-------
for comparison to the values during the test period. Data from each
ten-minute run were calculated as shown in table 3, then the most im-
portant aerosol and meteorological parameters were tabulated by computer
as shown in the DATA MAPS for GM run #7, shown in table 4.
Next, the background periods were averaged together and the test
periods were averaged together, using care to exclude system start-up
transients and the transient periods at the beginning and the end of
the test period. During runs #5, 8, and 11, the wind was from the
east, so that aerosol from the roadway did not consistently reach the
trailer. These are included for comparison to the car data, which are
valid for those runs. These runs were not included in the averages
calculated in table 6.
The last two columns in table 6 show the differences between the
test and background volume in the Aitken nuclei mode, and the accumulation
mode. The grand average increase in volume in the Atiken nuclei mode
3 3
was 1.49 ±.61 ynr/cm. The average increase in volume in the accumulation
3 3
mode was 0.63 ±1.05 ym /cm . However, it will be noted that the
standard deviation of the grand average is larger than the average for
the accumulation mode, and it is therefore doubtful that the increase
in the accumulation mode is significant.
Figures 7a-7d show typical surface and volume distributions for
the background and the test period measured at the trailer. These are
the averages during the test period for GM Run #7. By comparing the
surface distributions for the background and the test periods, it is
obvious that the nuclei mode is mostly due to the cars on the track.
The small nuclei mode during background conditions is undoubtedly
contributed by cars upwind of the proving grounds roadways, probably
at distances of several miles.
Figure 6 shows strip charts of the major variables measured. An
examination of this figure shows that condensation nuclei (CNC) increased
abruptly at the beginning of the test at 0740 and declined sharply at
the end of the test. This is also true of the volume in the Aitken
nuclei mode, VAN, V2, and NO. On the other hand, the volume in the
accumulation mode (VAC) stayed practically constant during the run,
55
-------
indicating that little volume was being added to the accumulation mode
by the cars on the roadway. It can also be noted that the mean size
of the Aitken nuclei mode decreased from 0.034 ym during the background
periods to 0.018 ym during the test period. This indicates that the
emitted size of the fresh aerosol from the cars on the roadway is
about a factor of 2 smaller than the aged nuclei mode aerosols contributed
by combustion sources at a much greater distance in the background.
It will also be noted that there was little addition of aerosol to the
coarse particles or little change in the coarse particle size.
Figure 8 shows strip charts for GM Run #16. During this run,
there was an abruot change in the wind from the NW of the roadway
around to the NE at 0840. Figure 9 shows the response of various
parameters to this step function change in the wind direction and
hence in the roadway as a source of aerosol. From the figure, note
that there were abrupt decreases in NO, CNC, and the volume of the
Aitken nuclei mode, VAN, with this wind shift. There was a small
change in the volume of the coarse particles and a nonsignificant
change in the volume of the accumulation mode. This is further evidence
that the roadway aerosols are essentially all in the nuclei mode.
Figure 9 shows a difference distribution for GM Run #7. This
provides further evidence that all the aerosol is added in the nuclei
mode. If figure 9 is contrasted with figure 10 for the car, it is
seen that at the trailer, there is not significant addition of aerosol
to the accumulation mode. However, the car distributions for GM 12
shown in figure 10, show significant additions of aerosol to the
accumulation mode. The conclusions that can be drawn from this is
that the aerosol additions to the accumulation mode shown in figure 10
are occurring after the aerosol has left the exhaust system of the
automobile. When the wind is across the roadway at reasonably high
velocities, it is diluted so rapidly that little aerosol is added to
the accumulation mode by the time it reaches the trailer. This is the
situation shown in figure 9. However, when the wind was traveling
parallel to the roadway as during Run 12, illustrated in figure 10,
coagulation transferred almost half the volume to the accumulation
56
-------
01 niLFORO PROU1W GROUTCS
SITE CTPC 16
TENM1HUTE OJEROGES FROM 6 « Ift>3ex73 TO ie M I
Figure 8
Strip charts of principal aerosol parameters measured by the EPA
trailer during GMPG Run 16. During this run, the wind abruptly
shifted between 0840 and 0850 from blowing the emissions from the
cars on the roadway toward the trailer to blowing away from it.
This step function in the aerosol source caused abrupt decreases
in NO, CNC, and VAN, but not in VAC. It is not clear whether
there was a significant change in the coarse particle volume, VCP.
E
i.
- z
Q.
O
A VAN * 1.6
DPG -0.021
SO -1.5
1 I
DIFFERENCE DISTRIBUTION
(AVG DURING RUN)- (AV6 BKGND)
GMPG 7 ON 10-13-75
WDIR 191°
_L
001
0 I
DP (/im)
Figure 9
Difference distribution calculated from the background and test
period averages for GMPG Run 7 measured by the EPA trailer.
Note that there is a significant addition of volume in only the
nuclei mode.
57
-------
o.
o
40
30
20
10
A VAN '3.32
DP6 0.025
SG 1.5
I I 1111 I I I I I I IIJ I I
1 DIFFERENCE DISTRIBUTIONS
RUN-BKGND
A GMPG 12 ON 10-23-75
WDIfl 186*
GMPG 10 ON 10-21-75
WDIR *226*
AVAN 21.0
DPS - 0.033
SG 1.6
AVAC »12 6
DPG-O.M
SG« I.B
i 11 in I i i i111ul
O.OC9 0.01 0.03 O.I 0.3
OP(ft.m)
10
Figure 10 Shown are difference distributions calculated from averages
of the size distributions measured by the car on the roadway
during the indicated runs and measurements of background
aerosol made before and after the test period. Included in
the figure are the volume (V), mean geometric size (DPG), and
geometric standard deviation for the resulting modes. These
are based on a fit of the difference data using the log-
normal fitting procedures.
58
-------
mode. It is interesting to observe that in spite of this mass transfer,
the nuclei mode and accumulation mode geometric standard deviations
remain essentially constant. There is, however, about a 30% increase
in the accumulation mode geometric mean diameter and a 100% increase
in the nuclei mode geometric mean diameter as measured by the car
during Run 12 as compared to the background value.
RESULTS FROM THE UNIVERSITY OF MINNESOTA CAR
The University of Minnesota (UM) car was used to obtain aerosol
data and sulfate samples. Most of the discussion here concerns the
UM aerosol data, although some comparisons with the available sulfate
data have been made.
The car arrived in Detroit in time to start participating in the
test program on October 6, 1975, GMPG Run #4. In Runs 4-13, aerosol
samples were obtained both inside and outside the car as the car
traveled around the track with the test fleet. For Runs 14-16, the
car was used to measure aerosol at different positions around the
track and did not travel with the test fleet. The off-the-track data
obtained by the car were used to compare the response of the car
aerosol sampling system with the trailer aerosol sampling system.
These data were used to calculate the background aerosol size distributions
that would have been measured by the car had the car been used to
obtain background data.
A. Data Format
The test conditions for all runs are summarized in table 2.
Presentation and interpretation of the aerosol data obtained with the
car is complicated by the fact that the car was a moving sampling
platform, so that both space and time variations of aerosol characteristics
were encountered. Hence, the data are presented in several different
ways. Tables 8 and 9 are DATA MAPS for the car obtained during Runs
7 and 12, respectively. These tables give run number, time, track
position, meteorological and aerosol data. The position on the track
is indicated by distance from the northern end when the car is traveling
59
-------
south and distance from the southern end when the car is traveling
north. The northern and southern ends of the track are designated as the
north and south loops, respectively. The cars circled the track in
a clockwise direction. Thus, when the car was traveling in a southerly
direction, it emerged from the north loop (at a location designated 0
miles south), traveled down the east side of the track passing the
position labeled 0.5 mi. (S), 1.0 mil. (S), etc. The trailer was
located at a position 30m east and approximately 1.3 miles south
(midway between the north and south loops).
When the aerosol data were obtained from inside tie car, it was
impossible to identify the aerosol with a specific location on the
track because the car acted as a large volume which integrated the
sample over the spatial distances on the order of the track length.
Aerosol data listed for each run include: condensation nuclei
counts (CNC), total number concentration calculated during aerosol
modeling (NTM), V2, V3, V3~, Aitken nuclei volume concentration
(VAN), volume mean diameter for the Aitken nuclei mode (DPG VAN),
accumulation mode volume concentration (VAC), and volume mean diamter
for the accumulation mode (DPG VAC).
The variation of VAN and VAC with track position and time are
presented in a more graphic form in figure 11. In its center, a map
of the track is illustrated. A set of time coordinates have been
superimposed on the map. These axes read away from the center of the
sheet with earliest times near the center and later times further
away. Aerosol data for outside samples (samples taken from outside
the car through the bag sampling system) have been plotted on the
figure with the numerical values of VAC and VAN placed on the figure
in the position corresponding to the space and time at which the data
were obtained. The format is (VAN, VAC).
B. Discussion of Aerosol Data Size Distributions
It is apparent from tables 8 and 9 and figure 11 that both
aerosol nuclei and accumulation mode volumes, VAN and VAC, vary as
the car moves around the track. Although the ratio of VAN to VAC
60
-------
10: 00 All 9: 00AM 8:00AM North Loop 8:00 AM 9:00 AM 10:00 AM
(VAN=5.8,VAC=9.4)
o
(2.7,9.6)
(2.1,9.1)
2,0 ml(N)
(6.1,9.0)
(3.8,9.0)
-1.5 ml (N)
(1.3,8.9)
.5 mi(S)
1.0 mi(S).
EPA
TRAILER
(5.3,14.0)
(5.9,9.6)
(3.3,10.3)
1.3
(7.2,9.4)
1.0 mi(N)
(2.9,10.2)
(8.9,11.5)
Numbers in parentheses are
(VAN, VAC)
where VAN is the volume In the
Aitken Nuclei mode and VAC is
the volume in the Accumulation
mode. Units used are ym^cm"^.
.0.5 mi (N)
(5.9,10.2)
(5.6,10.2) (2.5>1o.3)
1.5 ml(S)
(2.4,10.6)
(6.1,10.1)
2.0 ml(S)
.3,10.
u
(6.4,9.9)
(6.0.12J3)
South Loop
Figure 11 Distribution of the nuclei and accumulation mode aerosol
volumes around the roadway for GMPG Run 7.
61
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63
-------
varied somewhat with track position and time, the basic submicron
bimodal character of the aerosol, which was apparent in the trailer
data, was always present. Figures 12 and 13, which show the outside
average volumetric size distributions obtained for Runs 7 and 12,
respectively, clearly illustrate this bimodality. Run 7 was quite
typical for both car and trailer. The average Aitken nuclei mode
volume, VAN, and accumulation mode volume, VAC, are 4.56 ± 1.72 and
3 3
9.79 ± 0.61 ym /cm , respectively. The uncertainties given are one
standard deviation. This compares with background values of 0.05 ±
.05 and 8.43 ± .22 ym3 for VAN and VAC, respectively. Thus most of
the aerosol produced by the cars is added to VAN. The main difference
between the average car size distribution and the average trailer
size distribution for Run 7 is that VAN outside average for the car
is significantly larger than VAN average for the trailer: 4.56 ±
33 33
1.72 ym /cm , compared to 1.96 ± 0.42 ym /cm . The average values of
VAC for the car and trailer are about the same, 9.79 ± 0.61 and 10.4 ±
3 3
0.15 urn /cm , respectively. This behavior is consistent with the
view that the direct aerosol contribution from the car exhaust is to
VAN.
Run 12 is of particular interest because extremely high values
of both VAN and VAC were measured by the car. The average wind
o
direction during this run was 180 ; in other words, the wind was
blowing directly down the track. This apparently allowed significant
buildup in concentration along the track. The average values of VAN
and VAC are 22.9 ± 3.6 and 26.6 ± 6.9 ym3/cm3, respectively. Background
values of VAN and VAC were 0.15 ± 0.04 and 12.2 ± 0.5 um3/ctn3. It
is apparent that under these conditions, there is significant volume
addition to both VAN and VAC by the cars. The wind direction along
the track allows the aerosol to build up with little dilution so that
there is time for significant mass transfer by heterodisperse coagulation
from VAN to VAC; thus a large contribution to VAC as well. The
phenomena will be examined further in the section entitled "Discussion
of Car Data."
64
-------
ftUC. OF RUNS- 6
O1 MILFORO PROVING GROUNDS
SITE CM PG ? OUTSIDE AUG. CAR 19x13/75
3 18 11 12 13 14 15 16 17
2 02E 06
2 64E 06
1 09E 03
23 97
062 .81
Figure 12 Car average aerosol volume distribution for GMPG Run 7.
The average is for the samples taken in the center portion
of the track, nearest the EPA trailer.
CM HILFORD PROUING GROUNDS
SITE GM PC 12 CAR'OUTSIDE AVERAGE 16x23/77
AUERAGE OF RUNS; Z 3 4 5 6 7 8 9 13 14 15 16
7 13E 06
6 HE 06
4.91E 03
48 28
Figure 13 Car average aerosol volume distributions for GMPG Run 12.
The average is for the samples taken in the center portion
of the track. For this run, the wind was almost exactly
parallel to the roadway. Note that VAN = 22.91 ym3/cm3
for this run as compared to VAN =4.56 um-Vcm^ when the
wind was across the roadway (GMPG Run 7, Figure 12)
-------
Figures 12 and 13 also shown an aerosol volume mode above 1.0
ym, the coarse particle mode. The average size distribution for Run
7 (figure 7d) shows that coarse particle volume is comparable to the
volume below 1 ym, the fine particle volume. On the other hand, the
average size distribution for Run 12 (figure 12) shows that the
coarse particle volume is small compared to the fine particle volume.
This provides evidence that little coarse particle volume is being
added by the cars. Otherwise, a buildup in concentration similar to
that observed in the submicron range would be expected to occur in the
supermicron range.
C. Variation of Aerosol Concentrations and Size Distributions with
Car Position and Time
Examination of the data map in table 9 and the around-the-track
aerosol map in figure 11 for this run shows that there is a significant
variation in VAC and VAN during the run, and that the total nuclei
3 3
plus accumulation mode volume sometimes exceeds 60 ym /cm . The
relatively large variation observed during the run probably resulted
from the fact that the wind was shifting slightly during the run, and
the slight shift away from the down-the-track wind direction would
signficantly change the aerosol volumes observed.
This behavior is also apparent in the plots shown in figure 14.
Here the variation of CNC, VAN and VAC are plotted against time. The
values of CNC and VAN vary with time in essentially the same manner.
Since most of the nuclei count should be contributed by the nuclei
mode, this is to be expected. However, VAN and CNC were measured by
two independent, completely different instruments (the EAA and the
CNC), so that it is pleasing to the high level of agreement between
them. Note that all through the run, the nuclei count was very high.
Its average was 7.1 x 106 ± 1.6 x 106 number/cm3. CNC, VAN and VAC
all show significant variation with time. The standard deviations
were 22, 16, and 26% of the mean for CNC, VAN and VAC, respectively.
These variations probably result from charges in the vehicle operating
66
-------
1.5
i e
0 5
0.0
3.0
2.0
1 0
0.0
4.0
3.0
20
O1 MILFORD PROUING GROUNDS
SITE CM PC 12
POINT DflT« FROM 7 30 10-'23^75 TO 10 48 18/23/75
CMC
E+l
1.0
,uac
E+l
TIME(Hr)
IB
11
Figure 14 Strip charts of CMC, VAN and VAC for GMPG Run 12. Note
the increase VAC at the beginning and end of the test
period. This suggests that when the cars are idling or
moving at low speeds there is an increased output of aerosol
in the accumulation mode or a decrease in the effective
dilution of aerosol emissions.
67
-------
conditions as they circle the track as well as changes in wind direction
and velocity which alter the aerosol dilution and residence time over
the track.
Average values of VAN, VAC, wind direction and wind speed for
all test days are summarized in table 7. For each day, averages of
all northbound runs, all southbound runs, overall average of all
outside-the-car data, and overall average of all inside-the-car data
are presented. In addition, the difference volumes, AVAN and AVAC,
are presented. These difference volumes are obtained by subtracting
the best available average background values of VAN and VAC -rom
those measured using the car system during the test. Unfortunately,
in most cases, the background data was only available from the aerosol
analyzing system in the trailer.
When the background aerosol sampled through the trailer inlet
system and measured with the trailer EAA was compared with the same
background aerosol sampled through the car inlet system and measured
with the car EAA, a systematic difference was observed. The values
of VAN determined by the car system were about 70% of those obtained
by the trailer system, and the values of VAC obtained by the car
system were about 85% of those obtained by the trailer system.
Whenever it was necessary to use background data obtained with the
trailer to obtain difference distributions for the car, the trailer
values were corrected by multiplication by .7 for the nuclei mode
volumes and .85 for the accumulation mode volumes. In addition,
since the background aerosol concentration changed with time during
the run, an average based on the data obtained both before and after
the run was used for the background correction.
The background values of VAN were small compared to run values;
hence, any errors in them will not significantly alter the AVAN.
However, the background value of VAC was always a large fraction of
the run VAC. An examination of the data listed in table 7 shows that
typically AVAC determined by this method was only slightly larger
than the standard deviation in the average run VAC. These measurements
68
-------
are thus not believed to be highly significant. On the other hand,
the values obtained under all conditions were positive and it is
believed that there was a contribution by the cars to VAC in most
cases. Under certain conditions, for example at 7:35 (Run #4) of
GMPG 7 when the cars were parked on the track idling (see table 8),
and for most cases in GMPG 12 and GMPG 13 where the wind direction
was parallel to the track, the contributions to VAC by the test fleet
are indisputable.
D. Comparison of Aerosol Measurements Made Inside and Outside of
the Car
Aerosol concentrations measured inside the car in both the
nuclei and accumulation modes are significantly lower than comparable
measurements made outside the car. Average values of VAN and VAC
both inside and outside are listed in table 7.
The ratio of VAN inside to VAN outside averaged over all the
runs is 0.79 and the corresponding ratio for VAC is 0.70. This loss
of aerosol evidently results from impaction and diffusion to the
walls in the fresh air ducts, the heater core and fan, and the air
conditioner. It is rather surprising to note that the loss of volume
from the accumulation mode is greater than that from the nuclei mode.
Losses through duct systems of this type would be expected to be
lower in the size range of the accumulation mode rather than that of
the nuclei mode. It is difficult to deduce a plausible explanation
for this behavior without further detailed analyses of particle
losses along the aerosol path to the passenger compartment. Since
the difference between these ratios is probably not significant, such
a detailed analysis is not warranted at this time.
As a consequence of aerosol losses in the car ventilation ducts,
determination of the difference volumes for the aerosols measured
inside the car was complicated slightly. These difference volumes
would be strictly valid only if background aerosols were obtained
with the car moving through the background aerosol under exactly the
69
-------
same sampling conditions as during a run. It was impossible to
obtain such background data, so the following corrections were made.
As described above, the average inside-to-outside volume ratios were
0.79 and 0.70 for VAN and VAC, respectively. It was assumed that the
same ratios would apply to background measurements, and they were
corrected accordingly. Difference volumes were calculated using
these corrected background levels.
These difference volumes indicate a substantial aerosol contribution
by the test fleet to both VAN and VAC. The overall average contribution
3 3
to the nuclei mode measured inside the car is 6.7 ± 3.95 ym /cm , and
the contribution to the accumulation mode is 2.57 ± 2.25 ym /cm .
This compares with average outside contributions of 8.57 ± 5.17 and
3.62 ± 4.03 ym3/cm3 for AVAN and AVAC, respectively.
E. Influence of Wind Direction and Track Position on Measured
Aerosol Volumes
Whenever there was a significant across-the-track wind component,
car data obtained on the upwind side showed lower aerosol concentrations
than on the downwind side. For example, during Run 7, the average
o
wind direction was 198 ; thus, there was a significant crosswind
component with the southbound lanes in the downwind direction and the
northbound lanes in the upwind direction. As a result of this crosswind,
the car measured higher aerosol concentrations in the southbound lane
than in the northbound lane. The average value of VAN measured in
3 3
the southbound lane was 5.4 ym /cm , and in the northbound lane, 4.3
3 3
ym /cm . The same type of upwind-downwind dependence was observed in
most runs, which is of course to be expected. Figure 15 shows a plot
of the ratio of AVAN measured in the southbound lane to AVAN measured
in the northbound lane, plotted against wind direction. For wind
o
directions between 0 and 180 , the northbound lane is downwind and
o
should be higher, whereas for wind directions between 180 and 360 ,
the southbound lane is downwind and should be higher. Figure 15
shows this to be the case, and as can be seen, a simple sine wave
describes the data fairly well.
70
-------
h-
cc
o
<
>
2
1.5
I
o
CO
Z .5
> .2
AVANo
log AVAN = ~Q-028-0.264sinWDIR -
4
10
0 60 120 180 240 300 360
WDIR,(DEG.)
Figure 15 Shown is the ratio of the aerosol volume added to the nuclei
mode on the southbound side of the roadway to the volume on
the northbound side plotted against the wind direction. It
is seen that the data is fitted well by a sine function.
71
-------
F. Discussion of Car Data
The data described above show that aerosols produced by catalyst
equipped cars appear in the atmosphere mainly in two size ranges:
(1) nuclei mode at about 0.02 ym volume mean diameter, and (2) accumulation
mode at about 0.25 ym volume mean diameter. The ratio of average
AVAC to AVAN for each day is given in table 7. It varies from about
0.83 to 0.16 with an average value of 0.37. Thus on the average,
about 3/4 of the aerosol added by the cars appears in the nuclei
mode. The large run-to-run variation is mainly due to uncertainties
in AVAC, which is small in magnitude compared with the two VAC values
(both subject to errors) used to calcuate AVAC.
It appears that the primary emissions from the car add to VAN
and the observed addition to VAC results from heterodisperse coagulation.
Thus aerosols which have had more opportunity to age before sampling
should exhibit a higher ratio of AVAC to AVAN. This effect is clearly
illustrated in figure 10, which shows volumetric difference size
distributions for Runs 10 and 12. For Run 10 with a crosswind (WDIR
o
= 224 ), and therefore a short aging time before sampling, nearly all
of the volume appears in the nuclei mode. For Run 12, on the other
hand, for which the wind was blowing nearly straight down the track
o
(WDIR = 180 ), the aerosols could build up and age over the track.
Hence time was available for mass transfer to the accumulation mode
by heterodisperse coagulation. The difference distribution for Run
12 shows that under these conditions a significant volume, about 1/3
the total submicron volume, was added to the accumulation mode. Also
note the size shift in the nuclei mode between Run 10 and 12 from DPG
= 0.025 to 0.033 ym. This suggests that under the conditions existing
during Run 12, the nuclei mode also grew by monodisperse coagulation.
Further evidence of transfer from the nuclei mode to the accumulation
mode -- when wind directions are nearly parallel to the track, is
provided in table 7. For Runs 12 and 13, both with down-the-track
wind directions, the ratios of AVAC to AVAN are 0.63 and 0.83, respectively,
compared with an average ratio for the other eight runs of 0.28. Run
72
-------
13 (WDIR = 176 ) however, does not show the very high values of both
AVAC and AVAN observed in Run 12 (WDIR = 180°). Apparently the
slight departure from exactly down-the-track wind conditions in Run
13 significantly increases aerosol dilution, thus reducing aerosol
concentrations; while at the same time, still allowing enough residence
time over the track for heterodisperse coagulation to take place.
73
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APPENDIX I
EEECTRICAL AEROSOL ANALYZER CONSTANTS
To obtain aerosol particle size distributions from the currents
measured with the TSI Model 3030 Electrical Aerosol Analyzer it is
necessary to multiply the Al's calculated from the I's by a constant.
When the EAA is operated at an nt = 10 as it was in the GM study, it
has been found that the sensitivities as published by Liu and Puia are not
applicable as they are given in the paper. The published calibration
was done with moncdisperse aerosols, and the response en heterodisperse
aerosols will not be the same. Although various more complex calculation
schemes are being developed at Minnesota and by other investigators
using the EAA, it was decided to develop a single set of constants
that would improve the calculated distributions but would not require
complex calculations.
Constants "B" were used for the on-line data reduction performed
in Mil ford. Constants HC were used for all of the results presented
in this report.
To develop these new constants, a new matrix applicable to a
distributed aerosol was first derived from the Liu-Pui matrix3.
Then currents for a model distribution having both a nuclei and
accumulation mode were calculated. Next, using the AN's from the
model distribution and the I's calculated from the matrix, new sen-
sitivities were calculated so that when the new sensitivities were
multiplied by the Al's, the model AN's are obtained.
These new constants were evaluated against a variety of model
distributions before use, and it was concluded that the maximum
errors in integral parameters such as VT, ST, and NT were less than
15% for the extreme cases observed in the sulfate study. A complete
report on the derivation and calculation of these constants is being
written for distribution in early April.
aPTL Publication #237
74
-------
7 -3 -1
Table 1-1. Electrical Aerosol Analyzer Constants for nt = 10 cm sec
Channel No.
Dpi - \im
1
2
3
4
5
6
7
8
9
10
.0042
.0075
.0133
.0237
.0422
.075
.133
.237
.422
.750
1AI)1 AI. -
(AN/AI^
(B)
Liu - Pui
A
9.52 x 10°
c
4.17 x 105
K
1.67 x 10^
8.70 x 104
4.44 x 104
2.41 x 104
1.23 x 104
(AN/Ali)i (I.+1- I.)
particle/pa
(HC)
Whitby - Cantrell
6
1.36 x 10°
K
3.16 x 10°
c
1.53 x 10°
1.57 x 105
3.09 x 104
2.43 x 104
1.52 x 104
6.67 x 10
3.51 x 102
5.68 x 10
1.33 x 10
Note: Constants HC developed for DPGVAN = .04 ym,
SGN = 1.7, VAN - 1 ym3cm"3, DPGVAC = 0.35 ym,
SGAC = 2 and VAC = 30 ym3cm~3
75
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Appendix II
Nomenclature, a Description of Terms and Units
Below are listed the mnemonics, definitions and units for the various
parameters referred to in the text.
General
TIME
Meteorology
WDIR, WD
WSPD, WSP
TOUT
DEWPT
RH, RELHUM
PRESS
BBRAD
UVRAD
6as Chemistry
NO
N02
N0x
NO/NOV
Equipment References
EAA
CNC
ROYCO 220, R220
ROYCO 225, R225
ROYCO 218, R218
TWO MASS
hours, eastern daylight time
wind direction, clockwise degrees from north
wind speed, kilometers/hr.
o
outside temperature, C
o
dew point, C
relative humidity, percent
barometric pressure, mrn-Hg
2
broad bond radiation, mW/cm
2
ultraviolet radiation, mW/cm
Nitric Oxide, PPM
Nitrogen Dioxide, PPM
total Oxides of Nitrogen, PPM
ratio of Nitric Oxide to total Oxides of
Nitrogen
electrical aerosol analyzer; Thermo-Systems,
3030
condensation nuclei counter, Environment One,
RICH 100
Royco model 220 optical particle counter
Royco model 225 optical particle counter
Royco model 218 optical particle counter
Impactor - filter sampler with cut point at
2.0 vim
76
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Aerosol Mass Fraction
SC calculated sulfur concentration yg/m
SM measured sulfur concentration, yg/m
p Aerosol particle density, g/cc
Particle Size Distribution
DP particle diameter-interval boundary, pm
DPI particle diameter-geometric midpoint, ym
DN particle number concentration, in a size
interval number/cc
DN/DLDP particle number concentration per log-size
interval, No/cc.logD
DS surface area concentration, in a size interval,
mm2/cc
DS/DLDP surface area concentration per log-size interval,
ym2/cc. log Dp
DV volume concentration, in a size interval,
ym3/cc
DV/DLDP volume concentration per log-size interval,
ynvVcc. log D
Integral Particle Parameters
BSCAT light scattering coefficient, m" (nephelometer
data)
ANC, CNC Aitken Nuclei concentration, number/cc
1,2,3,4,5 particle size subranges, see diagram above.
NT,ST,VT total number, surface area, and volume concentrations
N2,S2,V2 number, surface area, and volume concentrations
in subrange -2
N3,S3,V3 number, surface area, and volume concentrations
in subrange-3
N4,S4,V4 number, surface area, and volume concentrations
in subrange-4
N5,S5,V5 number, surface area, and volume concentrations
in subrange-5
77
-------
Integral Particle Parameters (cont.)
N3-,S3-,V3-
N4+,S4+,V4+
number, surface area, and volume concentrations
in subranges 2 & 3
number, surface area, and volume concentrations
in subranges 4 & 5
.001 .01 0.1 1.0
PARTICLE DIAMETER, w
Figure II-l. Particle Size Subranges
10
100
Modal Fit Parameters
VAN
VAC
VCP
VFP = VAN + VAC
SGAN, SGAC, and SGCP
DPGVAN, DPGVAC, and
DPCVCP
NTM
volume in the Aitken Nuclei mode, ym /cc
3
volume in the accumulation mode, ym /cc
volume in the coarse particle mode, ym /cc
3
volume of fine particles, ym /cc
Geometric Standard Deviations of the AN, AC
and CP modes respectively
Geometric Mean Diameter of the AN, AC and CP
modes respectively ym.
total number concentration derived from the
log-normal distributions fitted to the data,
No./cc.
78
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ACKNOWLEDGMENTS
The work was performed under the financial support of Environmental
Protection Agency Research Grant No. R 803851, Aerosol Research
Branch, Environmental Sciences Research Laboratory. Since we were
not requested to participate until July 1975, our participation was
only made possible by the efforts of W. E. Wilson of the EPA, the
program officer, who arranged funding in a short time.
The authors would like to thank Ping Auw and Kui-Chiu Kwok for
their help during the assembly of the car; Dr. V. Marple for his help
in locating and arranging the lease of the car; Mr. Ruben Falldin,
Mechanical Engineering Department shop superintendent, for his help
in getting things done on very short notice; and Dr. R. Jordan, Head
of the Mechanical Engineering Department, for his help in making the
many arrangements that such a project entails. We would also like to
thank Tom Ellestad, Lester Spiller, and Ron Speer of EPA for their
help during operations in Milford.
REFERENCES
1. GMR - 1967 "Plans for General Motors Sulfate Dispersion Experiment,"
General Motors Environmental Science Department Research Laboratories,
Warren, Mich., (Sept. 1975).
2. E. S. Macias and R. B. Husar, "A Review of Atmospheric Par-
ticulate Mass Measurement Via the Beta Attenuation Technique,"
kzAo&ok Gzn&icutioYi, Meo4UAe.men£, Sampling, and
pp. 535 Academic Press New York (1976).
J. D. Husar, R. B. Husar and D. K. Stibits, Analy. Chm. 47:2062
(1975).
B. Y. H. Liu and D. Y. H. Pui , "A Sub-Micron Aerosol Standard,
and the Primary Absolute Calibration of the Condensation Nuclei
Counter," 3. Colloid Inte.i^ac.e. Scl. 47:155-171 (1974).
B. Y. H. Liu, R. N. Berglund and J. K. Agarwal , "Experimental
Studies of Optical Particle Counters," Atmoi. Env-iAon. 8:717-732
(1974).
79
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B. W. Loo, J. M. Jaklevic and F. S. Goulding, "Dichotomous
Virtual Impactors for Large Scale Monitoring of Airborne Parti cul ate
Matter," F^cne PcuvticJiu- h&ioAot Gen&i&tion, Mejzt>uAme.nt, Scmpting,
and knaJLy^Jj* , Academic Press, pp. 311 New York (1976).
7. K. T. Whitby and B. K. Cantrell, "Atmospheric Aerosols - Characteristics
and Measurements," Presented at ICESA Conference, Las Vegas,
Nev. (Sept. 1975).
8. K. T. Whitby "On the Multimodal Nature of Atmospheric Aerosol
Size Distributions," presented at the VIII International Conference
on Nucleation, Leningrad, U.S.S.R. (Sept. 1973).
9. K. T. Whitby, "Modeling of Multimodal Aerosol Distribution,"
presented at GAF, Bad Soden, Germany (1974).
10. K. T. Whitby "Modeling of Atmospheric Aerosol Size Distributions,"
Report on Grant #R 800971, "Sampling and Analysis of Atmospheric
Aerosols," submitted to Atmospheric Aerosol Res. Sec., Div. of
Chem. and Phys., Air Pollution Control Office, Environmental
Protection Agency (May 1975).
11. J. A. Nelder and R. Mead, The, Compute* J. 7:308 (1965).
12. D. F. Miller, D. A. Trayser and D. W. Joseph, "Size Characterization
of Sulfuric Acid Aerosol Emissions," Presented at the 1976
Automotive Engineering Congress and Exposition, Feb. 23-27,
Detroit, Mich. (1976).
80
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PARTICULATE SULFUR EMISSION RATE FROM A SIMULATED FREEWAY
£. S. Macias, R. A. Fletcher, J. D. Husar, and R. B. Husar*
ABSTRACT
The. pafLticutate. buJL^uJi e.mti>A wi£h two btage, AmptnAA and weAe -&ab^e.qu.e.ntly
ana£yze.d faon. 4a£j$u/i, u&iviQ the. ktat>k vapofi^LzatLon-^tame. photometric.
detection method. PaAtic.aJLate. mcu>£ wai at6o monx^to^ed u^ith a beta.
aXtenaa^con maAA monitofi. The. AutfiuA. ^tow fiate. ^on. thiA e.xpeMAjne.nt
IA)CU> fiound to be. 5.3 _+ 7.2 yg/m/^ec and the, buJifavJi m-ib&jjon note. peA
C.OA itiat, 3.5 +_ O.B yg/m. Tn-66 co-Vteipond4 to a 12. -^3.01
o^ the. faeJi buL^uJi em-itte-d 06 patticatate ^at^uA. It wa4 at6o
-tnat t,aJL^(jjT. accounted J^OA app/toxxjnatett/ 201 ojj ^Cne ^n
mai^. Mea^u/tementi ^cn an automobJJLe, ^indic.ate.d that the. &uJL^u)i c.on-
ce.n&uitionA on the. fioaduxiy and /ctii^cde a pa^^enget uenXc£e we^e com-
paAab£e and we^.e A-anJJLaA to the. conc.e.ntsiationA meaia/ted 75m downwind.
INTRODUCTION
Gasoline contains trace quantities of sulfur, on the order of
0.03 weight percent. From non-catalyst equipped cars, the sulfur is
emitted largely as S02- In catalyst equipped cars, however, a sub-
stantial portion of the fuel sulfur may be emitted in oxidized form.
The current available data (ref. 1) suggest that most of the sulfate
emissions have the chemical form of sulfuric acid. At present,
*The authors are with Washington University, St. Louis, Missouri,
where Drs. Macias and Fletcher are in the Department of Chemistry
and the Drs. Husar are in the Department of Mechanical Engineering.
81
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82
-------
however, the only information available is from dynamometer tests.
In this paper we present results of measurements of roadway aerosol
emission rates obtained as participants in the GM Sulfate Dispersion
Study during October 1975.
The primary objective of this work is the determination of the
particular sulfur emission rate from the roadway. The method employed
was the determination of the roadway particulate sulfur flow rate
across a plane 15m from the edge of the road. The fine particulate
sulfur concentration was determined at five heights above the ground
at 15m from the road as shown in figure 1. The wind velocity profile
perpendicular to the roadway was measured at three heights above the
ground and at 15m from the road. The automobile generated particulate
sulfur level was distinguishable from a background level of comparable
magnitude by employing high time resolution sampling (30 min) using
a two stage on-line mass monitor with aerosol sjze separator (TWOMASS)
sampler (refs. 2-4) and high sensitivity sulfur analysis using the
flash vaporization-flame photometric detection methods (refs. 5, 6).
The total mass concentration of both fine and coarse particles was
determined in 10-minute intervals using a TWOMASS automated mass
monitor located in a van.
A TWOMASS sampler was also operated by the University of Minnesota
in a car traveling with the test fleet. These filter samples were
also analyzed for sulfur.
Four aerosol charge detectors and three high response anemometer
bivanes were operated at several heights above the ground to illustrate
the aerosol concentration and flux fluctuation with subsecond time
resolution. This work will be reported in a later paper.
The daily configuration of the Washington University experiment
is given in table 1.
83
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Table 1. Experiment Summary
Equipment in Operation
Date
9/29/75
10/1/75
10/2/75
10/3/75
10/6/75
10/8/75
10/10/75
10/13/75
10/17/75
10/20/75
10/21/75
10/22/75
10/23/75
10/24/75
10/27/75
10/29/75
Run
272
274
275
276
279
281
283
286
290
293
294
295
296
297
300
302
TWOMASS TWOMASS
Sulfur Mass
Samplers Analyser
On Towers In Car
5
7
7
7 x
7 1 x
7 1 *
9 1 X
9 1 *
10 1
9
9 1
10 1
1
9 1
9
9
Aerosol
Chargers
5
5
5
5
5
4
4
4
4
4
4
Prevailing
Wind
Direction
E
NW
NW-N
SW
w
E
W
SW
NE
W
SW
NE
S
S
SW
N
NOTE: West wind component required for useful data.
84
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EXPERIMENTAL PROCEDURES
A. Test Conditions
The experiment was conducted on the 10km North-South Straightaway
at the GM Proving Ground in Milford, Michigan during October 1975.
The Proving Ground is located about 50km northwest of Detroit and
30km north of Ann Arbor in a very flat, lightly wooded area. The
test track is 30m (6 lanes) wide; however, the experiment was conducted
with two lanes of traffic in each direction simulating a four-lane
freeway.
The test fleet consisted of 350 catalyst-equipped vehicles from
model years 1975 and 1976 (equipped with air pumps) with relatively
low mileage (1000-5000 miles). The vehicles were driven in packs of
22, synchronized so that two packs (one in each direction) arrived at
the experiment site simultaneously every 29 seconds; therefore, the
automobiles arrive in pulses of 44 vehicles every 29 seconds or 5462
vehicles per hour. The fuel used was Amoco unleaded, with a sulfur
content of 0.33 ± 0.0005 weight percent. The fleet had a weighted
average fuel consumption calculated from EPA dynamometer tests
on similar models of 7.74 kilometers per liter (18.2 miles per
gallon). Actual fuel consumption figures for the GM test fleet were
not available; therefore, we have assumed a realistic fleet average
value of 6.97 kilometer per liter (16.4 miles per gallon), which is
90% of the EPA test value. A typical run was conducted as follows:
at 0715 (E.S.T.) vehicles began to arrive on test track, and the
test run was conducted from 0745-0945. By 1000, all vehicles were
off test track.
B. Aerosol Sampling
Aerosol sampling was performed with the TWOMASS sampler which
separates particles into two size fractions. Coarse particles are
impacted on a glass fiber filter; the remaining particles are collected
on an identical high-efficiency glass fiber filter. This system is
85
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shown schematically in figure 2. The single stage impactor head has
a 4.5mm diameter inlet aperture with a 4.5mm jet-to-plate distance.
The impactor was designed to have 50% efficiency for 3.5 urn particles.
This cutoff size was chosen as a compromise between the proper
separation of the two modes of the atmospheric aerosol size distribution
and the simulation of the aerosol removal characteristics of the
human upper respiratory system.
One sampler was located at 30m west of the roadway at a height
of 1m and five samplers were located 15m east of the roadway at
heights of 1.0, 1.9, 3.9, 5.6, 8.2m. One to four additional samplers
were operated at various heights and distances from the roadway.
Results from these extra samplers were used for cross-comparison and
determination of internal consistency. These samplers were used to
collect aerosol for sulfur analysis. One additional TWOMASS sampler
located in a van 20m from the roadway at a height of 3m was fully
instrumented for particulate mass analysis as described below.
The samplers were synchronized to advance the filter tape and
begin a new sample every 30 minutes on the half hour. The filter
tape on the TWOMASS mass monitor in the van advanced at 0700 and
1100. Samples taken between 0800-0930 were used to determine the
roadway aerosol contribution. Samples taken between 0630-1730 and
1000-1100 were used to determine background concentrations.
The horizontal and vertical wind conditions were determined by
GM at 15m east of the roadway at heights of 1.5, 4.5, and 10.5m
above the ground.
C. Atmospheric Particulate Mass Measurement
A TWOMASS sampler employing the beta attenuation technique was
used for high resolution monitoring of atmospheric aerosols as shown
in figure 2. This instrument independently analyzed the mass con-
centrations of two particle size fractions in 10 minute intervals.
Both the impaction and filtration heads of the TWOMASS had independent
source detector systems. Carbon-14 was used as a source of beta
86
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TWOMASS
Si DETECTOR
IMPACTION
STAGE
14,
'source
FILTRATION
STAGE
Si DETECTOR
-V
source
TO PUMP
COUNTER
PROGRAMMABLE
CALCULATOR
COUNTER
Figure 2 Schematic diagram of the TWOMASS sampler and mass monitor.
87
-------
particles which were detected by a solid state surface-barrier
detector. The accuracy of the aerosol mass concentration with this
3
instrument is 11%, with a precision of 4 yg/m .
D. Particulate Sulfur Analysis
Analysis of water soluble fine particulate sulfur was performed
using a flash vaporization-flame photometric detection method (refs.
5,6). The analyzing system shown in figure 3 consists of a flash
vaporization vessel, flame-photometric detector, integrator and
strip chart recorder. The sample vaporization is accomplished by
capacitor discharge across a tungsten boat, resulting in resistance
o
heating to 1100 (.. Vaporized gaseous decomposed products of sulfur
compounds are carried to the flame-photometric detector by a stream
3
of clean, charcoal filtered air at a flow rate of 2 cm /sec. The
detector used in the Meloy SA-160 flame-photometric total sulfur
sensor.
Samples were collected with TWOMASS samplers on a portion (0.3
2 2
cm) of a light weight (1.9 mg/cm ) low pressure drop glass-fiber
filter (Pallflex E 70/2075 W) with a consistent and low sulfur blank
2
of 0.36-0.5 yg/cm. A water extract of each fine particulate sample
2
was prepared by punching out a circular filter segment (0.6 cm )
2
containing the aerosol deposit (0.3 cm ). The segments were extracted
in double distilled-deionized water. The sulfur samples were collected
over one-half hour intervals. Under the conditions of this experiment,
for an uncertainty of 11%, the minimum detectable ambient sulfur
3
concentration was 0.44 yg/m (ref. 6). This includes inaccuracies
in sample air volume determination, sulfur determination and variations
in sulfur blank on the filter. The fine particle sulfur concentration
determinations from this work are given in table 2.
88
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4-
II)
ro
S-
CD
(O
O
r-
-l->
ea
O)
x:
o
oo
O)
s_
CD
89
-------
Table 2. Fine Particle Sulfur Concentration.
30 min Average Values Ending at Time Indicated
(in yg/m3)
Date
9/29/75
10/1/75
tun Tower
272 CM 5
(15. Eut)
274 CM 1
(30. Wot)
CM 5
(15. Eut)
Height (m)
1.0
1.9
3.6
5.6
8.2
1.0
1.0
1.9
8.2
Time I
0700
Time 1
1300
0.38
0.42
0.02
0.46
[EOT)
0730
[EOT)
1330
2.46
1.20
0.165
0.03
0800
1400
1.23
2.23
0.0
0.08
0830
1.18
1.74
0.15
0.65
4.03
1430
0.26
1.71
0.44
0.07
0900
1.89
4.21
3.13
1.16
4.03
1500
0.39
0.81
0.56
0.11
09 VI
2.81
12.67
3.30
3.32
4.03
1530
1.45
0.165
0.71
1000
8.63
12.15
9.53
8.23
4.03
1600
0.58
2.77
1.09
0.38
11130
1630
0.75
0.51
0.07
0.35
1100
lime (EPT)
10/10/75
10/13/75
10/20/75
283 CM 1
(30m West)
CM 5
(15. Eut)
GM 6
(30a Eut)
GM 7
(50. Eut)
286 CM 1
(30m West)
CM 5
(15m Eut)
CM 6
(30. Eut)
GM 7
(50m Eut)
293 EQR
(15. Eut)
1.0
1.0
1.9
3.6
5.6
8 2
1
1.0
1.0
1.9
3.6
5.6
8.2
1.0
1.0
1.0
1.0
0700
2.80
Tine
0700
1.48
1.52
1.44
1.20
1.12
1.48
Time
1030
1.00
0.31
0730
2.97
7T12
2.46
2.77
3.31
(EDT)
0730
1.39
1.64
1.88
1.49
1.66
3.38
1.02
1.68
(EDTJ
1100
1.34
1.14
0800
3.39
3.26
3.13
2.79
7.30
3.16
0800
1.51
2.02
2.63
2.43
2.09
1.46
1.17
2.42
1130
1.75
0.82
0830
2.04
3.84
3.48
2.72
2.66
2.91
4.71
3.00
0830
1.50
2.73
3.29
2.96
2.17
:.2C
1.78
2.15
1200
1.92
1.45
0900
2.45
3.62
3.48
3.93
3.01
3.19
4.23
2.80
0900
2.12
3.03
3.51
2.17
2.26
2.25
1.60
2.69
1245
1.17
0.95
0930
2.76
3.84
3.60
3.73
2.66
3.48
4.17
2.95
0930
1.79
3.50
3.59
2.09
1.85
3.10
1.94
2.65
1300
1.17
I.'l2
1000
2.77
3.48
3.15
3.43
2.42
3.89
3.37
2.74
1000
1.91
3.00
3.44
2.49
2.88
2.44
1.84
3.04
1030
3.01
2.99
2.57
2.61
2.14
3.45
3.21
2.38
1010
2.14
3.37
2.72
1.64
2.65
2.46
1.28
2.99
1100
2.23
3.22
2.35
3.49
2.54
1100
2.16
2.63
3.50
2.30
1.70
2.45
1.40
2.70
Tl»e (EOT)
10/21/75
10/24/75
10/27/75
10/29/75
294 EQR
(15 m Eut)
297 EQR
(15 m Eut)
300 CM 1
(30 m Ueet)
CM 5
(15m Eut)
EQ1
(15 . Eut)
302 tQR
(15 . Eut)
CM 1
(X) . Weit)
(15s. tut)
1.0
1.0
1.0
1.0
1.0
1.9
3.6
5.6
8.2
1
1
1
1
1.9
3.6
5.6
8.2
0735
2.02
1.40
Time
0700
Time
0700
Tine
0700
1.46
0.26
0800
2.40
1.70
(EOT)
0730
4.47
(EST)
0730
1.49
(EST1
0730
1.60
2.07
1.23
1.87
1.39
2.31
0.46
0.72
0.36
0.50
0.07
0.49
0.04
0910
3.52
8.24
0800
3.34
0800
1.39
0800
2.20
2.99
1.62
1.97
1.77
2.90
0.93
0.21
0.25
1.11
0.43
0.4*
0.76
0940
4.36
2.10
0830
3.64
0830
1.69
0830
2.80
3.04
2.11
2.00
1.91
3.07
0.75
0.095
0.66
1.07
0.93
1.07
0.41
1022
5.32
1.69
0900
3.27
0900
1.65
0900
1.72
2.94
1.69
2.48
2.17
3.20
0.75
0.42
0.78
2.10
0.78
1.12
0.71
1132
2.37
1.72
0930
4.03
0930
1.33
0930
3.08
3.11
2.94
2.30
1.97
3.21
0.43
1.14
0.92
1.07
0. 48
0.85
0 69
1200
1.43
0.55
1000
5.34
1000
1.29
1000
2.24
2.M
2.02
1.69
1.46
1.47
0.33
0.40
1.21
0.3*
0.17
0.20
0.17
1215
2.73
1.71
1030
4.53
1030
1.51
1030
1.20
1.60
1.51
1.42
1.22
2.20
0.11
0.55
1 97
0.48
0.63
0.0
0.0
1250
3.19
1.15
1100
2.52
1100
1.53
1100
1.20
1.95
1.36
1.33
1.48
1.92
0.44
0 29
0.20
0.11
0.20
0.01
90
-------
RESULTS
A. Particulate Sulfur Emission Rate from the Simulated Freeway
The particulate sulfur flow rate across a plane was determined
by simultaneous measurement of the particulate sulfur concentration
profile and wind velocity profile 15m downwind from the edge of the
roadway. The flow rate per unit length of the roadway (Q/L) is
determined by the separate measurement of the fine particulate
sulfur concentration as a function of height [C (z)], and the com-
ponent of the velocity profile perpendicular to the roadway [U(z)]. This
flow rate is calculated from the following integral:
h
Q/L = /*Cs(z)U(z) dz .
It is assumed that this flow rate corresponds to the actual emission
rate, which is valid for fine particulates, but is not correct for
settling coarse particles. The average emission rate per car per
unit length of roadway can be calculated by dividing this flow rate
by the traffic density.
The particulate sulfur concentration from each sampler was
determined in half-hour averages. A linear interpolation of sulfur
concentration from samples collected prior to and after each run was
used to determine the background concentrations. A sampler located
30m upwind was used to monitor the temporal variation of the background
during each run and was used as a check on the linear background
used. The sulfur contribution from the roadway was obtained by
subtracting the background concentration from each half-hour sulfur
measurement. It should be noted that the background concentration
was at least as large as the roadway contribution and it should be
mentioned that as in figure 4, on some days the background varied as
a function of time.
91
-------
PARTICIPATE S'JLF'Jh CONCENTRATION
GM PROVING GROUNDS I5rr. EAST TOWER
OCTOBER !3, 1975, (286)
OCTOBER 27, 1975 (300)
2 -
1
O
15
UJ
O
Z
O
O
C/)
nROAPWAY SULFUR
CONTRIBUTION
Figure 4 Half-hour average sulfur concentration data from
runs 286 and 300. The shaded area is the excess
sulfur concentration due to the roadway.
92
-------
The excess sulfur concentrations due to the roadway for run 286
(10/13) and 300 (10/27) at the five heights (1.0, 1.9, 3.6, 5.6, and
8.2m) are shown as the shaded area in figure 4. The excess sulfur
values generally vary between 0-1.5 yg/m . At a height of 2m (approximately
the height of an adult), for run 286 (10/13), the average roadway
o
particulate sulfur concentration was 1 yg(S)/m .
The vertical variation of roadway particulate sulfur concentration
and the wind profile perpendicular to the roadway was determined for
each half-hour interval and then averaged for the entire run as
shown in figure 5. The third frame of this figure shows the vertical
profile of the horizontal roadway particulate sulfur flux, C (z)U(z),
2 1
in units of yg m sec . Numerical integration of the flux with
respect to height yields the flow rate per unit length of roadway
Q/L. It is evident from figure 5 that the roadway plume height
exceeded 9m. This phenomenon has also been observed in the aerosol
charge profile measurements. The concentration profile above 8.2m
was estimated as indicated by the dashed portion of the curve. The
half-hour average flow rates for the four runs analyzed in detail
are given in table 3. Half-hour average sulfur concentration data
from runs 286 and 300 (October 13 and 27) are shown in figure 4.
The wind direction on run 302 (10/29) was within 15% of being parallel
with the roadway. Under these wind conditions, measurement of the
sulfur flow rate by this technique gives results with large uncertainties.
Therefore, the data from this run will not be included in the determination
of the particulate sulfur emission rate.
The particulate sulfur flow rate from the roadway averaged over
the entire experiment was 5.3 +_ 1.2 yg/m/sec. For the traffic
density of this experiment, 1.52 cars/sec, the particulate sulfur
emission rate per car was 3.5 +_ 0.8 yg/m (5.6 +; 1.3 mg/mile). This
emission rate corresponds to a 12 j^ 3.0% conversion of the fuel
sulfur emitted as particulate sulfur using the fuel sulfur content
and fuel consumption rate given above.
93
-------
cr
u
o
UJ
m
V)
o
I
5
o
z
IE
a.
2
o
CD
CVJ
(iu)2 'J.H9I3H
94
-------
Table 3. Sulfur Flow Rates, Q, (yg/(m.sec))
Half-hour Run
Ending Time 283 286 300 302
0830 2.4 4.2 5.2 2.7
0900 4.6 3.7 5.1 1.2
0930 4.6 10.5 7.6
Daily Average 3.9 6.1 5.9 2.0
95
-------
B. Roadway Aerosol Mass
The TWOMASS mass monitor gave no indication of an increase in
coarse particle mass during the experiment due to the roadway.
The fine particle mass did show a definite roadway component as
indicated by the shaded portion in figure 6. The mass monitor
indicated an average fine particle mass increase due to the roadway
3
of 4.4 ± 0.8 yg/m for four days of the experiment. These measurements
and the sulfur measurements were made at a different distance from
roadway and, therefore, can not be directly compared. However these
data indicate that sulfur accounts for approximately 201 of the fine
particle mass.
C. Temporal Variability of the Roadway Aerosol
The driving pattern of the GM test runs was such that packs of
automobiles arrived at the sampling site in 29-second intervals;
thus, the source intensity was pulsed with the period of half a
minute. The use of rapid response aerosol detection devices, such
as the aerosol charger, permits the temporal resolution of the
emission strength as shown in figure 7. This typical chart recording
of the charger output clearly indicates the periodicity of the
concentration with a period of 29 seconds. The data suggest the
utility of the charger for diffusion experiments and other cases
where time resolution is important.
It may also be noted that the charger signal downwind of the
-12
similated freeways was about 3 x 10 amps which is about a factor
of 20 to 50 higher than the charge values for background aerosol -
that is, upwind of the roadway.
D. Particulate Sulfur Concentration on the Roadway
Fine particulates sampled inside and external to the passenger
compartment of the University of Minnesota vehicle driving in the
test fleet were analyzed for sulfur in order to assess the particulate
sulfur concentrations on the roadway. These data, summarized in
96
-------
20
10
30
^ 20
Ti
to
5
LJ
O
cr
UJ
10
30
10
20
to
RNE PARTICLE MASS
10 WIN AVERAGES
GM PROVING GROUNDS
OCTOBER 3,1375
(276)
OCTOBER 6,1975
(279)
OCTOBER 10, B75
(283)
OCTOBER 13,1975
(286)
ROADWAY AEROSOL CONTRIBUTION
8 9
TIME (hrs)
10
Figure 6 10 min average fine particle mass concentration data. The
shaded area is the excess fine particle mass due to the roadway.
97
-------
CU
+-> O S-
3 rC 3
O O- CD
i-
-f-> CU
O) > C
-O T-
cu
CD x: c
cn-M 2
i- O
ro 4- -C
JC O tO
o
>> o
i 4-> CO
O T-
CO O ro
o -
S- -O CO
S- O
OJ O) i-
O CU
01 4- a.
S- O
ro
(-> C
S- O -C
ro - +J
x: +J -r-
o u S
E
3 QJ
ro 4- CD
O ro
i- ro to
Q_ to
>, to to
I fO O.
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3
cn
98
-------
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01
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r-
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«3- CO 1 l£> 1 LO
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00 i 1 00 1 <£>
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LO co CM i *
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CO CO CM CO LO «d"
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LO LO LO LO LO LO
r^* r**s r^« r^* r^* r*^»
*^^ ^*^ "^^ ^^^ "^*» "^^^
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i i i CM CM CM
"^^ ~"^. ^ *^-^ *^. ^*
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10
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r
3
10
cu
s_
1.
cu
r
Q.
E
re
CO
cu
E
S- 3
CU i
i O
S- Q. =>
QJ E
i re S
a. co o
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re cu
co E "O
3 C
co < re
co o
et > CO
2: co
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3 o s:
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4-> 4-> CD
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QJ QJ >
cz. cu
-------
table 4, indicate that under a variety of wind conditions, the
particulate sulfur concentrations were comparable within experimental
error inside and outside the vehicle. Furthermore, these concentrations
were about the same as the concentrations measured at 15m from the
roadway.
CONCLUSIONS
In this study, we have measured the sulfur emission rate from
automobiles traveling on a simulated freeway in order to assess the
impact of automobiles, specifically those equipped with catalytic
converters, on the ambient particulate sulfur levels. The particulate
sulfur emission rate per car was determined to be 3.5 ± 0.8 yg/m.
This corresponds to a 12 ± 3.0% conversion of the fuel sulfur into
emitted particulate sulfur. It was also found that sulfur accounted
for approximately 20% of the fine particulate mass. Measurements in
an automobile indicated that the sulfur concentrations on the roadway
and inside a passenger vehicle were comparable and were similar to
the concentrations measured 15m downwind.
ACKNOWLEDGMENT
The authors are deeply grateful to the General Motors Corporation
for their hospitality during this experiment. Thanks go to Dr.
Steven Cadle of the GM Technical Research Center for his help in
providing wind data and information on the test fleet. The authors
are also grateful to Dr. William Pierson for his comments on this
work.
This work was supported in part by the U. S. Environmental
Protection Agency under grant OZR80389601.
REFERENCES
1. W. R. Pierson, "Sulfuric Acid Generation by automotive Catalysts,"
paper #42, Symposium on Auto Emission Catalysis, Div. of Colloid
and Surface Chem., ACS 170th National Meeting, Chicago, August
27, 1975; Chem. Te.chno£. (to be published)
100
-------
2. E. S. Macias and R. B. Husar, "A Review of Atmospheric Participate
Mass Measurement via the Beta Attenuation Technique," In: P-tcc,
Symposium on F-cne PaKtictnA, Minneapolis, Minn. (1975).
3. E. S. Macias and R. B. Husar "High Resolution On-Line Aerosol
Mass Measurement by the Beta Attenuation Technique," In: PX.OC..
o^ thu Second Int&incutional Con^eAence on Nu.cJLe.aA. MethocLs in
EnviAonrnzntaJL Rue,aAdh, Vogt, J. R. (ed.) USAEC, Oak Ridge,
Tenn., 1975.
4. E. S. Macias and R. B. Husar "Atmospheric Particulate Mass
Measurement with the "TWOMASS" Beta Attenuation Mass Monitor,"
Submitted for publication, 1975.
5. J. D. Husar, R. B. Husar and P. K. Stubits, "Determination of
Submicrogram Amounts of Atmospheric Particulate Sulfur," Ano£.
Chm. 47, 26062, 1975.
6. J. D. Husar, R. B. Husar, E. S. Macias, W. E. Wilson, J. L.
Durham, W. K. Shepherd and J. A. Anderson "Particulate Sulfur
Analysis: Application to High Time Resolution on Aircraft
Sampling in Plumes," A&noApk&iic. EnviJtovmint (in press).
101
-------
COMPARISONS OF DISPERSION MODEL ESTIMATES
WITH MEASURED SULFATE CONCENTRATIONS
William B. Petersen*
ABSTRACT
A fiicet o& about 400 cataty&t equipped vehicle* wer.e operated on
the 1.0-km tut tsiack at GM1* Mi£&or.d Proving Ground, Thi6 type. o&
con&Lolted ex.perijnent provide* an excellent opportunity to compare.
estimate* £tom the. EPA. HIWAV Mode/ with measured So, concentration*.
Concentration estimate* ^fiom HIWAV ar.e composed with tampting
mzntf, ob&eAvad ^on 4eueAo£ weefei dating moaning kauAA.
o^ the. modeJt at the. tie.c.e,ptoft. h&ightd and at Ae.veAat di^tancu downwind
^n.om the. tut tna.dk. i* atf>o investigated.
HlWAy give* concentration estimate* but in COACA when the wind*
wene neon penpendicuJtan to the tAjaek. It oveAet>timate& concentration*
when the windt> weAe near, pasiattet. VuAi,ng un&tabte atmobphenic
condition*, HWAV modeti> concentnationA welt, for. stable condition*,
HIWAV oveAeAtimateA concentration*.
INTRODUCTION
Recent interest in sulfate emissions from catalyst equipped
vehicles caused an experiment to be initiated in which roadside
sulfate exposures from a fleet of catalyst equipped vehicles were
measured. A major purpose of this experiment was to gather data to
determine the physical and chemical properties of aerosols emitted by
automobiles equipped with catalytic converters under simulated
freeway conditions. The purpose of this paper is to compare the
*The author is a physical scientist with the U. S. Environmental
Protection Agency's Research Triangle Park, North Carolina Environ-
mental Sciences Research Laboratory.
103
-------
measured sulfate concentrations with estimated concentrations for
each sampling period and receptor location from the EPA HIWAY Model
(Zimmerman and Thompson, 1975). It should be empfow/czecf that the
results contained here are pn.tUjn-inan.ij and do not represent an
exhaustive analysis of the data. Although further analysis may
indicate how the model may be improved, that is not our main purpose
here.
In the past there have been a number of studies in which estimates
from HIWAY were compared with measured concentrations. For the State
of Tennessee, Noll (1975) used CO data from several highways to
evaluate the performance of three highway models, one of which was
the EPA HIWAY Model. Badgley (1975) conducted air quality studies at
several different sites for the Washington State Highway Commission,
Department of Highways, and made comparisons between estimates and
measured concentrations for several models including HIWAY. Kenneth
Noll et al. found that HIWAY tends to overestimate concentrations
when the winds are parallel to the roadway and underestimate concentra-
tions when the winds are perpendicular to the roadway. Regarding
atmospheric stability categories, Noll found that HIWAY tends to
overestimate for stable conditions and underestimate during unstable
conditions. The study prepared for the Washington State Highway
Commission shows similar results for the wind direction categories.
While the above study sites were on public highways, the General
Motors Sulfate Dispersion experiment was at Mil ford Proving Ground.
A fleet of about 400 vehicles was driven on a 10-km test track during
the morning hours on 16 different days. Air quality measurements
were made over half-hour periods and meteorological parameters
measured and averaged over half-hour periods.
A test track provides several advantages in a dispersion study.
Traffic volumes and vehicle speeds can be determined accurately. The
automobiles in this study were all catalyst equipped. Also, this
experiment included the use of a tracer, sulfur hexafluoride, which
was measured at the same receptors as was sulfate. This enabled
checks of dispersion independent on the vehicle emissions and without
high background interferences.
104
-------
SITE DESCRIPTION
The test track used for the experiment was a 5-km north-south
straightway at the Milford Proving Ground. Milford Proving Ground is
located in the gently rolling hills and lightly wooded area of
southeastern Michigan about 50 km northwest of Detroit and 30 km
north of Ann Arbor. There are only two major highways near the test
trackI-96, 7 km to the south, and M-23, 6 km to the west. The test
track is essentially level, with elevations varying less than 1 m
over the length of the track except at the ends where the track is
banked. For a more detailed description of the surrounding terrain
and the facilities located at the site, see GMC (1975).
Meteorological instrumentation and sequential samplers for
measuring SO. and SFfi concentrations were mounted on eight towers.
Figure 1 shows the perpendicular distances of the eight towers from
the center of the test track. The width of the four-lane track is
25.4 m, with a median width of 11.8 m. Although the roadway would
facilitate three lanes of traffic in each direction, the lane closest
to the median on either side was not used and therefore was included
in the median width. Temperature sensors and uvw anemometers were
located at 1.5, 4.5, and 10.5 m on Towers 1 through 6. The temper-
ature and wind sensors were located at 1.5 m on Towers 7 and 8. The
sequential samplers were at 0.5, 3.5, and 9.5 m on Towers 1 through 6
and at 0.5 m on Towers 7 and 8.
MODEL
The EPA HIWAY Model (Zimmerman and Thompson, 1975) is a short-term
Gaussian model providing estimates for averaging times of about 1
hour. Traffic emissions are simulated by a straight-line source of
finite length for each lane of the highway. A uniform emission rate
is assumed for each line source. Air pollution concentrations down-
wind from each line source are formed by a numerical integration
along the line source of a simple Gaussian point-source plume.
Initial spreading of the pollutant in the turbulent wake of a vehicle
is modeled by specifying appropriate values for the standard deviations
105
-------
Tower 1Q
42.7m
Lane 1
Lane 2
Tower 2
o
14.6m'
Tower 3Q )r
25.4m
11.8m
Lane 3
Lane 4
16.5
Tower 4
o
27.7m
Tower 5,
O
42.7m
Tower 6
'O
62.7m
Tower 7,
O
112
7m
Tower 8,
O
Figure 1. Orientation of test track and perpendicular distances of
the meteorological towers from the center of the test track.
106
-------
of pollutant distributions (i.e., dispersion coefficients). Based on
a limited amount of data, a conservative estimate of the initial
vertical standard deviation of the plume was determined to be 1.5 m.
The initial horizontal standard deviation of the plume was selected
as 3 m. The HIWAY Model requires information about highway geometry,
automotive emissions, and meteorological conditions.
EMISSION FACTORS
Probably nothing more dramatically emphasizes the importance of
a good estimate of the emission factor than to simply state that the
concentration estimates are directly proportional to the emission
factor. Personal communication with Dr. David Chock at General
Motors concluded in an estimate of the sulfate emission of 0.037
g/vehicle-mile. Dr. Chock indicated that 0.037 was a mean value of
the sulfate emission applicable for the cars driving at a steady
speed of 50 mph. However, he also pointed out that there was con-
siderable scatter about the mean. The traffic volume was held
constant during the experiment at about 1,365 vehicles per hour per
lane. Since the traffic volume and the vehicle speed remained
constant during the experiment, it was assumed that the emission rate
also remained constant.
Emission rates for sulfur hexaflouride (SFg) are given in table
1. The tracer (SFg) was released continuously from eight specially
equipped vehicles. In order to simulate the dispersion of SO^,, the
SFg gas was released directly into the exhaust streams. The eight
vehicles were evenly spaced in the traffic, with four in each lane.
At an average speed of about 50 mph, a total of 64 passes by the
sampling point was made by tracer-releasing vehicles during each 30-
minute sampling interval.
107
-------
Table 1. SF, Emission Rate per Unit Length
b (in
Day
274
275
276
279
281
283
286
290
293
294
295
296
297
300
302
303
Outer Lanes
(1&4)
3.166
3.085
3.053
2.282
3.150
3.150
3.182
3.214
3.214
3.198
3.166
3.166
2.378
3.166
3.053
3.134
Inner Lanes
(2&3)
2.941
2.362
3.085
3.150
3.1f>6
2.394
2.378
2.411
3.182
3.166
2.394
3.166
3.166
3.150
3.037
3.134
This table was provided by Dr. David Chock of General
Motors Corporation in a personal communication.
108
-------
BACKGROUND CONCENTRATIONS
Background concentrations of SO. for each half-hour period
were determined from the measurements and were added to the modeled
concentrations before comparisons were made. Measurements of SFfi
at the sampling sites upwind of the roadway were so low that the
SFg background was assumed zero.
In order to make the estimate of background concentrations
as objective as possible, the following scheme was used. The test
track is oriented north-south with the meteorological towers oriented
basically east-west, Tower 1 being on the west side of the track
and Tower 8 being the farthest tower on the east side. When the wind
o o
direction was between 0 and 180 , the concentrations at Towers 7 and 8
were averaged and that value was used for the background concentration.
o o
If, however, the wind direction was between 180 and 360 , the three
measured concentrations on Tower 1 were averaged and used as background.
Table 2 shows the extreme half-hour estimates of background
concentrations for SO. for different azimuth ranges. The number of
half-hour periods in each azimuth range is also recorded. There appears
to be only a slight relationship between background concentration and
wind direction. However, when the wind was from the north there was
a consistently low background. Figure 2 gives daily fluctuations of
SO^ background concentrations. The daily background concentration
is the average of half-hour background concentrations during that
day (the experiment was conducted mostly during the morning hours). The
o
lowest average daily background concentration was 0.57 pg/m and
the highest average concentration was 16.33 yg/m . The range of the
background concentration for individual periods is shown for each
day in figure 2.
ATMOSPHERIC STABILITY
The dispersion parameters a and a used in the EPA HIWAY Model
are basically extrapolations to shorter travel distances of the dis-
persion parameter values of the Pasquill stability type used in
109
-------
o
Table 2. Range of Sulfate Background Concentrations (yg/m )
for Different Wind Direction Azimuths
Number of
Observations
2
3
2
4
5
3
1
0
0
0
0
2
13
8
4
5
6
2
2
5
0
3
10
Azimuth
Range
1-15
16-30
31-45
46-60
61-75
76-90
91-105
106-120
121-135
136-150
151-165
166-180
181-195
196-210
211-225
226-240
241-255
256-270
271-285
286-300
301-315
316-330
331-360
High
7.30
11.52
10.74
8.87
7.09
16.96
13.47
-
-
-
-
12.64
15.07
13.00
14.51
7.22
17.69
18.72
4.79
9.35
-
2.44
3.63
Low
3.69
2.97
10.26
2.85
2.55
6.68
13.47
-
-
-
-
11.13
5.96
1.60
3.57
2.34
8.23
17.86
4.05
2.46
-
0.92
0.37
no
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Turner (1970). Table 3 is a summary of the meteorological data
gathered during the experiment (GMC, 1975). The atmospheric
stability was given in terms of the Richardson Number, which HIWAY
cannot use directly. Golder (1972) showed a technique to convert
the Richardson Numbers to the Pasquill stability classes. However,
the method was not applicable for Richardson Numbers greater than
0.14. Since Golder's method was not applicable for all the data,
the original Pasquill method (1961) was used to specify stability
class from cloud cover, ceiling height, and wind speed. The stability
class was determined using the wind speed at the experimental site
and the observations of cloud cover and ceiling at 3-hour intervals
for Flint, Michigan (about 44 km north of the site). The stabilities
determined from ;he Richardson Number were used subjectively in
determining how fast the atmospheric stability was changing from
half-hour to half-hour. The stability class never changed more than
one class from one half-hour period to the next.
METHOD OF ANALYSIS ANALYSIS AND RESULTS
Estimates from the EPA HIWAY Model, using meteorological and
emission input for each half-hour period, were compared with measured
concentrations at each receptor location for every half-hour period.
In order to compare model estimates with measured concentrations,
factors influencing model performance were isolated. The important
factors are wind speed, wind direction, stability, and receptor locatioi,
The available time for analysis of the data did not permit an ex-
haustive investigation of these factors; for example, the simultaneous
influence of two or more factors on model performance was not
investigated.
Individual factors were considered as follows. All the data were
separated into three wind direction categories and analyzed for each
category. Next, the data were separated into stability classes and
analyzed. No interactions between stability and wind direction were
considered. All data were analyzed by receptor height and were
112
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116
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separated and analyzed by tower location. Finally, performance of
the model at different wind speeds was investigated.
A. Comparison of Concentrations With Wind Angle
Figure 3 shows plots of measured versus estimated sulfate
concentrations for three broad categories of angle of wind with the
roadway. The perpendicular category includes angles of wind with
the roadway from 60° to 120° (also 240° to 300°); that is, within ±
o
30 of normal to the test track. The oblique category includes
o o
angles of wind with the roadway from 30 to 60 . The parallel
o
category includes angles of wind with the roadway from 0 (actual
parallel) to ± 30 (within 30 of parallel).
For the perpendicular wind case, eight points were not plotted
because the estimated concentrations were outside the range of the
ordinate. These eight points all occurred during the same half-hour
period (on October 22) when the wind speed was extremely light, 0.08
m/sec, the lowest average wind speed recorded during the experiment.
The estimated concentrations during this half-hour period ranged
from 57 to 217 ug/m , with the corresponding measured concentrations
ranging from 6 to 10 yg/m .
For the oblique wind case, all the data points were plotted.
For the parallel wind case, five data points were plotted. For the
parallel wind case, five data points were not plotted because the
estimated concentrations were outside the range of the ordinate on
the plot. These five data points also occurred during the same day
(October 22) when the half-hour average wind speed was 0.35 m/sec;
concentration estimates during this period were as high as 122
vg/m3.
In all, there were 13 data points that were not plotted from
the data set. The high estimated concentrations all occurred during
very low wind speed conditions, less 1 m/sec, when the HIWAY model
would not be expected to perform well, since steady-state conditions
are not a good assumption in low wind speeds. During such low wind
117
-------
1 .57
0.95
0.890
32.704
283
10-00 20.00 30.00 40.00
MERSURED SULFRTE CONCENTRflTION
PERPENDICULAR MIND CASE
5CTOO
10-00 20.00 30.00 40.00
MERSURED SULFRTF CONCENTRflTION
OBLIQUE HIND CASE
50?00
o
°0
o.
,00
ZO
U-O
CO
10.00 20.00
30.00
40.00
o
so'Jbo
.O
lT>
2.95
1.21
0.752
25.158
469
0010.00zb-OO30.0040.00
MEflSURED SUI FflTE CONCENTRRTION
PARALLEL MIM) CASE
o
.o
g
JO
8
2.82
1 -04
0.751
35.759
992
.00 10-00
MERSURED
20.00
SULFRTE
30.00 40-00
CONCENTRflTION
50-00
All SULFATE DATA
Figure 3. Sulfate concentrations (yg/mj). B, M, R, T, N in the plots
are the intercept, slope, correlation coefficient, T test,
and number of data points respectively.
118
-------
speeds, wind directions frequently meander over wide ranges. The
regression analyses shown in the figures were performed on only the
plotted points.
Estimating background concentrations during conditions when the
wind is nearly parallel to the test track is a rather formidable
task, since the roadway emissions may be affecting samplers on both
sides of the roadway. However, in this case the background concentrations
were calculated as stated in a previous section. The bottom part of
figure 4 shows the parallel wind comparisons with no background
concentration added to the estimated concentration from the model.
It is evident from a comparison of this figure with the lower left
portion of figure 3 that the background concentrations are significant.
Perhaps other techniques for estimating background concentrations
would yield even better agreement between the model and measured
concentrations.
2.84
0.45
0.366
8.693
490
"FPSURED
30- OC 49. DC
CONCFNTRRTT-3N
'jOVcc
PMMUR MHO CASE
Figure 4. Sulfate concentrations in (yg/m ). B, M, R, T, "I in
the plot are the intercept, slope, correlation coefficient,
T test, and number of data points respectively.
119
-------
HIWAY performs best for the perpendicular wind case for both SO,
and SFA as shown by the upper left portion of figures 3 and 5. At
3
measured sulfate concentration near 20 yg/m for the perpendicular
3
wind case, the range about the regression line is nearly ± 5 yg/m .
For the oblique wind case at the same measured concentration, 20, the
model yields 23 yg/m . Scatter is much larger than in the perpendicular
3
wind case, ranging from about 17 to 35 pg/m . At measured concentrations
of 20 yg/m , during parallel wind conditions, the model estimates
concentrations at 27 yg/m , with a range in the data from 20 to 48
3
yg/m . The SFg data show basically the same trend as that of SO,.
However, from the regression line the model overestimates concentrations
by about a factor of 2 for the parallel wind case.
Whenever tl-e model estimated very high concentrations, the wind
speeds were generally less than 1 m/sec. The low wind speed conditions
occurred mostly when the winds were nearly perpendicular to the test
track. Figure 3 for the perpendicular wind case was replotted, but
not shown, for wind speeds greater than 1 m/sec. The slope remained
nearly the same, with an intercept shifting from 1.57 to 1.07 and the
correlation coefficient improving from 0.89 to 0.96. Removing
low wind speed conditions thus removed some scatter about the regression
1 i ne.
B. Comparison of Concentrations with Stability Class
Figure 6 shows the measured concentration versus the estimated
concentration for the stabilities B through F. In general, the more
unstable the conditions, the better the model performed. During
B and C stability conditions, the model slightly overestimates
at the 20-yg/m level. The results for stability B and C are very
similar, with intercepts of 2.86 and 2.42 respectively. The
slope of the regression line for B stability is .89, as is that of
stability C. The correlation coefficiencies were 0.94 and 0.92
respectively. Stability D occurred more often than any other
stability, having a total of 413 data points. During this condition,
the model had a tendency to overpredict by 5 yg/m at the 20-ygm~
120
-------
10100
-0.11
! .34
0-981
27.8r>8
226
«.oo
.00 r-oo *.oo 6.00 9.00
MERSL'RED SF6 CONfFNTRfiMON
PERPEND1CUUW HUB CASE
9 /
"/
- /^ B
-"^ "
£/X» R
&T T
Ws" N
k
r 0-05
r ! .32
r 0-610
r 9-947
r 169
7.00 4.00 6-00 8-00
HESSUREO SF6 CONCENTRRTJON
OH.IOUE MIIB CASE
0.53
1 .62
0.726
20.493
379
0.17
1 -56
0.710
28.053
774
2.00 4.00 6.00 8.00
MERSURED SF6 CCJNCENTRflT I ON
PARALLEL MIIO) CASE
lo'rbo
oo z'.oo 4'.oo s'.oo B'.OO
MEflSURED SF6 CONCENTRfiTI ON
ALL SFs DATA
Figure 5. SFg concentrations in (PPb). B, M, R, T, N in the plots
are the intercept, slope, correlation coefficient, T test,
and number of data points respectively.
121
-------
B = 2.86
M = 0-89
R z 0.939
T = 25.271
N = 88
jfc.oo
"
10-00
20-00
30.00
CCo.
cc*1
Oo
ZO
^S.OO 10-00 20-00 30-00 40-00
MEflSURED SULFRTE CONCENTRRTION
STABILITY B
to
LU
2.42
0.89
0.918
42-827
343
^J.OO 10.00
MEflSURED
20-00
SULFflTE
30-00 40.00
CONCENTRfiTION
STABILITY C
°0.00
1 .75
I .15
0.799
26-938
413
.00
z
o
z
UJ
Oo
ZO
P>o.
Om
.00 10-00 2Y-00 30-00 40-00
MEflSURED SULFflTE CONCENTRflTION
50°00
10.00
20-00
30.00
40.00
o
5C°00
B
M
R
T
N
4 .00
1 -31
0.81 1
12.070
78
STABILITY D
ooib-oozb.oc30-00ioToo
MEflSURED SULFPTE CONCENTRflT1 ON
STABILITY E
Figure 6
Sulfate concentrations in (ug/m ). B, M, R, T, N in the
plots are the intercept, slope, correlation coefficient,
T test, and number of data points respectively.
122
-------
c
s-
20
8*J
U-O
00
10.00 20.00 30.00 40-00
10.00 20.00 30-00 40-00
MEASURED SUlFflTE CQNCENTRflTION
STABILITY F
o
50°00
.o
8.96
1 .23
0-608
6.323
70
50^0
Figure 6 (con.)
level, with a range from 17 to 35
With increasing stability, the data indicate that HIWAY fails
3
to model concentrations accurately. At the 20-yg/m level, the
3
model estimates 30 and 34 yg/m for stability E and F respectively.
Precision in the model during E and F stability conditions is also
less. The correlation coefficients for E and F stability are 0.81
and 0.61. The SFg data yield the same results except that the model
tends to overestimate by a factor of 2 to 3 for stabilities E and F.
C. Comparison of Concentrations with Height of Receptor
Figure 7 shows the measured SO. versus estimates from HIWAY for
three different receptor heights 0.5, 3.5, and 9.5 m. The largest
scatter in the data occurred at the 0.5-m height, with the least at
9.5 m. The model performed about equally well for all three heights.
3
At a measured concentration of 20 yg/m , the estimated concentrations
123
-------
.00
o
»o
>-<=
£§
3°-
to**
Q
10.00
20.00
30.00
4Q.QO
o
50°00
00 10-00 20.00 30.00 40.00
MERSURED SULFRTE CONCENTRRTION
HEIGHT 0.5 METERS
50^0
00 10.00 20.00 30.00 40.00
MERSUREP SULFRTE CONCENTRflTION
HEIGHT 3.5 NETERS
50^0
B r 0.94
11 - 1 .08
R = 0.853
T = 28.017
N = 295
'.00 10.00 2&.00 30-00 40.00
MERSURED SULFflTF CONCENTRRTION
HEIGHT 9.5 METERS
§
so?bo
Figure 7. Sulfate concentrations in
are the intercept, slope,
and number of data points
(lag/m3). B, M, R, T, N in the plots
correlation coefficient, T test,
respectively.
124
-------
for the three levels from lowest to highest were 24, 24, and 23
yg/m . For SFfi the estimated concentrations increased with increasing
heights, with more scatter in the data at higher receptor heights.
D. Comparison of Concentrations with Distance
The model response with distance from the roadway is shown in
figure 8. The top left graph is an analysis of data from the tower
in the median of the test track (Tower 3). Also shown are analyses
of the data for Towers 4, 6, and 8, which represent distances of 2,
30, and 100 m from the roadside. The data show that the model is
fairly consistent through the range of distances from the roadsides.
The slopes vary from 1.16 in the median down to 0.91 at Tower 8.
Correlation coefficients range from 0.89 at Tower 8 to a low 0.68 at
Tower 4.
The data show that the model overestimates at every tower, with
the greatest overestimation occurring at Towers 3 and 4. At a
measured concentration of 20 yg/m , the model overestimates by 4 or
5 yg/m at Towers 3 and 4, and overestimates at about 2 yg/m at
Towers 6 and 8.
E. Comparison of Concentrations with Wind Speed
In an attempt to understand how the model performs under
various wind speeds, figure 9 was plotted. Measured concentrations
from all samplers on the downwind side of the test track were
averaged for each half-hour period. Estimated concentrations from
the model plus background for the same sampling positions on the
downwind side of the test track were also averaged. The differences
of these averages, model plus background minus measured are plotted
as a function of wind speed. Circles, triangles, and plus signs
represent data when the wind direction category was parallel, oblique,
or perpendicular, respectively. For the perpendicular wind case,
the data show that the model is relatively invariant for wind speeds
greater than 1 m/sec; data are similar with the oblique wind case.
125
-------
40.00
50x00
B = 1.29
Mr 1 .16
R = 0.814
T = 21.513
N = 237
'.00 10.00 20.00 30-00 ' 40.00
MERSURED SULFRTE CONCENTRflTION
TONER 3
oo To.oo 2b.o_o
MERSURED SULFfll
30-00 40-00
CONCENTRflTION
50?00
TOWER
z
o
*«o
(0
Ss-
to
10.00
20.00
30.00
40.00
o
50°00
3.56
0.93
0.804
17.635
172
10.00
MFPSURED
20.00
SUlFflTE
30-00 40-00
CONCENTRRTION
so'Pbo
2.83
0.91
0.892
14.640
57
10.00
MERSURED
00 40.00
NCENTRRTION
so'Pbo
TOO 6
rao i
Figure 8. Sulfate concentrations in (ug/m°). B, M, R, T, N in the plots
are the intercept, slope, correlation coefficient, T test,
and number of data points respectively.
126
-------
ao
o
o
o.
r-
o.
(O
o
o
D.
in
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LU
(X0_
I
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UJg
(Xo.
£0
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o.
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O
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5.60
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A OBLIQUE MIND
PARALLEL WIND
O
O O
o
o
o
_o
r-
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CD
O
O
Lo
ID
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MEflN WIND SPEED fM/SEC)
o
o
o
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*
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5'. do
Figure 9.
Estimated sulfate concentrations ninus measured sulfate
concentrations versus mean wind speed.
127
-------
However, when the winds are within 30 of parallel, the model
overestimates and lacks precision in the results.
SUMMARY
The results shown here are preliminary and represent what was
accomplished during the short time period for which data were available.
It should be noted that comparisons between measurements and estimates
from the HIWAY dispersion model have been examined by categories
based on only one parameter at a time: wind direction with the
roadway, stability class, receptor height, receptor distance, and
wind speed. It is desirable to group the data based upon two or
more parameters. This will be attempted in the future.
Figure 3 is a plot of estimated concentrations versus measured
sulfate concentrations for all the data. From the regression line
3 3
HIWAY estimates a concentration of 24 yg/m when 20 yg/m was
measured. Similarly, from figure 5 for SFg (all data) when 2 ppb of
SFg were measured, the model estimates 3.3 ppb. Why there is such a
large difference between measured and estimated concentrations for
SFg compared to SO, is not clear. Further analysis of the data may
aid our understanding of why these differences occur.
The model performed best for unstable atmospheric conditions
or when the winds were near perpendicular to the test track. The
model overestimated concentrations to the greatest extent during
stable conditions or when the winds were near parallel to the test
track. Further analysis of the data should be very helpful and should
enable modifications to the model to improve performance.
REFERENCES
1. F. I. Badgley, A. T. Rossano, D. Lutrick, H. Alsid, Tke. S&le.ction
and Calibration o& AiA Quality V-i^uS^ion Model* Foi Washington
State. Highway Line. Sou/ice^.. Washington State Highway Commission
Department of Highways. University of Washington, Seattle,
Washington (1975).
128
-------
2. D. P. Chock (1976). Personal communication,
3. General Motors Corporation, "Plans For General Motors' Sulfate
Dispersion Experiment," General Motors Research Laboratories,
Warren, Mich. (Sept. 1975).
4. D. Golder, "Relations Among Stability Parameters In The Surface
Layer," Boundary- Lay Vi Meteorology, 3:47-58 (1972),
5. K. E. Noll, T. L. Miller, R. H, Rainey, R. C. May, kUi Mon£to>Ung
Vfiogficm To Vztifum^nz The. Impact 0{, H/ujfoway* On kmbi.e.nt ktji
Quality. Department of Civil Engineering-The University of
Tennessee, Knoxville, Tennessee (1975).
6. F. Pasquilla, "The Estimation of the Dispersion of Windborne
Material," Meteonol. 90:33-49,1063 (1961).
D. B. Turner, Workbook ofi ktmo&pkesu.c. ViApesiAion E&timateA. U.
S. Environmental Protection Agency, Research Triangle Park,
North Carolina. Publication No. AP-26. 1970. 84 p.
J. R. Zimmerman, R. S. Thompson, U^eA'^ Gtu.de Fo-t f/IWAy, A
Highway MJI Pollution Mode. U. S. Environmental Protection
Agency, Research Triangle Park, North Carolina. Publication
EPA-650/4-74-008. (February 1975).
129
-------
APPENDIX
CHEMICAL SPECIATION OF SULFATE EMISSIONS FROM
CATALYST EQUIPPED AUTOMOBILES UNDER AMBIENT CONDITIONS
R. L. Tanner and L. Newman
Department of Applied Science
Brookhaven National Laboratory
Upton, New York
131
-------
CHEMICAL SPECIATION OF SULFATE EMISSIONS FROM
CATALYST-EQUIPPED AUTOMOBILES UNDER AMBIENT CONDITIONS
R. L. Tanner and L. Newman*
ABSTRACT
ki.nbon.ne, parvtictu Aamplu w&ie. obtai.ne.d on tn.e,ate.d qaantz
fai&t&iA during ki-ve. day& o& the. GaneAol Modern (GM) Bat^ato. VpeAAi.on
Ex.peJiime.nt and analyzed ^O/L total acidity, AU.I&UJU.C acid, ammoni.wm,
soluble. kuJL^ate. (two met.hodt>] , total. buJt^uA. and nWiate.. Tfiom the.
data it i& concluded that the. iwm2.d4.atn fLoadbi.de. impact
by catalyst- e.qmippe,d auto* iA o{, the. oftd&i o& 3-6
, probably all. i.n the. ^ofm o^ AulfiuAsic. ad.d (i.n agsie.ejme.nt with
EPA and EPA contfiactox. data) . Th^U, pa?iti.c.ul.ate. ^uJi^uJtLd acid em-c6.4/ton
iA ne,u&tali.ze.d by ambi.e,nt ammoni.a uiith a hat^-LL^e. o& te.n^> o& Ae.condl>,
the. note. appa>ie.ntly de.pe.nde.nt on the. ambi,e.nt ammonia c.onc.e.ntsiation.
Ex.pesujne,ntal exomp£e6 o^ (a) ^(it^uJii.c. acid impact; (b) ammoni.a- ne.utAatize.d
. -impact; and (c) pafctlatly ne.utsiaLize-d bul^ate. impact at 30
oh. 100 meteJtb downw-ind finom the. roadway one. cite.d.
INTRODUCTION
The GM Sulfate Dispersion Experiment conducted at the General
Motors Proving Ground at Milford, Michigan during October 1975 was
designed to elucidate the quantitative hazard from the sulfate emissions
of catalytic converter-equipped automobiles under ambient roadside
conditions. It provided for the participation, in addition to the GM
Environmental Sciences staff, of two branches of EPA's Environmental
Sciences Research Laboratory (ESRL) and their contractors, as well as
independently supported groups such as Brookhaven National Laboratory
*R. L. Tanner and L. Newman, Atmospheric Sciences Division,
Department of Applied Science, Brookhaven National Laboratory,
Associated Universities, Inc., Upton, New York 11973.
133
-------
(BNL). The BNL experimental work consisted of the collection of one
hour HiVol samples on treated quartz filters at two locations (2
meters and 100 meters east of the roadway) and comparison of the
analytical results with those from a background sample (30 meters west
of the roadway). In addition, low volume samples of ambient and
diffusion-processed air (ref. 1) (single cut, 50% penetration diameter =
0.07 - 0.09 ym) were collected daily at one of the downwind locations.
EXPERIMENTAL
Airborne particle samples were obtained by HiVol sampling of
HLPOn-treated qu?rtz fiber filters during the Sulfate Experiment on
10/6, 10/8, 10/10, 10/21, and 10/22 (days 279, 281, 283, 294, and 295,
respectively), and analyzed for total acidity, sulfuric acid, ammonium,
soluble sulfate (two methods), total sulfur, and nitrate as described
below.
Titratable acidity of all samples was determined by the Brosset
method (ref. 2) employing Gran titration (ref. 3) and calculated as
yg/m of H2SO». A negative number indicates that part of the pH 4
leach solution was neutralized by the collected particulate sample.
Ammonium was determined in all samples by an Autoanalyzer version of
the indophenol colorimetric techniques (ref. 4). Soluble sulfate was
determined by two methods: an Autoanalyzer turbidometric technique
(ref. 5) (all samples); and the new flash volatilization-flame photo-
metric detection (FVFPD) technique (ref. 6) (most samples). Total
sulfur was determined in selected samples by reduction to H?S with
POo, conversion to CdS and radiochemical determination after
110
metathesization to Ag?S (ref. 7). Sulfuric acid was specifically
analyzed by extraction of a portion of the filter with benzaldehyde
(ref. 8), back leach into aqueous solution and determination as
sulfate by the FVFPD method. Nitrate was determined by the hydrazine
reduction-colorimetric method (ref. 9).
The summary of data from the five sampling days for which reasonably
coherent sets of analyses were obtained is included as tables 1-5.
Sample identification is by categories A-E: A indicates the mode of
134
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sample collection, HV = Staplex HiVol sampling on 4 inches diameter
circles of H.,P04 - treated quartz; PQU = low volume sampling of
untreated air; PQDB = low volume sampling of diffusion processed air,
the latter two on 47 mm treated quartz circles. B indicates the
location of filter vis-a-vis the track: 30m up corresponds to Tower
1 (GM designation), 2m down to Tower 4, and 100m down to Tower 8. C
indicates the vertical distance in meters of the sampler from the
ground (in parentheses). D indicates the number of the sample (in
chronological order) when more than one sample was taken at a given
location during an experimental run. E indicates the duration of the
sampling in hours. The 30m upwind samples were always taken at Tower
1 from 0.5 hr before to 0.5 hr after the run; hence, for 10/8 and
10/22/75, when the winds were out of the eastern quadrant, the 30m
upwind sample is actually downwind from the track. An example from
Day'295 data table, line 3: a high volume sample was taken 2m east of
the track at an elevation of 3m above gr'ound during the second hour of
the run.
All numerical values for chemical determinations are reported in
3
units of yg/m . NA = data not yet available; ND = data which cannot
be obtained from the sample collected due to experimental limitation;
L = sample lost, no analyses performed; E = erroneous data obtained.
RESULTS AND DISCUSSION
The information which we sought to obtain from these experiments
was as follows. Camparison of total soluble sulfate by turbidimetry
of FVFPD at the upwind and downwind sites would allow quantization
of the increase in sulfate concentration due to auto emissions from
the track. The results from this part of the experiments indicate an
3
increase in sulfate at 2m downwind which varied from 3.2 yg/m on
3
10/20 (data not tabulated to 6.2 yg/m on 10/6. During four simultaneously
sampled days, data obtained by GM at the same location indicated an
average of 0.9 yg/m g>ie.ateA sulfate increase
days, EPA observed an equal sulfate increase.
average of 0.9 yg/m g>ie.ateA sulfate increase while during 2 of those
140
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Secondly, comparison of total sulfur concentrations at downwind
sites versus background with soluble sulfate levels at the same sites
would reveal whether all the increase in sulfur is ascribable to
sulfate - presumably sulfuric acid and its neutralization products.
The data show that the average difference between soluble sulfate by
turbidimetry and total sulfur (as sulfate) for nine determinations at
all sampling locations was 1.8 pg/m and the difference in mean
values by the 2 methods is 4%. Clearly the water-extracted sulfate
and total sulfur methods are equivalent and the increase in sulfur is
with high probability in the form of sulfate.
We compared data for total acidity and sulfuric acid by the
specific benzaldehyde extraction-FVFPD method to determine if increases
in acidity matched increases in sulfate at two downwind locations
relative to background, and to see if the increased acidity was
attributable to HUSO.. The acidity data obtained at 2m downwind of
track were complicated by the presence of large, basic particles
apparently generated by the vehicular traffic on the roadway and by
the fact that background aerosol particles on four of six sampling
days were basic, /t.e., neutralized part or all of the pH 4 leach
solution. The increase in total acidity and sulfuric acid documented
by the Brosset-Gran titration and benzaldehyde extraction - FVFPD
methods, respectively, was comparable for samples taken 30m or 100m
o
from the roadway: 100m from roadway, 10/6, A(Acidity) =2.8 ya/m ,
A(H2S04) = 1.4; 30 m from roadway, 10/22, A(Acidity) = 0.8, A(H2S04)
= 0.55. The benzaldehyde extraction technique was superior to total
acidity determinations for the roadside samples (2m down) although
the observed hLSO. increase was 25% or less of the sulfate increase
on a molar basis.
No influence of the roadway traffic on the ambient nitrate
levels was observed.
Determinations of ammonium concentrations at downwind sites and
background led to the following observations: No ammonium increases
over background were observed at the roadside site (2m from track)
except for a marginally significant increase on 10/22 when the NE
141
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winds placed this site 2m upwind from the track. Significant ammonium
increases were observed at downwind sites on 10/6 (100m) and 10/22
(30m) with marginally significant increases on 10/8 (30m) and 10/21
(100m). Furthermore, the ammonium increases appear to be positively
correlated with the combination of "larger than average" sulfate
increases and the ambient ammonia concentration.
Close examination of our data led to the identification of three
sampling days which illustrate the apparent correlation outlined
above. On sampling day 283 (10/10), a substantial increase in sulfate
3
over background at the 2m down site was observed (BNL =5.2 yp/m ,
mean of BNL, GM, EPA data = 6.1 yg/m ), but the ambient ammonia
concentration wa: low (EPA: <2ppb NH.J. No significant increase in
ammonium at the 100m downwind site was observed, but there was a
downwind increase in sulfate (1.2 yg/m by reduction- Ag~S),
3
acidity by Gran titration (1.0 yg/m ) and H-SO^ by extraction (1.7
yg/m ). This indicates that on this day, the emitted sulfuric acid
was being diluted, but not significantly neutralized, during transit
of the first 100m from the roadway.
A different situation was observed on 10/21 when a moderate
3
increase of 4-5 yg/m of sulfate at 2m downwind was observed and an
increase of 0.5 to 0.7 persisted at the 100m downwind site. No
acidity increase and probably no H-SO, increase was observed at the
latter site, but an increase in ammonium ^, the molar amount needed
to neutralize the increased sulfate was observed. Unfortunately, no
ambient ammonia data are available for the 10/21 date, but we would
estimate a value of 2-3 ppb to be sufficient for the observed HUSO.-
particle neutralization effect.
A situation intermediate between those for 10/10 and 10/21 was
observed on 10/6. A large increase in sulfate at the 2m downwind
site was observed (BNL = 6.2 yg/m3; mean of BNL, GM, EPA data =6.2
yg/m ) which, according to BNL data, persisted at the 100m downwind
site (4.4 yg/m ). An increase in both acidity by Gran titration
(2,8) and sulfuric acid by extraction (1.4) was observed at the
latter location, but an increase in ammonium was also observed which,
142
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when combined with the acid increase, more than accounts for the
sulfate increase. It should be noted that a relatively high gaseous
ammonia concentration of 3.3 ppb was measured by EPA during this
experiment. It is tempting to conclude that the relatively high
sulfate increase from H?S(L emissions was partially neutralized (ca.
70%) by ambient NH., during passage from the roadway to the 100m
downwind location.
Sufficient data to determine if ambient ammonia concentrations
are significantly depleted and become the limiting reagent before the
sulfate plume reaches the 100m downwind location are not available
from BNL data. However, one may calculate a mean lifetime for
emitted sulfuric acid particles under the conditions of the 10/6
experiment (increase in [H^SO.] = 1.4 ppb, and ambient [NH-] = 3.3
ppb) based on the transit time from the roadway to the 100m downwind
site:
o
Mean wind direction = 250
Mean wind speed =1.31 m/sec
Mean distance upwind to roadway = !Lu = 106m
Mean transit time to sampler = -i 3?I!/sec = 8^ sec-
Mean H^SO, particle lifetime (assume 50% conversion and linear
chemistry) = ca. 1 min.
The observation of partially or wholly ammonia-neutralized
sulfuric acid at the 100m downwind site on some experimental days is
not inconsistent with the observation by EPA of unneutralized H^SO,
at the 15m down location. The methodology is insufficiently precise
to exclude 10 or 20% neutralization at the latter location, and
overall the agreement between BNL and EPA sulfate impact data is
exceptionally good.
Additional data (acidity, sulfate, ammonium, nitrate) were
obtained using low volume sampling of ambient and diffusion-processed
air (ref. 1). The diffusion battery was arranged and operated at
conditions giving 50% pentration for particles of diameter 0.07 -
143
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0.09 ym, e.g., above the expected size range of the emitted sulfuric
acid, but lower than the size of most of the mass of ambient sulfate.
The sampling rate for the diffusion battery configuration available
3
was necessarily only about 1m /hr and the sample size was thus in-
sufficient to yield reliable data on the size distribution of the
emitted acid sulfate. It should be noted that there is no inherent
limit on sampling rate and that new diffusion batteries soon to be
available in our laboratories will be able to give 4-cut size discrim-
ination and chemical composition information at sampling rates to
3
6m /hr on 47mm diamter filters.
CONCLUSIONS
A. Sulfate emissions from the fleet of catalyst-equipped vehicles
at the GM Sulfate Dispersion Experiment resulted in increased sulfate
burdens of 3.2 to 6.2 ug/m at the immediate roadside.
B. Comparison of total sulfur and sulfate data indicates that
the auto emission of sulfur is in the form of sulfate.
C. Increases in total acidity and sulfuric acid concentrations
downwind of the track strongly infer that the sulfate emission is in
the form of sulfuric acid.
D. Ammonium increases downwind of the track, when coupled with
acidity and H2SO. data, strongly indicate that the emitted sulfuric
acid is neutralized by ammonia with a resultant mean half-life for
sulfuric acid particles of on the order of tens of seconds. This
lifetime is not unexpectedly dependent on the ambient ammonia con-
centration.
REFERENCES
1. W. H. Marlow and R. L. Tanner "Aerosol size discrimination with
determination of chemical composition by diffusion sampling,"
submitted to Science, December 1975.
2. C. Askne, C. Brossnet and M. Fermm Swedish Water and Air Pollution
Research Laboratory, Bothenburg, Sweden, IVL Report B 157,
August 1973; C. Askne and C. Brosset, Atmot,. Env-inon. 6, 695
(1972).
144
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3. G. Gran, Analyst (London), 77, 661 (1952).
4. W. T. Bolleter, C. J. Bushman and P. W. Tidwell "Ammonia in
water and seawater," Industrial Method No. 154-71w/Tentative,
Technicon Industrial Systems, Tarrytown, N. Y., February 1973,
Anal. Ckm. 33, 592 (1961).
5. Technicon Industrial Systems, Sulfiate. Method (lib via. TuA.b
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1 REPORT NO.
EPA-600/3-76-035
3. RECIPIENT'S ACCESSIOWNO.
4 TITLE AND SUBTITLE
THE GENERAL MOTORS/ENVIRONMENTAL PROTECTION
AGENCY SULFATE DISPERSION EXPERIMENT
Selected EPA Research Papers
5. REPORT DATE
April 1976
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Edited by: R. K. Stevens, P. J. Lamothe, T. G. Dzubay
W. E. Wilson and J. L. Durham
8. PERFORMING ORGANIZATION REPORT NO.
9 PERFORMING ORGANIZATION NAME AND ADDRESS
Environmental Sciences Research Laboratory
Office of Research and Development
U. S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
10. PROGRAM ELEMENT NO.
1AA601
11. CONTRACT/GRANT NO.
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Sciences Research Laboratory
Office of Research and Development
U. S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
13. TYPE OF REPORT AND PERIOD COVERED
In-house
14. SPONSORING AGENCY CODE
EPA-OkD
15. SUPPLEMENTARY NOTES
16. ABSTRACT
In the fall of 1975, General Motors conducted an extensive field experiment at
the GM proving grounds in Milford, Michigan. The purpose of the experiment was to
measure the concentrations and assess characteristics of aerosols, especially sulfates
and sulfuric acid, emitted by a fleet of catalyst-equipped cars operated under
simulated freeway conditions. In addition, emissions dispersion and meterological
parameters were measured; this data served as input for developing a plume dispersion
model.
At the invitation of General Motors, EPA, along with their contractors and
grantees, participated in this experiment. This report consists of several important
research papers that discuss and present the results of studies carried out by EPA
during the GM experiment.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COS AT I Field/Group
*Air pollution
Field tests
*Automobiles
*Catalytic converters
*Exhaust emissions
*Aerosols
particles
*sulfates
*sulfuric acid
ammonia
atmospheric
diffusion
models
13 B
14 B
13
07
07 D
07 B
04 A
F
A
13 DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
19. SECURITY CLASS (ThisReport)
UNCLASSIFIED
21. NO. OF Pf GES
149
20 SECURITY CLASS (This page)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
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