EPA-600/2-76-063
March 1976
Environmental Protection Technology Series
SOURCES BY POPULATION
Industrial Environmental Research Ubwatwy
dfiict of Research and Deveipeflt
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development. U.S. Environmental
Protection Agency, have been grouped into five series. These five broad
categories were established to facilitate further development and application of
environmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The five series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
This report has been assigned to the ENVIRONMENTAL PROTECTION
TECHNOLOGY series. This series describes research performed to develop and
demonstrate instrumentation, equipment, and methodology to repair or prevent
environmental degradation from point and non-point sources of pollution. This
work provides the new or improved technology required for the control and
treatment of pollution sources to meet environmental quality standards.
E PA REVIEW NOTICE
This report has been reviewed by the U.S. Environmental
Protection Agency, and approved for publication. Approval
does not signify that the contents necessarily reflect the
views and policy of the Agency, nor does mention of trade
names or commercial products constitute endorsement or
recommendation for use.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/2-76-063
March 1976
POPEX
RANKING AIR POLLUTION SOURCES
BY POPULATION EXPOSURE
by
Lyndon R. Babcock, Jr. and Niren L. Nagda
University of Illinois
Medical Center, P.O. Box 6998
Chicago, Illinois 60680
Grant No. R-802111
ROAPNo. 21ADK-031
Program Element No. 1AB012
EPA Project Officer: C.T. Ripberger
Industrial Environmental Research Laboratory
Office of Energy, Minerals, and Industry
Research Triangle Park, NC 27711
Prepared for
U. S. ENVIRONMENTAL PROTECTION AGENCY
Office of Research and Development
Washington, DC 20460
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© 1976 by Niren L. Nagda
In accordance with the terms of its grant, the grantee has
granted to the Government a royalty-free, nonexclusive,
and irrevocable license throughout the world for Government
purposes to publish, translate, reproduce, deliver, perform,
dispose of, and to authorize others so to do, the copyrighted
material contained herein.
ii
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ACKNOWLEDGEMENTS
The financial support provided by the U. S. Environmental Pro-
tection Agency (EPA grant No. R-802111) is gratefully acknowledged.
I am indebted to Professor Lyndon R. Babcock, Jr., who served as
the thesis advisor, for his guidance, constant encouragement, and
support in this interdisciplinary research. I am, also, grateful to
Drs. Bertram W. Carnow, Ruy V. Lourenco, Alvin L. Miller, Irving F.
Miller, Richard A. Wadden, and Arthur H. Wolff, members of the
examining committee, for their critical comments and helpful sugges-
tions. My thanks to Carl T. Ripberger, the project officer of the
EPA grant, who suggested this interesting research problem.
Robert J. Allen and Sandra Finkelstein reviewed the entire manu-
script and their comments proved extremely valuable. The assistance
of Glenn F. Kerbs in writing and debugging the computer program is
acknowledged. Computational facilities for this research were pro-
vided by the Computer Center, University of Illinois at Chicago Circle
and their assistance is gratefully acknowledged.
My special thanks to Vera L. Donlan and Rosalie Miulli for their
meticulous typing of this dissertation.
I am indebted to my family for their patient understanding.
To all these persons, and many others, my sincere thanks.
NLN
iii
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TABLE OF CONTENTS
CHAPTER
PAGE
LIST OF TABLES viii
LIST OF FIGURES xi
SUMMARY , xiii
I. INTRODUCTION 1
STATEMENT OF THE PROBLEM ....... 1
OBJECTIVES 2
DEFINITIONS 2
JUSTIFICATION AND SIGNIFICANCE 4
APPROACH AND SCOPE 6
FORMAT OF PRESENTATION 7
II. AIR QUALITY MANAGEMENT SYSTEM 9
DEFINITION OF A SYSTEM FOR AIR QUALITY MANAGEMENT. . . 9
*. '
UNCERTAINTIES IN THE AIR QUALITY MANAGEMENT SYSTEM . . 12
> i i
III. MODELING , 16
INTRODUCTION 16
QUANTITATION OF UNCERTAINTIES 17
RATIONALE 25
SELECTION OF PARAMETERS AND DESCRIPTION 28
FLOW DIAGRAM 35
DEVELOPMENT OF SUBMODELS 38
IV
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IV. DISPERSION SUBMODEL 40
INTRODUCTION 40
DEVELOPMENT '. 43
V. POPULATION SUBMODEL 61
INTRODUCTION 61
DEVELOPMENT. , 61
VI. HEALTH-EFFECTS SUBMODEL 66
INTRODUCTION 66
DEVELOPMENT 67
VII. COMPUTER MODELS AND INPUT DATA 81
COMPUTER MODEL: POPEX 81
COMPUTER MODELS: MASS INDEX AND PINDEX 88
INPUT DATA 88
x
VIII. RESULTS OF THE POPEX MODEL 92
FORMAT OF RESULTS 92
RESULTS 129
IX. SENSITIVITY ANALYSIS OF THE POPEX MODEL 146
METHOD 146
RESULTS. . 148
DISCUSSION 151
X. IMPLICATIONS OF THE METHODOLOGY 154
APPROACH 154
IMPLICATIONS 175
LIMITATIONS OF THE POPEX MODEL 176
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FUTURE WORK 177
XI. CONCLUSIONS ....... 179
LIST OF REFERENCES 182
APPENDIX A: ASSESSMENT OF EXISTING STUDIES OF HEALTH
EFFECTS OF AIR POLLUTION 187
SUMMARY 187
INTRODUCTION 188
EXPERIMENTAL STUDIES (A3-A11) 195
EPIDEMIOLOGICAL STUDIES - GROUP 1 - CORRELATION
STUDIES (A16-A20) 210
EPIDEMIOLOGICAL STUDIES - GROUP 2 - CROSS-SECTIONAL
STUDIES (A21-A25) 213
EPIDEMIOLOGICAL STUDIES - GROUP 3 - LONGITUDINAL
STUDIES (A26-A31) 217
COMMENTS 219
ASSESSMENT OF HEALTHS-EFFECT STUDIES 230
CONCLUSIONS 233
LIST OF REFERENCES FOR APPENDIX A 236
APPENDIX B: LISTING OF THE COMPUTER PROGRAM 241
APPENDIX C: LISTING OF THE SOURCE-CATEGORY NUMBERS AND
THE SOURCE CLASSIFICATION CODES.(SCC) 264
APPENDIX D: EMISSIONS DATA FOR SOURCES OF AIR POLLUTION
IN THE CHICAGO AQCR 293
vi
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APPENDIX E: MAXIMUM POSSIBLE CHANGE IN TWO SETS OF
POPEX VALUES 325
VITA 327
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LIST OF TABLES
TABLE PAGE
I. PARAMETERS FOR EXPOSURE MODELING 26
II. COMPARISON OF UNITED STATES AND CHICAGO AQCR
EMISSIONS 32
III. DEMOGRAPHIC DATA FOR CHICAGO AQCR (27) 36
IV. ANNUAL RESULTANT WINDSPEEDS AND DIRECTIONS
FOR CHICAGO 45
V. EQUATIONS FOR ANGLE 0 IN THE DISPERSION SUBMODEL . . 59
VI. AIR QUALITY STANDARDS AND TOLERANCE FACTORS
(IN pg/m3) 69
VII. DERIVATION OF TOLERANCE FACTORS 75
VIII. EXPLANATIONS OF VARIABLES USED IN THE COMPUTER
PROGRAM 82
IX. EMISSIONS DATA FOR COUNTIES IN THE CHICAGO AQCR IN
TONS/YEAR OBTAINED FROM APPENDIX D . . . 90
t
X. EMISSIONS AND RESULTS OF MASS INDEX, PINDEX AND
POPEX FOR EACH OF ffHE SOURCE-CATEGORIES
IN THE CHICAGO AQCR ' 93
)
XI. CHICAGO AQCR SOURCE-CATEGORIES IN THE DECREASING
ORDER OF POPEX 122
XII. ASSIGNMENT OF RANKS BASED ON PERCENT CONTRIBUTIONS
OF EACH OF THE SOURCE CATEGORIES TO POPEX, PINDEX
AND MASS INDEX 129
XIII. POPEX - RANK-GROUPS 130
XIV. SOURCE-CATEGORIES IN POPEX-RANK-GROUP ONE 133
XV. SUMMARY TABLE FOR POINT SOURCES IN POPEX-RANK-
GROUP ONE 136
Vlll
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XVI. SOURCE-CATEGORIES IN POPEX-RANK-GROUP TWO 144
XVII. RESULTS OF THE SENSITIVITY ANALYSIS 149
XVIII. INDICES, PI/MI, PO/PI AND SOURCE LOCATIONS FOR
SOURCE CATEGORIES IN CHIAGO AQCR ......... 157
XIX. POPULATION DENSITIES AND SLOPES OF PO/PI VERSUS STACK
HEIGHTS FOR SIX COUNTIES 173
APPENDIX A
A-I. LUNG VOLUMES, CAPACITIES AND PULMONARY FUNCTION
MEASUREMENTS: NOMENCLATURE AND
DEFINITIONS (Al) 190
A-II. CRITERIA FOR EVALUATION OF OBSTRUCTION
PULMONARY DISEASES 193
A-III. THE GROUPING OF HEALTH-EFFECT STUDIES 195
A-IV. SUMMARY OF THE EXPERIMENTAL STUDIES 196
A-V. CHANGES IN LEVEL OF SIGNIFICANCE DUE TO A CHANGE IN
DURATION OF EXPOSURES OF SMOKERS AND NONSMOKERS
TO 0.37 PPM OZONE (A6) 203
i
A-VI. EFFECT OF OZONE AND EXERCISE ON THE PULMONARY
FUNCTION OF MALE ADULTS 206
s
A-VII. SEQUENTIAL EXPOSURE OF OZONE, NITROGEN DIOXIDE
AND CARBON MONOXIDE TO ADULT MALES* .' 208
A-VIII. EPIDEMIOLOGICAL STUDIES: GROUP 1 - CORRELATION
STUDIES .' 211
A-IX. EPIDEMIOLOGICAL STUDIES: GROUP 2 - CROSS-
SECTIONAL STUDIES 215
A-X. EPIDEMIOLOGICAL STUDIES: GROUP 3 - LONGITUDINAL
STUDIES 218
A-XI. SOME OF THE ACCEPTABLE METHODS FOR MONITORING OF
GASEOUS AIR POLLUTANTS 222
A-XII. DISTRIBUTION OF THE USE OF PULMONARY FUNCTION
TESTS IN THE STUDIES REVIEWED 224
IX
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A-XIII. PROPORTION OF HYPERACTIVE POPULATIONS IN SELECT
EXPERIMENTAL AND EPIDEMIOLOGICAL
STUDIES 229
A-XIV. RESULTS OF ASSESSMENT OF THE HEALTH-EFFECT
STUDIES 232
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LIST OF FIGURES
FIGURE PAGE
1. A system for air quality management 10
2. Representation of relative uncertainty in
processes and phenomena 19
3. Representation of relative uncertainty in
data bases 22
4. Representation of relative extent of knowledge
of processes, phenomena and data bases
associated with the air quality
management system 24
5. Map of Chicago air quality control region
(AQCR number 67, Illinois-Indiana) 31
6. Popex flow diagram 37
7. Plume model 42
8. Airport locations in Chicago AQCR for wind data ... 46
9. Wind roses for different locations in Chicago
AQCR for June 5, 1975 (9 am to 9 pm) 48
10. Wind roses for different locations in Chicago
AQCR for June 7, 1975 (9 am to 9 pm) 49
11. Wind roses for different locations in Chicago
AQCR for July 29, 1975 (9 am to 9 pm) 50
12. Wind roses for different locations in Chicago
AQCR for July 27, 1975 (6 am to 9 pm) 51
13. Wind directions at three-hour intervals for
different locations in Chicago AQCR
on July 27, 1975 52
14. Pollutant trajectory in a lake breeze,
adapted from (32) 54
XI
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15. Wind rose data for Dresden nuclear power
station of Commonwealth Edison
Company, 1972 (33) 55
16. Flow diagram: development of dispersion
submodel 58
17. Flow diagram: development of population
submodel 63
18. Sensitivity analysis and improvement of
population submodel 65
19. Concentration versus averaging time for
sulfur dioxide 71
20. Standards and tolerance factors for
sulfur dioxide 73
21. Flow diagram of popex computer model 87
22. Locations of the centers of counties in the
Chicago AQCR and their x and y
coordinates 91
23. Indices and variables ; . . . . 155
24. Plots of stack heights versus PO/PI for
different counties 172
25. Relationships of PO/PI versus population
density for different stack heights 174
APPENDIX A
A-l. Dose-response curve for two hours of exposure
to ozone for adults 200
A-2. Effect of combination of cumulative exposures
and duration of exposures on four "reactive"
adult males (A8) 202
A-3. Dose-response curve for ozone: effect of
durations of exposures 204
A-4. Dose-response curves for adult males for
six-hours of exposure to SO2 209
A-5. Dose-response curve of nitrogen dioxide for
children of age eleven years 214
xii
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SUMMARY
The goal of this research was to develop quantitative models for
relating emissions of air pollutants to their effects on people and
to use the methodology for a determination of the relative importance
of sources of air pollution.
The quantitative methodology for the ranking of sources devel-
oped in this project includes considerations of the dispersion of air
pollutants, exposure of people, and the subsequent health effects.
The computer model, called popex, consists of three submodels: dis-
persion, population exposure, and health effects. Optimal sophisti-
cation and balance of details among the submodels were emphasized in
this integrative computer model.
The popex model was applied to sources of air pollution in the
Chicago Air Quality Control Region. The results show that seventeen
out of a total of 227 categories of sources contribute nearly 80
percent to the total air-pollution-population-effect problem. These
seventeen categories include commonly recognized large sources, such
as automobiles, large utility and industrial boilers, as well as less-
recognized categories, such as solvent evaporation from industrial
operations involving surface coatings.
A sensitivity analysis of the popex model revealed that the re-
sults of the popex model are most sensitive to parameters related to
health effects. Other parameters, including the ones related to the
xiii
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dispersion of air pollutants, were found to have a lesser influence
on the outcome of the model. Past studies related to health-effects
of air pollution, specifically studies in which health-effects were
characterized by the pulmonary function tests, were reviewed and ana-
lyzed for possible improvements in the modeling of health effects.
Finally, based on the methodology developed in this project, a
simpler method for evaluating relative impacts of a smaller number
of sources is proposed.
xiv
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CHAPTER I
INTRODUCTION /
STATEMENT OF THE PROBLEM
Air pollution causes many deleterious effects, the most important
of which is its adverse impact on human health. There are numerous
sources of air pollution, and in order to reduce health risks to the
exposed human population, emissions of air pollutants from these sources
have to be controlled.
For an efficient strategy for control of air pollutant emissions,
a system for quantitatively relating emissions to their health effects
is necessary. Air quality and its health-effect implications are ex-
tremely complex functions of many variables, and such a quantitative
methodology, despite the obvious need, does not exist. The significant
areas of difficulty which underscore the lack of availability of quanti-
tative methodology include: (a) the duration of varying levels of con-
centration of air pollutants to which people are exposed cannot be
precisely estimated, and (b) significant uncertainty exists in the
quantification of the health effects of exposure to air pollution.
In this research some of these difficulties are addressed.
Modeling of air pollution-population exposures and evaluation of their
health effects for prioritization of sources of air pollution comprises
this dissertation.
1
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OBJECTIVES
The aim of this research was to develop and to use a "first genera-
tion" quantitative methodology for determination of the relative impor-
tance of sources of air pollution. The objectives of this study were
as follows:
1. Construct a mathematical model which relates source emissions
to population-pollutant exposures. This computerized model should in-
clude air pollution emission, meteorologic, spatial, population, and
health-effect parameters.
2. Use this model to assign rank-priority to sources of air
pollution.
3. Perform sensitivity analysis or analyze the model for sensiti-
vity of its results to changes in input parameters. Study in-depth the
sensitive parameters thus identified.
DEFINITIONS
Air Pollution
Air pollution is defined as the presence in the atmosphere of one
or more contaminants (dust, fumes, gas, mist, odor, smoke, or vapor) in
quantities, of characteristics, and of duration such as to be injurious
to human, plant or animal life, or to property, or which unreasonably
interferes with the comfortable enjoyment of life and property (1).
The following air pollutants are included in this study: particulate
matter, PM; sulfur dioxide, SO2; nitrogen oxides, NOX; hydrocarbons,
HC; carbon monoxide, CO; and oxidants, Ox. The first five of these are
-------
considered as primary pollutants or the pollutants which are directly
emitted by sources of air pollution. Secondary pollutants, like oxi-
dants, are formed within the atmosphere from primary pollutants and
other substances through a set of complex chemical reactions.
There are numerous sources of air pollution. Both point sources
(which are rather large readily identifiable sources, such as power
plants, petroleum refineries, etc.) and area sources (which represent
collectively a large number of smaller sources distributed over a well-
defined area, such as residential heating) are included. Air pollutants
emitted by these sources diffuse and decay in the atmosphere. The
diffusion process is dependent on meteorology and topography of the
region. Air quality is the result of this diffusion process. The
diffusion of air pollutants can be simulated to a limited extent by
mathematical modeling.
Health Effects
The effects of air pollution on personal or community health could
range from eye irritation to acute illness or death (2). Basically,
two approaches are used in studying health effects of air pollutants:
human and animal experimental studies and epidemiological studies. The
duration of exposures involved in experimental studies with humans are
generally less than a few days at a time. Epidemiological studies
enable evaluation of longer-term effects. The design of the air pollu-
tion epidemiologic studies is difficult; many causative factors could
simultaneously super-impose their impact on end-effects which are simi-
lar to the effects of air pollutants. Researchers in the past few
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4
years have been able to "isolate" the effects of air pollution on health
with varying degrees of success. Their studies have shown that the
level of effects depends on many factors including concentrations of
the air pollutants, durations of exposures and susceptibility of the
host.
Modeling
Mathematical models consist of sets of mathematical expressions
arranged in a logical format. To obtain a predesignated output, various
predefined inputs are fed into the model at various stages. The mathe-
matical expressions in the model could be in an analytical or empirical
form, and they are designed to simulate the process being modeled. The
use of modeling enables one to predict results of a complex process with
less time and effort. Modeling also has two other distinct advantages.
First, modeling provides an opportunity to see the interactions between
directly unrelated parameters. This allows, one to judge the importance
of results of variations in one parameter against others. A second,
and generally less well recognized advantage of modeling, is that it
shows explicitly the "missing links" in the whole system being modeled.
JUSTIFICATION AND SIGNIFICANCE
Attempts have been made in the past to model segments of the air
quality management system, such as modeling of the dispersion of pol-
lutants in the atmosphere, modeling of atmospheric reactions related to
pollutants, etc. There also have been attempts to model a large part
of the "overall" air pollution system. .These models have been of
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5
significant use for the understanding of air pollution. However, gene-
rally, these models have considered artificially structured situations
instead of actual ones. In some instances, prior studies have consid-
ered either real geographic and topographic data for atmospheric dis-
persion, or actual population data for estimating population exposures.
Models which use both real dispersion and population data are not avail-
able. Similarly, models of health effects have been conspicuously ab-
sent from the overall models of air pollution.
This research project was aimed at the construction of a quantita-
tive methodology for determining the relative importance of various
sources of air pollution. While many simplifying assumptions were made,
actual data on sources and population were used. This project represents
a "first generation" attempt to integrate diverse factors. The results
of the methodology and the model presented here are in the form of a
ranking of relative importance of categories of sources of air pollu-
/
tion. These rankings could be directly used in decision making processes
for determining the degree of control of emissions as well as in devel-
oping priorities in research and development related to the technology
of control systems.
It must be pointed out that at least two different groups (3,4)
have performed research in this area of prioritization of sources of
air pollution. One study (3) was restricted to an evaluation of sources
\ (
of nitrogen oxides. Their evaluation was based on the sensitivity of
changes in ambient air quality to changes in the nitrogen oxides
emissions. An important limitation of the study was that the
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6
consideration of atmospheric transformations of nitrogen oxides to oxi-
dants was not included and thus the results of the study are of a limited
value.
Another more useful study performed by Monsanto Research Corporation
(4) evaluates industrial sources of air pollution. On this study in addi-
tion to the five primary pollutants mentioned earlier, other toxic indus-
trial pollutants were considered. Atmospheric transformations of pollu-
tants were not considered. Similarly, only nonmetallurgical industrial
sources were evaluated.
In the present study all known sources of the five pollutants: PM,
SO?, NO , CO, HC are evaluated. Considerations of formation of oxidants
£ X
are also included. The approach and the scope of this study are briefly
described below.
APPROACH AND SCOPE
An attempt is made in this dissertation to combine numerous factors
all related to air pollution and its effectsfor the development of a
quantitative methodology which enables the evaluation of the relative
importance of different sources of air pollution. The approach that was
used toward achieving this goal was that of systems analysis. Briefly,
the steps included in this approach were (a) defining the system, (b)
analysis and simplification of the technical information relevant to the
system as well as to parts of the system, (c) modeling or integration of
this information in a systematic and quantitative manner.
To the extent feasible, reliance was placed on the available data
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7
and information. Where data were not available, approximations and
assumptions were made. Gathering of data through survey or other tech-
niques was not attempted. Statistical methods were used to obtain empi-
rical relationship from complex sets of analytical expressions.
The quantitative system or the model thus developed was applied to
actual conditions. The results were then analyzed and interpreted with
special reference to the simplifications and assumptions used in devel-
oping the model.
FORMAT OF PRESENTATION
A system for air quality management is defined and many uncertain-
ties associated with this system are described in Chapter II. Chapter
III analyzes some of these uncertainties, provides a rationale for
construction of the model and includes a brief description of the popu-
lation-exposure model called "popex". The details on the construction
of various submodels are given in the subsequent three chapters. Chap-
ter VII describes the computer algorithm and the input data.
The results of the popex model in the form of rankings of sources
are given in Chapter VIII. Chapter IX provides sensitivity analysis.
Implications of the popex methodology, limitations of the popex model
arid discussion of future projects are given in Chapter X. The conclu-
sions of this research work are presented in Chapter XI.
A reader whose primary interests are in the actual rankings of
sources of air pollution are referred directly to Chapters VIII and XI.
A reader interested in methodology should first read Chapters II, III,
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8
and VIII to XI and then refer to the three chapters (IV to VI) on
construction of submodels as necessary. Individuals interested in
modeling of health effects are referred to Chapters VI, IX, and to the
Appendix A.
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CHAPTER II
AIR QUALITY MANAGEMENT SYSTEM
The goal of this dissertation research was to develop methodologies
which can assess, in a systematic and quantitative way, the adverse
effects of air pollution and relate them back to individual sources of
air pollution. Thus, a definition of the system and understanding of
uncertainties in this system were considered to be of significant im-
portance. In this chapter, a system for air quality management is de-
fined and uncertainties in this system are discussed.
An all-inclusive system for the management of air quality would
involve many disciplines, such as physical and life sciences;, engineering,
and economics, etc. This system would also include the administrative
and regulatory aspects of management. Such a definition of the system
is, no doubt, too broad for this research. A somewhat narrower defini-
tion, which is more relevant to the goals of this work, is given in the
next section. A brief discussion of uncertainties in the air quality
system is also included later in this chapter.
DEFINITION OF A SYSTEM FOR AIR QUALITY MANAGEMENT
Figure 1 gives a basic idea of different aspects of air quality
management. As shown in Figure 1, emissions from various sources of
i
air pollution, the meteorology of the region, and the chemical reactions
of the pollutants in the atmosphere primarily influence the air quality
9
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SOURCE
EMISSIONS
ANXN
, COSTS
\x\\\\\
\\N\\\
ENFORCEMENT
EMISSION
CONTROLS
ATMDSPHERIC
CHEMISTRY
\\\\\\
\ \ MONITORING
\\V\\\\\
STANDARDS
pollutant pathways
part of the system not considered in this research
Figure 1. A system for air quality management.
METEOROLOGY
AIR QUALITY
RECEPTORS
(PEOPLE)
EFFECTS
(HEALTH)
,
\
DAMAGES
\ \ \ \
v
\
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11
of that region. The air quality at the receptor locations, or the air
i
quality experienced by individuals, depends on many factors. The "loca-
tion" of an individual with reference to distances from various emission
sources is important. This "location" parameter is dynamic in nature
and exposures to pollutants would depend on the length of time spent by
the individual at his residence, place of work, in shopping, and so on.
Other factors, such as differences in indoor and outdoor air quality,
also influence the dosages of exposure to air pollutants. These repeated
,
exposures cause varied effects on the health and well-being of the indivi-
dual. Exposure to air pollutants also cause damage to plants, animals,
and property. Effects other than on human health are not included in
this system but could be added at any time in the future.
The health effects are dependent on the degree and nature of air
pollutant dosages as well as on other factors including age, suscepti-
bility, and work load of the individual. As the box at the bottom of
Figure 1 indicates, these health effects are responsible for "damages".
These health-related damages are not limited to direct consequences of
ill health but would include indirect costs such as decrease in life-
span of an individual, or an increased possibility of a future disease
due to air pollution.
The efforts in the direction of reducing air pollution have been
underway for many years. However, the enactment of the Clean Air Act
Amendments in 1970 has helped to make the process proceed faster and be
better organized. The shaded portion of Figure 1 shows a major part of
the endeavor to reduce air pollution through the monitoring of the air
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12
quality, establishment of standards, and enforcement and maintenance of
the standards. In order to meet the ambient or emission standards, the
air pollution emissions are controlled by installing control devices on
the existing processes, or through process modifications. Another ap-
proach, not shown in Figure 1, would be through better land use policies.
Generally, there is a positive cost associated with most of these mecha-
nisms to reduce air pollution and at every level of control; ideally,
this control cost has to be compared with the negative cost of better
health due to reduction in air pollution. In the remainder of this
dissertation, the shaded part of Figure 1 is excluded and only the
unshaded portion is addressed.
Although the air quality management system was described here in
a very simple way, there are many uncertainties associated with most
of the boxes and arrows depicted on Figure 1.
UNCERTAINTIES IN THE AIR QUALITY MANAGEMENT SYSTEM
Pollutant Transport Mechanisms
Meteorological dispersion models with various levels of sophis-
tication can be employed for the estimation of pollutant concentrations
at receptor sites (5,6). Such models all require some form of calibra-
tion and have to be verified for, complex urban situations. Compounding
the difficulty, the large amounts of prerequisite meaningful meteoro-
logical data are virtually nonexistent.
Interaction of Pollutants
In the atmosphere, pollutants react with other pollutants as well
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13
as with other materials. These reactions could produce more-potent or
less-potent intermediates, leading to particulate matter which is even-
tually removed from the atmosphere, or to innocuous decay end products,
such as carbon dioxide and water. Some systems are understood better
than others. Oxidant formation has been the subject of intensive study
(7,8) but similar work is just beginning to shed light on the mechanisms
involved in the atmospheric conversion of sulfur dioxide (9) and nitro-
gen oxides into possibly more toxic sulfates and nitrates. None of the
? '
systems are understood sufficiently to permit the reliable prediction
of actual atmospheric reaction rates.
Source-Receptor Geometry;
In order to arrive at an estimate of pollutant dosage, source-
receptor geometry must be considered. Residences are not distributed
evenly throughout a region, and inhabitants do not spend all their time
s
near home. Exposures to pollutants during travel in an automobile (10)
could be significantly different from either the air quality at the
starting point or at the destination. Similarly, pedestrians and street-
workers in a downtown business district are exposed to high levels of
air pollution (11). There are also differentials between indoor and out-
door air quality (12), and these are only now increasingly being recog-
nized (13,14). Furthermore, monitoring stations which, of course, can
not adequately represent overall pollutant exposures, often are in a
location which is totally unrepresentative of the air quality of that
region.
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14
Health Effects
Numerous experimental and epidemiologic studies have been performed
on characterization of the health effects of air pollution. Most of
these studies are able to show a qualitative relationship between in-
V
crease in air pollution and increase in adverse effects.
In the experimental studies the effects have been studied at dif-
ferent organizational levels: biochemical, ultrastructural, tissue,
organ, etc. Given the complexity, it is not surprising that there are
numerous uncertainties associated with effects at all levels. Ideally,
it would also be of great value if the concentrations of pollutants
were known at which the normal homeostatic and compensatory mechanisms
are no longer adequate and some very difficult-to-detect (sub-subclinical)
effects are initiated (15). It appears that these types of studies have
been performed by Soviet scientists (16,17), but exact implications of
the Soviet studies, when compared with other studies, remain unclear.
Compounding these difficulties is the fact that exposure to air
pollution is seldom comprised of a single pollutant. The effects of a
combination of pollutants or a pollutant with other environmental stresses
could be synergistic, additive, or in a rare case, even inhibitory. The
uncertainties associated with a single pollutant are magnified when mul-
tiple pollutant exposures, as in the case of ambient air pollution, are
involved.
An even larger number of variables are generally included in epide-
miologic studies. The design of air pollution epidemiologic studies is
difficult. Two of the specific uncertainties related to these studies
-------
15
include difficulty associated with quantification of long-term effects
of pollutants at the levels near the ambient concentration of pollutants
and characterization of^segments of the population which may be hyper-
susceptible to environmental stressors, including air pollutants.
-------
CHAPTER III
MODELING
INTRODUCTION
The aim of this project was to construct a model which relates
source emissions to their effects on people and to use this model to
assign a rank-priority to sources of air pollution. In order to relate
emissions to health effects, intermediate steps of atmospheric trans-
port and atmospheric conversion as well as population-pollution expo-
sure need to be included in the model. Quite often these intermediate
steps or submodels are so large and complex that each qne of the sub-
models may require the full thrust of an investigator's efforts.
Atmospheric dispersion of air pollutants has been a subject of
numerous investigations and the models for dispersion are available
(18,19). Due to the sheer size and complexities of such models, the
application of these existing models for ranking sources is difficult.
Similarly, the exposure model must include diverse phenomena such as
atmospheric dispersion of pollutants and their health effects. For a
model to be useful, the accuracy of one part of the model must be
balanced with the remainder. Simplifications in the complex pollution-
population-effect interactions are also necessary to have a workable
model. Thus, a direct use of existing dispersion models was ruled out
for this project.
16
-------
17
In this chapter, uncertainties mentioned in the previous chapter
are analyzed, the desired optimum degree of complexity of the overall
model is discussed, and the rationale for the selection of parameters
and their data bases for modeling is briefly described. Finally, a
brief description of the model is included and the simplified flow
diagram of the model is explained.
QUANTISATION OF UNCERTAINTIES
This subjective quantitation of uncertainties is based on the
discussion of uncertainties in the preceding chapter and on the writer's
understanding of the air quality management system. It is possible that
different workers could view these uncertainties in different ways de-
pending on their background as well as their biases. However, the
writer feels that even with differing viewpoints the basic qualitative
picture of the quantitative representation of uncertainties described
below, will remain essentially the same.
Two forms of uncertainties are encountered: uncertainty associated
with processes or phenomena and uncertainty in data. An example of the
former is the precise mathematical estimation of concentration of a non-
reacting pollutant, in that the process or mechanism of dispersion has
to be well understood and be mathematically definable. As an example
of the latter, adequate data for various parameters, such as rates of
emission, location of sources, and several meteorological parameters,
are required when a dispersion model is used. Accuracy of estimation
of concentration would then depend on two factors; first, how close
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18
does the mathematical simulation or the model of the process resemble
the actual one, and second, whether qualitatively acceptable and quanti-
tatively sufficient data are available for input into-the model.
s
Uncertainty in Phenomena
The modeling of population-pollutant exposure and health effects
for setting source-control priorities basically requires the knowledge
of concentration of air pollutants at various locations, number of
people exposed along with the levels of concentration to which they are
exposed and the consequent health effects. In other words, three pro-
cesses or phenomena have to be well characterized: dispersion (including
atmospheric conversions), sourcer-receptor geometry, and the dose-res-
ponse relationships of the health effects.
A scale of zero to ten is used to characterize relative uncertainty,
with zero reflecting the least and ten the highest degree of uncertainty.
As mentioned earlier, this quantitation of uncertainties is necessarily
subjective and is attempted only with the goal of achieving a balance of
complexities and sophistication in the different aspects of the model.
Figure 2 ranks the degree of uncertainty related to the processes.
Health effects are rated ten on the uncertainty scale since there are
no generalized dose-response data available for effects at air pollutant
concentrations approaching ambient conditions. On the other hand, dis-
persion of a non-reacting (or very slowly reacting) pollutant from a
single source or multiple sources in flat topographic regions can be
estimated with reasonable accuracy (20). Thus dispersion is rated at
one on the uncertainty scale which implies that there is a finite but
-------
10 I
4J
H
-------
20
quite small uncertainty associated with simple dispersion of the pollu-
tant. The mechanism of oxidant formation is less well established than
dispersion. Models for prediction of formation of oxidant are avail-
able (21). However, the accuracy of estimation is less than that for
estimation of simple dispersion. Oxidant formation is thus ranked at
three. Mechanisms for formation of secondary pollutants such as sul-
fates are not as well understood as for formation of oxidantt,, but
some correlations between sulfates and their precursors are available
(22). Since formation of secondary pollutants other than oxidants can
be estimated to a limited extent, and few mathematical relationships
for health effects are available, formation of secondary pollutants .is
rated at seven, or in between oxidant formation and health effects.
The dynamics of source-receptor geometry poses a unique problem
for uncertainty rating, since a model for source-receptor geometry is
not difficult to visualize and basic data, i.e., population and source
data, for construction of such a model are available. However, little
I
work has been done to develop a generalized model in this area. Thus,
modeling source-receptor geometry is feasible, but since the models are
not available, an uncertainty rating of three is assigned.
Uncertainty in Data
Three major data-bases are required for modeling of pollutant
exposure and health effects: emissions, meteorology, and population
characteristics. Of these three, the data on population are best known.
In the United States, the census of population has been taken every ten
years since 1790 (23). Over the years, methods of taking a census have
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21
been refined and machinery for good statistical quality control has
been established. Thus, among the three data bases, it is by far the
best both in terms of completeness as well as in terms of quality of
the data. Population data-base is assigned the best rating of one on
the uncertainty scale of, again, zero to ten (Figure 3).
The National Emissions Data System (NEDS) of U. S. Environmental
Protection Agency (EPA) has been in operation for the last few years.
\
NEDS systems compiles emission inventories based on information supplied
by local and state air pollution control agencies. Emissions from the
individual sources are estimated based on emission factors (24) for each
of the sources and on operating information. EPA has rated these emis-
sion factors, depending on their accuracy, as A through E. An emission
factor rating of A for a source implies- that the emission factor is
based on measured emissions data, process data, and engineering analy-
sis. Thus, little uncertainty is associated with estimating emissions
for a source which has emission factor rating of A. A rating of E
i '
implies very little data exists for the particular emission factor, and
estimation of emissions based on such a factor is subject to a large
error. Other information such as process weights, load factors, capa-
1 V
cities, etc., required in addition to the emission factors for the esti-
mation of emissions may have some associated inherent errors. Thus,
even though emission data from NEDS represent the best available data
in terms of completeness and quality of data, it will rank poorer than
that of the census of population.
Meteorological data scores poorer on the uncertainty scale,
-------
10
4J
c
-------
23
especially in terms of "quantity" (Figure 3). For many years, the
National Weather Service has maintained a network of'continuously opera-
ting weather stations. Similarly, many of the air quality monitoring
stations also monitor certain meteorological parameters. However, there
are a very limited number of such stations in any single region. Thus,
,-
although good temporal (i.e., time varying) data are available for a
particular site, there is certainly a lack of spatial meteorological
data for predictive dispersion modeling.
Analysis
"Extent of known" for the processes and the data-bases discussed
above can be estimated from the following expression:
1
Extent known «
uncertainty
This expression is used to transform uncertainty ratings in Figures 2
and 3 to "extent known" in Figure 4. From Figure 4 it can be inferred
that even if good data are available on population, considerations of
source-receptor geometry limit the extent to which population data could
be used. Similarly, lack of spatial meteorological data as well as of
photochemical mechanisms governs how precise a dispersion model can be
constructed. Finally, health effects, which are the least known consi-
deration in the model, put a constraint on modeling of all the other
processes as well as the use of the data bases. Thus, an efficient and
useful model could be relatively simple in nature and attain the accu-
racy or validity contained by the uncertainty in health-effects data.
Specific parameters and mathematical relations for the construction
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1.0
o
a
a
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25
of the model are discussed in the following section.
RATIONALE
As discussed in the previous sections, there is a large degree of
uncertainty associated with most of the mathematical or empirical rela-
tionships among the parameters for relating emission to effects. The
underlying rationale in construction was that the relations used in
the models should be only as complex as warranted and undue complexity
should be avoided. Availability of adequate input data was also an
important constraint in modeling.
Selecting an appropriate time-base for the model is important for
the balance of degree of details. Selecting a time-base means to de-
cide whether the model should estimate hourly, daily, weekly, or annual
exposures or whether the model should be dynamic, i.e., time-varying,
in nature. The time-base would depend on availability of data for time-
implicit parameters and empirical relations as well as their projected
use in the model.
Rates of emissions are available only in terms of annual emissions
or in tons per year. Logically, the data on air pollutant emissions
forms a basis for a system or a model for priority-ranking of sources.
Thus, even if data for other parameters, including meteorological, are
available for a much finer time-basis, such as hourly or daily, etc.,
the annual or yearly basis for the model appears to be more practical.
Table I lists some of the many parameters that could be included
in the model. It shows for each of the parameters the type of data
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TABLE I. PARAMETERS FOR EXPOSURE MODELING
Parameter
(1) Desirable form
(2) Availabi- (3) Form used in
lity of (1) the model
(a) Emissions
Sources
Types of pollutants
Rate
Stack height
Plume height
Individual
Five
Amount/hour
Actual
Actual
Yes
Yes
No
Yes
No
Individual
Five
Tons/year
Actual
Zero
(b) Meteorology
Diffusivity
Wind data
In the three orthogonal
directions
Hourly windspeed and
directional data for
several locations
No
No
a a 1 for a single
stability C defined
by Turner (25)
Symmetrical wind rose
(c) Source-Receptor geometry
Population
Source locations
Census tract
x.
coordinates
(d) Atmospheric chemistry related to oxidant formation
Reaction mechanism Detailed mechanism of
\ formation and decay
Rate constants
Hydrocarbon emissions
(e) Health effects
Dose-response
All required rate constants
HC emissions with reactivity
classifications
Generalized dose-response
curves
Yes
Yes
Partial
Partial
No
No
County, ring of
average exposures'2
County centers2
Equimolar NO2 and HC
stochiometric time-
independent relation3
Not used
Total hydrocarbons
Tolerance factors
to
-------
TABLE I. PARAMETERS FOR EXPOSURE MODELING (CONTINUED)
l<3y az are the standard deviations of distribution of pollutant concentrations in a plume.
2See Chapter V on the development of population submodel.
See discussion of photochemical considerations in Chapter VI.
K)
-o
-------
28
that would be desirable for precise modeling as well as whether such
data are commonly available (Column 1 and 2 in Table I). Column 3 of
Table I shows the form of the parameters that were included in the model.
An explanation for selection of parameters follows.
SELECTION OF PARAMETERS AND DESCRIPTION
This population-pollution exposure model is called popex for short.
It includes factors related to source emissions, meteorological disper-
sion, population distribution, and pollutant toxicity. The geographic
area used in the model is the Chicago Air Quality Control Region (AQCR)
but the model could be readily adapted to any other region. Reasons for
the selection of the Chicago AQCR are given later in this chapter.
Emissions
Sources are treated individually in the model. In order to pre-
sent results in terms of priority rankings, the pollution-population-
exposure contributions for these sources are grouped into approapriate
source categories. (Single sources at specific sites are referred to
as "sources", and "source-categories" refer to predetermined categories
* v
of these sources. See Chapter VII for details.) The emission inven-
tory of five pollutants supplied by the National Emissions Data System
(NEDS) of EPA is used. Actual stack height for each of the sources is
used. It would have been desirable to include plume height,' however,
no data for estimation of plume rise were available.
Meteorology
Comprehensive spatial meteorological data are generally unavailable.
-------
29
To circumvent this lack of data, some simplifying assumptions were
made. First, a single windspeed, an annual average, is used for all
sources. Similarly, a symmetric wind rose is assumed. Next, a single
class of stability, c, as defined by Turner (25) is used.
The basis for the assumption of a symmetric wind rose is dis-
cussed in the section on dispersion submodels. Other assumptions,
along with the sensitivities of various meteorological parameters, are
evaluated in Chapter IX.
Source-Receptor Geometry
Ideally each of the source locations and their effects on each of
the population-receptors should be considered. However, due to size
considerations, the computer model would become unmanageable. Some
simplifying assumptions were necessary. In popex, all the sources
have been located at the center of each county and the population is
assumed to be uniformly distributed. This representation implies, as
in reality, that some of the people are located much nearer to sources,
whereas the majority of them are located at some distance away from
sources. The mathematical model which was developed for such a situa-
tion is described in Chapter V.
Photochemistry of Oxidant Formation
The exact mechanism of formation of oxidant is still not known.
More importantly, the emission inventory for one of the precursors of
oxidant, namely reactive hydrocarbons, is not available. In popex a
simple equimolar stochiometric reaction equation is used for estimation
of formation of oxidant.
-------
30
Health Effects
Modeling of health effects requires knowledge of cause-effect
relationships. These empirical relations may be in the form of an
increased' incidence of certain disease as a function of air pollution
dosages or in terms of the effect of air pollution as measured by cer-
tain clinical indicators. No such generalized air pollution-health-
effect relationships were available at the beginning of this project
in September 1973. Air quality standards which are based on health
effects of pollutants can form the basis for health-effect modeling.
Popex uses extrapolated air quality standards or tolerance factors.
The detailed method is given in Chapter VI.
Selection of the AQCR
The United States has been divided into 247 AQCRs by EPA. There
i ;
are many reasons for the selection of the Chicago AQCR for the popex
model (Figure 5). Popex model for the ranking of sources includes con-
siderations of source emissions as well as those of population receptors.
Thus, the AQCR selected for.modeling should not only have sources that
are representative of nationwide air pollutant emissions but also should
include counties which are significantly different from each other in
their population densities.
Emissions.-Emissions from sources in the Chicago AQCR are generally quite
well representative of the nationwide emissions. Table II compares emis-
sion data for the United States and for the Chicago AQCR (26). The emis-
sions are given in terms of percentages of the total for each of the two
cases. There are some differences in the percent emissions of Chicago
-------
31
Me HENRY
LAKE
Elgin
KANE
Aurora O
KENDALL
GRUNDY
DU PAGE
Joliet
WILL
Waukegan
LAKE MICHIGAN
Ol Chicago
COOK
O Kankakee
KANKAKEE
H LAKK
10 20
miles
30
PORTER
Figure 5.
Map of the Chicago air quality control region
(AQCR number 67, Illinois-Indiana).
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TABLE II. COMPARISON OF UNITED STATES AND CHICAGO AQCR EMISSIONS
Emissions
Categories
U.S. as percent of the total
(202, 567,000 tons/year)
Chicago AQCR as percent
of the total (7,477,000
tons/year)
Fuel combustion
External combustion
Residential fuel - area
Electric generation - point
Industrial fuel - area
- point.
Commercial-institutional - area
- point
Internal combustion - point
Electric generation
Industrial fuel
Commercial -institutional
Engine- testing
Industrial process - point
Chemical manufacturing
Food/agriculture
Primary metals
Secondary metals
Mineral products
Petroleum industry
Wood products
Evaporation
Metal fabrication
Leather products
1.1
13.3
1.8-
. 4.7
1.1
0.2
0.03
0.5
0.001
0.001
4.7
0.2
4.7
0.9
2.9
5.4
0.7
1.4
0.003
0.0002
2.7
8.4
3.6
17.4
0.8
0.3
nl1
nl
nl
nl
0.5
0.1
6.3
0.6
2.1
8.7
0.0001
-, -. w
2.3 NJ
0.01
nl
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TABLE II. COMPARISON OF UNITED STATES AND CHICAGO AQCR EMISSIONS (CONTINUED)
Emissions
U.S. as percent of the total Chicago AQCR as percent
(202,567,000 tons/year of the total (7,477,000
Categories tons/year)
Industrial process - point continued
Textile manufacturing 0.004 nl
Inprocess fuel 0.1 0.007
Other/not classified 0.1 0.1
Solid waste disposal
Government - point 0.2 0.4
Residential - area , 2.1 1.4
Commercial-institutional - area 0.2 0.2
- point 0.01 0.1
Industrial - area 0.9 2.8
- point 0.5 0.2
Transportation - area
Land vehicles
Gasoline 47.2 36 .'0
Diese-l fuel 1-.8 - 1.5
Aircraft 1.0 0.5
Vessels 0:4 0.1
Gas handling evaporation loss 0.5 0.4
Miscellaneous - area
Slash burning 0.5 nl
Solvent evaporation loss 0.8 2.5
Total 100.0 100.0
= none listed
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34
AQCR as compared to the nationwide numbers, but, generally, there is a
good agreement in the percent emissions for the same categories. The two
categories that are relatively large by themselves as well as the cate-
gories for which there are large differences are fuel-combustion-indus-
trial-point (U.S., 4.7; Chicago, 17.4) and industrial-process-chemical
manufacturing (U.S., 4.5; Chicago, 0.5). The large difference in the
industrial fuel category is primarily due to an error1 in the emissions
of a single source. After correcting for the error, the percent emis-
sions of the industrial fuel category for Chicago AQCR is 5.3 which is
comparable to 4.7 for the U.S. All the emissions data reported sub-
sequent to Table II and used in this research includes this correction.
It appears that industries involving the manufacture of chemicals
are less in number in the Chicago area. Thus, in this case, the results
of the popex model which is applied to Chicago AQCR data would tend to
underestimate the nationwide importance of emissions from chemical
industries.
Some of the source-categories appearing on national emissions data
such as internal combustion, slash burning, industries involving wood,
leather, and textile products, etc., are virtually nonexistent in the
-'-After examining the detailed emissions data referred to in the section
on input data (Chapter VII), it was found that a single source using
process gas located in Lake County in Indiana had unusually large emis-
sions (about 350 times the emissions of similar sources of equal capa-
cities) . In fact the NOX emissions of this single source were 789,000
tons per year or about 60 percent of the total emissions of 1,348,000
tons per year for the entire Chicago AQCR. This apparent error was
corrected by using average values of emissions of similar sources in
the same county. This correction also agrees with the more recently
9btained emission totals for the eleven counties from NEDS.
-------
35
Chicago area. However, emissions from these categories represent less
than 2 percent of the national emissions on a mass basis. Consequently,
these categories would be relatively unimportant even if they were pre-
sent in the Chicago area.
An additional point in favor of the selection of the Chicago AQCR
was that it was one of the few AQCRs for which nearly complete emissions
data were available at the start of this project in September 1973.
Population.-Counties included in Chicago AQCR range from the densely
populated urban area of Cook County (5753 people/square mile) to the
sparsely populated rural area of Grundy County (61 people/square mile).
Population densities of the remaining nine counties lie between these
two extremes (Table III). Heavily industrialized counties include Cook
and Will in Illinois and .Lake in Indiana. It is interesting to note
that two (Cook and Will) of the three also are almost at the two ex-
tremes of the population density scale.
FLOW DIAGRAM
A flow diagram for popex is given in Figure 6. The emissions of
different pollutants are weighted by their tolerance factors which are
based on ambient air quality standards, and are combined into one num-
ber (see Chapter VI for more details). The concentrations of the com-
bined emissions reaching the receptors are estimated using the dispersion
model whose construction is described in Chapter IV.
In calculating inter-county population exposures, county population
has been assumed to be concentrated at the center of its respective
-------
36
TABLE III DEMOGRAPHIC DATA FOR CHICAGO AQCR(27)
County
Cook
DuPage
Grundy
Kane
Kankakee
Kendall
Lake
McHenry
Will
Lake
Porter
State
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Indiana
Indiana
Population
5,488,328
491 , 882
26,535
251,005
97,250
26,374
382,638
111,555
249,498
546,253
87,114
Area,
sq. miles
954
331
432
520
678
320
457
610
847
513
425
Density
(people/
sq. miles)
5,753
1,486
61
483
143
82
837
183
295
1,065
205
Chicago AQCR
7,758,432
6,087
1,275
-------
APPARENT
TOLERANCE
FACTORS
POPULATION SUBMODEL
for average
exposures
TOLERANCE FACTOR SUBMODEL
combined emissions
of all the pollutants
DISPERSION SUBMODEL
I
average concentrations
POPULATION-POLLUTION
EFFECT
PRORATING OF EFFECTS
TO INDIVIDUAL SOURCES
Figure 6. Popex flow diagram
RANKINGS
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38
county. The concentrations of pollutants at these receptor locations
in each county are calculated for all the sources from all the other
counties. The extent of population exposure is determined by weighting
the receptor-point concentration proportional to the population of the
receptor county.
In the case of self or intra-county pollution (the pollution emitted
by a county affecting people in the same county), computation of pollu-
tion-population exposure is more complex. A submodel was developed which
estimates a ring of average exposure for each source for subsequent cal-
culation of average exposure to the population in the county. Details
\
of this population submodel are given in Chapter V.
Finally, the intra-county and inter-county exposures are summed
for all counties in the AQCR. The pollution-population exposure due to
all the sources in all the counties of the AQCR is then summed. The
percent contribution of each individual source to the total pollution-
population exposure is then back-calculated and is used for assigning
a priority-ranking for each source category.
DEVELOPMENT OF SUBMODELS
As discussed earlier, considerations of dispersion, exposure to
people and subsequent health effects of the air pollutants are included
in the popex model for ranking of sources. Each of these three areas
form submodels. Submodels for dispersion, population exposure, and
health effects are discussed in the following three chapters. For
each of the submodels, a generalized discussion along with a review of
-------
39
pertinent literature is given first, followed by a detailed description
of rationale, development and construction of the submodel.
-------
CHAPTER IV
DISPERSION SUBMODEL
l
INTRODUCTION
There are two basic types of dispersion models: steady state
models (box and plume models) and unsteady state models, or models
which have time as one of the variables (puff model) . The box model
is the simplest and assumed to be a rectangular covered box with de-
fined dimensions (28) . The height of the box is the mixing depth of
the atmosphere, or the height of the unstable layer in the atmos-
phere, in which pollutants can disperse. The flow of air is assumed
to be in one end of the box and out the other. The concentration in
this "box" is given by:
where C is the concentration of air pollutant,
q0 is the concentration of background air pollution,
Q is the emissions, g/sec
D and H are the width and the height of the box, km
and U is the windspeed, m/sec.
The sources within the box are modeled as a completely-mixed and
dispersed area source.
Gaussian plume models (18) have been developed as a more realis-
40
-------
41
tic representation of dispersion (Figure 7). With the plume model, an
individual characterization of each source is possible. The concen-
tration, C, at any downstream point (x, y, z) can be calculated from
the following equation:
= 2 Q-UT-V
exp
y z
" ^"-M
2 Uz I
i / y \
2~
2 \ayj
+ exp
-
_ 1 /z+hV
L 2\°* i.
A
(2)
where x = distance downwind in the direction of wind, km
y = crosswind distance, km
z = height above ground level, km
h = effective source height above the ground surface, km
ay, az = the standard deviations of the plume concentration
distribution in the crosswind direction and in the
vertical direction, respectively, km.
The total concentration at a receptor point is the sum of the contri-
bution from all the sources plus background concentration. In a
sophisticated puff model time variables are included and a simulated
puff can be made to react to altered weather conditions downwind from
a source (29).
The results obtained from any dispersion model are completely
dependent upon the quality or reality of the input data. Utilization
of a complex and time-consuming meteorological model in popex could
have increased the sophistication of the methodology. However, in
order to balance the levels of complexities and accuracies with other
-------
distribution
in y direction
(0,0,0)
Concentration
distribution
in z direction
(x,-y,z)
(x,-y,0)
Figure 7: Plums irodel
-------
43
aspects of the methodology, a simpler meteorological model which has
a level of sophistication beyond that of a box model was constructed.
DEVELOPMENT
A simple dispersion model, based on the Gaussian plume equation
2 was developed for estimating long term average concentrations in
concentric rings surrounding each emission point. Stack height and
distances from a source have been retained as variables, while most
meteorological conditions were held constant.
This submodel differes form other plume models such as the Air
Quality Display Model (AQDM) in one important aspect: the submodel
assumes a symmetrical wind rose, or that the wind blows from each
direction for an equal fraction of time. The bases for this assump-
tion are discussed in the following section.
The assumption of symmetric wind rose also allows for a simplifi-
cation of the overall dispersion algorithm. In this submodel, a set
of empirical expressions were developed which are used in conjunction
with equation 2. The actual procedure for the development and use of
the submodel is discussed later in this chapter.
Rationale for Assumption of Symmetric Wind Rose
The considerations that prompted the assumption of symmetric wind
rose were: (a) A detailed temporal wind rose data for one or two
locations within as AQCR can not adequately represent the wind rose
data for the AQCR. Different locations within the AQCR may have dif-
ferent wind roses, especially if the AQCR is located adjacent to an
-------
44
ocean or a lake. Such spatial wind rose data are not available.
(b) There are variations in the wind rose with seasons. Even if
the wind rose for a particular season is assymmetrical, the annual
averages, especially the data averaged for different altitudes, may be
quite symmetrical.
Lake Michigan has considerable influence on the meteorology of
the Chicago AQCR. Day-time heating of land surfaces, especially
during the warm seasons, either strengthens the onshore flow of winds
(lake breeze), weakens the offshore flow, or produces an onshore flow
i
that would not otherwise exist (30). The lake breeze can cause the
winds to blow in two different directions at two locations, one near
the lake shore and the other several miles inland, but both within
the AQCR. At certain times during spring and summer months the loca-
tion nearer the lake shore will have winds from the lake and the in-
land location may have winds governed by macroscale meteorology.
Similarly, the lake causes substantial recirculation of air. All
of these points related to the assumption of a symmetric wind rose
are discussed below.
In the Chicago area windspeed and wind direction data from the
two National Weather Service (NWS) stations located at Midway (MOW)
and O'Hare (ORD) airports are published regularly (31). The average
resultant annual windspeeds and directions for 1973 and 1974 for both
of these stations are shown in Table IV.
-------
45
TABLE IV. ANNUAL RESULTANT WINDSPEEDS AND DIRECTIONS
FOR CHICAGO
Midway Airport O'Hare Airport
Wind Wind speed Wind Wind speed
Year direction (mph) direction (mph)
1973 2101 1.6 230 1.8
1974 210 2.0 240 2.3
Figures for wind directions are in degrees from North, i.e.,
90 - East, 180 - South, 270 - West, 360 - North'.
The wind directions are essentially the same for these two
locations. However, as the Figure 8 shows, these airport locations
are inland (MDW is 9 miles from the nearest lake shore and ORD is 14
miles). The wind data from other locations (Figure 8) such as Meigs
Airfield (CGX), DuPage County Airport (DPA), and Glenview Naval Air
Station (NBU) are not published and are kept on NWS files for only 90
days. Even these locations, as Figure 8 shows, may not adequately
represent the outlying counties.
The data for two periods (June 5-7 and July 26-29, 1975) for
these airport locations were obtained by copying the hourly data-
logs2 kept at the NWS office, 1749 West Pershing Road in Chicago.
The weather conditions during these two periods were varied and in-
cluded days with (a) average windspeeds of 10-15 mph or moderate-to-
2Generally only data for 9 a.m. to 9 p.m. were available for all of
the five stations. CGX remains closed from 11 p.m. to 5 a.m. and on
most days no data was available from NBU between 9 p.m. and 9 a.m.
-------
Me HENRY
46
LAKE
KANE
KENDALL
GRUNDY
Du Page
3 County
Airport (DPI
DU PAGE
Lenview
Na^Hal Air LAKE MICHIGAN
Jion (NBU)
O' Harel Airport
Meig's Airfield
(CGX)
Airport
(MOW)
COOK
WILL
KANKAKEE
tn
H
H
H
H LAKE
PORTER
10
20
30 miles
Figure 8. Airport locations in Chicago AQCR
for wind data.
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47
strong winds with no lake breeze (June 5 and 6) and with lake breeze
(July 27), (b) average windspeeds of 7-9 mph or moderate winds with
no lake breeze (June 7 and July 26), (c) average windspeeds of 4-6
mph or moderate-to-light winds with lake effect (July 28 and 29).
On a day when the inland and near shore temperatures are the same
(difference of less than 3 to 4°F) or no lake-effect and when strong
winds are present, the wind roses for different locations are quite
similar (Figure 9). Even then there are some differences; MOW has
predominantly NW and ORD has predominantly W winds. The variability
in the wind roses increases when the windspeeds are lower (<10 mph)
as shown in Figure 10. In cases when there is a lake breeze, due to
the inland area being warmer than the lake water, wind roses at dif-
ferent locations are significantly different (Figures 11 and 12) . In
Figure 11, on a day with a light lake breeze the location near the
shore (CGX and NBU) has E winds whereas other inland stations have
winds from S and SE. Figure 12 shows a day (July 27) with stronger
lake effects.
To visualize the changes in wind directions for the day with a
strong lake effect (July 27), the wind directions at three hour inter-
vals are depicted on Figure 13. At 6 a.m. all stations except DPA
have winds from SW and DPA has W winds. W to NW winds predominate at
all the locations at 9 a.m. At 12 noon for CGX there is a change in
3Wind directions: E - east, SE - southeast, S- south, SW - southwest,
W - west, NW - northwest, N- north, NE - northeast.
-------
Dupa^e County
Airport (DPA)
Meigs Airfield
I (CGX)
Midway Airport
I (MOW)
:are Airport
(ORD)
17
17
25
nyi<
Glenview Naval
Air ^tation (NBU)
data)
Numbers indicate frequency (percent time) of
wind from a particular direction
Figure 9. Wind roses for different locations in Chicago AQCR for.
June 5', 1975 (9 am to 9 pm) .
03
-------
DuPage County Airport (DPA)
25 25 8
8
Meig's Airfield (CGX)
8
17
58
Midway Airport (MOW)
8 17
O'Hare Airport (ORD)
8
8 17
Glenview Naval Air Station (NBU)
-(Incomplete data")
17
Numbers indicate frequency (percent time) of wind from a particular direction.
Figure 10. Wind roses for different locations in Chicago AQCR for
June 7, 1975. (9 am to 9 pm).
10
-------
DuPage CouJity Airport (DPA)
Meig's Airfield (CGX)
8
8
Midway Airport (MDW)
17 33
8 25
O'Hare Airport (ORD)
Glenvie.w Naval Air Station (NBU)
Numbers indicate frequency (percent time) of wind from a particular direction.
Figure 11. Wind roses for different locations in Chicago AQCR for
July 29, 1975 (9 am to 9 pm).
-------
DuPage County Airport (DPA)
Meig's Airfield (CGX)
Midway Airport (MDW)
0'Hare
Glenview Naval Air Station (NBU)
(incomplete data)
13
Numbers indicate frequency (percent time) of wind from
a particular direction.
Figure 12. Wind roses for different locations in Chicago AQCR for
July 27, 1975 (6 am to 9 pm) .
-------
6 am
DPA
DPA
CGX,MDW,NBU
ORD
9 am
DPA 12
MDW
ORD
noon
MDW
DPA,ORD,NBU
DPA
NBU
MDW
CGX
ORD
CGX
Figure 13. Wind directions at three-hour intervals for different
locations in Chicago AQCR on July 27, 1975.
en
KJ
-------
53
wind direction by almost 90 degrees and its wind direction becomes NE.
This shows the start of the lake breeze. At 3 p.m. CGX has SE winds
but all other locations still show NW winds. At 6 p.m., wind direction
at both MDW and NBU, in addition to CGX, become essentially E, and DPA
and ORD still show NW. Note that MDW and NBU are nearer the lake than
DPA and ORD and, hence, the lake breeze from E affects MDW and NBU
first. At 9 p.m. DPA and ORD show N to NE winds, and CGX and MDW
show E to SE. Finally, at midnight (not shown in Figure 13) all the
reporting stations have W winds. Thus, in less than 24 hours wind^
have changed direction by almost 360°. Also, through a significant
part of the day different stations had different wind directions.
Such conditions could be experienced for 60 percent of spring and
summer days or for a substantial fraction of the time during a year
(28).
The lake also causes recirculation of air pollutants. In an ex-
periment performed by Lyons and Olsson (32), balloons released into
an onshore or lake breeze rose, went opposite to the lake breeze, then
descended and returned in the onshore breeze, then starred to repeat
the cycle as indicated on Figure 14. This means that pollution can be
blown away only to return, sometimes several times in the same day.
The dispersion equations are not able to account for this occurrence.
Finally, for a given location, different seasons of the year may
have different wind roses. Figure 15 shows wind rose data for a power
t * '
plant located within the Chicago AQCR (33) . Wind roses for each of
the calendar quarters are shown in the four corners on Figure 15.
-------
54
2.5 miles
Land
Lake
shore
Lake
Figure 14: Pollutant trajectory in a lake breeze,
adapted from (32).
-------
55
19v 10
20
8
S» calm
1%
13
Jan-Feb-Mar
13 10
15
13
12
13
11
11
calm
2%
9 18
11
8 11
Average of the
Four Quarters, 1972
16
10
Apr-rMay-Jun
calm
13 4%
v 10
Vl
15 ' 12
' '12
Oct-Nov-Dec
calm
1%
Figure 15: Wind rose data for Dresden nuclear power station
of Commonwealth Edison Company, 1972 (33).
-------
56
During the fall and winter months, winds are predominantly from W and
NW. The ME and E winds dominate to some extent in the spring months,
whereas during the summer, S and SW winds are more frequent. Of course,
these particular data for the wind rose for a single location may not
be truly representative of the whole AQCR. However, the average of
wind roses (Figure 15, center) is remarkably symmetrical.
In summary, the reasons for assuming a symmetric wind were: (a)
wind roses at a single location can not describe the conditions in the
entire AQCR, and the data for other locations are not available in
readily-obtainable published format, (b) an average of seasonal wind
; i ;
roses is noticeably symmetric.
Construction
The dispersion equation employed in this submodel for ground
level concentration (z = 0 in Figure 7) is as follows:
exp
(3)
and for stability C as defined by Turner (25):
0y = 0.1 x°-92 , (4)
0Z = 0.06 x °'9 (5)
where 0y, 0Z and x are in km.
In this case, the plume rise above the stack was assumed to be zero
and thus, h is the stack height. The concentration at any point x, y
can be calculated using equation 3. This would vary depending on the
wind direction, even if average windspeed and stability were held
-------
57
constant.
In order to get an estimate of average concentration at points
which are equidistant from a source, the following method was develop-
ed based on a symmetric wind rose, which saves a considerable amount
of computer time. The basic approach was to estimate an imaginary
angle 9 (where x = rCos 9 and y = rSin 6) such that the concentration
C(r,0) at the point (r,9) is the average annual concentration, C(r),
at any point at a distance of r from the source.
To obtain a generalized expression for 9, concentrations using
equation 3 were determined for different values of 9 with height of
stack and r held constant. Next, the averages of these concentrations
for different values of 9 were computed. This average concentration
would be the same as the average concentration with symmetrical wind
rose for a point at a distance r from the source. The average con-
centration was ^matched against the values of C(r,9) for different values
of 9. This would give a 9' for a particular r' so that C(r', 9')
would be the same as C(r') . This process was repeated for different
stack heights and distances up to 100 km. The angle, 9, was regressed
(34) against the stack height and distance from this data. The metho-
dology is given in Figure 16.
The following equation for 9 was obtained which is applicable to
all heights and distances above four kilometers. Table V gives a simi-
lar equations for the other conditions.
9 = 14.24 -. 0.79 ln(r) for r >4 (6)
-------
1
a , a
y
C(r,6)
vary
0 to 90°
i
E C(r,9)
vary r
0.01 to 100 km
C(r)
vary h
i
0 to 500 meters
58
x = rCos 6
y = rSin 6
o = 0.Ix
y
.92
a = 0.06x
z
.9
i c(r'e) = iorrexp
I y z
I
exp
n
E C(r,9n)
C(r) =
i
Match C(r) with C(r,6) for a
particular set of h and r
Regression
analysis
t
9 = f(h,r)
Figure 16: Flow diagram: development of dispersion submodel
-------
59
TABLE V. EQUATIONS FOR ANGLE 9 IN THE DISPERSION SUBMODEL
Equations Limits
Height/ h, Distance, r,
in meters in Km
9 = 14.24 - 0.79 ln(r) h<500 r>4
9 = 14.28 - 0.79 ln(r) - 0.01 r 100
-------
60
For this equation coefficient of determination,4 R2 is greater than
0.99.
Finally, in order to calculate a concentration at any location at
a distance r from a source with a stack height equal to h, the equa-
tions 6, x = rCos 0, y = rSin 0, 4, 5 and 3 are used, in that order.
The details of the computer algorithm are given in Chapter VXT.
4The coefficient of determination R2 is the proportionate reduction
in the variation of the dependent variable 6, which is explained by
the independent variable r.
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CHAPTER V
POPULATION SUBMODEL
INTRODUCTION
The purpose of the submodel was to characterize spatial distribu-
tions of population and population characteristics with respect to
sources of air pollution. There are a multitude of factors involved
in the characterization of population and its distribution and inclu-
e
sion of all the factors could make such modeling an exceedingly com-
plex, if not an impossible task. People are not located at equal
distances with respect to different sources or even similar sources
of air pollution. Quite often people work in different places than
they reside, which means that they are exposed to different levels of
pollution in a single day. Similarly, depending on the mode of travel,
they are exposed to more or less pollution. Thus, in a model which
simulates these conditions, not only do the complex distributions have
to be included but they have to be dynamic in nature or a time factor
needs to be included. Inclusion of age and other factors in the
people-location-time model would lead to further complications.
DEVELOPMENT
Rationale
In this first generation model only population and county area,
<
with an assumption that population density is constant within a county,
were considered. Even in this case, the modeling was not straight
61
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62
forward. Except in cases of very tall stacks, people living nearer to
the industries obviously experience a larger pollution dose than those
living at greater distances. It has not been feasible to determine
the source-receptor damage for each location-specific inhabitant.
Billions of computations would have been required (up to 1800 for each
inhabitant, in the extreme). Moreover, extremely large amounts of
needed computer storage could have made running and debugging a com-
puter program very difficult.
The principle used to reduce the complexity of the model and
computer time was to find a generalized expression for the distance
between the source and a point such that the concentration at that
point would be the same as the average concentration experienced by
people for that particular source and county combination. Thus, the
total number of computations of concentration would be equal to the
total number of sources in the AQCR. These source-county specific-
distances, called rings of average exposure, were derived in the
following manner and the methodology is depicted in Figure 17.
Construction
A series of weighted average self-pollution concentrations for
two county sizes (radii, 30 and 100 km) and for different stack
heights (1 to 500 meters) were calculated. Next, for each case, the
weighted average concentrations were matched against concentrations
for the various distances derived earlier. The distances at which
the two concentrations were equal were tabulated with the appropriate
stack height and county area. The results for the distances or ring
-------
1
Dispersion submodel
6 = 14.24-0.79 In r
and other equations
for 8
f
Expressions for
x, y,
y,
, C(r,6)
from Chapter IV
Area weighted
ring concentration
vary h
from 1 to 500 metdrs
Total weighted average
concentration =
total concentration (R)
total area
vary r
from 0 to R
63
Ring area
I
I
f
Match
i
J
Regression
analysis
RR = f (R,h)
Figure 17, Flow diagram: development of population submodel.
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64
radii were regressed against the height of the stack and county area,
and the following equation was obtained (coefficient of determination,
R2 = . 99) :
RR = _ 0.65 + 0.26 R + 0.02 h + 0.51 In (h) (7)
where RR (kilometers) is the ring radius for height h (meters) and for
a specific county size. R is the radius of a circle whose area is
equal to the area of the county, or R =,
A word is due about the chronological development of this sub-
model: equation 7 was actually derived after a second "iteration" of
the process described above (Figure 18). Initially, through an analy-
sis similar to Figure 17, but in a less rigorous manner, an approxi-
mate equation RR = .25 R was derived and used in the model. Subse-
quent sensitivity analysis showed that RR greatly influenced the
results. Thus, the whole process (Figure 17) was repeated for large
numbers of values for R and h and the results were regressed with the
help of the Biomedical computer program BMDO2R (34) to arrive at
equation 7 (Figure 18).
Finally, the algorithm of this submodel is simple: calculate R
for each source from R = J area/ir, where area is the area of the county
in which the source is located. Substitute this R and the stack
height, h, into equation 7 to compute RR, or the ring radius, for each
source. RR is then used as an input to the dispersion submodel.
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65
SENSITIVITY ANALYSIS
i
POPEX USING POPULATION
SUBMODEL : RR = 0.25 R
RR AN IMPORTANT PARAMETER
I
REPEAT : POPULATION
SUBMODEL DEVELOPMENT
RR, R, h
REGRESSION ANALYSIS
(BMDO2R)
RR = -0.65 + 0.26r + 0.02h + 0.51 In h
Figure 18. Sensitivity analysis and improvement of population submodel.
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CHAPTER VI
HEALTH-EFFECTS SUBMODEL
INTRODUCTION
The effects of air pollution on human health can be divided into
four groups (2): (a) acute sickness or death, (b) insidious or chronic
disease, shortening of life, or impairment of growth, (c) alterations
of important physiological functions, such as ventilation of the lungs,
and (d) discomfort, odor, or eye irritation. Large amounts of work
related to these groups of health effects have been done over the
past years.
A generalized model for predicting health risks would be extremely
valuable for determining the relative impact of different sources of
air pollution. There are many "gaps" in the knowledge related to the
precise effect of varying dosages of different air pollutants and no
data on dose-response relationships relating air pollution dosages to
effects on mortality and morbidity were available at the beginning of
this project in September 1973. Since early 1974, there has been an
extensive effort by the EPA and others (22, 35-37) to construct dose-
response curves in terms of aggravation of disease or increase in in-
cidence of a disease. Another approach would be to relate dosages of
air pollution to their effects on physiological functions as character-
ized by a set of clinical indicators. Such an effort is described in
Appendix A. However, none of these approaches was general enough to
66
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67
be used for all pollutants. In this project, the need was for an
evaluation of the relative effect of different pollutants. The follow-
ing approach was used for estimation of the relative effects.
DEVELOPMENT
Rationale
A common basis for assessing the relative potential for the
/
deleterious effect of different pollutants was needed. Pindex, ini-
tially developed by Babcock (38), provides such a basis. Pindex con-
siders the relative effect of each pollutant and combines individual
pollutant levels for a given emission source into a single meaningful
number. The tolerance-factor submodel is based on pindex, and the
methodology for pindex (39) as well as its data base (40) have under-
gone substantial revisions. New concepts such as apparent tolerance
factors (41) have been added through this research project.
The federal ambient air quality standards (42) are based upon the
available knowledge of the deleterious effects of the individual pol-
lutants and seem to be the best available means for relating one pollu-
tant to another as well as for indirect assessment of effects. The
basic premise has been that equivalent toxicity, harm, or unpleasantness
is experienced when any of the pollutant concentrations reaches its
ambient standard. Thus, ambient standards can serve as ready-made
tolerance factors for use in this submodel. This submodel is called
a tolerance-factor submodel.
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68
Construe t ion
Most-stringent standards. - There was, however, the problem of mul-
tiple standards for the same pollutant. For example, five different
standards were established for sulfur dioxide (Table VI). The work
of Larsen (43,44) provided some insight into the problem of multiple
standards. He found interesting relationships between annual average
concentrations for pollutants and the maximum concentrations present
for shorter time periods.
The Larsen relationship is described by Figure 19. The point A
indicates the annual average concentration for sulfur dioxide at a
certain location. Since this is the annual average, one-half of the
readings during the year would be expected to be above, and the other
half would be below this average value of A. Thus, approximately half
of the readings for any averaging time would lie above the 50 percent
probability line with the remainder below this line. It should be
noted that this probability line might not be horizontal unless the
i
mean and median values coincide.
To relate maximum concentrations for shorter time averages to the
annual average: Larsen found that for a given annual average in a
given locality, it would be unlikely that the monthly average would
exceed a certain level more than once a year (point B in Figure 19).
This point B, as we would expect, is above the annual average, since
the annual average lies intermediate between the higher and lower
monthly average concentrations. Similarly, the expected maximum
-------
TABLE VI. AIR QUALITY STANDARDS AND TOLERANCE FACTORS (in yg/m )
Pollutant
Oxidant
Sulfur
dioxide
(Secondary)
Nitrogen
oxides^
Carbon
monoxide
Particulate
matter
(Secondary)
Hydro-
carbons
EPA STANDARDS
Annual Levels not to be exceeded
measure more than once/year
24 hr. 8 hr. 3 hr. 1 hr.
160
(0.08)
80 365
(0.03)1 (0.14)
60 260 1300
(0.02) (0.10) (0.5)
200
(0.1)
10,000 40,000
(9) (35)
75 260
60 150
160
TOLERANCE FACTORS
24-hour Annual
Ambient Emission Ambient Emission
(apparent) (apparent)
59 8
260 260 41 41
800 330 200 53
7800 7800 2900 2900
150 150 54 54
A A
80C4 1004
(0.24)
-------
TABLE VI. CONTINUED
Footnotes for Table VI.
1 "
The numbers in parentheses are in ppm.
EPA standards are for nitrogen dioxide. It is assumed here that the half of all nitrogen- oxides
(emission or ambient) in the atmosphere are nitrogen dioxide.
This standard is only applicable to morning rush hours and was not used to determine the hydrocarbon
tolerance factors.
These numbers are based on a 1968 emission inventory (46) .
-------
1
c
S
-P
-P
C
0)
u
c
8
10.0
1.0
0.1
0.01
B
50 percent probability line
I
10
I
AM ^^
I I
10,000
n
G
H
1,000 g
rl
-P
(8
5-1
P
0)
O
c
o
u
100
1 Hr
24 Hr
1 Month
1 Year
Figure 19. Concentration vs. averaging time for sulfur dioxide.
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72
i
levels for the 24-hour and 1-hour periods are shown in Figure 19 as
points C and D.
Again, it is not surprising that such maximum concentrations rise
as the time intervals are reduced. High concentrations for s,hort time
intervals are expected and experienced. They are averaged together
with below-average values in order to arrive at the intermediate
annual average. A line through points A, B, C and D describes the
expected maximum concentrations for different sampling times which are
associated with a given annual average. If this "line of limits" is
exceeded for more than once a year for any time period, the annual
average would probably be increased.
Now it is possible to relate this line of limits to the standards
for sulfur dioxide. Figure 20 shows the three secondary and two primary
standards for sulfur dioxide. The relationship between the standards
is not the same as the average Larsen line of limits. The three
secondary standards do not lie in a straight line. The reason could
be that certain deleterious effects may be detected at a certain con-
centration over a short period, and other effects may be likely for a
different concentration over a longer time interval.
Even though the five standards are not in one line, individual
parallel Larsen relationships can be drawn through each of the points
as shown on Figure 20. One of them, the lowest line, is clearly the
most stringent. If this line is not exceeded, none of the upper lines
i
will be exceeded. This most-stringent relationship is based upon the
24-hour secondary standard. Fromf this line the most-stringent annual
-------
10.0
1.0
04
H
o
H
JJ
c
u
8 o.i
A Primary standard
Q Secondary standard
10,000
0.016
0.01
tn
H
1,000 §
"^1
100
41
-P
C
0)
O
c
o
u
1 Hr 3 Hr 24 Hr 1 Month
Figure 20. Standards and tolerance factors for sulfur dioxide.
1 Year
U)
-------
74
standard or annual-tolerance factor was derived as 0.016 ppm or
41 pg/m^ (Table VI) for sulfur dioxide. Similarly, most-stringent
annual standards were derived for the other pollutants and are like-
wise listed on the right-hand side of Table VI. The pertinent back-
ground information is listed on Table VII.
The toxicity-factor submodel is based upon these annual tolerance
factors thus derived. Apparent tolerance or toxicity factors were
computed for nitrogen oxides and hydrocarbons, the pollutants which
react to form oxidants. The discussion of photochemistry, as well as
the definition and discussion of apparent tolerance factors, is given
t /
below.
/
Photochemical considerations and apparent tolerance factors. - It was
assumed that nitrogen oxides and hydrocarbons contribute to photo-
chemical oxidant formation on a one to one molar basis (45). The
concept of a limiting reactant is important; if the total number of
moles of nitrogen oxides is less than the number of moles of hydro-
carbons, the limiting reactant would be nitrogen oxides, and thus
theoretically, the maximum amount of oxidant produced would be equal
to the number of moles of nitrogen oxides. However, the extent of
conversion to oxidant is also affected by solar radiation. In pindex,
the reaction to oxidant is assumed to be 22 percent complete (38),
based upon the average solar radiation level present in major USA
cities.
For example, consider an air pollution source with nitrogen oxide
emissions of 20 tons and hydrocarbon emissions of 15 tons; the moles of
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75
TABLE VII. DERIVATION OF TOLERANCE FACTORS
Oxidant
Sulfur dioxide
Nitrogen oxides
Carbon moxoxide
Particulate matter
Hydrocarbons 3
Slope of
Larsen
"Line of
limits"
log (yg/m3)
log (hr)
- 0.335
- 0.315
- 0.2461
- 0.179
- 0.212
- 0.238
Most
Stringent
Standard
yg/m3
160 (1 hr)
266 (24 hr
secondary)
200 (annual)2
10,000 (8 hr)
150 (24 hr
secondary)
160 (3 hr)4
Extrapolated
Annual
Ambient
Standard
yg/m3
8
41
2002
2900
54
*The slope, - 0.246, is for N©2 and this slope was used in the
extrapolation. The corresponding slopes for NO and NOX are
- 0.387 and - 0.310, respectively.
2EPA standards are for nitrogen dioxide alone. It is assumed
here that the half of all nitrogen oxides in the atmosphere
are nitrogen dioxide.
3Hydrocarbons assumed to be an oxidant precursor rather than
a pollutant.
is standard is only applicable to morning rush hours and
was not used to determine the hydrocarbon tolerance factors
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76
nitrogen oxides emitted are equal to:
weight of NOX in tons 20
= = 0.43 ton-mole.
molecular weight of NOX 46
Similarly, assuming the average molecular weight of hydrocarbons to be
\
16, the moles of hydrocarbon emitted are equal to 15/16 or 0.94 ton-
mole. Thus, nitrogen oxides is the limiting reactant, and the amount
of oxidant formed will be equal to the limiting reactant times the
fraction of reaction going to completion:
oxidant = 0.43 x 0.22
= 0.095 ton-moles of oxidant, or
= 0.095 x molecular weight of oxidant
= 4.6 tons of oxidant
assuming average molecular weight of oxidant to be 48.
The recent improvements in pindex methodology were related to the
method of assigning oxidant contribution (13). In the original model
(38), oxidant was formed only to the extent that an individual emission
category emitted both nitrogen oxides and hydrocarbons. For example,
in the case of a source which has only hydrocarbon emissions and no
nitrogen oxides there was no oxidant formation, and no "penalty" was
assessed in the original pindex. The tolerance-factor submodel assumes
mixing among emissions from different categories such that oxidant can
be synthesized from nitrogen oxides from one source and hydrocarbons
from another source. The oxidant contribution thus obtained is then
prorated back to its precursors, 50 percent to nitrogen oxides and 50
-------
77
percent to hydrocarbons, regardless of the source.
"Apparent" or emission tolerance factors are also listed in
Table VI. These adjusted factors approximate the contributions of
nitrogen oxides and hydrocarbons to photochemical oxidant formation
such that the oxidant effects can be distributed among nitrogen oxides
and hydrocarbon precursor emissions. Hydrocarbons have no tolerance
factor listed in the ambient column (Table VI) because they are con-
sidered to be solely pollutant precursors rather than actual pollu-
tants. Likewise, no tolerance factor is shown for oxidant emissions
because oxidant is usually formed in the atmosphere rather than
emitted directly.
The apparent tolerance factors were derived in the following
manner: From a nationwide emissions inventory (46), total hydrocarbon
emissions are 32.0x10^ tons and total nitrogen oxide emissions are
20.6x10** tons. Assume average/molecular weight is 16 for hydrocarbons
and 46 for nitrogen oxides:
hydrocarbon emissions = if^" x 1C}6 = 2-0xl°6 ton-moles
nitrogen oxide emissions = ' x 106 = 0.45xl06 ton-moles-
Again, nitrogen oxides is the limiting reactant, and from the earlier
discussion:
oxidant = 0.45xl06x0.22
= 0.1 xlO6 ton-moles
=4.8 xlO6 tons
-------
78
This oxidant is in turn prorated equally to both hydrocarbons and
nitrogen oxides.
Now, to calculate the apparent tolerance factor for nitrogen
oxides:
unreacted nitrogen oxides = (0.45 0.1)106 ton-moles
= 0.35xl06 ton-moles
= IG.lxlO6 tons.
The apparent tolerance factor for nitrogen oxides can be determined
from the equation: (8)
total NOX unreacted NOX oxidant attributed to NOX
apparent tolerance tolerance factor oxidant tolerance factor
factor for NOX for NOX
Substituting the appropriate tolerance factors from Table VI:
20.6xl06 IG.lxlO6 2.4xl06
= +
apparent tolerance 200 8
factor for NOX
or apparent tolerance factor for NOX =53 (when calculated with values
for nitrogen oxides and oxidant tolerance factors prior to rounding
off).
Similarly for hydrocarbons:
total HC _ oxidant attributed to HC
apparent tolerance factor oxidant tolerance factor
for HC
32.0x106 = 2.4xl06
apparent tolerance factor 8
for HC
or apparent tolerance factor for HC = 100 (when calculated with values
for oxidant tolerance factor prior to rounding off).
-------
79
Note that the apparent tolerance factor for nitrogen oxides is
independent of the nitrogen-oxides/hydrocarbon emission ratio as long
as nitrogen oxides are limiting (almost always the case). Such is not
the case for hydrocarbons, since the oxidant "penalty" must be prorated
among variable amounts of excess hydrocarbons.
The tolerance factor of 100 for hydrocarbons is based on the 1968
nationwide emission inventory (46) and it could be considered as the
upper limit, since hydrocarbon emissions have been steadily decreasing
since 1968. On the other extreme, is a case when both nitrogen oxides
and hydrocarbon are present in equal-molar basis; for such a case the
hydrocarbon tolerance factor will be 25. 'Similar calculations reveal
that the range for 24-hour apparent tolerance factors for hydrocarbons
is 175-800. Note that as hydrocarbon emissions are reduced, the re-
maining hydrocarbon emissions become more significant with regard to
oxidant synthesis. A much more realistic appraisal would result if
"reactive" rather than "total" hydrocarbons are considered as oxidant
precursors. This refinement would require more-explicit emission
information than is currently available for most hydrocarbon sources.
Finally, the annual emission (or apparent) tolerance factors given
in the extreme right column of Table VI are used in the tolerance-
factor submodel. From these annual apparent tolerance factors it is
clear that carbon monoxide is the least toxic pollutant. In the model
the emissions of all the pollutants are brought to CO-equivalent base
for comparison. This is accomplished by multiplying the emissions by
a factor TF(pollutant). This factor is given by:
-------
80
where K is the particular pollutant,
FF(CO) is the tolerance factor for CO, and
FF(K) is the tolerance factor for the pollutant K.
The details of a computer algorithm which uses the mathematical
relations developed in this chapter as well as in chapters IV and V
are given in the following chapter.
-------
CHAPTER VII
COMPUTER MODELS AND INPUT DATA
COMPUTER MODEL: POPEX
With the simplifications and assumptions utilized in the preced-
ing chapters to arrive at the three submodels, the basic computer
algorithm for popex is quite simple and is described below. Details
of the computer program are given later.
Computer Algorithm
The definitions of variables used in the following algorithm and
their equivalents used in Chapters IV, V and VI are given in Table VIII.
The computer algorithm, stepwise, is:
(1) Based on the method given in Chapter VI, combine emissions
of the five pollutants for each source into one number:
5
SOURCE(I,N,7) = Z_SOURCE(I,N,K) x TF(K)
K.X
(2) Calculate distances for inter-county and intra-county ex-
posures. For inter-county, distances between the centers of the
emitter and the receptor counties are calculated:
DIST(I,J) = |(X(I) -X(J))2+ (Y(I) -Y(J))2
or D = 1.6 x DIST(I,J) kilometers.
In the case of intra-county exposures, from Chapter V,
R = (AREA (I) A) ^
81
-------
TABLE VIII. EXPLANATIONS OF VARIABLES USED IN THE COMPUTER PROGRAM
Terms used in the
computer program
Equivalent
terms if
used in
Chapters
IV,V,VI
Explanation
AREA(I)
BCON(I,J)
CCON(J)
DIST(I,J) or D
DIST(I,I) or D
EXP(J)
FF(K)
H or. SOURCE (I, N, 6)
I
J
RR, r
FF(K)
h
Concentration of air pollutants in County J due to emissions of
source N located in County I
Area of County I
Concentrations in County J due to emissions of all sources in
County I
Concentrations in County J due to emissions of all sources in all
the counties
Distances between the centers of Counties I and J
Ring of average concentration for County I based on Chapter V
i
Total population-pollution effect for County J
Tolerance factor for pollutant K
Height of the stack of source N in County I
Emitter county
Receptor county
oo
to
-------
TABLE VIII. CONTINUED
Terms used in the
computer program
Equivalent
terms if
used in
Chapters
IV,V,VI
Explanation
N
NA
POPEXP(NA)
R
SIGMAY
SIGMAZ
SOURCE(I,N,K)1
K = 1-5
SOURCE(I,N,7)1
SUMEXP
Pollutants 1-PM, 2-SO , 3-NO , 4-CO, 5-HC
> £ X
Source number
Source-category number
Population-pollution effect due to the source-category NA as percent
of the total
Radius of a circle whose area is the same as that of a county
Standard deviations of the plume concentration distribution in the
crosswind direction
Standard deviations of plume concentration distribution in the
vertical direction
Emissions of five pollutants
Combined emissions of the five pollutants based on Chapter VI
Total population-pollution effect
oo
00
-------
TABLE VIII. CONTINUED
Terras used ir. zhe
computer program
Equivalent
terms if
used in
Chapters
IV,V,VI
Explanation
TF(K)
THETA
XX
YY
-VJ.ND
TF(K)
A factor based on tolerance factor of pollutants as defined in
Chapter VI
Angle for computing average concentration in the dispersion
submodel
X-coordinate of center of County I
Downwind distance from a source
Y-coordinate of center of County I
Crosswind distance from a source
Windspeed
To save on storage space, 'these variables are actually single-string arrays in the computer program.
Some of these are converted into three dimensional arrays by the FUNCTIONS ISOD and :;AMD described in
this chapter.
oo
-------
D = DIST(I,I) = - 0.65 + 0.26R + 0.02H + 0.51 In (H) .
(3) From Chapter VI, select an appropriate equation for 0
(Table V). For example, for h <100 meters and 1
-------
86
used for popex ranking.
Computer Program
In order to facilitate future updating of the popex model, the
computer program was constructed in a modular form. Several sub-
routines and functions, each for a specific task or pet of tasks, were
prepared. The flow of the program is given in Figure 21, and a listing
of the program is given in Appendix B. The subroutines and functions
are briefly described below.
MAIN - This is the central part of the program and is used primarily
for control of the program.
CORIBO - Contains the dispersion algorithm and is used for calculating
concentrations of emissions at the receptor points.
DATAR - All of the data is read by this subroutine. It :also prepares
tables related to the input data.
DISTAN - Calculates inter-county and intra-county exposure distances
based on the population submodel.
ISOD - The function ISOD provides the accessing ease of a three-
dimensional array while keeping the storage compactness of a single-
dimensional array.
MASSE - This is used to calculate the emission of each pollutant and
source in terms of percent of the total AQCR emissions.
NAMD - This function also provides the accessing ease of a two-dimen-
sional array while keeping the storage compactness of a single dimen-
sional array.
-------
87
*these are fxonctions; all others are subroutines
Figure 21. Flow diagram of the popex computer model.
-------
88
PINDEX - Tolerance factors developed in the health-effect submodel
are applied to emissions in this subroutine.
RITEA - Writes out the various results in different formats.
SENSE - In addition to the MAIN, this subroutine controls the program.
Values of input parameters are changed arbitrarily for sensitivity
analyses of the entire model (see Chapter IX for details).
SORTIT -This subroutine arranges source-categories in decreasing order
of their percent contribution to popex.
SUMDIS - SUMDIS sums concentrations and population-exposures from all
sources in all counties and prorates the total population-pollution
effect back to the individual source-categories for assigning rank-
priorities.
COMPUTER MODELS: MASS INDEX AND PINDEX
Two preliminary computer models called mass index and pindex were
also developed to form a basis for comparing the results of popex.
Mass index expresses the emissions of five pollutants for each of the
sources in terms of percentage of the total AQCR emissions. Pindex is
analogous to the tolerance-factor submodel and in it the emissions are
divided by the tolerance factors. Then "corrected" emissions are
normalized to a grand total of 100.
INPUT DATA
Emissions data were obtained from National Emissions Data System
(NEDS) of the U. S. Environmental Protection Agency (EPA). Data for
-------
89
the point sources were supplied by NEDS on a magnetic tape. Area-
source data were obtained from the printout of point and area emissions.
The emissions data on point sources were for 816 source categories as
defined by a source classification code (SCC). Emissions of area
sources were divided into 41 categories. SCC is a four-number code,
with a unique description for each of the 816 point-source-categories.
To save on computer storage space, instead of directly using SCC in the
computer program, these categories were assigned numbers 1 through 816.
The 41 area source categories were assigned numbers 821 through 861.
These source numbers (1 through 861) are used in this dissertation.
The Appendix C should be referred to to get the corresponding SCC for
point sources from the source-category numbers.
Emissions of the individual sources located in each of the eleven
counties are given in Appendix D. Stack heights are listed for each
source. In cases where there are no stacks, the estimated plume
heights given in the NEDS data were used in place of the stack height
in the model. For area sources, "stack heights" were assumed
(Appendix D). Table IX shows the total emissions of the five pollu-
tants for each of the eleven counties.
The centers and their x and y coordinates of each of the counties
are shown in Figure 22 (47). The center of each county is the center
of gravity of the geographical area of the county.
-------
TABLE IX. EMISSIONS DATA FOR COUNTIES IN THE CHICAGO A/CF. I!,' TONS/YEAR
OBTAINED FROM APPENDIX D
County
Cook
DuPage
Grunay
Kane
Kankakee
Kendall
Lake
McHenry
Will
Lake
Porter
State
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Indiana
Indiana
FM
287,882
8,284
13,525
10,583
7,709
574
12,988
3,120
64,523
196,738
7,160
so2
373,146
10,656
3,592
10,999
10,537
682
46,128
3,494
63,743
536,118
85,928
NO
X
280,900
25,158
- 3,561
12,914
7,168
1,499
31,620
6,269
47,046
121,693
26,410
CO
1,509,675
153,749
13,731
77,973
38,9S4
12,902
127,050
45,809
185,343
8S5 , 200
41,461
Ui-
580,912
41,584
5,393
27,002
11,030
3,025
74,562
11,947
84,860
106,945
11,566
Total
Grand total for
Chicago
613,086
1,145,023
564,238
3,097,378
6,378,551 tons/year
958,826
-------
en
H
X
(14,91)
Me HENRY
X
(15,64)
KANE
(15,40)
KENDALL
(15,19)
X
GRUNDY
I
(36,91)
X
LAKE
DU PAGE
X
(31,59)
(34,31)
X
WILL
91
LAKE MICHIGAN
X
(48,55)
COOK
X (42,9)
KANKAKKE
(68,29)
X
LAKE
X
(84,32)
PORTER
(0,0)
X axis
10
20
30 miles
Figure 22. Locations of the centers of counties in the
Chicago AQCR and their X and Y coordinates.
-------
CHAPTER VIII
RESULTS OF THE POPEX MODEL
FORMAT OF RESULTS
In the Chicago AQCR, there are 227 source-categories out of a
total of 857 nationwide source-categories given in Appendix C. As
explained earlier, each source-category may include more than one
source (Appendix D). Table X lists the results of the popex model
along with the emissions, mass index, and pindex for each of the source
categories. For each category, the first row lists total emissions, as
well as emissions of the five pollutants. The mass index is given on
the second line and it gives the emissions of each source-category and
of each pollutant in terms of percentage of total emissions for the
Chicago AQCR. On the next line pindex for the source-category, as well
as prorated pindex for each pollutant in the source-category, are given.
Results using the popex model are given on the last line.
To get a better idea of source-priorities, source-categories are
listed in the order of decreasing popex in Table XI. The source-
category "transportation-gasoline light vehicles" representing auto-
mobiles is responsible for 23 percent of popex and is listed first.
The three columns on the right (Table XI) list "ranks" for each of the
source-categories according to the three models or indices: mass index,
i
pindex, and popex. These ranks are based on percentage contribution
to each index (Table XII). .
92
-------
! AcJLh X . LMISSICNS AND HF.StH.7tr-C-P-'-» fl~,S fNO£.:.X» P IfgggX-jftNO-POPfc
SOURCE- CATEGORIES IN THE CHICAGO AUCR.
SOUKCt
CATEGORY
O C f-fl .1 S-.3 I U N i>
MASS INDEX
P INDEX
PQFcX
9 EMISSIONS
M«SS INDEX
P INDEX
10 EMISSIONS
MASS INDEX
P i. CL A
P INDEX
PCPEX
Jo c IK 1 i> 5 I u IN 5-
MASS INDEX
PINDt'X
POPEX
37 EMISSIONS
VASS INDEX
P INDEX
P t) P t X
39 EMISSIONS
MASS INDEX
PCPEX
I U 1 AL
0^43
olie
32128=-.
5.04
12.51
2.73
t> G *J
3.59
672.
. 01
0.02
0.03
23435.
0.45
1,02
0.43
0 . 0 0
0.00
fl ("^ f
45,
0,00
V.' ; - - -^
C - v 3
1 13 6 »
C.02
C.03
10027.
0.3i
1223.
0.02
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0.01
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0*01
C.02
2.
C .00
C « 0 0
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rt ---w.-
su<;
0.35
C,91
275633.
6.32
11.17
135104.
2. 12
215.
0... /"Lyi,.
0.01 .
3v yy .
C.25
0.65
70 .
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c.oo
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r ,-,3.
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rrfcQ'*1
0* 11
0.2i
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36132.
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30.
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0*02
9 ,_,.
0.00
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1 .
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1
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-------
TABLE X.
CONTINU6D
SOURCE
CATEGORY
42 EMISSIONS
MASS INDEX
K 1 NU E X
POPEX
43 EMISSIONS
MASS INUcX
P INDEX
POPEX
MASS INDEX
P INDEX
POPEX
65 EMISSIONS
MASS INDEX
P INDEX
FUr-'t*
66 EMISSIONS
t/ASS INDEX
- - P IiNuEX
POPEX
6t> EMISSIONS
P INDEX
POPEX
j, y EMlbbiCNS
MASS INDEX
PINDEX
PCPEX
72 EMISSIONS
MASS INDEX
PINDEX
LI 1 ' O r-~ i.
TCTAL
22C77.
0.35
U.&7
C.39
45.
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0.00
0.00
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0.55
olis
15253.
0.24
0.53
u o 1
122579.
1 .92
4.45
2.29
217"36.
0 . J4*
0.61
0.43
J 1 3 6 .
0.05
0.1 !
0.16
0.32
0. 72
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c.oo
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2784.
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0.02
0.03
7S39*
C. 12
C.24
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50.
C.OO
- ' C'.'O'O -
1 .
c.oo
c.oo
1 34 i»0 .
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6640.
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0.28
74771 .
1.17
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15584.
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C.63
0.02
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10140.
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0.41
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21169.
0.33
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0.32
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5400,
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0.17
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678.
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-------
TABLE X.
CONTINUED
SOURCE
CATEGORY
73 EMISSIONS
MASS INDEX
!- INDEX
POPEX
77 EMISSIONS
MASS INUfcX
PINOEX
PCPEX
VASS~INDEX
P INDuX
PCPEX
y«r, EMISSIONS
MASS INDEX
PINOEX
97 EMISSIONS
MASS INDEX
P iiNkEA
PGPEX
98 EMISSIONS
1 <
0.07
0.09
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0.10
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0.02
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c.oo
3.
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0*22
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1 330 .
C.03
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ctrs
1 .94
13827.
0.22
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1400.
0 .06
0.02
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c.oo
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2470.
C.04
0 « 0&
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0.00
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331.
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-------
TABLE X,
SOURCE
CATEGORY
101
102
10J
104
105
106
" ~- i uo
1 10
EMISSIONS
MASS INDEX
PlNDEX
POPEX
EMISSIONS
MASS INDEX
PlNDEX
POPEX
EMISSIONS
WASS INDEX
PlNDEX
PCPEX
EV1SSIGNS
MASS INDEX .
PlNDEX
EMISSIONS
PASS INDEX
P1NJEX
PGPEX
EMISSIONS
MAbS INJcX
P INDP.A
PGPEX
LN iii iUi\i>
MASS INDEX
PlNDEX
PCPEX
EMISSIONS
MASS INDr.X
P INDEX
LJ . iL-- ;- k ~~
TCTAL
225.
0.00
b.Ui
t.OO
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0.99
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-------
TABLE X.
CCNTINUED,
SOURCE
CATEGORY
111
1 12
1 lo
128
1 30
135
JO
147
EMSSIQKS
MASS INDEX
PINDtX
POPEX
EMISSIONS
MAbb INDEX
PlNDuX
PGPEX
L-M ISblONS
<*ASS INDEX
P INDEX
PUPfcX
EMISSIONS
MASS INDEX
PINDtX
H U H £1 A
FMISSIONS
,MASS INDEX
P INDtA
HUPEX
EM ISSIONS
MASS 1NDE.X
PINDEX
PGPEX
1. 1*, t o o i u i\ a
MASS INDEX
PINDtX
POPEX
EMISSIONS
,VAS3 INDL.X
P INOEX
TOTAL
2 1.
0.00
oloo
141.
" 0 O 0
0.01
0.00
C.Ol
0.03
0.01
718.
0.01
O.OJ
0 « 0 0
151 1 1 .
O. 24
0.53
0.14
36.
0.00
0. 00
t 1 £ «
C. 01
0 . 0 ?.
0, OC
3 s>5 .
0.01
0.01
0.04
PM
13.
0.00
c.oo
3.
C » \J 0
0.00
0 .
c.o
c.o
1S3.
0.00
0.00
6£17.
C. 1 1
. d\
1 .
C.OO
0.00
0.01
C.OO
C.OO
SQ2
1 .
C.OO
c.oo
111.
C w U
C.OO
£26 .
0.01
C.03
475 ,
C.Ol
0.02
6S84 .
0.1 i
.26
17.
O n-n
U . ^ O
C.OO
C.Ol
C.Ol
251 .
0.00
C.Ol
NCX
5 .
0.00
o.oo
oloo
c .
0.0
0.0
75.
C.OO
0.00
1090.
0.02
' . UO
1.
o.co
o.oo
0.00
96.
O.CO
0.00
CO
1 .
0.00
tO 0
3.
f^ ** n
U . U U
0.00
0.0
0.0
10.
o.oo
o.oo
144.
0.00
U U
14.
ei m r\ n
0.00
G
0.00
0.00
6.
0.00
0.00
HC
1.
O.OO
i-» UU
1 *
Q * OO
G*GO
.
0.0
0.0
s.
0.00
o»oo
76.
0.00
.OO
3.
0.00
0.00
0.00
5. -1
0.00
0.00
-------
CONTINUED
SOURCE
CATEGORY
143 EMISSIONS
MASS INDEX
HlNUtX
POPEX
149 EMISSIONS
MAi>S INUhX
P INDEX
PCPEX
151 fc..v;liJ5lLilNi>
MASS INDEX
PIND£X
PCPEX
152 EMISSIONS
MASS INDEX
PINDEX
1-tPtX
153 EMISSIONS
MASS INDEX
H INUCA
PCPEX
154 EMISSIONS
M M S S I N D fc X
PINDd/X
POPEX
MASS INDEX
PINDEX
PCPEX
iai EMISSIONS
NASS INDEX
PINDEX
«- PUMEX " ' - *
TCTAL.
87.
O.OO
o.oo
0.01
90.
o.oo
0.00
0.01
0.00
0.01
O.OJ
1362.
0.02
0.05
U . U 1
4A.
0.00
0.00
0.00
133.
0.00
0.00
0.01
0.00
0.01
0.01
0.01
0.01
0 .'0
-------
TABLE X.
CONTINUED
SOURCE
CATEGORY
183 EMISSIONS
MASS INOLX
H 1 N L) t A
PCPEX
205 EMISSIONS
MASb INDcX
PINOtX
POPEX
MASS INDtX
PINDEX
POPEX
209 EMS SICKS
MASS INDfcX
P INDEX
210 EMISSIONS
MAiSS INQEX
^- - . if1 -
PGP EX
211 EMISSIONS
* . A rf . *- »..»* *" *. X
P INDEX
PQPfcX
2. £. i fc .yi .; o j i u i-ic
MAi>S INDEX
PCPEX
230 E V ISS IONS
MASS INDEX
P INDtX
TOTAL
1618.
0.03
0.00
0.00
1648.
" Oi03 ~
0.05
0.10
7 UoO .
0.11
0.22
0.04
44 .
o.oo
0.00
C". O'O
7-^6.
0.01
ai*> ~*
* V J-'
0« 0 1
2A£9.
0M n-. ,,.,, ,,.,,,
U -4-
0.08
0.01
-... 3
0. 04
0.07
O.01
305.
O.OO
. 0.01
o.oi
PM
0.
0.0
C.O
1643.
C . 03
0.05
0 .
c.o
0.0
o.
0.0
c.o
1.
0.00
A A
* \J V
1590,
9.,,,,o..;s
0.05
. --Q-r
C.O
c.o
17.
0.00
c.oo
SO2
0.
0.0
C * 0
o.
- c,o - -
0.0
0 .
c.o
c.o
0.
0.0
c.o
735.
0.01
n IT
£74.
e,. fj I
C.02
--0
0.0
c.o
0.
c.o
c.o
NOX
0.
0.0
. 0
0.
O * C
0.0
0.11
0.22
<4.
0.00
0.00
0,
0.0
6f-
265.
n n n
0.01
-2290 .
0.04
0.07
0.
0.0
0.0
CO
1618.
0.03
u u
0.
w
0.0
,
o.o
0.0
0.
0,0
0.0
0.
o.o
o o
Oo
n n
0.0
.
0 »
0.0
0.0
0.
o.o
0.0
HC
0.
0.0
6n
V V
0.
u
O.O
-» - - --
0.0
0*0
0.
0.0
0.0
0.
0.0
On
0.
G. n
0.0
o
0.0
0.0
2 oti ^Q
0.00
0.00
-------
TABLE X«
CCNTINUE-D
SOURCE
CATEGORY
234
237
244
247
249
262
2 '6 3
267
EMISSIONS
MASS INDEX
PINDEx
POPEX
EMISS IONS
MASS INDEX
PINDdX
PGPEX
EM IbblONS
MASS INDEX
. PINDEX
POPEX
EMISS IONS
MASS INDEX
PINDEX
HUFr;*
EMISSIONS
I*ASS INDEX
F INOcA
POPEX
EMISSIONS
~WASS 'INDEX
PINDEX
-POPEX
LMISSICNS
MASS INDEX
PINDEX
PCPEX
EMISSIONS
MASS INDEX
P INDcX
crT-j-Ji- x
TOTAL
13 1 .
0.00
o.uo
C.OO
34.
U.UU
0.00
0.00
4 1^ .
0.01
0.01
0.03
219.
0.00
0.01
I/ . U 1
263.
0.00
0.00
0.01
51 .
.01
0.03
0.01
0.04
0. 10
0.02
5050.
O.Cd
0.20
O. 05
PM
0.
0.0
C.U
0.
c.u
C.O
'i 14.
0.01
C.01
219.
C.OO
C.01
0.
C.O
v * u
72.
» u u
C.OO
1 ii "7 -
Jl H 1 »
C.OO
C.OO
50.
C.OO
C.OO
S02
0.
C.O
o.u
0.
C.O
C.O
0 .
0.0
0.0
0.
C.O
0.0
0.
C.O
u
779.
0.03
0,04
0.09
5000.
C.08
C.20
NCX
0.
0.0
0.0
0.
-o.o
0.0
.
0.0
0.0
0.
0.0
0.0
0.
0.0
\J
0.
0.0
-A--!
0.0
0.0
0.
0.0
o.o
CO
0.
o.o
0.0
0.
o.o
0.0
1 1
0.0
0.0
0.
0.0
0.0
0.
0.0
81 v f>
fe \J
0.
9, n
0.0
n
0*0
0.0
0.
0.0
0.0
HC
131.
0.00
o.oo
34.
o .00
o.oo
" -1-
0.0
0.0
0.
0.0
0.0
23.
0.00
en n
0.
ei n
0.0
0.0
0.0
.,
o« °
0.0 °
0.0
-------
TABLE X.
CCNTINUED.
SOURCE
CATEGORY
268 EMISSIONS
MASS INDEX
P INUfcX
PCPEX
301 EMISSIONS
MAbb 1NULX
PINDEX
PQPEX
3Ub EMISSIONS
MASS INDEX
PINDEX
POPEX
306 EMISSIONS
MASS INDEX
PINDEX
PuP£X
333 EMISSIONS
MASS INDEX
PCPEX
345 EMISSIONS
WTvpo 1 IV U t A
PINDiiX
PCPEX
*» O t"liil.LiN3
fcASS INDEX
PINDEX
POPEX
347 UV ISSICNS
MASS INDEX
P INDEX
_ __ _ PCFirx
TOTAL
5900.
0.09
0 . 24
0.05
173.
0.00
0.01
0.01
» *J 9 .
0.02
0.03
0.05
40J.
0. 01
0.01
. 02
1560.
0.02
0.04
13.
0.00
0.00
i- _
0.00
o.uo
0.00
26.
0 . 0 0
c.oo
PM
0.
0.0
G.O
173.
0.00
C.01
599 .
C.02
0.03
403.
0.01
0.01
£48.
0.00
O i
13.
C.OO
'- "
C.OO
' 0 . 0 C
2c.
C.OO
c.oo
S02
NCX
5SOO.
C
0
C
0
C
0
0
0
0
e.
0
C
C
0
C
.09
-------
TABLE X.
CONTINUED
SOURCE
CATEGORY
349
350
351
,.
352
354
361
o/-i
3fc9
EMISSIONS
WASS INDEX
PINDEX
POPEX
EMISSIONS
MAbb INOkX
PINDEX
POPEX
EM 15b ILiNb
MASS INDEX
PINDEX
PCPEX
EMISSIONS
MASS INDEX .
PINDEX
HUHt X
EMISSIONS
M.ASS INDEX
p1 INDEX
POPEX
EMISSIONS
M"A S S i iV) O b X
P INDEX
PCPEX
EM IS i: IONS
MASS INDEX
P INDEX
POPEX
fc«I5S IONS
MASS INDEX
PINOtX
TCTAL
3710.
0.06
U.ll
0.23
1 120.
0.02
0.03
0.07
0.01
0.02
' 0.04
4C8.
C.01
0.01
u . u^
54.
0.00
0.00
0.00
967.
0 .02
0.03
0.01
0.00
0.00
0.00
215.
0.00
0.01
o-rQ-i
PM
3710.
O.C6
c. 11
1 120.
C.02
C.03
C 5 / .
C.01
C.02
408.
0.01
0.01
54.
c.oo
.00
S67.
C.03
0.00
C.OO
215.
0.00
0.01
SO2
0.
C.O
o.o
0.
0^0
c.o
0 .
c.o
0.0
0.
c.o
c.o
0.
c.o
. 0
0.
U . V
0.0
n j.
0.0
c.o
0 .
c.o
0.0
NOX
0.
o.o
0.0
0.
o.o
0.0
0.
0.0
0.0
0.
0.0
0.0
0.
0.0
* u
0.
0.0
B-.
0.0
0.0
0.
0.0
0.0
CO
0.
o.o
VrQ
0.
0-5-0- - -
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
HC
0.
0.0
O.O "
0. '
» o "
0*0
O -*
o.o
0.0
0.
0.0
0.0
0.
0.0
0.
0.0
9-,
0.0
0.0
o.o* w
0.0
-------
TABLE X,
CONTINUED,
SOURCE
CATEGORY
399 EMISSIONS
MASS INDEX
KiNOtX
PCPEX
400 EMISSIONS
MASS INDEX
PINDEX
PCPEX
4ui tMIiSluiNS
MASS INDEX
PINDEX
PQPEX
402 EMISSIONS
MASS INDEX
PINDEX
405 EMISSIONS
MASS INDEX -.
P Ls>4iJc./\
PCPtX
425 EMISSIONS
PIND5X
POPEX
MASS INDEX
P INDEX
PUPEX
427 LMISSIONS
MASS IVDfcX
P INDEX
... PCPC.X
TOTAL
56764.
0.89
1.11
0.33
25540.
0.40
0.50
0.20
0. 10
0.16
0.07
5735.
0.09
0. 17
^J ^^ ^^
173d6.
0.27
. i U
0.31
1009.
0.01
0.01
0.01
0.02
0.01
230157.
3.61
O'laj-
PM
22C60.
0.35
C. 6d
9 CO 7.
0.14
0.28
C.07
0.13
0.09
C.I 7
0.
C.O
f\ ....,.
« v
242.
- - coo
0.01
C.01
0.02
36C57.
C.57
1.11
SO2
0.
0.0
- " 0
128.
- - o.oo
0.01
c.oo
0.00
1 .
0.00
0.00
17384.
0.27
0.
C 0
0.0
0.0
C.O
0.
0.0
0.0
NCX
254.
0.00
» C 1
190.
0 .00
0.01
0.00
0.00
2, -
0.00
0.00
2.
0.00
Onn
0.
Go
0.0
O
0.0
0.0
0.
0.0
0.0
CO
6002.
0.13
' * U *J
3143.
"7 0 5
0.00
0.01
0.00
49.
0.00
0.00
0.
0.0
0^ o
767.
0. n i
0.00
0 A
0*0
0.0
194100.
3.04
0.11
HC
26448.
0.41
9ft !?
13O72.
1 »cU
0.21
0.02
0.02
190.
0.00
O.OO
0.
0.0
Q Q
0.
0.0
o
0.0
0.0
O. o
0.0 w
0.0
-------
TABLE X.
CONTINUED
SOURCE
CATEGORY
429 EMISSIONS
MASS INDEX
PINUhX
PCPEX
433 EMISSIONS
MASS INDEX
PINDEX
PCPEX
<*J<» tMIi>5»lONS>
MASS INDEX
PINDEX
POPEX
435 EMISSIONS
MASS INDEX
H INDEX
HliHt X
436 EMISSIONS
MASS INDEX
PCPEX
437 EMISSIONS
.^ MASS INDEX
PINDEX
PUPEX
= 4' 38 EMISSIONS
MASS INDEX
PINOEX
POPtX
440 EMISSIONS
MASS INDEX
PINDEX
-: n n is F x
TCTAL
2180.
0.03
0.06
0.03
430.
U.01
0.02
0.01
0.36
0.73
0.27
14506.
0.23
0.11
u . Go
84575.
1 .33
* 90
0.32
113.
0.00
C.OO
-> i «
0.00
0.01
0.01
7.
0.00
0.00
PM
1 719.
0.03
o.os
206.
C.OO
C.Ol
0.31
0.61
3425.
C.05
0.11
C.44
O /
113.
n n n
C.OO
±2} 1 t
0.00
C.OO
7.
C.OO
0.00
SO2
0.
c.o
cvo
224.
0 .00
0.01
C.05
0,12
0.
0.0
C.O
0.
0.0
0.
f Q
0.0
guf,
0.00
0.00
0.
C .0
c.o
NOX
2.
0.00
0-5-00
0.
1111 O?C "
0.0
0 .
0.0
0.0
0.
0.0
o.o
0.
0.0
o.
Q * Q
0.0
0.0
0.0
0.
0.0
0.0
CO
131.
o.oo
0*00
0.
O.O
0.0
0 .
0.0
0,0
11081.
0.17
0.01
56364.
.CL.88
0.
ft,- Q =
0.0
0.0
0.0
0.
0.0
0.0
HC
328.
0.01
.01
0.
0-7-0
0.0
0.0
0,0
0'.
0.0
o.o
0.
0.0
Q 0
0.
0,0 ,
0.0
o.o
0.0
o. %
0.0
o.o
-------
TABLE X.
CONTINUED,
SOURCE
CATEGORY
463 EMISSIONS
MASS INDEX
UNUEX
POPEX
471 EMISSIONS
MASS INDCIX
PINDEX
POPEX
4/2 EKISS IONS
MASS INDEX
PINDEX
POPEX
*73 EMISSIONS
MASS INDEX
PINDEX
HUPEX
474 EMISSIONS
MASS INDEX
I-1 1 INL/C. A
PCPtX
475 EMISSIONS
MA,Si> liNUl-A.
PINDEX
POPEX
i*7t> r r». i o .3 i L> N ^
.VASS INDEX
P INDEX
PCPF. X
477 EMISSIONS
MASS INDEX
p INDEX
TOTAL
524.
0.01
0.02
0.02
301 .
0.00
0.01
0.02
61. -
0.00
0.00
0.00
6.
0.00
0.00
0.00'
774.
0.01
. 0 si.
0.04
233.
0.01
0.01
Of)
0.00
,00
0.01
31451 .
0.49
0,05
PK
£24.
C.01
C. 02 '
201 .
C. 00
C.01
c.oo
c.oo
6.
0.00
c.oo
774.
C.01
233.
C.Ol
C.OO
0.00
0^02
C.O 3
SO2
0.
C.O
0.
.0
C.O
t
0.0
C.O
0.
C.O
0.0
0.
0.0
ft \J
0.
Q ^ Q .
C.O
0.0
C.O
15.
c.oc
0.00
NCX
0.
0.0
0-5 0
0.
V
0.0
1 »
0.0
0*0
0.
0.0
0.0
0.
0.0
en
C.
O 0
0.0
0 .
0.0
0.0
0.
o.o
0.0
CO
0.
0.0
V
0.
91 ft
' WV
0.0
. v . ,-
0.0
0.0
0.
0.0
0.0
O.
0.0
* w
0,
0 O
0.0
0 j
0.0
0.0
30475.
0.48
0.02
HC
0.
0.0
. O
0.
On
0.0
O.
o.o
o.o
0.
0.0
0.0
0.
0.0
en
# V
0.
0 0
0.0
0
0.0
0.0
M
0. w
0.0
0.0
-------
TABLE X*
CCNTINUED
SOURCE
CATEGORY
478
479
4Kb
494
495
498
HVV
500
EMISSIONS
MASS INDEX
P INDEX
HOPEX
EMISSIONS
MASS INDEX
PINDEX
POPtiX
fcM IbS 1UNS
MASS INDEX
PINDfeX
POPEX
EMISSIONS
MASS INDEX
F3 INDEX
HOHtX
EMISSIONS
KASS INDEX
M1NDEX
PQPEX
EMISSIONS
V:A5S INDEX
PINDEX
POPEX
t MISSIONS
MASS INDEX
PINDEX
PGPEX
EMISSIONS'
MASS INDEX
P INDEX
Pf,P!-'X
TOTAL
7.
0.00
u.uu
0.00
16.
" U.UU
c.oo
0.00
0.07
0.17
0.32
85.
0.00
0.00
(j 0 y
2895.
0.05
0.09
0.07
t.
i .00
0.00
0.00
0.
o o
0.0
0.0
o.o
0.
0.0
o.o
HC
0.
0.0
0.0
0.
o.o -
0.0
.
0.0
0.0
0.
0.0
0.0
0.
0.0
Qn
0.
f\ f\
0.0
0.00
0.00
0. o
0.0 °^
0.0
-------
TABLE X.
CONTINUED,
SOURCE
CATEGORY
502
504
620
522
523
524
525
527
EMISSIONS
MASS INDEX
I-' iNOtiX
POPEX
EMISSIONS
MASS INDEX
F INDEX
POPEX
EM 1 S3 IONS
MASS INDEX
P1NDEX
PCPEX
EMISSIONS
MASS INDEX
P INDEX
P' (_>P C_A
EMISSIONS
MASS INDEX
NDtX
PCPEX
fcMISSICNS
<*i A .3 is 1 lx u c. -s
F INDEX
HOPEX
MASS INDfcX
H INDEX
PQPtX
EMISSIONS
MASS INDEX
PI NDtX
TOTAL
3.
0.00
0.00
0.00
1 1 .
0.00
0.00
0.00
210.
0.00
0.01
0.01
<567,
0.02
0 .02
0 . 0 1
155.
0.00
V/ VJ
0.00
9
fi HH-1
0.00
0.00
.3 Q «
0.00
0.00
0.00
101 1 *
0.02
0.03
PM
3.
0.00
Q~^O 0
11.
C .'O 0
c.oo
i 10 .
c.oo
C.01
397.
0.01
C.01
155.
C.OO
u u
9.
Q ..Q 0
0.00
0.00
o.oo
1C03.
C.02
C.O 3
S02
0.
C.O
0 tO
0.
O
C.O
*
C.O
0.0
0.
C.O
0.0
0.
0.0
. u
0.
Q n
C.O
C.O
C.O
5.
c.oc
0.00
NOX
C.
0.0
-rrw
0.
c.c
*
0.0
0.0
0.
0.0
o.c
0.
o.c
8f\
* U
0.
6-s-O
0.0
0.0
0.0
3.
0.00
o.co
CO
0.
0.0
hrv
0.
1 U
0.0
0.0
0.0
300.
0.00
0.00
0.
0.0
90
* VJ
0.
0«0
0.0
"*0
0.00
0,00
0.
o.o
0.0
HC
0.
o.o
Brt,,
0.
9, n
' V w
0.0
0.0
o.o
270.
0.00
0.00
0.
o.o
On
0.
0 0
0.0
o
0.0
0.0
,_
o. 3
o.o
0.0
-------
TABLE X. CONTINUED.
SOURCE
CATEGORY
52d
530
a.5 1
533
541
544
b47
EMISSIONS
MASS INDEX
PINDEX
PCPEX
EMISSIONS
MASS INUbX
PINDEX
PCPEX
hM ISS lUNb
MASS INDEX
PINDEX
POPEX
EMISSIONS
MASS INDEX -
P INDciX
EMISSIONS
MASS INDEX
PINDEA
PGPEX
EMISSIONS
y A s s INDEX
PINDEX
POPEX
EMISSIONS
MASS INDEX
PINDEX
POPfcX
EMISSIONS
MASS INDEX
P INDtX
PHPtrX
TOTAL
6625.
0. 14
C.47
5S6.
O.02
0.03
0.06
15b(J.
0. 02
0.05
O.C8
28.
0.00
0.00
U 0 0
129.
0.00
.00
0.00
2.
0.00
0.00
0.00
0.00
0.00
1400.
0.02
0. 04
o . oa
PM
8C25.
0.14
O + cL i
3 ^ W
C.02 ' ~
C.03
1 500.
C.02
0.05
2.
0.00
0.00
129.
C.OO
U \J
2.
0.00
49 .
c.oo
c.oo
1400.
C.02
C.04
SO2
0.
C.O
e o
0.
0.0
0 .
C.O
C.O
2.
0.00
c.oo
0.
C.O
0.
r n
0.0
Q
0.0
C.O
0.
0.0
0.0
NOX
c.
0.0
0.
0.0
0.
0.0
0.0
IS*
0.00
0.00
0.
0.0
en
0.
f> . n
0.0
Q
0.0
0.0
0.
0.0
0.0
CO
0.
0.0
0.
o.o
0.0
0.
0.0
0.0
4.
0,00
0.00
0.
0.0
en
0.
Q- 0
0.0
Q
0.0
0.0
0.
0.0
0.0
HC
0.
0.0
o»o
0.
0.0
o . - -
0.0
0.0
2.
o.oo
0.00
0.
o.o
Go
0.
0.0
0-.
0.0
0.0
I-1
0. co
0.0
0.0
-------
TABLE X,
CONTINUED.
SOURCE
CATEGORY
54o EMISSIONS
MASS INDEX
H INDCA
POPEX
551 EMISSIONS
MASS INDEX
PINDeX
POPEX
D S> y EMISSIONS
MASS INDEX
PINOEX
POPEX
560 EMISSIONS
MASS INDEX
PINDEX
PGi-'llA
579 EMISSIONS
MASS INDEX
3 INDEX
POPEX
582 EMISSIONS
MMOO INUt-A
PINDEX
PCPEX
589 e M 1 o i> lUIMo
MASS INDEX
PINDEX
KUPEX
590 EMISSIONS
MASS INDEX
PINDEX
_ PHPEX
TOTAL
539.
0.01
0 .02
0.03
9320.
0.15
0.34
0.10
0.01
0.03
0.00
302*.
0.05
0. 09
u. 01
79.
0.00
VJ v
0.00
252.
« O U
0.01
0.01
1 fi lj
0.00
0.00
0 . 00
10.
0.00
0.00
u . GO
PM
£39.
0.01
c .02
3500.
0*05
C.ll
c *j 0 *
0.01
0.03
3023.
C.05
C.09
0.
C.O
2£2.
6- f\ n
C.O I
IT
0.00
0.00
10.
c.oo
c.oo
SO2
0.
0.0
c.o
5£20.
.09
C.24
C.O
0.0
0.
0.0
C.O
0.
0.0
6. o , .
u
0.
f\ f\
\J * U
. o.o
o
c.o
0.0
0, .
o.o
c.o
NOX
0.
0.0
o
0.
. o
0.0
0.00
0.00
1.
0.00
0.00
0.
0.0
0.
9n ...
. ^
o.o
Q
0.0
0.0
0.
o.o
c.o
CO
0.
o.o
1 * U
0.
. u
0.0
0.0
0.0
0.
o.o
0.0
0.
0.0
n n
0.
* V
0.0
Q
0.0
o.o
0.
0.0
0.0
HC
0.
0.0
\f
0.
en
* I/
0.0
0.0
o.o
0.
0.0
0.0
79.
0.00
f^ ^\ f\
0.
en
0.0
0.0
0.0
1-
u
0. &
0.0
0.0
-------
TABLE X.
CONTINUED
SOURCE
CATEGORY
591
592
593
595
60S
610
o 11
612
EMISS IONS
MASS INDEX
H I NUt A
POPEX
EMISSIONS
VAbb INUbX
F- INDEX
POPEX
EM 155 IUNS
MASS INDEX
PINDEX
PCPEX
EMISSIONS
MASS INDEX
PINDEX
PDPEX
EMISSIONS
MASS INDEX
p INDEX
POPfcX
EMISS IONS
MASS IND6X
PINDEX
POPEX
EMISSIONS
MASS INDEX
P INDEX
HGPEX
EMISSIONS
MASS INDtX
P INDEX
POPEX
TOTAL
20.
0.00
0.00
0.00
£932.
u.uv
0.10
0.03
/Ut>.
0.01
0.02
0.00
25910.
0.41
0.80
. 23
42.
0.00
. UU
0.00
1537.
0.05
0.01
0.05
0. 1 1
0.02
13295.
O.29
0.55
PM
20.
0.00
-c.oo
5 "532.
C.Ov
0. 16
7Uo.
0.01
C.02
25910.
0.41
C.80
42.
C.OO
8f\ f\
» U VJ
0.05
. .... » A a 1 .
0.05
C. 11
18295.
0.29
C.56
SO2
0.
C.O
0.0
0.
0.0
0.0
0 .
0.0
0.0
0.
0.0
0.0
0.
0.0
n
. w
0.
6-rrA
0.0
Q-m
0.0
0.0
0. .
0.0
C.O
NOX
0.
0.0
0.0
0.
0.0
0.0
0.
0.0
0.0
C.
0.0
0.0
0.
0.0
0.
Q . U
0.0
Ow
0.0
0.0
0.
0.0
0.0
CO
0.
o.o
-5-9
0.
. 0
o.o
0.0
0.0
0*
0.0
o.o
0.
0.0
V
0.
6-.-O
0.0
.
Q
0.0
0 .0
0.
0.0
0.0
hC
0.
0*0
-₯-6
0.
o - -
0.0
* - ... ...
0.0
0.0
0.
0*0
o.o
0.
0.0
en
0.
o o
0.0
o .
0.0
0.0
IT
0. o
0.0
0.0
-------
TABLE X,
CONTINUED.
SOURCE
CATEGORY
614
6 15
b 15
617
632
633
_ 53*-
637
EMISSIONS
JWASS INDEX
P 1NUEA
PCPEX
EMISSIONS
" 'MASS INDEX
P INDEX
POPEX
LM ISS IQNS
MASS .INDEX
PINDEX
POPEX
EMISSIONS
MASS INDEX
PINDEX
F-UH t X
EV-ISSIGNS
MASS INDEX
F I NDcX
POP6X
EMISSIONS
MASS INiDEX
PINOEX
PCPEX
**( 1 ^ c I U 1^ S
MASS INDEX
PINDEX
POPEX
EMISSIONS
MASS INDtX
PINDtX
TCTAL
899.
0.01
0,03
0.00
4103.
0. 06
0.13
0.05
1 7J34.
0.27
0.53
0. 10
46295.
0.73
1 .42
2 . ^v
3290.
0.05 -
U * A U
0.21
25241 .
HO
0.99
0.26
(j r. -f (j f
0. 15
0.37
0.14
361639.
b.67
0.73
O.S4
PM
£99.
C.01
0.03
4 103.
0.06
C.13
17^34.
C.27
C.53
46295.
0.73
1.42
3290.
C.05
V> i V
f06.
» u A
0.02
(: 3 *
0.00
y.oo
3414.
C.05
0. 10
SO2
0.
0.0
G"r6
O.
0.0
c.o
- "" 0.
0.0
c.o
0.
c.o
0.0
0.
0.0
. u
22447.
C.91
7'COt3 »
0.12
0.31
7322.
0.11
C . 3 C
NCX
0.
0.0
o*c
0.
-5-6
o.o
o * '
0.0
0.0
0.
0.0
0.0
0.
o.c
. 0
20S7.
..-u J
0.07
1 6 1 4
0.03
0.05
16 16.
O.C3
0.05
CO
0.
0.0
-rv
0.
-i"O
0.0
1 O»
0.0
0*0
0.
0.0
0.0
0.
0.0
* u
0.
0*0
0
0.0
0.0
344490.
5.40
0.20
HC
0.
0*0
8, rt
u
0.
u
\ a.o
1
0.0
o.o
0.
0.0
0.0
0.
0.0
* -
0.08
O.OS
-------
X.
CONTINUED
SOURCE
CATEGORY
638
639
642
645
646
647
: o**o
649
EMISSIONS
MASS INDEX
UNUbX
PGPEX
EMISSIONS
MASS INULX
PINOEX
PGPEX
kMlSblUNS
MASS INDEX
PINOEX
POPEX
EMISS ICNS
MASS INDEX
P INDEX
f-UHtA
EMISSIONS
MASS INDEX
P INuJEX
FOPEX
EMISSIONS
MASS INDEX
PINDEX
I-OPEX
tMlbilLiNS
MASS INDtX
FINDEX
PDPEX
fcNlSSICNS
MASS INDEX
H INDdX
H U*- fc X
TOTAL
£108.
0.08
0. 16
0.04
69.
u.uu
0.00
0.00
Ji!HO.
0.05
0.05
0.01
3000.
0.05
0.05
u u 1
389.
0.01
0.01
0.00
153.
1 . tru
0.00
o.oc
Z^jfc »
0.00
0.00
0.00
69,
0.00
0.00
PM
2£9.
C.OO
C . 0 1 ~
0.
ti .0
c.o
0.
0.0
0.0
0*
0.0
0.0
0.
0.0
O
0.
0.0
c.o
0.0
0.
0.0
c.o
502
3740.
0.06
-O-.TS
0.
0.0
0.0
.
c.o
0.0
0.
0.0
c.o
0.
0.0
(J
0.
r n
0.0
0.0
c.o
0.
0.0
c.o
NCX
88.
o.oo
o.oo
C.
0.0
0.0
.
0.0
0.0
0.
0.0
0.0
0.
0.0
0.
o n
o.c
0.0
0.0
0.
0.0
0.0
CO
983.
0,02
o.oo
0.
0.0
0.0
o.o
0.0
0.
0.0
0.0
0.
o.o
0.
9. n
0.0
Q
0.0
0.0
0.
0.0
0.0
HC
23.
-0.00
OTtro
69.
o .00
0.00
J2.OO .
0.05
0.05
3000.
0.05
0.05
389.
0.01
153.
ft-arfVfl
O.OO
gj^j
0.00
0.00
69. H
0.00 M
O.OO
-------
TABLE X.
CONTINUED,
SOURCE
CATEGORY
650
651
.
6S7
658
677
692
y o
706
EMISSIONS
MASS INDEX
PINDEX
POPEX
EMISSIONS
PINOEX
POPEX
EM ItiS IONS
MASS INDEX
PINOEX
PCPEX
EMISSIONS
*ASS INDEX
P1NDEX
EMISSIONS
MASS INDEX
1 INDEX
POPEX
EMISSIONS
P INDEX
POPEX
tM |- f f- « p f^ *7 .
MASS INDEX
P INDEX
POPEX
EMISSIONS
MASS INDEX
P INDEX
-PGPE-X
TOTAL
128.
0.00
o.oo
0.00
12.
v * O 0
o.oo
0.00
2055C I . "
3.22
1 .67
0.43
33061.
0.52
I .27
O 9o
8.
0.00
. oo
0.00
666.
en i
0.02
0.04
1 97 »
o.oo
O.Oi
0.01
15.
O.OQ
0.00
&v-3-e
I
PM
0.
0.0
.. -e-i-O
0.
u w
c.o
...
- 0 . '
0.0
c.o
2JO.
0.04
O.Ob
a.
c.oo
u u
£66.
Qn i
0.02
l"~ 7
0.00
0.01
0.
c.o
G.O
SO 2
0.
0.0
e-5-o-
12.
\J v U \J
C.OO
3^'93 1 *
0.58
1.50
27337.
0.43
1.11
0.
0.0
6' /\
u
0.
Sj n-
0.0
o
0.0
c.o
15. .
C.OO
c.oo
NOX
0,
0.0
-rv
0.
Q ^J
0.0
.. . _ IJtJJUJ-
0.04
0.08
2167.
0.03
0.07
0.
0.0
eLJ A ,
u
0.
Gf\
0.0
o
0.0
0.0
0.
0.0
0.0
CO
0.
0*0
hriJ
0.
w v/
0.0
2.60
O.10
0.
0.0
0.0
0.
0.0
0_L A
9 \J
0.
Qn
0.0
.
0 4.
0.0
0.0
0.
0.0
0,0
HC
128.
0.00
0.
41 * V
o.o
0.0
0.0
927.
0.01
O.OI
0.
0.0
0n
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c.
0.0
0 j.
0.0
0.0
1-
~
0. u>
0.0
0.0
-------
TA6LE X.
CONTINUED-.
SOURCE
CATEGORY
714
730
^31
737
739
741
7<*3
744
EMISSIONS
MASS INDEX
PINUeX
POPEX
EMISSIONS
MASS 1NULX
PINDEX
POPEX
tMlbblONb
MASS INDEX
PINDEX
PGPEX
EMISSIONS
MASS INDEX
PINDEX
EMISSIONS
MASS INDEX
' P INDEX
POPfcX
EMISSIONS
MASS INDEX
P INDEX
POPEX
p. MISS IONS
MASS INDEX
PINDEX
POPLX
EMISS IONS
MASS INDEX
PINDtX
PUP LA
TOTAL
- 232.
0.00
0.00
a.
o.oo
o.oo
0.00
0.00
0.01
0.01
7643.
0.12
0.22
o
468.
0. 01
\j » 0 1
0.00
679.
.01
0.01
0.00
OoeTO.
0.22
0.22
0.33
574*
0.01
0.01
PM
0.
0.0
CTO
0.
o.o
c.o
0.00
C.01
17.
0.00
c.oo
0.
c.o
0
0.
. v
0.0
t-fl -t
0.00 ,
c.oo
0.
0.0
c.o
SO2
229.
C.OO
O'.Oi
5.
0.00
0
0.0
c.o
3925.
0.06
0.16
0.
C.O
u
0.
C.O
0.0
0.0
0.
c.o
0.0
NGX
3.
0.00
0 .00
3.
o.oo
0.00
'- 0.
0.0
0.0
204.
0.00
0.01
0.
0.0
0.
Ql «-
0.0
Q-m
0.0
0.0
0.
0.0
0.0
CO
0.
0.0
0.
0.0
0.0
0.0
0 . -
0.0
o.o
0.
0.0
en
0.
0.0
0.0
0.0
0.
0.0
0.0
HC
0.
0.0
0.
0.0
0.0
0.0
3497.
0.05
0.06
468.
0.01
ei n i
679.
A- . . __
O . 0 1
13725. '
0.22
0.22
574. H
0.01 **
0.01
-------
TA81.E X, CCNTINUEO.
SOURCE
CATEGORY
745
746
7«f 7
748
...
749
7£0
'31
752
EMISSIONS
MASS INDEX
M1NUEX
POPEX
EMISSIONS
MASS INUtX
PINDSX
POPEX
t M 1 55 I OK S
MASS INDEX
P INDEX
POPEX
EMISSIONS
MASS INDEX
PINDEX
fUl-'t. A
t'MISSIQNS
MASS INDEX
INDEX
PUPEX
EMISSIONS
MAS>5 INOcA
PINDEX
POPEX
t M 1 O .31 U IN S
MASS INDEX
f- INDEX
POPEX
EMISSIONS
MASS INDLX
PINDEX
POPilX
TOTAL
38307.
0*60
O.bl
1.14
4531.
0 07
0.07
0. 13
3 1 3 *
0.05
0.05
O.CS
28V.
0.00
O.OO
u 00
58702.
0.92
. y*
0.37
1935.
UJ
0.03
0.01
- - A O*V?M -
**^.O * O *
0.67
0.6d
0.26
2230.
0.03
0.04
0»01
PM
0.
G.O
C.O
0.
0,0
C.O
0 *
0.0
0.0
0.
C.O
C.O
0.
0.0
e. f\ . ..-. , .
m U
0.
0,0
f\
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C.O
0.0
0.
C.O
C.O
SO 2
O.
0*0
C.O
0.
* V
C.O
0.0
0.0
0.
0.0
0.0
0.
C.O
u
O.
0.0
Ql -
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C.O
0.0
0.
0.0
o.o
NOX
0.
0*0
. O
0.
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0.0
*
0.0
0.0
0.
o.o
0.0
0.
0.0
9m f\
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0.
0.0
n
VJ .
0.0
0.0
0.
0.0
0.0
CO
0.
0.0
1 * u
0.
.0
0.0
0.0
0.0
0.
0.0
0.0
0*
0.0
9.. A ,_,.
*v
0.
0.0
91. . . M.
1 *
0.0
0.0
0.
0.0
0.0
HC
. - «-
38307.
0.60
0-11. A |
V O 1
4-581.
n 07
0*07
31 "^O .
0*05
0.05
289.
0.00
0.00
58702.
0.92
9. O A
*Vf
1935.
0.03
A o 0-7 e»
vdOrOi "
0.67
0.68
M
2230. ^
0.03
0.04
-------
TABLE X,
CONTINUED
SOURCE
CATEGORY
758
760
ft> I
762
776
782
7 b J
7<35
EMISSIONS
MASS INDEX
P INDEX
POPEX
EMISSIONS
MASS INDEX
PINDEX
POPEX
MASS INDEX
PINDEX
POPfcX
EMISSIONS
MASS INDEX -
PINDEX
f UK t A
EMISSIONS
MASS INDEX
POPEX
EMISSIONS
MASS INDEX
PINOtX
POPEX
hKli>SICN5
MASS INDEX
PINDEX
PCPEX
EMISSIONS
MASS INDEX
p INDEX
FUPtX
TOTAL
876.
O.01
O.O1
0.03
477.
U.Ui
0.0 I
0.01
0.41
0.39
0.52
4118.
O.06
0.06
0 » 0 ^
85.
0.00
00
0.00
4492.
' . C /
0.0*
0.1 i
1 .
0.00
0*00
0.00
301 .
0.00
O.Oi
0 * OO
PM
0.
c.o
cvo
0.
c.o
0.0
C.16
C.30
828.
0.01
0.03
23.
c.oo
« uu
1046.
0 0 rt " ~
C.03
0,00 .
C.QO
74.
0.00
C.OO
S02
0.
C.O
0.
0.0
c.o
1003*
0.02
0.04
210.
0.00
0.01
4.
0.00
6-v A C\
0.
c.o
0.00
0.00
Jl .
c.oo
c.oo
NOX
0.
0.0
: 0*0
0.
0T6
0.0
0.01
0*03
167.
0.00
, 0.01
4.
0.00
n nn
123.
0.00
0.00
0.00
37.
0.00
0.00
CO
0.
0.0
&TT&
0.
-g-0
0.0
1 40OO *
0.22
0.01
1664.
O.O3
O.OO
31.
O.OO
o oo
3077,
- - O . 0 5 -
0.00
O.OO
0.00
122.
0.00
0.00
HC
876.
O.OI
.01
477.
Or
0.01
GO2 .
0.01
0.01
1249.
0.02
0.02
23.
0.00
O OO
246.
0 00
0.00
0.00
O.OO
t-1
. 1-1 --
37. °*
0.00
0.00
-------
TABLE X.
CONTINUED,
SOURCE
CATEGORY
796
797
au«£
821
822
823
825
826
EMISSIONS
MASS INDEX
PINUtX
POPEX
EMISSIONS
MASb INDEX "
PINDEX
FOPEX
fcM H»S IUNS
MASS INDEX
PINDEX
POPEX
EMISSIONS
MASS INDLX
PINDEX
EMISSIONS
MASS INDEX
P 1 t^itj E A
PCPEX
EMISSIONS
"iASS INDEX
P INDEX
PCPEX
C ml f -C -^ T n ftr 1 - -
t_ M 1 i> -> 1 UIH J
MASS INDEX
PINDEX
POPEX
EMISSIONS
MASS INDEX
PINDEX
TOTAL
12376.
0.19
0.21
0.22
17.
0,00
0.00
0.00
10.
0.00
0.00
0.00
134.
0.00
0.00
Q » GO
137514.
2.ie>
3.09
5.49
49237.
f I
1.72
2.73
1 C 1 J, Q
4 »^ 4 T u
0.24
0.36
0.56
37,
0.00
0.00
PM
2239.
0.05
C'»-i-«
2.
o.oo
0.00
1 .
c.oo
0.00
11.
o.oo
c.oo
11297.
0. Id
u «j *j
5672.
4 U V
C.17
2950
C.OS
0.09
24.
C.OO
C.OO
SO2
£72.
0.01
OrO-2
2.
C .0 0
c.oo
0.00
c.oo
23.
0.00
C.OC
6C719.
0.95
<£. "r O
32219.
f '""I
W * 3 1
1.31
92 .
C.OO
0.00
0 . .
0.0
c.o
NCX
459.
O.01
.01
13.
CO
o.oo
0.00
0.00
3.
0.00
o.oo
1709.
-0.03
* uu
68C7.
e« I< t
0.21
yrr.^.i. .
0. 12
0.24
9.
0.00
o.co
CO
4023.
O.O6
o o
0.
u
0.0
o.oo
o.oo
95.
0.00
0.00
51292.
o.ao
91 n TI
* U «7
2837.
e--fy&
0.00
3105
0.05
0.00
2.
0.00
C.OO
HC
3978.
0.06
0.
0.0
0.00
0.00
2.
O.OO
O.OO
12397.
0.19
6r m S7.rt - . . ...
-------
TABLE X.
CONTINUED
SOURCE
CATEGORY
828
829
a JU
331
635
836
-_ : 337
838
» ; : '
EMISSIONS
MASS INDEX
PlNUtX
POP'EX
EMISSIONS
MASS INDEX
P INDEX
POPEX
t w ti>a IUINS
MASS INDEX
PINDEX
PCPEX
EMISSIONS
MASS INDEX
PINDEX
-------
TABLE X.
CCNTINUED,
SOURCE
CATEGORY
840
841
842
643
844
845
- d * t->
847
EMISSIONS
MASS INDEX
PINDEX
POPEX
EMISSIONS
MASS INDEX
P INDEX
PCPEX
EM IE SIGNS
I*ASS INDEX
PINDEX
POPEX
EMISSIONS
MASS INDEX
PINDEX
A
EMISSIONS
MASS INDEX
INDEX
PCPEX
EMISSIONS
C'AJo tfvllJIlX
PINDEX
POPEX
CM io o 1 U i> *j
MASS INDEX
PINDEX
PGPEX
EMISSIONS
MASS INDEX
PINDtX
--PCPLX
TOTAL
85871.
1.35
O.bS
0.60
21714.
0. 34
0.20
0.30
JOl 2.
0.05
0.04
0.05
7237.
0. 11
0.07
.10
U035b.
1.26
I f
I .90
125367.
1...-G TT
V f
1.16
1.87
** 1 4l ^n f 1 f i ""*
33.6*
11 .65
22.89
29S3/0.
4.63
1.89
2 « 6S
PM
5570.
0.09
<3"."-t"8-
2447.
C .04
C.08
95 .
0.01
0.02
615.
0.01
0.03
21 193.
C.33
ef~K,: ... ->
C.43
i i n tt **
0.17
0.34
633.
0.01
0.03
SO 2
99.
0.00
0*00
152.
OO
0.01
" «
0.00
0.00
50.
0.00
.00
2649. '
0.04
91 1
Li
882.
r n i
0.04
6\f **7
0.10
C.27
£00.
0.01
0.02
NCX
200.
0.00
*» «*
918.
* Ul
0.03
1 O9
0.00
0.00
304.
0.00
0.01
3532.
0.06
. ,| nl
1 "i
5297.
OPH
0.17
1Kn°^fi
2.48
4.96
27741.
0.43
Oi-87
CO
59703*
0.94
91 rt "^
12998.
1 to CU
0.01
- _, 0 -,
0.02
O.OO
4334.
0.07
0.00
3S320.
0.55
Oj. O !>
75044.
i 1 a
0.04
i & A a o a <£.
25.84
0.94
213086.
3.34
0.12
hC
19899.
O.31
032
5199.
eft ft
0.08
6ifiO j.
0.01
0.01
1734.
O.O3
0.03
17662.
0.28
aio
. C'O '
30019.
O_ fL~r
0.48
-*> \ f,A 1
5.04
5.14
53210. i-
0.83 *
0.85
-------
TABLE X.
CONTINUED
SOURCE
CATEGORY
848
849
UbU
851
852
853
854
856
EMISSIONS
MASS INDEX
MINUhX
POPEX
EMISSIONS
MASS INDEX
PINOEX
PGPtX
bMIbSIUNb
MASS INDEX
PINDEX
PCPEX
EMISSIONS
MASS INDbX
PINDEX
\* UMh X
EMISSIONS
MASS INDEX
H INDEX
PQPEX
EMISSIONS
MASS INDEX
PINOtX
PCPEX
EMISSIONS
I*ASS INDEX
PINDEX
HOPtX
EMISSIONS
WASS INDEX
P INDEX
-PUPEA
TOTAL
71811.
1 .13
U.J3
0.17
77336.
1 .21
1.60
2.75
y/24.
0. 15
0.20
0.26
32854.
0.52
0.76
1 . i2
1337.
0.02
0. G£
0.03
3180.
1 . 03
0.02
0.02
IcJ55.
0.50
0.32
O.fcS
1075.
0.02
0.02
PM
160.
C.OO
o.otr
lf.il.
C.02
C.05
1B8.
0.00
C.01
2862.
C.05
C.09
206.
0.00
U 1
100.
i . tro
C.OO
^w .
0.05
0. 10
94.
C.OO
C.OO
SO 2
98.
0.00
c.oo
3043.
0;05
0.12
3-sU
C.01
0.02
7494.
0.12
O.JO
40.
0.00
. \J U
20.
0.00
C.01
0.03
246. .
0.00
0.01
NCX
3493.
0.05
Q.lt
43107.
^-Q-i^r&
1.35
3353.
0.08
O.17
8646.
0. 14
O.27
98.
0.00
0_ f\f\
» uo
91.
81 . nn
0.00
g fl o ft *
0.03
0.06
263.
0.00
0.01
CO
57079.
0.89
O.O3
25355.
-J-H.Q
0.01
3255*
0.05
0*00
8069.
0.13
0.00
£14.
0.01
0,, , ft-f\
1 » W O
2527.
' Q . QA
0.00
1 npfi& *
0.29
0.01
263.
0.00
0*00
HC
10961.
0.17
O^ 16
4310*
*-. O r
O.07
537 * -
0.01
0.01
5763.
0.09
0.09
479.
0.01
0r (VI-
r* U 1
442.
& ot
0.01
77Q 1 .
0.12
0.12
189. g
O.OO °
0.00
,
-------
TABLE X.
CONTINUED,
SOURCE
CATEGORY
857 EMISSIONS
MASS INDEX
HINUtA
PCPEX
358 EMISSIONS
MAbb INDEX
P INDEX
POPEX
ooy t M i;>;> IUNS>
MASS INDEX
PINDEX
PCPEX
861 EMISSIONS
MASS INDEX
PINDEX
TCTAL
1977.
0.03
O.C7 ""
0.03
21174.
0.3J
0.09
0.11
2 1 v** o
0.50
0.51
0.8J
1341 18.
2.89
2.94
PM
245.
0.00
o-i-oi
44.
c.oo
0,00
0
0.0
c.o
0.
0.0
c.o
SQ2
1C61 .
C.02
0.04
27.
O.OG '
0.00
0
0.0
0.0
0.
c.o
0.0
NQX
637.
0.01
TV2
986.
0*02
0.03
o *
0.0
o.o
0.
0.0
0.0
CO
2.
0.00
1 .ou
17010,
0<27
0.01
*
0.0
0.0
0.
0*0
0.0
HC
32*
0.00
Onn
3105.
1 *O J
0.05
Jl 9*1 C! *
0.50
0.51
1841 IS*
2.89
2.94
HUHt A
(O
-------
I AiJLc XI
SOURCE
CATEGORY
OHO
622
do!
10
d-- v
66
* is
5 5
556
63 1
A 0 5
96
629
10.8
637
- - - a
657
t_Hl AtoU AUCR bULWCL L
SOURCE-CATEGGKY NAME
HA
EXT
EXT
MIS
XT
EXT
EXT
EXT
Tt< A
TRA
EXT
INO
so«_
SOL
IND
PSL
! RA"
I NO
EXT
INO
EXT
EXT
- CXT
EXT
SOL
EXT
-EXT-
1NO
SW
IND
LXT
INO
V5MOUI- I I DEN
PETROL
GOVERN
'tLBC GET
PETROL
HEAVY VEHI
BITUMINOU
STONE QUA
C fs, S i T C i ?'J
OPEN 8URM
Li Me y.-^G
LAQUcIR
CTHEP/.MOT
NATURAL GA
IKO-fi FRCO
L.-L I INVJ c: v AP
PROCESS G
RLS IDUAL
CCM.VERC IAL
ti ITUMINOU
RESICUAL U
ON SITE IN
CCKE
NATURAL C>A
FLUID CRA
MUNICIPAL
ASPHALT 1C
I TOW I NiJO
CTHER/NOT
^ 1NUEA. Pl-p-fKErt- A » >- u-
AtiiOUhlES IN r*iE CECREASING ORDER
OF POPEX.
PERCENT CONTRIBUTION TO INDICES1 RANKINGS
MI PI PC MI PI PO
GlOOMMcTU PU
G100MMETU CY
CUT STQNE-G
CALCINNC-KQ
GENERAL
SPECIFY IN
SINTERING G
GlOOMMbTl./H«
1 0 U ,v, fr O 1 L H u
10-100MM8TU
GENERAL (F
.VULTIPLE CH
GThEP SCURC
C 1 0 O M M LJ T L* ^Px^
SPECIFY IN
X
3.6
2.2
2.9
C . C
2.7
.74
« 4
it 9
.73
J
,41
.6G
- -- (7" *?
i» *_ i-
*.33
3.
i .C
tso
- le
1 .3
.40
*"* /I
5.7
3.2
rzn
8.1
3.1
2.9
6.7
1.7
1.7
. \j
1 .9
4.5
1 .4
i ,,,,*>
* &
1.2
.ao
.61
« ( 6
1.3
.56
1 .2
n; f
«U 1
2.2
2.3
.32
_...._. . r .
.37
.55
.99
,'36
.73
t27
1.7
12.
5.5
5.5
"V'O "'"""" """"
3.6
2.8
2.8
^ *5J
2.7
2.3
2.3
J, Q
to V
1 ,9
1 .3
1.1
* 1
i » i
.96
.65
.83
d T
» c J
I 71
, CD
'- \
.61
.60
.59
.,56
,52
.47
.43
A
1
1
1
_ _
1
2
2
1
i
2
X
2
2
2
2
2
1
2
2
2
1
2
1
2
2
1
*
1
1
1
1
1
1
1
1
1
I
2
2
1
2
I
2
1
1
2
2
2
2
2.
Z
Z
4-
i
1
1
1
"
1
1
1
______
1
1
1
....... _.. , _
1
i
1
"
Z
Z
z
1
2
2
2
Z
^
Z
z
2
2
2
2
2
M
NJ
-------
TABLE XI.
SOURCE
CATEGORY
36
63
830
7*9
73
97
399
436
4*5
405
at i
838
434
751
eso
796
79
400
737
72
70
45
c-i-*
130
746
612
477
1 u 1 U A I.
CUNTINUtO. - - .
SOURCE-CATEGORY NAME
EXT
EXT
EXT
bXT
P St
EXT
EXT
IND
I NO
INO
IND
EXT
IND
PSE
I N:J
TRA
IND
SW
EXT
I NO
IND
R7T
EXT
EXT
EXT
EXT
PSE
INU
S v»
IND
-5 TKTT
PERCENT CONTRIBUTION
MI PI
ELEC GEN HhSlUUAL t, 1UUMMB ! U'/HK
INOUST BITUMINGU G 1 OOK.V £T U SP
INOUSTR DISTILLATE
ELEC GEN NATURAL G G 100KM6 TU/HR
HL. 1 RU
INDUST
INDUST
PR I MAR
PR 1 MAR
SECOND
PKlMAR
Ht.i> i w EIN
CCMK/ IN
PRltfAR
PETRO
cT HUL
DIhScL
FCXTD/A
F< I fvt KA
INDUST
PR I MAR
CTrEH/
f i AtU KUU
3ITUMINOU
RESIDUAL
CCKE MET
HAi IN I
STEEL PRO
LEAD SMEL
CUKE-VET
0 r* fcl N tJUfi> H
GFF HIGHtaA
FEED/GRAI
INCINERAT
BITUMINGU
COKE-MET
SPECIFY I
bAbUL i IM urr nivjnwM
INDUST BITUMINGU
INOUST BITUMINOU
ELhC GEN PRCCESS G
-'i. 1 hUL
CCMMER
SURF A
MINE^A
CCMM I
SECOND
«i: X . P 1 -I
3ITUMINOU
ENAMEL
STONb QUA
GRAY 1RC.M
J 1 MJEX . PG f
tJKt« i Mi INV> P
10-100MNBTU
10-10OMMBTU
TGENERAL
ELECT ARC W
REVERB FNC
CTHEP/NCT C
OPNHEARTH N
u it_
SHIPNG/RECE
SINGLE CHAM
SPEC IFY IN
CTHER/NCT C
OVEN ChARGI
10-1 OOMf/BTU
10-100M!«BTU
G100MMB TU/HR
10-100MMBTU
GENERAL
TERT CRUSH/
CUPCLA
.34
.1 1
.35
.42
.28
.89
I .3
.67E-01
.27
* 3 *T
. 11
.36
.67
.15
.5SE-01
.19
I £ 4 E- 0 1
.40
. 12
. i
.32
tss
.24
.72E-01
9-p-r.^ A -t- ..
.49
1 .U
.81
«25
.95
.68
1.1
.22
.90
.17
.70
* 2 O
.18
.73
.68
9
.20.
.11
.21
0
. 12 .
.50
.22
.72
.11
1.2
.53
.73E-01
.56
.4aE-Ol
TO INDICES1
PO
43
.39
.39
. -17
,34
.33
.33
.32
.32
.31
. 3C
.23
.27
.26
.26
.23
.22
.20
.20
.18
/
. 16
.16
. 15
*
. 14
. 13
. 12
7 l
.11
RANKINGS
MI PI PO
2
2
2
2
2
2
1
3
2
2
2
2
2
3
2
3
2
2
2
3
2
2
3
2
J
" J-
2
i
2
2
2
2
2
1
2
2
2
2
2
2
4-
2
2
2
2
2
2
2
2
1
2
3
2
3
to
U)
C.
2.
2
2
2
2
2
»*
2
2
2
2
2
2
£
2
2
2
2
2
2
2
2
2
2
2
2
2
-------
TABLt XT%
SOJRCE
CATEGORY
551
205
o it>
762
402
547
531
103
350
401
635
4J =
530
104
JUb
26«
2o7
47**
692
106
527
147
63b
208
S52
CUT
<1 INUtU.-
SOURCE-CATEGORY NAME
1 R A
SGL
I NO
IND
i l\U
SW
EXT
IND
I NO
INO
EXT
I NO
IND
INO
EXT
l.NJ
IND
EXT
INO
I ND
INO
SOL
IND
IND
INO
EXT
1 ND
INO
EX/
INO
I NO
TRA
T P
blUNc UU«
MUNICIPAL
RESICUAL
CCKE-KET
P P I ,'/ L R
CEMENT MF
BRICK MAN
NATURAL G
EEL ruU
FEED/GRAI
COKE- MET
BITUM INCUS
StEtiL PnU
BRICK MAN
NATURAL G
STONE QUA
r CfkT 1L I L
H2S04-CCN
H2S04-CON
CN SITE IN
i r i -i ~~ " f f n T
C. 1 < -i- n /I^NJ 1
dHASS/ORO
IRON/STEE
PROCESS G
'EEO/ I VL
MILITARY
IND&.X. p-e
PERCENT CONTRIBUTION
Ml PI
KILNS-CCAL
SOAP/DET SP
CPEN STCKAG
SINGLE CHAM
LlONMBTU/hR
QUENCHING
KILNS
GRINDING-RA
10-100MNb.TU
TRANSFER/CO
OVEN PUSHIN
C OF" "tt N ER AL
DRYING-RAVi
LI OMMBTU/HR
SCREEN/CCNV
UK » t.K~ C,UUl_TC.
CTHER/NCT C
93.0 CCNVER
REVERB FNC
CTHcfr/NCT C
10-100MNBTU
C /" O-F -IE M T K'"^ 'i/ ^- -~ -
O C NIL t. W 1 fX o J V.
ROTARY CRYE
GIOON..VBTU/HR
GENERAL (T
TN i 1 r* /* 1 1 o i N K
.11
.15
.26E-01
27'
.65E-01
.31E-C1
.9CE-01
* 50c-" 0 1
.22E-01
..24E-01
.83E-01
. 1 8 E- 0 1
.98E-01
. 8 1 E- 0 I
. 1 6 E- 0 i
.34E-01
.64E-01
C t. u I
I 7 Si E- 0 1
. 4 7 E- 0 1
j. ? /i r f) 7
. 1 2 E- 0 1
. 1 0 E- 0 1
.63E-01
i_n.r-_ n -i
.16E-01
.62E-02
.80E-01
1 1
.2 1E-01
. SULU
,t>7E-0
.34
.51E-0
t
1
1
.53
.60E-01
73E-01
.17
-~ f^ *- rti *
. w1 OL0
.43E-0
.46E-0
.16
« 89C~" 0
.34E-0
.16
.18
11
1
.31E-0
.61E-0
.13
.24
.20
.44E-0
t29£-0
.24E-0
.20E-0
.15
. -. P Q £^ Q
i
1
1
in
~
i
1
1
1
i
1
1
-»
.31E-01
Ilo
0 't
. .19E-0
1
TO INDICES1
PO
. 10
.10
97E-01
* ^ 7EQ1
.89E-01
.89E-01
« 8bE-01
.62E-01
. 6 1 E- 0 1
.80E-01
7 ft f7 (-\ 1
« / ** L. U *
.69E-01
.67E-01
.67E-01
* /i i~ ^\ «
. c<* L o l-
.f 3E-01
.62E-01
52E-01
^nr" n i
.49E-01
.49E-01
,40E-01
ft T^ 01
.42E-01
.41E-01
,41E-01
1 4pg Q ^
.40E-01
.4QE-01
.40E-01
.._., ^QC 0 1
.35E-01
RANKINGS
MI PI
2
2
3
'2. "
3
3
3
3
3
3
3,
3
3
3
3
3
3
3
3
9
3
3
3
3
3
4
3
3
=»
3
2
3
1 2
3
3
2
3
3
2
3
2
2
3
3
2
3.
2
2
3
T
3
3
2
3
3
2
3
to
PO
2
2
3
3
-3- -
3
3
3
^
3
3
3
3
3
3
3
3
3
3,
1
3
3
3
7
3
3
3
3
3
3
3
..3
3
-------
TABLc XT.
SOURCE
CATEGORY
543
758
102
937
G57
244
t 1
151
463
306
lei 1
352
611
263
471
/"OU
211
152
47b
dc-c,
339
520
221
1 fv
247
642
426
731
' HI l Jl .1 <-.
CONTINUtO. ' - ~ - "- ~
SOUPCE-CATEGCRY NAME
INO
INO
PSE
EXT
IND
EXT
TRA
IND
cXT
EXT
IND
INO
i NU
TftA
INO
INO
Pbt
IND
IND
EXT
h'bt
EXT
IND
j H'\
INO
IND
INO
1 N J
INO
I NO
I'ND
IND
INO
-c: TMT
MINhKA
MINERA
MISC
INDUST
PR I MAR
CCK.M/IN
VESSELS
CHtM MFG
LLtiC GtN
CCMMLK
SEXCND
ChEM MFG
ci-ic.?*1 mt- 1>
Alii
FCUO/A
MINEF.A
S Ilk i- A
SECCND
INUliST
i«l l bv,
CHEM MFG
COiMtK
Sc.CC.ND
LIHh MHo
CEMENT' MF
CTHER/KCT
NATURAL G
IKLN PkUO
OIST ILLATE
RESIDUAL 0
PLASTICS
b i ( UM i i\^iij
OISTILLAT
ALUMINUM
FERTIuIZ
A i*l N' C N I A »SI
CIVIL
FEED/GRAI
STONE QUA
V AKN ibH/1 i
H2S04-CCN
bHASS/JKU
DIST ILLAT
EXhLCSIVE
OISTILLAT
'VLSbhLb Uic;bcL t-Uc.
f-OGO/A CTHEK/NJT
SECOND MISC CAST
ChEM MFG NITRIC AC
-1^*1 Mr ,v C N I
OTHER/
GEN V./Q
bLAST F
CTVER/N
POPEX
IN
IN
ACXID
NUT C
CGN
NC-A
OT C
PERCENT CONTRIBUTION
Ml PI
.SSE-02
. 14E-01
. 3 C £- 0 1
. JSE-01
. 3 I E- 0 I
» 1 i e 0 1
.42C-02
.62E-02
.63E-02
2 E 0 l
. bCE-01
,6
-------
TAtJLE XI,
SOURCE
CATEGORY
230
361
438
JO1
6^5
610
249
582
210
522
262
499
476
560
750
61**
4J7
'101
234
128
136
34C
714
795
37V
-- - .U t M li, -^
COT
M'| INUhU.
SOURCE-CATEGGPY NAME
INO
IND
I ND
IND
IND
IND
IND
IND
hXT
INO
EXT
EXT
HCst-
IND
IND
IND
1 ND
IND
IND
IND
PSE
IND
"F x r
IND
EXT
cXT
rxfy~
IND
INO
Sw
- IN J
IND
T rrsrC
Mt 1 AL HLA 1 ING U
CKEM'MFG PAINT MFG
FOOD/A GRAIN PRO
PRI.MAR SThEL PRO
CHuM NFMU I U / UK
.ULtfCfiESINGU
1 0-1 OOMVBTU
CTHEP/NCT C
TRANSFER/CO
OTHER /NUT C
MULTIPLE CH
i""l d'^l \ 'f**Uf
CUHuL/V r"i^%-
GENERAL
a
*
*
*
*
*
»
*
*
*
A
*
%
*
*
'ft
<3
*
*
2 1E-C2
4fcE-02
1 5 E- 0 1
25E-02
27E-02
47E-01
24E-C1
41E-G2
1 2 t G i
40E-02
14E-O2
2 IE- 02
3 £ E 0 1
12E-01
12E-01
C 7 fe 0 2
14E-02
47E-01
i/i r~ n *""
<* 1_ " U i
T'iE-Ol
18E-02
21E-C2
1 IE-01
I It- 01
I -JJH ' " 0 "*
a eh- 03
36E-02
47E-02
t/jp 03
fcfcE-03
51E-02
.30E-01
51E-02
.48E-0 I
.47E-0!
.42E-02
,33fc -Oi
.78E-02
.30E-02
.36E-02
. JUE--0 1,
.32F.-01
. 17E-01
.34C.-01
1 5j £"-0 1
.26E-02
28E-02
.93E-01
<. t * f-^ *-
.31E-C1
28c-0l
.35E-02
M**j*vn P ., i n ^
.21E-02
.26E-01
24E-0 1
'~" f" E 0 *
.17E-02
.S4F-02
.54E-02
i Of; ,. 02
. 13E-02
TO INDICES1 RANKINGS
PC MI PI
» 1 IE-01
.1 IE-01
. 10E-01
. IOE-01
- i<536 02
.91E-02
.90E-02
.66E-02
.83E-02
.82E-02
.80E-C2
.58E-.-02
.5TE-02
.54.^-02
f- t, r- f\ / »
* j 4 L O c.
.£2E- 02
.S2E--02
s 5.2.F. C 2
,50E-02
.47E-02
A ° F n "
.41E-C2
.37E-02
.36E-02
3 5 F ') °
.c3t-02
29E-02
,29£-02
28E02
.25E-02
«*
4
3
4
4
3
3
4
1
4
4
4
3
3
3
-P
i
4
3
A
3
3
4
rt
4
3
3
5
4
4
5
5
«*
4
3
4
3
3
4
4
4
4
3
3
3
i
4
3
f
-z.
4
4
3
3
4
4
4
i
NJ
PO
3
3
3
3
4
4
4
4
4
4
4
1
4
4
4
' °
4
4
4
4
4
4
A
4
4
/I
4
4
*
-------
TABLE XI »
SOURCE
CATEGORY
r~ 500
135
778
133
730
783
341
112
646
589
82o
7^1
650
1OO
479
524
37
651
730
821
525
677
647
f f
110
- * .' t \x .t ',.'
CONTlNUtO.
SOURCE-CATEGORY KAMt
IND
EXT
SW
I NO
Sw"
IND
EXT
IND
IND
IND
IND
EXT
INO
PSE
INU
IND
EXT
INO
IND
EXT
IND
EXT
IND
INO
EXT
MiJ
IND
IND
X l
EXT
-c r\n
SfcCLND
CCV-MEIR
CCMM-I
ChLM MFC
CLL AN
CCMM-I
MINERA
INDLST
XJJU/A
MINERA
PETRCL
MINERA
M 1 N t !* A
RES I DEN
V1NERA
CLEAN
Pt 1 KCL
PETRCL
INDUST
SECOND
M I N L R A
ELCC GEN
MINERA
C G M M E R
PETROL
INPRUC
RESIOLN
' 'JU <^S A
M I N L R A
ViUJD P
PtTv.CL
r"J ij U i. 1
INDcST
t'-1 x . i- I P
B I T U M I N 3U
INCINERAT
AM^CNIA W
DHYCLEAN1
APARTMENT
CASTABLb
LIQ PETRG
CERAMIC/C
MISCELLAN
GYPSUM MF
L l,v,e i-irG
WJUD
ASPHALT R
LLGP.EASTN
MlbCeLLAN
MISCELLAN
DISTILLAT
GRAY IRCN
ASPHALT M
RESIDUAL
CASTAELE
FLARES
NATURAL G
ANTHRACITE
i-; A i l -4 i- rt _
ASPHALT R
PULPOOARD
MISCtLLAN
O I 1 U i»l i IS UU
V.UOD
"T \ni- x . P -,
POP.CENT CONTRIBUTION
MI PI
KETCRT F1MC
L10WMSTU HAN
SINGLE CHAM
REGENERATOR
ST LUC. ARC
FLUE KEO
RAkf/ATL CRY
10-1 OOMf-'fiTU
DRY I NG
PIPE/VALVE-
CALCINEfi .
StCNCHY CRU
DIPPING CNL
CTHER/NGT C
MUMP bE ALS ' '
OTHER-GENL
10-100MN8TU
ELECT INCUC
SPRAYING ON
CIHER/NCT C
G 1 0 0 M V L! T L .' MR
NATURAL GAS
CThEP/NCT C
f.. -.-^ ,. . . . . , .
O IPP 1NG/SPR
F IDEREO^RC-
VESL RELIEF
U. A UT" M C 1 >J :lj K U
VnOCD toASTE
PP. P P"X
.56E-03
. 13E-02
,2£E-01
72E-02
.4VE-03
.20E-02
.22E-02
.4 IE 03
. 13E-01
.C1E-02
.24E-02
1C 01
.56E-03
I I l£-ol
.3 7E- 02"
.20E-02
.S7E-03
.2EE-03
7E~ 0 J
. 14E-03
.iee-02
. 77E-03
. C 9 L"~ 0 J
. 19E-03
. 13E-03
.61E-O3
, 13E-03
.24E-02
.49E-03
.81E-03
.14E-02
.93E-03
7 5 E 0 2
.59E-O3
.40E-02
.53E-02
dOfc~03
,26E-01
.62E-02
.48E-02
01
« 1 1E-02
IllE-01
38E 02
.20E-02
.23E-02
.49E-03
i4.t~-0 J
.2QE-03
,37E-02
15E-02
i J !_~"U«i
.49E-03
.30E-03
, 15E-02
* A 7l_ vJ ii
,6Ub O3
O"c: p ^
* *_ O *_ ~~ w *s
* «._** L_ (J
-------
lAuLh XU
SOURCE
CATEGORY
fO
706
605
345
~ 7*t-b
533
639
£09
**.}
649
1 11
591
nu<£
237
579
eS02
jy
590
797
4VO
j»^0"
473
S*
IND
I NO
acv.ur\u
INPKCC
MINE* A
FOUC/A
SURF A
MINERA
PETKCL
ChEM MFG
EL fct, vjfcN
PF.TKCL
I NO L S T
M I N t ft A
CHEM MFC
MTNEfcA
INDUST
hLLC GEN
MINtkA
INOtiT
SEC C NO
P f : I V A t<
SECGND
MI NEK A
vj^M T IK UN
BITUMINOU
PHOSPHATE.
Ffc£D/GKAl
GTHER/'NGT
BRICK MAN
ELCVv-DOioN
EXPLOSIVE
f\.ATUrvAL G
MISCELLAN
tftOOD
GYPSUM MF
ZINC 5 c C
VARNISH M
FIBERGLAS
OPEN BURN
DI S 7ILLAT
GYPSUM XF
INCINERAT
STEEL FOU
LEAD SWfcL
BRASS/6KU
CAS TABLE
PERCENT CONTRIBUTION
MI PI
PCVFRB FfrC
OTHEf./NGT C
ORY1 KG
SHIPING/REC
SPfct-'IFY I-1M
CURING GAS
rt/CLNTftCLS
HNG3 CONIC
IG^IOONNBTU
CCMPRESK SE
SMALL H/SNDF
OTHEF/NCT C
fC-l r\j«i\#«v.c.
GThEH/NGT C
GTHES/NCT C
KErLSt
G 1 G 0 r- MolL/ nR
CCNVEYING
CCNTKOLLED
INDUCTICN F
it *i c T 1'" i LJ ^ i \
C3 L A 5 ! ! U K N A
EL--IC1 INDUC
CURING GVc.N
» HE. U.J
.24E-03
..66E-03
*2eE-03
. 4CE 02
.44 £-03
.1 IE- 02
.6SSE-03
» 7 lf_ Co
. 1 IE- 02
.33E-03
.3 IE- 03
, jt; -- f * _ /* A
» 4 i L C 4
.53E-03
. 12E-C2
. IfcE-03
f l-t_~.U J
. 16E-03
27E-03
.^4E-04
ti r A *T
1 1_^ w J
.c^E-04
. 3 1 E- 04
* gg!_ BrS
.61E-03
.13E-02
.55E-03
*4fat: 6-2
.74E-03
.1 1E-02
.I4E-02
i J t ~\-' c.
. 11E-02
.61E-03
.&2E-03
ft T r~ f\ ft
v
7E 03
.36E-03
.35E-03
.33E-03
c'goc &3
.26E-03
.2*E-03
.24E-03
o j r- f\ ~3
' " ' g<5r^ ~H>-j -
.22E-03
20E-03
. 18E-03
(-* ^ rs -3
* i Ljfl " U o
. 15E-03
. 13E--03
. i IE- 03
.'90E--0*
.85E-04
*64C-04
i1 1 r -"j 4.
C VJ !_ U **
.35E-04
*21G-0'+
RANKINGS
MI PI PO
^r ^ <
5
5
5
,
S
4
5
i
4
5
5
,
" 5
4
5
5
5
5
5
K
5
5
9-
5
4
5
,
5
4
A
A
4
5
5
5
4
5
A
5
5
5
-&-
G
5
*A
5
5
5
S
5
5
5
'
5
5
5
5'
1
5
5
5
G
Q»
5
5
b
5
5
'MI-MASS INOLIX,
PI-PINDEX, PO-PCPEX
to
CD
-------
129
TABLE XII. ASSIGNMENT OF RANKS BASED ON PERCENT
CONTRIBUTIONS OF EACH OF THE SOURCE-
CATEGORIES TO POPEX, PINDEX, AND
MASS INDEX
Range of Percentages Rank
Index1 £1.0 1
0.1 ^ Index <1.0 2
0.01 i$ Index <0.1 3
0.001 ^ Index <0.01 4
Index <0.001 5
1Value of popex, pindex or mass index
Thus, the assignment of ranks is based on the order of magnitude of
percent contribution to each index. A source-category having a contri-
bution equivalent to the average of all categories, or 0.44 (100
divided into 227 source-categories) has a rank of 2. The source-
category representing a median popex contribution of 0.025 (source-
category 463) has a rank of 3.
Table XIII which was derived from Table XI shows the number of
point and area source-categories and their contribution to popex for
each of the rank groups.
RESULTS
General Observations
It should be evident from the construction of popex and its sub-
models that the results of popex estimate specific source-related air
pollution problems in terms of the impact on people. Sources in the
first rank-group contribute most to the popex on a percent basis
-------
130
TABLE XIII. POPEX RANK-GROUPS
Rank
1
2
3
4
5
Number
Point
6
40
63
44
41
ol
source-categories
Area Total
11
13
7
1
1
17
53
70
45
42
Cumula-
tive
total
17
70
140
185
227
Percent
Point
15.05
14.05
2.50
0.189
0.0155
contribution to
Area
62.27
5.71
0.21
0.001
0.0005
Total
77.32
19.76
2.71
0.19
0.016
popex
Cumula-
tive
total
77.32
97.08
99.79
99.98
100.00
-------
131
(Table XIII). Seventeen source-categories of rank one are responsible
for over three-fourths of the total popex, or three-fourths of air-
pollution-population-effect problem. Thus, a reduction by 50 percent
in the popex of the 17 source-categories of rank one would reduce the
total popex level by over one-third. On the other hand, even complete
elimination of the 87 source-categories of ranks 4 and 5 would hardly
be noticeable. It should be pointed out that this phenomenon of a few
source-categories contributing most, if not all, of the air pollution
problem is not unique to popex rankings. From Table XI it can be seen
that even in mass index or pindex, the source-categories of rank 1, as
defined by the respective indices, are responsible for over 70 percent
of the index level.
Area sources also tend to dominate the total as compared to point
sources (Table XIII): 194 point source-categories contribute 32 per-
cent of popex whereas 33 ;area source-categories are responsible for 68
percent of popex. It should be kept in mind that the classification of
the point source-categories is on a much more detailed basis than the
area source-categories. For example, there are 15 different categories
for external-combustion-industrial point sources burning bituminous
coal, but all of the area sources, similarly characterized, are in-
cluded in only a single category. Similarly, emissions from all types
of automobiles are lumped into one area source-category, but there are
ten different categories for manufacturing sulfuric acid. Eight of
these sulfuric acid manufacturing categories are differentiated only on
-------
132
the basis of variation in conversion efficiency between 93 to 99.7
percent. Finally, since the area source-categories tend to be large,
all except two are included in the first three popex rank-groups.
In the following section, the source-categories included in the
popex-rank-group one are discussed in detail. Source-categories of
the rank-group two are enumerated later in this chapter.
Discussion of Sources of the Popex-Rank-Group One
Seventeen out of a total of 227 source-categories each contribute
more than one percent to popex (Table XIII). Table XIV shows these
categories along with their popex levels. The first six categories are
point sources and the rest are area sources. In the point source
categories of rank one, there are only three basic source types: (1)
large boilers using bituminous coal, (2) mineral product industries
involving lime manufacture and stone-blasting operations, and (3)
i
solvent evaporation. Similarly, area source-categories of rank one
could be classified into four subgroups: (4) external combustion, (5)
solid waste disposal, (6) transportation, and (7) solvent evaporation.
The first three subgroups of point source-categories are sum-
marized in Table XV and are discussed below in detail. Since each area
source-category comprises a large number of small sources, similar
information on individual area sources is not available. A generalized
discussion of the area sources in rank-group one follows the discussion
on point sources.
(1) Large external combustion boilers. - The first subgroup of sources
consists of large bituminous coal fired industrial and electric utility
-------
TABLE XIV. SOURCE-CATEGORIES IN POPEX - RANK - GROUP ONE
Source Source Name of the source-category
category! classification
code
Popex Popex for each
subgroup
10
66
1-01-002-02
1-01-002-03
1-02-002-02
External combustion boiler - electric generation
- bituminous coal - >100 MMBTU pulv dry 4.45
External combustion boiler - electric generation
- bituminous coal - >100 MMBTU cyclose 3.59
External combustion boiler - industrial -
bituminous coal - >100 MMBTU pulv dry 2.30
10.34
(Subgroup 1)
595
617
3-05-016-04
3-05-020-08
Industrial process - mineral products - lime
manufacturing - calcining-rotary kiln
Industrial process - mineral products
quarry processing - cut stone-general
- stone
1.28
2.29
3.57
(Subgroup 2)
745
4-03-004-01
Point-source evaporation - surface coating
lacquer - general
1.14 1.14
(Subgroup 3)
u
OJ
-------
TABLE XIV. CONTINUED
Source Source Name of the source-category
category classification
code^-
Popex Popex for each
subgroup
822
Area source
External combustion - residential -
bituminous coal
5.49
823
828
Area source
Area source
External combustion - residential -
distillate oil
External combustion - industrial -
bituminous coal
2.78
12.48
23.56
(Subgroup 4)
336
Area source
External combustion - commerical -
institutional - residual oil
open burning
2.81
844
845
Area source
Area source
Solid waste disposal -
site incineration
Solid waste disposal -
industrial - on
industrial -
1'9° 3.77
(Subgroup 5)
1.87
U)
-------
TABLE XIV. CONTINUED
Source ^ Source Name of the source-category
category classification
code
Popex Popex for each
subgroup
846
847
849
851
Area source
Area source
Area source
Area source
Transportation
light vehicles
Transportation
heavy vehicles
Transportation
heavy vehicles
Transportation
rail
- land vehicles - gasoline
- land vehicles - gasoline
- land vehicles - diesel
- land vehicles - diesel
22.89
2.69
2.75
1.12
29.45
(Subgroup 6)
861
Area source Miscellaneous - solvent evaporation loss
5.48 5.48
(Subgroup 7)
See Appendix C.
u>
01
-------
TABLE XV. SUMMARY TABLE FOR POINT SOURCES IN POPEX - RANK - GROUP ONE
Subgroup Source-
category
number
1. External com- 9
bustion - large
boilers (>106 BTU/hr)
using bituminous
coal
10
66
2. Mineral-product 595
industries, such
Number of sources
in each county
3-Cook
3-Lake, 111.
6-Will
15-Lake, Ind.
7-Cook
2-Lake, 111.
5-Will
2-Porter
3-Cook
1-Grundy
1-Will
12-Lake, Ind.
6-Cook
Major
emis-
sions
S02
NOX',
PM
so2,
NOX
S02,
PM,
NOX
PM
(only)
Height
of
stack
(ft.)
225-
530
200-
400
0 -
200
45-75
Control devices Emission
(control ef- factor
ficiency, rating2
percent)
Electrostatic A
precipitator
(90-98)
High efficiency
wet scrubbers
(98-99)
Electrostatic A
precipitator (98)
High efficiency
scrubbers
No control equip, or A
Centrifugal col-
lector (85) low
efficiency fabric
filter (90)
Fabric filters (99.5) A
Wet scrubbers (99+)
Ratio of
emissions
US/Chicago
1.6
1.6
1.6
1.4
as lime manufactur-
ing, stone quarrying
-------
TABLE XV.
Subgroup
CONTINUED.
Source- Number of sources
category in each county
number
617 4-Cook
Major
emis-
sions
PM
(only)
Height
of
stack
(ft.)
75
Control devices
(control ef-
ficiency,
percent)
Largest source
does not have any
Emission
factor
rating2
C
Ratio of
emissions
US/Chicago
1.4
control equip. Some
of smaller sources
have centrifugal
collectors (70) or
fabric filters (99).
3. Point source
evaporation
745
5-Cook
1-Kane
HC
(only)
No No control
stacks, equipment
esti-
mated
plume ht.
20 ft.
B
0.6
£From Table XIV
Based on U. S. Environmental Protection Agency (24)
-------
138
*
boilers. Source-categories 9 and 10 are electricity generation
boilers which use pulverized coal. Source-category 10 uses cyclone
furnaces and has a low emission factor for particulates (24). Most of
the sources in categories 9 and 10 have high efficiency control equip-
ment and tall stacks (over 200 feet).
Source-category 66 is for industrial boilers and, although this
category, like categories 9 and 10, is also for boilers having greater
than 100 million BTU/hr as a design capacity; the boilers in category
66 are generally smaller. Capacities of the boilers in category 66
range from 2 to 20 tons of coal per hour «s compared to at least 50
ton per hour and quite often in excess of 100 tons, as in the case of
categories 9 and 10. On the other hand, quite often the load factor
for industrial boilers is greater than that for the electric utility
(boilers. Approximately one-half the total number of industrial boilers
use no control equipment while others use low efficiency fabric filters
i
i i
or centrifugal collectors. Stack heights for these boilers are
generally lower than that of the utility boilers (categories 9 and 10).
* \
Thus, in the case of industrial boilers, a combination of the factors:
higher load factor, lower efficiency control equipment, and low stacks,
results in a popex level which is comparable to that of the much larger
capacity electric utility boilers.
The emission factors ratings (24) for all of the source-categories
in this group are "A" which means that emissions data are most precise.
/
From Table II, the ratio of total U. S. to Chicago AQCR emissions is
-------
139
1.6. Thus, in a nationwide rating this group of sources could rank
even higher.
Control technologies for elimination or reduction of SO2 and NO
emissions are under development (48). In case of SO2, the efforts of
Industrial Environmental Research Laboratory, IERL (previously Control
Systems Laboratory, CSL) of EPA have accelerated the development of
flue gas cleaning technology which is now in the process of commercial-
ization. The early efforts of the IERL were directed towards develo-
ment of lime/limestone scrubbing processes and the present efforts are
directed towards increasing process reliability and lowering costs (48).
Other methods for flue gas cleaning under development through the IERL
include magnesium oxide, catalytic oxidation, sodium ion scrubbing with
thermal regeneration, etc.
In the case of NOX emissions, the technology is not as advanced
as for SO2 removal. Efforts directed by IERL include combustion modi-
fication to prevent NOX formation and flue gas cleaning to control NOX
emissions. Completion of major development efforts is not expected
before 1980 (48).
(2) Mineral products processing industries. - This subgroup includes
two source-categories: (a) manufacture of lime using rotary kilns, and
(b) stone quarrying operations. All the sources in this subgroup have
emissions of particulates only.
In the manufacture of lime, rotary kilns have much higher emissions
(200 Ib/ton processed) as compared to vertical kilns (8 Ib/ton processed)
-------
140
However, all six sources in the category (number 595} have moderate to
high efficiency control equipment and are located in densely populated
Cook County. An emission factor rating of B indicates the emissions
data are fairly accurate.
Among the four sources in the second source-category related to
stone-quarrying operations, the largest source processing over 4.5
million tons/year did not have any control equipment. This may be one
of the important reasons why this category has ranked so high in the
priority listings. The other three sources in this source-category
(number 617) process 25,000 to 60,000 tons/year and have low to moderate
efficiency control equipment. This category of sources has an emission
factor rating of C, which indicates that emission data may not be very
accurate. Thus, with improved emissions data, this category may or may
not have a popex rank of one.
This group of sources involving mineral product processing in-
dustries has nationwide emissions of 2.9 percent as compared to 2.1
percent in the Chicago AQCR. Thus, this category could rank somewhat
higher when nationwide emissions are considered.
An important consideration which would reduce the importance of
this category is that the emissions consist of mostly large-size
particles which may settle to the ground near the source itself and,
thus, significantly reduce the pollutant-exposure to people. Similarly,
larger particles (>2 microns) are less hazardous than finer particles
since the larger particles are deposited primarily in the nasopharyngeal
-------
141
region of the human respiratory tract (49).
(3) Point-source evaporation. - The source-category related to solvent
emission from surface coating (number 745) involves application of paint,
varnish, lacquer, or paint primer for decorative and protective purposes.
Many different types of industries are involved including automobile
assemblies, manufacture of containers, furniture appliances, plastic
products, etc.
All the emissions from this subgroup of sources are hydrocarbons
only. The methods for control of hydrocarbons include adsorption using
activated charcoal or use of after-burners. None of the sources had
any control equipment listed in the emission data. Similarly, none of
the sources had stacks. An emission factor rating of B implies the data
on emissions are fairly accurate. This category may have ranked some-
what lower nationwide since the ratio of nationwide versus Chicago AQCR
emissions is only 0.6.
A detailed study assessing industrial sources involving surface
coating operations has been performed (50) . It should be referred
to for additional information on prioritization of similarly categorized
different sources. Status of control equipment is also discussed in
detail in the same study (50).
(4 through 7) Area source-categories. - The last four subgroups on
Table XIV are area sources. In the NEDS emission data, the smallest
element considered for an area source is a county. All of the eleven
area source-categories are present in each of eleven counties in the
-------
142
Chicago AQCR. As described in the previous chapter, no stack heights
were given in the emissions data. Therefore, certain stack heights,
ranging from 3 to 25 feet, were assumed for all the area sources.
Most of the area source categories, with the notable exception of
automobiles, have little in the way of control equipment for emissions.
Subgroup 4, comprising industrial and residential combustion
sources, contribute almost 25 percent to the total popex. Again,
there is virtually no control equipment used in these categories.
Transportation (subgroup 6), especially automobiles, also con-
tribute heavily to the total popex. A substantial control program
initiated by the EPA is underway to reduce CO, HC, and NOX emissions
from automobile exhaust. It may seem surprising that less-recognized
air pollution sources such as heavy diesel gasoline vehicles and rail
transport are also included in this rank-group. The explanation could
i
lie in the large emissions of hydrocarbons and nitrogen oxides coupled
with low "stack" height.
Solvent evaporation contributes significantly (over 1/20 of the
total) to the total popex even though the emissions consist of only
hydrocarbon emissions which have higher tolerance factors as compared
to other pollutants (Table VI). The marketing and transportation of
petroleum products, especially gasoline retailing, comprises the
. * ^
largest fraction of emissions in this category. Control equipment in
the form of vapor recovery systems are used at various points in the
gasoline distribution system except at the last stage of distribution
or at the filling stations. The control efficiency ranges from 90-95
-------
14 J
percent. The emission data for solvent evaporation have a rating of
A, implying that the data are most precise. The ratio of U.S. to
Chicago AQCR emissions is 0.3, which indicates that the Chicago AQCR
data exaggerates the importance of this category.
Source-Categories of Popex-Rank-Group Two:
Table XVI lists source-categories having rank two. There are
53 categories in this rank-group. Popex levels of each are indicated.
The categories are diverse and include all major categories of
sources.
-------
144
TABLE XVI. SOURCE-CATEGORIES IN POPKX - RANK - GROUP TWO
Subgroup
EXTERNAL COMBUSTION (POINT)
Electric generation
Industrial
Commercial-institutional
INDUSTRIAL PROCESS
Food- agricultural
Primary metals
Secondary metals
Mineral products
Petroleum industry
Not classified
Source-
category
number
8
36
42
45
65
68
70
72
73
79
96
97
105
108
130
349
399
400
405
427
434
436
477
485
528
612
632
633
634
637
657
658
737
Popex
Source- Sub- Total
category total
5.89
0.46 1.43
0.43
0.39
0.15
0.61 4.32
0.43
0.16
0.16
0.34
0.20
0.71
0.34
0.78
0.59
0.14 0.14
6.23
0.23 0.23
0.33 2.26
0.20
0.31
0.83
0.27
0.32
0.11 0.43
0.32
0.47 0.80
0.12
.0.21
0.26 2.33
0.14
0.54
0..43
0.96
0.18 0.18
-------
TABLE XVI. CONTINUED
145
Subgroup
POINT-SOURCE EVAPORATION
Surface coating
Petroleum
SOLID WASTE DISPOSAL (POINT)
Government
Commercial-institutional
Industrial
EXTERNAL COMBUSTION (AREA)
Residential
Industrial
Commercial- institutional
SOLID WASTE DISPOSAL (AREA)
Residential
Commercial- institutional
TRANSPORTATION
Gasoline off-highway
Diesel
Air
Vessels
Gasoline handling
Popex.
Source- Source- Sub- Total
category category total
number
743
746
749
751
761
782
796
825
829
830
831
838
840
841
843
848
850
854
858
859
1.09
0.33 0.46
0.13
0.37 0.63
0.26
0.85
0.52 0.52
0.11 0.11
0.22 0.22
2.69
0.56 2.41
0.61
0.39
0.85
0.28 0.28
1.00
0.60 0.90
0.30
0.10 0.10
2.02
0.17 0.17
0.26 0.26
0.65 0.65
0.11 0.11
0.83 0.33
-------
146
CHAPTER IX
SENSITIVITY ANALYSIS OF THE POPEX MODEL
In the case of mathematical models with multiple input parameters,
it is often useful and illuminating to determine the extent of changes
in results derived from changes in the input values of different para-
meters. This process of analyzing the relative importance of parameters
is known as sensitivity analysis. Sensitivity analysis indicates whe-
ther the results of the model are sensitive to changes or uncertainties
in an input parameter. If changes in certain parameters affect the
overall results more than similar changes in other parameters, it would
be necessary to examine more carefully the input data and mathematical
expressions related to those particular parameters. On the other hand,
insensitive variables may require less detailed input data. Finally,
sensitivity analysis could be used to establish an order of priorities
as to which parameters or parts of the model need further refinement.
In this chapter, the method for conducting sensitivity analysis is
described first, followed by results of the analysis. The integrative
discussion of the approach utilized in the construction of popex and
the results of sensitivity analysis are given later in this chapter.
METHOD
To estimate the sensitivity of a parameter, the extent of change
in results from the base were calculated. In this sensitivity analysis
-------
147
the base-case input parameters were the same as those used to arrive at
the results described in the preceding chapter. Popex was applied to a
case where the input value of the parameters was increased by 50 percent.
above its base value (with all the remaining parameters kept unchanged
from the base-case values) . The popex levels for each of the source-
categories for this modified case were calculated and compared with base-
case results. The absolute values of the changes in popex for all cate-
gories were summed and the sensitivities of each of the parameters were
calculated as follows:
857
1(p0pex)NA, - (P°Pex)NA, with
base-case 50 percent
increase in
parameter A
Sensitivity of _
a parameter A NA =
number of
source-
categories
A similar procedure was followed for a case with a 50 percent reduction
in the input value of the same parameter. The whole process was re-
peated for each of the input parameters.
The theoretically maximum possible sensitivity for a parameter
from the above equation is 200 (Appendix E). However, as pointed out
in Appendix E, this would occur only in an extreme and unrealistic case
where all the non-zero popex levels for the different source-categories
would change to zero popex levels and popex for the rest of the cate-
gories would change from zero to non-zero values.
In order to further understand implications of the sensitivity in
the form of percent change (above equation), the results of the
-------
148
sensitivity analysis were also obtained in terms of changes in rankings.
Table XII shows the basis on which ranks one through five were assigned to
different source categories. Changes in the rankings for each source-
category from the base-case were computed. For example, the source-
category "industrial-processes-lime manufacturing" (number 595) had a
rank of one (popex level of 1.3 percent) in the base-case but when the
tolerance factor for particulates was increased by 50 percent, it had
a rank of two (popex level of 0.9 percent). This was considered as a
change in ranking of one and the absolute values of such changes were
summed for all the categories.
RESULTS
Table XVII lists results of the sensitivity analysis in the order
of decreasing sensitivity. Both the total percent change in results as
well as the change in rankings are listed. The results in the two forms
are quite similar, if not the same, and thus, only the results in the
form of total percent changes are referred to in the following dis-
cussion.
Decreasing the stack-heights of the area sources seemed to affect
results the most. However, sensitivity to decrease in height should be
viewed with caution since it represents the results from 33 area source-
categories extrapolated to all 227 categories. In any case, the height
of the stack is an important parameter for determining impact, since
concentrations of primary pollutants decrease at ground level as the
height of stack is increased (20).
-------
14 y
TABLE XVII. RESULTS OF THE SENSITIVITY ANALYSIS
Parameter
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
(16)
(17)
(18)
(19)
(20)
(21)
(22)
Height of the stack
PM tolerance factor
SO2 tolerance factor
HC tolerance factor
NOX tolerance factor
Ring radius
PM tolerance factor
SO2 tolerance factor
HC tolerance factor
Ring radius
NOX tolerance factor
°y
CO tolerance factor
Height of the stack
e
6
cy
CO tolerance factor
a
az
Windspeed
Windspeed
Change in
parameter
by 50
percent
Decrease
Decrease
Decrease
Decrease
Decrease
Increase
Increase
Increase
Increase
Decrease
Increase
Decrease
Decrease
Increase
Increase
Decrease
Increase
Increase
Decrease
Increase
Increase
Decrease
Total change
in Popex,
percent
32.91
32.7
25.2
23.8
17.8
14.3
13.9 '
12.5
10.6
10.6
7.8
6.9
3.1
3.0
2.6
2.1
1.5
1.0
0.6
0.1
0
0
Changes in
ranking
27
24
30
22
19
9
20
6
11
9
8
5
2
2
1
4
3
2
0
0
0
0
LExtrapolated from 4.. 8 for 33 area spurce-categories
-------
150
The next four parameters, in decreasing order of sensitivity
(Table XVII), are related to the tolerance factors. Decreasing the
tolerance factor of a pollutant means increasing the importance (or
toxicity) of that pollutant as compared to others. Thus, for a same
pollutant, results are more sensitive to a reduction than to an increase
in tolerance factors. Results are sensitive to the tolerance factors
of all the pollutants except CO. The tolerance factor for CO is very
large as compared to all the others (Table VI). Thus, an increase or
decrease of 50 percent does not alter appreciably the relative unim-
portance of CO when compared to the other pollutants.
Sensitivity of pollutant emissions was not checked, since mathe-
<
matically, increasing emissions of a pollutant is the same as decreasing
the tolerance factor of that pollutant. Thus, from the sensitivity of
* *.
the tolerance factors, it can be inferred that the results of the model
are sensitive to the emissions data.
Changing the ring radii also has significant effects on the results.
5
Ring radius, RR, is really a lumped parameter for population and disper-
sion of pollutants. The meteorological parameters do not seem to have
appreciable influence on the results. It was to be expected that emis-
sions and plume height would be more important parameters than meteoro-
logical parameters related to dispersion of pollutants (51).
i i
The changes in windspeed do not at all alter results. This is due
to the fact that the same windspeed is used for all the sources. Simi-
larly, the concentration of a pollutant and windspeed have a simple
inverse relationship.
-------
151
DISCUSSION
To develop a methodology based on damages associated with indivi-
dual sources of air pollution for priority ranking of the sources, it
was necessary to consider a substantial part of the air quality manage-
ment system shown earlier (Figure 1). Specifically, factors that needed
to be considered were (a) how do the pollutants disperse in the atmos-
phere, (b) how and to what extent are the pollutants transformed in the
atmosphere, (c) where are the people located with respect to sources
and what are the levels of concentrations of pollutants to which people
are exposed, and lastly, (d) what are the effects of this exposure on
people. Due to the complexities and numerous uncertainties associated
with each of these factors, it would have been extremely difficult to
construct a model which would rigorously simulate this emissions-to-
effects process. The research for this dissertation did not attempt to
remove the uncertainties. In this project, these uncertainties were
examined and analyzed. In light of the uncertainties, simple assump-
tions were made to circumvent the complexities of the air pollution
emission-to-effect process.
The most notable of the assumptions was that of a symmetric wind
rose. As described earlier (Table IV), the average annual resultant
windspeed for Chicago was from south-southwest at approximately 2 miles
per hour. This implies that the wind roses at the locations where data
for Chicago are monitored (Midway and O'Hare Airports) are not completely
symmetrical. However, there were more important considerations which
prompted the assumption of symmetric wind rose (Chapter IV).
-------
152
It was shown that the wind rose at different locations in a large
region could be substantially different. Annual wind data for other
locations is not available routinely. Lack of such spatial meteorolo-
gical data combined with the effect of Lake Michigan on recirculation
of pollutants and inadequate knowledge of distribution of people around
sources justifies the symmetric wind rose assumption.
The sensitivity analysis points out that even though the lumped
parameter for population exposure i.e. the ring radius was important,
in general, parameters related to meteorology were not significantly
important in the possible alteration of the results. The sensitivity
analysis also revealed that tolerance factors related to health effects
were, as a group, by far the most important for changes in the results.
In other words, the rankings could significantly change if the tolerance
factors are changed. On the other hand, an improvement in dispersion
modeling may change the results only to a limited extent.
Generally, the inability to quantitatively relate the effects of
air pollutants in the management of air quality is well recognized (52).
This weakness is inescapably reflected in this research. The use of
tolerance factors seemed justified in this first-generation pollution-
people-effect model. However, tolerance factors are only indirectly
based on health-effects and they cannot be substituted for healthr
effect dose-response curves. In this project, considerable time was
spent in analyzing the health-effects literature to examine the feasi-
bility of construction of dose-response relationships which are based
on effects of air pollution on the respiratory function. The
-------
153
relevant literature was reviewed and analyzed (Appendix A).
There are some excellent studies which have related specific air
pollution "dosages" to effects. These include the experimental studies
which, as a group, have been able to show specific dose-response rela-
tionships (Figures A-l, A-3 to A-5 in Appendix A). The results of the
epidemiological group studies are less-conclusive and, hence, are not
useful in the construction of longer term dose-response curves.
Appendix A assesses the air-pollution-pulmonary-effect studies
based on criteria for characterization of air pollutants and character-
ization of pulmonary function. It was concluded that the reason for
the lack of data was not due to the lack of enough studies as commonly
viewed but rather due to the following study-design shortcomings: (a)
an incomplete characterization of the concentration of air pollutants
whose effects were being studied and inadequate recognition of other
pollutants which were not being specifically studied but, nevertheless,
may have been present; (b) failure to use sufficiently sensitive tests
for characterization of lung function; and (c) inadequate elimination
of, or accounting for, other factors which may interfer with the air
pollution-effect results of a study. Details of this review and
assessment are given in Appendix A.
-------
CHAPTER X
IMPLICATIONS OF THE METHODOLOGY
In this chapter various factors that were implicit in the methodo-
logy are examined, analyzed, and highlighted. Based on a comparison
and analysis of the models, a simplified procedure for the ranking of
sources is presented. Next, limitations of the popex model and the
methodology are enumerated. Finally, recommendations for future re-
search are included.
APPROACH
In Chapter VIII, the results of the popex model were presented
with those of mass index and pindex (Table XI) . In order to under-
stand some of the factors related to the methodology which are implicit
in these models it is necessary to recapitulate how the three models:
mass index, pindex and popex, differ from each other. Figure 23 shows
the variables included in these models. Mass index considers only
the mass emissions of five pollutants; pindex, in addition, considers
tolerance factors of the pollutants. Popex includes considerations of
dispersion and population in addition to pollution emissions and toler-
ance factors. Thus, a comparison of the results of mass index and pindex
for a given source-category would indicate the influence of the tolerance
factors. Similarly, a comparison of the results of pindex versus popex
t
would show the effect of factors related to dispersion and population.
154
-------
155
Mass emission weights of the
five pollutants: PM, SC>2,
NOX, HC, CO
Tolerance factors for the
five emitted pollutants and
oxidants
Variables related to pollutant
dispersion: windspeed,
atmospheric stability, stack.
height
Variables related to population:
population, area, source-
receptor distances
Mass
Index
Pindex
Popex
Figure 23. Indices and Variables
-------
156
Finally, an analysis of the factors which differentiate the models
would allow one to examine implications which are. not seen otherwise.
For this analysis, two ratios are calculated for each of the
source-categories as follows :
pindex for source-category NA, percent
(PI\ p
MI/N, m
mass index for source-category NA, percent
»
PO \ popex for source-category NA, percent
,PI/ pindex for source-category NA, percent
k /NA
Thus, for example, for. the source-category 8 from Table X:
'PI\ 1.16
(
=2-42
g 0.48
PO\ 0.46
= 0.40
PI8 1.16
Table XVIII gives these ratios for all of the source-categories.
PI/MI
The mass index, pindex, and PI/MI are listed in the first three
columns of Table XVIII. The ratio PI/MI depends on the tolerance fac-
tors and mix of the pollutant emissions of a source category. CO has
the largest tolerance factor, whereas SO- has the smallest (Table VI).
Consequently, PI/MI is the largest or equal to 2.58 for the source-
categories which have only SO2 emissions. The categories with only SO2
emissions include boilers burning special fuel (category number 118, a
single source) , manufacture of sulfuric acid (category 268) and natural
gas flares (category 651) . On the other hand, PI/MI is the smallest
-------
TAtiLE XVIII. INDICESfPI/.MItPQ/PI AND SOURCE LOCATIONS FOR SOURCE CATEGORIES JN CHICAGO AQCR.
SOURCE
CATEGORY
8
9
10
11
36
37
39
42
43
45
65
66
68
70
7*
73
77
79
MASS
INDEX
0.432
5.037
2.728
0.011
0.446
0.002
0.001
0.346
0.001
0.550
0.239
1.9
-------
TABLE XVII U CONTINUED.
,£!£§§ PINDEX -El POPEX £0 ----- NUMBER OF SOURCES IN COUNTIES1 ----
INDEX fft FT12345678910U TOTAL
96
97
98
99
100
101
102
103
104
105
106
108
110
111
112
118
128
130
0.942
0.279
0.031
0.023
0.001
0.004
0.036
0.083
0.034
1.005
0.063
0.400
0.0
0.0
0.002
0.013
0.011
0.237
2.298
0.676
O.G73
O.U55
O.CC2
0.008
O.C68
0.155
0.061
2.238
0.155
0.990
O.C.01
OcOCl
0.005
0.033
0.026
0.528
2.44
2.42
2.37
2.40
2.37
2.27
1.86
1.86
1.77
2.23
2.46
2.47
1.82
1.86
2.41
2.58
2.34
2.23
0.714
0.333
0.089
0.014
0.001
0.004
0.030
0.080
0.062
0.782
0.041
0.592
0.0
0.0
0.002
0.008
U.004
0.139
0.31
C.49
1.22
0.26
0.33
0.53
G.44
0.52
1.02
0.35
0.26
C.60
0.43
0.33
0,29
C.25
0-14
0.26
9
29
13
0
0
3
7
31
17
1
0
0
0
0
0
0
0
3
0
2
0
0
0
0
1
4
0
0
0
0
0
0
0
0
Q
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
2
6
9
0
0
0
I
0
0
0
0
7
0
1
0
0
0
0
0
7
1
0
0
0
0^
0
0
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Q
1
6
0
0
0
0
0
13
0
Q
0
0
0
0
Q
0
0
0
0
1
0
0
0
0
0
2
0
0
0
0
0
0
0
o
0
0
2
25
0
0
0
0
4
36
3
0
0
0
0
0
0
0
1
0
36
6
4
5
1
3
13
4
4
47
16
4
1
i
1
1
Q
0
0
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
0
Q
48
73
17
5
1
6
29
103
34
52
16
4
2
1
1
1
1
20
1 l-COOKt2-DUPAGE,3-GRUNDY,4~KANE,5-KANKAKE£,6-KENCALL,7-LA!'.E,8-MCHEHRY,9-WlLLf 10-LAKE IN, K
il-PQRTEK
-------
TAdlE XVIII. CONTINUED.
KLt
LJftY
135
136
147
148
149
151
152
153
154
179
181
163
205
208
209
210
211
221
MASS 1
INDEX
0.001
0.011
0.006
0.001
0.001
0.004
0.021
0.001
0.002
0.003
0.012
0.025
0.026
O.L11
0.001
0.012
0.033
0.036
PINUtX
0.001
0.024
0.014
0.003
0.003
O.OC9
O.G49
0.001
O.C04
0.006
0.012
0.001
O.C51
0.221
0.001
0.032
0.080
0.072
«
1.43
2.25
2.32
2.18
1.85
2.19
2.30
1.65
1.72
2.00
1.02
0.04
1,96
2. CO
2.00
2.58
2.11
2.00
PUPhX
0.002
0.004
0.040
0.008
0.005
0.025
0.013
0.001
0.003
0.012
0.024
0.002
0.097
0.039
0.0
C.006
0.014
0.012
«
2.77
0.15
2.77
2.77
1.95
2.72
0.27
0.48
2.23
1.93
2.01
1.98
1.92
0.18
0.17
0.18
0.17
0.17
1
1
0
2
4
8
5
3
0
4
1
1
3
5
0
0
0
0
0
2
0
0
0
0
1
0
1
0
0
0
0 .
0
0
Q
0
0
0
0
Nur
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
IBtK
4
0
0
0
0
1
0
0
0
2
0
0
0
0
0
0
0
0
0
ui- :
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
>UUK<
6
0
0
0
0
0
0
0
0
Q
0
0
0
0
0
0
0
0
0
-to
0
0
0
0
2
1
7
1
0
0
0
0
0
0
0
0
0
0
I ft i.5J
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
luroi i
9
0
2
0
0
0
0
3
0
0
0
0
0
0
1
1
1
1
1
ICi -
LO
0
0
0
0
0
0
0
0
0
0
0
0
X
0
0
0
0
0
11 TOTAL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
2
4
12
6
14
1
6
1
I
3
6
1
1
1
1
i
1l-COOK,2-DL»PAGE,3-GRUNDY,4-KANE,5-KANKAKEEf6-KENDALL,7-LAKE,8-MCHENRY,9-WlLL,lO-LAKE IN,
11-PORTfcR
-------
TABLE XVIII. CONTINUED.
SOURCE
CATEGORY
2JO
234
237
244
247
249
262
26 J
267
263
301
305
J06
333
345
346
347
349
MASS
INDEX
0.005
0.002
0.001
0.006
0.003
0.004
0.013
0.039
0.079
0.092
0.003
0.016
0.006
0.024
0.0
0.001
0.0
0.058
PINOEX
0.005
0.002
0.001
0.013
0.007
O.OC4
0.034
O.C99
0.204
0.239
0.005
0.031
0.012
. 0.029
0.001
0.002
0.001
0.114
.p y
i3i~
1.07
1.02
1.02
1.96
1.96
1.02
2.53
2.55
2*58
2.58
1.96
1..96
1.56
1.17
1.96
1.96
1.96
1.96
POPEX
0.011
O.G04
0.0
0.025
0.012
0.009
0.005
0.018
0.049
0.049
0.009
0.050
0.025
0.043
0.0
0.003
0-002
0.223
ft
*.09
1.96
0.28
2.00
1.79
2.04
0.16
0.18
0.24
0.21
1.76
1.63
2.00
1.52
0.59
1.98
1.90
2.00
»«[
I
2
1
0
1
1
i
0
0
0
0
1
1
1
3
1
2
1.
1
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
- NUMBER
3 4
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
OF i
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
iOURI
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
:ES
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
IN COUNT]
8 9
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
2
0
0
0
0
0
0
0
0
0
0
IPS1
Itj
10
0
0
0
0
0
0
0
0
1
2
0
0
0
5
0
0
0
0
11 TOTAL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
1
1
1
1
1
2
1
, 2
1
1
1
9
2
2
1
1
1i-COOK,2-DUPAGEf^-GkUNDY,4-KANEf5-KANKAKEE,6-KENDALL,7-LAKe,8-MCHENRY,9-«ILL,lO-LAKE IN,
11-POKTtK
-------
TABLE XVIII. CONTINUED.
IKLt MAbb P INDEX PI POPEX _PU
iORY INDEX Hi 1*1
350
351
352
354
361
379
389
399
400
401
402
405
425
426
427
429
433
4-34
0.018
0.010
0.006
0.001
0.015
0.001
0.003
0.890
0.400
0.098
0.090
0.273
0.016
0.012
3.608
0.034
0.007
0.356
0.034
0.020
0.013
O.CQ2
0.030
0.001
0.007
1.113
0.499
0.156
0.172
0.704
O.C08
0.023
1.220
O.Obti
0.015
0.7^7
1.96
1.96
1.96
1.96
1.S6
1.96
1.96
1.25
1.24
1.59
1.91
2.58
0.50
1.96
0.34
1.70
2.29
2.C4
0.069
0.040
0.022
0.001
0.010
0.002
0.013
0.327
0.202
0.067
0.088
0.312
0.012
0.012
0.833
0,029
0.005
0.270
2.00
2.00
1.76
0.33
0.35
1.90
1.90
0.29
0.40
0.43
0.51
0.44
1.50
0.51
0.68
C.50
0.35
0.37
i
1
1
i
0
0
1
1
0
1
1
1
0
1
0
2
1
i
0
2
0
0
0
0
0
0
0
0
0
0
0
0
c
0
0
0
0
0
- NUf
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
IBtK
4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
ui- :
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
ttJUKt
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-tb
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
in ui
d
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
JUINi
9
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Ito -
10
0
0
0
1
7
0
0
21
21
21
21
21
0
20
14
11
8
47
11 TOTAL
0
0
0
0
0
0
0
2
2
2
2
0
0
2
0
1
0
0
1
1
1
1
7
1
1
23
24
24
24
21
1
22
16
13
9
47
l-COOK,2-DUPAGEf3-GRUNDY,4-KANEf5-KANKAKEE,6-KENOALL»7-LAKE,8-MCHENRY,9-WILL,10-LAKE IN,
il-PURTER
-------
TAiLE XVIII. CONTINUED.
>nv» l_
iO*Y
435
436
437
438
440
463
471
472
473
474
475
476
477
478
479
485
494
495
n« jo
INDEX
0.227
1.326
0.002
0.002
u.o
0.008
0.005
O.OOi
0.0
0.012
0.004
O.OOi
0.493
0.0
0.0
0.067
O.OOi
0.045
r AWUCA
0.112
0.9CO
0.003
0.005
0.0
0.016
0.009
0.002
0.0
0 . 024
0.007
0.003
0.048
0.0
0.0
0.168
O.CC3
0.089
fit
0.49
0.68
1.96
2.06
1.96
1.S6
1.96
1.96
1.96
1.96
1.96
1.96
0.10
1.96
1.96
2.50
1.97
1.96
rurCA
0.064
0.324
0.005
0.010
0.0
0.025
0.017
0.003
0.0
0.042
0.013
0.005
o.ior
0.0
0.001
0.321
0.004
0.074
ft
0.58
0.36
1.34
1.98
0.28
1.54
1.83
1.50
C.i9
1.75
1.79
1,88
2,24
i.73
1.46
1.91
1.35
0-84
1
1
4
2
2
0
1
3
1
0
2
2
1
4
2
1
t
1
2
2
»» *IIW«**
-------
TABLE XVIII. CONTINUED.
KUC
ORY
498
499
500
502
504
520
522
523
524
525
527
528
530
531
533
541
5*4
546
PIAii
INDEX
0.0
0.003
0.001
0.0
O.U
0.003
0.015
0.002
0.0
0.001
0.016
0.135
0.016
0.024
0.0
0.002
0.0
0.001
KlNUtA
0.0
0.003
0.001
0.0
0.0
0.006
0.017
0.005
0.0
0.001
0.031
0.265
0.031
O.C48
0.001
0.004
0.0
0.002
ft
1.96
1.C3
1.96
1.96
1.96
1.96
1.10
1.96
1.96
C.97
1.97
1.S6
1.96
1.96
1.69
1.96
1.96
1.96
HUKfcA
0.0
0.005
0.002
0.0
0.001
0.012
0.006
0.001
0.001
0.001
0.040
0.469
0.063
0.081
0.0
0.002
0.0
0.001
H
0.35
2.00
1.33
1.91
2.00
1.93
0.34
0.21
2.31
0.91
1.29
1.77
2.07
1.69
0.35
0.40
0.34
0.41
1
0
1
1
1
1
1
1
0
1
1
6
6
1
1
0
0
0
0
2
0
C
0
0
c
0
0
0
0
0
0
0
0
0
0
0
0
0
- NUNBtK
3 4
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
ur :
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
iUUK(
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-ti IN w
7 8
0
0
0
0
0
0
0
1
0
0
2
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
JUN 1
9
0
0
0
0
0
0
1
1
0
0
c
0
0
0
0
0
0
0
ICd -
10
1
0
0
0
0
0
2
0
0
1
0
0
0
0
2
2
1
3
11 TOTAL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
4
2
1
2
8
7
1
1
2
2
1
3
1 i-cOQKt2-DUPAGE,3-GRUNDY,4H
-------
TAbLE XVIII. CONTINUED,
SOURCE
CATEGORY
547
548
551
559
560
579
562
589
590
591
592
593
595
605
610
611
612
614
MASS
INDEX
0.022
0.008
0.146
0.013
0.047
0.001
0.004
0.002
0.0
0.0
0.093
0.011
0.4G6
0.001
0.024
0.055
0.287
0.014
PINDEX
0.043
0.017
0.343
0.026
0.093
0.001
0.008
O.OC5
0.0
0.001
0.182
0.022
0.797
0.001
0.047
0.107
0.563
0.028
u-
1.96
1.96
2.35
1.96
1.96
1.02
1.96
1.96
.1.96
1.96
1.96
1.96
1.96
1.96
1.96
1.96
1.96
1.96
POPEX
0.082
0.032
0.100
0.001
0.005
0.0
0.003
0.001
0.0
0.0
0.032
0.001
1.283
0.0
0.009
0.021
0.118
0.005
ft
1.91
1.93
0.29
0.06
0.06
0.10
1.08
0.28
0.29
0.29
0.18
0.05
1.61
0.27
0.19
0.19
0.21
C.18
1
1
1
0
0
0
0
1
0
0
0
1
0
6
0
0
0
1
0
2~"
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NUMBER OF SOURCES
3 4 5 67
0
0
0
2
2
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
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
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
1
0
0
0
0
IN COUNT I
8 9
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
5
4
1
PS*
to
10
1
0
1
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
11 TOTAL
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
2
1
1
2
2
1
3
2
1
1
2
2
6
1
6
6
5
1
1l-COL)K,2-DUPAGE,3-GRUNDYf4-KANE,5-KANKAKEt,6-KSNCALL,7-LAKE,8-MCHENRY,9-WILL.10-LAKE INt £
il-PURTtR
-------
TABLE XVIII. CONTINUED.
iUUKCt
CATEGORY
615
616
617
632
633
634
637
638
639
642
645
646
647
648
649
650
651
657
MAbi PINUfcX
INDEX
0.064
0.272
0.726
0.052
0.396
0.15u
5.673
0.080
0.001
0.051
0.047
0.006
0.002
0.004
0.001
0.002
0.0
3.223
0.126
0.533
1.424
O.I 01
0.995
0.367
0.729
0.163
0.001
0.052
0.048
O.C06
0.002
O.OC4
0.001
0.002
0.0
1.673
tt
1.96
1.96
1.96
1.96
2.51
2.45
0.13
2. C4
1.02
i.02
1.C2
1.02
1.02
1.02
1.02
1.02
2.58
0.52
PUPtX
0.052
0.097
2.289
0.210
0.262
0.141
0.540
0.040
0.0
0.012
0.009
0.001
0.0
0.001
0.0
0.001
0.001
0.432
»
0.41
0.18
1.61
2.07
0.26
0.38
0.74
0.24
0.22
0.23
0.19
0.23
0.19
0.2J
0.20
0.39
1.18
0.26
l"
2
0
4
1
0
1
2
0
0
0
0
0
0
0
0
0
1
0
"2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
" NUMBtK
3 4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Ut- iUUKLti
567
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
0
0
0
0
0
0
0
0
0
0
0
iN uuuni ica
8 9 10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
3
5
0
0
0
0
1
0
1
1
1
1
1
1
1
0
0
0
0
0
0
0
8
8
2
2
0
0
0
0
0
0
0
1
0
10
11 TOTAL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
6
4
1
8
9
5
2
1
1
1
1
1
1
1
1
1
10
1 i-COOK,2-DUPAGEf3-GRUNDYf4-KANE,5-KANKAKEE,6-KENDALL,7-LAKE,8-MCHENRY,9-WILL,10-LAKE IN,
11-PURTER
-------
TABLE xvni. CONTINUED.
SOURCE
1* » ^ ^k
.DRY
658
677
692
693
706
714
730
731
737
739
741
743
744
745
746
747
743
749
i ir^ ****
INDEX
0.518
0.0
0.010
0.003
0.0
0.004
0.0
0.004
0.120
0.007
0.011
0.217
0.009
0.601
0.072
0.050
0.005
0.920
r * iitxw. /\
1.271
0.0
0.020
0.006
0.001
0.009
0.0
O.C07
0.222
0.007
0.011
0.222
0.009
0.612 .
0.073
0.050
0.005
0.937
ft
2.45
1.96
1.96
1.96
2.58
2.58
2.36
1.96
1.85
1.02
l.CZ
1,02
1.02
1.02.
1.02
1.02
1.02
1.02'
i-urc A
0.964
0.0
0.041
0.011
0.0
0.003
0.001
0.011
0.176
0.002
0.001
0.325
0.018
1.142
0.133
0.085
0.0
0.373
flf
0.76
1.96
2.00
1.83
0.60
C.31
1.88
1.50
0.80
0.22
0.09
1.46
2-. Go
1.87
1.82
1.68
0.06
0.40
1
4
1
1
1
0
1
1
1
2
0
0
23
2
5
1
2
0
4
2
0
0
0
0
0
0
0
0
.0
0
c
2
0
0
0
0
0
0
nu
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
HOCK
4
0
0
0
0
0
0
0
0
0
1
0
12
0
1
2
0
0
0
ur ;
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
sucmt
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
,Cd il
7
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
1
* V.
8
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
.UUIMI J
9
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
101
ica ^-
10
7
0
0
0
L
8
0
0
5
0
0
0
1
0
1
1
0
1
11 TOTAL
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
11
1
1
I
1
9
1
1
9
1
1
45
3
6
4
3
1
107
1 i-COOK,2-DUPAGEt3-GRUNDY,4-KANE,5-KANKAKEE,6-KENDALL,7-tAKE,8-MCHENRY>9-WlLLflO-LAKE IN,
U-PORTER
-------
TABLE XVIII. CONTINUED.
RCE
DRY
750
751
752
758
760
761
762
778
782
783
795
796
797
802
821
822
823
825
MASS
INDEX
0.030
0.672
0.035
0.014
0.007
0.412
0.065
0.001
0.070
0.0
0.005
0.194
0.0
0.0
0.002
2.156
0.772
0.237
PINOEX
0.031
0.685
0.036
0.014
0.008
0.388
O.C60
0.001
0.042
0.001
O.C05
0.206
O.OC1
0.0
0.001
3.C91
1.722
0.359
ft
1.02
1.02
1.C2
1.02
1.02
C.94
0.93
1.03
0.59
1.21
1.13
1.C6
2.C6
1.17
0.69
1.43
2.23
1.51
POPEX
0.005
0.262
0.006
0.030
0.014
0.521
0.089
0.002
0.107
0.002
0.003
0.224
0.0
0.0
0.001
5.489
2.784
0.553
T#
0.16
0.38
0.16
2.17
1.88
1.35
1.49
1.59
2.58
2.77
0.53 -
1.09
0.15
0.60
0.38
1.78
1.62
1.55
1
0
2
0
1
1
9
4
1
3
1
1
5
0
0
0
1
1
1
2
0
0
0
0
0
0
0
0
0
0
0
.0
0
0
0
1
1
1
NUJ
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
IBfcR
4
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
1
1
OP :
5
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
1
1
S>OUR<
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
-fcb
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
IN C
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
UUNI .
9
9
96
8
0
0
0
1
0
0
0
0
2
1
0
0
1
1
1
Lti ^
10
0
1
0
0
0
0
0
1
0
0
0
0
0
1
1
1
1
1
11 TOTAL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
9
99
8
1
1
9
5
2
3
1
2
8
1
1
2
11
11
11
1l-COOK,2-DUPAGE,3-GRUNOY,4-KANE,5-KANKAKEE,6-KENCALL,7-LAKE,8-MCHENRYf9-WILL,10-LAKE IN,
il-PORTER
-------
TABLE XVIII. CONTINUED.
IRCE
.OKY
826
828
829
830
831
835
836
837
838
840
841
842
843
844
845
846
847
848
MASS
INDEX
0.001
3.604
0.155
0.113
0.328
0.081
0.740
0.03i>
0.109
1.346
0.340
0*047
0.113
1.260
1.9&5
33.642
4.631
1.126
PINDEX
0.001
8.053
0.367
0.250
0.561
0.185
1 . 745
O.C77
0.183
0.546
0.201
0.044
0.067
1.172
1.158
11.648
1.887
0.3*16
«f
1.82
2.23
2.36
2.22
1.71
2.28
2.36
2.22
1.68
0.40
0.59
0.93
-. 0.59
0.93
0.59
0.35
0.41
0.29
POPEX
0.001
12.478
0.606
0.394
0.848
0.067
2.813
0.028
0.282
0.597
0.305
0.048
0.102
1.896
1.875
22.891
2.687
0.174
W
1.05
1.55
1.65
1.58
1.51
0.36
1.61
C.36
1.54
1.10
1.52
1.10
1.52
1.62
1.62
1.97
1.42
0.53
I
1
1
1
1
i
0
1
0
1
i
1
1
1
1
1
1
1
1
z
c
1
1
1
1
0
1
0
1
i
1
1
1
1
1
1
1
i
- NUMBER OF !
345
0
1
1
1
1
0
1
0
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
0
1
0
1
1
1 .
1
1
1
1
1
1
1
0
1
1
1
1
0
1
0
1
1
1
1
1
1
1
1
1
1
SOUR(
6
0
1
0
0
1
0
1
0
1
1
1
1
1
1
1
1
1
1
;ES
i
i
i
i
i
0
1
0
1
1
1
1
1
1
1
1
1
1
IN COUNT]
8 9
0
1
1
1
1
0
1
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
0
1
1
1
1
1
1
1
1
1
1
rce 1
Lt J
10
I
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
11 TOTAL
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
4
11
10
10
11
2
11
2
11
11
11
11
11
11
11
11
11
11
1 i-cOOK,2-OUPAGfct3-GRUNOY,4-KAN£»5-KANKAKEEf6-KENCALL»7-LAKE,8-MCHENRY,9-WILL»10-LAKE IN, %
11-PORTfcR c
-------
TAdLE XVIII. CONTINUED.
iUUKCt
CATEGORY
849
850
831
852
853
854
836
837
858
859
861
MAb5 -KINUbX . ILL
INDEX Ml
1.212
0.152
0.515
0.021
0.050
0.500
0.017
0.031
0.332
0.501
2.8d7
1.604
0.2CO
0.760
0.019
0.015
-O.324
O.C25
0.071
O.C93
0.510
2.940'
1.32
1.31
1.48
0.90
0.31
0.65
1.48
2.29
C.28
1.02
1.02
PUKtA
2.755
0.255
1.122
0.035
0.024
0.646
0.013
0.027
' 0. 106
C.825
5.477
-til
PI
1.72
1.28
1.48
1.84
1.55
2.00
C.50
0.39
1.14
1.62
1.86
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
0
1
0
0
1
1
NUMDtK
3 4
1
1
1
0
0
0
1
1
1
1
I
1
1
1
0
0
0
0
0
0
1
1
ur
5
1
1
1
0
0
0
0
0
1
1
1
iUUKUCS 1
6 7
1
1
1
0
0
0
0
0
0
1
1
1
1
1
1
0
0
1
0
1
1
1
in ouuii i ico -
8 9 10
1
1
1
0
0
0
0
0
1
1
1
1
1
1
0
0
0
1
1
1
1
1
1
1
1
0
0
0
1
1
1
1
1
11 TOTAL
1
1
1
0
0
0
1
1
1
1
1
11
11
11
3
2
1
7
5
8
11
11
TOTAL 419 64 37 80 53 21 95 30 398 531 74 1802
1 i-COOK,2-CUPACEf3-GRONDY,4-KANEt5«KANKAKEE,6-KENDALL,7-LAKet8-MCHENRy,9-rfILLtlO-LAKE IN,
11-PURTER
-------
170
(0.04) for sources which have only CO emissions, such as in manufacture
of ammonia by the catalytic reformer process from natural gas (category
183). All other source-categories have the PI/MI between these two
extremes. For example: (a) sources such as boilers for electric power
generation as well as many industrial boilers with emissions of SC^
and particulates have generally a high PI/MI (1.96 to 2.58); (b) food
and grain processing industries which have only particulate emissions
have PI/MI of 1.96; (c) for the various solvent-evaporation sources,
PI/MI is in the vicinity of 1; and (d) at the lower end of PI/MI scale
(0.04 to 0.4) are sources such as automobiles with large CO and HC
emissions.
PO/PI
The comparison of PO/PI for the different source categories is
more complicated than the comparison of PI/MI. In addition to the
emissions and tolerance factors considered in pindex, popex includes
considerations of atmospheric dispersion and population exposure.
Popex and PO/PI are shown in1column 4 and 5 of Table XVIII. For each
of the source-categories, columns 7 through 17 of Table XVIII indicate
county locations and number of sources. Generally, PO/PI is large if
the majority of sources of a source-category are located in a populated
county, such as Cook County. PO/PI also depends on the height of
emission stacks.
In order to. evaluate the impact of population, area, and the stack
height on PO/PI, source-categories which had all the sources located in
-------
171
a single county were chosen for further analysis. PO/PI of such cate-
gories is influenced by the population area of a single county instead
of a complex combination of population and areas of many counties. For
example, out of the first four categories listed on Table XVIII, only
source-category 11 has all of the five sources located in a single
county (Cook). Thus, source-category 11 was selected and PO/PI of this
category, along with the stack heights of the sources included in this
category, were noted. In the case of a source-category which had sources
with different stack heights, a pindex-weighted average stack height was
computed for the emissions and stack height data given in Appendix D and
the tolerance factors given in Table VI.
Six counties (Cook, Grundy, Kane, Lake in Illinois, Lake in Indiana,
;
and Will) out of the eleven counties had source-emission data satisfying
the criterion of having all sources of a source-category located in a
single county. PO/PI for these six counties are plotted versus the
stack height (Figure 24). Plots for each of the six counties are
straight lines. The slopes increase with increasing population den-
sities (Table XIX).
To visualize the influence of the variables related to population,
area, and stack heights, PO/PI is plotted against the county population
densities (Figure 25). According to Figure 25, for a constant stack
height the impact of a source as measured by PO/PI increases with in-
creasing population density. Similarly for the same population density,
PO/PI on the population-health-effect impact of a source increases with
decreasing stack height.
-------
0.5
H 0.4
I
0. 3
X
0)
T!
"I
a
X
g,. 0.2
O
4-f
O
0
H
tJ 0.1
0.0
1.
Figure 24.
j
_ GRUNDY
_L
I
10
100
Stack height, feet
Plots of stack heights versus PO/PI for different counties.
1000
8
o
u
o
>H
H
2
X*
0)
c
H
04
X
I
ft
14-1
o
NJ
-------
173
TABLE XIX. POPULATION DENSITIES AND SLOPES OF PO/PI VERSUS STACK
HEIGHTS FOR SIX COUNTIES
County
Grundy
Will
Kane'
Lake, Illinois
Lake , Indiana
Cook
Population density
people/square mile
61
295
483
837
1,065
5,753
PO/PI
1 J~ T~~li3.
Stack height,
in meter"
.0001
.0006
.0009
.0016
.0021
.0096
-------
2.5 r
H
O)
04
1
H
a
X
&
0
04
M-l
o
o
H
-P
2.0
1.5
1.0
0.5
0.0
10 100 1000
Population density, people/sq. mile
Figure 25. Relationships of PO/PI versus population density for different stack heights.
10,000
-------
175
IMPLICATIONS
Both of the above observations related to stack height and popu-
lation density variables are generally accepted. However, Figure 25
which is based on results of the computer models, pindex and popex,
provides a quantitative method for comparison of the health-effect im-
pact on people attributable to the sources of air pollution.
Pindex is a useful way to combine emissions of different pollutants
into a single number and it is used in the following section for eva-
luating the impact of sources. The comparison of PI/MI for different
sources indicates the relative health-impact of their emissions.
PO/PI and its relation to population densities is useful for esti-
mation of the relative impact on the population of two or more sources
of air pollution. In calculating the ratio, the effect of mass emis-
sions and pollutant-tolerance factors are eliminated and thus PO/PI be-
comes a measure of the extent of population exposure only. By combining
the pindex calculations with the relation of PO/PI with stack height and
population density, one can estimate the relative dispersion, population
and health-effect impact of different sources without using the computer
simulation.
A Simple Method for Determining Relative Impact of Emission Sources
The preceding analysis can be used to determine the relative im-
pact of sources. As in popex, the data required are the emissions of
the five pollutants, stack heights, and population densities of the
counties in which the sources are located.
The method for determination of impact involves three steps:
-------
176
(1) Apply tolerance factors (Table VI) to the emission data. Pindex for
each source N can be calculated using the following expression:
5
(pindex)N = I emissions(N,K) x TF(K)
K=l
where emissions(N,K) are the emissions in tons per year of pollutant K
from source N. TF(K) is the factor based on the tolerance factor FF(K)
and TF(K) = FF(CO)/FF(K).
(2) From Figure 25, obtain the ratio PO/PI for the appropriate stack
height and population density.
(3) Calculate popex for each source from
PO
(popex)N =
x (pindex)N
This method can efficiently be used for a smaller number of sources
(less than ten). For a large number of sources, the direct use of the
popex computer model would be preferred.
LIMITATIONS OF THE POPEX MODEL
An important limitation on the use of the popex model is that it
should be used in toto or, in other words, parts of the model should
not be used independently of the rest of the model. To balance the
complexity and inadequacies in data, popex was built as a "package".
Thus, it may be unfruitful to use the population submodel of popex
with other dispersion models such as AQDM. Similarly, the dispersion
submodel should not be used only for estimation of air quality.
Secondary pollutants other than ozone were not considered in the
model. Inclusion of a mechanism of formation of secondary pollutants
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177
like sulfate or nitrates, etc., and their tolerance factors could possi-
bly alter the results.
Other limitations are explicit in the methodology of the construc-
tion of the submodels. For example, since the model is based on average
annual factors, episodic conditions are not considered in the model.
Finally, the research for this dissertation is a "first-generation"
attempt to combine diverse parts of the air quality management system.
Thus, this work does not provide unchangeable or ever-correct answers.
As our understanding of many of the lesser known factors related to
air pollution and its effects grows, the popex model could be improved.
Further verifications and improvements in the model are left to others
and to the future. Recommendations for future work are given in the
following section.
FUTURE WORK
Future work related to this research could be performed in many
directions. Some of the specific recommendations are:
(1) Results of the popex model could be compared with rankings arrived
at by a totally different method, for example, a ranking based on eco-
nomic and/or technological considerations. Similarly, the results of
other prioritization studies mentioned in Chapter I (3,4) could be
compared with the results of the popex model. A comprehensive compar-
ison of rankings by different approaches would help in establishing
true priorities.
(2) Popex model was applied to Chicago AQCR data. Even though the
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178
emission inventory of the Chicago AQCR was largely representative of
national emissions, it would be useful to apply popex to some other
region for comparison of the rankings.
(3) Specific parts of the model could be improved. . Of course, health-
effect modeling deserves a high priority. The dose-response curves
for short term (a few hours) responses to ozone and sulfur dioxide are
presented in Figures A-l and A-3 to A-5 of Appendix A. The levels of
pollutant concentrations included in these figures are somewhat higher
than generally experienced for 03 and, in the case of SC^, concentra-
tions are substantially higher than ambient levels. When more defini-
tive dose-response information is available for the short term effect
as well as for longer term effects (several months or years) of all the
pollutants with concentrations near the ambient levels, it could be
used instead of the tolerance factors for a more-realistic priority
rankings of sources.
(4) The computer program of popex is flexible and could be modified to
consider the impact of secondary pollutants such as sulfates and ni-
trates when more definitive information on mechanism of formation and
on dose-response relationships is available.
(5) Population distributions which are specific to various air pollu-
tion sources could be explored and added to the popex methodology.
(6) Dispersion model could be refined and expanded to include other
meteorological conditions not presently included.
-------
CHAPTER XI
CONCLUSIONS
The results of the popex model show that seventeen out of a total
of 227 source-categories are responsible for nearly 80 percent of the
air-pollution-population effect problem (Tables XI and XIII). These
seventeen categories include commonly recognized large sources, such
as automobiles, large utility and industrial boilers, mineral product
industries, etc., as well as less-recognized categories such as sol-
* i
vent evaporations from operations involving surface coatings. These
source-categories have been individually discussed, and the factors
which could possibly change the rankings are enumerated in Chapter
VIII.
The Industrial Environmental Research Laboratory of the EPA has
ongoing research, development, and demonstration projects for control
of emissions from all the stationary source-categories assigned rank
one by popex, except possibly for the control of solvent emissions in
industrial operations (48). Methods for control of solvent or hydro-
carbon emissions include adsorption using activated charcoal or use of
afterburners, but these do not appear to be in widespread use. It may
be necessary to develop better and more economical methods for control
of hydrocarbons in operations involving solvents. Perhaps, a more
important problem related to hydrocarbon emissions is the lack of a
179
-------
180
hydrocarbon emission inventory which classifies the emissions according
to their reactivities. A more realistic mechanisms for the formation
of oxidant than the one included in this project may not be of signi-
ficant use until such a hydrocarbon emission inventory is available.
The sensitivity analysis of the popex model provides interesting
results. Tolerance factors which are related to health effects of air
pollutants were identified as the parameters most sensitive in the
popex model. Other parameters including the variables related to
meteorological dispersion were shown to be of less importance. The
results of the sensitivity analysis thus indicate that any additional
effort for improvement or additions in the model should be aimed at
improving the part related to health effects.
The present tolerance factors are only indirectly based on health
effects. Construction of dose-response relationships is essential to
the development of a more realistic model. However, sufficient data
are not available for developing these relationships. The review and
analysis of studies on the effect of air pollution on human pulmonary
function (Appendix A) shows that the lack of usable health-effects
data is not due to lack of studies in this area, as commonly believed,
but is primarily due to the failure in a majority of these studies to
adequately characterize the cause (air pollutants), and the effect
(pulmonary function) as well as inadequate recognition and elimination
of interference factors. These and other aspects of the health-
effects studies are discussed and suggestions for future studies are
included in Appendix A.
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181
Until more definitive information on dose-response relationships
is available, use of the tolerance factors, described in this disser-
tation, appears to be the best available means for assessing the rela-
tive impact of the exposure to any combination of the six pollutants.
The third significant output of this project is to supply a
simple method for assessing relative impact of air pollution in a
situation with a smaller number of sources. Development of the pro-
posed method was based on the analysis of the results of the popex
model (Chapter X) , and this method does not require the use of a com-
puter .
-------
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10. Kahn, A., Rutledge, R. B. , Davis, G. L., Altes, J. A., Gantner,
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12. Benson, F. B., Henderson, J. J., and Caldwel, D. E.: Indoor-Out-
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15. Hatch, T. P.: Criteria for hazardous exposure limits. Arch.
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16. Rjazanov, V. A. : Criteria and methods for establishing maximum
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Research Triangle Park, N. C., U.S. Environmental Protection
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20. Smith, M. E. and Frankenberg, T. T. : Improvement of ambient sul-
fur dioxide concentrations by conversion from low to high
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and Fuel Supply, Washington, D.C., Federal Power Commission,
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184
23. U.S. Bureau of the Census: Statistical Abstracts of the United
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25. Turner, D. B. : Workbook of Atmospheric Dispersion Estimates.
Publication AP-26. Research Triangle Park, N. C.: U.S.
Environmental' Protection Agency, 1970.
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27. U.S. Bureau of Census: Statistical Abstracts Supplement-County
and City Data Book-1972. Washington, D.C.: U.S. Department of
Commerce, 1972.
28. Allen, R. J., Babcock, L. R. and Nagda, N. L.: Air pollution dis-
persion modeling: application and uncertainty. Regional Science
Perspectives 5:1-26, 1975.
29. Rote, D. M., Gudenas, J. W. and Conley, L. A.: Studies of the
Argonne Intergrated Puff Model. Publication ANL-ES-9. Argonne,
111.: Argonne National Laboratory, 1971.
30. Neuberger, H., and Cahir, J.: Principles of Climatology. New
York, Holt, Rinehart and Winston, 1969.
31. National Oceanic and Atmospheric Administration: Local Climato-
logical Data for Midway and O'Hare Airports. Asheville, N.C.,
National Climatic Center, U.S. Department of Commerce.
January 1973 through July 1975.
32. Lyons, W. A. and Olsson, L. E.: Mesoscale air pollution transport
in Chicago lake breeze. J. Air Pollut. Control Assoc. 22:876-
881, 1972.
33. Commonwealth Edison Co.: Meteorological Data for Dresden. Dresden,
111., 1972.
34. Biomedjcal Computer Programs. Ed., W. J. Dixon. Berkley, Calif.,
University of California Press, 1972.
35. Carnow, B. W., Wadden, R. A., Scheff, P., and Musselman, R. :
Health Effects of Fossil Fuel Combustion - A Quantitative
Approach. Washington, D.C., American Public Health Association,
1974.
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185
36. Pinklea, J. F., Shy, C. M., Moran, J. B., Nelson, W. C., Larsen,
R. I. and Akland, G. G. : The Role of Environmental Health
Assessment in the Control of Air Pollution.Research Triangle
Park, N. C., U.S. Environmental Protection Agency, 1974.
37. Finklea, J. F., Nelson, W. C., Moran, J. B., Akland, G. G.,
Larsen, R. I., Hammer, D. C. and Knelson, J. H.: Estimates of
the Public Health Benefits and Risks Attributable to Equipping
Light Duty Motor Vehicles with Oxidation Catalysts. Research
Triangle Park, N. C., U.S. Environmental Protection Agency, 1975.
38. Babcock, L. R. : A combined index for measurement of total air
pollution. J. Air Pollut. Control Assoc. 20:653-659, 1970.
39. Nagda, N. L. and Babcock, L. R.: Engineering Analysis Methodolo-
gies for Air Resource Management - Interim Report. EPA Grant
No. R-802111. Chicago, University of Illinois, 1974.
40. Babcock, L. R. and Nagda, N. L. : Indices of air quality. In
Indicators of Environmental Quality, ed. W. A. Thomas, pp. 183-
197. New York, Plenum Press, 1972.
41. Babcock, L. R. and Nagda, N. L. : Cost effectiveness of emission
control. J. Air Pollut. Control Assoc. 23:173-179, 1973.
42. U.S. Environmental Protection Agency: National primary and
secondary ambient air quality standards. Federal Register
36:84, Part II 8186, 1971.
43. Larsen, R. I.: A new model of air pollutant concentration averaging
time and frequency. J. Air Pollut. Control Assoc. 19:24-30, 1969.
44. Larsen, R. I.: A Mathematical Model for Relating Air Quality
Measurements to Air Quality Standards. Publication AP-89,
Research Triangle Park, N. C., U.S. Environmental Protection
Agency, 1971.
45. Faith, W. L. and Atkisson, A. A.: Air Pollution, p. 251. New
York, Wiley-Interscience, 1972.
46. National Air Pollution Control Administration: Nationwide Inven-
tory of Air Pollutant Emission 1968. Durham, N. C.,' 1970.
47. U.S. Geological Survey: Base Map for Illinois and Indiana,
1:500,000. Washington D.C., U.S. Department of Interior, 1958.
48. Control Systems Laboratory: Research Objectives Achievement Plans.
Research Triangle Park, N. C., U.S. Environmental Protection
Agency, 1974.
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186
49. National Air Pollution Control Administration: Air Quality Criteria
for Particulate Matter. Publication AP-49- Washington D.C., U.S.
Department of Health, Education and Welfare, 1969.
50. Hughes, T. W., Horn, D. A., Sandy, C. W., and Serth, R. W.: Source
Assessment - Prioritization of Air Pollution from Industrial
Surface Coating Operations. Publication EPA-650/2-75-019-a.
Washington D.C., U.S. Environmental Protection Agency, 1975.
51. Rubin, E. S.: The influence of annual meteorological variations
on regional air pollution modeling. A case study of Allegheny
County, Pa. J. Air.Pollut. Control Assoc. 24:349-356, 1974.
52. Assembly of Life Sciences, National Academy of Sciences - National
Research Council: Proceedings of the Conference on Health Effects
of Air Pollutants. Serial No. 93-15. Prepared for the Committee
on Public Works, U.S. Senate. Washington D.C., U.S. Government
Printing Office, 1973.
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APPENDIX A
ASSESSMENT OF EXISTING STUDIES OP HEALTH EFFECTS
3 j-
OF AIR POLLUTION
SUMMARY
Studies on the health effects of air pollutants v?ere reviewed and
evaluated. In order to provide a quantitative frame of reference, only
the studies which have used pulmonary function tests for characteriza-
tion of the health effects were selected for this assessment.
, The past studies reported in the literature wer§ divided into four
groups based on study designs. Results of the 'studies in each of the
groups were collectively analyzed. Whenever possible, based on the data
i'
j
reported in these studies, dose-response curves were constructed. Some
* : '
of the more subtle results of the studies are also discussed.
The studies in each of the four groups were examined in detail
for the telative merits of their methodologies. In the determination
of the relative merit of the methodologies, the degree of resolution and
the quality of results were considered to be of significant importance.
This analysis showed why some of the studies, or groups of studies, have
yielded useful results, whereas others have not. The reasons for this
situation are discussed and recommendations for future work are included.
Based on this review and the assessment of the past studies it is
concluded that the tolerance factors are still the best available means
187
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188
for a relative assessment of the damage potential of the six pollutants
INTRODUCTION
In this dissertation, the tolerance factors derived from the air
quality standards were used for quantification of relative effects of
the six air pollutants: particulate matter, PM; sulfur dioxide, S02,-
nitrogen oxides, NOV; carbon monoxide, CO; hydrocarbons, HC; and oxidants,
a
Ox. The derivation and the use of the tolerance factors are given in
Chapter VI. The air quality standards are based on deleterious effects on
humans, vegetation, property, etc. of the air pollutants and thus the
tolerance factors are based on health effects. The tolerance factors,
however, allow only a single-point comparison of the relative effects of
pollutants. Dose-response relationships are necessary for a more realis-
tic assessment of the effects of each pollutant as well as for a compa-
rison of effects among the different pollutants. In this appendix, re-
sults of the studies on the health effects of air pollutants were re-
viewed and analyzed in depth for possible construction of dose-response
relationships. Furthermore, these studies were examined for the rela-
tive merits of their methodologies.
Dose-response Relationships
Dose-response relationships or predictive equations for health
effects of air pollutants, allow one to estimate effects of various
levels of dosages of air pollutants. The parameter related to dosages
of air pollutants could be a complex combination of time and concentra-
tion variables. For example, the effect of continuous exposure to
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189
constant level of air pollutants may be different than intermittant ex-
posure to similar concentrations especially if the degree of effect
depends on cumulative exposures.
Similarly, "response" parameters on dose-response curves could
also be a combination of effects. Generally the response is character-
ized (a) by increase in incidence of diseases, (b) by aggravation of
existing diseases, or (c) some clinical indicators, such as pulmonary
function tests or level of carboxyhemoglobin in blood.
Pulmonary Function Tests
Review of the literature on health effects of the six air pollu-
tants (PM, SO2» NOX, CO, HC, Ox) showed that in numerous studies va-
rious pulmonary function tests have been used alone or in conjunction
with other approaches for characterization of effects. This is not
surprising since inhalation is the major route of entry of pollutants
into the human body and most of these pollutants, with the exception of
CO and HC, have their primary effects on the respiratory system. The
pulmonary function tests supply objective and quantitative information.
Similarly, pulmonary function measurements could indicate effects at a
subclinical level which can not be adequately reflected if only increases
in incidence of diseases are considered. Symptomology should be con-
sidered for a complete characterization of effects on the respiratory
system. Studies involving pulmonary function tests were selected for
this research in order to evaluate the effects of air pollutants in a
generalized and quantitative manner.
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TABLE A-I. LUNG VOLUMES, CAPACITIES AND PULMONARY FUNCTION MEASUREMENTS:
NOMENCLATURE AND DEFINITIONS (Al).
Name
Abbreviation
Explanation/definition
Lung volumes and capacities
Tidal volume TV
Residual volume RV
Total lung capacity TLC
Vital capacity VC
Functional residual capacity FRC
Pulmonary function measurements
Forced vital capacity FVC
Forced expiratory volume
FEV.
The volume of gas inspired or expired during each respira-
tory cycle (liters)
The volume of gas remaining in the lungs at the end of a
maximal expiration (liters)
The amount of gas contained in the lung at the end of a
maximal inspiration (liters)
The maximal volume of gas that can be expelled from the lungs
(liters)
The volume of gas remaining in the lungs at the resting
expiratory level (liters)
Maximum volume measured on forced expiration after the
deepest inspiration (liters)
Volume of gas expired over a given time interval, t, (in
seconds) during a forced expiration (liters)
-------
TABLE A-I. CONTINUED.
Pulmonary function measurements
Forced expiratory time FET
Peak expiratory flow PEF
Mid-maximum expiratory flow MMEF
Maximum expiratory flow
Maximum expiratory flow
volume curves
Airway resistance
Specific conductance
"Closing" volume
MEF0
%vc
MEFV
curves
Raw
SGaw
CV
Time required to expel the total vital capacity during a
maximal forced expiration (in seconds)
Peak expiratory flow rate (liters per second)
Flow rate during 25-75% segment of VC of the forced expira-
tory volume (liters per second)
Instantaneous maximum expiratory flow rate at specified
lung volumes
Graphic recording of flow versus volume during a forced
expiratory volume maneuver followed by forced inspiration
(flow in liters/second and volume in liters)
Airway resistance is measured by body plethysmograph using
the relation:
airway resistance = (atmospheric pressure - alveolar
pressure)/flow
Reciprocal of (Raw x Vtg) where Vtg is thoracic gas volume
Lung volume at which dependent lung regions tend to close.
A normal person can expire fully to residual volume; persons
whose lungs have less elastic recoil, whose airways have
lost structural supporting tissue or whose airways are nar-
rowed, develop widespread airway collapse and trapping when
they breathe between RV and FRC or even at higher volumes.
i-1
ID
-------
TABLE A-I. CONTINUED.
Pulmonary function measurements
Static and dynamic . Cst, Slope of static recoil pressure and the volume of lungs
compliance Cdyn reflects lung compliance. When lung stiffness increases as
a pathological phenomenon, compliance is low. The measure-
ment of compliance during breathing is called as dynamic
compliance (Cdyn) and the compliance measured from the static
curve is called as static compliance (Cst). Cdyn is fre-
quency dependent and can be used to assess airways obstruc-
tion in disease.
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193
Some of the many diagnostic techniques used for the assessment of
pulmonary function or pulmonary function tests (PFTs) include (a) spiro-
metric, (b) flow-volume curve, (c) airway resistance, (d) closing volume,
and (e) compliance measurements. The measurement techniques are briefly
described in Table A-I1 which also contains definitions of various lung
volumes and capacities (Al).
Physiological changes as a result of exposure to air pollution are
qualitatively similar to those observed in certain pulmonary diseases.
In evaluation of obstructive pulmonary diseases, the criteria given in
Table A-II are often used (A2).
TABLE A-II. CRITERIA FOR EVALUATION OF
OBSTRUCTIVE PULMONARY DISEASES.
PFT1
FEV
PEF
FEV,
FEVl
FEV,
FEV,
Reduction from
Normal Values,
Percent
<20
>50
20-35
35-50
50-65 .
>65
Severity of
Disease
minimal
mild
moderate
severe
very severe
1For explanation of abbreviations of the pulmonary function tests
see Table A-I.
As shown later in this appendix reductions in the pulmonary
'Numbers of all the tables, figures and references in the Appendix have
a prefix 'A' to distinguish them from the rest of the dissertation.
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194
function measurements due to air pollution and due to respiratory infec-
tions are smaller in magnitude (less than 10 percent at the most) than
given in Table A-II.
Scope
Studies on measurement of health effects of air pollution include
animal and human experimental studies done in an exposure-chamber set
up, and human epidendological studies performed under environmental or
occupational conditions. Each of these types of studies have their ad-
vantages and limitations. In order to have a complete and reliable
characterization of the effects, all of the above-mentioned types of
studies are required. In this research the studies which have used the
pulmonary function tests for characterization of effects of the air
pollutants on the human lung were considered. The literature reviewed
in this study is not exhaustive, however an effort was made to include
the majority of recent (after 1970) studies published in English-lan-
guage journals.
Format of Presentation
The studies have been divided into four groups for review and
analysis of their results (Table A-III). This grouping was done only
for convenience in analysis of the studies and the inclusion of a study
under one or another group could, in some instances, be arbitrary.
In the following section, first results of the studies in each
of the groups are reviewed for construction dose-response curves. In
the section entitled 'Comments', some of the results and other subtle
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195
Groups
TABLE A-III. THE GROUPING OP HEALTH-EFFECT STUDIES.
Type of Studies
Experimental
Epidemiological
Group 1 - correlation
Group 2 - cross-sectional
Group 3 - longitudinal
Studies done in exposure
chambers.
The goal of these studies was
to correlate results of the
pulmonary function measure-
ments with the environmental
variables.
Studies which compare two or
more groups of subjects having
different air pollution ex-
posures .
Studies assessing long-term
effect of air pollution
points which are common to all of the groups are collectively discussed.
Later the method and the results of assessment of the studies in the
four groups are described.
EXPERIMENTAL STUDIES (A3-A11)
Experimental Details
The details of the parameters studied in each of the experimental
exposure-chamber studies are given in Table A-IV. In most of the studies
the duration of exposures were not more than a few hours at a time. All
the studies except one (All) used artificially generated pollutants.
Ozone in seven studies was the most studied single pollutant; two
-------
TABLE A-IV. SUMMARY OF THE EXPERIMENTAL STUDIES.
196
-^Studies
Parameters ^""""^-^^^
Year of the study1
Duration of exposures
Pollutants
Concentrations, ppm
Generated or ambient
Pulmonary function tests
FVC, TLC
FRC, RV
FEVt
PEF
MMEF
MEF%VC
KEFV Curves
CV
Raw, Vtg*1
Cst. Cdyn
DLCO
Other
Population
Young Hallet(A4)
et ajU (A3)
1963 1964
2 hr. 30 min.
ozone ozone
0.6-0.8 1-3
gen. gen.
FVC FVC
FEV-?5 FEVi
PEF
MMEF MMEF
DL DL
CO CO
11 adults 20 normal
(10 males, adults
1 female), (9 males,
ages 20-45 11 females)
years ages 17-38.
5 COPD
patients
(2 males,
3 females
ages 48-61.
Bates Hazucha
et al. (AS) elt al_. (A6)
1971 1972
2 hr. 2 hr.
ozone ozore
0.75 0.37,0.75
gen. gen.
FVC FVC.,TLC
RV
FEVX FBVj^
PEF
MMEF MMEF
MEFV MEFV
CV
Cst,Cdyn
10 males 24 males,
ages 22-35. age 24.
12 smokers,
12 nonsmokers.
* Approximate, based on year of acceptance of the particular paper for publication or
on year of publication.
20ther pollutants such as oxidants, nitrogen oxides may have been present which were
not monitored.
3Particulate measured as' number of particles per cubic feet for different size ranges
(accurate conversion to ug/m3 very difficult). SO2 levels were monitored and were
generally two-thirds less than the ambient levels.
^Specific conductance or Gaw/vtg were calculated from Raw and Vtg.
5Partial expiratory flow rate at 50 percent VC.
-------
TABLE A-IV. SUMMARY OP THE EXPERIMENTAL STUDIES. (CONTINUED)
197
Parameters
^Studies Xagawa and Hackney
f Hackney Anderson Kerr (All)
Toyama (A7) et a^. (A8) et al. (A9) et a^. (AlO)
Year of the study1 1974
Duration of exposures 5 min. '
Pollutants ozone
Concentrations, ppm 0.9
Generated or ambient gen.
Pulmonary function tests
FVC, TLC
FRC,RV FRC
PEVt
PEF
MMEF
MEF%VC
MEFV Curves
CV
Raw, Vtg1* Raw, Vtg
Cst,Cdyn
DLCO
Other
Population 4 males,
ages 20-25.
1974
4 hr.
ozone
0.25,0.37,
0.5
gen.
FVC, TLC
RV
FEV,
PEF
:
MEF MEF
50 25
MEFV
CV
Raw, Vtg
Cst, Cdyn
DLCO
4 normal
males,
average
age 43.
4 males
sensitive
to air
pollution,
average
age 34.
1974 1973 1972
2 hr. 6 hr. 6 days
ozone S02 PM, S022
0.25,0.37, 1,5,25 3
0.5
gen. . gen. amb.
FVC, TLC TLC
RV FRC,RV
FEVj^ FEVj FEy
-------
198
involved a combination of 03, NC>2 and CO; and one study dealt with S02.
The study done by Kerr (All) used "natural" or ambient air pollutants
and it also had the longest duration (six days) of exposures.
Generally, an experimental set-up allows better characterization
of variables and a greater degree of control over experimental variables
and the factors which may affect the results. This fact is reflected on
Table A-IV. The experimentation with ambient air with simultaneous con-
trol of temperature and humidity poses special problems. These problems
are discussed later in this appendix.
In the last ten or twelve years there have been substantial im-
provements in experimental techniques and design of the exposure-chamber
studies. The problems encountered in these types of studies were first
discussed by Bates (A12) and Bates et al. (A13), and more recently by
Hackney et al. (A14). Due to the difficulty in establishing statistically
significant changes in pulmonary function before and after the exposures,
recent studies have used a larger and larger number of PFTs. This fact
is apparent when Ballet's pre-1964 study (A4) which used five PFTs, is
compared with the recent Hackney et^ al. studies (A8, A9) in which 10-14
different tests were used. All the experimental studies done after 1970
generally have adequate characterization of changes in pulmonary function
(Table A-IV).
Results
Ozone. - Similar experimental protocol and conditions in the studies
done by two groups: Hazucha et^ al_, (A6) and Hackney et^ al_. (A8, A9)
-------
199
allow construction of a dose-response curve in terms of FEV, . The curve
shown in Figure A-l is, in most cases, for two-hour exposures with inter-
mittent exercise and is based on "average" FEV, responses for each of
the two studies. Hackney e_t al^ (A8) studied two groups of subjects: one
group of "normal" male subjects who had no history of cough, chest dis-
comfort or wheezing associated with allergy or air pollution, and a
"reactive" group of male subjects who had some of these symptoms. In
the experiment with the normal group, there were no significant and
consistant changes in normals in most of the tests even with a four-
hour exposure to 0.5 ppm ozone.
However, for the "reactive" group, FEV-j^ decreased significantly.
The data-points shown in Figure A-l are average of response for the nor-
mal and the reactive group (A9). Smokers and nonsmokers were studied
separately in the study by Hazucha et al. (A6). Although smokers and
nonsmokers had different initial pulmonary function measurements, the
changes in FEV, due to exposure to ozone were similar in both the groups.
The dose-response curve shown in Figure A-l was for single expo-
sures of ozone and the "dose" was defined by concentration of ozone only.
For more realistic dose-response curves or for response-predictive ex-
pressions, effects of the length of duration of exposures as well as the
effect of cumulative exposures have to be considered. Although enough
quantitative information for construction of such response-predictive
expressions is not available, qualitative effect of the above mentioned
factors as well as other factors such as exercise are discussed below.
One series of experiments done by Hackney (A8) gave an opportunity
-------
200
xww
90
0
il
c
o
t \
0 80
M-l
O
4J
C
>0
x *v
X \u
\ X
maximum ^^^ ^L X^
response, V x 10
Hackney et al. O \ \
(A9) \ ^ \
^ \ >
\ x
>
\ \
v ^
O
maximum response,
Hazucha e^t al. (A6)
-
o Average response of
6 adults per group,
-
O Average response of
,_..__ VQCU'V^l'l C!O
ClVfcii cty G J. co^Jwiioc
in both the studies
v
\
\
\
\
\
\ \
\ \
\
^A \
*^ V
\ ^
v
»
\
s
%
^
smokers and nonsmokers,
from Hazucha et al. (A6)
reactive and normal males
three groups, 5-7 adults per group, from
Hackney et^ al. (A9)
£ ~"~
I l
l i
0.25
0.5
0.75
1.0
O Concentration, ppm
Figure A-l. Dose-response curve for two hours of
exposure to ozone for adults.
-------
201
to examine the effect of a combination of two factors: cumulative ex-
posure and the duration of exposure (Figure A-2). in this particular ex-
periment, with four-hour exposures, on the second day of exposure to 0.5
ppm ozone the experiment had to be stopped at the end of two hours for
three out of four subjects. Thus the data reported for various PFTs in
Figure A-3 are for four-hour exposure on the first day and two-hour ex-
posure on the following day. In Figure A-2, the effect of cumulative
exposure is seen in MEF5Q and MEF25 since second-day values for these
tests are lower than, for the first day despite the fact that duration
of exposure was reduced on the second day. In FVC and FEV1 such cumu-
lative effect is not seen and the results of these tests appear to be
dependent on the length of exposure. These conclusions should be con-
sidered as tentative since the differences between the first and second
day of exposures may not be statistically significant.
The observations in Figure A-2 were for "reactive" subjects and
showed the combined effect of cumulative exposures and duration of ex-
posures. The effect on the pulmonary function is greater when the length
of exposure increases from one to two hours. Table A-V shows the changes
in the statistical levels of significance between the controls and the
group subjected to one-hour and two-hour exposures to 0.37 ppm ozone.
The level of significance improved in all cases with an increase in
duration of exposures (Table A-V). Levels of significance for 0.75 ppm
ozone are even better (A6) . Figure A-3 shows that MMEF decreases by
approximately 20% after each one and two hours of exposures for 0.75
ppm ozone. It is likely that some type of "leveling off" in reduction
-------
100
90
80
70
60
o^
"
-
-
-
i
c
: 1 2 c 1 2 c
.
-
«M
'
-
i ;
12 c 1 2
100
90
80
70
60
? 0
FVC FEVjL MEF5Q MEF25
c - control
1 - exposure to 0.5 ppm ozone first day, four hours,
Figure A-2.
as percent of control
2 - exposure to 0.5 ppm ozone the following day, two hours,
as percent of control
Effect of combination of cumulative exposures and duration
of exposures on four "reactive" adult males (A8).
to
o
to
-------
203
TABLE A-V. CHANGES IN LEVEL OF SIGNIFICANCE DUE TO A CHANGE IN
DURATION OF EXPOSURES OF SMOKERS AND NONSMOKERS
TO 0.37 PPM OZONE (A6)
Test
Nonsmoker/
Smoker
Level of statistical significance
for the difference from the control
One-hour exposure
of 0.37 ppm 0
Two-hour exposure
of 0.37 ppm 03
FVC
FEV
MMEF
MEF5Q
nonsmoker
smoker
nonsmoker
smoker
nonsmoker
smoker
nonsmoker
smoker
<.05
<.05
NS'1
NS
NS
NS
NS
NS
<.01
<.001
<.01
<.005
<.05
<.05
<.05
1NS - not significant at 0.05
-------
100
8
H
-M
H
H
4-1
0
0)
O
A
(S
to
a
90
80
70
60
50
204
Vertical lines represent one
standard deviation on each side.
Based on exposure of 0.75 ppm ozone
to smokers and nonsmokers, six
adult males per group, Hazucha
et al. (A6).
Duration of exposures, hours
Figure A-3. Dose-response curve for ozone: effect
of durations of exposures.
-------
205
would occur after two hours but this certainly is not seen up to two
hours of exposures. Studies of longer exposure durations are required
for any further analysis of effect of the length of exposure.
The effect of cumulative exposure is also clearly seen in normal
subjects. The exposure to 0.5 ppra ozone on two consecutive days showed
a marked reduction in lung function on the second day (A9). On the
*,
first day of the two-day exposures (two hours each day) only one out of
13 PFTs showed a significant change from the control measurements. How-
ever, on the second day, 10 out of the same 13 tests showed significant
changes.
The effects of ozone are more pronounced with exercise. The com-
parison of results of Young et^ al. (A3) with no exercise and Hazucha
et al. (A6) with moderate intermittent exercise (enough to double the
minute volume) show that for similar concentration there is a greater
.decrease in FEV. with exercise. Similarly, Kagawa and Toyama (A7) found
no significant difference in Gaw/Vtg from control if the subjects did
not undertake exercise. With exercise, the difference in Gaw/Vtg was
highly significant (Table A-VI). It thus appears that exercise exacer-
bates the effect of ozone in view of the significant difference between
the effects of ozone with and without exercise observed in these res-
piratory function studies. However, based on available information,
incorporation of effect of exercise in dose-response curves was,not,
possible.
Ozone, nitrogen dioxide and carbon monoxide. - No consistent results
were obtained in two experimental studies with sequential exposure to
-------
206
TABLE A-VI. EFFECTS OF OZONE AND EXERCISE ON THE PULMONARY
FUNCTION OF MALE ADULTS.
Study
Concentrations
and Duration
of Exposure
Excercise
PFT
Level of Signifi-
cance of the
difference from
control
(no ozone)
Young
et al.
(A3)
Hazucha
et al.
(A6)
Kagawa and
Toyama
(A7)
0.6 - 0.8 ppm No
2 hours
0.75 ppm
2 hours Yes 1
' i
0.9 ppm
5 minutes No
0.9 ppm
5 minutes - Yes2
FVC P <.,05
FEV->75 P <.05
MMEF Not significant
FVC , , P <.05
FEV-i P < . 01
MMEF P <.05
V ^
Gaw/Vtg Not significant
Gaw/Vtg P <.01
Fifteen minutes on ergometer, sufficient to double minute-volume.
-Pedaling at 50 rpm for 5 minutes at a load of 100 kg - m/min.
-------
207
°3' N02' ^"d C0 (A8' A9) These studies are summarized in. Table A-VII.
Sulfur dioxide. - The study by Andersen et. al. (A10) was done to eva-
luate the S02 threshold limit value, TLV, of 5 ppm for occupational ex-
posures. Concentrations (1, 5 and 25 ppm) involved in this study are
much higher than ambient levels except 1 ppm level may possibly be
reached in episodic conditions. However, some of the conclusions of
this study are interesting. Figure A-4 shows that the effect on FEV,
of high concentrations of S02 is minimal. The changes in MMEF are some-
what larger. The dose-response curves are nonlinear and twenty-five
percent the change at 25 ppm in MMEF occurs at one ppm and after one
ppm the changes are almost linear. It is possible that this initial
steep change could occur at concentrations well below 1 ppm. Another
interesting finding in the Anderson et_ al. study was that changes in
closing volume were not significant even at high concentration, implying
that SO2 may effect only the upper airways.
Ambientair. - In an unusual study with experimentally controlled six-
day exposure to ambient air no meaningful differences were observed
between clean and ambient air phases (All). The subjects breathed
clean filtered air for the first three days and ambient air for the last
three days of the six-day exposure. In the second experiment this order
was reversed; ambient air was breathed for the first three days and
clean filtered air for the last three days. Other variables such as
temperature, humidity and sleep-awake cycle were rigidly controlled.
The results of the study implying ''no effect" due to ambient air
-------
TABLE A-VII. SEQUENTIAL EXPOSURE OF OZONE, NITROGEN DIOXIDE
AND CARBON MONOXIDE TO ADULT MALES.
Study
Population
Pollutant and Exposure
Results
Hackney (A8)
4 - normal
Hackney (A9)
1 - normal
5 - 'reactive'
1st day:
O.Sppm 03
2nd day:
0.5ppm 03 + 0.3 ppm N02
3rd day:
O.Sppm 03 + 0.3 ppm NO2
+30 ppm CO
(four-hour exposures)
1st day:
0.25 ppm O3
2nd day:
0.25 ppm O3 + 0.3 ppm NO2
3rd day:
0.25 ppm O3 + 0.3 ppm NO2
+ 30 ppm CO
(two-hour exposures)
Changes small in
magnitude and
not consistent
and FVC
decreased with
03 + N0? (day 2),
no significant
changes in other
measurements.
to
o
00
-------
209
100
s
r-l
(D
H
-P
-H
S
id
-M
0>
P4
Based on Andersen et al. (AlO)
10
15
20
SO Concentration, ppm
Figure A-4
Dose-response curves for adult males for
six-hours of exposure to SO2.
-------
210
pollutants were not surprising since the concentrations of air pollu-
.*
tants in the "ambient air" phases of the study were substantially lower
(possibly 60-70 percent lower) than actually prevailing outside (All,
A15).
Although the results of the Kerr study (All) were negative, it
offers useful information for future studies (see the section on
comments).
EPIDEMIOLOGICAL STUDIES: GROUP 1 - CORRELATION STUDIES (A16-A20)
Details
The details of the studies are given in Table A-VIII. The time-
span of this group of epidemiological studies were a few weeks to one
year in length. In most of the studies PFT observations were made once
a week, whereas enrivonmental variables were continuously being moni-
tored. Two of the more recent studies (A19, A20) seemed to have moni-
tored all six of the air pollutants for which ambient air quality stand-
ards exist. It is recognized that the term "all of the pollutants" is
relative; the list of air pollutants is expected to grow with time and
newer pollutants are continually being recognized and studied. Thus
it must be noted that in the mid 1960's oxidants and nitrogen oxides
were not thought to be a problem outside Los Angeles area, also routine
methods for monitoring these pollutants may have been unavailable. How-
ever, for the sake of comparison of the results of these epidemiologic
studies, it was necessary to define the "pollutants not included"
(Table A-VIII).
-------
TABLE A-VIII. EPIDEMIOLOGICAL STUDIES: GROUP 1-CORRELATION STUDIES. 211
^\^St«dies
Parameters "--N^,^^
^*""*%«s>to
Study period1
frequency of
observations
Pollutants studies
Pollutants not included3
Spodnik
et al.
(A16)
Sept '64
June ' 65 .
weekly
PM
Spicer Emerson (A18)
et al. (A17)
two 7 week 1969-1971
study
periods
1965-1966.
daily weekly
PM,S02,H02 PM2,S02
Kagawa and
Toyawa (A19)
June-Dec.
1972.
weekly
PM,S02,NO
N02,HC,Ox,
°3
Kagawa
et a^. (A20)
Nov 1972-
Oct 1973.
weekly
PM,SO2,N02
Ox
(which could possibly have
interference effects)
SOX,NOX
Ox NOx,Ox*
_^^
Other stressors studied5 T,RH T,RH,BP,WS T,RH,BP,WS T,RH
T,RH
Pulmonary function
FVC, TLC
FRC, RV
FEVt
PEF
MMEF
MEF%VC
MEFV Curves'
CV
Raw, Vtg6
Cst, Cdyn
Other
Population
.
tests
TLC FVC, TLC
FRC FRC, RV
FEV^, FEVj
PEF
.
Raw.Vtg7 Raw.Vtg7
100 mal* 37 patients
adults with chro-
average nic bron-
age 20 chitis and
years bronchial
asthma
FVC
FEVi
PEF
MMEF
Max inspi-
ratory flow
rate
18 patients
(14 males,
4 females)
with chronic
airways
obstruction
FVC
FRC
MEF50,MEF25
MEFV Curves
Raw,Vtg
Slope of
alveolar
plateau
(N2%)
20 children
(10 males,
10 females) ,
average age
11
t
FVC
FRC
MEF50,MEF25
MEFV Curves
Raw,Vtg
20 children
(10 males.
11 females),
average age
11
lAs reported in the particular study or estimated based on the date of publication.
2As smoke in jig/»^.
3See text for explanation.
''British studies, generally, include only smoke and SOX as pollutants. It is possible
that due to automobile traffic, nitrogen oxides and oxidants could be present in the
London atmosphere.
5T - temperature, RH - relative humidity, BP - barometric pressure, US - windspeed.
6Gaw/Vtg is calculated from Raw and the thoracic volume.
7Uppei: and lower airway resistance *nd lower airway conductance were also calculated.
-------
212
All of the studies have monitored other environmental stressors
such as temperature and relative humidity. Most of the studies have an
adequate characterization of the pulmonary function including character-
ization of both upper and lower airways. Finally, a good spectrum of
segment of population has been studied including healthy adults and
children, as well as patients with chronic obstructive pulmonary diseases.
i
Results
Larger number of variables were involved in this group of five
epidemiological studies than in the group of experimental studies. The
results of these studies were less conclusive phari the experimental
studies.
All of the studies attempted to obtain correlation between environ-
mental variables and results of the pulmonary function tests. Ambient
i
temperature seemed to have the strongest correlation with changes in
pulmonary function. With decrease in temperature, air-way resistances
increased (A17, A20) and MEF^Q decreased (A20). Increase in temperature
appears to have a dilating effect on both upper and lower airways.
Among other environmental variables, windspeed and humidity had some
effect on the pulmonary function.
In pre-1971 studies only one study (A17) was able to show some
i ;
correlation between concentration of air pollutants (SO_) and decrease
in FEV^ Even in this case, the correlation may be due to very high SO2
levels (peak concentration of .45 ppm) experienced in one segment of the
study. It appears that absence of significant correlations between con-
centration of air pollutants and pulmonary function could be due to the
-------
213
fact that all the pollutants were not monitored. This observation seems
to be substantiated by two of the more recent studies (A19, A20) .
In two studies (A19, A20) performed in Japan on 11-year old chil-
dren, pollutants such as oxidants and nitrogen oxides were monitored in
addition to particulates and sulfur dioxide. Characterization of pul-
monary function was also more extensive as compared to the pre-1971
studies. Ozone and nitrogen dioxide seemed to have effect on the upper
airways of majority of the children during the period November to March
(low temperature season in Japan). Concentrations of NO, SO,, and PM
correlated well with MEFg0 and MEF25 which are reflectors of changes
in the lower airways.
Finally, Kagawa et al. (A20) has found a dose-response relationship
between concentration of NO2 and MEF50 (Figure A-5). Although R2 of this
regression exercise is small (0.20), this is the only air-pollution-re-
lated dose-response relationship which has resulted from this group of
epidemiological studies.
EPIDEMIOLOGICAL STUDIES: GROUP 2 - CROSS-SECTIONAL STUDIES (A21-A25)
Details
The details of six epidemiologic cross-sectional studies are shown
on Table A-IX. Although some of the studies were done over a period of
two or three years, the main aim of each of these cross-sectional stu-
dies was to compare the effects on similar segments of population of
the differentials in air pollution prevalent in two or more areas.
Particulates and S02 were the only pollutants considered in three
-------
214
160
140
1
120
100
Based on Kagawa et al. (A2Q)
R2 = 0.2
extreme-response envelopes
0.05
0.1
0.15
0.2
Concentration of NO,,, ppm
Figure A-5. Dose-response curve of nitrogen dioxide
for children of age eleven years.
-------
TABLE A-IX. EPIDEMIOLOGICAL STUDIES: GROUP 2 - CROSS-SECTIONAL STUDIES
^ .^Studies
Parameter ^"""^-"..^^^
Locations and study
period
Pollutant studied
Average concentration
of pollutants in low
pollution areas as a
percent of the same in
high pollution areas
Interference factors
studied
.
Anderson and
Ferris (A21)
Berlin, N.H. : 1961,
Chilliwack, B.C.
Canada: 1963
PM, SO
PM, 29
S02, 8
Smoking
Lunti et al.
(A22)
Sheffield,
England: Summer
terms 1963-65
PM, SO
PM, 31
S02, 50
Socioeconomic ,
siblings
Shy et
Chattanooga :
1968-69 school
year
PM, SO .sulfates.
NO , nitrates
NO , 64
Socioeconomic ,
sex, month of
testing
al. (A23, A24)
Cincinnati :
1967-68
school year
PM, S02,
sul fates
PM, 64
Socio-
economic
sex, race
New York:
1970-71
PM, S02,
sulfates, NO.
PM, 49
S02, 46
Sulfates, 77
NO2, 37
Socio-
economic, sex.
age group
Mostardi
(A25)
Barberton and
Revere , Ohio :
1970-73
PM, SO22
PM, 70
S02, 78
Race
Pulmonary function tests
FVC
FEVt
PEF
MMEF
Population
FVC
FEV1
Berlin, N.H.
(high pollution)
1261 adults, ages
2574 years
ChillawacJc, B.C.
(low pollution)
558 adults.
ages 25-74 years
FVC
FEV.75
Four areas of
Sheffield (one
in low, 3 in
high pollution
areas)
819 children.
average age.
5 years
FEV.75
Four areas of
Chattanooga
987 children,
ages 7-8 years
*
FEV.75
Several areas
of Cincinnati
394 children.
ages 7-8 years
FEV_75
Several areas of
low, intermediate
and high- pollution
2 364. children.
ages 5-13 years
FVC
PEV.75
(FEV! in 1970)
MMEF (in 1970)
Barberton (higher
population)
50 children.
average age.
14 years
*PM mean and as dustfall.
In these studies, SO2
3PM measured as smoke.
levels were estimated
from lead sulfaticn rates.
to
LT.
-------
216
studies (A21, A22, A25). The other three studies done under the U.S.
Environmental Protection Agency's Community Health and Environmental
Surveillance System (CHESS) program monitored pollutants such as N02,
sulfate, nitrates, in addition to PM and SC>2 (A23, A24) .
A very limited number of pulmonary function tests have been used
in all of the studies. A majority of studies including the CHESS
studies chose to use FEV^ 75 which is thought to be 4 less sensitive in-
dicator of changes in lower airways. One of the factors that might have
influenced choice of the test could be the large number of subjects stu-
died. In five out of six studies, size of the population sample was of
the order of several-hundred. Similarly, in a majority of the studies
effects on children were studied.
Results
,A11 of the studies are able to show some differences in pulmonary
function between groups of subjects who were exposed to "high" and "low"
!
levels of air pollution. In one of the early studies, Anderson and
Ferris (A21) found significant differences in FEV, and PEP in residents
of Berlin, New Hampshire and Chilliwack, British Columbia. Berlin being
a manufacturing center of pulp, paper and paper products had levels of
SO_ twelve times that of Chilliwack, which is situated in an agricultural
area. The differences in FEV^ and PEF were significant even after con-
trolling for age, height, sex, and smoking habits. In this study, PEF
appeared to be a somewhat more-sensitive indicator than FEV, (A21).
In the case of children, most of the studies are able to show
small but significant differences between low and high air pollution
-------
217
exposure areas (A22, A25). The differences in pulmonary function between
low and high pollution have been gradually decreasing over the years as
the air pollution levels in higher pollution areas have been decreasing
(A24, A25).
Results of these studies are less conclusive than the results of
the first two groups of studies. It is felt that the pulmonary function
tests such as FEV_?5 may not be a sufficiently sensitive indicator for
observing effects of air pollution.
EPIDEMIOLOGIC STUDIES: GROUP 3 - LONGITUDINAL STUDIES (A26-A31)
Details
Longitudinal studies on the long-term effect of air pollution on
pulmonary function were conducted (Table A-X) by two groups of inves-
tigators: Lawther et^ aJU (A26-A28) and Ferris et^ ai. (A29-A31) . These
studies were five to ten years in length. Lawther et^ al. (A26-A28) per-
formed pulmonary function measurements almost daily on a small number
of individuals. The second group of studies done in the U.S., by con-
trast used a large sample of population. In the Berlin, New Hampshire
study, Ferris et. al.- (A29-A31) took spirometric measurements twice:
once at the beginning of the study in 1961 and then at the end of the
study in 1967. Particulates and S02 were the only two pollutants moni-
tored in all of these studies.
Results
Results of this group of studies were less conclusive than the
first three groups of studies. Lawther ejt al^. (A26/A27) found small but
-------
TABLE A-X. EPIDEMIOLOGICAL STUDIES: GROUP 3 - LONGITUDINAL STUDIES
Parameters
Lawther et al. (A26,A27) Lawther et al. (A28) Ferris et al. (A29,A30,A31)
Study period
Location
Frequency of
observations
Pollutants studied
Inteference factors
considered
1960-65, 69
London, England
Daily
PM,2 SO
CD
'PM as smoke.
-------
219
consistent seasonal changes in FEV± and in PEP (winter values 1.5 percent
lower than summer). Changes in pulmonary function over a period of years
were less consistent. In fact, there was a gradual increase (1.5 percent)
in PEF over five years whereas a decrease of about 0.3 percent per year
due to age would be expected. One possible reason: performing the res-
piratory function tests daily may have had the effect of "training".
Reduction in air pollution from 1961 to 1967 in Berlin, New Hamp-
shire (by approximately 20 percent in particulates and 30-40 percent in
sulfur oxides) showed some increase in FVC and PEF and inconsistent
changes in FEV (A31). Repiratory infections (A27,A28) and smoking (A29,
A31) appear to be strong factors in influencing changes in pulmonary
function.
MMEF showed the most consistent association with air pollution as
compared to FVC, FEV± and PEF (A26,A27) . The use of less-responsive
tests may be one of the important reasons for the inconsistent results
obtained for the long term effect of air pollution on the pulmonary
function.
COMMENTS
The preceding reviews affirm the recognized complexity of the
problems of interactions of exposure to air pollution and the difficulties
inherent in the design of studies to measure the effects of air pollutants
on human health. It is natural that any document or studies dealing with
the problem of how air pollution affects health would draw criticism. On
the other hand, almost all of the studies, even those not having any
-------
220
consistent positive results, provide useful insights into the complex
problem. The purpose of this section is to review and discuss such
subtle points as well as specific difficulties associated with both
experimental and epidemiological studies, and to develop recommendations
for methodologies and techniques for future studies. The following dis-
cussion on exposure chamber studies is specifically related to experi-
mental studies, subsequent discussion is common to both experimental and
epidemiological studies.
Exposure-Chamber Studies
Studies with artificially generated pollutants have been performed
more frequently than those involving exposure to ambient air pollution.
Even in the case of artificially generated pollutants, exposure to single
pollutants are studied more often than exposure to multiple pollutants.
It is very difficult to realistically duplicate actual exposure conditions
with artificially generated single pollutants and much more difficult to
do so with multiple pollutants. The concept of experimentally controlled
exposure to ambient air which allows simultaneous exposure to several
pollutants present in the atmosphere is thus very attractive. In prac-
tice, however, the experimentation with ambient air pollution poses seve-
ral problems.
Among the environmental variables, temperature may have a greater
effect on the pulmonary function than the air pollutant of interest.
Therefore, temperature must be rigidly controlled in experimental stu-
dies. A substantial portion of particulates present in the ambient air
may be removed in the process of controlling temperature and humidity
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or in the conditioning of ambient air. Similarly, once inside the ex-
posure chamber, pollutants such as S02 or Ox may decay rapidly. In the
only study with ambient air, oxidants were not monitored. The levels
of SO2 were 6 to 62 percent (average 33 percent) of those actually pre-
vailing outside.
To circumvent the problems with ambient air, artificially generated
pollutants are used. With artificially generated pollutants, replication
of levels of O3, S02, NO, N02 is possible but replication of concentra-
tion and composition of particulates would be difficult. Similarly
total oxidants include ozone and other oxidants and even though exact
levels of ozone could be achieved, it would be very difficult to repli-
cate the total oxidants in exposure chambers. Pros and cons of the
artificial or ambient air pollutants have to be considered before de-
ciding on a specific experimental study.
Monitoring of Air Pollutants
Adequate characterization of all the air pollutants is extremely
important. Generally, studies which adequately monitored pollutants
have been able to show consistent and distinct effect of air pollutants.
Unfortunately, only four (A19,A20,A23,A24) out of the 15 non-experimental
!
studies have adequately characterized the six air pollutants present in
the ambient air. It is recognized that at the time when some of the
studies were done (early or mid 1960s), routine methods for monitoring
of pollutants such as NOX, Ox, were not available. However, even in some
of the more recent studies (A11,A25) air pollutants have not been
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adequately characterized and monitored.
The list of identified pollutants is expected to grow. Similarly
the techniques for measurement have been and will be improved with time.
For example, even the reference method for NO2 had to be changed recently
due to its variable efficiency over the concentration measurement range
(A32). The following table gives methods for measurement of various
gaseous pollutants (A33).
TABLE A-XI. SOME OF THE ACCEPTABLE METHODS FOR MONITORING
OF GASEOUS AIR POLLUTANTS.
Pollutants Method based on
S02 Colorometric
Coulometric
Flame Photometric
NO2 Colorometric
Chemiluminescent
03 Chemiluminescent
UV Absorption
CO Flame ionization using
gas chromatograph
Nondispersive infra-red
HC Flame ionization using
gas cfrromatograpfr
In the case of particulates, hi-volume sampler for measurement of
total suspended particulates is a minimum requirement. However, it re-
veals nothing about size or species. Deposition of particles in the lung
depends on particle size and thus hi-vol measurements should be supple-
mented with measurement of particle-size distribution (A34). Similarly,
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223
the chemical analysis of particulates (A35) should be carried out in
order to provide useful information for correlation with health effects.
Pulmonary Function Tests
The distribution of the use of different pulmonary function tests
among the four groups of studies is interesting (Table A-XII). The first
two groups of studies, i.e., experimental and epidemiological-correlation
studies, have almost equal use-distribution of the different PFTs, al-
though experimental studies have used FEV^, MMEF, CV, Cst and Cdyn, etc.,
more frequently. In the remaining two groups of epidemiological studies
FEVfc/ FEV, and PEF or the PFTs which characterize function of upper air-
ways were used more often.
As mentioned earlier in this review cross-sectional and longitu-
dinal epidemiological studies have less consistent results than the expe-
rimental and epidemiological-correlation groups of studies. A larger
number of variables are involved in epidemiological studies and thus the
results are expected to be less conclusive or clear-cut as compared to
the studies done under more controlled experimental situations. However,
it is felt that one of the reasons for less conclusive results of the
last two groups of studies could be an inadequate characterization of
pulmonary function or use of less-sensitive PFTs. A brief review on
sensitivity of the different PFTs follows.
Sensitivity. - Macklem and Mead (A36) have demonstrated that the major
site of resistance to air-flow in the normal tracheobronchial tree is in
the larger or central airways (> 2mm). The smaller or peripheral airways
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TABLE A-XII. DISTRIBUTION OF THE USE OF PULMONARY FUNCTION TESTS IN THE STUDIES REVIEWED
Group
Total Number
of Studies in MEFV Raw, Cst
Each Group FVC FEVt PEF MMEF MEF%VC Curves CV Vtg Cdyn
Experimental studies (A3-A11) 9
Epideraiological studies:
Group 1 - correlation (A16-A20) 5
Group 2 - cross-sectional (A21-A25) 6
Group 3 - longitudinal (A26-A31) 3
68552 444 3
42212
3 61
2231
ro
NJ
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225
(< 2mm), in contrast, appear to contribute very little to overall resis-
tance. The importance of this finding is that early airways obstruction
involving smaller airways may be present and smouldering for many years
before it becomes extensive enough to cause measurable changes in air
flow by conventional spirometric tests such as FEV,, FVC, PEF, etc.
(A37). Similarly, early effects of air pollutants could be on smaller
airways and thus characterization of smaller airway function is essential.
The ability to detect early airways obstruction would appear to
depend on the use of a technique which is capable of measuring changes at
the small airways. Such techniques include closing volume, MEFV curves,
frequency dependence of compliance as well as the spirometric tests such
as MMEF, MEFcjQ, and MEF2^- The measurement of compliance is a useful
technique but it requires complex and costly equipment and, due to some-
what unstable measurements, it may not be suitable for routine use.
The maximum expiratory flow volume (MEFV) curves allow analysis of
flow at both high and low lung volumes. Analysis of flow at low lung
volumes is particularly important in detection of early obstruction
(A38). Bouhuys (A39) stresses that recording MEFV curves can be rigor-
ously standardized, quality-controlled by computer software, and suitable
for routine use. In fact, in an air pollution-effect study of 111
children, Zapletal et. al. (A40) showed use of MEFV curves to be a sensi-
tive and valuable test.
Measurements such as MMEF, MEF5Q, and MEF25 are also suitable
since they provide flow rates at low lung volumes (A41). McFadden and
Linden (A42) showed that even when tests such as Raw, FEV-^ PEF and TLC
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226
were all within the predicted statistical norms, low MMEF represented
significant airways obstruction in peripheral bronchioles. Cochrane
ejt al. (A43) found that in a group of 21 smokers with relatively normal
values of FEV-L, over 60 percent of these individuals had abnormal values
of MEF75, MEFso and FET.
The measurement of closing volume is a simple and sensitive test
for the obstruction of smaller airways. It is also considered to be
well suited for routine use in a pulmonary function laboratory or as a
screening tool in epidemiological studies (A44,A45). However, in one
study (A43) for 9 out of a total of 21 subjects, there were difficulties
in the intrepretation of tracings of closing volumes. Similarly for
closing volume measurements the range of the normal values is large
which tends to diminish the usefulness of the technique (A46).
The above comments on the relative-insensitivity of conventional
spirometric tests (FVC, FEV1, PEF) to detect minor abnormalities in
small airways and to detect effects of air pollution are in essence the
same as those made in 1968 by Bates (A47) and by Frank (A48). The
choice of appropriate and sufficiently sensitive PFTs may determine the
potential for results of a given air pollutionTeffect study. For ade-
quate characterization of pulmonary functions, a combination of tests
that are sensitive to lower airways (such as MEFV curves, MMEF, MEFcQ,
MEF25' FET) as well as tests that are predominantly for detecting resis-
tance in upper airways (FEv^, PEF) should be used.
Interference factors. - There are many factors which could interfere
with a measurement of effects of air pollutants with pulmonary function
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227
tests. Smoking, respiratory illnesses, as well as environmental factors
such as temperature have considerable influence on the results of pul-
monary function tests. A reduction of 8 percent in PEF was noted in one
study (A26) following a respiratory illness and the magnitude of changes
due to infections was large as compared to observed seasonal variations.
Thus, in any air pollution-effect study even trivial illnesses such as
the common cold must be recorded.
Smoking, not surprisingly, has an overwhelming influence on pulmo-
nary function measurements (A21). In the analysis of an air pollution-
effect study, particularly, in case of a cross-sectional study, not only
is it required to treat smokers and nonsmokers as different groups, but
within the smoking group, light or non-inhalers versus inhalers,.as well.
as number of cigarettes per day should also be noted.
Substantial diurnal variations (20-40 percent) are present in some
of the pulmonary function measurements. Lowest Gaw/Vtg as well as lowest
PEF in a 24-hour period were recorded during early morning (0300-0600
hours) in two separate studies (A11,A28).
As discussed earlier, several studies have shown that ambient tem-
perature has a strong influence on the pulmonary function (A16-A19).
Sometimes it is difficult to separate the effects of temperature and of
an air pollutant such as S02 (A49). Both a decrease in ambient tempe-
rature or an increase in the SO2 concentration causes a reduction in
pulmonary function. Thus the separation of the effects of the two var-
iables is especially difficult for winter months since as the temperature
decreases the concentration of SO2 increases because of the increased
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228
combustion of sulfur-containing fuels for space heating.
Finally, daily measurement of pulmonary function may have a
"conditioned training" effect which may distort any trend analysis of
the measurements (A27). Thus, frequency of observations should not be
greater than once a week in long term longitudinal studies.
Population
In a number of studies it was observed that some individuals in
almost all of the groups of subjects that were studied were hyperreactive
to environmental changes. Table A-XIII shows the number of hyperreactive
individuals and the total sample in various studies. Although none of
the population samples was truly random, it is interesting to note that
10-50 percent of any segment of population including children, adults,
and individuals with lung disease could be hyperreactive to air pollution
and other environmental factors. These individuals, in general, may be
expected to show stronger clinical symptoms in case of respiratory in-
fection.
Sensitivity to respiratory infections may not be the only factor
responsible for hypersensitivity. However other factors for distin-
guishing individuals hypersensitive to air pollution are not known. In
the Hackney et al. (A9) study, one-third of the individuals who were not
thought to be sensitive before the study showed hypersensitivity to air
pollution. Conversely, not all of the patients with chronic obstructive
pulmonary diseases were hypersensitive to air pollution (A18).
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229
TABLE A-XIII. PROPORTION OF HYPERREACTIVE POPULATIONS IN
SELECT EXPERIMENTAL AND EPIDEMIOLOGICAL STUDIES.
Number of
Population Hyperreactive
Study Sample Individuals
Emerson (A18) 18 adults
with COPD1 7
Kagawa et_ al. (A20) 20 children 6
Lawther et al. (A26) 4 adults 1
Hackney ejt al. (A9) 13 adults 7
Bates e_t al. (A3) 11 adults 1
Hyperreactive
as Percent of
Total Sample
39
30
25
54
9
^Chronic obstructive pulmonary disease
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230
ASSESSMENT OF HEALTH-EFFECT STUDIES
Rationale
The optimally designed study should include: (a) monitoring of
all air pollutants permitted by the "state-of-the-art", including those
pollutants which are not specifically being studied, (b) use of suffi-
ciently sensitive tests for adequate characterization of effects on
pulmonary function, (c) elimination of or accounting for interference
factors, and (d) at least a part of population sample consisting of
hypersensitive persons. These factors also permit a rational evaluation
of the relative merit of the methodologies used in past studies for an
assessment of present status of research and future needs. In determining
the relative merit of methodologies, the degree of resolution and the
quality of the results were considered to be of significant importance.
The rationale was that the results of air-pollution-effect studies in the
form of cause and effect relationships would have good resolution (i.e.,
significant differences in measurements for the control values) and be
of an acceptable quality if cause, effect, and interference factors are
defined with sufficient detail and if a sensitive population sample is
used.
Approach
For the evaluation of relative merits of methodologies only two of
the previously listed factors: characterization of air pollutants and use
of sensitive pulmonary function tests are considered. The other two
factors would provide more stringent criteria but were not used in this
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231
assessment. The approach was to individually rank the two factors for
each of the studies based on the following criteria:
Ranking
(a) Characterization of air pollutants
(i) all air pollutants adequately monitored 1
(ii) study-pollutants adequately monitored, but
inadequate characterization of other pollutants 2
(iii) inadequate characterization of the study
pollutants 3
(b) Characterization of pulmonary function
(i) at least one PFT for characterization of smaller 1
airways (Cst and Cdyn, MEFV curves, MMEF, MEF5Q,
MEF^c, FET, CV, etc.) and one PFT for upper airways
(FEV, PEF, Raw/Vtg, etc.)
(ii) at least one PFT for smaller airways 2
(iii) no PFT for smaller airways 3
In ranking the degree of resolution and reliability of the results
for a given study, the lower of two rankings for characterization of air
pollutants and pulmonary function was considered to be the appropriate
one. The reason for selecting the lower ranking was that since these
studies evaluate the relationship between two interdependent variables,
both factors have to be characterized equally well. For example, in
Young et al. (A3) the characterization of both air pollution and lung
function meet the criteria of rank one and, thus, this study was rated
to have a high degree of resolution and reliability in its results.
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232
Conversely, in the study with experimental exposure to ambient air (All),
even if characterization of pulmonary function were ranked as one, all
air pollutants were not monitored and thus this study was rated to have
a low degree of resolution and reliability in the results. A similar
approach was used for evaluating all the studies and totals for each
group of studies are presented:
TABLE A-XIV. RESULTS OF ASSESSMENT OF THE HEALTH-EFFECT STUDIES.
Number Degree of resolution of and reliabi-
°f lity in the results of studies
studies
Studies High Intermediate Low
Experimental studies 97 1 1
Epidemiologic studies
Group 1 - Correlation 52 3 0
Group 2 - Cross-sectional 60 0 6
Group 3 - Longitudinal 30 1 2
Results
Table A-XIV shows that most of the experimental studies had adequate
monitoring of air pollutants as well as of pulmonary function. Approxi-
mately half of epidomiologic-correlation studies had potential for a high
degree of resolution and reliability in results. Most of the cross-
sectipnal and longitudinal epidemiologic studies had either a poor charac-
terization (rank 3) of air pollutants or of pulmonary function and conse-
quently most of these studies were rated as having a low degree of reso-
lution and reliability.
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233
The above observations are generally the same as one would get
from reviewing the results of different studies which were discussed in
preceding sections. Experimental studies have yielded dose-response
relationships for ozone. This should not imply that no additional research
is necessary or that generalized dose-response curves can be constructed
from available information, but it is clear that, with adequate charac-
terization of air pollution and the effects on pulmonary function, expe-
rimental studies have yielded conclusive and useful results. Similarly,
epidemiological correlation studies have shown correlations between the
environmental and pulmonary function variables. In addition, one of the
correlation studies has been able to show a tentative dose-response curve
' for NOo- The results from'the last two groups of epidemiologic studies
are less reliable and the conclusions are less clear. The reason for
this could be inadequate characterization of air pollution as well as of
pulmonary function.
The important conclusion that can be drawn from this assessment is
that the lack of epidemiological dose-response data is not due to lack of
studies, but is due to a lack of results or data with high degree of
reliability.
CONCLUSIONS
Numerous studies of the health effects of air pollution have used
pulmonary function tests for the characterization of effects on a human
lung. Enough data for construction of generalized dose-response curves
are not available. Thus the tolerance factors derived from the air
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234
quality standards still represent the best available approach for a
relative assessment of the deleterious effects of simultaneous exposure
to any combination of the six pollutants.
Short term effects of ozone with exposure-duration of up to four
V
hours have been extensively studied. Figures A-l and A-3 show dose-res-
ponse relationships in terms of pulmonary function measurements for
ozone. Short term effects of other pollutants as characterized by pul-
monary function tests have received little study. Epidemiologic studies
involving cross-sectional and longitudinal analysis have not been very
fruitful beyond showing a qualitative association between air pollution
and decrease in the pulmonary function.
Many factors inter fere with a plausible demonstration of the rela-
tionship between air pollution and its effects. Effects on pulmonary
function of ambient temperature, smoking, and respiratory infections
overwhelm the possible effects of air pollution. A number of studies
have identified some of the individuals in the population sample as
hyperreactive or hypersensitive to air pollution.
The importance of adequate characterization and monitoring of all
the air pollutants and adequate characterization of pulmonary function
cannot be overstressed. For any future study to be productive in terms
of conclusive results, the study must monitor all the air pollutants, use
sensitive tests for measurement of the pulmonary function, eliminate or
account for all the possible interference variables and finally, include
in the population sample a group of population who are hypersensitive to
air pollution.
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235
In the future, experimental studies involving exposure of several
days to concentration of ozone and sulfur dioxide which are lower than
previously studied such as 0.1-0.3 ppm of ozone and 0.05-.5 ppm of sul-
fur dioxide and other pollutants with concentrations near the ambient
standards deserve a priority. In the case of the air pollution-epidemio-
logical research, the studies aimed at quantifying long-term (5-15 years)
i
longitudinal effects of air pollutants are needed.
Finally, at the risk of being repetitive, future epidemiologic
studies must take into account all of the factors discussed above.
Failure to do so in this area of complex research will diminish the value
of the results obtained.
-------
APPENDIX A
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i
A48. Bates, D. V.: Health effects of oxidants - Discussion. J. Occup.
Med. 10: 480-484, 1968.
A49. Carnow, B. W. and Namekata, T.: Impact of multiple pollutants on
emergency room admissions: II Analysis for the entire study period.
Project No. 10.033. Chicago, Illinois: Illinois Institute of
Environmental Quality, 1975.
-------
APPENDIX B
LISTING OF THE COMPUTER PROGRAM
241
-------
rcKTSAN ly c
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».INO=5,
5 itiKT = l .
fi- ( 1 ) = 54 .
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CO S K=l .5
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C COMPACTNESS OK A 1 - CtWfcNSIGNAL AHHAY
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CALL OISTAN
CALL PINOEX
CALL MASSE
CALL SUMDIS
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00*3
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IJCP.CP .E.U. 12) GC TO 25
CALL SENog
CC TC 1
10 FCRMATd 1 IS)
^OPTIONS IN EFFECT* KCTERM.ID.EbCOiC.SOtWCE iNOLIST.NCCECK.LUAO.NCMAP.NQTEST
OPTIONS IN EFFECT* KAKt = MAIN . LINECNT - 50
STATISTICS* SC.L'JCe STATEMENTS = *7.PKaORAM SIZE = S4U
~*STAl 1ST l(-b* Nlj U1AONCST1C.S OcNcKATED
-------
FORTRAN IV Gl
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24 IF(D .l-T. .7) GO TO IOO
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15/43/25
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25 EMSbllOl )-SUP-K( 101 )/CTOT*lOO.
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*OPTIONS
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SOUHCE STATEMENTS =
NO DIAGNOSTICS vlf
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171
-------
FORTRAN iv GI HEL=ASE n.o NAKQ CATE = ? = ji2 15/43/25
t*4«»1*»**t*»»********************************************
C
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C A^5t>KC5^ Or A I u I MtNS ICNMU AK t< A^? V_U'*** **************************
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-------
FUKTRAN IV GI SELEASE 2.0
_QOOl SliiNL'tT 1\E
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DATE
7S3I2
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IF! IS .i'3 0) GO TO 10
1CEX= !S.JO( I , J,l >
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STATISTICS* NO OIAGNOSTICS GENERATED
SI/E
"1414
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FOHTRAN IV Gl-
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0003
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RELEASE 2.0 HI TEA DATE = 75312 15/43/25
SLOftCUTINE: RITEA
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CCKMON /LtrV 1G1 ( 1 1 ) .X ( 1 1 ) .Y( 1 1 ) ,FOP( 1 1 ).AREA{ 1 1 j > 1CO{ 1 1 . 2 ) .
CCVVCN XCS/ CCNS(£60.4)
COMMON /PlMOE/ PiCUCeide 1 ) .PPM! Sol ) . PSUX (ttbl ) , PNOXI 861 ) . PCO(861 ).
1 Pt-C(ttl)
COfMCN /I"f/ OCQNU1 .11 ) .CCONd 1 ) ,EXPC(23OO) .EXPAd 1 )
CCMMCN /CPT/ JUBOP.OSC. JF(S>.FF(S) .WlND.TheT.SIGMV.SIGMZ
DIMENSION ADUPt 1OOO) .AOUFU 1OOO > - USE
CO 10 1 =1,1)00
ADUC1 < I )=0
AUUC2( I )-O
CC »9 M^-1.4
ISf ISM 1 1
IT( li .E.Q, O) GO TO 16
Cu ^0 J=l , IS
ACUf , 12 X , 'TABLE XI. EKISSICNS A NO KESLLTS OF MASS I
INOEX. F-iNDC-X ANO POPEX FOR EACH CF T HE' . / .2JX. * SOCRCE-C ATEOOR IES 'I
30O1 WKF.TC ie.*OOO>
4OOO FCKKAT < .13X. 'SOljSCE TOTAL PM SO2
I NOX CO HC« ./,12X.«CATE&OBY« ,//)
OC 2? 1=2.661
3
I
I
i
to
Ul
en
-------
0049
0050
O 0 "j \
OOt.2
OC3"
i>0 bo
0057
oosa
ooto
GOtl
COC-2
OOC3
OOti
OOSc
OOo7
ooea
OOC9
0070
0071
0072
00?.»
O074
OO 75
0076
0077
007B
OOT9
OOBO
00£>2
0063
OOrfS
COSfc
OOBO
OOS9
O090
OUVI
0092
0093
0094
009o
OCS'
0090
\j o y y
01 00
Ol 01
0102
010J
0104
DIVlrj = SPM(I) + SSUX»SHCt It
iF(oivio .ea. o .AND. ACUPC i ) .Eo. o J GO TO 22
HAT I UP=SPM< 1 i/Dl V1D
RAT[UN=SNOXi I )/OI VIC
RAT 1CC=SC(]( I I/O IV ID
rtAT ILH-ShC( I I/O IVID
cPKil. At ICP+ADoP( 1 J --
tSCX^KAT 1 OS*ACUP{ I >
fcNOX=HAT I CK*ADOPI 1 j
ECO=KAT1CC*AOI/P(I !
IFtSSKl .NE. 1 i AOUP2 ( I I
22 CONTINUE
5000 FCKMAT ( , 1 oX . I 3 , 2 X . EM I S3 1 CNS ,F I I . 0^5F 1 o. O/22Xi MASS _ I NDEX .
»RI JE ( t ,St }
£6 FCki^AT (1H1. " M.'M MASS INDEX PINO6X PI/M POP6X
I PO/P1 )
IF (ACUP(I) «LE. O.) GO TO 300
PMK=AOl,P2< I >/ADUPl ( I )
P1NMK = ADUP1 ( I ) /ACUHIi
1006 FOt-MAT ( '0' .5X. 15.SF10.3)
3OO CCNT INUE
»R1TE|6.IOI2). .ADUP2. 3x . D If rCBCUCCS" //")
[)U J 1 1=1. 10OO
IF(Al)UP2(I> .EO. 0) GO TC 31
C IK'» = AD'JF ( I )-AL>UP2( 1 )
O1F6=ADUP( I 1-ADUP1 ( 1 )
DIP l=AbS< OIF4 )/AOUP2< I 1 »100.'
01F£-At»S(UIK5 I/ADUP2 ( I 1*100.
SLD1=SUD1+OIK1
SLD J=SOU3*DIF3
SLtm^SUC'D »ABb(DIf4J
»R1>TE?6'". foto) 1 .AOUP2( I 1.DIF1 .DIF4 ,O IF2. O IF5 . O IF3 .DIF6
10 1U PCMtATt' ,3A, 1 3. SX.F10 . J. J(F 10.2 t 1X«I lO.E.jXI 1
31 v'CNTlNUt
10.1,3 FCRJ'»T(''l°!5X.'THc SCW OF OIF l-6'/^J
- -T> till-in tin.^ OliriT T.I in A '"lirifiullinrj
___ ftH'i Tfc.(tr;-fOl 1 ) SUO1 « SLD2 «2UOJ*5UD4 » jUO j JUU'J
1011 FORMAT (' ,5x,6f=l0.2)
CO TC 99
93 NNNNN=3
IM JOB .EC. 2) GO TO £00
t
:
i
a
m
NJ 4
en
ON
-------
01 05
O106
0107
Cii Ott
0109
01 10
0111
U 1 1 «£
0113
Ol 14
U4 1 6
01 ID
0117
olio
ul IV
O121
O12Z
O12J
0124
O125
01?6
u I «2 r
OI2B
0129
Ui -3U
O131
0132
O133
O i J1*
0135
0136
0137
u i Jti
0140
0141
U 1 42
0»4J
OJ44
014S
01 411
01*7
Ol4tt
C14V
OlbO
0151
0132
01 S3
" Ol 91
015S
O1SO
0157
' u I 38
0159
*RIT§ (6.50)
DO 3= I=i .1000
35 iChT ( I )=AUUM( I )
I'll iai-i- - i i t sin i .naUt-T, lui}j) ..,,.,
CO 40 l=l,10JO
I I=MSChT< I )
IF(ADUPCIt) .fcO. 0) CO TO 40
1 AOUP( I I ).AOUPi«l I I .AOL-F2( I I »
1005 FCHMAT( «0' .SX. I E .5X , 4 < 2X , 13. 2X ) . 3F 1 0. 2 .3 1 5 . 2F 1 0 .2 )
40 CONTINUE
CO 45 1=1 . 1000
45 SORT ( 1 )=ADUP1< I)
CALL SCFiTlTCSORT.MS3RT.10OO)
I 1=MSCRT( I )
IF(ADUPKII) .EQ. 0) GO TO SO
WRITE (6. 1005) I l.(MX(I I.NM).NM-1,4).
1 AUUPIIL). AOUP1 1 1 1 J . ACUP2 ( I I t
SO CONTINUE
99 KNNNN-3
C
!_ 1 AULt SiA - '" '' ' '
r« »*»»*<»«<»*«»«»«»*»»»»**»»***********»*»**»»*«*****»»«**»«****««»*«**
fcCOl CONTINUE
SSKl=l
1014 FC^MAT <*1'.11C/1> SX. 'T/-8LE XH. CHIACGO *OCR SCOPCE-CATEGOR1 ES
1 IM THE DECREASING CHOER OF POPEX.".//)
»M ITEI6. 1015 )
52 SPO( I )=0
Ct 51 1=1 .100O
CALL SC«TIT(SCRT,MSOfiT,lOOO>
CO 5b 1-1.1000
1 I = MSCRT( I )
'CAUUP2tiIl .KG. 0) GO TO Jb _ .
A =AL"UE 1 ( i >
A1=AUUH1 (II)
A2=ADUF2C 11)
It-' (Al.GE. AA)K1=1
IF IA2.CE. AAIK2=»
IF (A .GE . Lib .AND. A .LT . AA) K =2
1PJA1 Gl- OO AfjO PI LT AA ) Itl"""
irCAzlcI. Ob .AND. A2.LT. AA> KZ=2
IF (A .CE. CC .AND. A .LT.BBJ K«3
IF (Al .CE. CC .AND. Al .LT.tB) Kl=3
IF (A .Ot. DO .AND. A .LT . CC) K=4
IF (Al.GE. DO .»NC. Al .LT . CC) Kl=
-------
01 60
(JIM
Ol 62
OloJ
Olii-t
016ti
OlOO
0167
0168
0169
Ol 70
0171
01 72
01 73
01 74
0173
Ol 76
0177
0179
01 60
Ol 81
0182
0163
01 34
01 ES
01 fc6
01 87
01 at)
0189
U 1 VU
0191
0192
019J
01 <»
0195
0196
0197
01 -
0216
0217
0218
0219
1021
1O20
211
203
100
101
us
110
SCO
T20
tu
P*K=AOLP2( I 1 ) / AOLP(II)
If= (SSM .M*; JS > CC ti 211
SSK!=1
»KJTt )
RltC (6.1020)
FCR«AI ('I*. 111/). cX. 'TABLE XII. CONT INUEO. // )
wire (c.ioib) . -
SSK1= SSKl+1
Rut (e. 1007) i i,(ccA5( n.J) ,j=i .;) .AOUPI 1 1) .AOUPI ( 1 1) .
1 ADUP21 I 1) . K.K1 .K2
ci_N;ru- Kl 2
1F(A .Gfc. CC .ANO. A .LT. dd) K=3
IF(A1 .uE. CC .ANC. Al .LT.bb) Kl=3
IF(A .GE. DO .AND. f .LT. CC) «-t
II- 1 A i .Oc« DU .A!SC. Al .LI. CC) Kl-J.
IF I.ADUP2C 1) .DI .OJF.AOD( I ),K.K1
FCRMATC .5X.I5.F12.5.2FJ0.2.F12.5.2I10J
CLNTINUE
NAD=0
DO 60 1=1 .10OO
1FCAODM-) .NE. 0) NAC=NAC+1
CLNT iNOt
S1=SAC/NAD
,
- .
-
I
i
z
I
,
D
m
M t 1
Cn
- 00
-------
§220 S2=SDI/NAD
2<2t **ITE (o.glOl J06UP.S1 .S2.rOTC.TTC
02iJiJ £10 FCSKAT ("I'l 5X.'JOdOP=«. I3t« AVG PCT O IFF=« .F10 .3.
- T" - AVO lUFF-i ' . I- 1U.H. ' - Cn.M'i I IV HAMK1KOS-' .!». - '
2 ChNG feNK J-2 OR 2-l=",I3)
0223 1007 FCkMAT (< . 1 JX . I 3.2X .8 A4 . A J.3G 1 0 .2. 3X. J I 5 1
IOIS FCKMAT < 0« . 6»X , 1 . / . 1 1 X , SOURCE SUURCE-CATbGGMY NAMt",J6X,
240X.
3'Ml PI PO MI =! PO'/>
O22S 2OO JOB=I
0227 END
N kl-rtCT* ^UlknM.l
OPTIONS IN EFFECT* NAME = SITEA LINECNT = EO
STATISTICS* SOURCE STATEMENTS = 227.PRUCHAM SI2E = 315*4
»STATISTICS*NO OIA&NCSTICS GENERATED
NJ
Ul
-------
FOKTHAN iv Gi
0001
OOOZ
O003
0004
0005
OC06
OOO J
0003
000<<
0010
001 1
OCI2
OO 13
OO14
001 b
0016
0017
00 It)
. 0019
0020
OC21
0022
0023
0020
0027
0028
OOJO
0031
OOJ2
0034
RELEASE
C
C****
C
C
C
C
C****
C
C
C
C
I
100
C
t
C
2
101
t:
C
C
3
C
C
C
bit
51
C
C
C
2-0 SENSE DATE = 75312 15/43/2b
Sl.Ra,1llTIKF SFN«,F
»**»*******«*«»*»«**»*«*«»«***»» t««******v* ************************
Tt-IS SUBFOoriNE CcFEhMINES MO* SENSITIVE THE MODEL IS TO
VAKiACLb i.nAMjc.ij
*»»**»***»********»*»»»**»»***»* »*»*«*»«»****»*»»«***********»*»»»
I.LMMLS / bO/ 1 bM 1 1 ) iNST ( t 1 ) .IVS£ ( 1 1 ) -
COWWGN /dlG/ SUORCEt I60C01 .MX(Uel.4>
CCKMCN /Al/ NC.IO<2300I
CCVMON /CRT/ jabOP.DSC, TF15) .FF(S) . * INO. THtT . SI GMY ,S I GMZ
I . JU'J
CI-ECK=0
(.HtCKb U^C &£zl\d i 1 1 V i 1 T
CSC=OSC»J .5
JJ=1
OGC=( 1/3.)*DSC
GC TO 1O
TF<5) = FF{4)/25.
JJ=2
^} U 1 U i U
TF( 1 J=0
TF(2)=l
GO TC 10
CHECKS JOBOP 3-6
KK=JC£>GP-2
1MK.K .tU. 4) bU tU SO
FF(KK)=1 .5»FFtKK)
TF-tKK )=FF < 4.J./FF
-------
OO36
0037
OC3B
Ou«U
UO4I
OU44
OC'<. 3
OC47
UCoQ
OOil
0052
O05.3
OOSS
OO'.'O
OOSf
0059
coeo
OOfil
0002
OOtJ
OO6*
ooos
UU6b
O067
OOOB
OCb9
0071
O072
0073
' OUf*
00/5
0(176
0077
UD/B
OO79
OOdO
ooai
103
c
c
c
1O4
c
c
c
0
10S
c
c
c
f
25
ice
31
35
10
20
GC~TC 10
li. rc To ' -
SIGMA ₯ SENSITIVllY
JJ=5
GO TO 10
bu i u i u
SIGMA 2 SENSITIVITY
b IbXiai.s
JJ=6
liQ TO 10
SIGK2=.5
tu I l. 10
PCLLUTI3.M HEIGHT SENSITIVITY
UL £ 1 1-1 . 1 1 ' .
IK IS lEC. 0) GO TO 21
DO <;= j=i.is
i I\LJ- i SOU vI.J.C> .' ' " ' . . ,- .. -
SvWRCEt INO)=SOUHCE< INOi *I.S
JJ-7
DC 30 1=1.11
IS-1SN( I )
IFIIS .EQ. 0) OK TO 30
lCEX=NA«tJ( I. J)
IKD=[ SCO! I.J.fc)
ir < I L'( ICtX ) .OK. 821) GC TO 31
CO TC- 35
5ClMC£( INOJ = SCURCE< INC) *l/3.
CCNT I Nut
CALL DISTAN
CALL PINOt-X
CALL MASSE
CALL SUMO IS
CALL RITE A
IF (CHECK .EQ. II GO TO 2O
GC"*TO Jioo.xct . 102. iC3.io«.ios,ioe>.jj
RETURN
END
*OPrlONSTAT15TICa
STATISTICS*
NO DIAGNOSTICS OENERATEO
to
.cn
-------
FORTRAN IV Gl
0001
0002
0003
OO04
OOU:>
OOOe
0007
OOOo
0009
OO1O
U01 1
0012
13
00t«
OOtb
0016
001 7
001M
*CPT IONS IN
OPTIONS IN
STATISTICS*
STATISTICS*
RELEASE 2.0 SCRTIT . DATE = 75312 IS/43/25
SiilHOUIINt SGHTITISOKT.MSPHT.NII
c**»*****»«*»*»«**4»»**»»*»*l»*J*.**»***»»»**+»»»» ++*****»4***** **»*-***
c
C SORTING SLdKQCTlNE
C
C ti-Ia IS A CbCHcAin.SiG GRCEtt 3UBBLE i>UK 1
C IT LLAVES THE AMHAY TU EE SURTtd IN ITS ORIGINAL OHOtA
C IT LEAVES Tht ) GO TU 20
3U=Si:« 14 -i 1
SCRU I ) = SCRT«NJ
:»CRT(N) = SU
MX=MSCRT< I I
KiUHT I 1 > = VtsuKl IMI
MSOMT (M=MX
20 CONTINUE
16 CCNTINLiE
KETUKN
END
EFFECT* NAME = SORTIT . LINfcCNT = SO
SOURCE STATEMENTS = IS. PROGRAM Sl££ * £24
NC DIAGNOSTICS GENERATED
OOOOOOOO
-OoootrOTtr
00000020
OOOOOOJO
COCO0040
OOO
-------
FGuTRAN IV Gl
com
O002
OC03
OOOA
OOOo
OOC7
Ui*ilM
J009
CoiO
001 1
Or>12
00 H
Q01»
fli/;s
uo lo
U01 7
301.1
JUI J
ooi'a
CT/ JOBOP.DSC.
1 . oO3
COMMON /VALV £MSS(2300)
uC 10 J=l .NC
DC Ic 1=1 .SC
15 CCON1 J)=CCCN( J) + BCCNC
10 SoMcXP=S^M£XP * EXPA(J)
DC ?.Q 1=1 .NC
IS=1SM 1 )
DATE = 75312 15/43/25
I.CCONU 1 ).£XPC(2300).EXPA( 11 )
11) ,Y< 11 ) , PUPlll ) .AKiiAd 1).ICQ(11.2).
Ill) .NS2C 11)
TF(i) .FF(S).WINU.ThET,SIGMY.SIGM^
,PIND(2JOO) .PCPEXP12JOO)
i.J)
.
CO 26 S=l . 15
£5 POPEXPINA)=(EXPClNA)/SUHeXP) * 1OO.
ftRiTE (6.6CI
ION MATRIX*.///)
SX.'PINOcX COHRECTfcD POLLUTION CONCtNTKATI
5O HJhHATll 1 (SX.A4) . TO1AL FDR CCL.NTV")
CO 30 J=1.NC
30 Af\lTF (e.AQ) (tICCNd . J) .1 = 1 .NO .CCON(J), 1CC( J.I)
RETURN
6 NO
x.-rrEvr2TT
TO-
nrr
TX
«A»)
OPTIONS IN EFFECT* NOTERC . I 0 .Ei3CO 1C. SOURCE .NOL 1ST,NOOECK.LOAD.NOMAP.NOTEST
UPT1CNS IN EFFECT* NAME = SUMDIS . L1NECNT = £0
STATISTICS* SOURCE STATEMENTS = 29.PROGRAM SIZE = 1060
»!>rAI I5T1C5* 'MO Ol«l»NCSrlCS tSC^t^^ATEO
STATISTICS* NO DIAGNOSTICS THIS STEP
IO
U>
-------
APPENDIX C
LISTING OF THE SOURCE-CATEGORY NUMBERS AND THE
SOURCE CLASSIFICATION CODES (SCC)
2 04
-------
NO.
sec
SOCECB CIASSIFICATIOS COPE (SCC1 CATEGOM NAMES
1
a
3
*
5
b
7
H
9
1O
11
12
13
14
IS
16
17
la
19
20
21
22
23
24
25
26
2T
28
29
30
1 Ol OOl 01 EXTCOUe
1 01 001 02 EXTCOHB
1
1
1
1
I
1
1
1
I
1
1
1
1
1
I
1
1
1
1
1
1
1
1
i
1
I
1
1
01 001
01 001
01 001
01 001
01 OOl
01 002
Ol OO2
01 O02
01 002
01 002
01 002
Ol O02
01 002
01 002
01 OO2
01 O02
01 O02
01 OO2
01 003
Ol OO3
Ol 003
Ol 003
01 003
01 003
Ol 003
01 OO3
Ol O03
Ol 003
03 tXTCUMB
04 EXTCOM3
05 EXTCOMB
06 EXTCOM3
99 EXTCOMB
01 EXTCOMB
02 EXTCOMB
03 EXTCOMB
04 EXTCOMb
05 EXTCOMB
06 EXTCOMB
07 EXTCOM6
08 EXTCOMfa
09 EXTCOMd
10 EXTCOM9
11 EXTCOMB
12 EXTCOMS
99 tXTCOMS
01 EXTCOMb
O2 EXTCOMB
03 EXTCQM&
04 EXTCOMB
05 EXTCOMd
06 EXTCOMb
O7 EXTCGM8
oa txTCOMc
09 EXTCOMfa
1O EXTCOMb
BOILER
8OILEK
BC1LEH
BOILER
60ILCR
ctOlLEa
BUI LEA
bO I LER
BOILER
dOlLER
bOILER
BtilLEri
BOILER
C.OILEK
bOILER
UOILER
BOILER
BO ( LEH
BOILER
bOILER
BOILER
B'JlLER
COILED
BOILEH
UOILER
bOJLES
BOILER
BOILER
dOILER
BU1L EH
/ELECTRIC
/ELECTRIC
/ELSCTHIC
/ELECTRIC
/ELECTRIC
/fcUECTRIC
/ELECTRIC
/ELECTRIC
/ELECT HI C
/ELECTI'IC
/ELECTS 1C
/ELECTRI C
/ELECTHIC
/ELECTRIC
/ELECTRIC
/ELE<-TRIC
/ELECTRI C
/ELECTRIC
/ELECTRIC
/ELECTRIC
/ELECTRIC
/ELECTKI C
/ELECTHIC
/ELECTRIC
/ELECTRIC
/ELECTHIC
/ELECTRIC
/ELECTRIC
/tLECTHIC
/ELECTRIC
OC.NLAATN/ ANTHRACITE
GENERATN/ ANTHRACITE
G&NERATN/AKIIHKACITE
GsilMERATN/ANTHHACITE
liENERATN/ANTHRAC ITE
GtNER A TN/ ANTHRACITE
GENERA TN/ ANTHRACITE
GENLRATN/b I TuM I NOUS
GENER AT N/d I TUM i NUUS
OcNERATN/t> I TUM i NOUS
GEMtRATN/b I TUMI NOUS
GENERA T N/a I TUM I NOUS
GENERATN/dt TUMI NOUS
GENtH ATN/B I TuM I NUUS
GtNEP. AT N/d 1 TUM I NUUS
GENERA TN/B I TUM I NOUS
GcNtHA TN/dlTuMl NOUS
GENER ATN/B I TUM 1 NUUS
GENERA TN/t) 1 TUM 1 NOUS
GENERAT N/B 1 1 UM I NOUS
GENERATN/LIGN1 TC
GENLRATN/L IGNITE
GENEH AT N/C IGNITE
GENENATN/L IGNI I E
GENER AT H/L IGNITE
G£NE0A rN/L 1 GN 1 t f
CENERATN/L 1 GN1 T E
GENtHATN/L IGNITE
GENERATN/L IGNITE
GENER ATN/L IGNITE
COAL
COAL
COAL
COAL
COAL
COAL
COAL
COAL
CUAL
COAL
COAL
CUAl.
COAL
COAL
COAL
COAL
COAL
COAL
COAL
COAL
/GlUUMMbTU FULVIZO
/GlOOMMbTU STOKERS
/ IO-10OMMBTU PULVD
/ 10-lOOMMBTU STuKh
/LlOMMnTU PULVIZt-O
/LlOMMuTU STOKEk
/ OTHhft/NUT CLAS IFO
/GlOOMMbTU PtlLV«ET
/GtOOMMBTU MULVDHY
/G1OOMMBTU CYCLONE
/GIOOMMbTU bPOSTKR
/GIOOMMUTU/HH UFSK
/ 10-10UMKBTU PUL*T
/ 10-1COMM3TU POLDY
/ 10-lOOMMbTII OhSTK
/ 10 IOOMMOTU UPSTK
/LlOMMdTU OFSTUKEfc
/LIOKM6TU urSTOKER
/L10MMUTU PULV DRV
/ OTHER/NOT CLASIFU
/GlOUMMbTU PULV*ET
/GlOOMMbTU PULVDRY
/blOOMMbTU CrCLuNE
/G1OOMMBTU OF STKk
/G10UMMOTU UF STKR
/b*00MMfe*U SPOSTKh
/ 10-100WMbTU DYPUL
/ IO-IOOMMBTU «TPUL
/ 10-lOOMMBTU OFSTK
/ 10-100MMUTU UFSTK
/TUNS
/TONS
/TONS
/TONS
/TUNS
/TONS
/TUNS
/TONS
/TONS
/TUNS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONU
/TONS
/TONi
/tONS
/TUNS
/TONS
/TONS
/TONS
/TONS
/TONS
/IONS
/TUNS
/TUNS
/TONS
/TONS
bUKNtD
UURNbO
bUHNED
UUKNEG
bUi<.Nc:L)
bUKN&O
DDK i-ilLU
BURNED
BURi<4E*O
UU^NEJ
bUii Nc. O
. uUANED
BURNtO
SUtiNfcD
BUWNElJ
UUKNKU
tlURNLO
bJQUt'U
BUi
-------
31
32-
33
34
35
36
, J7
30
3V
40
41
42
43
44
45
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1 71
1 72
1 73
174
J 75
176
177
178
179
180
182
163
184
185
1
1
1
1
1
f~
1
2
^
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
03
03
-oa
03
03
Oi
03
01
Ol
01
01
01
02
02
02
02
02
02
O3
03
03
04
01
01
01
01
01
01
01
006
00V
010
01O
999
999
999
001
002
003
999
999
O01
001
002
002
003
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999
999
001
999
999
O01
001
001
002
002
003
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O03
03
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02
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97
96
99
01
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97
98
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02
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97
98
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97
90
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01
99
01
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EXTCOMB dOILEH /COMMERCL- INSTUTNL/NATUK AL GAS
/LlOMMdTU/HK
EXTCOMa LOILEri /C GMMEKCL-1NSTUTNL/WUOO /LI UMMb TU/HK
EXTCOMB BOILER /COMMLRCL-INSIUT NL/L I U PETROLEUM GAS/ 1 0- 1 OGMMal U/HS
EXTCOMB BOILE« /COMMERCL-INSTUTNL/LIO PETROLEUM GAS/LI OMMfaTU/HK
EXTCOMB BOILER /CGMMCRCL-INSTUTNL/U7 HER/NOT CLAS^FO/ SPECIFY JN fteMAKK
EXTCOMB BOILER /COMMEHCL- INSTUTNL/UThEK/NUl CLAb IFO/
EXTCOMB dOIcER /COMMERCE-INS! UTNL/UTHcR/NUT CLASi-FD/
INTfcKNLCOMQUSTION/ELECTHIC GENLRATN/Ol ST ILLATE OIL
INTERNLCQMBOST i ON/ELECTRIC GENERATN/NAI JKAL GAS
/
/
INTERNLCUMQUST ION/ELECTRIC GENbKATN/OI EbbL /
iNTERNLCuMbusr ION/ELECTRIC GENEHATN/OTHEK/NOT CLASIFU/
INTEKNLCOM6«ST ION/ELEX. TRI C GENERATN/OT HER/NOT CLAMFD/
INTErfNLCOMdUST ION/INDUSTRIAL /D1STILLATF OIL /
INTE^Ni-CuMbUST ION/ IC4DUSTR I AL
INTERNLCCMBUST ION/INDUSTR lAL
INTERNLCUMtlUST ION/INOUSTR 1 AL
INTEHNLCOMbuST ION/1 NDUSTR IAL
INTEBNLC^.'-IBUST ION/INOUSTR IAL
INTEPNLCJMbuST lON/lNDUSTH IAL
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/NATURAL «>AS
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INTERNLCGMSUSTIUN/INOUSTR IAL /Ol HEK/NOT CLAS1FO/
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INTERNLCOMrtUST I UN/COMMEHCL-INSTUTNL/OT HER/NOT CLASIFi)/
INTE^NLCOMUUSf ION/ENGINE TEST ING
INDUSTRIAL PROCES/CH6MICAL MFG
INDUSTRIAL P-/OCES/CHEM I CAL MFG
INDUSTRIAL PROCES/CHEMICAL MFG
INDUSTRIAL PROCES/CrtEMlCAL MFG
INDUSTRIAL PROCCS/CHEM ICAL MFG
INDUSTRIAL PROCES/CHEMICAL MFli
INDUSTRIAL PHOCES/CHEMICA1. MFG
/AIRCRAFT
/ADIPIC ACID PKOO
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/APIPIC AC1O PROD /
/AMMONIA W/METHNTR/
/AMMONIA W/METHNTR/
/AMMONIA W/CUAeSftd/
/AMMONIA tt/COAUSHn/
/AMMONIA */COAbSR(3/
SPECIFY IN REMARK
SPECIFY IN KEMAKK
TURHINE
TURUlflc
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SPECIFY IN RC*A«K
SPECIFY IN RcrtARK
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SPECIFY IN htrtARK
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TUKOOJET
GENfcRAL-CYLLUHEX
OTHER/NOT CLASIrD
PURGE GAS
STORAGE/LOADING
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/MILLION CUBIC
/1UUO GALLONS
/IOOO GALLONS
/MILLION CUBIC
FtbT uURNtD
bUKNEO
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/IOOO GALLON BURNED (LIQUID)
/TONS -BURNED (SOLID)
/IOOO GALLONS
/MILLION CUBIC
BURNER
FEET
/THOUSANDS OF GALLUNS
/MILLION CUblC FEET dUHNb»
/LOGO GALLONS
/lOOO GALLONS
BURNED
/I 000 GALLONS bUkNEO
/MILLION CUBIC FEET
/MILL1UN CUBIC
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/MILLION C'Jal C
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/THOUSANDS OF GALLONS
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/1UOO GALLONS BURNER
/THUUSANOb UF
/TurJS PKjouChO
/TuNj PRODUCED
/TUNS PRODUCED
/TUNS PRODUCED
/TONS PRODUCED
/TONS PKOUOCEO
/TONS PRODUCED
GALLON/FUEL
VN
-------
186
187
taa
109
190
191
192
193
194
19S
196
197
198
199
200
201
2O2
203
204
205
206
2O7
2 OB
209
210
211
212
213
214
215
216
3 01
J 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
3 01
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3 01
J 01
3 01
3 01
3 01
3 Ol
3 01
3 Ol
3 01
3 01
3 01
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OOS
OOS
OOS
oos
oos
006
006
007
OO7
008
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ooa
oos
ooa
ooa
009
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OO9
010
010
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Oil
Oil
Oil
99
01
99
01
02
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O4
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99
01
99
01
99
01
02
03
O4
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99
01
10
99
01
O2
O3
04
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99
01
02
99
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INOUSTR IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PROCES/CHEMICAL
PSOCtS/CHEMICAL
PROCES/CHEMICAL
PROCfcS/CHtMICAL
PROLES/CHEMICAL
PHUCES/CHEM ICAL
PHOCES/CHEMICAL
PROLES/ CHEMICAL
PROCES/CHEMICAL
PROCEb/CHEMI CAL
PROCHS/CHEM ICAL
PROCES/CHEMICAL
PROCtb/CHEMICAL
PRUCE5/CHEM ICAL
PROCES/CHEM I CAL
PROCEb/CHEM ICAL
PROCE1./CHEM 1 CAL
PKOCES/CHEM CCAL
PROCESACHEMfCAL
PROCES/CHEM ICAL
PROCE3/CHEM ICAL
PROCES/CHbM ICAL
PROCES/CHEM ICAL
PRUCtS/CHEM I CAL
PROCES/CHEM I CAL
PROCEb/CHEMICAL
PROCES/CnEMiCAL
PROCES/CHEMICAL
PROCES/CHEMICAL
PRUCES/CHEMICAL
PROCES/CHEM ICAL
MFG
MFli '
MFG
MFG .
MFG
MFG
MFG
MFG
MFG
MFG
MFG
MFC
MFG
MFG
MFG
MFG
MFG
MFG
MFG
MFG
MFG
MFv,
MFQ
MFG
MFG
MFG
MFG
MFG
MFG
MFG
MFG
/AMMONIA /
/AMMONIUM NITMATL /
/AMMONIUM NITMATL /
/CARUON bLACK /
/CARUON ULACK /
/CARUON aLACK /
/CARBON bLACK /
/CARbON BLACK /
/CAIiaON bLACK /
/CHAPCOAL MFG /
/CHAPCOAL MFG /
/CHLORINE /
/CHLORINE /
/CHLOH-ALKALI /
/CHLOR-ALKALI /
/CHLUfc-ALKALl /
/CHLOh- ALKALI /
/CHLOH-ALKALI /
/CHLOH-ALKALI /
/CLEANING CHEMICLi/
/CLEANING CHEM1CLS/
/CLEANING CHtMICLS/
/EXPLOSlVtS-TNT /
/LXPLOSIVLS-TNT /
/EXPLOSIVES TNT /»
/tXPLOSlVES-TNT /
/CXPLOSI VES-TNT /
/EXPLUSIVF.S /
/HYDROCHLORIC ACID/
/HYDROCHLORIC ACID/
/rlYJi^OCHLURlC ACID/
CTHE«/.JCfcD
PRODUCED
PROuUCEJ
PKO-UCtO
PRODUCED
PHOUotED
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TONS CHLORINE LIOULFItO
TONS CHLlJKlNfc LI^JE^IfcD
TONS CHLORINE LIUUcFIED
TONS CHLORINE LIUUtFlED
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TONS CHLUcINE LIClOEFItD
PHOUUCtD
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bURNED
PRODUCED
FINAL ACID
FINAL ACID" .
FINAL ACID
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X
s
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-------
217
zia
219
220
221
222
223
224
225
226
227
228
229
230
£31
232
233
23*
235
236
237
23»
239
240
241
242
243
244
24S
246
247
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
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Ol
01
Ol
01
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01
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0 12
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012
013
013
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016
016
016
016
017
017
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06
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99
01
02
99
01
02
03
05
99
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99
01
99
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99
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
1N3USTR IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
IlfOUSTR IAL
INDUSTRIAL
INDUSTRIAL
1NDUSTK IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PROCes/CHEMlCAL
PRULtS/CHEM 1CAL
PRUCE5/CHEMICAL
PrtOCES/CHEMICAL
PROCES/CHENJCAL
PROCcS/CHEMICAL
PROCEi/CHEM ICAL
PROCE3/CHEMICAL
PROCES/CHEMICAL
PROCES/CHEM ICAL
PRUCES/CHEM ICAL
PKOCES/CHEMICAL
PROCES/CHENI1CAL
PWOCES/CHEM I CAL
PROCE5/CHEM ICAL
PRUCES/CrtEMlCAL
PKOCE j/CHEM ICAL
FRUCES/CHEMICAL
PROCES/CHEM ICAi.
PROCES/CHEM ICAL
PROCES/CHEMICAL
PROCES/CHEMICAL
PROLES/CHEMICAL
PROCES/CHEMICAL
PHOCES/CHEM 1 CAL
PROCES/CHEMICAL
PHOCES/CHEM ICAL
PRUCES/CHEM ICAL
PROCES/CHEM I CAL
PROCtS/CHEM ICAL
PROCES/CHEMICAL
MFG
MFu
MFli
MFli
MFli
MFG
MF^
MFl,
MFi,
MFtj
MFG
MFG
MFG
MFC
MFC;
MFu
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MFli
MFJ
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MFG
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/HYDWUFLOimlC ACPJ/
/HYDKUf LJUn !C ACID/
/HYUHOFLUUKIC ACIO/
/NITH1C AI.1D /
/NITRIC ACID /
/NITRIC ACID /
/NITRIC ACID /
/NIThlC ACID-fcCAK /
/NITRIC AClL>-KL«K /
/NITKlC ACID-SThlVo/
/NITRIC ACIO-STRNli/
/NITRIC ACID /
/PAINT MFG /
/PAINT MrG /
/PAINT MFG /
/VAKNISH MPb /
/VARNISH MFG /
/VARNISH Mt li /
/VARNISH MKG /
/VAKNISH MFG /
SPUDS-ACID KETPHOC/
/PHOS-AC1D METPRUC/
/PriUS-ACID WLTPR'JC/
/PHOS-ACIO KETPRUC/
/PHCS-ACID THEhNAU/
/PHQS-ACID THERMAL/
/PLASTICS /
/PLASTICS /
/PLASTICS /
/PLASTICS /
HOTiCRUU«
ROTHYK lLN»/oSv.r
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UNCONTROLLED
«/AoSU3UERS
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/TUNS
/TONS
/TUNi
/TUNS
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/TUNS
/TONS
/TUNS
/TONS
/TJNS
/TONS
/TONS
/TONS
/TuNb
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/IONS
/TONS
/TONS
/TONS
/TONS
/TONS
/IONS
AC 10
AC ID
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PUKE ACID PKGi>uCED
PUKE ACID P«COUCrD
PU*E ACID fHUOOCr. O
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PUKc ACIU HHUOOCLJ
PUhic ACID PfiUjJccO
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PKUOUCtO
PMOUUCT
MfcJDUCT
PWJuUCtO
PRODUCED
PrtOUUCtO
Pt-JUUCtD
PrtODUCEU
PHOSPHATE KfJCit
PHOSMHATh MOCK
PHOSPHATE HOCK
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PHOSPHOROUS dURNED
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-------
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3 Ol 019 03 1NOUSTHIAL PRUv.es/CHtMICAl, HFG
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2*9
250
251
252
2 S3
254
255
256
257
258
259
260
261
262
2t>3
264
265
266
267
268
269
270
271
272
273
27*
275
276
277
278
3 01 02O Ol INDUSTRIAL PROCES/CHEM ICAL MFG
3 01 020 02 INDUSTRIAL PROCES/CriEMICAL MFG
3 01 0£0 03 INDUSTRIAL PfiJCES/CHEM ICAL MFG
3 01 020 04 INDUSTRIAL PROCES/CHEM ICAL MFG'
3 01 020 os INDUSTRIAL PROCES/CHEM ICAL MFG
3 01 02O 99 INDUSTRIAL PROCES/CHEMI CAL MFG
3 01 021 01 INDUSTRIAL PRUCES/CHEM 1 CAL MFC
3 01 021 02 INDUSTRIAL PROCES/CHEM ICAL MFG
3 Ol 021 99 INDUSTRIAL PHUCES/CHEMICAL MFG
3 01 022 01 INDUSTRIAL PROCES/CHEM ICAL MFG
3 01 023 01 INDUSTRIAL PHUCES/CHEMICAL MFG
3 01 0?3 0* INDUSTRIAL PROCE S/CH6M 1 CAL MF(,
3 01 O23 06 INDUSTRIAL PROCta/CHEM ICAL MFG
3 01 023 os INDUSTRIAL PROCES/CHEM ICAL MFG
3 01 023 1O INDUSTRIAL PROCES/CHEM ICAL MFG
3 01 023 12 INDUSTRIAL PHUCES/CHEMICAL MFG
3 01 023 14 INDUSTRIAL PRdCtS/CHEMlCAL MFG
3 Ol O23 16 INDUSTRIAL PROLES/CHEMICAL MFC
3 Ol O23 IB INDUSTRIAL PROLES/CHEMICAL MFci
3 01. 023 99 INDUSTRIAL PROCES/CHEMI CAL MFG
3 01 024 Ol INDUSTRIAL PHOCES/CHEMICAL MFG
3 01 024 02 INDUSTRIAL PRUCcS/CHEM ICAL MFG
3 01 024 03 INDUSTRIAL PROCfcS/CHEMICAL MFG
3 01 024 04 INDUSTRIAL PHOCES/CHEM ICAL MFvi
3 01 024 05 INDUSTRIAL PftUCfcS/CHEM ICAL MFG
3 Ol O24 O6 INDUSTRIAL PROCCS/CHEM1CAL MFG
3 01 02* O« INDUSTRIAL PROCES/CHEM I CAL MFu
3 01 024 10 INDUSTRIAL PR3CES/CHEMICAL MFG
3 01 02* 12 INDUSTRIAL PRUCES/CHEM ICAL MFG
3 01 02* 1* INDUSTRIAL PROCES/CHEM 1 CAL MFG
/PRINTING INK /
/PRINTING INK /
/PR INI ING INK /
/PRINTING INK /
/PRINTING INK I
/POINTING INK /
/SODIUM CARBONATE '
/oODIUM CARBONATE /
/SODIUM CARBONATE /
/H2S04 -CHAMBER /
/H2S04-CONTACT /
/H2SO4- CONTACT i
/H2SO4-CONTACT /
/H2S04-CONTACT t
/H2SO4-CONTACT y
/H2SO4-CONTACT /
/H2S04-CONTALT /
/H2SO4-CONTACT /
/H2S04-CONTACT i
/H2S04-CONTACT I
/SYNTHETIC FIBhRS /
/SYNTHtTIC FiilLRS i
/SYNTHETIC FldtRS /
/SYNTHETIC FIBERS I
/SYNTHcTIC FIULRa /
/SYNTHtTIC FIBERS /
/s/NTn£iTic FIBERS .,
/SYNTHETIC FIBERS y
/SYNTHETIC FIBERS /
/SYNTHETIC FIBERS t
COJKING-Gb'NERAL
' COOKING-OILS
' COOKING-OLEOREbIN
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' PIGMENT MIXINGGEN
' OTHfcR/NOT CLASFO
' AMMONIA RECOVERY
' HANDLING
' OTHER/NOT LLASFO
' GENERAL
' SCJ.7 CONVERSION
' 94. 5 CONVERSION
' W.O CONVERSION
' 9d.O CONVERSION
' 97. O CONVERSION
' 9u.U CONVERSION
' 9:>.0 CONVERSION
' 94.0 CONVERSION
' 93. 0 CONVERSION
' OTHER/NOT CLA5FD
' NYLON GENERAL
' DACRON GENERAL
' ORLJN
' ELAST 1C
' TeFLON
' POLYESTER
' NOMEX
' ACRYLIC
' TYVEX
' OLEFINS
/TONS PRODUCED
/TONS PRJDUCEO
/TONS PRODUCED
/TONS PRODUCED
/TON^ PIGMENT
/TONS PRODUCED
/TONS PRODUCED
/TONS PRODUCED
/TONb PRODUCED
/TONS PURc ACID PRODUCED
/TONS PURE ACIO PRODUCED
/TONS PUMK ACID PRODUCED
/TONS PUHt ACID PRODUCED
/IONS PURE ACIO PKODUcLD
/TUNS PUKii ACIU PRODUCED
/TONS PUHt ACIO Hi
-------
£79
«!60
2di
282
263
2B4
285
286
267
288
284
290
291
292
293
29*
295
296
297
298
299
300
301
302
303
3-04-
305
306
307
308
309
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
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Ol
01
01
01
01
01
01
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01
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01
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01
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0.24
025
025
025
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O26
026
026
026
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026
026
026
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027
027
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99
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01
02
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01
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99
01
99
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
IN3UST3I AL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTR IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PROl.es/CHfcMICAL
PRUCES/CHEM ICAL
PROCCj/CrttM ICAL
PROCES/CHEMICAL
PROCES/CMEMICAL
PROCES/CHEM1LAL
PRJCfcS/CHEMICAL
PHUCEb/CHEMJCAL
PROCES/CHCM ICAL
PRUCES/CHEM I CAL
PRUCES/CHEM ICAL
PROCtS/CHEMICAL
PROCES/CHEMICAL
K>HOCeS/CMEMIC4L
PROCtS/CHEM ICAL
PROCES/CHEMICAL
PROCEb/CHEMICAL
TRUCES/CHEMICAL
PROCES/CHEMICAL
PRUCfS/CHEMlCAL
PRQCtS/CHEM ICAL
HROCtS/CHEMICAL
PRUCES/CHEMICAL
PROCES/CHEMICAL
PHOCES/CHEMICAL
PROCES/CHEM I CAL
PHOCES/CHEM ICAL
PROCES/CHEMICAL
PROCES/CHEM ICAL
PROCES/CHEMICAL
PHQCES/CHEMILAL
MFu
MFC.
MFU
S4FC.
MFS '
HFf,
MFO
MFC,
MFli
MFC
MF&
MF5
MFu
MF 1 AMHHJS/
/FERTILIZER /
/TEKEPTHALIC ACID /
/T6REPTHALIC AGIO /
OTHE.RS/NCIT CLASPO
KAYuN OEHtf-AL
ACE TATi:
viscust
OTHERS/NUT CLA5FD
dUTAO lENc-OtNESAL
MCTHYLPRUPE NE-GNL
BJTYNfc bEN'F.ttAL
Pt-NT A C I ENt-OtNKL
OIMETMMEPTNE (ft HL
PENTANE-GENEHAL
E.THANfcNITT. ILt-OtN
ACrtYLON ITR ILE-udN
ACiUCT
PkuUUCt-U
pKoDOChO
PrtOOJCI: O
PKUOOCtD
PHOOUCLO
pt-ODuceo
PfkOJUCtO
Ff-OJUCED
PRODUCED
PfVOOUCEJ
PRODUCED
PRUDUCtD
PkOQUCfcO
PiiOOUCEO
PrtOUUCEU
-to
«J
£>.
-------
310
3 Ot O32 OI INDUSTRIAL PROCES/CHEM1CAL MFC
/SUL'FURIELtMtNl AL>/ NIOD-CL AuS 2STA&E /TONS PHUOUCT
311
312
313
314
315
316
317
318
319
320
3.JI
322
323
324
325
326
327
320
329
330
331
332
333
334
335
336
337
338
339
340
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
01
01
.01
01
01
01
01
01
01
01
01
Ol
0-1
01
01
01
01
01
01
01
01
01
01
02
02
02
02
02
02
02
032
032
032
033
033
034
035
035
036
036
037
037
038
939
040
OSO
090
OV1
100
101
1 10
9OO
999
001
001
002
OO2
O02
002
003
02
03
99
01
99'
01
01
99
01
02
01
02
01
01
01
Ol
99
01
01
01
Ol
99
99
01
99
01
02
03
*9
01
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
1 NDUSTR I AL
PRICKS/CHEMICAL MFG
PROCES/CHEMICAL MFG
PHOCcS/CHEMICAL MFG
PROCCS/CHEMICAL MKG
PROCES/CHfcMICAL MFG
PROCES/CHEMICAL MFG
PROCES/CHEMICAL MFG
PR3CEd/CH£MICAL MFG
PROCES/CHEMICAL' MFG
PROCES/CHfcMlCAL MFG
PROCES/CHEMICAL MFti
PROCES/CHEMICAL MFG
PHOCEb/CHEMICAL MFG
PRUCfei/CHEMICAL MFG
PROCcS/CNEMICAL Ufa
PROCES/CHEMICAL MFG
PROCES/CHEMICAL MFG
PHOCCS/CHEMICAL MFG
PHUCES/CHEM1CAL MFG
PROCES/CHEMICAL MFG
PROCfcS/CHEMICAL MFG
PRQCuii/CHEMICAL MFG
PROCES/CHEMICAL MFG
/SULFUM ( 6LE MLNT AL 1 /
/SULFUk
-------
341
342
34J
34*
3*5
3*6
3*7
3«B
3*9
350
351
3 S3
35*
355
356
357
358
359
360
361
362
363
36*
J&5
3t>u
367
360
30V
370
371
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
02
02
02
02
02
02
02
02
02
02
O2
02
02
02
02
02
02
02
02
02
O2
02
O2
02
02
02
02
02
O2
02
02
00*
OO4
00*
004
006
005
005
005
O06
006
OO6
006
OO6
OO7
007
007
O07
007
O07
0(17
OO7
ooa
DOS
009
OO9
009
009
009
O10
010
010
01
02
03
99
01
02
03
0*
01
02
O3
04
99
01
02
OJt
O*
05
06
30
99
01
99
01
02
O3
VU
9V
01
02
03
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PROCES/FOOD/AGRICULTURAL/CUTTON GINNING /
PRJCeS/FOOO/AGRICULTUHAL/CJTTUN GINNING /
PROCES/FOOD/AGRICULTUHAL/COTTON GINNING /
PRUCE-J/FOOC/AGRICULTURAL/CUTTUN GINNING /
PROCEa/rOOD/AGRlCULTURAL/FEEO/G^AIN TtWMuL/
PROCEb/FOUD/AGRlCULTURAL/FLED/GKAlN TtRMtL/
PROCtS/FOOO/AGHICULTUHAL/FeEO/GRAIN TtRMhL/
PROCES/FOOO/AGHICULruUAL/hEtiU/GHAIN TLRMtLX
PROCES/FOOD/AGHlCvJLTUHAL/Fet:O/GRAlN CNTNYt/
PRUCES/FOUD/AGRlCULTUflAL/FEIiD/GrtAIN CNTRYfc/
PROCtfS/FOOD/AGRlCULTuR AL/FEl-D/GKAI N CNTI/AGRICULTUHAL/FKRMENTAlN-UEfcR /
PR JCtS/FOOD/AGrt I CULT UH AL/t-ERMbN TA TI ON-bteM/
P'wOCES/FOOO/ACRIClA.TUHAL/FEHMfcN.'ATIUN-dLeR/
PfJOCeS/FOOO/AGRlCULTUHAL/FtRMENTATN-KHlSKY/
PROCci./FOOD/AGRICULTUkAL/FLRM£NTATN-«Hl bKY/
PROCES/FODO/AGRlCULTUhAL/PtRMCNTATN-WHlSKY/
UNLOADING FAN
ClfcANfR
STICK/HUHR MACHNt
UTMER/NiJT CLAbFO
SniPING/RtCLIV ING
TSANSFch/CONVtVNG
bCHctNINC/CLEAN!-rfi
ORYING
SHIPNG/«ECeiVNG
SCriffuNING/CLcANNG
DRY INC.
UTHEi
-------
372 3 02 010 99 INDUSTRIAL PROLES/FOOD/AGRICULTURAL/FENMCNfATN-WHl SKY/ OTH^R/NOT CLASFD /GALLONS PRODUCT
373
374
375 -
376
377
378
379
330
381
382
383
384
305
386
387
388
389
390
391
392
393
394
395
396
397
398 -
399
4OO
402
3 02 Oil 01
3 02 012 01
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
02 012
O2 012
02
O2
02
02
02
02
02
O2
02
O2
02
O2
02
02
O3
03
03
03
03
03
03
03
03
03
03
03
012
013
014
015
015
016
016
017
017
oia
030
O30
999
999
000
001
001
001
001
001
001
002
003
OO3
O03
OO3
02
03
99
01
01
01
99
01
99
20
99
99
01
99
98
99
Ol
0 I
02
03
04
OS
99
01
Ol
02
O3
04
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PHOCEb/FOOO/AGRlCU-ruRAL/FhHMLNI ATN-fclNL /
PHOCdS/FOOD/AGRICU^ruHAL/f- liH Mi:AL /
PROCtfb/FUOD/AGkICUl_TURAL/K ISH Mt;AL /
PROCES/FOOU/AGRrcUcTURAL/FISH MtlAL /
PROCES/FOOD/AGRICULTUkAL/FliH MtAL /
PROCEb/FOUD/AGRlCULTURAL/MEAT SMuKINij /
PHCJCtb/FUOD/AGHICULTUhAL/sTARCH MFG /
PROCtS/FQOO/AGRlCULTURAL/SOGAR CAN6 PRUCfcb/
PRuCES/FCJOO/MSRlCULTuKAL/SUGAR LANE PKUCtS/
PRUCES/FOOD/AGRICULTUfi AL/SUGAR bfcET PROCdj/
PHOCES/FOOD/AGHlCULTURAL/bUGAK UELT PROCES/
PROCeS/FOOD/AGRl CULTURAL/PEANUT HHOCLSblNG/
PRUCES/FOOD/AGRICULTUKAL/PrlANUT PROCtSblNu/
PRGCES/FOOO/AGRlCULrURAL/CANOY/CONFELTNRY /
PROCEb/FOOD/AGHICOLIURAL/OAIRY PRODUCTS /
PRUCtS>/FOOD/AGRlCULTURAL/O«lRY PRODUCTS /
PROCES/FOOD/AGRICULTURAL/OTHER/NCI1 CLAbIKO/
PHUCtS/FOOD/AGHlCOLTuhAL/OI HER/NOT CLAS1FO/
PROCES/PR 1MARY
PROCES/PR IMAKY
PHuCES/PRIMARY
PROCES/PR1MARY
PftUCES/PRI MARY
PROCES/PRIMARY
PROCEb/PRIMAUV
PROCES/PR IMARY
PROCtS/PRIMARY
PROCES/PH IMARY
PBOCfcS/PRIMARV
PKUCES/PRlMAHtr
METALS
MET AL »
METALS
METALS
MfcTALS
ME T AL S
METALS
METALS
METALS
METAI.S
METALS
METALS
/ALUMINUM ORE-tJAUX/
/AL vJRt-£l.ECI-:uREi>N/
/AL ORL-cLEChORfcDN/
/AL ORE-ELECHORtON/
/AL Oht H.BCKliKtUN/
/*L OHE-hLECROHEON/
/ALUMINUM OPC.KATN /
/AL URL-CALC ALHYO/
/COKE MET BYPfiUUUC/
/COKE-MET BYPHODUC/
/COKE-MET BYPRUDUC/
/CUKE-Mtr BYPRUDUC/
GENcHAL
COOKEzHi rRLbHr I SH
CUUKFmi ST AL.£r 1 Vi
l)H 1 fcH S
UTHfcR/NOT CLASIFD
JLNEKAL
GENERAL
OTHtK/NOT CLASIf-O
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OTHER/NOT CL*.« II L>
OIL/NUT CLAbHU
OTHKH/NOT CLASFO
JTHLH/NUT CLASFO
MtLK SPRAY-DKYcR
OTHKR/NUT CLASFD
SPECIFY IN KEMAP.K
SPECIFY IN REMARK
CRUSH 1 NG/HANDL 1 NG
PRtriAKt CELLS
MOklt^TD bOOtfiuKG
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MxIdPiALS hANi>LNG
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OThcR/NOT CLASFD
GENERAL
TGENEHAL
UVEN CHARGING
UVEN PUSHING
QUENCHINu
/GALLONS PKJOUI-T
/TijNS I- ISH MbAL l-.iGiJJCcO
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
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/ 1 UN j
/TUNS
/TONS
/TONS
/TONS
/TONS
/Tons
/TUUS
/funs
/TONi
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TUNS
/TUNS
/TUNS
FISn MEAL PKCOUCLC/
FISH SCRAP
PROCESSED
MfcAT SMOKED
STANCH P«ut*UCcLI
SUGAR P*oDUCfcO
PrtuCtSSED
KA A 'at: c. TS
RA« jEtTS
PKoCtSSEC
PRO .tUCT
PKOCUCT
PKiJcJUCT
P«Ji-bS5LO <|NI-OT)
PKOJOCtiO IFlNlbMEOI
OF OWE
ALUrtlMJrf PKuOUCtO
ALUMINUM P«OOUCEO
ALJMINUM p& uL-UCEuJ
ALUM! NOM HHuOUCcD
ALUMINUM HHuuUCEJ
ALOMI NUM PKuOOC£O
ALUMINUM PRODUCED
CUAL CHAKGED
CUAL CMARuED
COAL CHARGED
CUAL CnARGtt)
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S
I
I
D
«-. m
-------
403
«0«
405
406
407
4oe
4O9
410
411
412
413
414
415
416
417
418
419
2O
421
422
423
424
4i>5
426
427
4£B
429
430
31
43«>
433
3
J
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
03
03
03
03
03
03
03
03
O3
03
03
03
O3
03
03
03
03
03
03
03
03
03
03
03
03
O3
03
03
03
03
03
OO3
003
003
004
OOS
005
005
005
005
005
005
006
006
006
006
O06
006
006
OO6
006
OO7
OO7
008
ooa
OOS
OOS
003
ooa
OOS
000
OO9
OS
06
99
01
01
02
03
04
OS
06
99
01
02
03
O4
05
10
1 1
12
99
01
02-
01
02
03
04
05
O6-
07
OX FES I
*&% FtSl
90X FESI
SIL ICON METAL
SIL iCUMANCAMcjE
SCREENING
URfc DRYtR
L>J*CAhB CK-REACTR
OTHCR/NUT CLASFu
FLRUMf NGANESE
GENFKAL
OLA^T KNC-ORECHO
tlLAST FNC-AGLCHG
S INTER INii GENERAL
UWE-CRUSH/HANDLL
SCARF ING
SANu HANDLING UPN
MOLD UVE1NS
UTHLR/NOT CLASFD
OPNHEARTH OXLANCK
/tONS
/TONS
/TUNS
/IlJNS
/TONS
/IONS
/ION'S
/TONS
/TUNS
/TUNS
/T JN3
VTONs
/TsJNS
/TONS
/TONS
/TuINi
/TOMS
/TUNi
/TL.NS
/TONS
/TONS
/TUNS
/TUNS
/TONS
/Tl^NS
/IONS
/i
OF Uhit
PKLiCEbbED
MANULtO
bANJ OAKtU
PHOJ'.JCcO
PRUDuCfD
to
^1
CD
-------
434
435
436
437
433
439
440
441
442
44 J
444
445
446
447
448
449
4 SO
451
452
453
454
455
456
' 457
458
4S9
460
461
462
463
464
3 03 009 02
3 03 OO9 O3
3 O3 009 04
3
3
3
3
3
3
3
3
3'
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
03
03
03
03
03
03
03
03
'03
03
03
OJ
03
03
03
03
03
03
03
03
03
03
03
03
O4
04
04
04
009
009
010
010
010
010
Oil
Oil
Oil
012
012
O13
Olft
014
014
014
030
030
030
030
O3O
030
030
999
001
OO1
001
001
05
99
01
02
03
99
Ol
02
99
Ol
99
Ol
01
O2
03
99
01
02
03
04
OS
06
99
99
01
O2
03
04
INDUSTR IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PRUCES/PRIMARY
PROCEi/PHIMARY
PROCES/PRIMARY
PROCtS/PR IMARY
PROCES/PRIMARY
PROCES/PRIMARY
PROCdi/PRlMAHY
PROCES/PRIMARY
PRUCtb/PRlMARY
PHOCES/PR IMARY
PROCES/PRIMARY
PRUCES/PRIMARY
PROCtS/PRIMARY
PROCES/PRI MARY
PRUcfcS/PR IMARY
PROCES/PRIMARY
PRUCES/PRIMARY
PROCES/PRIMARY
PHOCES/PHIMARY
PRUCES/PRIMARY
PROCES/PRIMARY
PROCES/PRIMARY
PROCtS/PHIMARY
PROCEi/PHIMARY
PROLES/PRIMARY
PROCES/PH IMARY
METALS
MtTALS
METALS
MtTALS
MtTAl S
METALS
MLTALS
METALS
METALS
MtTALS
MLTALS
MFTALS
MCTALS
METALS
METALS
MLTALS
METALS
METAI S
METALS
METAI S
METrtLS
MbTALS
METALS
METALS
METALS
METALS
METALS
PStjCES/SECONDARY MuTALS
PROCeS/SECONOARY METALS
PUOCES/SECONDARY METALS
PROCES/SECONOARY METALS
/STEEL PRODUCTION /
/STEEL PRODUCTION /
/iTEEL PRODUCTION >
/STEEL PRODUCTION /
/STtEL PRODUCTION /
/LEAD SMELTERS >
/LEAD SMtLTEfcS t
/LEAO SMULTEHS /
/LEAD SMELTERS I
/MULYUNUM MINING /
/MOLYoNUM MILLING >
/MOLYt.NUM PktiCE-S <
/TITANIUM PROCESS /
/TITANIUM PROCES /
/GOLD /
/UARIUM /
/UARIUM /
/UARIUM t
/BARIUM /
/ZINC SMELTING /
/ZINC SMELTING /
/ZINC SMELT ING /
/ZINC SMELT INu /
/ZINC SMELTING /
/ZINC SMELTING. /
/ZINC SMELTING /
/OTHER/NOT CLASFU ,
/ALUMINUM UPERATN /
/ALUMINUM OPERA1N t
/ALUMINUM OPERATN /
/ALUMINUM UPLRATN >
' OPNHEARTH NOXLNCE
' BUF GENERAL
' eLc<.T ARC 0/LANCE
' ELECT At-c NULANCE
' OTHER/NOT CLASFD
' SINTER/CRUSHING
' tlLAiT FURNACE
' UEVcRU HIPNACE
' OTHER/NOT LLAiFO
' GENLKAL
' GfcNKRAL
' OTHLR/i'TOT CLASIFD
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' OTHER/NUT CLAblFO
' MINING/PSUCESSING
' JKfc GR1NO
' REDUCT.N KILN
' Ort IC.RS/CALC INtRS
' OTht-.R/NOT CL~aFO
' i^OASTNG/KULT-MHTH
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' SWEAT INGFUKNACE
' SMELT-CRUCIBLE
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' CHLHRINATN STATN
/TONS
/TO.SS
/TONS
/TONS
/TONS
/TONS
/TONS
/TUNS
/TONS
PROOUCEO
PK.j'JUCfeO
PRJOUCEO
PRUUOCEO
PKOOUCtO
CONCENTSATtu URE
CUNCENTKATfco ORE
CuNCENTKATiu) Ot. c
/nUNUHEOa jF TONS MINED
/TONS PK'JuUCT
/TUNS
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/TONS
/TONS
/TUNS
/TONS
/IONS
/TONS
/TONS
/TOSS
/TONS
/TONS
/1UNi
/TONS
/TONS
/TUNS
/TUNS
/TUNS
/TONS
/TONS
PROCESSED1
PRJUIUCT
PROCES3EO
ORE
PKOCiiStO
PKOCtSSLu
Pt.IJCE.aSEU
PRocIsSEO
PWUCtibED
PHUCLSSED
PP OCtiScO
PROCf SSED
PROCtLSStO
PRODUCED
PRODUCED
METAL PRODUCED
METAL PRODUCED
MtTML PWOOUCho
to
-J
D
-------
4bS
466
467
408
. 409
470
471
472
473
474
475
476
477
47B
479
480
4U1
483
484
405
4U6
487
46B
499
49O
491
492
493
494
49S
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
04
04
O4
04
O4
04
04
O4
04
04
O4
O4
04
O4
O4
04
04
04
04
O4
04
04
O4
04
C4
04
O4
O4
O4
O4
O4
001
001
CO1
001
001
OO2
OO2
002
002
002
002
002
OO3
OO3
003
OO3
003
003
OO3
004
004
004
004
O04
004
005
005
OO6
006
"007
OO7
10
11
20
bO
99
01
02
03
04
OS
06
99
01
02
OJ
O5
30
40
99
01
02
OJ
04
oa
99
Ol
99
01
99
01
02
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL.
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PWOCES/SECONDAdY
PROCtS/ SECONDARY
PROCES/ SECONDARY
f-RUCES/SECONDAHY
PRvlCES/SECONOAKY
PROCES/SECGNDARY
PROCES/SECONOARV
PROCLS/SECONDAHY
PROCCS/SECONDAHY
PRUCES/SECUNDARY
PHOCES /SECOND ARY
PRUCES/SECONOARY
PROLES/SECONDARY
PHUCES/SECONDARY
PROCES/SECONOAKY
PHUCES/bECONOARY
PR JCES/SECCNOA RY
PRUCtS/SEC ONDA KY
PROCES/SECONOAHY
PROCLS/SECONDARY
PROCES/ SECOND ARY
PHOCES/ 5EC GNO A BY
PROCES/ SECOND ARY
PROCfcS/ SECONDARY
PROCEi/SECONDAHY
PROCtS/SECONDAHY
PROCES/SECONDAHY
PHOCES/SECUMMHY
PROCESS SECONDARY
PROOFS/SECONDARY
PROCtS/seCONDARY
MEI ALS
METALS
METALS
MuTALS
METAL3
MEI ALS
ML T ALS
ME T AL S
METALS
METALS
ME f ALS
MCTALS
ML f AL S
METALS
MEI ALS
METALS
METALS
METAui
METALS
METALS
MET ALS
METALS
METALS
METALS
METALS
ME r ALS
METALS
Me T ALS
METALS
METALS
METALS
/ALUMINUM OPERATN
/ALUMINUM UPLRATH
/ALUMINUM OPEHATN
/ALUMINUM UPERATN
/ALUMINUM OPERATN
/Lift ASS/rtKUN2 MELT
/URASS/BRJN2 MtLT
/UMASS/URDN2 Mt L T
/dRASS/iJR'JN/ MELT
/dRASS/tlRONZ MELT
/BKAS'j/BMUNZ MELI
/GRAY IRON
/GRAY I RUN
/GRAY IRON
/GRAY IRON
/GRAY IRON
/i»RAY IRON
/GRAY IRON
/LEAD SMELT SEC
/LEAD SMELT SEC
/LdAO SMELT SEC
/LEAD SMELT SEC
/LEAD SMELT SEC
/LEAD SMLLT SEC
/LEAD fcATlERY
/LEAD BATTERY
/MAGNSS 1UM SCC
/MAGNESIUM SEC
/STFEL FOUNDRY
/STEEL FOUNDRY
/ FOIL ROLLING
/ FOIL CJNVfeKTIIMii
/ CAN MANUFACTURE
/ ROLL Dw AW-L XTrtUOc
/ OTHcR/NOT CLASFD
/ dLAST FNC
/ CRUCIBLE FNC
/ CUPOLA FNC
/ ELECT INDUCTION
/ REvERQ FNC
/ ROTARY FiJC
/ OTHiiM/NOT CLAS1FO
/ CUPJLA
/ HtVEHB FNC
/ ELECT INOUCTIUN
/ ANNEALING LJPtRA TN
/ MISC CASJ-FAdCTN
/ GK1HD ING-CLEANI NG
/ OTHER/NOT CLASIFD
/ POT FURNACE
/ REVERB F.MC
/ bL AST /CUPOLA FNC
/ HOT ARY REVEKd FNC
/ LEAD OXIDE MFG
/ OTHER/NOT CLASIf-D
/ GENERAL
/ OTHER/NOT CLASIKO
/ PUT FUMNACfc
/ OTHER/NOT CLASIFD
/ ELECTRIC AhC FNC
/ UHEN KEAkTH FNC
/TUNS
/TON3
/TUNS
/TUNS
/TUNS
/TONS
/TONS
/TiiNb
/TUNS
/lONi
/TUNS
/TUNS
/TONS
/TuNi
/TONS
/TONS
/TONS
/TON j
/TONS
/TONS
/TuNb
/TUNS
/TONi
/TONS
/TONi
/TONS
/TONS
/TONS
/TONS
PRODUCT
PRODUCED
PRUOUCCD
PRJUUC-U
PROOUCcU
CHAhut
CHARGE
CHAKGt
CHAHGc
CHA^Gc
CrIArtGL
PF. JOJCtU
MtTAL CHANGE
MLTAL LHAr
-------
496
«V7
SOO
SOI
5 OZ
503
SQ4
505
506
507
508
509
510
511
512
513
514
515
Sib
517
518
S19
520
521
522
523
524
S25
526
3 04
3 04
3 04
3 04
3 04
3 O4
3 O4
3 O4
3 O4
3 04
3 O4
3 04
3 04
3 04
3 04
3 04
3 04
3 04
3 04
3 04
3 O4
3 04
3 04
3 04
3 04
3 04
3 OS
3 OS
3 OS
3 OS
3 OS
007
007
OO7
007
OO8
008
ooa
ooa
008
008
ooa
OO3
ooa
oat
OO9
010
010
on
Oil
O2O
020
O20
020
020
050
999
O01
001
O01
OOl
OOI
03
04
05
99
01
02'
03
O4
OS
06
07
08
99
Ol
99
01
99
01
99
01
02
O3
O4
99
01
99
Ol
02
03
04
99
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PROCEi/SECONDARY
PR uCeS/SECUNDARY
PROCES/SECONDARY
PROCES/SECUNUAHY
PROCtS/SECONDAHY
PROCfcS/SECONOARY
PROCEb/SECONOARY
PROCES/SECUNOAHY
PROCES/SECONOARY
PROCES/SECONOARY
PROCES/SECONDARY
PROCES/SECONDA BY
PROCES/SECUNOARV
PKOCtS/SECONDARY
PRUCES/SECONOARV
PROCES/SECONDARY
PROCES/SECONOASY
PR OCfcS/ SECONDARY
PROCES/SECONDARY
PROCES/SECONOARY
PROCES/ SECONDARY
PROCES/SECONOAfiY
PROCtb/SECONDASY
PROCES/SECUMDARY
PROCES/SECONDARY
METALS
METALS
MUTALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
METALS
PROCES/SECONDARY METALS
PROCES/ MINERAL PRODUCTS
PRUCES/MINERAL PRODUCTS
PROCES/MINERAL PRODUCTS
PROCES/MINERAL PRODUCTS
PROCES/MINERAL PRODUCTS
/STEEL FOUNDRY /
/STEEL FOUNDHY /
/STEEL (FOUNDRY /
/STEEL FOUNDRY /
/ZINC SEC /
/ZINC SEC /
/ZINC SEC /
/ZINC SEC /
/ZINC SEC /
/ZINC SEC /
/ZINC SEC /
/ZINC SEC /
/ZINC SEC /
/MALLEABLE I HUN /
/MALLbAULE IRON /
/NI CKEL /
/NICKEL /
/ZIRCONIUM /
/ZIRCONIUM /
/FURNACE ELECTRODE/
/FURNACC ELECTRODE/
/FURNACE ELECTRODE/
/FURNACE ELECTRODE/
/FURNACE ELECTkllOc/
/MISC CASTtFABRCTN/
/OTHEh/NOT CLASIFD/
/ASPHALT ROOFING /
/ASPHALT ROOFING /
/ASPHALT ROOKING /
/ASPHALT ROOFING /
/ASPHALT ROUt-INb /
(IPtrf HEARTH LANCD
MEAT-TREAT FNC
INDUCTION FURNACE
OTHER/NOT CLASIFO
RETORT FNC
HOHIZ MUI-FLE FNC
POT FUKNACE
GALVANIZING KETTL
CALCINING KILN
CUNCENTHATK DKYEft
REVERU-SttLAT FNC
OTHeH/NOT CLAS1FO
ANNEALING (JPErtATN
OTHER/NOT CLASIFU
FLUX FURNACE
OTHER/NOT CLAS1FD
OXIDE KILN
OTHEH/NOI CLASIFD
CALCINATION
MIXING
PITCH TKFAT1N5
BAK£ FURNACES
OTHER/NOT CLASIFU
SPECIFY IN REMARK
SPECIFY IN REMARK
BLOWING OPERATION
DIPPING ONLY
SPRAYING ONLY
DIPPING/SPRAYING
UTHER/NOT CLAS1FC/
/TONS
/TONS
/TONS
/TONS
/TONS
/TUNS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TUNS
/TUNS
/TONS
/TONS
/TUNS
/T3NS
/TONS
/TONS
/TiJUi
/TUNi
/TONS
/TONS
/TUN.i
/TONS
/TONS
PROCESSED
PRUCESSED
PROCESSED
PKOCfcSSEO
PRdKUCEO
PHuOUCED
PkUUUCcO
PKOOUCtO
PKUuUCfcD
PH3UUCEO
HROCESSttl
PRUOUCLO
PFcoCESSfcO
METAL CHAr£ia£
METAL CHARGE
PKUCESSEO
PKOCESSEO
PROt-ESiEO
PrtOcESStU
PROCESSED
PKIJCfcSStD
PPUCeiotO
pKjcesseo
PKUOUCEO
PROCESSED
SATUIStTgo FcLT PKUUUCLO
I :.l FcLf PRODUCED
^AlUMAItl'- KtLT prJOUUCfcO
jAfJRAltO »"tLT PROiJoCED
SATuKATED FELT PHUOoCtD
i
K
r
s
i
D
^^^
00
-------
527
528
529
53O
531
532
S3J
534
S3S
536
537
538
539
540
541
542
543
544
545
546
547
546
549
550 '
551
552
- 553
554
555
556
557
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
"" 3
3
05
05
05
05
OS
05
OS
05
OS
O5
05
OS
05
05
05
05
05
O5
OS
OS
05
OS
OS
05
OS
OS
OS
OS
OS
OS
OS
OO2
002
002
OO3
O03
OO3
OO3
O03
OO3
OO3
004
OO4
O04
004
OOS
OOS
OOS
OOS
005
OOS
OO6
006
006
OO6
OO6
006
O07
007
OO7
ooT
O07
01
02
99
Ol
02
O3
04
OS
06
99
01
02
O3
99
Ol
02
03
O4
OS
V9
01
02
03
04
OS
01
02
03
O4
05
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTHIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTHIAL
PROCES/MI NERAL
PRUCEi/MINERAL
PRUCES/MINERAL
PROCtS/MINERAL
PROCES/Mi NERAL
PRUCES/MINERAL
PROCES/MI NEHAL
PROCES/MINEfiAL
PROCfci/MlNERAL
PROCES/MI NERAL
PROCES/ MINERAL
PROCEj/ MI NERAL
PROCtb/MINtRAL
PROCES/ MI NERAL
PROCES/ MI NERAL
PROCES/ MI NERAL
PRUCES/MI NF.NAL
PROCES/MI NfcRAL
PRUCES/MINERAL
PR OCEb/MI NERAL
PRUCES/MINERAL
PRUCES/MI NERAL
PRUCES/MI NE &AL
PRUCES/MINERAL
PROCES/MI NERAL
PROCES/ MINERAL
PROCeS/ MINERAL
PRUCES/MINERAL
PRUCES/MINERAL
PRUCES/MI NEHAL
PRUCtS/MI NERAL
PRODUCTS
PRODUCTS
PRODUCT S
PRODUCTS
PRUDUCTS
PRODUCT S
PRODUCTS'
PRODUCT:;
PRODUCTS
PRODUCTS.
PRODUCTS
PRODUCTS
PRODUCT S
PRUDUCTS
PHO DUCTS
PRODUCT S
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCT S
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCf S
PRODUCTS
PRODUCTS
PRUDUCTS
PRODUCT S
PRODUCT S
/ASPHALT 1C CONCRET/
/ASPHALT 1C CCJNCR6T/
/ASPHALT 1C CONCRET/
/BRICK MANUFACTURE/
/CMICK MANUFACTURE/
/tMICK MANUFACTURE/
/URICK MANUFACTURE/
/ttrtICK MANUFACTURE/
/URICK MANUFACTURE/
/tMICK MANUFACTURE/
/CALCIUM CARBIDE /
/CALCIUM CAKiUDE /
/CALCIUM CARBIDE /
/CALCIUM CAhblDL /
/CASTAbLE KEFRACTV/
/CASTAULE REFHACTY/
/CASTABLt HEFRACTY/
/CASTAULE HEFRACTY/
/CASTAULE REKRACTV/
/CASTAULfc Hfcl RACTY/
/CEMENT MFG DRY /
/CEMENT MFG DRY /
/CEMENT MFG DRY /
/CEMENT MFG DRY /
/CEMENT MFli DRY /
/CbMENT NFG DRY /
/CEMENT MFG MET /
/CEMENT MFG «ET /
/CEMENT MFG MET /
/CEMENT MFS «UCtU
PKODUCEO
PKDDUCzD
PRODUCED
PROOUCtO
PROCESSED
FEfcD MATERIAL *
s
f-Efj MATERIAL |
FEED MATcRIAL -
f-b£D MATERIAL
t-ktO MATERIAL
FfcEU MATERIAL
SLS CEHfcNT ^nuiJUCLD
/BARRELS CEMENT PRODUCED
/TUNS CLMtNT PHUOUCEO
/TONS
/TONS
CfcMfcNT PfiUOUCcD
CEMbNT PROOUCEO
/ION3 CSMfcNT PKOUUCtti
/BARRELS CEMENT PRODUCED
/UARKtLS CbMEMT PMOuUCED
/TUNS CErtLNT PROOuCbO
/TONS
/TUNS
CbMtNT PKOOUCtU
CtHtNT PRODUCED
00
-------
559
-'. 55V
SoO
661
562
563
564
5bS
S67
5 08
570
S7i
572
57J
574
S7S
576
S77
578
579
580
561
5d2
583
584
585
986
587
588
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
J
3
3
3
3
3
3
3
05
05
05
05
OS
05
05
05
OS
OS
05
OS
05
05
05
OS
O5
05
05
05
05
05
05
Ob
05
05
Ob
05
OS
OS
OS
007
006
006
OOb
008
009
009
009
009
O10
010
O10
010
Oil
Oil
Oil
012
012
012
012
O12
012
013
013
014
014
014
014
014
015
OlS
99
01
02
03
99
01
02
03
99
01
02
O3
9V
01
20
99
01
O2
03
04
05
99
01
99
Ol
10
11
12
99
01
02
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PROCES/MI NERAL
PROCES/MINERAL
PROCLS/MINERAL
PROCES/MINERAL
PROCES/MINERAL
PROCti/ MINERAL
PROCtS/ MINERAL
PR GCtS/ MINERAL
PROCeS/ MINERAL
PROCES/MI NfcRAL
PHOCtS/MINEHAL
PROCfcS/Ml NERAL
PRUCE3/MINERAL
PROCCi/MI NERAL
PROCES/MI NEBAL
PRilCEi/MlNEKAL
PROCES/MINERAL
PROCES/MINERAL
PROCES/MI NERAL
PROCES/MI NEKAL
.PHOCES/M.I NERAL
PRUCEi/MINERAL
PROCES/MINERAL
PRUCt-3/MINtRAL
PROCES/MINEHAL
PROCES/MINERAL
PROCES/MINERAL
PAOCts/MlNEKAL
PRUCi-S/MI NERAL
PK OCE S/ M 1 NE R AL
PHOCtS/MINEHAL
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCT 3
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRuDOCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PhOCrUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
/CEMENT MFG «fT /
/CERAMIC/CLAY MHG /
/CEKAMIC/CLAY Mt-G /
/CERAMIC/CLAY MFG /
/CEKAMIC/CLAY MFG /
/CLAY/FLYASHSINTtR/
/CLAY/FLYASHblNTKH/
/CL AY/FLY ASMS INlTt*/
/CLAY/FLY ASMS I NTbR/
/CUAL CLEANING /
/CUAL CLEANING /
/COAL CLEANING /
/COAL CLEAN ING /
/CONCRETE BATCHING/
/CONCRETE PATCHING/
/CJNCHtTfc HATCHING/
/FIBERGLASS MFG /
/FIBERGLASS MFG /
/FIBERGLASS MFG /
/FlSEHGLAbS MFG /
/FIBERGLASS MFG /
/FISEWGLAib MFG /
/FRIT MFG /
/FRIT MFG /
/GLASS MFG /
/GLASS MFG /
/GLASS MFG /
/GLASS *FG /
/GLASS MFG /
/GYPSUM MFG /
/GYPSUM MFG /
OTHtH/NOT CLASIFO
DRYING
GKINU ING
STOSAtic
OTHtR/NOT CLASIFD
FLYASH
CLAY/COKE
NATURAL CLAY
OTHER/NOT CLASIFD
THERM/FLU I J bEL-
THLrtM/HLASH
T HBMM /MUL TIL UUV «l>
OTHcS/NOT CLASII-D
GEMcRAL
ASu^ST/CEMNT POTS
OTHEM/NOT CLAShD
RfcVERbFNC-WEC'JPex
ELECTRIC INb FNC
FORMING LINE
CURING OVEN
JTHEM/NOT CLA51FO
ROTARY FNC GENL
OTHER/NOT CLASIHJ
SODALIME GtNL FiMC
RAM MAT RtC/5TORG
UATCHING/MIXING
MOLTEN HOLD TANKS
OTHER/NOT CLASIFO
R* MTL DRYER
PRIMARY GRINOtH
/TONS
/TONS
/ToNS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
CEMENT PRODUCED
INPUT TO PkoCtbb
IN^uT TQ PKOCESS
PKOoOCcD
FINISHED P^OOUwT
FINISHcD PKCDUCT
FlMSHdO HKOL.ULT
PhOL'UCcD
CUAL OnlfzO
COAL OfilfcO
COAL C/HltO
COAL CLtANLJ
/CUoIC YAt,DS CONCRETE PNUiJUCfcCJ
/TONS PHJOUCT
/TONS
/TONS
/TONS
/TONS
/IONS
/TONS
/TONi
/TONS
/TONS
/TONS
/TONS
/TOUS
/TUNS
/TONi
/TUNS
/TON j
Pfi JOOCI
MATt^IAL P«OCESSEP
MATLrtlAL PROCcSSCD
MATcSIAL PROCcSiEJ
MATERIAL fhoCtbSED
MATtKI'AL PhOCcbSED
PkOCEiSED
CHAkGfcD
GLAbS PSODUCEO
PROCESSED
PROCESSED
PKOC6SSEU
PKOoUCtU
THROUGHPUT
THROUGHPUT
W
CD
LO
D
-------
589
59O
591
592
5 SI 3
594-
595
596
597
599
6OO
601
602
6O3
604
605
6O6
607
60S
6O9
610
611
612
613
614
615
616
617
610
619
3
3
3
J
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
.1
j
3
3
3
3
"3
3
05
05
OS
OS
05
05
OS
05
OS
OS
O5
OS
OS
OS
O5
05
OS
OS
OS
OS
05
OS
05
05
05
05
05
05
05
OS
015
0 15
015
016
016
016
016
016
017
017
017
017
017
017
016
018
019
O19
019
019-
019
020
020
020
O20
020
020
020
020
02O
020
03
04
99
01
02
03
04
99
01
02
03
04
05
99
01
99
01
02
03
99
01
02
03
04
05
06
O7
oa
09
99
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INOUSTR IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PROCES/MINERAL
PRQC6S/MINEKAL
PftOCES/ MINERAL
PROCES/ MINERAL
PROCES/MINERAL
PR OCES/ MINERAL
PROCES/MINEKAL
PROCES/MINERAL
PROCES/MINERAL
PRO(.CS/M1N[; RAL
PROCfcS/M I NE RAL
PRUCES/MINEKAL
PROCE S/ M I NE R AL
PROCES/MINEKAL
PROCES/MINERAL
PROCE3/MI NERAL
PROCES/MINEHAL
PROCtS/MI NERAL
PROCES/MI NEH AL
PROCES/MINEHAL
PHOCS.S/M1 NERAL
PRUCES/M1 NEPAL
PROCE.S/MINERAL
PhOCES/MlNERAL
PROCES/Ml NEfcAL
PROCES/MINEHAL
PROCES/MI NEWAL
PROCES/MI NE RAL
PROCEW MINERAL
PROCES/MINEfiAL
PROCES/MINEfiAL
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PROOOCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PfcUUUCTi
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCT S
PRODUCTS
/GYPSUM MFG /
/GYPSUM MhG /
/GYPSbM MFC /
/LIME MFG /
/LIME MFG /
/LIME MFG /
/LIME MFC. /
/LIME MFG /
/MINERAL VHOOL /
/MINERAL WOOL /
/MINERAL KOOL <
/MINERAL WOOL /
/MINERAL WOOL /
/MINERAL KOOL /
/PEHLITE MFG /
/PERL1TE MrG /
/PHOSPHATE ROCK /
/PHOSPHATE RUCK /
/PHOSPHATL ROCK /
/PHOSPHATE RUCK /
/PMOSPHATIi COCK /
/STONE OUANY/PROC /
/STONE QUARY/PROC /
/STONE QUAKY/PROC /
/SfONE OUAHY/PROC /
/STONE OUARY/Pf,OC /
/STONE SUAKY/PkOC /
/STONE OUAKV/PROC /
/STONE OUAHY/PROC /
/STONE QUARY/PROC /
/STONE QUARY/PkUC /
CALCINEH
CONVEY ING
UTHtR/NCT CLASIFD
PHIMAHY CRUSHING
SECNORY Cf-U^HING
C ALC I NNG- VtR TK I LN
CALC I NNG-H OT YK I LN
OTHcK/NOT CLASIFD
CUPOLA
REVbRU FilC
dl_O« CHAMBER
CUHINb UVtN
COOLER
OTHtR/NOT CLASlf-D
VURTiCAL FNC GEN
OTHER/NOT CLASIFD
DHY1NG
GRINDING
TRAi-iSFtk/ STORAGE
OPEN STORAGE
OTHtlR/NOT CLASIFD
PRIMAHY CRUSHING
ate CRUSH/SCREEN
TEHT ChUSH/SC-VEEN
RcCROSH/SCHEEN ING
FINEo MILL
SCRcEN/CONVV/HNDL
OPEN STORAGE
CUT STONE-GPNtkAL
tk-AjT ING- GENERAL
OTHSR/NOT CLASIFU
/TONS
/TONi
/TONS
/TUNS
/TONS
/TONS
/TUNS
/TONS
/TONS
/TONS
/TuN5
/TUNS
/TONS
/TONS
/TONS
/TUNS
/TUNS
/TONS
/TUNS
/TONS
/TUNS
/TUNS
/TOUS
/TONS
/IONS
/TONS
/TONS
/IONS
THROUGHPUT
THROUGHPUT
ThKouGHPuT
PKJCcSScD
PROCESSED
PROCESSED
CHAHvid
CHARGE
CHA^ioF
CHANGE
PHoCCSaED
CHARGE
PKJCcSSED
t-HO'jPHATt HOCK
PHOSPHATE ROCK
PHOaPHATt HOCK
PHUS"HATE HOCK
RA«r MATfcRlHL
HAW MATERIAL
HAD MATERIAL
FcA« MATERIAL
hA« MAI ER IAL
PRODUCT
PRODUCT STORED
PROCESSED
PHOCcSSED
PSOCESSEO
|
S
3
i
CD
-------
620 «
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
045
646
647
64U
649
650
3 OS 021 01 INDUSTRIAL
3 OS 022 01
3 05 022 99
3 05 023 Ol
3 OS 023 99
3 05 024
3 05 024
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
OS
05
05
05
05
05
06
06
06
06
O6
O6
O6
06
06
O6
O6
06
06
06
06
06
06
06
025
O25
026
026
030
994
001
001
001
001
002
003
004
004
OOS
O05
OO6
006
007
O08
ooa
ooa
ooa
ooa
01
99
01
99
01
99
99
99
01
02
03
04
01
01
01
02
01
02
01
02
Ol
01
02
03
04
OS
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PRUCtS/MINERAL PRODUCTS
PRICES/MINERAL PHOJUCTS
PMUCLi/ MINERAL PRODUCTS
PROCES/MINERAL PRODUCTS
PRUCfcS/MINERAL PhUUUCTS
PR OCES/ MINERAL PRODUCTS
PROCCS/MINEHAL PRODUCTS
PHOCES/MINEHAL PRODUCTS
PRUCES/MlNEfiAL PRODUCTS
PROCES/MINEKAL PROU'JCTS
PROCES/MINERAL PRODUCTS
PRUCES/M1NLRAL PRODUCTS
PROCE5/MINERAL PRODUCTS
PROCES/PETRCLEUM
PR OCES/PETR OLEUM
PROCES/PETRULEUM
PRCJCE3/PETR OLEUM
PROCES/PETHGLEUM
PROCtS/PETROLEUM
PRUCtS/PETHCLEUM
PR GCES/PE THOLE UM
PROCEa/PETRCLEUM
PRUNES/PETROLEUM
PROCES/PliTH OLEUM
PROCEi/PET«CLfcUM
PROCES/PETROLEUM
PROCEi/PETRCLEuM
PROCES/PETRCLEUM
PfcUCfcS/PETROLEUM
PR OCIT.S/PETH OLEUM
PHOCeS/PETaOLEUM
IUOHY
I N DRY
INORY
INOHY
IN DRY
INDRY
INDKY
INORY
INDRY
INDRY
INDRY
INOHY
INORY
INJRY
IN DRY
INuKY
1NOMY
INUriY
/SALT MINING /
/PUTA5H PRODUCTION/
/POTASH PHOOUCT lOiH/
/CALCIUM UORATfe ' /
/CALCIUM uOKATE /
/MG CARdONATfc /
/Mti CARUONATE /
/SANO/GHAVLL /
/SAND/G>4AV£L /
/UI ATOMACOUSkKTH /
/DIATOMACOUS EAKTH/
/LERAHIv ELECT PTS/
/OTHER/NOT CLASIKD/
/.PrtOCtSS HfeATth /
/PROCESS HEATfcw /
/PROCESS H&ATtH /
/PROCESS HcATEH /
/FLUID CRACKtfis /
/MJV-LiED CAT-CRACK/
/dLDK-OOlKN SYSTM /
/ULOW-DJlIN SYSTM /
/PKOCSSi UrtAINS /
/MHOCES'5 DRAINS /
/^ACUU.1 JuTS /
/VACUUrt JETS /
/COOL1N-J TOUtRS /
/MISCELLANEOUS /
/MISCELLANEOUS /
/MISCELLANEOUS /
/MISCELLANEOUS /
/MISCELLANEOUS /
GENERAL
OTHcR/NOT CLASIFCl
MINlNG/PRCCtLSSING
UTMR/NOT CLASIFD
MINb/f-RJCESS
OTHtH/NJT CLASIFD
CHUiM ING/ SCREEN IN
OTHER/NOT CLASIFO
HANDLING
OTHER/NUT CLASIFD
OTH6K/NOT CLASIFD
SPRCH-Y IN R5KARK
OIL
GAS
OIL
GAS
GENERAL (FCCt
GENERAL (TCC)
K/CONTkOLS
U/O CONTROLS
GcN K/CQNTKUL
GEN D/u CONTROL
W/CON1KOL
W/O CUNTKOL
PIPK/VALVE-FLANGE
VESL HELIEF VALUt
PUMP SEALS
COMPRtSR SEALS
UTHER-GENL
/TONS MINED
/TONS O~c
/TONS PROCESSED
/TONS PhJDUCT
/TONS PKJCcSSED
/TONS PROJOCT
/TONS PhJCt-^itO
/TONS PKOJUCT
/TONS PROCESSED
/TONS PK'JUOCT
/TONS PKjCtSSED
/TONa KKLiCtSSeU.
/TUNS P^CJOUCT
/IOOO CUJIC FEfcT GAS oUt-NLJ
/1OGO GALLONS UIL bU«NCU
/MILLION CU6IC FbET bOWNEO
/IOOO oA- T 1 LL A I 1 ON
/IOOO BA*KELS VACUUM UISI ILLATION
/MILLION GALLONS COOLING itATtK
/IOOO BAKKELS RtFINERY CAPACITY
/IOOO BAARELS KtFINt»
-------
691
652
653
654
65S
650
657
658
659
660
661
662
663
664
665
666
667
66U
669
670
6M
672
673
674
6.7S
676
677
678
679
680
681
3 06 009
3 06 009
3 06 010
3 06 Oil
3 O6 Oil
3 00 012
3 06 999
3 06 999
3 07 001
3 O7 001
3 07 001
3 07 001
3 07 OOI
3 07 001
3 O7 OOI
3 O7 OOI
3 O7 OOI
3 O7 001
3 07 002
3 07 OO2
3 07 O02
3 07 O02
3 07 002
3 07 002
3 07 002
3 07 004
3 07 004
3 O7 OO4
3 O7 OOS
3 07 003
3 07 OO6
01
99
01
01
99
01
98
99
01
02
03
04
05
06
O7
08
09
99
01
02
03
04
OS
06
99
01
02
99
01
99
01
INDUSTRIAL
[NOUSTR IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INOUSTR IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INOUSTR IAL
PRUCeS/PETKCLE JM I,lUHY
PROCfcS/PCTROLEUM IiNllRY
PfiUCES/PcTrtGLtuK INORY
PHOCES/PETROLEUrt I NDKY
PROCES/PETROLEurt INURY
PROCEi/P£TRUL6UM INDHY
PROCES/PETROLEUM IrtDRY
PROCEi/PETHOLeUM IMOHY
PROCES/KOOD PRODUCTS
PROCES/tfOOD
PROCES/400D
PROCCS/WOOD
PRUCtCi/WOOO
PROCES/*OOO
PROCES/MCOD
PROCES/MOOO
PROCEi/*OOD
PRQCES/WOOD
PROCbS/mOOD
PHOCES/KCOD
PROCES/MOOD
PROCeS/»OOO
PROCcS/llOOO
PROCe3/«OOO
pRt)ces/»oco
PROCES/VOOO
pRoces/nooo
PROC£S/*GOD
pRoces/«ooo
PROCES/tfOOD
PROCES/tfOOD
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PHODUCTi
PRODUCTS
PRODUCTS
PRCDUCTb
PRODUCTS
PRODUCT^
PRODUCT!.
PRODUCTS
PRCDUCTb
PRODUCTS
PRODUCTS
PRCDUCT3
PRODUCTS
PRODUCTS
PHOOULTS
PRODUCTS
PRODUCTS
PRODUCTS
/FLARES
/
/SLUOGfc CONV1RTIR /
/ASPHALT
/ASPHAL r
OXIOIlhH /
OXIDIZtR /
/FLUID COKING /
/OTHER/ NOT CLASIFD/
/SULFATE
/SULFATC
/SULFATti
/SULFATt
/SULFATL
/bULFAf E
/SULFATE
/SULFATE
/SULFATF
/SULFATE
/SULFATE
/SULFATE
/SULF«Tfc
/SULFATE
/SULrATE
/oULFATg
/5ULFATE
T CLAblFO/
PULPNG /
PULPNG /
PULPNG /
PUL=NG /
PULPNG /
PJLPNG /
PULPNG /
PULPNi. /
PULPNG /
PULPHG /
PULPNG /
PULPNu /
PULPNG /
PULPNG /
PULPNG /
PULPNG /
/PULPbOARD MFG /
/PULPdUARD MFG /
/PRESSURE TREATING/
/PRESSURE T.RfcATINt./
/TALLOIL/ROSIN /
NATURAL GAS
GENicRAL
GENERAL
OTHcH/NOT CLASIFD
GENt-'MAL
SPECIFY IN ftiMORK
SPECIfY IN KCL#{,(
-------
662
683
064
OSS
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
70Z
703
70*
70S
706
707
708
709
710
711
7*2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
07
07
07
07
07
07
07
07
09
O9
0»
09
09
O9
20
3O
30
30
30
90
90
90
90
90
90
90
90
90
90
90
90
007
007
007
ooa
009
010
020
999
001
OOl
001
010
020
999
999
OOl
001
002
OO3
001
002
002
002
002
002
004
004
OO4
004
OO4
004
02
01
99
99
99
99'
99
99
01
O2
99
99
99
99
99
Ol
99
99
99
99
01
06
07
OB
99
01
02
03
O4
OS
06
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL.
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PRQCESXWOOD PRODUCTS
PROCES/tfOOU PRODUCTS
PKOCESXHCOO PRODUCTS
PROCESXnOuD PRODUCTS
PROCESXKOOD PRODUCTS
PROCESXMOOO PRODUCTS
PROCES/HOOO PRODUCTS
XPl.lTWOlJDXi'AHTOOAHDX
XPLYWOUOXPARTdUArtDX
XPL YoOCDXPAhTUQAHDX
XbAUMILL U^LKATNS
XtXCCLSIOB MFfe
XCURK PROCESSING
XFURNITURE MFG
X
X
X
X
PKOCtS/HOOD PRODUCTS /OTHER/NOT CLASIFDX
PROCti/METAL F ABR I CAT ION/ IRONXST6EL X
PROCESXMET.AL F AOft I CAT I UN/ IHON/ S fEEL
PROCtS/METAL F AUK I CATION/ I RUN/STEEL
X
X
PROCES/METAL FAuKlCAT ION/PLAT ING OPEHATONSX
PRUCES/CETAL FAUrt ICnT I ON/CAN MAKING OPHNo /
PHUCESXMETAL F AJR IC«T I ON/UT HER/NOT CLAS1FOX
PROCEaXLEATHER PRODUCTS X'JIHfcR/NOT CLASIFOX
PrfOCESXTEXTILE MFG
PRUCES/ TEXTILE MFC,
PROCES/TEXTILE MFG
PROCESXTEXTILE MFG
PROCESXINPROCESS FUEL
PROCEiXINPWOCESS FUEL
PROCESXINPROCESS FUEL
PROCES/INPROCESS FutL
PROCES/INPROCESS FUEL
PROCESXINPROCESo FUEL
RrtOCESXINPMOCESS FUEL
PROCeSXINPRGCESS FUfcL.
PROCESXINPRCCESS FUtL
PROCESXINPROCESS FUEL
PRQCti/INPROCcSb FUEL
pRocesxihPRocess FUEL
XutNERAL FAURICS
XGENERAu FABRICS
X
X
XKUBbRIZED FABHICSX
XCARPfcT, UPEHATNS X
X ANTHRACITE COAL
Xd I TUMI NOUS COAL
XU I TUMI NOUS COAL
/BITUMINOUS COAL
XU I TUMI NOUS COAL
Xt) I TUMI NOUS COAL
XKESIOUAL OIL
/HtSIDUAL OIL
/Hf. SI DUAL OIL
XRES1DUAL OIL
XRESIDufcL OIL
XRESIDUA.L OIL
X
X
X
/
X
/
/
X
X
X
X
/
VE.fie.EH DhYEH
SANLJUoG
OTHtkX/MOl CLAilFU
OTriERXNCT CLASIFD
UTMERXNOI CLASIFU
UTHEHXNOT CLASIFU
OTHERXNOT CLASIFD
SPcCIFY IN fit^APK
MISC HARDWARE
KARM MACMINLRY
UTHtWXNOT CLASIFD
OTHEHXNOT CLASIFD.
OTHtRXNUT CLASIFO
SPECIFY IN REMARK
SPECIFY IN HCMAftK
YARN PHEPXJLEACH
OTHERXNOf SP6CIFD
JTHERXNOT SPfiCIFO
OTHEWXNOT SPEC1FD
aTHEHXNOT CLASIFD
CEMtNT KILN
tiRICK KILNXURY
GYPSUM KILNXETC
COAL DRYERS
OTHtR/NOT CLASIFl>
ASPHALT OKYcK
CEMENT KILN
LIME KILN
KAOLIN KILN
ricTAL MELTING
cIRICK MLNXl'RY
XTUNS
XTON3
XTONS
XTUNS
XTONS
XTONS
XTONS
XTONS
XTUNS
XTONo
XTUNS
XTUNS
XTONS
XTONS
/TONS
/TUNS
XI JN3
XTUNS
/TONS
/TONS
XTUNS
XTUNS
XTUNS
XTONS
XTONS
xioca
X1OOO
XIOOO
xtooo
XI OUO
XIOOO
PROCESSED
PrtCjCfcSScO
PKUCt-SStU
PROCESSED
PRUCtSStO
PKOCfcSSED
PHDCtSStO
PROCESSED
OF PRODUCT
Ol- PKUiiUCT
MRUCeSSED
PLATfcD
P.'
-------
713
714
71S
716
7J7
7ltt
719
720
721
722
723
724
725
720
727
728
729
730
731
7J2
733
734
735
736
737
738
739
740
741
742
743
3
3
3
3
3
3
3
' 3
j
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
90
90
90
9U
9O
90
90
90
90
90
90
9O
90
90
9O
90
90
90
9O
90
90
90
90
90
99
01
Ol
01
01
01
02
004
004
OOS
OO5
005
005
005
005
005
OOS
006
006
006
006
006
OO6
006
006
OO7
ooa
009
999
999
999
999
001
001
002
002
999
003
07
99
01
0*
03
04
05
06
07
99
01
02
03
04
05
06
07
99
99
99
99
97
98
99
99
01
02
01
99
99
01
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTR IAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
PRUCEj/INPROCfcSS
PROCES/ I NPKOCESS
P-itlCES/ I NPROCE Sb
PROCc i/ 1 N»R OCE SS
PROC6S / I NPROCE SS
PROCES/INPHOCESS
PROCES/INPHCCESS
PR OCE S/ I NPROCt; SS
PROCES/lNPKUCESb
PROCES/ I NPROCESS
PR OCES/ I NPROCE SS
PROCES/ I NPROCE SS
FUEL
FJi;..
FUcL
FUEL.
FJEL
FUEL
FUFL
FUcL
FUtL
KUcL
F-JEL
FUfcL
PROCES/ I NPROCESS FUEL
PROCES/INPROCESS FUtL
PROCES/ I NPROCESS FUtL
PROCES/ I NPROCESS FUEL
PRUCES/lNPHOCfcSS FUcL
HHOCeS/ I NPROCESS FUCL
PRUCfS/ INPRUCE5S
PROCE5/INPRQCESS
PROCt S/ I NPROCE SS
PR aCES/ I NPROCESS
PROCES/ I NPROCESS
PROCES/OTHER/NOT
POINT SC EVAP /CLEANING
POINT SC EVAP /CLEANING
POINT SC EVAP /CLEANING
POINT SC EVAP /CLEANING
FUEL
FUcL
FUcL
FUfcL
/hi SI DUAL OIL /
/hcSIOUAL OIL /
/JiSTlLLATE OIL '/
/DISTILLATE OIL /
/DISTILLATE OIL /
/DISTILLATE OIL /
/DISTILLATE OIL /
/DISTILLATE OIL /
/t>I5TILLATc OIL /
/DISTILLATE OIL /
/NATURAL GAS /
/NATURAL GAS /
/NATURAL GAS /
/NATURAL GAS /
/NATURAL GAS /
/NATURAL GAS /
/NATURAL GAS /
/NATURAL GAS /
/PROCESS GAS /
/C3KE /
/»UOO /
/O1 HfeR/NOT CLAS1FO/
/OTHER/NOT CLASIFD/
FUtL /OTHER/NUT CLASIFD/
CLASIFD/SPECIFY IN RfcMAHK/
SOLVENT
SULVENT
SOLVENT
SOLVENT
POINT SC EVAP /CLEANING SULVENT
POINT SC EVAP /SURFACE COATING
/DRYCLEANING /
/ORrCLEANING /
/DECREASING /
/DECREASING /
/OTHER/NOT CLAblFD/
/VARNISH/SHELLAC /
GYPSUM KILN/ETC
UTHeR/N
-------
74*
7*5
7*6
7*7
7*8
7*4
7SO
751
752
753
75*
755
756
757
7b6
759
760
761
762
763
76*
765
766
767
768
769
77O
771
772
773
77*
« 02
* 02
4 02
* 02
* O2
4 03
* 03
* O3
4 03
* 03
« O3
* 03
4 03
4 04
» O*
4 OS
« 9O
5 01
5 01
5 01
5 Ot
5 01
5 01
5 01
5 01
5 01
5 01
5 01
5 01
5 01
5 01
001 01 POINT
004 01 POINT
005 01 POINT
006 01
999 99
001 01
001 02
001 03
001 04
002 01
O02 02
002 OJ
OO2 OA
999 99
OOI 99
OO1 01
999 99
001 01
OOI 02
002 01
OO2 02
OO2 03
OOS OS
OO5 O6
OOS O7
OOS 99
VOO OA
900 05
900 06
900 10
900 97
POINT
POINT
POINT
POINT
POINT
POINT
POINT
POINT
POINT
POINT
POINT
POINT
POINT
POINT
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOL I Cl
SOLID
SOLID
SOLID
SOLID
SOL ID
SOLID
SC EVAP
SC tVAP
SC EVAP
SC feVAP
sc EVAP
SC EVAP
SC EVAP
SC EVAP
SC EVAP
SC EVAP
sc EVAP
SC cVAP
SC tVAP
SC EVAP
SC EVAP
SC EVAP
SC EVAP
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
«Asrt
*ASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
/SURFACE COAT INC
/SURFACE COATING
/SURFACE COATING
/SURFACE COATING
/SUHFACE COATING
/PETROLEUM STG
/PETROLEUM SFG
/PETROLEUM STC
/PETROLEUM STG
/PETROLEUM STG
/PETROLEUM STG
/PETROLEUM afG
/PETROLEUM bTG
/PAINT
/LAQUER
/ENAMEL
/
/
/
/PRIMER /
/OTHER/NOT CLASIFO/
/FIXED ROOF
/FIXED RUUF
/FIXED RUOF
/FIXED ROOF
/
/
/
/
/FLOATING ROOF /
/FLOATING ROOF /
/FLOATING ROUF /
/FLOATING ROUF /
/PETHCLEUM STG /OTHER/NOT CLASIFD/
/MISC ORGANIC STUR/OT HER/NOT CLASIFO/
/PRINTING PHtSS
/MISC HC EVAP
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/GOVERNMENT
/l>RYERS /
/OTHER/NOT CLASIFO/
/MUNICIPAL INC1N /
/MUNICIPAL INCIN /
/OMEN BURNING
/OPEN d URN ING
/OPEN BURNING
f INCINERATOR
/ INCINEHATUH
/INCINERATOR
/ INCINERATOR
/AUK. FUEL/NO
/AUX.FUEL/NU
/AUX. FUEL/NO
/AUX.FUKL/NO
/AllX. FUEL/NO
DUMP/
DUMP/
DUMP/
/
/
/
/
UM&NS/
EMSNS/
EMSNi/
EMSNS/
EMSMb/
GENERAL
GENERAL
GENCRAL
GENERAL
SPECIFY IN HcMARK
UHE ATH I Nu-PHOOUCT
BREATHING CRUOc
aURKING-HRDuUCT
HUSKING CRUUE
UREATH1NG PRODUCT
WORKING PROUUCT
UkEATHI NG-CRUDd
WORKING-CRUDE
SPECIFY IN KEMAhK
SPECIFY IN REMARK
GENERAL
SPECIFY IN REMARK
MULTIPLE CHAMBER
SINGLE CHAMBER
GENERAL
LANDSCAPE/PR UN I NO
JET FUEL
PATHOLOGICAL
SLUDGE
CONICAL
OTHbH/NOT CLAblFO
RESIDUAL OIL
DliTILLATt OIL
NATURAL GAS
LPG
OTHER/NOT CLASIFD
/TONS
/TONS
/TONS
/ 1 UNS
/TONS
/IOOO
/IOOO
/IOOO
/IOOO
/IOOO
/IOOO
/I QCtO
/IOOO
/IOOO
/TUNS
/luNS
/TUNS
/TONS
/TUNS
/TONS
/TONS
COATING
CUATING
COATING
COATING
COATING
GALLONS STUKAub CAPACITY
GALLONS bTUKAGt CAPACITY
GALLONS TrtWjUuHPUT
GALLONS THkUGGHi-'UT
GALLONS STORAGE CAPACITY
GALLONS THKUUGHPUT
GALLONS STuRAGt CAPACITY
GALLONS TilKUUuHPUT
GAL i>IGPto
STOHcD
SOLVENT
PMilCcSStO
BUKNfcL)
BUNNEO
DURNbO
BURNED
f
r
m
0
-------
775
5 01 900 98 SOLID WASTE
/GOVERNMENT
/AUX.FUEL/NO EMSNS/ OTHER/NOT CLASIFO /'10OO GALLONS
776
777
778
779
78O
Tttl
782
783
784
783
786
787
788
789
79O
7V1
792
793
794
79S
796
. 797
798
799
800
801
a 02
803
804
805
5
5
S
5
S
S
6
S
S
5
5
S
S
S
5
S
f>
5
S
S
S
5
5
5
5
S
5
5
5
5
Ol
O2
02
O2
02
O2
O2
02
02
02
O2
OZ
02
02
02
02
02
O2
02
03
03
03
03
03
03
03
03
O3
03
O3
90O
OOl
OOI
OOl
001
001
OO2
003
.OOJ
005
OOS
005
900
<*OO
90O
9OO
900
900
90O
001
OOl
OOl
001
OOl
001
002
OO2
O02
003
O03
VV
01
02
O3
04
OS
01
Ol
02
05
06
99
O«
OS
Ob
1O
97
98
99
Ol
02
O3
04
05
06
Ol
02
03
01
O2
SOLID
SOLID
SOLID
SOLID
SOL 1C
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SULIO
SOLID
SOLID
SOLID
SOL 10
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
SOLID
WASTE
ASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
»AS1£
WASTE
WASTE
WASTE
WASTE
WASTE
HASTE
WASTE.
WASTE
WASTE
WASTE
WASTE:
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
WASTE
/(OVEHNMcNT
/COMM-INST .
/COMK-INST
/COMM-INST
/CCMM-INST
/COMM-INST
/COMM-INST
/COMM-INST
/COMM-INST
/CCMM-l.MST
/COMM-INST
/COMM-INST
/COMM-INST
/COMM-INST
/CCMM-INST
/COMM-INST
/CQMM-INbT
/COKM-INST
/COMM-INST
/INDUSTRIAL
/INDUSTRIAL
/INDUSTRIAL
/INDUSTRIAL
/INDUSTRIAL
/INDUSTRIAL
/INDUSTRIAL
/ZNDUSTHIAL
/INDUSTRIAL
/INDUSTRIAL
/INDUSTRIAL
/AUX. FUEL/NO E.MSNS/
/INCINERATOR GSN /
/IlMCtNlRATOR GEN . /
/INCINERATOR GEN /
/INCINtRATUrf GEN /
/INClNEkrtTUH GfcN /
/OPEN BURNING /
/APARTMENT INCIN /
/APARTMENT INCIN /
/INCINcHATOH /
/INCINERATOR /
/INCINERATOR /
/AUX. FUEL/NO EMSNS/
/AUX. FUEL/NO EMSNS/
/AUX. FUEL/NO EMSNS/
/AUX. FUEL/NO EMSNS/
/AUX. FUEL/ML) en SMS/
/AUX. FUEL/NO EMSNS/
/AUX. FUEL/NO EMSNS/
/INCINERATOR /
/INCINERATOR /
/(NCINEHATOM /
/iNCINtfJATOR /
/INCINERATOR /
/INCINERATOR /
/OPEN BURNING /
/OPcN BURNING /
/OPEN BURNING /
/AUTO BODY I NCI NAT/
/AUTO BOOr 1NCINAT/
OTHER/NOT CLASIFO
MULTIPLE CHAMiiCR
SINGLC CrtAMoER
CONTROLLED AIR
CONICAL FEFUSE
CONICAL WOOD
UJO
FLUE FED
FLUE FED-MODIFIED
PATHOLOGICAL
SLUDGE
OTHER/NUT CLASIFO
RESIDUAL UIL
DISTILLATE OIL
NATURAL C.AS
LPG
OTHER/NOT CLASIFD
OTHER/NOT CLASIFO
OTHER/NOT CLASIFD
MULTIPLE CMAMBFK
SINGLE CHAMBER
CONTROLLED AtK
CONICAL REFUSE
CUNIC*L WUUU
OPEN PIT
«Ol>D
REFUSE:
AUTU t>ODV COMPTb
W/U At- TtrtbUKNEw
»/ AFTbkbUKNErf
/TONS
/TONS
/TUNS
/TONS
/TONS
/TONS
/1UHS
/TONS
/1UNS
/TONS
/TONS
/TONS
/IOOO
/1UOO
UURNEO
UUUNC.O
OUhNtD
bUKNi;O
UUKNEU
BUhNLU
BUKNEU
BU^iNED
BUhcNfcD
OUT iLUUGt
UUH.NEO
GALLUNS
GALLUNS
/MILLION CUU1C KEfcT
/IOOO GALLONS
/MILLION CUBIC FEET
/IOOO GALLONS
/TONS
/TONS
/IONS
/TUNS
/TONS
/TONS
/TONS
/TONS
/TONS
/TONS
UUHNEO
bURNcD
UUftNcD
bUHNEO
DUKNED
OF HASTE
BuNNEO
tJUk.MEO
BURNED
/AUTOS SUKNfcD
/AUTOS uUrtNEO
10
VO
o
-------
806 5 03 00* 01 SQL ID HASTE /INDUSTRIAL /RAIL CA« t>Ji
-------
SOLID HASTE OI RESIDENTIAL OPEN BURNING
a 42
643
8»»
845
646
847
8C8
849
050
651
392
833
a 54
ass
656
WS7
858
859
860
861
SOLID WASTE 01 COMM/INST
SOLID HASTE DI COMM/INST
SOLID HASTE DI INDUSTRIAL
SOLID HASTE INDUSTRIAL
TRANSPORTATION GASOLINE
TRANSPORTATION GASOLINE.
TRANSPORTATION GASOLINE
TRANSPORTATION DIESEL
TRANSPORTATION DIESEL
TRANSPORTATION DIESEL
TRANSPORTATION AIR
TRANSPORTATION AIR
TRANSPORTATION AIR
TRANSPORTATION VESSELS
TRANSPORTATION VESSELS
TRANSPORTATION VESSELS
ON SITE. INC I NCR
OPEN BURNING
ON SITt INCINKH
OPEN BURNING
LIGHT VEHICLES
HEAVY VEHICLES
UFF HIGHWAY
HEAVY VEHICLES
UFF HIGHWAY
RAIL
MILITARY
CIVIL
CUMMEfcLlAL
UITUMINOUS COAL
DIESEL FUtEL
rttSIOUAL OIL
TRANSPORTATION VESSELS GASOLINE
TRANSPORTATION GASOLINE HANDLING EVAP LOSS,
MISCELLANEOUS CAS HANDLING EVAP LOSS
MISCELLANEOUS SCLVENT EVAP LOSS
U3
to
-------
APPENDIX D
EMISSIONS DATA FOR SOURCES OF AIR POLLUTION
IN THE CHICAGO AQCR
293
-------
EH1SSICN SGUVSCES IN CCCK
COUNTY * SOUKCE «
,
d
a
5
10
10
10
10
10
10
10
1 1
1 1
1 1
11
1 i
36
36
36
42
42
42
42
42
42
42
42
42
42
42
42
6S
tS
6!
66
Ct
66
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928 1
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248.
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APPENDIX E
MAXIMUM POSSIBLE CHANGE IN TWO SETS OF POPEX VALUES
To calculate the maximum possible changes between two sets of
popex levels, or in other words, between two sets of numbers both of
which add up to 100:
Let a-jy a2, . . . an and b^, b2, . . . bn be the two sets,
such that:
n all ai J o
Z a± = 100
i = 1
Z b± = 100 all
and n
Z
i = 1
n
In order to find the maximum value of Z absolute (a^ - bj.) :
i = 1
n
Z absolute (a.^ - b.^) = ^ - b]L| + |a2 - b21 + . . . + |an - bn|
i = 1
each of the ja.^ - bi| has to be maximized. For this to be true,
either a- or b- has to be zero for all values of n. Therefore the
preceding equation can be rewritten as
n i i I I II
Z absolute ^ - b±) = \a1\ + |a2| + . . . + |an| +
1=1 I I IK I .IK I
b,l + |b2| . . . + |bj
. + Zb±
1 I
325
-------
326
n n
By definition, I a- = 100 and £ b. = 100.
1 1 1
Thus the maximum possible total change in two sets of popex levels
is 200.
-------
327
TECHNICAL REPORT DATA
(Please read Inunctions on the reverse before completing)
REPORT NO.
PA-600/2-76-.Q63
2.
3. RECIPIENT'S ACCESSION-NO.
TITLF ANDSUBTITLE
POPEX--Ranking Air Pollution Sources by Population
Exposure
5. REPORT DATE
1976_
6. PERFORfdlNG ORGANIZATION CODE
AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
Lyndon R. Babcock, Jr. and Niren L. Nagda
PERFORMING ORGANIZATION NAME AND ADDRESS
University of Illinois
Medical Center, P.O. Box 6998
Chicago, Illinois 60680
10. PROGRAM ELEMENT NO.
1AB012; ROAP 21ADK-031
11. CONTRACT/GRANT NO.
Grant R802111
2. SPONSORING AGENCY NAME AND ADDRESS
EPA, Office of Research and Development
[ndustrial Environmental Research Laboratory
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final; 5/74-11/75
14. SPONSORING AGENCY CODE
EPA-ORD
5. SUPPLEMENTARY NOTES EpA project officer for this report is C. T. Ripberger, Mail
Drop 61, Ext 2911.
AR<5TRAI"*T
The report gives results of research to develop quantitative models for
relating emissions of air pollutants to their effects on people, and to use the
methodology for determining the relative importance of air pollution sources. The
quantitative methodology for ranking the sources developed in this project includes
consideration of the dispersion of air pollutants, exposure of people, and subsequent
health effects. The computer model, called POPEX, consists of three submodels:
dispersion, population, and health effects. The model was applied to sources of air
pollution in the Chicago Air Quality Control Region. Results show that 17 of 227
categories of sources contribute nearly 80% of the total air-pollution/population-
effect problem.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. cos AT i Field/Group
Air Pollution
Mathematical Models
Dispersing
Health
Exposure
Ranking
Air Pollution Control
POPEX
Emissions
Effects
Population Effect
. DISTRIBUTION STATEMENTT
Unlimited
13B
12A
07A,08H
06N
06F
12B
05E
19. SECURITY CLASS ('lilts Keport)
Unclassified
?n r.f-ruRiTY>i A°.S ,'vvm-;~>wi
Unclassiiied
21. NO. OF PACiES
341
EPA Form 7.220-1
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