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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                                   -2-

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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                                    -4-
                              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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                                    -5-

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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                                    -7-

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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                                     -8-

                              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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                                    -10-

     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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                               -11-

                         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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                                   -12-

     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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                                   -13-
    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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                                    -14-

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

-------
                             -15-
                      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.

-------
                                    -16-

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,

-------
                                                 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.

-------
                                                 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

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-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

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       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


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     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

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                                 -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

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                                 -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.

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                                  -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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                                 -36-


                        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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