Technical Report
AIR QUALITY ANALYSIS IN SUPPORT OF A
SHORT-TERM AMBIENT AIR QUALITY STANDARD
FOR NITROGEN DIOXIDE
By: R. H. THUILLIER
W. VIEZEE
Prepared for:
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF AIR QUALITY PLANNING AND STANDARDS
POLLUTANT STRATEGIES BRANCH
RESEARCH TRIANGLE PARK, NORTH CAROLINA 27711
EPA CONTRACT 68-02-2835
333 Ravenswood Avenue
Menlo Park, California 94025 U.S.A.
(415) 326-6200
Cable: STANRES, Menlo Park
TWX: 910-373-1246
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Technical Report
February 1978
AIR QUALITY ANALYSIS IN SUPPORT OF A
SHORT-TERM AMBIENT AIR QUALITY STANDARD
FOR NITROGEN DIOXIDE
By: R. H. THUILLIER W. VIEZEE
Prepared for:
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF AIR QUALITY PLANNING AND STANDARDS
POLLUTANT STRATEGIES BRANCH
RESEARCH TRIANGLE PARK, NORTH CAROLINA 27711
EPA CONTRACT 68-02-2835
SRI Project 6780
Approved by:
R.T.H. COLLIS, Director
Atmospheric Sciences Laboratory
RAY L. LEADABRAND, Executive Director
Electronics and Radio Sciences Division
Copy No.
103
.333 Ravenswood Avenue • Menlo Park, California 94025 • U.S.A.
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CONTENTS
LIST OF ILLUSTRATIONS v
LIST OF TABLES vii
PREFACE ' ix
ACKNOWLEDGMENT xi
I SUMMARY AND CONCLUSIONS 1
'II INTRODUCTION 3
III THE SCOPE OF CURRENT PROBLEMS 5
A. General Considerations 5
B. Continuous 1-Hour Monitoring 5
1. Instrumentation 5
2. Analysis ..... 6
C. Estimates from 24-Hour Manual Sampling ........ 9
1. Instrumentation 9
2. Analysis 9
D. Estimates from Area Source Air Quality Modeling .... 11
1. Modeling Procedure 11
2. Analysis 14
E. Estimates from Point Source Air Quality Modeling ... 15
1. Modeling Procedure 15
2. Analysis 17
F. Analysis Summary 21
1. 1-Hour Observations 21
2. 24-Hour Observations 22
3. Area Source Modeling 22
4. Point Source Modeling 23
5. Combined Estimates 23
IV THE NATURE OF CURRENT SOURCE CONTRIBUTIONS 27
A. General Considerations 27
B. Source Structure Analysis 27
iii
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V ASSESSMENT OF FUTURE TRENDS 35
A. Near-Term Trends 35
B. Long-Term Trends 37
VI CONTROL REQUIREMENTS, OPTIONS, AND FEASIBILITY 41
A. Control Implications of Possible Standards 41
1. Scope of Required Control 41
2. Stringency of Required Control 41
3. Control Options 44
4. Control Feasibility and Effectiveness 45
VII INTERACTION OF THE N02 AND OXIDANT CONTROL PROGRAMS .... 47
A. The Modeled Isopleth Method 47
B. DIFKIN Photochemical Modeling 49
REFERENCES 53
APPENDICES
A SIMPLIFIED MODELING TECHNIQUES A-l
B EMISSIONS AND GROWTH DATA, BY AQCR B-l
iv
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ILLUSTRATIONS
Comparison of N02 Measurement Statistics for the
1-Hour Averaging Time
Histogram of Highest Second-Highest 1-Hour N02
Concentrations, by AQCR, Obtained by Continuous
Monitoring (1974 through 1976)
3 Comparison of N0£ Measurement Statistics for the
24-Hour Averaging Time Obtained by Two Manual
Sampling Techniques 10
4 Histogram of Highest Second-Highest N02 Concentration
Estimated Statistically from 24-Hour Measurements
(1974 through 1976) 12
5 Comparison of Annual Average NOX Concentration,
Estimated Graphically, with the Highest Annual
Average Observed in the Same City (1974 through 1976) .... 14
6 Comparison of Annual Average NOX Concentration,
Estimated by Modeling, with the Highest Second-
Highest 1-Hour N02 Concentration Observed in the
Same City (1974 through 1976) 15
7 Histogram of Highest Second-Highest 1-Hour N02
Concentration, by AQCR, Estimated by Modeling and
Statistical Conversion of Averaging Time 16
8 Histogram of Highest Second-Highest 1-Hour N02
Concentration, by AQCR, Obtained Either by Observation
or by Estimation 25
9 Relative Contribution of Source Categories to Total
NOX Emissions, by AQCR Based on Latest EPA NEDS File 29
10 Emission Trends for Nitrogen Oxides in the San
Francisco Bay Area 38
11 Cumulative Distribution of Fractional Change in NOX
Emissions Between 1975 and 1982 39
12 Percentage of AQCRs Expected to Exceed a Specified
N02 Standard, Based on Various Area Source Estimation
Methods 42
13 Percentage of Point Source Ground Level Maxima
Expected to Exceed a Specified N02 Standard (based
on Gaussian modeling with assumed 10070 conversion
from NO to N02) 43
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14 Estimated Percentage of Sites for Which Specified
Standards for 1-Hour Concentration Would be More
Stringent Than the Existing Federal Annual Average
Standard of 100 /ig/m3 44
15 Isopleths of Peak Ozone Concentration Expected
Under Stagnant Meteorological Conditions for Various
Initial Concentration Ratios of Nonmethane Hydro-
carbons to Oxides of Nitrogen 48
16 Illustration of a Wind Trajectory Through an
Urban Area 50
17 Ozone Concentration Along an Air Trajectory, as a
Function of Time, for Three Emissions Scenarios 52
A-l Graphical Calculation of Normalized Maximum Ground-
Level Concentration from a Point Source as a Function
of Plume Height (H) and Downwind Distance A-5
A-2 Graphical Calculation of Annual Average Concentration
as a Spatial Average A-8
vi
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TABLES
1 Distribution of Modeled Point Source Ground-Level
Maximum Concentration Estimates by Concentration
Interval ........ 18
2 Relative Contribution to Total Emission for a
Typical AQCR 34
B-l Base Year Emission Rates (Tons per Year) and Percent of
Total Emissions of NO by Source Category and AQCR .... B-4
X
B-2 Population Growth by Air Quality Control Region B-ll
vii
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PREFACE
This technical report presents the results of research conducted
as Work Assignment 2 under EPA Task Ordering Agreement, Contract Number
68-02-2835. The purposes of the research were to provide an assessment
of 1-hour averaged nitrogen dioxide (N0~) concentrations across the
nation, and to describe prospects for control of nitrogen oxide (NO )
X
emissions and the possible impact of such control on efforts to achieve
the short-term oxidant standard. The information in this report is
intended as input to analyses related to the short-term nitrogen dioxide
standard presently under consideration by EPA.
Since the study involved many simplifying assumptions, the analysis
presented should be viewed as a first approximation of the nationwide
NO- problem. More intensive local validation of study results is
recommended as input to firm and final decisions, especially those with
significant social or economic impact.
ix
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ACKNOWLEDGMENT
We wish to extend our gratitude and appreciation to Mr. Hisao
Shigeishi of SRI International. Without the benefit of his programming
skill and his generous allottment of time and energy to the project, our
efforts would have fallen far short of their intended goal. Appreciation
is due also to the many SRI people involved in various stages of manual
data analysis and textual review. Last, but by no means least, we thank
the EPA for continuing assistance in assuring the availability of neces-
sary data and information.
xi
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I SUMMARY AND CONCLUSIONS
This report describes our assessment of short-term ambient N0« prob-
lems throughout the United States. The current problem was assessed on
the basis of monitoring observations, statistical estimates, and simpli-
fied modeling estimates. Future trends were assessed for both the near
term and long term. The possibilities for control of NO emissions were
X
explored, and the interaction between the NO- and oxidant control pro-
grams was investigated. Based on the analysis as described in this
report, the following conclusions are drawn:
• Short-term exceeding of concentration levels that are within
the range being considered for a proposed standard (200 to
1000 |j,g/irr) is frequent and widespread throughout the United
States.
• Short-term concentrations observed at most existing air
monitoring sites are probably dominated by area sources,
particularly by motor vehicle activity on urban roads.
• Point source emissions such as those from industrial plants
can cause locally high short-term concentrations of NO?
in unmonitored as well as in monitored locations. Such
concentrations are more likely in unmonitored locations
since most monitoring sites are located to avoid the dis-
proportionate impact of strong point sources.
• The trend in NOX emissions indicates the possibility of a
slight reduction in the near term (1983), but a probable
increase over the longer term. Near-term reductions, if
realized, will generally not be substantial enough to
achieve and maintain standards within the range being
considered.
• Because of the different locations and meteorological
conditions associated with their maximum impacts, point
sources (e.g., industrial plants) and area sources (e.g.,
automobiles) should be subject to separate control programs
designed to mitigate their specific effects.
• Programs for NO emission reduction may have adverse
effects on ambient ozone concentrations.
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II INTRODUCTION
A variety of nitrogen oxides and nitrogen acids are expected to be
present in the atmosphere under normal conditions because of naturally
occurring processes within the atmosphere. The concentrations of these
natural nitrogen compounds are extremely small — generally less than one
part per billion by volume. In a typical polluted atmosphere, the waste
products of human activity greatly increase the concentrations of most
of the nitrogen compounds. Two compounds, nitric oxide (NO) and nitrogen
dioxide (NO-), reach concentrations approaching one part per million in
some urban areas and have caused concern because of problems related to
human health.
An ambient air quality standard for N09 of 100 micrograms per cubic
3
meter (|JLg/m ) as an annual average has been in existence since 1971, and
pursuant to the Clean Air Act Amendment of 1977 a short-term standard
for an averaging time of 3-hours or less is now being considered by EPA.
Both NO and NO- play important roles in the photochemical process leading
to the formation of oxidants (primarily ozone) for which an air quality
standard has also been set.
The principal source of elevated NO and NO- concentrations in urban
areas is the ubiquitous cumbustion process, which fosters the reaction
of fuel nitrogen with the nitrogen and oxygen in the air. The high
temperatures of typical combustion processes favor the formation of
nitric oxide initially, which oxidizes rapidly to NO- upon mixing with
the air through the reversible reaction:
2 NO + 02 ^ 2 N02 (1)
until an equilibrium is reached. When ozone is present, NO- formation
may be enhanced by the reaction
NO
(2)
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In the presence of strong sunlight and reactive hydrocarbon compounds,
also present in the atmosphere, photochemical reactions result in the
formation of oxidants.
The processes described above in conjunction with varying degrees
of dispersion occasioned by meteorological conditions give rise to a
geographic, seasonal, and diurnal variability of NO and N0« concentra-
tions in the ambient air. These characteristics have been described
extensively by Trijonis (1977) and also by Ludwig (1977).
Typically, NO concentrations build up during the early morning
traffic peak as the result of increased emissions from automobiles com-
bined with minimally dispersive atmospheric conditions. Concentrations
of N00 reach a peak shortly after the traffic maximum, because of the
^ -2T/,j ,-,? ce.-TL,t^ / •& J><: t«-f tf*' 2 •?<£
process described in equation (1), accompanied by a rapid decline in
concentrations of NO. During midday, NO,, concentrations decline because
of a decrease in emission rate, an increase in meteorological dispersion,
and (in some cases) the photolysis of NO- in the production of ozone.
In the evening, concentrations of NO and N0? again increase with in-
creased emissions from evening traffic accompanied by a decrease in
meteorological dispersion. Evening concentrations typically remain
elevated for a longer period than in the morning because of the trend
of decreasing meteorological dispersion characteristic of the evening
hours. Coastal locations are prone to later evening peaks than are
more inland locations possibly caused by the prolongation of dispersion
in afternoon thermal (sea breeze/lake breeze) circulations. Evening N02
peaks are apparently enhanced by the presence of elevated concentrations
of ozone (eq. 2) in the late afternoon.
Seasonal variability is typified by a fall or winter peak in levels
of NO and N07 most probably caused by decreased dispersion during those
seasons of the year and, in the case of N02, decreased photolysis. The
winter peak is most pronounced in locations with minimal photochemical
activity (ozone production) in the summer months. In areas of signifi-
cant photochemical activity, summer peaks or diminished seasonal
variability are likely.
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Ill THE SCOPE OF CURRENT PROBLEMS
A. General Considerations
As input to the process of choosing a suitable short-terra standard
for N02, we sought to determine the concentrations of NO- likely to
occur on a short-term averaged basis in the various AQCRs. This was
done using a combination of air quality data and estimation. We chose,
also, to define the NO., problem in terms of the highest second-highest
NO- concentration at the 1-hour averaging time; that is, in terms of the
maximum of all second-highest values observed or estimated within a spe-
cific AQCR. This definition is consistent with past EPA practice in
allowing one exceedance of the standard per year. Wherever possible,
suspicious values obtained from magnetic tape data files were verified
with the agency responsible for producing the data. Separate assess-
ments were performed for area source and point source problems because
of their general lack of coincidence either in space or in time. Assess-
ment of seasonal, diurnal, and geographic variability of concentration
was largely neglected because of time limitations, although their signi-
ficance is discussed qualitatively.
B. Continuous 1-Hour Monitoring
1. Instrumentation
Continuous sampling for N02, the basis for 1-hour observations,
is done almost exclusively throughout the United States by either the
colorimetric or cheiniluminescent techniques. The latter technique has
recently been favored over the former by the EPA, although data from both
methods are currently maintained in the SAROAD data bank. A check with
the San Francisco Bay Area Air Pollution Control District (BAAPCD) (Siu
1977), where both types of instrumentation are in use, indicated that
comparable results are obtained for continuous short-term measurements
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of NCL. As a further check on comparability, we searched the published
data (EPA 1977a) for air monitoring sites at which simultaneous sampling
was done by both methods. Figure 1 shows a scattergram of 50th and 90th
percentile values for NO- from the simultaneous data sets available in
1975. The scatter is caused, in many cases, by the differing sampling
times and lengths of record for the two instruments. At the few stations
with records that show more than 7000 observations for each monitoring
technique, scatter is much reduced as indicated by the circled data points
in Figure 1. Because of the small data sample, no rigorous statistical
analysis was attempted. On the basis of this limited investigation of
instrument comparability in the short-term measurement of N0? concentra-
tion, we decided to use all data contained in the SAROAD file without
adjustment regardless of measurement method. Length of record was also
ignored since the second-highest observed value in any record is of
interest regardless of the length of record.
2. Analysis
As an indication of possible short-term NO™ concentration
within an individual AQCR containing continuous monitoring sites, the
second-highest 1-hour N0? value for each station in each of the 3 years
1974 through 1976 was extracted from a magnetic tape of the SAROAD file
supplied by the EPA. The maximum of these second-highest values was then
selected to indicate exceedance of candidate standards within each AQCR.
This process was repeated for each AQCR containing one or more station
years of continuous NO™ monitoring during the 3-year period.
The results of the 1-hour monitoring analysis are presented in
histogram form in Figure 2. The ordinate of the graph indicates the
highest second-highest concentration in micrograms per cubic meter. The
abscissa indicates the cumulative number of AQCRs with highest second-
highest concentrations exceeding specific levels on the ordinate. The
AQCRs are plotted in descending order of concentration, and the AQCR
identification numbers are plotted at the top of the histogram bars.
(AQCRs can be identified in Figure 9.) A total of 84 AQCRs is included
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140
20
CHEMILUMINESCENCE — jug/m'
300
CHEMILUMINESCENCE— JUg/m3
400
@ CIRCLED DATA ARE FROM SITES WITH GREATER THAN 7000 HOURS OF OBSERVATION
500
FIGURE 1 COMPARISON OF N02 MEASUREMENT STATISTICS FOR THE 1-HOUR AVERAGING TIME (obtained by
color!metric and chemiluminescent instrumentation located at the same site)
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00
2500 r-
_E
~oi
2000
1500
H 1000
•z.
UJ
O
•2.
8 500
10
15 20 25 30 35
CUMULATIVE NUMBER OF AQCRs
40
2500 r
2000
2 -\500
O
I-
ir
21000
LU
CJ
500
I
I
I
I.I.
I I
-^— -.Poal
. r^^-
•eiss
1 ^T . I . I , 1 . I
50 55 60 65 70 75 80 85
CUMULATIVE NUMBER OF AQCRs
90
95
100
Last minute information indicates that the concentration in AQCR 30 should be adjusted downward to 600 jUg/m .
FIGURE 2 HISTOGRAM OF HIGHEST SECOND-HIGHEST 1-HOUR NO2 CONCENTRATIONS, BY AQCR, OBTAINED BY
CONTINUOUS MONITORING (1974 through 1976)
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in the histogram of Figure 2. In the published air quality data for
1975 (EPA, 1977a), the value for AQCR 47 is flagged as an extraordinarily
high maximum value. Its validity, therefore, is in doubt.
C. Estimates from 24-Hour Manual Sampling
1. Instrumentation
Manual sampling for a 24-hour average is accomplished by
bubbling the gas stream through an impinger containing an absorbing
solution, which is then subjected to laboratory analysis after the 24-
hour sample is collected. Data listed in the SAROAD data bank were
obtained by two methods: NASN Sodium Arsenite-Orifice and NASN Sodium
Arsenite-Frit. We compared data from these two methods in the same way
as for the 1-hour instrumentation techniques; the results are presented
in Figure 3. Again, the scatter tends to be large, due in part to data
points based on few observations (< 20). We chose to use all data with-
out adjustment for monitoring technique. A rigorous statistical analysis
of the type required to establish the degree of agreement between the
two methods could not be performed within the time limit of this study.
2. Analysis
Since we are interested in the 1-hour averaging time rather
than the 24-hour averaging time, the 24-hour observations were used to
estimate the 1-hour values. This was done by taking ratios of second
highest 1-hour-to-second highest 24-hour average observations obtained
in each of the 3 years (1974 to 1976) and in each city where both 1-hour
and 24-hour measurements were available concurrently. A cumulative
frequency distribution of these ratios was then obtained and a 50th
percentile ratio equal to 3.0 was determined. The observed 24-hour
values were then multiplied by the 50th percentile ratio to produce the
histogram presented as Figure 4.
Other methods are also available for such analysis. Morris
(1977), for example, estimated a ratio of 2.0 between 1-hour and 24-
hour maximum values on the basis of a best fit to 1974 and 1975 data.
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180
160
MM
50th PERCENTILE
M M U_
I I I I I
I I I I I
0 20 40 60 80 100 120 140 160 180
300
— 250
200
— 150
100
— 50
50 100 150 200 250
FRIT — jUg/m3
300
FIGURE 3 COMPARISON OF NO2 MEASUREMENT STATISTICS FOR THE 24-HOUR AVERAGING TIME OBTAINED BY
TWO MANUAL SAMPLING TECHNIQUES
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Using Larsen's technique, he obtained a ratio of 2.05. We determined a
l-hour-to-24-hour maximum ratio from our 50th percentile analysis approach
which was very similar to these values. Thus, we feel that Figure 4
represents a reasonable best estimate of the 1-hour NO™ problem based on
24-hour data. The data did exhibit considerable scatter, however, with
ratios of 2.0 and 6.0 for the 10th and 90th percentiles, respectively.
A total of 179 AQCRs is shown in Figure 4. The estimated
value for AQCR 55 is based on a highest second-highest 24-hour measure-
3
ment of 996 |j,g/m monitored by the EPA in Hamilton County, Tennesee in
1974. This value was verified as the correct value on record. The
relatively high values for AQCRs 7 and 67 (Athens, Alabama and Jolliet,
Illinois, respectively) were validated also. The 1-hour second-highest
maxima obtained from 24-hour measurements in Alaska, Hawaii, and Puerto
Rico are not included in Figure 4 since they were unavailable at the
time the histogram program was run. They were subsequently determined to
be 339 M-g/m3 (AQCR 9, Alaska), 396 ^g/m3 (AQCR 60, Hawaii), and 228 |j,g/m3
(AQCR 244, Puerto Rico).
D. Estimates from Area Source Air Quality Modeling
1. Modeling Procedure
Where neither 1-hour nor 24-hour measurements are available,
estimates were made of the possible second-highest 1-hour concentrations
by mathematically relating emission rates and meteorological conditions
to ambient concentrations. This modeling process is reasonably simple
when applied to area source emissions of nonreactive pollutants. We
used such a mathematical model based on the work of Hanna (1971) and
Holzworth (1972), outlined in Appendix A, to estimate annual average
concentrations of total oxides of nitrogen. The modeling was done for
the largest city in each air quality control region, where the population
of such a city equaled or exceeded 50,000 people at the time of the last
(1970) census. It was assumed that the largest cities would have the
highest NO- concentrations related to area sources. AQCRs with the popu-
lation of their largest city less than 50,000 were assumed to have area
11
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2500
15
20
25
30 35 40 45
CUMULATIVE NUMBER OF AQCRs
50
55
60
65
70
75
2500
- 2000
x
i
• 1500
D
(
C
; 1000
]
j
7
5
j
500
0
.,.,.,.,.
-
-
^lll!_illlfe 2 c !i53?SiS*a??3
1 1 I.I. \ ,
1 1 1 1 1 1 1 1 1 '
_ —
.
•
•B**»lfi*aSB8S8i|Mgggaa8gBg
, 1 , 1 , 1 . 1 .
1 1 1 1 1 1 1 1 i
.
.
.
—
SlStgSsjgesSeggsSssfcigBses
— i i i . i 1 1 . —
80 85 90 95 100 105 110 115 120
CUMULATIVE NUMBER OF AQCRs
125
130
135
140
145
150
FIGURE 4 HISTOGRAM OF HIGHEST SECOND-HIGHEST NO2 CONCENTRATION ESTIMATED STATISTICALLY
FROM 24-HOUR MEASUREMENTS (1974 through 1976)
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ZOUU
CO
Z 1500
o
OCENTRATI
o
o
o
0 500
0
15
' — ~I ' 1 ' 1 ' 1 '
-
-
-
I±¥*$l¥lll¥*±in9*iiti
-
-
-
-
1 8 » •
0 155 160 165 170 175 180 185 190 195 20
CUMULATIVE NUMBER OF AQCRs
FIGURE 4 (Concluded)
source-related second-highest 1-hour N09 concentrations less than
3
200 |j,g/m on the basis of rough estimates using the model. This assump-
tion made the modeling task more tractable since many of the AQCRs fell
in this category.
The modeling process is easily implemented by using the nomo-
graph in Figure A-2 of Appendix A. Emission densities for the cities in
question were obtained by calculating a per-capita emission rate for
oxides of nitrogen (NO ) from area sources (based on the National
X
Emissions Data System (NEDS) emissions summaries for the AQCR containing
the city) and multiplying by the average population densities of the
cities taken from census information. Annual average wind speeds for the
cities were obtained from Holzworth (1972). City size was taken as the
square root of the quotient of city population and population density.
An estimate of annual average NO was then obtained from the nomograph.
X
To test the reliability of the modeling process, we compared
our estimates with available measurements of annual average NO in the
X
same cities as our modeling. The highest measurements in 1974 through
1976 were used. The results are presented in Figure 5.
13
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600
600
ESTIMATED ANNUAL AVERAGE — M9/m°
FIGURE 5
COMPARISON OF ANNUAL AVERAGE NOX CONCENTRATION,
ESTIMATED GRAPHICALLY, WITH THE HIGHEST ANNUAL
AVERAGE OBSERVED IN THE SAME CITY (1974 through 1976)
2. Analysis
Since we are interested in 1-hour rather than annual average
concentrations, it was necessary to convert from one averaging time to
the other. We did this statistically by comparing our modeled annual
average NO concentrations to maximum second-highest 1-hour N02 measure-
ments in the same city, but not necessarily at the same site. The com-
parison is shown in Figure 6. The 50th percentile of the ratio values
was extracted from the scattergram after eliminating points with ratios
of NO to NO greater than 15:1, which were considered anomalous in an
fL X
area source context and which had the appearance of outlyers on the
scattergram.
14
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CO
"a
2
O
<
OC
2
LU
O
z
O
O
CM
O
oc
D
O
LLI
X
O
O
LU
CO
O
LU
>
oc
111
C/J
CO
O
2000
1800
1600
1400
1200
1000
800
600
400
200
50% (6:1)
50
100
150
200
250
300
ESTIMATED ANNUAL AVERAGE NOx CONCENTRATION—jUg/m
FIGURE 6
COMPARISON OF ANNUAL AVERAGE NOX CONCENTRATION,
ESTIMATED BY MODELING, WITH THE HIGHEST SECOND-
HIGHEST 1-HOUR NO2 CONCENTRATION OBSERVED IN THE
SAME CITY (1974 through 1976)
After performing the indicated analysis, we converted our
annual average NO estimates to pragmatic best estimates of second-
X
highest 1-hour NO- concentration using the 50th percentile ratio as a
multiplier. The analysis results are displayed graphically in histogram
form (Figure 7).
E. Estimates from Point Source Air Quality Modeling
1. Modeling Procedure
The procedure for modeling short-term N0_ concentrations caused
by point sources differs considerably from that used to model area source
concentrations. For point source modeling, we chose the standard
gaussian plume model described in detail by Turner (1969) with plume
rise estimates according to Briggs (1969), as outlined in Appendix A.
15
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2500
2500
2000
10
15
20
25
30 35 40 45
CUMULATIVE NUMBER OF AQCRs
50
55
60
65
70
5
1500
o
CC
Hi
O
1000
500
1
1
oooooooooooo
80
85
90
95
100
105 110 115 120
CUMULATIVE NUMBER OF AQCRs
125
130
135
140
145
150
FIGURE 7 HISTOGRAM OF HIGHEST SECOND-HIGHEST 1-HOUR N02 CONCENTRATION, BY AQCR, ESTIMATED BY
MODELING AND STATISTICAL CONVERSION OF AVERAGING TIME
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On the basis of the procedures described in these publications, we esti-
mated the maximum ground-level concentration expected downwind of indi-
vidual point source facilities in each AQCR under adverse meteorological
conditions. Point sources modeled were those for which data was available
in the National Emissions Data System (NEDS) maintained by the EPA.
Meteorological conditions chosen as adverse consist of Turner "B" sta-
bility and a 2 m/s wind speed. To simplify the modeling process, we
assumed that ground level maxima from individual stacks within a given
facility are additive and that all NO is converted to N0? before reaching
the point of ground level maximum. The assumption of additive maxima will
produce an overestimate in most cases, but since highest emissions are
frequently from a few stacks of similar characteristics and stacks are
fairly close together, we feel the assumption is reasonable as a safe
estimate of a worst case situation. The assumption of 100% conversion
to NO- will also produce an overestimate. Research done on NO to N00
^ tL
conversion in power plant plumes (Davis, 1974; Hegg et al., 1976 and
Caenepeel et al., 1976) indicates that the actual ground-level N0_ con-
centrations may be as much as 50% lower than those obtained on the basis
of a 100% conversion assumption.
2. Analysis
To portray the point source problem in a reasonable way in
view of the large and undetermined uncertainty in the modeling procedure,
we chose to indicate the individual point source impact in terms of a
number of ranges of ground-level maximum concentration rather than as
specific values. Because of the somewhat discrete nature of point source
problems and the location of some point source problems in remote areas,
we thought also that the number of impacted sites within an AQCR would
be a more useful statistic than a single maximum value. To accomplish
the above objectives, we chose the format of Table 1. This table con-
tains a list of AQCRs; to their right are 10 classes of concentration in
micrograms per cubic meter. Next to each AQCR we have indicated the
number of modeled sites by concentration class. An indication of impact
17
-------
Table 1
FREQUENCY OF MODELED POINT SOURCE, GROUND-LEVEL MAXIMUM
CONCENTRATION ESTIMATES BY CONCENTRATION INTERVALS
...NOX CONCENTRATION CLASS — MICROSRAMS/CUIJIC METER...
oo
AOCR
I
2
3
4
5
6
7
8
9
10
11
12
13
14
IS
16
17
IB
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
*1
42
43
44
45
46
47
48
49
50
100
2
5
2
12
177
1
56
2
8
3
4
7
13
11
21
21
5
61
27
14
4
46
0
31
3
3
1
2
3
7
30
3
7
5
5
20
9
14
1
2
1
48
677
0
921
15
31
74
162
95
too
0
n
0
l
In
0
2
(1
1
1
0
0
1
3
2
1
n
0
?
1
n
8
n
9
2
1
0
0
^
\
i
0
0
0
0
3
1
1
0
0
0
3
22
0
22
0
2
?
S
4
300 *00
n
0
n
0
4
6
i
i
i
0
6
i
6
p
6
6
6
i
2
0
6
2
(i
4
0
1
6
0
i
i
0
0
6
0
0
6
0
0
6
6
6
6
16
0
6
6
6
6
4
4
0
0
c
0
2
C
0
0
0
0
0
0
0
0
0
0
1000
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
5
0
0
0
0
0
0
0
1
1
1
0
0
0
1
0
0
4
0
0
0
0
0
0
0
0
0
0
1
0
0
1
1
0
0
0
0
0
3
a
5
0
0
0
4
0
...NOX CONCENTRATION CLASS — MlCROORAMS/CuBlC METER..
AQCR
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
6B
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
100
34
94
22
12
31
17
7
18
13
9
3
24
7
1
15
2
99
7
20
43
11
50
9
0
4
21
56
138
65
126
11
20
16
55
15
9
0
20
20
7
10
30
S
39
3
Z
3
6
9
21
200
0
10
2
1
1
1
0
3
1
3
0
0
1
1
3
1
9
2
2
11
2
1
0
?.
0
5
3
7
V
3
1
2
3
2
0
1
0
2
2
0
0
0
0
3
0
0
0
1
1
0
300
2
1
0
0
0
2
0
1
0
3
0
0
0
0
2
0
6
1
3
3
0
1
0
0
2
0
0
1
0
0
0
1
0
1
1
0
0
1
0
0
0
1
0
1
0
0
0
0
0
1
400
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
3
0
0
2
0
1
0
0
0
0
0
0
2
1
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
500
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
2
1
0
1
0
0
0
0
0
0
3
0
0
0
0
0
1
0
c
0
0
0
0
0
0
1
0
0
0
1
0
0
600
0
u
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
2
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
700
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
800
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
900 1000 >1000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
2
2
2
0
0
0
0
0
0
0
1
0
0
0
1
0
3
0
3
0
1
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
3
2
0
0
0
0
2
0
0
0
1
0
0
-------
Table 1 (Continued)
...NOX_CONCENTRATION CLASS -- MICROGRAMS/CUblC METER... ...NOX CONCENTRATION CLASS -- MICROGRAMS/CUB1C METER...
AOCR
101
102
103
10*
105
106
107
108
109
110
111
112
113
11*
115
116
117
118
119
120
121
122
123
124
125
126
127
126
129
130
131
132
133
134
135
136
137
138
139
100
30
54
35
40
43
181
32
10
40
16
0
0
0
2
0
0
16
91
722
70
150
38
54
20
17
24
3
24
24
2
81
14
5
19
37
112
24
9
18
200
1
3
3
1
0
34
1
0
0
0
0
0
0
1
0
0
0
?
ft
5
2
2
6
4
3
2
0
1
2
1
1
0
0
1
1
5
0
P
1
300
6
P
1
1
6
12
1
6
6
0
6
6
6
6
6
6
6
0
i
6
0
2
3
1
C
0
6
0
n
6
6
0
P
0
0
6
1
1
1
400
0
0
0
0
0
9
0
0
0
0
0
C
0
0
0
0
0
0
0
u
0
0
0
0
2
0
0
0
0
.0
0
0
0
0
0
1
0
0
i
500
0
0
0
0
a
4
0
0
0
0
0
n
0
0
0
0
0
5
0
0
0
0
1
0
0
1
P
0
0
0
0
0
0
0
0
2
C
0
0
600
0
0
0
0
1
2
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
0
0
0
0
(1
n
0
0
II
0
0
700
0
0
2
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
n
0
1
0
0
C
0
C
0
0
0
BOO
0
0
0
0
0
2
0
0
0
0
u
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
900 1000 >1000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
C
0
0
0
0
0
1
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-0
0
0
0
0
0
0
1
0
0
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
3
0
0
0
0
0
1
0
0
1
1
1
1
0
0
AOCR
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
1BO
181
182
183
184
185
186
187
188
189
100
36
6
5
2
10
1
3
127
40
65
141
146
41
49
51
66
54
30
42
37
21
9
25
51
15
19
20
41
13
5
27
1
4
17
5
17
1
4
7
200
1
2
0
0
3
0
0
3
3
9
14
7
4
4
2
2
3
4
2
7
2
3
0
7
1
1
2
1
0
0
4
1
1
2
0
2
1
5
1
300
1
0
0
0
2
0
0
0
0
2
5
2
1
2
1
1
3
2
0
3
0
0
3
2
0
1
0
0
0
0
1
0
1
1
2
0
0
0
0
400
1
1
0
0
0
0
0
0
0
1
3
1
2
0
0
0
0
0
1
1
1
0
0
0
C
0
0
0
0
0
1
0
ll
1
0
1
1
0
0
500
0
0
0
0
0
0
0
1
1
1
1
0
0
1
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
]
0
0
0
1
0
0
0
0
600
1
0
0
0
0
0
0
1
0
1
1
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
700
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
1
0
0
0
0
3
0
0
0
0
0
0
0
0
n
0
1
0
0
0
0
0
800
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
r
0
900 1000 >1000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
2
0
0
0
14
0
0
2
0
3
6
1
0
1
0
0
0
0
0
0
0
1
0
1
0
0
0
0
1
0
1
0
0
2
0
0
1
0
0
140 5 0 o 1 0 0 0 0 0 0 0 1*0 11
141 2 0 0 1 0 00000 0
142 41 no (I 00000 0
143 2 n o 0 (I 0 0 0 0 (i U
144 61JOOOOOCO 0
145 87 ) n 1 n 1 C 0 0 0 0
146 7n
-------
Table 1 (Concluded)
..NOX CONCENTRATION CLASS — MICROGRAMS/CUBIC METER*
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
226
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
100
19
67
9
9
5
2
?08
85
62
13
20
21
4
15
39
50
19
15
9
15
13
38
72
11
56
27
14
66
115
8
11
1
8
11
8
4
22
15
14
8
2
2
10
8
0
. °
* 4
0
0
0
200
4
1
0
2
0
0
10
3
3
3
3
1
0
0
2
9
0
1
0
0
0
2
4
1
5
3
1
1
3
2
0
0
0
2
0
0
2
2
3
0
2
0
5
3
0
0
0
0
0
0
300
1
5
0
6
0
6
5
4
4
6
i
0
0
2
2
3
6
i
6
i
6
i
3
1
6
i
1
0
?
6
0
0
6
o
0
6
6
6
i
6
6
6
6
i
6
6
Q
0
6
6
400
0
1
0
1
0
0
1
4
1
1
0
0
0
0
0
2
0
0
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
500
0
0
0
0
0
0
2
0
0
0
0
0
0
2
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
600
0
0
0
0
0
0
2
0
1
0
1
0
0
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
700
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0,
0
800
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
900
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1000
0
0
0
0
0
0
1
1
0
0
0
6
0
0
6
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
0
6
0
0
0
0
0
0
c
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
1
0
0
2
1
0
1
1
0
0
0
0
0
0
0
0
1
1
0
1
0
0
1
0
0
0
0
0
0
TOTAL 8487 t>33 182 88 54 29 29 14
20
15 134
-------
associated with various degrees of conversion from NO to N02 may be
obtained by proportionate reduction of the class interval values.
Table 1 reveals a substantial number of sites at which high
ground level concentrations are indicated. In reviewing the impact data
that led to these estimates, unreasonable values for source character-
istics such as stack height and gas temperature were occasionally
detected. A validation check of individual data on the NEDS point
source subfile would be a monumental task and could not be performed
with any degree of usefulness within the scope and time frame of our
study. Because of the probable errors inherent in the generally crude
estimates of point source emissions as well as those apparent from the
data analysis, we urge caution in the interpretation of the Table 1
results. The same caution applies to use of the NEDS data in general.
In areas where serious problems are indicated by the analysis, detailed
local studies based on validated data bases are strongly recommended.
F. Analysis Summary
In Sections II A through E, above, we discussed the statistical
analyses of 1- and 24-hour monitoring data and the modeling analyses of
area and point source emissions data. In this summary section, we will
discuss the significance and usefulness of each of these four segments
and attempt to fit them into a complete and meaningful indication of
current air-quality problems.
1. 1-Hour Observations
Continuous monitoring that yielded 1-hour observations of N00
concentration was available from 237 communities in 84 of the 247 AQCRs.
These observations represent the most direct and least uncertain esti-
mates of short-term N0« problem in the immediate areas of the individual
air monitoring sites. Since, however, there are many unmonltored AQCRs,
many unmonitored cities within the monitored AQCRs, and many unmonitored
sites within monitored cities, the available 1-hour data represents
only a small sampling of the possible N02 problem areas.
21
-------
Since continuous air monitoring stations are frequently placed
in center city locations and away from industrial areas, the continuous
data is most strongly influenced by area source emissions such as those
from automobiles and space heating. Although some few sites exhibit
characteristics (such as high peak-to-mean ratios) indicative of point
source influence, the 1-hour NO- data should not be expected to be well
related to point source emission levels within the region.
2. 24-Hour Observations
Manual sampling for 24-hour averaged NO,, was available from
871 communities in 182 AQCRs. Since the 1-hour and 24-hour observations
overlapped in only 53 communities, the 24-hour data added 818 to the
sample of monitored communities for a total of 1055. The total of
monitored AQCRs was increased to 193. Since the 24-hour data must be
converted statistically to 1-hour estimates, the 24-hour observations
are only an indirect indication of short-term N0_ problems. The uncer-
*
tainty in individual estimates is considerable—on the order of ±50?0
of the 50th percentile value.
As in the case of the 1-hour data, the 24-hour observations
indicate more the influence of area sources than of point sources. In
fact, the point source influence should be even less in the case of the
24-hour data because point source plumes are unlikely to influence a
given receptor more than a small fraction of the total 24-hour sampling
time.
3. Area Source Modeling
The estimates of short term NO- maxima made from modeling area
source emissions are the least direct because no monitoring is involved.
The uncertainty in the modeling estimates, however, as evidenced by
Figures 5 and 6, is comparable to that in the 1-hour estimates from
*We define uncertainty as one-half the difference between the 10th and
90th percentile values.
22
-------
24-hour observations. The implications of this uncertainty are the same
as those in the 24-hour estimates, and it can be seen from the histograms
that the modeling estimates of the number of AQCRs exceeding the stan-
dards are comparable to estimates made by the other methods.
The modeling estimates are obviously representative of area
source influence since they are based exclusively on area source emis-
sions. The purpose of this analysis was twofold: to provide information
for those AQCRs where no monitoring is available, and to flag those AQCRs
where problems might possibly be worse than indicated by available
monitoring.
4. Point Source Modeling
In the foregoing analyses, we have emphasized area source
rather than point source influence. This being the case, these analyses
have not provided a complete effort to determine the presence of short-
term NO- problems within an AQCR. The reason is that serious problems
may exist in the plumes of large point sources and go undetected at
sparsely located monitoring sites. In the interest of a more complete
assessment, this section provides a modeling estimate of possible,
extreme short-term concentrations of N0_ in the vicinity of point sources
listed in the EPA/NEDS data bank. These modeling estimates are somewhat
crude because of many simplifying assumptions. We believe, however,
that they, as with the area source modeling estimates, provide a reason-
able indication of possibly undetected problems at locations within
certain AQCRs and provide the most specific indication of point source
influence.
5. Combined Estimates
Since each of the four estimation segments listed above repre-
sents only a part of the total picture, the information must be combined
in some way to better represent this total picture. Because of the gen-
eral comparability of the three area source analyses, we believed that
it was reasonable to pool the information available in the form of a
23
-------
single histogram (Figure 8). The figure indicates all AQCRs in which a
second-highest 1-hour NCL concentration in excess of given values has
either been observed or is estimated to possibly exist. In constructing
the combined histogram, the highest value given for an AQCR by any of
the three methods was selected as the value representing the AQCR problem.
The uncertainty, as outlined above, for 24-hour and for area source
modeling estimates is, of course, carried over to this combined analysis.
Because, however, of the considerable variability in pollutant concentra-
tions that exists, even within individual communities, we believe that
the indicated levels represent reasonable possibilities for the AQCRs in
question and a good indication of the number or percentage of AQCRs
involved at a specific level of concern.
Because of the very different implications for control (dis-
cussed later in the report) we have chosen not to pool the point-source
analysis results (Table 1) with those for the three area source segments.
24
-------
2500
n 2000
E
01
z 1500
O
H
H 1000-
LU
O
o
0 500-
0
C
2500
„ 2000
t
2 1500
O
1-
CONCENTR/
§o
o
- — > 1 1 1 — '-^~- 1 "> 1 '
"S0 A/,/ /i*t-^ro ^*i.f^*fl'T
^n*"- t7- "St£»* **«*/' '
'-Al /i/ £*>•***- K *J~**t. -
S y /_7" H*.-*.*-*- • B£t~Li"~C" &
.. rn^lt^j"' """ """'_
~L-^__zl=^»ig a s §s a e
.
i . i . i . i i
i 1 1 1 1 1 r 1 '
_
_ —
_ —
__ —
. -
— , — ^ — ^^iyntjhsjsjg
i . i . i . i
1 j • i ' i ' i '
fcs§8«§sPs »S8iStsSSS8SSe5S
I . 1 . 1 . 1 .
) 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75
CUMULATIVE NUMBER OF AQCRs
1 1 1 ' 1 ' 1
-
flit'fl. •••*(•, I..S8«tll
i . i . i . i , ...
i i i i . i i i >
P «
.
' 1 ' 1 1 1 ' 1
— —
HlUliii!. 8 3 s B s e B s = » s ? s s i ~
i . i . i . i .
^5 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150
CUMULATIVE NUMBER OF AQCRs
* 3
Last minute information indicates that the concentration in AQCR 30 should be adjusted downward to 600 JLlg/m .
FIGURE 8 HISTOGRAM OF HIGHEST SECOND-HIGHEST 1-HOUR N02 CONCENTRATION, BY AQCR, OBTAINED EITHER
BY OBSERVATION OR BY ESTIMATION
-------
2500
E 2000
3)
• 1500
5
(
- 1000
LJ
J
?
3 500
0
1E
-
-
8»38fe888BSg"J89r=;B85g8g§j
i . i . i . i t_
' I ' I ' I i 1 '•
-
_ _
-
6 Z 5 • » S S jj 8 g g fe . „ g f
1 . 1 .1 T""'— I -v
>0 155 160 165 170 175 180 185 190 195 20
CUMULATIVE NUMBER OF AQCRs
FIGURE 8 (Concluded)
26
-------
IV THE NATURE OF CURRENT SOURCE CONTRIBUTIONS
A. General Considerations
Although some N02 may be ascribed to natural sources, the urban
area natural background levels are negligible compared with the levels
from the influence of anthropogenic emissions. The key, therefore, to
devising a workable control program geared to the attainment and mainte-
nance of a short-term air quality standard for N02 is a knowledge of the
sources of NO emissions.
X
In this section, we describe the sources in individual AQCRs to
facilitate devising control strategies. The data base for our analysis
consisted of the EPA/NEDS file of emissions summary reports by AQCR.
This set of summaries provides the latest available estimates of total
AQCR emissions in a number of source categories. Inventory data used
for the discussion in this section are provided in detail in Appendix B.
B. Source Structure Analysis
As the basis for our analysis, we chose seven categories, which are
well defined and which, from cursory analysis, appeared to contribute
most of the AQCR NO emissions:
X
• Aircraft (A)
• Light-duty highway vehicles (L)
• Heavy-duty highway vehicles (H)
• External combustion area sources (space heating) (S)
• External combustion point sources (P)
• Electric generation (power plants) (E)
• Industrial processing (I).
The remaining emission sources were then treated as Miscellaneous. In
addition to the seven individual categories, we defined the two general
categories of point sources and area sources. The area source general
27
-------
category may further be divided into distributed and nondistributed
area sources. These two subcategories of area sources refer, respec-
tively, to area sources such as highway vehicles and space heating,
which are spatially distributed throughout the community; and area
sources such as airports, which are confined to discrete locales.
In Figure 9, we have attempted to portray graphically the distribu-
tion of these key source categories within the individual AQCRs. Next
to each number and name in the list of AQCRs we have placed solid and
dashed lines representing area and point sources, respectively, and a
set of code letters representing selected source categories as indicated
in the list provided above. The length of the lines and the positions
of the code letters indicate the approximate percentage contributions
of the individual categories to total NO emissions within the AQCR.
X
Code letters were not plotted when the contribution was less than 5%.
Table B-l presents the actual data used in preparing Figure 9.
On the average, area sources provide 62.9% and point source 37.1%
of the total annual AQCR NO emissions. Distributed area sources taken
X
as highway vehicles and space heating combined provide 40.9% of the
total annual AQCR NO emissions in the summer and 51.5% in the winter
season based on the assumption that most of the space heating occurs
during a 6-month period. With respect to the individual source cate-
gories, percentage contributions averaged over all AQCRs, on an annual
basis, are summarized in Table 2. These percentages may be construed
to represent conditions in the typical AQCR, although considerable
variability is evident in Figure 9. Especially striking is the con-
trast between industrial AQCRs, such as metropolitan Birmingham, and
nonindustrial AQCRs such as Northwestern Connecticut.
28
-------
VO
AIR QUALITY CONTROL REGION
1. ALABAMA AND TOMBIGBEE RIVERS
2. COLUMBUS-PHENIX CITY
3. EAST ALABAMA
4. METROPOLITAN BIRMINGHAM
6. MOBILE-PENSACOLA-PANAMA CITY-
SOUTHERN MISSISSIPPI
6. SOUTHEAST ALABAMA
Q) TENN RVR VALLEY-CUMBER LAND MTS
8. COOK INLET
9. NORTHERN ALASKA
10. SOUTH CENTRAL ALASKA
11 SOUTHEASTERN ALASKA
12 ARIZONA-N M SOUTHERN BORDER
13 CLARK-MOHAVE
14 FOUR CORNERS
15 PHOENIX-TUCSON
16 CENTRAL ARKANSAS
17 METROPOLITAN FORT SMITH
18 METROPOLITAN MEMPHIS
19 MONROE-EL DORADO
20 NORTHEAST ARKANSAS
21 NORTHWEST ARKANSAS
23 GREAT BASIN VALLEY
(H^ METROPOLITAN LOS ANGELES
26. NORTH COAST
27. NORTH EAST PLATEAU
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
I I I I I I I I I
S H L
S H L
S H L
H L E
SAH L
PH L
E LS A
SLP E
P
E S P
H IE P L
L E
L E
SH E L
H SE L
SH L
HP L E
HSEI L P
SH EL
ISH E L
HP L
PH L
AIR QUALITY CONTROL REGION
29 SAN DIEGO
30 SAN FRANCISCO BAY AREA
31 SAN JOAQUIN VALLEY
32 SOUTH CENTRAL COAST
34 COMANCHE
35 GRAND MESA
36 METROPOLITAN DENVER
37 PAWNEE
38 SAN ISABEL
39. SAN LUIS
40 YAMPA
41 EASTERN CONNECTICUT
42 HARTFORD-NEW HAVEN-SPRINGFIELD
43. NEW JERSEY-NEW YORK-CONNECTICUT
44 NORTHWESTERN CONNECTICUT
45 METROPOLITAN PHILADELPHIA
46 SOUTHERN DELAWARE
^^ NATIONAL CAPITAL
48. CENTRAL FLORIDA
49. JACKSONVILLE-BRUNSWICK
50. SOUTHEAST FLORIDA
51. SOUTHWEST FLORIDA
52 WEST CENTRAL FLORIDA
53. AUGUST A-AI KEN
54. CENTRAL GEORGIA
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
1 1 1 1 1 1 1 1 1
S H L
SHE L
SE_HI L
SIH P L
PL E
PL E 1
1 PH L
PHE L
SH LE
IH P L
H L E
PSEH L
L E
PSH E L
H S E L
PH S LE
PSH L
ISPH LE
P LH E
SH E L
H L E
H LPE
H L E
PH L E
H L E
IHEP L
H L E
A = Aircraft
L = Light-duty highway vehicles
H = Heavy-duty highway vehicles
S = External combustion area sources (space heating)
P = External combustion point sources
E = Electric generation (power plants)
I = Industrial processing
FIGURE 9 RELATIVE CONTRIBUTION OF SOURCE
BASED ON LATEST EPA NEDS FILE
= All area sources
— — — = All point sources
CATEGORIES TO TOTAL NOX EMISSIONS, BY AQCR
-------
AIR QUALITY CONTROL REGION
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
I I I I I I I I I
AIR QUALITY CONTROL REGION
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
I I I I I I I I I
> CHATTANOOGA
56. METROPOLITAN ATLANTA
57. NORTHEAST GEORGIA
58. SAVANNAH-BEAUFORT
SOUTHEAST GEORGIA
60. HAWAII (ENTIRE STATE)
61. EASTERN IDAHO
62. EASTERN WASH INGTON-N. IDAHO
63. IDAHO
64. METROPOLITAN BOISE
65. BURLINGTON-KEOKUK
66. EAST CENTRAL ILLINOIS
T METROPOLITAN CHICAGO
. METROPOLITAN DUBUQUE
. METROPOLITAN QUAD CITIES
70. METROPOLITAN ST. LOUIS
71. NORTH CENTRAL ILLINOIS
72. PADUCAH-CAIRO
73. ROCKFORD-JANESVILLE-BELOIT
74. SOUTHEAST ILLINOIS
75. WEST CENTRAL ILLINOIS
76. EAST CENTRAL INDIANA
77. EVANSVILLE-OWENSBORO-HENDERSON
78. LOUISVILLE
79. METROPOLITAN CINCINNATI
80. METROPOLITAN INDIANAPOLIS
81. NORTHEAST INDIANA
HP
EL
S H
HIP L E_
L
PHE
AH
SH
SHP
PSH
SHP L E
H L
H L P
LE
L
SH
HE P
S H EL
82. S. BEND-ELKHART-BENTON HARBOR
83. SOUTH INDIANA
84. WABASH VALLEY
85. METROPOLTN OMAHA-COUNCIL BLUFFS
86. METROPOLITAN SIOUX CITY
87. METROPOLITAN SIOUX FALLS
88. NORTHEAST IOWA
89. NORTH CENTRAL IOWA
90. NORTHWEST IOWA
91. SOUTHEAST IOWA
92. SOUTH CENTRAL IOWA
93. SOUTHWEST IOWA
94. METROPOLITAN KANSAS CITY
95. NORTH EAST KANSAS
96. NORTH CENTRAL KANSAS
97. NORTHWEST KANSAS
98. SOUTHEAST KANSAS
99. SOUTH CENTRAL KANSAS
100. SOUTHWEST KANSAS
101. APPALACHIAN
102. BLUEGRASS
103. HUNTGTN-ASHLAND-PRTMTH-IRNTN
104. NORTH CENTRAL KENTUCKY
105. SOUTH CENTRAL KENTUCKY
106. SOUTHERN LOUISIANA-S.E. TEXAS
107. ANDROSCOGGIN VALLEY
108. AROOSTOOK
SH
LP
SPH ILE
SEH
SPEH
S H
SEH
S H
SEPH
PH E L
H L
SPIEH L
H PE L
H P E L
U E
SHE
SEH P
A = Aircraft
L = Light-duty highway vehicles
H = Heavy-duty highway vehicles
S = External combustion area sources {space heating)
P = External combustion point sources
E = Electric generation {power plants)
I = Industrial processing
= All area sources
= All point sources
FIGURE 9 (Continued)
-------
AIR QUALITY CONTROL REGION
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
AIR QUALITY CONTROL REGION
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
109. DOWN EAST
110. METROPOLITAN PORTLAND
111. NORTHWEST MAINE
112. CENTRAL MARYLAND
113. CUMBERLAND-KEYSER
114. EASTERN SHORE
tj^. METROPOLITAN BALTIMORE
116. SOUTHERN MARYLAND
117. BERKSHIRE
118. CENTRAL MASSACHUSETTS
119. METROPOLITAN BOSTON
METROPOLITAN PROVIDENCE
121. MERRIMACKVLY-S. NEW HAMPSHIRE
122. CENTRAL MICHIGAN
123. METROPOLITAN DETROIT-PORT HURON
124. METROPOLITAN TOLEDO
125. SOUTH CENTRAL MICHIGAN
126. UPPER MICHIGAN
127. CENTRAL MINNESOTA
128. SOUTHEAST MINNESOTA-LACROSSE
129. DULUTH-SUPERIOR
130. METROPOLITAN FARGO-MOORHEAD
131. MINNEAPOLIS-ST. PAUL
132. NORTHWEST MINNESOTA
133. SOUTHWEST MINNESOTA
134. MISSISSIPPI DELTA
135. NORTHEAST MISSISSIPPI
SEH
SPH E
HEP
PS
HEP
EL
H S
EL
EL
L P
HS
EL
SH P
PL
S H
S HE
H UP E
PSH
SH
SHP
EHS
SPHIE L
136. NORTHERN PIEDMONT
137. NORTHERN MISSOURI
138. SOUTHEAST MISSOURI
139. SOUTHWEST MISSOURI
140. BILLINGS
141. GREAT FALLS
142. HELENA
143. MILES CITY
144. MISSOULA
145. LINCOLN-BEATRICE-FAIRBURY
146. NEBRASKA
147. NEVADA
148. NORTHWEST NEVADA
149. NEW HAMPSHIRE
150. NEW JERSEY
151. NEPENN-UPPER DELAWARE VALLEY
152. ALBUQUERQUE-MID RIO GRANDE
153. EL PASO-LAS CRUCES-ALAMOGORDO
154. NORTHEASTERN PLAINS
155. PECOS-PERMIAN BASIN
156. SW MOUNTAINS-AUGUSTINE PLAINS
157. UPPER RIO GRANDE VALLEY
158. CENTRAL NEW YORK
159. CHAMPLAIN VALLEY
160. GENESSE-FINGER LAKES
161. HUDSON VALLEY
J62\ NIAGARA FRONTIER
P H LE
IHE LP
SH LIE
HI L
SHI EL
SHE
EHPSL
SPH L E
EP H
EL
PHS
PSH E L
SHI E L
SHE
H E P L
S PH
SP EL
SHP
S PL
SP El L
H SP EL
A = Aircraft
L = Light-duty highway vehicles
H = Heavy-duty highway vehicles
S = External combustion area sources (space heating)
P = External combustion point sources
E = Electric generation (power plants)
I = Industrial processing
= All area sources
= All point sources
FIGURE 9 (Continued)
-------
AIR QUALITY CONTROL REGION
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
AIR QUALITY CONTROL REGION
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
LO
to
163. SOUTHERN TIER EAST
164. SOUTHERN TIER WEST
165. EASTERN MOUNTAIN
166^ EASTERN PIEDMONT
167. METROPOLITAN CHARLOTTE
168. NORTHERN COASTAL PLAIN
169. SANDHILLS
170. SOUTHERN COASTAL PLAIN
171. WESTERN MOUNTAIN
172. NORTH DAKOTA
173. DAYTON
174. GREATER METROPOLITAN CLEVELAND
175. MANSFIELD-MARION
V76x METROPOLITAN COLUMBUS
177. NORTHWEST OHIO
178. NWPENNSYLVANIA-YOUNGSTOWN
179. PARKERSBURG-MARIETTA
180. SANDUSKY
181. STEUBENVILLE-WEIRTON-WHEELING
182. WILMINGTON-CHILLICOTHE-LOGAN
183. ZANESVILLE-CAMBRIDGE
184. CENTRAL OKLAHOMA
185. NORTH CENTRAL OKLAHOMA
186. NORTHEASTERN OKLAHOMA
187. NORTHWESTERN OKLAHOMA
188. SOUTHEASTERN OKLAHOMA
189. SOUTHWESTERN OKLAHOMA
HS P E L
H L
PH L E
PH L
H PL
PEH
H P LE
ELPH
SHP
SPH
LE
SL
SH
PSEIH L
IS H L
HE
H L
190. CENTRAL OREGON
191. EASTERN OREGON
192. NORTHWEST OREGON
193. PORTLAND
194. SOUTHWEST OR EGON
195. CENTRAL PENNSYLVANIA
196. SOUTH CENTRAL PENNSYLVANIA
197. SOUTHWEST PENNSYLVANIA
198. CAMDEN-SUMTER
199. CHARLESTON
200. COLUMBIA
201. FLORENCE
202. GREENVILLE-SPARTANBURG
203. GREENWOOD
204. GEORGETOWN
205. BLACK HILLS-RAPID CITY
206. SOUTH DAKOTA
207. EASTERN TENNESSEE-SW VIRGINIA
208. MIDDLE TENNESSEE
209. WESTERN TENNESSEE
210. ABILENE-WICHITA FALLS
211. AMARILLO-LUBBOCK
212. AUSTIN-WACO
213. BROWNSVILLE-LAREDO
214. CORPUS CHRISTI-VICTORIA
215. METROPOLITAN DALLAS-FT. WORTH
216. METROPOLITAN HOUSTON-GALVESTON
H
LP
SHP
LI
SIPH
SIH P
L H
SH L
P L
PHE
EPH
IH P LE
IEH
P L
PH
P L E
H P EL
LE
S E HL
SI LE
A = Aircraft
L = Light-duty highway vehicles
H = Heavy-duty highway vehicles
S = External combustion area sources (space heating)
P = External combustion point sources
E = Electric generation (power plants)
I = Industrial processing
^~~*™~ = All area sources
— — — = All point sources
FIGURE 9 (Continued)
-------
CO
AIR QUALITY CONTROL REGION
217. METROPOLITAN SAN ANTONIO
218. MIDLAND-ODESSA-SAN ANGELO
219 UTAH
220. WASATCH FRONT
221. VERMONT
222. CENTRAL VIRGINIA
223 HAMPTON ROADS
224 NORTHEASTERN VIRGINIA
225 STATE CAPITAL
226 VALLEY OF VIRGINIA
227 NORTHERN WASHINGTON
228 OLYMPIA-NORTHWEST WASHINGTON
229 PUGET SOUND
230 SOUTH CENTRAL WASHINGTON
231 ALLEGHENY
232 CENTRAL WEST VIRGINIA
233 EASTERN PANHANDLE
235 NORTH CENTRAL WEST VIRGINIA
236 SOUTHERN WEST VIRGINIA
237 LAKE MICHIGAN
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
I I I I I I I I I
SPH E L
ELI P
SHI L
IHPESL
S H L
SHP L
HI E PL
HE L
H IL E
IHE PL
HP L
HP L
SPH IL
SHP L
L ^ E
S H L
PH SI L
SLP E
L E
S H L
H P L E
LP 1
S H LE
SE H L
LS E
H LS
IHSPL E
AIR QUALITY CONTROL REGION
244 PUERTO RICO
245 AMERICAN SAMOA
247 US VIRGIN ISLANDS
PERCENT OF TOTAL EMISSIONS
10 20 30 40 50 60 70 80 90
1 I 1 1 1 1 1 1 1
SHIP EL
A L
L E
HA L
A = Aircraft
L = Light-duty highway vehicles
H = Heavy-duty highway vehicles
S = External combustion area sources (space heating)
P = External combustion point sources
E = Electric generation (power plants)
I = Industrial processing
• = All area sources
— — — = All point sources
FIGURE 9 (Concluded)
-------
Table 2
RELATIVE CONTRIBUTION TO TOTAL EMISSIONS
FOR A TYPICAL AQCR*
Source Category
Area sources
Point sources
Area combustion
Electric generation
Other point combustion
Industrial processing
Aircraft
Light-duty vehicles
Heavy-duty vehicles
Miscellaneous
TOTALS
Percentage of
Total AQCR Emissions
62.9
37.1
5.3
22.4
10.8
3.2
0.7
30.5
10.4
16.7
100.0 100.0
k
Defined as a hypothetical AQCR having the average
emissions for all AQCRs in each source category.
34
-------
V ASSESSMENT OF FUTURE TRENDS
A. Near-Term Trends
With a view toward a requirement for achievement of the short-term
air quality standard by the end of 1982, we attempted to estimate the
trend in the short-term NO™ situation by 1982. Our method consisted in
the application of growth rates to base-year emissions by source category.
This method provided the basis for a weighted estimate of changes that
might be expected in ambient N0» concentrations, on the assumption that
concentrations and emissions are proportional. Such an assumption
appears reasonable in the case of total oxides of nitrogen (NO ), but
X
might not be entirely accurate in the case of N0? since nonlinear photo-
chemical reactions are involved in its formation. The approach can be
considered reasonable, however, as a first approximation based on pro-
fessional judgement and experience.
In performing the projections, we utilized information from the
Bureau of Economic Analysis (1973), the Bureau of the Census (1977), the
Federal Energy Administration (1976), the Department of Transportation
(1975), and the Environmental Protection Agency (1977). On the basis of
this information, we deduced a reasonable growth rate, as a national
average, of 2% per year, compounded, for vehicle miles traveled and the
same rate for energy use in industrial and household/commercial energy
use sectors. A large average growth rate of 5.4% per year was indicated
for electric energy utilization in the absence of further control
The national average population growth was indicated at approxi-
mately 0.9% per year between 1975 and 1982. From this information, we
assumed that area source emissions, in lieu of additional control, would
grow at the rate of 2.2 times the population growth rate, as a national
average. We then weighted this source emission growth rate by the popu-
lation growth rates in the individual AQCRs to produce an estimate of
35
-------
area source emissions growth by AQCR at current levels of control.
Since the actual growth rate in emissions will reflect the influence of
additional controls,, in the future, further estimating adjustment is
required.
In the case of highway vehicle emissions, the degree of control by
1983 for the national mix of vehicle model years was calculated from
preliminary emission factors provided by EPA (Fleckenstein, 1977)
applied to California and non-California locations. In the case of all
other source categories, no further control was assumed beyond that
operating in the base year (1975) since we were unable in the time
available for the study to research the control programs for individual
AQCRs. Finally, with regard to fuel use, it must be recognized that the
mix of fuels may change considerably from base year 1975 to horizon
year 1982. Shortages of natural gas in some areas of the country will
force a switch to coal or fuel oil use for external combustion particu-
larly in the point source combustion category. This will most probably
give rise to greater emissions of NO than might be expected solely on
X
the basis of increases in energy demand.
Because of factors such as stationary source control and fuel
switching (which may vary considerably from one AQCR to another) and
strict time constraints, we chose not to present emissions change esti-
mates for the individual AQCRs. We can, however, present some semi-
quantitative conclusions from our basic investigation of the matter.
These conclusions, which may be construed to apply to a typical AQCR,
are as follows:
• On the basis of the latest EPA emission factors, we can
expect as much as a 207= decrease in NO emissions from
highway vehicles in the near term (1975-1982) for non-
California AQCRs and a 25% decrease in NOX emissions for
California AQCRs.
• Emissions in sources categories other than highway vehicles
will probably increase by 15% in the near term in lieu
of further control and adverse changes in the fuel mix.
• Because of a fairly even balance between vehicle and non-
vehicle emissions, most AQCRs will have, at best, a very
slight decrease in net regional emissions of N0x in the
short term.
36
-------
Figure 10 (ABAC 1977) shows the near-term (and long-term) expecta-
tions for NO in the San Francisco Bay Area in the absence of new con-
X
trols and supports the conclusions we have drawn relative to near-term
changes in NO emissions for a sample AQCR. Figure 11 presents a
X
cumulative distribution of the fractional change in NO emissions
X
between 1975 and 1982 for the AQCRs analyzed. Population growth rates
input to this analysis appear in Appendix B.
B. Long-Term Trends
Although we have not performed a quantitative analysis of long-
term NO emission trends, certain conclusions may be drawn from past
X
experience, judgement, and the quantitative studies that are available.
As illustrated in Figure 10, which represents long-term trends for the
San Francisco Bay Area AQCR, near-term improvements in NO emissions
X
will be offset by growth in the longer term, presenting a virtually
changeless picture over a 25-year period. Decreases in auto emissions
will be offset by increases in stationary source categories especially
in the fuel combustion category. Throughout the long term, motor
vehicle emissions will remain the major contributor to N0_ air quality
problems. Another, competing, influence on long-term trends is the
impact of hydrocarbon emission reduction on the ambient concentrations
of N0». Since N0« production is partly photochemical, a possible impact
would be suspected. In this regard, Trijonis (1977) observed empirically
that hydrocarbon reduction is indeed related to accompanying, though
disproportionately smaller, reductions in peak N02 concentrations.
37
-------
TONS/DAY
800
700
600
500
400
300
E*
200
100
KV
I ;
A
B
C
D
~
.^-— -""
/
II
II
II ll
If
1
= /
F
======
A
B
C
D
^
tr
F
i\
1975 1985
|^
^^.
^^^
^
SUURfJE CATfcUUKY:
A
B
C
D
F"*^^
F
JN.
KN,
L
2000
A OTHER
B LIGHT DUTY AUTO
C AIRCRAFT
D OFF-HIGHWAY MOBILE SOURCES
E BURNING OF MATERIALS
F COMBUSTION OF FUELS
J OTHER IND/COMM
= K CHEMICAL
L PETROLEUM REFINING
SOURCE: Association of Bay Area Governments.
FIGURE 10 EMISSION TRENDS FOR NITROGEN OXIDES IN THE SAN FRANCISCO
BAY AREA
38
-------
100
0.80
0.90 1.00
FRACTIONAL CHANGE
FIGURE 11 CUMULATIVE DISTRIBUTION OF FRACTIONAL CHANGE IN
NOX EMISSIONS BETWEEN 1975 AND 1982
39
-------
VI CONTROL REQUIREMENTS, OPTIONS, AND FEASIBILITY
A. Control Implications of Possible Standards
The EPA is currently considering a short-term (1-hour) ambient air
o
quality standard between 200 and 1000 (ig/m . The standard chosen will
determine the degree of control and the cost required to achieve and
maintain the standard. Based on the analysis, the need for control
varies considerably with the level of the standard as outlined in the
following discussion and illustrated in Figures 12, 13, and 14.
1. Scope of Required Control
In Figure 12, which is based on the histograms of Figures 2,
4, 7, and 8, it can be seen that the number of AQCRs involved in control
programs for NO varies in a highly nonlinear manner with the level of
X
air quality (standard) that must be achieved. Similar conclusions can
be drawn from Figure 13 for point sources based on the data of Table 1.
2. Stringency of Required Control
Comparison with Long-Term Standard—Since a long-term standard
for N09 (100 (j,g/m as an annual average) already exists, one item of
concern is the relative stringency of the long-term standard and the
various short-term standards within the proposed range. To illustrate
this issue, we prepared Figure 14, which indicates the percentage of
receptor sites for which a specific short-term standard is estimated to
be more stringent than the existing long-term standard. Greater strin-
gency for a short-term standard means that even if the long-term standard
is achieved, the short-term standard will still be a problem to achieve.
Figure 14 is based on a cumulative distribution of the ratios of second-
highest 1-hour average-to-annual average N0« concentrations constructed
from available continuous monitoring data. Since monitoring data, for
the most part, reflects an area source rather than a point source
41
-------
2000
1000
900
« 800
^ 700
Q
K 600
Q
Z
500
oN
400
o
I
C 300
o
UJ
a.
v>
200
100
• 4--O ••
i Ir^HR-M^ASUREMENTS
'•' "~ MrEASUREWENTS
20 40 60 80 100
PERCENT OF AQCRs EXPECTED TO EXCEED A SPECIFIED 1-HOUR STANDARD
FIGURE 12 PERCENTAGE OF AQCRs EXPECTED TO EXCEED A SPECIFIED NO2
STANDARD, BASED ON VARIOUS AREA SOURCE ESTIMATION METHODS
42
-------
--.-.IL i,_ir \ i _-, i,- -*
i ,5 "--i- L ^r \i -i- ~ --
. J_^kr ir-L- - >,. i - -' - ,-•
100
2 4 6 8 10 12
PERCENT OF MAXIMA EXPECTED TO EXCEED A SPECIFIED 1-HOUR STANDARD
FIGURE 13 PERCENTAGE OF POINT SOURCE GROUND LEVEL MAXIMA EXPECTED TO
EXCEED A SPECIFIED N02 STANDARD (based on Gaussian modeling with
assumed 100% conversion from NO to NOo)
influence, the results in Figure 14 may not apply at sites where N0_
concentrations are influenced primarily by point source plumes.
Degree of Improvement—The required degree of air quality
improvement implied by various possible standards is readily deduced
from Figure 12, which has been drawn on log-linear scale. On the
assumption that NCL levels at the 1-hour averaging time are roughly
proportional to NO emissions from contributing source categories,
X
Figure 12 may be used, also, to obtain a first approximation of the
degree of required control on contributing sources. As an example of
the procedure, we note using the all methods curve for the median AQCR,
3
a standard of 200 |j,g/m would imply a 50% reduction in contributing
emissions. For the 10th percentile AQCR, an 80% degree of control is
3
implied by a 200 |J,g/m standard.
43
-------
300
400
500
600
700
800
900
1000
1-HOUR N02 STANDARD-
FIGURE 14
ESTIMATED PERCENTAGE OF SITES FOR WHICH SPECIFIED STANDARDS
FOR 1-HOUR CONCENTRATION WOULD BE MORE STRINGENT THAN
THE EXISTING FEDERAL ANNUAL AVERAGE STANDARD OF 100 ng/m3
3. Control Options
Although control options exist in most of the major source
categories shown in Table 2, emphasis should be placed on those cate-
gories for which the smallest percentage of control will yield the
greatest percentage decrease in NCL concentrations. On the other hand,
care must be taken to avoid the unnecessary control of source categories
largely unrelated to the existing NO,, problem. As an example, consider
an AQCR in which automobile emissions represent 40% of the total regional
emissions of NO and point source combustion another 40%. A simplistic
X
approach to control might consider either source category an appropriate
candidate for control. In the case of a center city N02 problem, how-
ever, automobile emissions might account for 90% of the N0_ concentra-
tion, and in such a case more astute reasoning would favor the choice
of automobile controls. Depending on the type of problem diagnosed, the
following are the prime options for control:
44
-------
• Automobile emissions
• External combustion emissions
• Industrial processing emissions
• Space heating emissions
For a typical AQCR, control of automobile emissions will
undoubtedly yield the greatest return in community-wide air quality
improvement. For AQCRs in which specific point source problems have
been identified, control of contributing point source emissions will
also be required. Where possible, control strategies should be soundly
based on local analysis. Blanket control of source categories solely
on the basis of relative contribution to total AQCR emissions may not
provide proportionate improvement in air quality.
Several approaches exist for the control of NO emissions:
tighter emission standards for highway vehicles; modifications of exist-
ing sources (retrofit program); minimum performance standards (best
available control technology) for new sources; inspection and maintenance
programs (primarily for automobiles); and transportation control (to
reduce NO generated as a result of vehicle operation). Other control
A
options include parking management; auto use deterrents such as higher
bridge tolls, and gasoline, parking, and auto use taxes; and gasoline
rationing. These latter options cannot be imposed legally at the fed-
eral level but are available as options for State Implementation Plans
(SIPs).
4. Control Feasibility and Effectiveness
We utilized primarily the experience of the air quality mainte-
nance planning effort in the San Francisco Bay Area for indications of
control measure feasibility and effectiveness. Except for gasoline
rationing and parking management, which have proven politically unaccept-
able in the past, the control approaches listed in the preceding sub-
section were all deemed feasible for implementation in the air quality
maintenance planning effort. Reductions achieved in N0x emissions were
negligible in the case of transportation controls and auto use deterrents.
The best available control of new and existing stationary sources
45
-------
yielded an 11% reduction in NO emissions in the near term (1975 through
X
1985). Studies conducted by the BAAPCD air quality maintenance planning
staff (ABAC 1977b) concluded that additional reduction in current auto
emission standards might be possible over the longer term. Although
no reduction estimates were made by the staff, we estimate that such a
program would result in at best 1570 reduction in NO emissions over
X
current emission trends.
46
-------
VII INTERACTION OF THE N02 AND OXIDANT CONTROL PROGRAMS
One of the most complicated problems in NO control is the chemical
X
interaction between NO and oxidant. Because of this interaction, con-
X
trols intended to improve air quality by lowering the N0? content are
likely to have an adverse effect on efforts to control the oxidant
(primarily ozone) content. To clarify the problem, we chose two methods
of analysis: the graphic modeled isopleth method described by Dimitriades
(1977) and by Dodge (1977), and a photochemical modeling exercise using
the DIFKIN model as described in Martinez et al. (1973).
A. The Modeled Isopleth Method
This method consists of a set of isopleths of maximum ozone concen-
tration expected to develop as the result of chemical reaction between
initial concentrations of nonmethane hydrocarbons (NMHC) and oxides of
nitrogen (NO ) in a reaction chamber. The isopleths (Figure 15) are
X
derived from reaction chamber (smog chamber) experiments modified by
mathematical simulation to more closely approximate true atmospheric
conditions. The set of isopleths is tuned to represent stagnant meteoro-^
logical conditions and clear skies in the Los Angeles area. The iso-
pleths are useful for semiquantitative estimates of changes in oxidant
air quality resulting from joint or individual changes in emissions for
nonmethane hydrocarbons, or oxides of nitrogen, or both.
To use the isopleths, select a starting point representative of the
current ozone maximum and the ratio of NMHC to NO in the region of
X
interest. Proposed percentage changes in either NMHC or NO emissions
^—— j£
or both are then represented by horizontal or vertical arrows paralleling
the abscissa or ordinate, as appropriate to the pollutant(s) subject to
control. The percentage change in ozone can then be noted as the per-
centage change in the value at the end point relative to the value at
the starting point. Perusal of the isopleth pattern will reveal that in
47
-------
00
0.7
0.6
.9 0.5
E
I
S 0.4
x
O
~ 0.3
z
LU
O
O
rr
H
Z 0.2
LL
O
CO
UJ
Q
§ 0.1
O STARTING POINT I
• END POINT
T
T
2:1
NOX CONTROL
NMHC CONTROL
OZONE = 0.08 /0.20 0.30 0.40 0.50 0.55 0.60 0.65 (parts per million by volume)
NMHC
SQURCi: Dodge, M.C., 1977.
1.0 2.0 3.0 4.0
NONMETHANE HYDROCARBONS (NMHC) — parts per million, carbon
5.0
SA-6183-7
FIGURE 15 ISOPLETHS OF PEAK OZONE CONCENTRATION EXPECTED UNDER STAGNANT METEOROLOGICAL
CONDITIONS FOR VARIOUS INITIAL CONCENTRATION RATIOS OF NONMETHANE HYDROCARBONS
TO OXIDES OF NITROGEN
-------
regions with NMHC:NO ratios less than about 5.6:1, NO reductions will
x ' x
tend to increase ozone concentrations if NMHC concentrations are held
constant. At NMHC:NO ratios greater than 5.6:1, NO reductions will
x x
reduce ozone concentrations. Regardless of the ratio, changes in NMHC
are less effective (result in lesser percentage changes in ozone) as
ratios increase because of NO reduction. We have presented two situa-
X
tions in Figure 15: one in which a 30% reduction in NO produces a 100%
X
increase in ozone concentration; and a second in which a 50% reduction
in NO decreases ozone concentration, but changes the effectiveness of
X
NMHC control from a 50% reduction in ozone concentration to a 25%
reduction.
B. DIFKIN Photochemical Modeling
The second illustration we have prepared consists in mathematically
simulating the chemical reactions taking place in a parcel of air fol-
2
lowing a trajectory through an urban area (Figure 16). A 2500-km city
(~ 2 million people) was assumed. A uniform emission rate of 0.34 tons
2
per day of both NMHC and nitrogen dioxide per km in the peak traffic
2
periods and an emission rate of 0.27 tons per day per km in the off-
peak periods were assumed. This is roughly equivalent to emission rates
observed in San Jose, California. A wind speed of 10 km/hr (~ 3 m/s)
was assumed. The air parcel, therefore, spent 5 hours over the city and
was assumed to enter at the beginning (7 a.m.) of a two hour morning
traffic peak, exiting at 12 noon. The air entering the city (located
at 25° N latitude and simulated for midsummer) was assumed "clean" with
nominal initial concentrations of 1 part per hundred million for all
pollutants.
Ozone formation was simulated separately for the initially defined
emission conditions, and after a 50% reduction in NO emissions was dis-
tributed uniformly over the trajectory. A third simulation was performed
after replacing the eliminated NO emissions by equivalent emissions con-
verted to an initial concentration at the beginning of the trajectory
and at altitude (199 to 563 meters above ground) to simulate an indus-
trial plume. The simulated industrial plume was assumed one-half
49
-------
Ui
o
SA-3515-7
FIGURE 16 ILLUSTRATION OF A WIND TRAJECTORY THROUGH AN URBAN AREA
-------
NO and one-half NO- by volume as opposed to the 100% NO flux of the
surface emissions.
The results of the simulation are given in Figure 17. It can be
seen that the 50% reduction in NO resulted in a 57% increase in ozone
concentration. Replacement of the original NO emissions at the surface
by an equivalent amount of NO at altitude restored the ozone concen-
tration to near its original value. The simulations illustrate the
possible adverse interaction between NO control and the ozone problem
X
and indicate that the same problem probably pertains to both elevated
point source and ground level area source emissions.
51
-------
0.24
0.22
0.20
0.18
0.16
a.
a
0.14
H 0.12
z
UJ
o
z
o
o 0.10
UJ
o
N
O
0.08
0.06
0.04
0.02
50% REDUCTION
IN BASELINE x
EMISSIONS/
HALF-SURFACE AND
HALF-ELEVATED
EMISSIONS
BASELINE
(ALL EMISSIONS
AT THE SURFACE)
10 11 12 13
TIME — LOT
14
15
16
17
FIGURE 17
OZONE CONCENTRATION ALONG AN AIR TRAJECTORY,
AS A FUNCTION OF TIME, FOR THREE EMISSIONS
SCENARIOS
18
52
-------
REFERENCES
1. Association of Bay Area Governments (1977a), "Air Quality Maintenance
Plan/' Tech Memo 11, Berkeley, California.
2. Association of Bay Area Governments (1977b), "Air Quality Maintenance
Plan," Tech Memo 8, Berkeley, California.
3. Briggs, G. A. (1969), "Plume Rise," U.S. Atmoic Energy Commission,
Div. Tech. Inf.
4. Bureau of the Census (1977). Series P-25, No. 704.
5. Bureau of Economic Analysis (1973), "Projection of Economic Activity
for Air Quality Control Regions," BEA Publication PB-259 8070.
6. Caenepeel, C., et al. (1976), "Impact of Power Plants on Short Term
Ambient NCv Concentrations," EPA Draft Report.
7. Davis, D. D., et al. (1974), "Trace Gas Analysis of Power Plant
Plumes via Aircraft Measurement: 0,,, NO and S0? Chemistry,"
Science. Vol. 186, p. 733. X *
8. Dimitriades, B. (1977), "An Alternative to the Appendix-J Method
for Calculating Oxidant and N0?--Related Control Requirements,"
Proc. International Conference on Photochemical Oxidant Pollution
and Its Control. EPA-600/3-77-001.
9. Dodge, M. C. (1977), "Combined Use of Modeling Techniques and Smog
Chamber Data to Derive Ozone Precursor Relationships," Proc. Inter-
national Conference on Photochemical Oxidant Pollution and Its
Control, EPA-600/3-77-001.
10. Department of Transportation (1975), "Selected Highway Statistics,
1975."
11. Environmental Protection Agency (1976), "Monitoring and Air Quality
Trends Report, 1974," EPA 450/1-76-001.
12. Environmental Protection Agency (1977a), "Air Quality Data--1975
Annual Statistics," EPA 450/2-77-002.
13. Environmental Protection Agency (1977b), "Mobile Source Emission
Factors," Interim Document.
14. Federal Energy Administration (1976), "National Energy Outlook."
53
-------
15. Fleckenstein, L. (1977), EPA, Private Communication.
16. Hanna, S. R. (1971), "A Simple Method of Calculating Dispersion
from Urban Area Sources," Jour. Air Pollution Cont. Assn., Vol. 21,
No. 12.
17. Hegg, D., et al. (1976), "Reactions of Ozone and Nitrogen Oxides in
Power Plant Plumes," Atmospheric Environment, Vol. II, pp. 521-526.
18. Holzworth, G. C. (1972), "Mixing Heights, Wind Speeds and Potential
for Urban Air Pollution Throughout the Contiguous United States,"
EPA Publication AP-101.
19. Larsen, R. I. (1971), "A Mathematical Model for Relating Air Quality
Measurements to Air Quality Standards," EPA Publication AP-89.
20. Ludwig, F. L. and E. Shelar (1977), "Selecting Sites for Monitoring
the Photochemical Pollutants," Final Report (Draft), EPA Contract
68-02-2028.
21. Martinez, J. R., et al. (1973), "User's Guide to Diffusion/Kinetics
(DIFKIN) Code," Final Report, EPA Contract 68-02-0336, General
Research Corporation, Santa Barbara, California.
22. Morris, R. (1977), "Nitrogen Dioxide Problem Areas," Draft Report,
October 12, 1977, Environmental Policy Office, Department of Energy,
Washington, D.C.
23. Siu, W. (1977), BAAPCD Private Communication.
24. Trijonis, J. (1977), "Empirical Studies of Ambient Nitrogen Dioxide
Air Quality and N02 Precursor Relationships," Final Report (Draft)
for the Environmental Protection Agency.
25. Turner, D. B. (1969), "Workbook of Atmospheric Dispersion Estimates,"
EPA Publication AP-26.
54
-------
Appendix A
SIMPLIFIED MODELING TECHNIQUES
A-l
-------
Appendix A
SIMPLIFIED MODELING TECHNIQUES
In the body of this report, reference was made to modeling tech-
niques used to estimate point and area source impacts on ambient concen-
trations of NO and NO,. This appendix outlines the techniques used in
/ X £»
the modeling.
A. Point Source Modeling
1. Dispersion Algorithms
The basic algorithm describing the point source plume is of
the form
C =
CT U
exp
exp
v
+ exp - -=
(A-l)
In this algorithm, C is concentration at a point within the plume a dis-
tance y horizontally and z vertically from the centerline of the plume.
Quantities a and a are measures of plume spread, which increases with
downwind distance according to the relationship
CT = aX
(A-2)
where X is distance, and a and b are constants that reflect the degree
of turbulence. The height of the plume is given by the quantity H, the
mean wind speed by the quantity U, and the rate of pollutant emission
by the quantity Q.
A-3
-------
The solution of equation (A-l) may be obtained graphically in
Figure A-l, taken from Turner (1969). The figure provides the solution
for stability category B (slightly unstable), which we have taken to
represent adverse conditions leading to relatively high, though probably
not worst case, concentrations at ground level. By fitting a line
through the peaks in the concentration as a function of distance curves
(dashed line in the figure), we obtained a simple algorithm for maximum
ground level concentration in the form
r - 4.44Q U x 104 , ox
'-'MAY ~ i 5^ « (A-3)
"MAX H1.87
This algorithm, with an assumed wind speed of 2 m/s, provides a reason-
able estimate of maximum ground-level concentrations under adverse
meteorological conditions.
2. Plume Rise Algorithms
The rise of buoyant plumes above the level of the emission
point has been fully described by Briggs (1969).* The most general
algorithm takes the form
AH -
U
where AH is the amount of plume rise, and F is given by
(A-5)
c iQ 2/5
and X* = 14F~^ and 34F for F less than and greater than 55, respec-
tively. In the above equations, T is ambient air temperature, T is
the temperature of the exiting gas, Vf is the velocity of the exiting
"Briggs, G. A. (1969), "Plume Rise," U.S. Atmoic Energy Commission,
Div. Tech. Inf.
A-4
-------
1 10
DOWNWIND DISTANCE — km
100
FIGURE A-1
GRAPHICAL CALCULATION OF NORMALIZED MAXIMUM GROUND-LEVEL
CONCENTRATION FROM A POINT SOURCE AS A FUNCTION OF PLUME
HEIGHT (H) AND DOWNWIND DISTANCE (adapted from Turner, D. B.f 1969)
A-5
-------
gas, F is a buoyance factor, U is wind speed, and X* is a distance
scaling factor. Equation (A-4) gives the final, stabilized height of
the plume above the exit point of the gas. This plume rise is then
added to the height of the exit point to yield the total height of the
plume, referred to also as effective stack height, which is the same as
the quantity H in equation (A-3).
These plume rise algorithms were used to obtain plume height
H for each individual stack as input to our point source modeling effort.
B. Area Source Modeling
Since an area source may logically be treated as a series of line
sources side by side, the area source algorithm is derived by integration
of the guassian line source equation and takes the form
2Q^
"" '"" (A-6)
or
2Q (1-b)
C — (A-7)
V2lcUa(l-b)
where Q is the rate of emission per unit area, L is the upwind length
of the area source, X~ and X- are the distances from the recptor point
to the farthest and closest edges of the area source respectively, and
other variables are as defined earlier. Equation (A-6) applies to points
downwind from the edge of the area source; equation (A-7) provides a con-
centration at any downwind point within the confines of the area source.
A variant of (A-7) in the form
2Q (1-b)
C = — (A-8)
provides a spatial average of concentration within the area source con-
fines. At downwind distances exceeding one or two area source dimensions,
A-6
-------
spreading of a finite area source plume gradually begins to invalidate
equation (A-6), which allows for vertical plume spread only.
Figure A-2 provides a graphical solution of equation (A-6), which
provides a reasonable estimate of annual average concentration spatially
averaged throughout a population center.
A-7
-------
0.10—1
-< £ 0.08-
tn "
O
i
UJ
0.06-
0.04-
0.02 —I
0.5—1
0.4 —
0.3 —
0.2 —
0.1—J
SOLUTION OF:
2QAL
Ua(1-b)(2-b)
a = 0.15; b = 0.75
A = Area
(1-b)
EXAMPLE
1.5 mg/km2-day
2km
'A
L
U = 2m/s
C = 1 mg/m3
^0.10
—0.4
—0.3
— 0.2
—0.1
— 0.08
z
o
O
Q
-0.06 z
C
0-1
y o>
O
^0.04
HI
ID
<
CC
ui
— 0.02
Z
I—0
SA-5600-29
FIGURE A-2 GRAPHICAL CALCULATION OF ANNUAL AVERAGE CONCENTRATION
AS A SPATIAL AVERAGE
A-8
-------
Appendix B
EMISSIONS AND GROWTH DATA, BY AQCR
B-l
-------
Appendix B
EMISSIONS AND GROWTH DATA, BY AQCR
In the body of the report, reference was made to emissions by
source category and population growth factors by AQCR. This appendix
provides the data referenced.
B-3
-------
Table B-l
BASE YEAR EMISSION RATES (TONS PER YEAR) AND PERCENT OF TOTAL EMISSIONS OF NO BY SOURCE CATEGORY AND AQCR
AQCR
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Grand
Total
Emissions
T/Yr
16,161
39,527
32,020
146,592
238,121
31,336
87,355
25,148
14, 614
11,534
10,672
19,985
105,040
145,718
120,463
65,842
24,092
83,537
67,639
48,050
15,920
172,711
3,089
698,945
38,181
28,366
10,531
73,673
83,516
279,023
134,564
22,052
33,898
7,911
16,125
%
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Total
Area Source
Emissions
T/Yr
15,207
39,256
32,008
67,615
128,854
30,573
75,446
14,799
5,310
5,736
7,018
10,459
21,187
41,403
92,554
52,079
23,770
42,050
34,503
34,230
15,489
94,995
2,993
491,618
23,883
20,480
9,158
70,349
64,209
222,718
100,710
7,346
6,103
6,239
12,261
X
94
99
100
46
54
98
86
59
36
50
66
52
20
28
77
79
99
50
51
71
97
55
97
70
63
72
87
95
77
80
75
33
18
79
76
Total
Point Source
Emissions
T/Yr
954
271
12
78,977
109,267
763
11,909
10,349
9,304
5,798
3,653
9,526
83,852
104,315
27,908
13,763
322
41,487
33,136
13,820
431
77,716
97
207,326
14,299
7,886
1,372
3,324
19,307
56,305
33,854
14,706
27,794
1,672
3,863
%
06
01
0
54
46
02
14
41
64
50
34
48
80
72
23
21
01
50
49
29
03
45
03
30
37
28
13
05
23
20
25
67
82
21
24
External
Combustion
Area Source
Emissions
T/Yr
1,375
3,200
2,132
6,320
13,382
2,396
3,744
2,894
751
420
2,148
767
574
2,481
8,463
8,469
3,355
1,314
4,423
3,188
1,822
8,262
78
47,995
1,450
1,076
348
3,987
4,663
19,542
6,479
309
222
337
702
%
09
08
07
04
06
08
04
12
05
04
20
04
01
02
07
13
14
02
07
07
11
05
03
07
04
04
03
05
06
07
05
01
01
04
04
Point Source
Emissions
From Electric
Power
Generation
T/Yr
0
0
0
77,882
66,570
763
10
1,265
4,206
391
649
2,950
81,357
99,439
22,244
11,123
0
35,919
4,764
12,782
338
30,137
0
150,966
8,966
936
0
0
18,540
24,014
626
12,922
7,149
338
2,268
"/,
0
0
0
53
28
02
0
05
29
03
06
15
77
68
18
17
0
43
07
27
02
17
0
22
23
03
0
0
22
09
0
59
21
04
14
Nonelectric
Generation
Point Source
External
Combustion
Emissions
T/Yr
420
271
0
43
28,863
0
10,105
8,855
1,786
5,385
2,760
4,181
1,995
3,400
2,704
2,421
165
5,106
22,109
775
58
41,943
81
18,212
3,561
5,274
1,068
2,012
754
5,467
21,308
1,361
2,883
956
1,582
7.
03
01
0
0
12
0
12
35
12
47
26
21
02
02
02
04
01
06
33
02
0
24
03
03
09
19
10
03
01
02
16
06
09
12
10
Point Source
Industrial
Process
Emissions
T/Yr
488
0
12
1,026
13,392
0
1,601
227
28
0
0
2,392
500
1,406
1,959
0
128
430
6,120
3
10
5,335
1
38,036
1,769
206
10
445
3
26,598
10,980
420
17,674
378
10
%
03
0
0
01
06
0
02
01
0
0
0
12
0
01
02
0
01
01
09
0
0
03
0
05
05
01
0
01
0
10
08
02
52
05
0
Aircraft
Emissions
T/Yr
42
543
15
380
4,799
3,387
188
5,398
628
188
114
73
1,456
171
2,237
767
248
1,040
126
59
14
662
7
5,581
203
82
39
1,456
1,198
1,823
1,363
20
302
16
196
7.
0
01
0
0
02
11
0
21
04
02
01
0
01
0
02
01
01
01
0
0
0
0
0
01
01
0
0
02
01
01
01
0
01
0
01
Light-Duty
Highway
Vehicle
Emissions
T/Yr
6,501
18,373
16,677
30,898
60,674
16,850
39,642
2,727
821
284
451
6,022
13,897
22,260
49,650
21,878
9,464
20,768
14,770
14,517
6,795
46,491
2,166
256,640
13,620
10,118
5,626
41,043
36,148
118,116
55,108
4,340
3,677
3,030
6,616
%
40
46
52
21
25
54
45
11
06
02
04
30
13
15
41
33
39
25
22
30
43
27
70
37
36
35
53
56
43
42
41
20
11
38
41
Heavy Duty
Highway
Vehicle
Emissions
T/Yr
2,827
7,857
6,014
13,245
22,366
4,750
13,811
927
703
356
292
1,475
3,759
6,356
15,707
7,835
4,751
8,187
4,530
5,317
2,280
12,086
367
75,976
3,625
2,383
1,242
10,100
10,132
40,054
14,616
1,020
802
1,103
2,227
%
19
20
19
09
09
15
16
04
05
03
03
07
04
04
13
12
20
10
07
11
14
07
12
11
09
08
12
14
12
14
11
05
02
14
14
w
-------
Table B-l (Continued)
AQCR
Number
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68 '
69
70
71
72
73
Grand
Total
Emissions
T/Yr
120,806
29,895
60,266
3,528
19,977
27,654
176,143
957,604
6,832
459,991
24,051
189,305
118,736
132,131
153,945
36,474
174,924
56,994
64,587
86,495
132,097
26,916
52,976
38,831
63,679
20,861
44,206
40,969
13,761
232,117
64,028
772,215
33,893
96,334
400,177
32,080
242,985
50,611
%
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Total
Area Source
Emissions
T/Yr
78,176
20,486
25,775
3,073
2,568
21,440
130,579
586,231
6,441
259,492
12,854
134,065
54,233
62,822
79,072
20,664
86 , 703
32,187
28,781
41,617
85,234
26,384
20,597
30,434
32,017
19,389
36,397
33,054
13,136
41,416
45,802
383,153
13,274
33,647
127,842
16,572
28,778
32,921
'/.
65
69
43
87
13
78
74
61
94
56
53
71
46
48
51
57
50
56
45
48
65
98
3.9
78
50
93
82
81
95
18
72
50
39
35
32
52
12
65
Total
Point Source
Emissions
T/Yr
42,630
9,410
34,491
455
17,409
6,214
45,564
371,373
391
200,500
11,197
55,239
64,503
69,309
74,873
15,809
88,221
24,806
35,806
44,877
46,863
532
32,379
8,396
31,662
1,471
7,809
7,915
625
190,701
18,226
389,062
20,619
62,687
272,335
15,508
214,207
17,690
7=
35
31
57
13
87
22
26
39
06
44
47
29
54
52
49
43
50
44
55
52
35
02
61
22
50
07
18
19
05
82
28
50
61
65
68
48
88
35
External
Combustion
Area Source
Emissions
T/Yr
7,035
1,291
2,026
261
120
1,866
21,459
131,815
574
37,971
627
12,731
1,046
1,927
2,308
314
1,459
1,541
1,445
1,964
5,700
1,512
885
1,195
596
1,487
2,789
1,597
1,224
4,048
3,590
61,942
856
3,064
13,717
1,277
1,582
3,593
%
06
04
03
07
01
07
12
14
08
08
03
07
01
01
01
01
01
03
02
02
04
06
02
03
01
07
06
04
09
02
06
08
03
03
03
04
01
07
Point Source
Emissions
From Electric
Power
Generation
T/Yr
38,274
0
32,413
259
17,187
4,451
37,336
303,011
0
123,347
9,535
49,829
57,179
34,467
63,242
13,750
81,114
10,226
34,430
37,524
42,456
97
24,197
5,396
2,049
0
359
129
0
159,011
4,812
243,137
19,593
38,281
240,608
9,201
209,890
16,449
%
32
0
54
07
86
16
21
32
0
27
40
26
48
26
41
38
46
18
53
43
32
0
46
14
03
0
01
0
0
69
08
31
58
40
60
29
86
33
Nonelectric
Generation
Point Source
External
Combustion
Emissions
T/Yr
2,979
6,272
785
192
198
1,761
7,716
61,758
391
51,467
1,662
4,671
7,086
30,333
6,645
2,000
3,813
10,222
1,162
6,624
1,755
309
4,150
2,555
28,155
808
7,260
7,655
625
31,342
13,407
112,200
1,026
23,537
15,224
3,034
3,142
1,216
%
02
21
01
05
01
06
04
06
06
11
07
02
04
23
04
05
02
18
02
08
01
01
08
07
44
04
16
19
05
14
21
15
03
24
04
09
01
02
Point Source
Industrial
Process
Emissions
T/Yr
1,365
3,138
1,293
0
1
2
184
5,841
0
24,567
0
0
17
4,272
4,502
52
3,283
4,345
214
641
2,577
126
3,360
444
1,252
620
51
0
0
327
7
31,395
0
481
914
3,273
1,076.
0
%
01
10
02
0
0
0
0
01
0
05
0
0
0
03
03
0
02
08
0
01
02
0
06
01
02
03
0
0
0
0
0
04
0
0
0
10
0
0
Aircraft
Emissions
T/Yr
2,015
44
641
4
9
118
718
5,997
5
2,107
178
2,694
717
1,518
3,134
138
1,231
160
239
33
3,061
40
407
246
2,936
149
518
222
293
239
172
4,660
51
200
3,067
22
767
175
%
02
0
01
0
0
0
0
01
0
0
01
01
01
01
02
0
01
0
0
0
02
0
01
0
05
0
01
01
02
0
0
01
0
0
01
0
0
0
Light -Duty
Highway
Vehicle
Emissions
T/Yr
37,586
10,206
12,017
1,430
1,264
15,006
79,455
299,869
4,518
121,186
4,535
76,714
31,386
30,935
32,678
10,355
50,343
18,226
15,649
23,539
42,961
15,039
10,564
17,483
16,447
6,678
18,518
12,364
4,681
19,522
23,767
171,306
5,143
14,745
66,183
8,451
13,276
15,285
%
31
34
20
41
06
54
45
31
66
26
19
41
26
23
21
28
29
32
24
27
33
56
20
45
26
32
42
30
34
08
37
22
15
15
17
26
05
30
Heavy-Duty
Highway
Vehicle
Emissions
T/Yr
14,972
3,634
5,006
545
423
2,301
14,449
63,964
662
49,138
4,852
18,095
9,988
11,672
14,674
3,531
15,714
5,099
4,863
7,298
14,339
4,277
3,575
4,591
3,762
2,890
5,195
4,730
2,194
5,789
5,348
57,999
2,459
5,556
23,100
1,763
4,053
4,747
%
12
12
08
15
02
08
08
07
10
11
20
10
08
09
10
10
09
09
08
08
11
16
07
12
06
14
12
12
16
02
08
08
07
06
06
05
02
09
Ul
-------
Table B-l (Continued)
AQCR
Number
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
Grand
Total
Emissions
T/Yr
50,512
204,639
45,585
137,531
131,469
203,399
97,580
35,765
99,719
106,853
163,271
71,035
25,875
12,467
46,711
32,015
16,767
21,378
67,880
22,318
434,955
56,395
24,878
22,922
54,390
55,935
22,600
23,970
48,153
181,020
19,472
34,149
815,406
38,341
7,466
22,269
27,580
86
%
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Total
Area Source
Emissions
T/Yr
34,634
44,710
37,129
33,838
36,030
82,088
65,207
34,170
56,505
40,601
59,299
35 , 743
12,571
10,213
31,010
25,267
15,428
19, 359
46,096
22,077
73,381
29,798
20,588
15,742
20,000
36,985
14,137
22,648
27,186
42,974
18,685
21,356
228,589
21,078
4,846
11,228
18,553
0
7.
69
22
81
25
27
40
67
96
57
38
36
50
49
82
66
79
92
91
68
99
17
53
83
69
37
66
63
94
56
24
96
63
28
55
65
50
67
0
Total
Point Source
Emissions
T/Yr
15,878
159,929
8,456
103,693
95,439
121,311
32,373
1,596
43,213
66,252
103,973
35,292
13,304
2,255
15,701
6,748
1,338
2,019
21,783
241
361,575
26,597
4,290
7,179
34,390
18,951
8,464
1,322
20,967
138,046
787
12,793
586,818
17,263
2,620
11,041
9,027
86
7.
31
78
19
75
73
60
33
04
43
62
64
50
51
18
34
21
08
09
32
01
83
47
17
31
63
34
37
06
44
76
04
37
72
45
35
50
33
100
External
Combustion
Area Source
Emissions
T/Yr
2,218
3,755
4,248
3,273
3,984
6,829
7,918
4,660
6,972
3,856
5,892
4,483
961
607
2,170
1,645
895
1,136
3,229
969
8,172
1,764
1,202
743
1,234
2,967
673
910
1,921
5,198
805
1,455
18,279
.2,021
535
1,038
1,806
0
%
04
02
09
02
03
03
08
13
07
04
04
06
04
05
05
05
05
05
05
04
02
03
05
03
02
05
03
04
04
03
04
04
02
05
07
05
07
0
Point Source
Emissions
From Electric
Power
Generation
T/Yr
5,333
152,693
3,329
94,714
82,929
85,233
27,537
0
41,231
62,861
72 , 144
17,873
12,463
1,706
11,582
2,912
674
1,508
19,254
169
38,314
21,732
1,631
4,293
31,773
8,578
4,251
612
19,681
118,144
1
7,410
154,672
5,808
847
1,313
5,689
0
7,
11
75
07
69
63
42
28
0
41
59
44
25
48
14
25
09
04
07
28
01
09
39
07
19
58
15
19
03
41
65
0
22
19
15
11
06
21
0
Nonelectric
Generation
Point Source
External
Combustion
Emissions
T/Yr
10,137
7,227
2,060
1,958
10,859
32,652
4,375
1,514
1,949
2,680
30,823
5,794
822
536
3,821
2,425
661
495
1,610
71
320,593
4,653
2,092
2,437
848
2,902
3,734
248
1,106
4,467
740
5,213
334,163
10,718
1,551
9,301
2,454
57
7.
20
03
05
01
08
16
04
04
02
03
19
08
03
04
08
07
04
02
02
0
74
08
08
11
02
05
17
01
02
02
03
15
41
28
20
41
08
66
Point Source
Industrial
Process
Emissions
T/Yr
404
8
2,349
7,018
1,527
2,889
414
80
24
709
932
11,453
10
3
62
1,371
3
15
901
1
2,634
211
227
449
1,767
7,470
479
433
119
9,123
25
163
96,841
38
0
31
372
0
7.
01
0
05
05
01
01
0
0
0
01
01
16
0
0
0
04
0
0
01
0
01
0
01
02
03
13
02
02
0
05
0
0
12
0
0
0
01
0
Aircraft
Emissions
T/Yr
34
264
64
134
479
702
702
142
200
60
246
440
134
190
154
32
21
164
358
31
1,366
272
262
68
24
663
57
12
165
107
191
13
1,890
42
9
135
188
0
7.
0
0
0
0
0
0
01
0
0
0
0
01
01
02
0
0
0
0
0
0
0
0
01
0
0
01
0
0
0
0
01
0
0
0
0
01
01
0
Light-Duty
Highway
Vehicle
Emissions
T/Yr
18,762
22,470
18,372
15,260
15,284
41,827
30,686
15,594
29,157
20,209
29,491
13,315
5,008
4,378
11,840
10,492
6,339
9,036
20,280
9,897
30,791
10,755
8,021
6,841
8,221
14,533
6,028
12,199
13,626
17,463
9,179
9,988
84,110
12,583
2,399
7,042
11,193
0
7.
37
11
40
11
12
21
31
44
29
19
18
19
19
35
25
33
38
42
30
44
07
19
32
30
15
26
27
51
28
10
47
29
10
33
32
32
41
0
Heavy-Duty
Highway
Vehicle
Emissions
T/Yr
4,092
5,562
7,332
6,062
7,057
13,458
13,690
6,480
9,642
7,814
11,271
8,665
2,524
2,058
6,432
4,590
2,718
3,627
9,393
3,872
16,282
8,389
3,773
2,841
3,976
7,700
2,597
4,391
4,458
5,595
2,902
3,394
29,088
3,729
856
2,038
3,245
0
%
08
03
16
04
05
07
14
18
10
07
07
12
10
17
14
14
16
17
14
17
04
15
15
12
07
14
11
18
09
03
15
10
04
10
11
09
12
0
to
-------
Table B-l (Continued)
AQCR
Number
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
Grand
Total
Emissions
T/Yr
7,740
19,343
23,960
159,255
29,653
9,561
39,643
188,215
136,504
103,084
217,687
322,845
128,919
101,698
62,414
20,620
105,062
72,178
8,927
167,529
41,205
31,330
35,941
45,057
102,381
83,868
56,228
113,819
22,661
14,918
26,882
14,422
25,616
24,805
86,230
12,368
17,096
4,391
%
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Total
Area Source
Emissions
T/Yr
5,362
12,384
17,106
89,519
7,583
7,691
33,056
128,001
85,328
62,969
125,964
193,628
35,840
78,031
35,440
19,406
83,391
31,987
8,179
96,662
34,293
28,254
20,492
43,176
60,542
45,012
28,449
49,682
15,054
14,504
21,936
12,113
19,332
15,266
76,000
11,451
10,476
3,861
%
69
64
71
56
26
80
83
68
63
61
58
60
28
77
57
94
79
44
92
58
83
90
57.
96
59
54
51
44
66
97
82
84
75
62
88
93
61
88
Total
Point Source
Emissions
T/Yr
2,378
6,959
6,854
69,737
22,070
1,870
6,588
60,214
51,176
40,114
91,723
129,217
93,079
23,667
26,974
1,214
21,671
40,192
748
70,867
6,912
3,075
15,449
1,881
41,840
38,855
27,779
64,136
7,607
414
4,946
2,310
6,285
9,539
10,230
916
6,620
530
1,
31
36
29
44
74
20
17
32
37
39
42
40
72
23
43
06
21
56
08
42
17
10
43
04
41
46
49
56
34
03
18
16
25
38
12
07
39
12
External
Combustion
Area Source
Emissions
T/Yr
261
619
843
6,276
264
1,870
8,934
33,624
15,313
10,110
10,792
21,664
3,363
7,012
2,696
1,392
6,564
2,565
1,089
15,362
2,054
2,905
1,967
3,650
2,725
3,533
2,800
4,520
2,092
1,405
2,622
1,155
4,531
1,565
3,528
250
557
483
%
03
03
04
04
01
20
23
18
11
10
05
07
03
07
04
07
06
02
12
09
05
09
05
08
03
04
05
04
09
09
10
08
18
06
04
02
03
11
Point Source
Emissions
From Electric
Power
Generation
T/Yr
65
2,085
5,847
29,145
21,267
0
2,046
51,996
46,820
34,479
0
0
18,008
0
451
294
18,189
26,098
0
57,888
863
2,217
6,452
0
36,258
13,398
13 , 702
57,058
4,251
0
0
2,124
1,849
7,961
4,370
0
4,259
176
%
01
11
24
18
72
0
05
28
34
33
0
0
14
0
01
01
17
25
0
35
02
07
18
0
35
16
24
50
19
0
0
15
07
32
05
0
25
04
Nonelectric
Generation
Point Source
External
Combustion
Emissions
T/Yr
386
4,866
666
10,469
793
1,691
3,716
7,585
3,560
4,415
90, 279
123,777
71,553
21,303
19,690
920
3,458
13,452
748
6,500
6,040
849
3,305
1,481
5,447
20,299
487
1,337
864
90
3,901
165
4,216
1,566
4,025
916
20
235
%
05
25
03
06
03
18
09
04
03
04
41
38
55
21
32
04
03
19
08
04
15
03
09
03
05
24
0
01
04
0
15
01
16
06
05
07
0
05
Point Source
Industrial
Process
Emissions
T/Yr
1,927
0
116
30,106
10
0
0
7
57
50
1,315
4,432
3,518
2,160
6,808
0
21
616
0
6,267
0
9
5,413
182
133
5,137
13,495
5,692
2,491
324
952
15
100
5
1,816
0
1
0
°l.
25
0
0
19
0
0
0
0
0
0
01
01
03
02
11
0
0
01
0
04
0
0
15
0
0
06
24
05
11
02
04
0
0
0
02
0
0
0
Aircraft
Emissions
T/Yr
13
31
21
864
410
10
52
1,748
734
296
493
1,643
169
459
272
22
399
182
108
1,209
55
28
72
273
330
108
78
269
171
210
84
37
75
181
158
228
230
10
%
0
0
0
01
01
0
0
01
01
0
0
01
0
0
0
0
0
0
01
01
0
0
0
01
0
0
0
0
01
01
0
0
0
0
0
02
01
0
Light-Duty
Highway
Vehicle
Emissions
T/Yr
3,515
7,858
10,977
52,275
4,589
4,088
16,874
62,961
48,628
37,645
74,857
109,714
19,303
44,281
21,141
9,708
38,964
15,803
2,983
43,947
16,023
12,539
9,490
23,705
30,335
18,774
12,512
22,418
5,053
4,808
7,614
4,535
5,459
5,533
29,399
5,398
5,189
2,447
%
45
41
46
33
15
43
43
33
36
37
34
34
15
44
34
47
37
22
33
26
39
40
26
53
30
22
22
20
22
32
28
31
21
22
34
44
30
56
Heavy -Duty
Highway
Vehicle
Emissions
T/Yr
677
1,645
2,123
12,752
931
868
3,556
15,236
10,969
7,850
16,443
28,413
5,451
10,770
4,637
2,975
12,677
5,295
1,649
17,011
4,855
3,695
3,623
7,361
13,525
8,418
5,784
10,247
2,154
2,397
3,958
1,727
2,517
3,751
16,494
786
1,585
487
%
09
09
09
08
03
09
09
08
08
08
08
09
04
11
07
14
12
07
18
10
12
12
10
16
13
10
10
09
10
16
15
12
10
15
19
06
09
11
w
-------
Table B-l (Continued)
AQCR
Number
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
Grand
Total
Emissions
T/Yr
60,596
146,603
33,081
42,789
8,913
27,993
5,536
7,742
85,833
34,157
118,325
146,388
78,694
35,706
65,113
70,599
91,118
122,823
29,463
37,302
70,630
41,496
79,017
75,774
275,367
32,220
65,693
51,614
155,594
110,030
19,792
291,589
23,106
82,997
77,965
17,059
87,226
15,134
7,
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Total
Area Source
Emissions
T/Yr
36,187
97,844
21,665
33,306
7,136
16,272
5,377
6,808
48,644
28,143
44,457
72,870
47,226
21,981
26,490
26,149
52,441
60,215
23,282
32,301
43,842
24,345
52,930
55,479
160,283
30,826
59,657
41,126
87,556
26,482
18,568
30,200
14,874
17,898
62,383
11,646
54,091
11,671
%
60
67
65
78
80
58
97
88
57
82
38
50
60
62
41
37
58
49
79
87
62
59
67
73
58
96
91
80
56
24
94
10
64
22
80
68
62
77
Total
Point Source
Emissions
T/Yr
24,409
48,759
11,417
9,483
1,777
11,721
160
934
37,190
6,015
73,868
73,518
31,468
13,725
38,623
44,450
38,676
62,608
6,181
5,002
26,787
17,151
26,087
20,295
115,084
1,394
6,036
10,488
68,038
83,548
1,224
261,388
8,232
65,099
15,582
5,413
33,135
3,462
7.
40
33
35
22
20
42
03
12
43
18
62
50
40
38
59
63
42
51
21
13
38
41
33
27
42
04
09
20
44
76
06
90
36
78
20
32
38
23
External
Combustion
Area Source
Emissions
T/Yr
3,732
13,123
2,493
2,161
365
918
189
424
7,084
3,039
5,637
8,859
9,674
2,170
3,558
1,684
2,409
2,934
631
1,224
1,020
969
7,267
4,273
16,063
2,169
5,249
2,389
11,540
7,257
1,337
3,898
784
1,303
4,281
1,117
6,287
458
%
06
09
08
05
04
03
03
05
08
09
05
06
12
06
05
02
03
02
02
03
01
02
09
06
06
07
08
05
07
07
07
01
03
02
05
07
07
03
Point Source
Emissions
From Electric
Power
Generation
T/Yr
22,675
39,592
6,870
7,752
141
4,558
0
0
28,239
166
49,438
30,944
22,258
9,862
34,504
42,446
32,255
53,920
117
3,085
16,466
7,922
23,708
16,353
84,829
386
540
1,008
52,858
79,589
426
182,621
0
62,823
14,503
1,686
25,855
3,147
7.
37
27
21
18
02
16
0
0
33
0
42
21
28
28
53
60
35
44
0
08
23
19
30
22
31
01
01
02
34
72
02
63
0
76
19
10
30
21
Nonelectric
Generation
Point Source
External
Combustion
Emissions
T/Yr
1,270
7,132
301
761
1,617
6,248
149
912
8,817
5,828
24,153
9,040
9,089
3,802
3,048
1,993
5,736
8,429
4,959
1,875
8,778
9,209
1,962
2,418
27,827
988
5,315
5,274
14,964
3,889
798
68,806
8,220
1,365
975
885
2,464
9
%
02
05
01
02
18
22
03
12
10
18
20
06
12
11
05
03
06
07
17
05
12
22
02
03
10
03
08
10
10
04
04
24
36
02
01
05
03
0
Point Source
Industrial
Process
Emissions
T/Yr
464
2,033
4,234
955
0
914
0
2
126
20
264
33,528
104
55
1,068
7
219
249
1,040
34
1,525
14
416
1,127
2,163
20
9
4,205
133
2
0
9,923
12
911
104
2,841
4,816
306
%
01
01
13
02
0
03
0
0
0
0
0
23
0
0
02
0
0
0
04
0
02
0
01
01
01
0
0
08
0
0
0
03
0
01
0
17
06
02
Aircraft
Emissions
T/Yr
290
497
473
749
6
241
3
48
626
354
394
466
660
195
118
48
312
530
15
869
877
116
406
629
1,279
93
748
50
221
101
31
52
15
19
596
205
420
44
7.
0
0
01
02
0
01
0
01
01
01
0
0
01
01
0
0
0
0
0
02
01
0
01
01
0
0
01
0
0
0
0
0
0
0
01
01
0
0
Light-Duty
Highway
Vehicle
Emissions
T/Yr
12,930
49,676
8,374
14,548
4,670
7,667
3,508
3,288
29,849
16,921
27,912
46,269
26,568
14,792
16,957
11,873
25,412
30,569
6,009
15,101
13,208
8,789
15,536
30,758
85,615
17,195
31,975
22,682
44,711
9,096
10,333
13,740
8,682
10,302
28,650
4,098
21,062
4,480
%
21
34
25
34
52
27
63
42
35
50
24
32
34
41
26
17
28
25
20
40
19
21
20
41
31
53
49
44
29
08
52
05
38
12
37
24
24
30
Heavy-Duty
Highway
Vehicle
Emissions
T/Yr
2,518
16,884
3,517
5,391
752
2,762
704
1,210
4,910
4,136
4,543
7,045
4,781
2,212
2,604
5,246
11,057
12,626
2,662
6,784
6,080
10,221
10,663
8,517
26,085
ft, 277
9,357
5,359
14,206
2,646
2,510
4,113
2,055
2,503
19,603
3,402
16,403
3,210
7.
04
12
11
13
08
10
13
16
06
12
04
05
06
06
04
07
12
10
09
18
09
25
13
11
09
13
14
10
09
02
13
01
09
03
25
20
19
21
w
00
-------
Table B-l (Continued)
AQCR
Number
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
Grand
Total
Emissions
T/Yr
43,539
33,592
18,237
17,079
10,049
119,725
32,111
88,682
172,239
471,875
12,958
48,567
50,029
27,427
58,202
13,603
20,425
11,950
38,028
276,237
168,423
39,839
84,144
136,589
131,803
38,630
287,478
273,929
392,636
89,309
162,937
24,292
90,845
15,998
44,109
87,198
36,671
93,243
7.
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Total
Area Source
Emissions
T/Yr
22,364
19,889
12,389
13,905
5,250
91,412
21,890
56,778
65,911
134,923
10,582
17,442
21,085
17,977
44,559
11,213
9,637
9,432
36,946
106,072
67,654
36,969
42,105
52,182
72,841
23,641
39,443
216,520
160,988
67,091
30,866
20,043
63,468
15,445
37,342
51,175
28,199
38,706
%
51
59
68
81
52
76
68
64
38
29
82
36
42
65
76
82
47
78
97
38
40
92
50
38
55
61
13
79
41
75
19
83
70
97
85
58
76
41
Total
Point Source
Emissions
T/Yr
21,175
13,703
5,848
3,174
4,799
28,313
10,221
31,904
106,327
336,952
2,376
31,125
28,943
9,449
13,643
2,390
10,788
2,517
1,082
170,165
100,769
2,870
42,038
84,406
58,961
14,988
248,035
57,409
231,648
22,218
132,071
4,249
27,386
554
6,768
36,023
8,472
54,538
7.
49
41
32
19
48
24
32
36
62
71
18
64
58
35
24
18
53
22
03
62
60
08
50
62
45
39
87
21
59
25
81
18
30
04
15
42
24
59
External
Combustion
Area Source
Emissions
T/Yr
1,109
705
463
1,028
512
8,477
1,675
7,195
8,250
20,107
337
860
1,199
470
1,380
421
233
408
1,552
2,083
1,036
628
1,958
2,839
3,873
1,222
2,312
20,079
20,509
4,793
1,550
1,745
15,035
1,273
2,697
3,484
1,598
3,076
7.
03
02
03
06
05
07
05
08
05
04
03
02
02
01
02
03
01
03
04
0
0
01
02
02
02
03
0
07
05
05
0
17
16
03
06
03
04
03
Point Source
Emissions
From Electric
Power
Generation
T/Yr
18,718
11,680
0
93
72
675
500
23,427
100,478
301,438
0
24,886
27,266
5,304
8,590
748
5,972
1,271
425
128,691
86,383
0
26,202
12,479
55,785
8,509
26,683
41,147
71,006
13,397
8,663
3,482
12,492
0
813
13,974
6,162
29,126
7.
43
35
0
01
0
01
02
27
58
64
0
51
55
19
14
05
29
10
01
46
51
0
31
09
42
22
09
15
18
15
05
14
13
0
02
16
16
31
Nonelectric
Generation
Point Source
External
Combustion
Emissions
T/Yr
784
502
5,747
2,531
1,543
16,132
7,984
8,221
5,372
34,023
2,344
5,228
1,494
4,077
5,035
1,554
3,644
181
512
37,177
9,294
1,839
14,844
64,624
999
6,292
211,660
10,053
133,258
7,174
106,879
309
9,210
552
5,614
15,211
2,307
7,383
%
02
01
32
15
15
13
25
09
03
07
18
11
03
15
09
11
18
02
01
13
06
05
18
47
0
16
74
04
34
08
65
01
10
03
13
17
06
08
Point Source
Industrial
Process
Emissions
T/Yr
1,671
1,521
49
376
3,138
11,370
1,503
65
472
1,450
14
1,010
131
68
13
60
1,171
975
5
4,175
4,330
962
992
6,776
1,748
187
9,575
6,160
27,054
1,556
16,515
458
5,615
2
292
6,732
0
18,013
%
04
05
0
02
31
09
05
0
0
0
0
02
0
0
0
0
05
08
0
01
02
02
01
04
01
0
03
02
06
01
10
01
06
0
01
07
0
19
Aircraft
Emissions
T/Yr
37
765
116
49
7
1,474
90
153
484
1,598
216
329
219
16
150
6
217
182
69
576
457
25
573
606
1,422
87
2,191
2,600
1,317
1,504
445
20
882
14
107
1,173
85
355
7.
0
02
01
0
0
01
0
0
0
0
02
01
0
0
0
0
0
01
0
0
0
0
0
0
01
0
0
0
0
01
0
0
0
0
0
01
0
0
Light-Duty
Highway
Vehicle
Emissions
T/Yr
8,819
7,416
5,857
5,731
2,581
43,711
10,495
29,922
33,240
66,208
6,027
9; 106
11,080
10,394
28,426
6,656
5,140
3,660
14,241
63,455
37,933
18,622
19,806
25,713
35,849
9,230
17,058
68,322
63,109
29,055
15,655
9,321
18,785
9,335
21,780
26,354
17,114
21,695
•/.
20
22
32
34
26
37
33
34
19
14
47
19
22
37
48
48
25
30
37
22
22
46
23
18
27
23
05
24
16
32
09
38
20
58
49
30
46
23
Heavy Duty
Highway
Vehicle
Emissions
T/Yr
6,928
5,956
2,628
2,304
1,148
21,149
4,460
9,868
11,556
24,662
1,539
2,891
3,250
2,583
6,296
1,568
1,354
1,698
6,647
17,736
12,050
5,760
8,182
7,153
7,778
3,317
2,991
73,683
19,727
9,144
4,659
3,582
9,393
3,147
5,516
7,846
4,094
6,236
7.
16
18
14
13
11
18
14
11
07
05
12
06
06
09
11
12
07
14
17
06
07
14
10
05
06
09
01
27
05
10
03
15
10
20
13
09
11
07
-------
Table B-l (Concluded)
AQCR
Number
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
Grand
Total
Emissions
T/Yr
75,655
11,732
39,004
182,844
28,213
37,553
8,158
7,657
98,954
174,205
20,057
134,944
81,889
146,760
42,230
35,345
17,742
55,525
93,659
256
15,095
4,567
7.
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Total
Area Source
Emissions
T/Yr
40,128
8,866
30,133
101,524
23,796
9,963
8,140
5,434
20,058
16,936
20,036
59,291
22,463
91,034
37,334
13,619
16,698
26,423
46,572
256
3,247
4,552
%
53
76
77
56
84
27
100
71
20
10
100
44
27
62
88
39
94
48
50
100
22
100
Total
Point Source
Emissions
T/Yr
35,527
2,866
8,871
81,320
4,416
27,590
18
2,223
78,896
157,268
21
75,653
59,426
55,726
4,896
21,726
1,044
29,103
47,087
0
11,847
15
7.
47
24
23
44
16
73
0
29
80
90
0
56
73
38
12
61
06
52
50
0
78
0
External
Combustion
Area Source
Emissions
T/Yr
2,664
495
1,586
9,100
2,418
1,510
931
1,471
7,536
3,975
1,263
458
1,842
10,549
2,868
2,690
3,296
3,531
4,608
0
2
3
7.
03
04
04
05
09
04
11
19
08
02
06
0
02
07
07
08
19
06
05
0
0
0
Point Source
Emissions
From Electric
Power
Generation
T/Yr
7,709
0
1,092
0
0
27,105
0
30
68,719
157,106
0
55,089
4,673
46,030
3,794
19,039
0
21,543
26,988
0
10,739
0
%
10
0
02
0
0
72
0
0
69
90
0
41
02
31
09
54
0
39
29
0
71
0
Nonelectric
Generation
Point Source
External
Combustion
Emissions
T/Yr
21,909
2,443
6,480
11,266
3,389
485
7
407
10,172
162
12
20,270
12,167
6,407
1,079
1,179
458
4,830
9,745
0
634
13
°l.
29
21
17
06
12
01
0
05
10
0
0
15
15
04
03
03
03
09
10
0
04
0
Point Source
Industrial
Process
Emissions
T/Yr
5,830
306
1,181
69,984
1,017
0
0
1,786
0
0
0
114
42,558
2,736
0
1,416
568
2,663
10,288
0
0
0
%
07
02
03
22
04
0
0
23
0
0
0
0
52
02
0
04
03
05
11
0
0
0
Aircraft
Emissions
T/Yr
260
18
308
1,628
263
7
5
31
209
164
14
342
39
633
295
114
124
41
1,756
15
265
1,186
7.
0
0
0
01
01
0
0
0
0
0
0
0
0
0
01
0
01
0
02
05
02
26
Light-Duty
Highway
Vehicle
Emissions
T/Yr
24,792
4,752
15,937
51,149
12,821
5,181
4,312
2,506
7,822
7,882
11,837
26,599
10,685
40,810
16,904
2,621
3,301
7,195
31,676
130
2,240
2,821
7.
32
40
40
28
45
14
53
33
08
05
59
20
13
28
40
07
19
13
34
51
15
62
Heavy-Duty
Highway
Vehicle
Emissions
T/Yr
6,193
1,146
4,016
16,760
3,184
1,557
1,428
675
2,394
2,430
3,780
9,618
3,703
16,343
6,138
1,812
2,093
3,424
5,578
130
737
536
%
08
10
10
09
11
04
18
09
02
01
19
07
05
11
15
05
12
06
06
01
05
12
w
I
-------
Table B-2
POPULATION GROWTH BY AIR QUALITY CONTROL REGION
(1975 to 1982)
AQCR
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Ratio of
1982 to
1975
Population
1.01
1.01
1.02
1.02
1.03
0.98
1.05
0.98
1.11
1.05
1.00
1.17
1.02
1.12
1.03
1.06
1.06
0.97
0.98
1.00
1.03
1.09
1.11
1.07
1.07
1.02
1.07
1.08
1.11
1.03
1.08
1.04
0.93
0.99
1.10
1.03
1.04
0.98
1.01
1.06
1.08
1.05
1.08
1.06
1.06
1.10
1.12
1.07
1.11
AQCR
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
Ratio of
1982 to
1975
Population
1.13
1.07
1.02
1.04
1.07
1.12
1.07
1.01
0.98
1.07
1.01
1.00
0.96
1.00
1.05
1.11
1.05
1.01
1.02
1.05
1.05
1.03
1.07
1.04
1.06
1.05
1.05
1.08
1.06
1.08
1.06
1.07
1.08
1.06
1.05
0.95
1.00
1.03
0.98
0.97
1.05
1.03
0.99
1.08
1.08
0.97
0.94
1.03
1.03
0.95
AQCR
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
Ratio of
1982 to
1975
Population
0.95
1.06
1.02
1.04
1.03
1.05
1.04
1.00
1.03
1.08
1.05
1.08
1.08
1.07
1.06
1.10
1.09
1.05
1.07
1.05
1.07
1.06
1.06
1.05
1.10
1.04
1.01
1.02
1.02
1.01
1.09
0.99
0.98
0.95
1.01
1.08
1.00
0.99
1.02
0.97
0.96
0.99
0.95
1.02
1.03
0.97
1.12
1.18
1.04
1.03
AQCR
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
Ratio of
1982 to
1975
Population
1.03
1.10
1.01
0.95
0.99
0.91
0.92
1.05
1.04
1.12
1.05
1.04
1.06
1.05
1.05
1.02
• 1.06
0.99
1.01
1.00
1.07
0.96
1.12
1.06
1.06
1.09
1.08
1.02
1.06
1.08
0.99
1.08
1.04
1.07
1.05
1.06
0.93
0.99
0.94
1.03
1.00
1.05
1.07
1.01
1.04
1.06
1.01
1.02
1.04
1.05
AQCR
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
Ratio of
1982 to
1975
Population
1.02
1.08
1.04
1.01
0.97
0.96
1.05
1.07
1.03
0.99
0.92
1.04
0.98
1.01
1.12
1.11
1.02
0.98
1.01
1.07
1.06
1.07
1.01
1.04
1.08
1.08
1.04
1.04
1.08
1.01
1.03
0.95
1.04
1.04
1.02
0.95
1.04
1.04
1.05
1.07
1.02
1.03
0.99
B-ll
------- |