examined
in Section IV are also representative of large-scale impacts. As
such, either set of projections could be used to project ambient
diesel particulate impacts over large-scale urban areas.
C. PEDCo-Kansas City Study
The final comparison to be performed is between the PEDCo-
Kansas City results (Table 2) and the projection for Kansas City
developed in Section IV (Table 8-B). As can be seen, the PEDCo
projections are less than half those in Table 8-B. Somewhat
aggrevating this difference is the fact that the Section IV pro-
jection for Kansas City, MO., is the lowest to be found in Tables
8-A, 8-B, and 8-C. In other words, with respect to the impacts in
other large cities, the Section IV Kansas City impact appears to be
too low rather than too high.
Given this and the fact that the impacts shown in Table 8 are
consistent with PEDCo's three city study and GM's work, it would
appear that PEDCo underestimated the diesel's impact in Kansas
-------
-34-
City. This criticism in fact, has already been made in a previous
comparison of carbon monoxide and diesel particulate emissions in
Kansas City.llJ The problem most likely lies with the use of AQDM,
which would be expected to underestimate line sources, such as
motor vehicle .J_8/ Because of the discrepancy between PEDCo ' s
Kansas City results and that of the other studies, the impacts
shown in Table 2 should not be used as valid projections of future
diesel impacts.
VI. Conclusions
1. In the PEDCo-Kansas City study, the use of AQDM had
probably underestimated future ambient particulate levels from
diesel emission in Kansas City.
2. In the PEDCo three-city study, an error was made that
overestimated the impacts in New York and Chicago. After correc-
tion of this error, however, the resulting impacts appear to be
reasonable for further use. In addition, the locations of the
monitors modelled were such that the projections should be repre-
sentative of large-scale urban impacts.
3. The GM work has been repeated, essentially confirmed, and
extended to many other cities in the U.S. Along with the PEDCo
three-city results, these Section IV projections appear to be among
the best available and could be used in further studies.
-------
-35-
References
\J "Draft Regulatory Analysis, Light-Duty Diesel Particulate
Regulations," OANR, OMSAPC, EPA, Dec. 22, 1978.
_2_/ "Air Quality Assessment of Particulate Emissions from Diesel
Powered Vehicles," PEDCo Environmental Inc. for EPA, March
1978, Contract No. 68-02-2515.
_3_/ "Summary and Analysis of Comments on the Notice of Proposed
Rulemaking for Light-Duty Diesel Particulate Regulations for
1981 and Later Model Year Vehicles," EPA, OANR, OMSAPC, ECTD,
SDSB, October 1979.
kl Personal communications with Jim Throgmorton, PEDCo, June 15,
~ 1979.
_5_/ "The Impact of Future Diesel Emission on the Air Quality of
Large Cities," FED Co Environmental for the EPA, February
1979, Contract No. 68-02-2585.
6J "General Motors Response to EPA Notice of Proposed Rulemaking
on Particulate Regulation for Light-Duty Diesel Vehicles,"
Attachment 4, General Motors, April 19, 1979.
]_/ "Environmental Impact Statement for Lead," OANR, OAQPS, EPA,
September 1978.
8/ Grolicki, P.J., and C.R. Begeman, "Particle Size Variation in
~~ Diesel Car Exhaust," SAE 790421.
9/ Schreck, Richard J. et al, "Characterization of Diesel Exhaust
Particulate Under Different Engine Load Conditions," Presented
at 71st Annual Meeting of APCA, June 25-30, 1978.
10/ Huntzicker, James J. et al, "Material Balance for Automobile
Emitted Lead in the Los Angeles Basin," Environmental Science
and Technology, Vol. 9, 1975.
ll/ "Standard Support and Environmental Impact Statement: Na-
tional Ambient Air Quality Standard for Lead-Emissions, Air
Quality, and Environmental Impact," Appendices A through Y,
Mitre Corporation, MTR-7525, Vol. II.
12/ Telephone conversation with Richard Klimisch of General
Motors, July 10, 1979.
13/ "Air Quality Criteria for Lead," EPA, 1977, EPA-600/8-77-017.
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Reference (cont'd.)
14/ Hidy, G. M. and S. K. Friedlander, "The Nature of the Los
Angeles Aerosol," Proceedings of the Second International
Clean Air Congress, 1971.
15/ Kleinman, Michael T., "The Apportionment of Sources of Air-
borne Particulate Matter," Doctoral Dissertation at New York
University, New York, N.Y., June 1977.
16/ "Air Quality Surveillance and Data Reporting," 43 FR 34892,
August 7, 1978.
17/ Rykowski, Richard A., "Relative Impact of CO and Particulate
on Air Quality," EPA Memorandum to Charles L. Gray, Jr.,
Director, ECTD, August 1979.
18/ Neilgan, Robert E., Director, Monitoring and Data Analysis
Division, OAQPS, OANR, "Information Concerning Particulate
Emissions from Nonmobile Sources," EPA Memorandum to Charles
L. Gray, Jr., Director, Emission Control Technology Division,
OMSAPC, OANR, July 11, 1979.
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