United States ~
Environmental Protection
Agency . , ,
Region 5
Air and Radiation Division
230 South Dearborn Street
Chicago, Illinois 60604
September. 1989
5EPA
T883.5
.I32C45
1989 c. 3
Estimation and OCLC29019631
Evaluation of Cancer
Risks Attributed to Air
Pollution in Southeast
Chicago
Fn\
Ur- ilk i \\' ^
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Estimation and Evaluation of
Cancer Risks Attributable to
Air Pollution in Southeast Chicago
John Surrmerhays
Air and Radiation Division
United States Environmental Protection Agency
Region V
Chicago, Illinois
U.S. Environmental Protection
Region S.Utwy (PH2J)
H West Jackson Boulevard, 12th Floor
Chicago, IL 60604-3590
Septetttoer 1989
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11
Acknowledgements
A study of this magnitude is not completed by a single individual. This
report reflects knowledge possessed by numerous people with expertise on
various source types and pollutants. Both in the technical development of
emissions and risk estimates and in the documentation of this study, the
assistance and advice from many people made this study far better than would
otherwise have been possible.
Particularly noteworthy are the contributions by Tom Lahre of the
Noncriteria Pollutant Programs Branch of the Office of Air Quality Planning
and Standards (OAQPS). Through Tom's arrangements the Noncriteria
Pollutant Programs Branch provided contractual assistance for the dispersion
and risk analyses in this study, without which this study would not have
been possible. Tom also provided valuable information, feedback, and
comments in both the emissions estimation and risk analysis phases of
this study.
The Illinois Environmental Protection Agency and the Indiana Department of
Environmental Management made important contributions to this study. These
agencies sent out questionnaires to industrial facilities and supplied key
information used in the study.
The author wishes to acknowledge important assistance from other employees of
Region V working on this study. Dr. Harriet Croke compiled emissions estimates
for many industrial facilities and managed a contract to develop emissions
estimates for waste handling. Also assisting in developing emissions estimates
were Barry Bolka and Mardi Klevs. Special appreciation is also extended to
Carole Bell and Melody Noel who typed this report.
Several other individuals made significant contributions Dr. Milton Clark.
of Region V's Office of Health and Environmental Assessment, provided useful
advice and comments on the report. Fred Hauchman, of the Pollutant Assessment
Branch of OAQPS, served an important role as a central source of information
on unit risk factors. Dr. Ila Cote, formerly also with the Pollutant Assessment
Branch, provided significant comments and feedback on health impact assessment.
Loren Hall, of the Office of Toxic Substances, provided useful information and
constructive comments 1n both the emissions estimation and risk analysis phases
of the study. American Management Systems provided contractual assistance in
loading and refining PIPQUIC, a data handling system for urban risk assessments.
Midwest Research Institute and Alliance Technologies provided contractual
assistance 1n assessing emissions from waste handling facilities. Valuable
review and comments were provided by Penny Carey (Office of Mobile Sources)
and Cheryl Siegel-Scott (Office of Toxic Substances). Finally, a lengthy list
of other individuals contributed other information on emissions from particular
source types or on other aspects of the study.
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111
TABLE OF CONTENTS
Section Page
Tables 1v
Figures v
Summary vi
Introduction 1
Study Design 3
Emissions Estimation 7
Estimation of Concentrations by 14
Atmospheric Dispersion Modeling
Comparison of Modeling and Monitoring 19
Concentration Estimates
Evaluation of Cancer Risk Factors 26
Incidence and Risk Estimates 32
Conclusions 49
References 53
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IV
TABLES
Number
Page
la. Emissions in Source Area by Source Category and Pollutant 12
Ib. Other Substances in Study 13
2. Monitoring Studies Conducted in Southeast Chicago 21
3- Comparison of Modeled-Versus Monitored-based Concentration
Estimates for Organic Toxicants 22
4. Comparison of Modeled-Versus Monitored-based Concentration
Estimates for PCBs 24
5. Comparison of Modeled-Versus Monitored-based Concentration
Estimates for Particulate Toxicants 25
6. Carcinogenicity of Inventoried Pollutants 29
7. Contributions to Area Cancer Cases by Source Type and
Pollutant Across the Study Area 34
8. Estimated Contributions to Lifetime Cancer Risk at the Grid
with the Highest Estimated Number of Cancer Cases 45
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V
FIGURES
Number
A. Contribution to Estimated Annual Cancer Cases by Source Type vii
la. Southeast Chicago Study Area - Source Area 4
Ib. Southeast Chicago Study Area - Receptor Area 5
2. Map of Estimated Coke Oven Pollutant Concentrations 17
3. Map of Concentrations of Polycyclic Organic Matter 18
4. Contributions to Estimated Annual Cancer Cases by Source Type 33
5. Relative Distribution of Estimated Lifetime Cancer Cases 35
6. Breakdown by Source Category of Contributions to Estimated
Cases 37
7. Contributions to Estimated Cases from Consumer-
oriented Sources 38
8. Contributions of Various Types of Solid Waste Handling 40
9. Contributions to Estimated Annual Cancer Cases
by Pollutant 41
10. Map of Estimated Lifetime Cancer Risks from Air Pollutants
in Southeast Chicago 43
11. Estimated Lifetime Cancer Risks from Air Pollutants 44
12. Contributions to Estimated Risk at the Peak Incidence Location 46
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SUMMARY
Increasing concern has developed that air pollution may cause significant
cancer risks in urban areas due to the combined effects of multiple sources and
multiple pollutants. Given the density of exposed populations in urban areas,
the possibility of high risks would further suggest that the number of incidences
of resulting cancer cases may also be relatively high. The Southeast Chicago
area has both a substantial concentration of industrial and non-industrial
emission sources and a relatively high population density exposed to these
emissions. This study was undertaken to evaluate the extent to which this
exposure to ambient (outdoor) air contaminants may be a public health problem
and to provide an informed basis for determining what emission reductions if
any, might be warranted to reduce the exposure.
The study sought to use as broad a base of information as possible in
evaluating air pollution-related cancer risks in the Southeast Chicago area.
The study considered every air toxicant for which the United States Environ-
mental Protection Agency (USEPA) can estimate a quantitative relationship
between the exposure to the air toxicant and the resulting increase in the
probability of contracting cancer. All source types for which emissions of the
identified pollutants could be quantitatively estimated were included. Estimates
were made of emissions in a relatively broad area, so that impacts both from
nearby sources and from more distant sources could be included.
The National Academy of Sciences has defined risk assessment as a process having
four steps: hazard identification, exposure assessment, assessment of dose-
response relationships, and risk characterization. The hazard identified for
assessment in this study is cancer due to ambient air contamination. The
exposure assessment principally involves estimation of ambient atmospheric
concentrations which, for most pollutants- were estimated by first deriving an
inventory of emissions, and then estimating atmospheric dispersion of these
emissions. The assessment of dose-response relationships involves derivation
of a unit risk factor, which expresses the probability or risk of contracting
cancer that is associated with exposure to a unit concentration of air pollution.
Finally, risk characterization involves deriving various measures of risk. The
simplest measure of risk is individual risk, representing the risk attributable
to air contaminants at a specific geographic location. An alternative measure
of risk is the number of cancer cases attributable to air contaminants estimated
to occur among the population in the study area. In addition to estimating
these general measures of cancer risk, this study also investigated the origins
of these risks and Incidences, i.e., which source types and which pollutants
are the most significant probable causes of these individual and area-wide
risks estimated to result from air pollution in the Southeast Chicago area.
It must be noted that the risk estimates presented In this report should be
regarded" as only rough approximations of total cancer cases and Individual"
lifetime risks, and are best used in a relative sense. Estimates for Indivi-
dual pollutants are highly uncertain and should be used wTth particular caution.
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VI 1
This study found atmospheric emissions of 30 pollutants in the study area which
USEPA considers to be carcinogens. Some of these pollutants have been shown
to be carcinogenic based on human exposure data, and others have been impli-
cated by animal studies.
The cumulative total number of cancer cases that this study estimated to be
attributable to air pollution is about 77 cases over 70 years or about 1 per
year. The area for which exposure was assessed has a population of about
393,000 residents. Therefore, the average risk across the area due to air
pollution as estimated by this study is approximately 2.0xlO-4, or about 2
chances in 10,000. It should be noted that, as a national average across
the United States, the chance of contracting cancer over a lifetime from a
number of factors (including both voluntary and involuntary exposures) which
are not fully understood, is about one chance in three. One in seven people
die from cancer.
Several types of sources appear to contribute significantly to the cancer cases
estimated to result from air pollution in Southeast Chicago. Figure A is a
pie chart of the contributions of various source types to cancer cases in the
area. The^most significant source type 1_s_ steel_mjlls, particularly the coke
ovens found ai steel mil Is. Steel miTTs appear to contribute about 372! of
the total estimated cancer incidence. Frm'sslo"* fynm.-ft-thar •inH^tritil facili-
ties, primarily chrome platers, are,,estimated to CAU5£_app'"OximatpLy 1R* gf
-±he__lnc.jd_ence. Roadway vehicles are estimated to cause about 16% of the total
cancer cases, and consumer-oriented area sources (e.g., home heating and gaso-
line marketing) contribute about 8%. Furthermore, the background pollutant
impacts from formaldehyde and carbon tetrachloride contribute almost the entire
remaining 21%. Together, these source types account for about 99.7% of the
estimated air pollution-related cancer risks in the area.
This study also provides useful information on what source categories in the
area make only minor contributions to the total estimated cancer risks. In
terms of estimated contributions to overall area cancer incidence, facilities
with hazardous and non-hazardous waste (including landfills, two hazardous
waste incinerators, and liquid waste storage tanks and including abandoned
hazardous waste sites) contribute about 0.15% of the total, and wastewater
treatment plants contribute about 0.14% of the total. Thus, these facilities
are clearly estimated to cause much less risk in the Southeast Chicago area
than the more dominant source types discussed previously.
It is useful to apportion the estimated total number of cancer cases according
to the weight of evidence that the pollutants are carcinogenic. According to
USEPA's review of the weight of evidence of carcinogenicity, the 30 pollutants
for which risks were estimated in this study include 6 "known human carcinogens",
22 "probable human carcinogens, and 2 "possible human carcinogens". Of the
estimated 77 cancer cases per 70 years, about 58% are attributable to pollu-
tants that USEPA labels "known human carcinogens," almost 42% are attributable
to "probable human carcinogens," and only about 0.03% are attributable to
"possible human carcinogens."
This study also estimated lifetime individual risks in an array of locations.
A peak lifetime risk of about 5x10*3 (or about 5 chances in 1,000) is estimated
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Figure A. Contributions to Estimated
Cases by Source Type
Consumer Sources (7.9*)
STPs (0.1 %}
Roadway Veh (16 0%)
Waste Fccil. (0.2*) f
Indirect Impacts (20.6SK)
Steel Mills (37.1*)
Other industry (13.18)
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IX
in the study area. However, available Census Bureau information does not
indicate any residents in this area. The square kilometer with the highest
estimated number of cancer cases has an estimated lifetime risk of about 9xlO'4
(9 in 10,000). In general, risks are greatest in the northeast part of the
area and are relatively lower in the less populated southern and western part of
the area. The average lifetime risk across the area is about 2.0xlQ-4 (about 2
in 10,000).
Consideration of the results of this study should include consideration of
various uncertainties inherent in the study. The estimation of emissions
generally relies on extrapolation of studies of emission sources elsewhere to
the sources in the Southeast Chicago area. In addition to uncertainties in
quantitative emissions estimates, there is also qualitative uncertainty since
we may not be aware of some sources and source types for some pollutants.
Atmospheric dispersion modeling also introduces uncertainty in the estimation
of ambient (outdoor) concentrations. Finally, there are significant uncer-
tainties in the unit risk factors used in this study, due to the necessity for
various extrapolations from the exposure conditions in the studies deriving
the risk factors to the exposure conditions in the Southeast Chicago area.
It is difficult to judge whether the risks in this study are more likely to be
underestimated or overestimated. Comparison of monitoring data to the modeling
data used in this study suggests that most pollutants are reasonably well
addressed, but some pollutants appear underestimated. Thus, this comparison
suggests that actual risks may in fact be higher than indicated in this study.
Conversely, the conservatism underlying the unit risk factors used in this
study implies that actual risks may be lower. Both types of uncertainty appear
to be relatively modest for some pollutants and relatively major for other
pollutants. Thus, the risk estimates derived in this study may either overstate
or understate actual risks.
This study did not evaluate routes of exposure to environmental contaminants
other than ambient air pollution. While most if not all the water consumed in
the area is from Lake Michigan, and not groundwater, drinking water is another
potential source of risk. Other environmental exposures include indoor air
pollution (including radon gas), fish consumption and dermal exposure.
Further, there may be other potential carcinogens or source categories which
have not yet been identified.
This study identifies various aspects of air toxics exposure in Southeast
Chicago that warrant further study. Several such investigations are currently
underway.
At the same time, the study suggests that options for reducing risks due to
air pollution in Southeast Chicago should be investigated. This study
identifies the source categories which contribute most to risk in the area and,
therefore, most warrant control. The States and USEPA are working toward
regulating several of the important source types that this study indicates
are significant. It is hoped that this study will form a basis for further
discussions concerning the reduction of cancer risks potentially attributable
to air toxic emissions in the Southeast Chicago area.
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Introduction
Increasing national attention has focused on the health risks from "toxic"
(non-criteria) air pollutants that arise in urban areas where a concentrated
level of industrial activity coexists with high population density. Within
Region V, an area that combines concentrated industrial activity with high popu-
lation density is Southeast Chicago. In particular, Southeast Chicago and the
surrounding area is one of the nation's foremost locations for integrated steel
production and a wide range of other manufacturing activity. This area also
has one of the nation's five facilities permitted for polychlorinated biphenyls
(PCB) incineration and has a variety of other facilities for treating, storing
and disposing of hazardous waste. Therefore, Region V of the United States
Environmental Protection Agency (USEPA), with assistance from the Illinois
Environmental Protection Agency (IEPA) and the Indiana Department of Environ-
mental Management (IDEM), has completed an extensive study of air toxicants in
the Southeast Chicago area.
The goal of this study has been to obtain a broad understanding of the risks of
cancer that may be attributable to inhalation of ambient air pollutants found
in the Southeast Chicago area. The National Academy of Sciences defines four
steps of risk assessments: hazard identification, exposure assessment, evaluation
of dose-response relationships for the pollutants in the study, and estimation
and characterization of risk. Hazard identification involves identifying an
exposure scenario, in this case inhalation of air contaminants, which may be
causing adverse health effects. Exposure assessment involves evaluating
the ambient concentrations of the pollutants to which the public is exposed.
The principal method for assessing exposure in this study is to estimate emis-
sions and then estimate atmospheric dispersion of these emissions. The evalua-
tion of dose-response relationships in this study involves the estimation of
cancer risk factors, representing the cancer risk estimated to result from
breathing a unit concentration (e.g., one millionth of a gram per cubic meter
of air). Finally, estimation and characterization of risk involves compiling
and analyzing all this information in a way that provides useful statements
about risk.
It is instructive to compare the methods of risk assessment used in this study
to the methods of epidemiological studies of cancer statistics. Epidemiological
studies provide a more direct means of considering the impact of environmental
contaminants on cancer rates. Unfortunately, due to the difficulties of
distinguishing environmental factors from other factors, such studies are often
inconclusive. Further, such studies generally do not even attempt to consider
the separate Influences of the various sources of the various environmental
contaminants. The study described in this report thus has different purposes
from the purposes of epidemiological studies. Epidemiological studies, if
conclusive, can provide a better evaluation of the correlation between air
pollution and cancer statistics. However, this study provides a more detailed
data base on the potential relative significance of different source types and
different pollutants. Further, due to the long periods of exposure that are
considered to be involved in cancer induction, current cancer statistics probably
reflect exposures over the last several decades. In contrast, this study
addresses cancer risks that USEPA methods of risk assessment would associate
with current air pollutant concentrations. (This study may be considered to
estimate future risks if air pollutant concentrations were to remain constant
at current levels for the next several decades.) Furthermore, given the mobility
of population in the United States, cancer statistics reflect exposure in
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multiple areas where members of the studied population have lived. In contrast,
this study focuses specifically on estimated impacts of exposure to pollutant
concentrations in the Southeast Chicago area. Thus, this study more serves the
purpose of evaluating which source types and which pollutants are best addressed
in order to reduce the future cancer risks that current risk assessment methods
suggest may result from air pollution in the Southeast Chicago area.
This study may be considered in the context of national concern about urban air
toxics issues. A USEPA report entitled The Air Toxics Problem in the United
States: An Analysis of Cancer Risks for Selected Pollutants (dated May 1985)
estimates that as many as 1800 to 2400 cancer cases per year may be attributed
nationally to air pollution (not including indoor radon). This report further
finds that while individual industrial operations may lead to high localized
risks, a much greater share of the cumulative risk from air toxicants comes
from activities that are more population-oriented, such as driving motor
vehicles and heating (with fireplaces and wood stoves). In fact, limited
monitoring data in some large cities indicates that risks even in residential
and commercial areas approach the risks found near the highest risk industrial
facilities. Further, various studies suggest that cancer risks from air
pollution throughout urban areas are commonly in the range of lxlO~3 (i.e.,
1 case per thousand people exposed for a lifetime) to IxlQ-4 (1 case in 10,000).
These risks arise from the multiple sources of emissions of multiple pollutants
that exist in all urban areas. Since 61% of the United States population lives
in urbanized areas, and the exposure to high urban toxics risks extends
throughout these urban areas, this urban air toxics exposure appears to contri-
bute the major share of the cases of cancer attributable to air pollution. The
purpose of the Southeast Chicago study, then, given the general national picture
of urban air toxics risks, is to define, in more detail, the relative contri-
butions of various source types to that risk in this geographic area.
Conducting a study like this requires substantial computerized data handling.
Data handling for developing emissions estimates required specifically developed
computer programs. Dispersion modeling, risk estimation, and cancer incidence
estimation relied heavily on a data handling system known as PIPQUIC (Program
Integration Project Queries Using Interactive Commands). PIPQUIC also provided
many of the figures shown later in this report.
This report includes eight sections. This introduction has focused on the
context in which this study was conducted. The next section describes
several of the general features of the design of this study. The third
section summarizes the procedures and results of the emissions inventory phase.
The fourth section describes the exposure assessment, particularly describing
the atmospheric dispersion modeling used as the principal method for esti-
mating pollutant concentrations, and also providing a sampling of the concen-
tration outputs of this study. The fifth section compares the modeled concen-
tration estimates against concentration estimates based on monitoring. The
sixth section describes the dose-response relationships (i.e., the health
Impacts associated with given concentrations) used to estimate risks. The
seventh section then presents results of the risk estimations, discussing
the estimated magnitude of the cancer risk attributable to air pollutants,
the relative contributions of different source types and pollutants, and the
spatial distribution of the risks over the studied receptor area. The
final section summarizes the conclusions of this study.
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Study Design
The first step in this study was to plan a study design. A key decision here
was whether to develop a screening study covering multiple pollutants and
multiple source types using only readily available information or whether to
develop a more focused inventory investigating only a few pollutants and source
types. This study was designed for screening purposes, to provide an overview
of excess cancer risks that may be attributable to ambient air pollution in the
area.
This study has been designed to be comprehensive in several respects. First,
it has attempted to include all source types that emit any of the substances
being studied. Second, although the focus of this study is on exposure in a
moderately sized area (approximately 65 square miles), a much broader area was
inventoried to include all sources with potentially significant impacts in the
selected receptor area. Third, this study attempted to address a comprehensive
list of potential carcinogens.
With respect to source types, this study included all source types for which
air toxics emissions could be estimated. A special aspect of this study was
the inclusion of the volatilization from wastewater treatment plants, and
emissions from various kinds of facilities with hazardous and municipal solid
waste. Specific kinds of such facilities addressed in this study include
hazardous waste treatment, storage, and disposal facilities (TSDF's), abandoned
hazardous waste sites, and landfills for municipal waste. Emissions from these
source categories are difficult to estimate and are not included in traditional
air pollutant emissions inventories. However, they were included in this study
due to national and local interest in their relative contribution to risk.
Also included were source types which have more traditionally been inventoried,
such as industrial facilities, population-oriented sources (e.g., dry cleaning)
and highway vehicles. Although more information is generally available to
estimate emissions from these types of sources, the derivation of emissions
factors for the substances inventoried in this study nevertheless required
substantial literature research and then development of factors suitable for
use in this kind of inventory. This study did not involve direct emissions
measurements; instead, emissions estimates reflected production rates of sources
in the area (e.g. tons of steel produced) in conjunction with results from
various studies of the relationship between production and emissions (e.g.,
pounds of emissions per ton of steel produced).
With respect to spatial coverage, Figure la is a map showing the broad "source
area" included 1n the inventory, and Figure Ib is a map showing the smaller
target "receptor area" for the exposure analysis. The focus of this study
is on air pollutant concentrations in the receptor area and on the cancer
impacts that exposure to these air pollutants in this area may cause. However,
it is clear that the air quality in this area is affected by emissions that
can be transported in from a much broader area. Consequently, emissions were
inventoried for a much broader area.
For purposes of this study, the "Southeast Chicago" receptor area was defined
as an area that is approximately a 13 kilometer (8 mile) square, having a
total area of 169 square kilometers (65 square miles). This area covers much
of the southeast corner of the City of Chicago plus portions of adjoining
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SOUTHEAST CHICAGO STUDY AREA
Source Area ,/lif
I *ST ISC
BLUE
ISLAND |HIVERDALE ^
HAMMOND
KINGERY k'xPWY
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SOUTHEAST CHICAGO STUDY AREA
Receptor Area
Dolton
Siblev Blvd.
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suburbs, ranging specifically from 87th Street to Sibley Boulevard and from
Western Avenue to the Indiana State line. This area has a population of about
393,000.
By comparison, the inventoried source area covers a 46 kilometer (about 29 mile)
square area, with a total area of 2136 square kilometers (about 817 square
miles). Since the prevailing winds in the area are from the southwest quadrant,
the source area is skewed toward the south and west of the receptor area. The
specific boundaries of the source area are, in terms of UTM (Universal Trans-
verse Mercator) coordinates, from 4584 to 4630 kilometers northing and from 420
to 466 kilometers easting in zone 16. This source area extends 30 kilometers
south and west and 16 kilometers north and east of the center of the receptor
area. Thus, the emissions study area includes roughly a third of the City of
Chicago, most of the city's southern and southwestern suburbs, and a portion
of Northwest Indiana. This source area has a population of about 2,361,000.
The inventory further includes a few additional point sources outside of this
source area which were judged to be potentially significant sources.
With respect to pollutants, this study included all potential carcinogens for
which a quantitative relationship between air concentration and risk has been
estimated. During the initial design of the study, unit risk factors had been
estimated for 47 of the 51 substances on the targeted pollutant list. However,
further review led to the conclusion that for many of these 47 substances, the
evidence of carcinogenicity is too weak or the cancer risk factor estimates are
too unreliable to use in this study. This further review concluded that 32
substances had reasonable evidence of being carcinogenic and risks could rea-
sonably be quantified. Thus, the study list of 51 substances includes 15 sub-
stances which may or may not be carcinogenic, but could not be quantitatively
analyzed, and 4 substances that were included only on the basis of potential
noncarcinogenic impacts. (As will be discussed below, all but 2 of the 32
quantifiably carcinogenic pollutants were found to have atmospheric emissions
in the studied source area.)
Analysis of systemic, noncarcinogenic health effects was considered beyond the
scope of this study. First, Agency-reviewed dose-response data for systemic
effects due to inhalation of air contaminants were not available at the inception
of this study. Second, analysis of systemic health effects generally requires
consideration of concentration thresholds below which no adverse health effects
are observed. Therefore, it is necessary to conduct a substantially different
and more complicated exposure assessment to evaluate the extent and frequency
with which the threshold may be exceeded. Thus, this study focused on cancer
effects of the 32 pollutants with agency-reviewed risk factors.
As indicated above, this study primarily used emissions estimates in conjunction
with atmospheric dispersion modeling rather than using monitoring data to esti-
mate ambient concentrations of the pollutants being studied. Both methods
have advantages and disadvantages as approaches for estimating ambient concen-
trations. The advantages of modeling include the ability to address concentra-
tions across an entire geographic area, to address long term average concentra-
tions, and to estimate concentrations below the concentration levels that avail-
able monitoring methods can detect. The corresponding disadvantages of monitoring
data are that resource constraints generally limit the collectable data to one
or a few locations and for relatively short time periods. Additionally, moni-
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7
toring methods are not available for some pollutants, and for other pollutants,
monitoring cannot detect some of the concentrations of interest. A further
advantage of the emissions estimation/dispersion modeling approach is that it
readily identifies the separate contributions of sources and source categories
to any given concentration, which monitoring data alone cannot do. For these
reasons, the emissions estimation/dispersion modeling approach was judged a
better means of evaluating concentrations throughout the study area and judged
to be a more informative approach, particularly in describing relative contri-
butions of different source types. On the other hand, monitoring data have the
advantage that for the time and location being monitored, and if concentrations
are detectable, the uncertainties are generally less than the uncertainties
inherent in emissions inventorying and dispersion modeling. For this reason,
monitoring data can be used to obtain a "reality check", to suggest at least
for the locations and pollutants successfully measured whether or not the
modeled concentrations are approximately correct.
A further advantage of monitoring is the ability to assess concentrations (at
least if concentrations are above detection limits) of atmospheric contamination
which is not the direct result of current emissions. A corresponding disadvantage
of the emissions estimation/dispersion modeling approach is that this approach
is unable to consider such "background impacts". For most pollutants in this
study, "background concentrations" may be presumed to be overwhelmed by urban
area emissions, and such background concentrations may reasonably be ignored.
However, two pollutants in this study are presumed to have origins other than
current emissions: formaldehyde and carbon tetrachloride. Although current
emissions of these pollutants contribute to ambient concentrations, most of the
ambient concentrations are attributable to other origins. Much of the formal-
dehyde concentration is presumed to be attributable to atmospheric photochemical
reaction of other organics. Since carbon tetrachloride remains unreacted in the
atmosphere for a very long time, current concentrations are largely the result
of an accumulation of historic emissions over wide geographic areas. Thus,
monitoring data were used in this study to indicate the concentrations of these
two pollutants from origins not addressed by the emissions estimation/dispersion
modeling approach. The term "background pollutants" is used in this report to
identify these origins of risk.
Emission Estimation
The emissions inventory is described in separate reports. A detailed description
of the inventory is given in a July 1987 report entitled "Air Toxics Emissions
Inventory for the Southeast Chicago Area", authored by John Summerhays and
Harriet Croke. This report documents emissions estimates for a wide range of
source types, Including source types that are traditionally inventoried in air
pollution studies as well as some source types that are not traditionally
inventoried such as volatilization from wastewater at sewage treatment plants.
An addendum to this report (dated August 1989) updates this report by describ-
ing limited revisions to the previously described inventory and by describing
procedures and results of estimating air emissions from various waste handling
sources including facilities for the treatment, storage, and disposal of hazardous
waste, from abandoned hazardous waste sites, and from landfills storing municipal
waste. Further details on the estimation of air emissions from the handling of
hazardous and nonhazardous waste are provided in two reports by the Midwest
Research Institute: "Estimation of Hazardous Air Emissions in Southeast Chicago
Contributed by TSDF's", covering air emissions from the treatment, storage, and
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disposal of hazardous waste, and "Estimation of Hazardous Air Emissions From
Sanitary Landfills", covering air emissions from landfills for ordinary muni-
cipal solid waste. Further details for abandoned waste sites are given in a
report by Alliance Technologies Corporation entitled "Estimation of Air Emissions
form Abandoned Waste Sites in the Southeast Chicago Area." The reader interested
in more details of the procedures, data sources, and emissions estimates should
consult these separate reports. The discussion that follows will present only
an overview of the development and results of the emissions inventory.
This study involved no direct measurement of emissions. Instead, emissions
estimates in this study were generally based on local activity levels (e.g.
point by point steel production or local traffic levels) in conjunction with
the results of measurement studies elsewhere establishing the relationship
between activity levels and emissions (e.g.. emissions per ton of steel produced
or per mile driven). This approach is used partly because emissions measurements
even just for the 88 industrial facilities in this study would be prohibitively
expensive, and partly because limited emissions measurements do not necessarily
provide representative long-term data on emissions.
The sources considered in this study include industrial sources, consumer-
oriented sources (e.g. dry cleaning and gasoline marketing), roadway vehicles,
facilities for handling hazardous and municipal waste, and wastewater treatment
plants. From another perspective, many of the industrial sources as well as
the waste handling facilities and the wastewater treatment plants are at clearly
identified locations, and are labeled "point sources." whereas other industrial
activities as well as all of the consumer-oriented sources and roadway vehicles,
are more broadly distributed, and are labeled "area sources." The distinction
between point and area sources leads to the use of different methods for esti-
mating emissions.
For industrial point sources, three emission estimation methods were used. These
methods may be labeled the questionnaire method, the species fraction method, and
the emission factor method. In the first method, questionnaires were sent
to 29 companies considered candidates for being significant sources of air
toxics emissions. These questionnaires requested the annual emissions for each
pollutant in this study, as well as stack data necessary for dispersion modeling.
These questionnaires were sent by the Illinois Environmental Protection Agency
and the Indiana Department of Environmental Management. Region V then reviewed
these company responses to assure that complete and reasonable emissions esti-
mates would be used for these facilities.
The second, species fraction method, was used for 59 other identified facilities.
This method begins with estimates of emissions of total organic emissions and
total suspended particulate emissions, estimates which are based on the best
available information on plant operating rates and estimated emissions per unit
operation. This method then calls for multiplying these emissions totals times
species fractions, expressed as the ratios of the particular species emissions
versus the total emissions, thereby estimating species emissions. For example,
particulate emissions from blast furnaces (e.g., Standard Classification Code
3-03-008-25) were estimated to be 0.013% arsenic, and so a blast furnace
casthouse that emitted 20 tons per year of particulate matter would be estimated
to emit 0.0026 tons per year of arsenic. Similarly, for coke ovens, "coke oven
-------
emissions" (expressed as benzene soluble organics) are estimated as 1.1 times
total participate emissions (thus including a fraction of the particulate
emissions plus a gaseous organic fraction.)
The third, emission factor method, uses a direct emission factor, expressing
the quantity of a particular species emitted per unit activity level (e.g. per
1000 gallons of paint solids). The emission factor is multiplied times the
actual level of activity to estimate total emissions. This method was only
used for one type of source (coke by-product recovery plants), since for all
other point source types the direct emission factors were either not available
or the source types were not found in the Southeast Chicago area.
For area-type sources, both the species fraction method and the emission factor
method were used. As an example of the species fraction method, roadway vehicles
were inventoried by multiplying total emissions of organics times measured or
derived species fractions. As an example of the emission factor method, wood
combustion emissions were estimated by multiplying estimates of wood quantities
burned in fireplaces and wood stoves times an emission factor of the quantity
of the pollutant, polycyclic organic matter, per pound of wood burned. The
companion emissions inventory reports provide more details of the methods used
for each category in this study, as well as a discussion of the advantages and
disadvantages of the two methods.
A further issue to be addressed in inventorying area and mobile sources is the
spatial distribution of these emissions. The impacts of given quantities of
emissions at any particular location are a function of how distant and how
frequently upwind the emission sources are from the impact location. By
definition, area sources are collections of sources too numerous and too dis-
persed to identify the location of each source. The solution to this problem
used in this study was to distribute emissions according to the distribution of
"surrogate parameters" such as population, housing, or manufacturing employment.
For example, it would not have been feasible to identify locations of the
estimated 2650 buildings with air conditioner cooling towers, not to mention
identifying the approximately 15% of those towers which use chromium as a
corrosion inhibitor. Instead, these emissions were distributed in accordance
with the known distribution of nonmanufacturing, nonretail employment. Simi-
larly, roadway vehicle emissions on freeways and other roadways were distributed
according to traffic estimates for freeway and other roadway travel.
In addition to Inventorying the above, which are relatively traditional air
pollution source types, this study also included several source types that
have not traditionally been included in air pollution Inventories. One such
source category Is hazardous waste treatment, storage, and disposal facilities
(TSDFs). The Southeast Chicago study area includes a total of 43 facilities
regulated under the Resource Conservation and Recovery Act to handle hazardous
waste. Included among these facilities is one of the nation's five incinerators
of polychlorinated biphenyls (PCBs), a second incinerator handling non-PCB
hazardous waste, a hazardous waste landfill, several facilities storing waste
in storage tanks, and a majority of facilities loading wastes into drums or
trucks.
Estimating emissions for TSDFs required several steps. The first step was
identifying facilities. The second step was obtaining data on the quantity of
-------
10
each type of waste handled by each facility. The third step was reviewing
studies of the composition of various waste streams to estimate the quantity of
individual pollutants in the waste streams at each facility. Finally, emissions
estimation models were used, relying on the derived estimates of waste quantities
and often relying on assumptions about operating procedures to estimate emissions
of each pollutant at each facility. Most of these emissions estimates were
derived by Midwest Research Institute under contract to USEPA Region V, with
Region V deriving a few additional emission estimates.
A second type of source for which air impacts have rarely been studied are
abandoned hazardous waste sites (sites potentially to be addressed in USEPA's
Superfund program). Estimation of emissions for these sites followed procedures
very similar to the procedures used for TSDFs.
A third type of facility which has not traditionally been included in air
pollution studies, but was included in this study, is municipal waste landfills.
Biodegradation in landfills generates methane, and this methane can carry trace
amounts of contaminants contained in household and industrial solid waste into
the atmosphere.
The first step in estimating these emissions was to review available data on
the contaminant concentrations found in gases emanating from landfills. The
second step was to estimate landfill gas generation rates based on the estimated
volumes of landfill gases for each landfill in the study area. The third step
multiplied the results of the first two steps to estimate the emissions of each
species of concern from each landfill. These estimates were again developed by
Midwest Research Institute under contract to USEPA Region V.
A fourth source type not traditionally included in air pollution studies but
included in this study was wastewater treatment. The focus in this study was
on two wastewater treatment plants handling the largest volumes of industrial
wastewater in the source area, i.e. the Calumet and the West-Southwest treat-
ment plants. For each of these plants, the Metropolitan Sanitary District of
Greater Chicago made measurements of the volatile organic concentrations in the
wastewater entering and exiting each of these facilities for seven consecutive
days. Daily quantities of volatile organics were computed by multiplying the
wastewater concentrations of each compound of interest times the respective
day's volume of wastewater, after which the seven days' quantities were averaged.
The next step of the analysis was to address the fate of these contaminants.
Possible fates for contamination in the influent wastewater include volatili-
zation to the atmosphere, biodegradation in the treatment plant, sludge, and
treated wastewater leaving the plant. Contaminants in the wastewater leaving
the treatment plant, where significant, were addressed by subtracting outgoing
contaminant quantities from incoming contaminant quantities. Partitioning to
sludge was 1n all cases Insignificant. Nevertheless, volatilization from
sludge is included, insofar as sludge contamination was inventoried as if the
contaminants remained in the wastewater available to volatilize. Most wastewater
contamination either volatilizes or biodegrades. Based on studies measuring
volatilization and biodegradation for nonpolar organic solvents (the most
significant contaminants considered here) at other wastewater treatment facili-
ties, it was assumed that volatilization accounts for 40% of incoming contami-
nation (minus any adjustment for contamination in outgoing wastewater) and
biodegradation accounts for the remaining 60%.
-------
n
This study also addressed several other source categories which may be relatively
unimportant with respect to the "traditional" (criteria) air pollutants but
which have the potential to be significant with respect to toxic air pollutant
emissions. While these categories generally emit relatively small quantities of
the traditional pollutants, the materials being emitted appear to be highly
toxic. Examples of such source categories included in this study are chrome
electroplaters (emitting chromium), wood combustion in fireplaces and wood
stoves (emitting polycyclic organic matter, a component of "wood smoke", as a
product of incomplete combustion), and hospitals (emitting ethylene oxide
used in some sterilizing operations).
It should be noted that all emissions estimates were, in general, compiled for
a 1985 base year. A minor deviation from use of 1985 data is the deletion of
sources which are known to have permanently shut down since that time. In
addition, the estimates compiled in this study are for typical actual emissions.
No attempt was made to evaluate emissions for the scenario in which al1 plants
emit maximum allowable amounts, because this scenario is unlikely to persist
continuously over a 70 year lifetime.
An important influence on emissions from many source categories is the existence
of emission controls. This study sought to develop emissions estimates
appropriate to 1985 levels of emission control. A special effort was made
to assure that steel mill emissions estimates reflect the current status of
controls. For other point sources it is less clear whether emission controls
adopted according to various regulations are, in fact, represented in the emis-
sion estimates used in this study, though again, the goal was to use emission
estimates that correspond to 1985 levels of control. For roadway vehicles.
the emission estimates reflected elaborate, computer-assisted evaluation of
what portion of the vehicle fleet had what degree of emission control as of the
1985 inventory date. In particular, the MOBILE 3 emission factor model was used
in conjunction with some updates for the consideration of evaporative emissions.
It is noted that more recent information suggests that evaporative emissions may
be much higher due to "running losses." For other types of sources, for the few
source categories where emissions controls are in place, this study attempted
to use emissions estimates that reflect these controls.
One special element of the emissions inventory development was the use of data
on facility emissions that Section 313 of the Superfund Amendments and
Reauthorization Act requires companies to submit. In particular, companies are
required under this Section to develop and report emissions estimates for
nunerous pollutants including most of the pollutants in this study. These
data were compared with the emissions estimates that were independently derived
in this study. Unfortunately, these reports do not address area sources.
Nevertheless, these data were used for additional refinement of the industrial
source component of the Southeast Chicago area inventory.
Table la summarizes the emissions of known or suspected carcinogens found in
this study. In the study area, 30 pollutants were found which USEPA considers
carcinogenic. This table distinguishes emissions from steel mills, other
industrial operations, consumer-oriented sources, roadway vehicles, hazardous
waste treatment storage, and disposal facilities (also including municipal
waste landfills), and wastewater treatment plants. This table shows that 30 of
the 32 known or suspected carcinogens were found to be emitted in the Southeast
-------
12
Table la. Emissions in Source Area by Source Category and Pollutant (in metric tons/j
Steel
Compound* Mills
Acryl amide
Acrylonitrile
Arsenic 3.9
Asbestos
Benzene 3044.2
Beryllium
Butadiene .2
Cadmium 4.3
Carbon Tet.
Chloroform
Chromium** .07
Coke Oven Em. 388.0
Dioxin
Epichlorohydrin
Eth. Di bromide
Eth. Dichloride
Eth. Oxide
Formaldehyde 14.6
Gas. Vapors
Hex-chl-benz.
Methyl Chi.
Methyl ene Chi.
Perch! oroeth.
PCB's
Other
Industrial Consumer
Sources Sources
.02
1.0
1.2
.02
55.2 37.1
.0008
8.3
.2
.0003
.0003 31.1
2.5 .5
.0002
.09
54.6
61.5 11.2
12.6 110.0
216.2 4737.2
.07
.3 10.9
287.3 1084.0
383.7 802.0
.0002
Mobile Waste
Sources Facilities
.002
.04
812.8 12.0
73.1 .2
.02
2.7
.2
.000009 .0000007
.00002
.8
.2
353.5 .04
14376.0
.5
.0003
61.9
.7
.001
Sewage
Treatment
Plants Total
.02
1.0
5.1
.06
.7 3962.0
.0008
81.8
4.6
2.7
.7 32.0
3.2
388.0
.0002
.09
.8
.7 55.5
72.7
491.7
19329.2
1.3 1.8
.07 11.3
8.6 1441.7
6.0 1192.3
.001
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13
Table la. (Continued)
Other
Steel
Compound* Mills
POM
Prop. Oxide
Styrene
Trichloroeth.
Vinyl Chi.
Vinylidene Chi.
*Abbreviations:
Carbon Tet.
Eth.
Gas.
Hex-chl-benz. -
Industrial Consumer Mobile
Sources Sources Sources
.02 5.6 8.9
.9
3.8
374.7
2.3
.4
Carbon tetrachloride Chi.
Ethyl ene PCB's
Gasoline POM
Hexachlorobenzene Prop.
Waste Treatment
Facilities Plants Total
1.5 2.4
27.8 1.9
4.0
.8 .01
- Chloride
- Polychlorinated bi
- Polycyclic organic
- Propylene
14.6
.9
7.6
404.4
6.3
1.2
phenyl s
matter
**Estimates are for hexavalent (+6) form of chromium.
Table Ib. Other Substances in Study
Substances without Unit Risk Factors
found in Southeast Chicago Area
Acetone
Diethanolamine
Dioctylphthalate
Ethyl Acrylate
Ethylene
Mel amine
Mercury
Nickel
Nitrobenzene
Pentachlorophenol
Titanium Dioxide
Toluene
Xylene
Substances without Unit
Risk Factors not found
Dimethylnitrosamine
Isopropylidene Diphenol
Methyl ene Di am" line
Nitrosomorpholine
Propylene Di chloride
Terepththalic Acid
Substances with Unit
Risk Factors not found
Ally! Chloride
Radionuclides
-------
14
Chicago study area. The significance of the emissions shown here is best
interpreted in terms of risk assessment results, so this topic will be discussed
in the section discussing risk estimates.
As shown in Table lb- this study found no emissions of ally! chloride or radio-
nuclides. This reflects the fact that either this study found no methods for
quantifying emissions of these pollutants, or no sources were identified in this
area. The emissions inventory phase of this study also attempted to include 19
substances without unit risk factors; as described in the inventory reports.
13 of these 19 substances had quantifiable emissions in the study area.
A variety of uncertainties apply to the emissions inventory used in this study.
Emissions measurements were not conducted in the Southeast Chicago area, and so
it was necessary to apply emission factors (i.e., emissions per unit operation)
measured elsewhere in estimating emissions in the Southeast Chicago area. This
extrapolation from sources elsewhere to sources in the Southeast Chicago area
is probably the greatest cause of uncertainty in the emissions inventory. On
the one hand, this extrapolation is probably fairly good for some source types,
especially for area and mobile sources. For example, roadway vehicles in South-
east Chicago are probably similar to the roadway vehicles in other places in the
United States. On the other hand, for other source types, source-to-source
differences in the raw materials used and differences in source operations may
yield significant differences in emissions, not just in the quantity of emissions,
but even in whether particular substances are emitted at all. Sources providing
their own emissions estimates in response to questionnaires may have a better
knowledge of the materials being emitted but may have less knowledge of methods
for estimating emissions. A second major uncertainty is that some sources of
some pollutants may be missing in this inventory either due to lack of awareness
of the source or source type or due to unavailability of information with which
to quantify emissions. This is likely to be a particular problem for relatively
unknown pollutants and for pollutants that are difficult to measure.
Lesser uncertainties exist in various aspects of the emissions estimation
process. Data used to estimate emissions in this study include source operating
rates, emission factors for particulate and organic emissions, data on composition
of these emissions, data on the extent of emissions producing activities (e.g.,
pounds of wood combusted), and data used for area sources to spatially distribute
these emissions. For each of these types of data, the best reasonably available
data were used, but even the best reasonably available data have uncertainties
in their measurement and in their adequacy in representing emissions in the
Southeast Chicago area.
Estimation of Concentrations by Atmospheric Dispersion Modeling
The principal method used in this study to estimate concentrations is to model
the atmospheric dispersion of the emissions estimates described in the previous
section. Atmospheric dispersion is a function of several factors. From the
standpoint of selecting atmospheric dispersion models, two important factors
are the averaging times of the concentrations and the nature of the emissions
sources. With respect to averaging times, some dispersion models are designed
to estimate short term average (e.g., 1 hour average) concentrations, and other
models are designed to estimate long term average (e.g., annual average) concen-
trations. The health effect being addressed in this study, cancer, is most
-------
15
appropriately addressed, by evaluating lifetime cumulative doses (Cf. the "USEPA
Guidelines for Carcinogen Risk Assessment", 51FR33992). Therefore, dispersion
models for estimating long term average concentrations were selected. With
respect to the emissions sources, some dispersion models are designed to address
point sources (i.e., stacks or other similarly localized emission points), and
other dispersion models are designed to address area sources. This study
includes both types of sources. Therefore this study used one model for point
sources and a second model for area sources.
The models used in this study were the Industrial Source Complex Long Term
model (ISCLT) for point sources and version 2 of the Cl imatological Dispersion
Model (CDM-2) for area sources. The two models reflect the obvious differences
in initial dispersion (e.g., the broad dispersion of area source emissions even
at the moment of emission). However, the degree of atmospheric dispersion
assumed in the application of these two models was the same. One parameter in
both models is the choice of dispersion coefficients. Separate sets of disper-
sion coefficients are available for urban versus rural areas to represent the
degree of atmospheric mixing under various meteorological conditions. In this
study, for both models, Briggs' urban dispersion coefficients were used. A
second parameter in both models is the meteorological data used. As a simpli-
fication in estimating long-term average concentrations, both models in this
study use stability array (STAR) data showing the joint frequency distribution
of winds in each of six classes of wind speed and six classes of atmospheric
stability for each of 16 wind directions. Both models estimate concentrations
for each wind speed/stability/wind direction category. These models then
estimate an annual average concentration by averaging the category-specific
concentrations, weighted according to the frequency of each meteorological
category. For both models, the meteorological frequency distribution was based
on 1973 to 1977 data collected at Midway Airport, representing the nearest, most
recent, and most representative complete data set available. Further, both
models assumed relatively flat terrain. Finally, it should be noted that both
of these models are state-of-the-art models which are routinely used for regu-
latory applications where estimates of atmospheric transport and dispersion are
necessary. In fact, both of these models are reference models noted in USEPA's
Guideline on Air Quality Models (Revised), July 1986, (EPA-450/2-78-027R).
Although this guideline does not address the pollutants in this study, the
study uses the models recommended in the guideline for the general type of
modeling being conducted here.
The discussion of emissions estimation has noted that point sources in this
study include steel mills, most other industrial sources, waste handling
facilities, and wastewater treatment plants. That discussion also noted that
area sources include a few industrial source types (chrome platers, degreasing,
and barge loading), consumer-oriented sources, and roadway vehicles. This same
distinction applies to selection of a dispersion model for addressing each source
type. An important exception is that a selected set of steel mill operations
were simulated with a small but finite initial dispersion, reflecting the
modest area from which these emissions arise. These emissions were simulated
using the area source algorithm of ISCLT. For example, a typical coke oven was
simulated by distributing emissions into three neighboring 40 foot squares.
This approach was intended to simulate more realistically the dispersion of
these emissions, and was used for coke ovens and for roof monitors at steel-
-------
16
making furnaces. A second exception is chrome platers. In Illinois, it appeared
that a sufficient listing of electroplaters was available to treat these emis-
sions as point sources, assigning the area's emissions to the identified plater
locations. This treatment has the advantage of providing more realistic treat-
ment of the dispersion characteristics of these sources. Note that in Indiana,
where no listing of sources was available, this source category was both inven-
toried and modeled as area sources. A third exception is municipal waste
landfills, which were simulated as area sources using CDM-2 using landfill-
specific dimensions.
A sample of the concentrations estimated in this study is shown in Figure 2.
This figure shows a map of coke oven pollutant concentrations. This map
highlights the grid system used in estimating concentrations. The area was
divided into 1 kilometer squares, and concentrations were estimated at the
center of each square. The geographic coordinate system used in this study was
the Universal Transverse Mercator (UTM) system. In UTM coordinates, the square
with the highest coke oven pollutant concentrations extends from 4614.5 kilo-
meters to 4615.5 kilometers north and from 452.5 kilometers to 453.5 kilometers
east in zone 16. In Chicago streets, this square extends roughly from 117th
Street to 112th Street and from almost a kilometer west of Torrence Avenue to a
little east of Torrence Avenue. The concentration estimate used for this grid
square was estimated at 4615 kilometers north/453 kilometers east, which is
near 114th Street and Torrence Avenue.
Although the receptor resolution (i.e., the estimation of concentrations at
1 kilometer intervals) is adequate for the purposes of this screening study, it
must be understood that a finer receptor resolution (i.e., estimation of concen-
trations at more closely spaced intervals) would be expected to yield a higher
peak concentration. This is because estimation of concentrations at more
locations can be expected to identify some locations with somewhat higher
concentrations. That is, the actual peak concentration for coke oven pollutants
is probably somewhat higher than the 6.1 ug/m^ shown in figure 2. However, the
design and scope of this study was not to obtain a precise peak concentration
estimate but rather to address area-wide impacts from multiple pollutants and
multiple sources.
The estimate of area-wide exposure to specific pollutants would also be more
precise if a finer receptor resolution were used. However, concentrations
generally do not change dramatically more than a few kilometers from a given
source, so the use of a finer receptor network would not be expected to alter
the area-wide exposure estimates significantly.
Figure 3 shows a map of concentrations of polycyclic organic matter. (This map
and Figure 2 were both produced by PIPQUIC.) This figure shows concentrations
generally increasing toward the center of Chicago, reflecting the increase in
population density and, therefore, density of sources of polycyclic organic
matter (particularly mobile sources and homes being heated) as one approaches
the center of Chicago.
Similar concentration estimates were made for the other pollutants in this study.
However, the most meaningful way of addressing multiple pollutants is to use
the common denominator of risk. This discussion will be included later in this
report.
-------
Figure 2. Map of Estimated Coke Oven Pollutant Concentrations
2
(in ug/m )
max.
87th St.
Sibley Blvd.
-------
Figure 3. Map of Concentrations of Polycyclic Organic Matter
(in ug/m )
0.020
0.015
0.010
max.
oo
87th St.
Sibley Blvd.
V
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19
An unavoidable element of uncertainty is introduced in estimating atmospheric
dispersion. In general , the data and equations used to estimate atmospheric
dispersion are an approximation of real atmospheric phenomena. Specifically,
in Southeast Chicago, the proximity of Lake Michigan may cause alterations in
the frequency of some wind directions and wind speeds and may also affect the
extent of dispersion in this area as compared to the meteorology at Midway
Airport. Generally, atmospheric dispersion models are considered accurate
within a factor of two. Although actual uncertainties for annual average
concentration estimates are difficult to quantify, this generalization does
give a sense of the uncertainties in the modeling element of this study.
A measure of the uncertainty in the exposure assessment may be obtained by
comparing this study's results to the results of a study by USEPA's Office
of Mobile Sources (QMS) using a different method off assessing exposure. The
QMS study used a modified version of the National Ambient Air Quality Standards
Exposure Model (NEM). In this model, a matrix of relationships between carbon
monoxide emissions factors for various situations and the resulting monitored
carbon monoxide concentrations for various exposure environments are used in
conjunction with other pollutant emission factors to estimate exposure to these
other pollutants. An important aspect of the NEM is the consideration of the
variable exposure encountered by a typical commuting individual traversing
various types of locations (including indoor locations). This model also
relies ultimately on monitoring data rather dispersion modeling to estimate
exposure.
If the QMS study results are "normalized" to the same emission rates as were
used in the Southeast Chicago study, the following population-average exposures
from mobile source emissions are estimated: for benzene, 1.22 ug/m3 (OMS study)
versus 0.57 ug/m3 (Southeast Chicago study), a ratio of 2.2:1; for butadiene,
0.13 ug/m3 (OMS) versus 0.05 ug/m3 (Southeast Chicago), a ratio of 2.6:1; and
for formaldehyde, 0.63 ug/m3 (OMS) versus 0.25 ug/m3 (Southeast Chicago), a
ratio of 2.5:1. (The OMS study also found a roughly 6 times higher average
risk from polycyclic organic matter. However, this assessment was based on a
"relative potency" approach of using mutagenicity tests and analogous bioassay
tests to estimate adjusted carcinogenic potencies of particulate extracts from
specific sources types, e.g. diesel particulate. Thus, these results are
difficult to compare to the Southeast Chicago assessment using carcinogenic
potencies based on whole animal studies for a surrogate polycyclic organic
compound.)
These comparisons do not demonstrate that the Southeast Chicago study results
are a given factor too low or that the OMS study results are a given factor too
high. This comparison also may or may not be indicative of differences that
might apply for source types other than mobiles sources. Nevertheless, this
comparison, involving exposure for a mobile individual versus exposure at fixed
points and exposure estimates tied to monitoring data versus exposure estimates
tied to dispersion modeling, suggests an uncertainty and potential underestimation
of exposure by a factor of two or three.
Comparison of Modeling and Monitoring Concentration Estimates
This study uses monitoring data in two ways. The first use is to compare with
dispersion model estimates, to provide an indication of the reliability of the
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20
model estimates. The second use, applicable to formaldehyde and carbon tetra-
chloride, is for quantifying concentrations of "background pollutants" which are
not the direct result of current emissions. Various monitoring programs have
been conducted in the Southeast Chicago area to measure concentrations of
pollutants in this study. Table 2 summarizes the studies from which data were
available. This table shows the organization conducting the monitoring, the
location(s) of the monitoring site(s), the monitoring method, the sampling
period, the number of samples, the sampling duration (frequency and averaging
time) and the pollutants monitored.
Table 3 presents a comparison of modeled versus monitored concentration estimates
for the organic substances for which monitoring data are available. For each
comparison, the monitoring data represent the average over the full time period
for which reliable data are available. The modeling data in effect are 5 year
averages (since the underlying meteorological data are 5 year averages and the
underlying emissions data are intended to be similarly long-term averages).
The modeling results are also specifically interpolated to the location of the
monitor from the concentrations estimated at the nearest modeling grid points.
Although in a few cases such interpolated results may differ significantly from
the results that would be obtained by direct modeling for concentrations at the
monitor location, particularly near major sources where spatial gradients may
be high, in most cases these differences should be small.
The best comparison on Table 3 is for benzene. For this pollutant, the monitored
values are within a factor of two to three higher than the modeled concentrations.
Given the relative sparsity of monitoring data (in no study were more than about
30 days sampled), the uncertainty of the monitoring methods at concentrations
close to the detection limit (generally not more than around three times the
detection limit), and the uncertainties in the emissions inventory and modeling
analysis, these results should be considered quite comparable. Note that although
the modeled estimates could be adjusted to include the benzene component of
coke oven emissions, this would only be a few percent increase. Less encouraging
are the comparisons for toluene and xylene, where monitored values are between
one and two orders of magnitude greater than modeled estimates. The same may
be true of chloroform, whereas the comparison for perch!oroethylene and
trichloroethylene appear to be as close as the comparison for benzene. However,
the concentrations that the Illinois Institute of Technology (IIT) and the
Hazardous Waste Research Information Center (HWRIC) identify for perch!oroethylene,
trichloroethylene, chloroform, and carbon tetrachloride are below the detection
limits as identified for Illinois EPA/Radian's monitoring, so these comparisons
may not be reliable.
It has been noted previously that a substantial portion of formaldehyde and
carbon tetrachloride concentrations may be attributed to origins other than
current emissions. In this study, the emissions estimation/dispersion modeling
approach is considered the best means of addressing the impacts of current
emissions. For formaldehyde and carbon tetrachloride, monitoring data provide
the best indication of the sum of direct Impacts from current emissions plus
indirect impacts from other causes. Thus, in this study, background concen-
trations for these two pollutants were evaluated by determining a total con-
centration from available monitoring data and then subtracting the concentration
attributable to current emissions. These background concentrations were assumed
to be uniform throughout the Southeast Chicago area. Total concentrations of
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Organization
Table 2. Monitoring Studies Conducted in Southeast Chicago
Monitoring Location
Monitoring
Method
Sampling
Period
Number
of Samples
Sample
Duration
Monitored
Pollutants
Illinois EPA/Radian
Carver High School
(4611.7N/450.9E)
Canister
Cartridge
Filter
9/87 to 3/88
16
24 hrs. Organics
every Formaldehyde
12 days metals,B(a)p
USEPA (Toxic Air
Monitoring System
(TAMS))
Illinois Institute
of Technology (IIT)
National
Particulate
Network
S.E. Police Station
(4615.5N/450.0E)
Tenax 7/85 to
(no data for 11/86
canister samples)
30
Illinois Dept. of
Energy and Natural
Resources/Hazardous
Waste Reseach and
Information Center
(HWRIC)
Illinois EPA
S.E. Police Station
(4615.5N/450.0E)
Carver El em. School
(4611.1N/449.8E)
Washington High School
(4615.ON/455.OE)
Addams School
(4616.2N/453.8E)
Bright School
(4616.5N/453.2E)
Bright School
(4616.5N/453.2E)
Bright School
(4616.5N/453.2E)
Washington High
(4615.ON/455.OE)
Grissom School
(4612.3N/453.9E)
Canister
Tenax
Filters
11/86 to 2/87 5 to 7
1985 to 1987 30/year
Canister 10/86 to 6/87
Impactor 1987
Dichot.sampler 6/86 to 6/87
Streaker 1987
Polyurethane
Foam
2/86 to 8/86
24 hrs.
every
12 days
Organics
4 hrs. Organics
24 hrs. metals, B(a)p
every
12 days
10-15
4
?
1
1 min.
24 hrs.
100 hrs.
7 days
Organics
metals
metal s
metal s
24 hrs,
PCB
-------
Table 3. Comparision of Modeled-versus Monitored-based Concentration
Estimates for Organic Toxicants
(all concentrations in ug/m3)
IEPA/Radian'
TAMS*
I IT'
COMPOUND
Benzene
Carbon Tet.
Chloroform
Ethyl ene
Formaldehyde
Methyl ene Chi.
Perchloroethylene
Toluene
Trichloroethylene
Xylenes & Styrene
* These acronyms are defined and details of the monitoring programs are given in Table 2.
** < signifies below the identified detection limit
Monitored
3.63
<3.8**
<4.4**
2.50
<1.4**
<5.4**
11.66
<4.8**
43.03
Modeled
1.16
.0030
.016
.27
.72
.47
.24
.25
.13
Monitored
4.14
2.37
12.97
9.94
Modeled
1.55
.92
.24
.10
Monitored
4.75
2.70
2.78
4.61
2.23
9.93
.91
7.86
Modeled
1.55
.0027
.023
.008
.92
.24
.36
.10
HWRIC*
Monitored
5.10
0.44
1.95
6.39
14.35
Modeled
5.12
.0052
.017
.94
.34
PO
ro
-------
23
these two pollutants at each of the receptor locations were then derived by
adding the uniform concentration representing background impacts plus the vari-
able concentrations representing direct emissions impacts.
As seen in Tables 2 and 3, formaldehyde was monitored at one location in the
area. Data are available for a year starting in September 1987. The average
of available data is a concentration of 2.50 ug/m3. At the monitor location,
the impact of direct emissions is estimated to be 0.27 ug/m3. Therefore, the
formaldehyde concentration attributed to photochemical formation is the
difference of 2.23 ug/m3.
Tables 2 and 3 show that carbon tetrachloride was monitored at three locations
in the Southeast Chicago area. However, Table 2 also shows that two of the
three studies (by IIT and HWRIC) include only a small number of samples, and
Table 3 shows that the third study (by Illinois EPA/Radian) did not report any
detectable concentrations. Atmospheric accumulation of carbon tetrachloride
over prior decades may be presumed fairly uniformly distributed in the global
atmosphere, and so a more reliable indicator of the atmospheric accumulation of
carbon tetrachloride is from more thorough studies elsewhere. In areas of the
United States that may be presumed not to have significant sources of carbon
tetrachloride, available monitoring data suggest concentrations generally
between 0.6 and 0.8 ug/m3. An average value of 0.76 ug/m3 is used as the average
value in the Southeast Chicago area. Most of this concentration is assumed
uniform throughout the area; only the minor portion of the concentration
attributable to current emissions is treated as varying from location to location.
Table 4 compares PCB concentrations monitored by IEPA with modeled concen-
trations. Possible explanations for this relatively poor comparison include
missing emission sources, uncertainties in the monitoring method, a short and
therefore possibly unrepresentative monitoring period, and the long atmospheric
residence of PCBs.
Table 5 compares particulate matter monitoring data with modeled concentrations.
For arsenic, cadmium, and chromium, the two sets of concentrations are quite
similar, indeed well within the uncertainty ranges for the monitoring and
modeling data. (Note that for chromium, both the monitoring and modeling data
show total chromium concentrations.) The other pollutant shown in Table 5,
benzo(a)pyrene, again seems to show a close comparison between monitored and
modeled concentrations. This comparison is complicated by the fact that the
monitoring method measures specifically benzo(a)pyrene, a compound which in
the inventory is Included in the class of compounds labeled polycyclic organic
matter (POM) as well as in coke oven emissions. The designated modeled value
in Table 5 was estimated as a somewhat arbitrary 1% of the combined mass of POM
plus coke oven pollutants. Given the uncertainty in this comparison, no firm
conclusions can be drawn from the similarity of these monitored and modeled
data.
These comparisons of modeled versus monitored concentration estimates appear to
support two generalizations: (1) for many pollutants, the modeled and monitored
concentration estimates agree reasonably well, and (2) where substantial
differences exist, the modeled values are much lower than the monitored values.
The first generalization suggests that for most pollutants, this study provides
-------
24
Table 4. Comparison of Modeled- Versus Monitored-based
Concentration Estimates for PCBs
(all concentrations in ug/m^)
Monitored Modeled
Bright School .0019 .000003
Washington School .0003 .000002
Grissom School .0005 .000004
-------
Table 5. Comparison of Modeled- Versus Monitored-based Concentration
Estimates for Participate Toxicants
(all concentrations in ug/m^)
BRIGHT
ELEMENT
Arsenic
Cadmium
Chromium
Benzo(a)
pyrene
CARVER
Monitored
<*
.0044
.021
--
Modeled
.0014
.0020
.029
—
WASHINGTON
Monitored
.0036
.0037
.04
.0064
Modeled
.0091
.0123
.11
.0098
ADDAMS
Monitored
<*
.003
.029
—
Modeled
.0056
.0064
.026
--
Monitored
(NPN)
.00214
.00055
.0064
.0076
Modeled
.0027
.0031
.021
.0072
Monitored
(HWRIC)
.001
.002
.013
--
rv>
en
* < signifies below detection limit
-------
26
a reasonable assessment of the concentrations of these pollutants. The second
generalization suggests that while there may be a mix of underestimates and
overestimates of concentrations, the net effect is probably to underestimate
overall pollutant exposure. This in turn suggests the possibility that the
emissions inventory of this study underestimates emissions, perhaps by under-
estimating emissions at identified facilities and perhaps by failing to identify
some sources of emissions. Supporting this hypothesis, some of the pollutants
which appear most underestimated by modeling (particularly PCBs and chloroform)
are also among the more difficult pollutants for which to estimate emissions.
This study seeks not just to estimate total risks from various pollutants but
also to assess the relative significance of various source types. Thus it
would be desirable to use the comparison of modeling versus monitoring to assess
whether pollutants from some source types appear more reliably analyzed than
pollutants from other source types. Qualitatively, relatively good comparisons
were found for the metals, which are most emitted by steel mills, for benzene,
most of which is emitted by steel mills and mobile sources, and for the degreasing
solvents, which are emitted by "other industrial sources." However, no such
statements can be made for pollutants where modeling and monitoring results do
not compare well. Since it is not clear what modifications may be warranted to
improve the modeling versus monitoring comparison, it is not clear what
modifications to source contribution estimates are warranted. For example, if
the emissions inventory is missing significant emissions of particular pollutants,
it is not clear what source types might have significantly underestimated
emissions and what source types might be altogether missing from the inventory.
Consequently, no conclusions can be reached as to impacts of particular
source types being especially underestimated.
Evaluation of Cancer Risk Factors
Once concentration estimates have been made for the identified pollutants, it
is then necessary to estimate the relationship between concentration and the
increased probability or risk of contracting cancer that exposure to each pollu-
tant may cause. This relationship is commonly expressed in terms of a unit
factor, representing the risk estimated to result from exposure to a unit con-
centration of a pollutant. For example, if a pollutant has a unit risk factor
of IxlO-4 per ug/m3, then lifetime exposure to 1 ug/m3 (1 millionth of a gram
of the pollutant per cubic meter of air) would be estimated to increase the
probability of contracting cancer by IxlO'4 or 1 chance in 10,000. The pro-
bability or risk of contracting cancer is generally treated as linear within
the range of actual exposure conditions, so that in the example above, exposure
to a concentration of 3 ug/m3 would be estimated to increase cancer risks to
3xlO'4 or 3 chances in 10,000.
There is a lack of data where large numbers of people are exposed to typical
environmental concentrations, where the concentrations and the resulting number
of cancer cases are well defined for several subpopulations, and where confounding
influences from other causes of cancer can be clearly factored out. Therefore,
a variety of methods, scientific judgments and assumptions are used to assess
the relationship between exposure to a pollutant and the resulting risk of con-
tracting cancer.
-------
27
For some pollutants, sufficient data do exist for specifiable human exposure
circumstances to estimate the exposure levels and to evaluate the cancer risks
that apparently result. The interpretation of these statistical data is gene-
rally designed to derive a maximum likelihood estimate of the unit risk factor
(i.e., deriving a unit risk factor which the data suggest will have the greatest
likelihood of accurately representing the ratio between exposure and cancer
risk for the conditions of the study). In general, the exposures that can be
studied are higher than typical ambient concentrations, and so extrapolation of
the exposure-cancer risk relationship must be performed. This extrapolation of
the dose-response relationship down to lower exposure levels uses conservative
methods, so as to decrease the likelihood of underestimating risks.
For a majority of pollutants, however, no human exposure situation can be
sufficiently characterized to support the derivation of a unit risk factor.
The only data for deriving unit risk factors for these pollutants, then, will
generally be from studies involving animals. These studies provide statistical
data which by various interpretations can yield alternative unit risk factor
estimates. The usual interpretation method is to select a 95% upper confidence
level value. This signifies that the selected unit risk factor is the value
which has a 95% likelihood of not understating the true risk factor indicated
by the data. It should be noted that this discussion refers only to the con-
servatism inherent in the statistical interpretation of cancer data, which is
not the only element of conservatism in the unit risk factor. As with the
maximum likelihood estimate, a downward extrapolation from studied exposures to
ambient exposures is necessary, and this extrapolation is done in a way that
adds conservatism. (For animal studies, practical considerations generally
require studied exposures to be higher than ambient exposures. For example, a
study involving 100 animals cannot provide a meaningful result if the risk is
1 in 1,000,000.) The extrapolation of the unit risk factor applicable to
typical ambient concentrations involves best scientific judgement of a plausible
yet conservative extrapolation. With animal studies, an additional adjustment
is made from animal carcinogenicity to human carcinogenicity based on differences
in body weight and breathing rate, again involving best scientific judgement of
a plausible yet conservative extrapolation. Thus, the methods of extrapolating
unit risk factors add some conservatism to the conservatism inherent in the use
of a 95% upper confidence limit.
The relationship between pollutant concentration and cancer risk is a function
of both the quantity of pollutant inhaled and the body's reaction to the inhaled
quantity. Unit risk factors are designed to estimate the cancer risk resulting
from inhaling a unit concentration for 24 hours a day for a 70 year lifetime.
Similarly, cancer risks in this study are estimated by assuming that Southeast
Chicago area residents are exposed to the estimated concentrations for 24
hours per day for a 70 year lifetime. Clearly, these residents spend some time
outside the study area and spend some time indoors, but the absence of knowledge
of pollutant concentrations in these other environments makes it impossible to
make upward or downward adjustments according to these other exposures.
In addition to variability in carcinogenic strength, there is also variability
in how much evidence exists to indicate more fundamentally whether individual
pollutants are in fact carcinogenic. Therefore, USEPA has established a
classification system describing the weight of experimental evidence that a
pollutant is carcinogenic. The classifications used by the U.S. EPA are-
A - human carcinogen; B - probable human carcinogen; C - possible human car-
-------
28
cinogen; D - not classifiable as to human carcinogenicity; and E - evidence of
noncarcinogenicity in humans. These ratings reflect the following types of
evidence: A - "sufficient" human data show carcinogenicity; B - is subdivided
into Bl and B2, in which either "limited" human data or "sufficient" animal
data show carcinogenicity; C - human data are inadequate or nonexistent but
limited animal data show carcinogenicity; D - data to assess carcinogenicity
are inadequate or nonexistent; and E - well designed studies suggest that the
pollutant is noncarcinogenic. More detailed definitions of these classifications
can be found in USE PA's Risk Assessment Guidelines of 1986. For clarity,
references to group A pollutants in this report will use the term "known human
carcinogen."
The classifications in the weight of evidence approach are intended to indicate
the strength of the evidence of carcinogenicity independently of any evaluation
of carcinogenic strength. As yet, no equivalent system has been developed to
address the accuracy of the unit risk factors. For some pollutants, a greater
weight of evidence of carcinogenicity also signifies a better data base from
which to estimate unit risk factors, but this is not the case for all pollu-
tants.
This study found and quantified emissions for 30 presumed carcinogens. USEPA's
evaluation of the weight of evidence is that these 30 pollutants include 6 known
human carcinogens. 22 probable human carcinogens, and 2 possible human carcino-
gens. Table 6 provides the names of these pollutants, the weight of evidence
classification, the unit risk factor used in this study, and whether this risk
factor is calculated as a 95% upper confidence level (UCL), a maximum likeli-
hood estimate value (MLE), or a best estimate (BE). This table also shows
which USEPA office developed the unit risk factor. In this table, IRIS (Inte-
grated Risk Information System) signifies risk factors that have received
agency-wide review. Other values have not received agency-wide review but have
been developed by the Office of Health and Environmental Assessment in the
Office of Research and Development (designated OHEA), by the Office of Air
Quality Planning and Standards (designated OAQPS), or by the Office of Toxic
Substances (designated OTS).
Several of the pollutants in Table 6 represent mixtures of compounds. One
such mixture is designated in Table 6 as "Benzo(a)pyrene (POM)." Benzo(a)
pyrene is the most studied member of the class of compounds known as polycyclic
organic matter (POM). This study inventoried emissions and estimated concen-
trations of the full class of POM compounds, and then estimated risk by multi-
plying the POM concentrations times the benzo(a)pyrene unit risk factor. While
some POM compounds are probably more carcinogenic and other POM compounds are
less carcinogenic, this approach in effect assumes that the average cancer
potency of the full range of POM compounds equals the cancer potency of
benzo(a)pyrene.
Another mixture shown in Table 6 1s coke oven emissions. For this mixture, a
unit risk factor for the full mixture has been developed (based on epidemio-
logical analysis of occupational exposure data). This mixture includes sub-
stantial quantities of other pollutants in this study, including polycyclic
organic matter and benzene. However, no effort was made to assess emissions or
risk from these coke oven gas constituents individually. Instead, the emissions
estimates, the unit risk factor, and the risk estimates for coke oven emissions
are designed to address the emissions, toxicity, and risk of the full mixture
emitted from coke batteries.
-------
29
Table 6. Carcinogenicity of Inventoried Pollutants
Pollutant
Acryl amide
Acrylonitrile
Arsenic
Asbestos
Benzene
Benzo(a)pyrene (POM)
Beryllium
Butadiene
Cadmium
Carbon Tetrachloride
Chloroform
Chromium
Coke Oven Emissions
Dioxin
Epichlorohydrin
Ethyl ene Di bromide
Ethylene Dichloride
Ethyl ene Oxide
Formaldehyde
Gasoline Vapors
Hexachlorobenzene
Methyl Chloride
Weight of
Evidence
Rating*
B2
Bl
A
A
A
B2
B2
B2
Bl
B2
B2
A
A
B2
B2
B2
B2
B1-B2
Bl
B2
B2
C
Unit Risk
Factor
(in (ug/ml)zi)
1.2 x 10'3
6.8 x lO-5
4.3 x 10'3
8.1 x ID'3
8.3 x lO'6
1.7 x 10'3
2.4 x 10~3
1.1 x ID'4
1.8 x 10'3
1.5 x lO'5
2.3 x 10-5
1.2 x 10'2
6.2 x lO'4
3.3 x 10+1
1.2 x lO'6
2.2 x lO'4
2.6 x lO'5
1.0 x lO'4
1.3 x ID'5
6.6 x ID'7
4.9 x lO'4
3.6 x ID'6
Type of
Risk
Factor**
UCL
UCL
MLE
BE
MLE
UCL
UCL
UCL
MLE
UCL
UCL
MLE
UCL
UCL
UCL
UCL
UCL
UCL
UCL
UCL
UCL
UCL
Source
of
Data***
IRIS
IRIS
IRIS
IRIS
IRIS
OAQPS
IRIS
OAQPS
IRIS
IRIS
IRIS
IRIS
OHEA
OHEA
IRIS
IRIS
IRIS
OHEA
OTS
OAQPS
OHEA
OHEA
-------
30
Table 6. (Continued)
Pollutant
Methylene Chloride
Perchlorethylene
PCB's
Propylene Oxide
Styrene
Trichloroethylene
Vinyl Chloride
Vinylidene Chloride
Weight of
Evidence
Rating*
B2
B2
B2
B2
B2
B2
A
C
Un i t Ri s k
Factor
(in (ug/m3)-l)
4.7
5.8
2.2
3.8
5.7
1.7
4.1
5.0
X
X
X
X
X
X
X
X
10-7
10-7
lO'3
io-6
10-7
io-6
10~6
10-5
Type of
Risk
Factor**
UCL
UCL
UCL
UCL
UCL
UCL
UCL
UCL
Source
of
Data***
OHEA
OHEA
OHEA
OHEA
OHEA
OHEA
OAQPS
IRIS
* - As discussed in text, these ratings signify:
A - Known human carcinogen
B - Probable human carcinogen
Bl - Based on "limited" human data
B2 - Based on "sufficient" animal studies
C - Possible human carcinogen
** _
The three types of risk factors used in this study are
UCL - 95% upper confidence limit
MLE - maximum likelihood estimate
BE - best estimate
*** IRIS - Integrated Risk Information System
OAQPS - Office of Air Quality Planning and Standards
OHEA - Office of Health and Environmental Assessment
OTS - Office of Toxic Substances
Note- As described in the text, each unit risk factor estimates risk from
lifetime exposure to a unit pollutant concentration.
-------
31
A third mixture shown in Table 6 is dioxin. In this study "dioxin" represents
a class of 75 chlorinated dibenzo-dioxins and 135 chlorinated dibenzo-furans.
The unit risk factor shown in Table 6 is for 2,3.7,8 - tetrachloro-dibenzo-
dioxin (2-3,7-8 - TCDD). the best studied dioxin. Other dioxins were inventoried
on the basis of toxic equivalents, i.e., what mass of 2,3,7,8 - TCDD would have
equivalent toxicity to the given mass of identified dioxin. For example, 10
grams of 2,3,7,8 - tetrachloro-dibenzo-furan, having an estimated toxicity
equivalence factor of P.!, would be inventoried as if it were 1 gram of
2,3,7,8 - TCDD. Quantitative details are given in the inventory documentation.
Two other mixtures shown in Table 6 are gasoline vapors and polychlorinated
biphenyls (PCBs). The unit risk factor for gasoline vapors was derived from a
study of the full mixture, though it does not include the impact of gasoline's
benzene component. The unit risk factor for PCBs was derived for a representative
compound of this set of compounds. Finally, it should be noted that "hexa-
chlorobenzene" emissions in some cases included emissions of other chlorinated
benzene compounds, a mixture which was conservatively treated as having the
carcinogenicity of hexachlorobenzene.
Chromium and ethylene oxide also warrant special comment. For chromium, both
the emissions estimates and the unit risk factor are only for the hexavalent
(+6) form of chromium. For ethylene oxide, the classification B1-B2 refers to
the fact that there is both "limited" human evidence and "sufficient" animal
evidence of the carcinogenicity of this compound.
The above discussion addresses the calculation of risks from individual pollu-
tants. This study also seeks to estimate the combined impact of all the
pollutants included in this study. The methodology recommended in the "Chemical
Mixtures Risk Assessment Guidelines" (part of USEPA's Risk Assessment Guidelines
of 1986) is to estimate total risks as a linear sum of the individual pollutant
risksin the absence of information suggesting otherwise. It is possible that
exposure to some combinations of pollutants may cause a greater risk (synergism)
or a lesser risk (antagonism) than the sum of the risks resulting rrom exposure
to the substances individually. However, there are no clear means of quantify-
ing any synergistic or antagonistic effects from exposure to the complex and
variable mixtures in the Southeast Chicago area atmosphere, if in fact such
effects are occurring. Therefore, the method for combining risks used in this
study was to sun the risks estimated for individual pollutants.
The unit risk factors used in this study reflect the best judgements of USEPA
scientists in evaluating available evidence both as to the interpretation of
specific studies and as to the procedures that most reliably extrapolate unit
risk factors from these studies. Nevertheless, the uncertainties in the unit
risk factors are probably the greatest uncertainties in this study. These
uncertainties arise from the significant extrapolations such as from high
concentrations to lower concentrations and from rats or mice to humans that
are necessary to estimate the risk factors.
The Risk Assessment Guidelines of 1986 discuss the significant assumptions and
therefore the significant uncertainties that are necessary in developing unit
risk factors. In summary, these assumptions and uncertainties are as follows:
(1) Exposure to any amount of the substance, no matter how small , is assumed to
represent an increased probability of cancer. There is uncertainty that cancer
impacts may occur only above some pollutant-specific threshold concentration;
-------
32
(2) For risk factors base-d on animal studies, the development of cancer in
humans is analogous to the development of cancer in the animals. There is
uncertainty that the biological process of cancer formation is the same process
in humans as in animals. For this and other reasons, there is also uncertainty
in the quantitative extrapolation of the relationship between cancer risks and
exposure for humans from the relationship for animals- (3) Information on the
carcinogenicity of substances at "high" concentrations can be used to predict
the effects at "low" concentrations; and (4) The increased probability of cancer
incidence is proportional to the concentration of the substance at low
concentrations.
Incidence and Risk Estimates
As indicated previously, risks at a given location were estimated by multi-
plying, for each pollutant, the modeled concentration estimate (in ug/m3) times
the risk per ug/m3 of that pollutant, and then summing for all pollutants.
These risks are commonly expressed in exponential form, where, for example,
2xlO-3 equals 2 chances in 1,000. Thus, a person residing for a lifetime at
such a location will have 2 chances in 1000 of contracting cancer from this
exposure.
Incidence is a more population-oriented measure of pollutant impacts. By multi-
plying the risk in a given grid times the number of people in that grid, one
can estimate a probable number of cancer cases contracted as a result of the
exposure. For example, if a grid square with an estimated lifetime risk of
2x10-3 has a population of 2000, one would estimate that a lifetime of exposure
would lead to 4 cancer cases. This figure is sometimes translated to an annual
probability: a probability estimate of 4 cases divided by a 70 year lifetime
suggests a probability estimate of 4/70 or 0.057 cases per year or one case per
17.5 years. This calculation is done for each grid square; the total across
all grids is then the estimated number of cancer cases in the entire study area
attributable to air pollution.
It should be noted that the risk estimates presented in this report should be
regarded as only rough approximations of total cancer cases and individual
lifetime risks, and are best used in a relative sense. Estimates for indivi-
dual pollutants are highly uncertain and should be used with particular caution.
The total cancer incidence estimated in this study is approximately 77 cases
over 70 years, or about 1 case per year. Figure 4 is a pie chart illustrat-
ing the contributions of the various source types to this estimated incidence.
Table 7 presents a more detailed table breaking down the contributions by
pollutant and by source type. Figure 5 shows the spatial distribution of
cancer incidence estimates. (Areas with zero incidence estimates, such as in
the Lake Calumet area, represent areas with no residents.)
Figure 4 and Table 7 show that the greatest contribution to cancer incidence in
the Southeast Chicago area appears to result from emissions at steelmaking
facilities. In total, the various integrated steel mills in the southern Lake
Michigan area were estimated to cause about 29 cancer cases over 70 years.
representing about 37% of the total. Coke ovens in particular appear to
contribute more than any other individual operation to air pollution-related
cancer incidence. Specifically, the emissions from coke ovens, including the
emissions from charging coal into the ovens and from leaks around the oven
-------
Figure 4. Contributions to Estimated
Cases by Source Type
Consumer Sources (7.9*)
5rPs
Roddwdy Veh (16 0*)
Waste Facil. (0.2*)
Indirect Impacts (20.6*)
Steel Wills (37.1*)
GJ
00
Other Industry (1S.1*)
-------
34
Compound*
Acryl amide
Acrylonitrile
Arsenic
Asbestos
Benzene
Beryl 1i urn
Butadiene
Cadmium
Carbon Tet.
Chloroform
Ch rom i urn
Coke Oven Em.
Dioxin
Epichlorohydrin
Eth. Di bromide
Eth. Bichloride
Eth. Oxide
Formaldehyde
Gas. Vapors
Hex-chl-benz.
Methyl Chi.
Methylene Chi.
Perch! oroeth.
PCB's
POM
Prop. Oxide
Styrene
Triehioroeth.
Vinyl Chi.
Vinylidene Chi.
Table 7. Contributions to Estimated Area Cancer Cases by
Source Type and Pollutant Across the Study Area
(in cases per 70 years)
Steel
Mi 11 s
m
.8
.06
24.2
m
Other
Industrial Consumer Mobile
Sources Sources Sources
m**
m
.1
Sewage
Waste Treatment Background
Handling Plants Pollutants
m
.02
.01
m
m
13.0
.2
m
.05
.2
m
m
m
m
.04
.04
m
m
m
m
.2
m
m
.04
.1
.2
1.7
.3
.4
.9
.01
.1
.1
2.2
.1
1.9
2.2
.01
.05
1.3
2.6
4.3
m
m
m
m
m
.01
m
.01
m
m
m
m
To
1.
4.5
m
1
2
m
m
.06
m
m
m
m
m
m
.01
.01
.01
11.4
m
m
m
m
m
m
TOTAL***
*Abbreviations:
Carbon Tet,
Eth.
Gas.
29 14
- Carbon tetrachloride
- Ethylene
- Gasoline
Hex-chl-benz. - Hexachlorobenzene
**m - minor (<.005 cases per 70 years)
12
Chi.
PCB's
POM
Prop.
*** Most figures have been rounded to nearest whole number.
.1
16
Chloride
Polychlorinated biphenyls
Polycyclic organic matter
Propylene
BECAUSE OF UNCERTAINTY IN PROCEDURES, METHODS. ASSUMPTIONS AND DATA. THESE RISK NUMBER
SHOULD BE REGARDED AS ONLY ROUGH APPROXIMATIONS AND ARE BEST USED IN A RELATIVE SENSE.
ESTIMATES FOR INDIVIDUAL POLLUTANTS ARE HIGHLY UNCERTAIN AND SHOULD BE USED WITH
PARTICULAR CAUTION.
-------
SOUTHEAST CHICAGO STUDY AREA Figure 5.
Relative Distribution of Estimated Lifetime Cancer Cases
(TOTAL CASES APPROXIMATELY 86 OVER 70 YEARS)
87th St.
crt
Sibiey Blvd.
-------
3f
doors, lids, and offtakes were estimated to contribute 24 cases over 70 years
or about 85% of the steel mill contribution to area incidence. Coke oven
by-product recovery plants, which refine the gases baked out of coal by the
coke ovens, are estimated to contribute an additional 2 cases over 70 years.
Since this operation may be considered an adjunct to coke production, the
total risk estimated for coke production is 26 cases over 70 years, or about
92% of the steel mill contribution. The remaining 8% of the steel mill con-
tribution to incidence arises principally from arsenic, cadmium, and chromium
emissions from basic oxygen furnaces, electric arc furnaces, blast furnaces,
and sintering operations.
Figure 4 and Table 7 indicate other significant contributors to estimated
air pollution related cancer cases in the Southeast Chicago area. Also use-
ful here is Figure 6- showing a more detailed breakdown than Figure 4 of
specific source types to area cancer case estimates. After steel production,
the most significant contribution to risk is labeled "background pollutants."
which contribute 16 cases over 70 years or about 21% of the total. This
category includes air pollution which is not caused by current emissions,
but rather represent "background concentrations" from other causes. Specifi-
cally, this category includes formaldehyde, which results from atmospheric
photochemical reactions of other currently emitted organics, and carbon
tetrachloride. which results largely from atmospheric accumulation of previous
carbon tetrachloride emissions. As seen in Figure 6, photochemically formed
formaldehyde appears to be one of the most significant air pollution-related
causes of area cancer cases. Atmospheric accumulation of carbon tetrachloride
also appears significant, although less significant than other contributions
in Figure 6.
A third significant contribution to risk as shown in Figure 4 is industrial
operations other than steelmaking, which cause about 14 cases over 70 years
or about 18% of the total. As seen in Figure 6, this risk is predominantly
due to chrome plating operations. Degreasing and miscellaneous other manu-
facturing operations adc1 a fairly modest contribution to estimated cancer cases
relative to other causes of air pollution-related risks. A fourth significant
contributor to risk is from roadway vehicles such as cars and trucks traveling
on streets and highways, causing about 12 cases over 70 years, or about 16% of
the total. A fifth significant contributor to risk is identified on Figure
4 as consumer sources, which cause about 6 cases over 70 years, or about 8% of
the total. This category includes several activities engaged in by the general
public which result in emissions of presumed carcinogens.
Figure 7 provides more detailed information on the contribution of consumer-
oriented sources of air emissions to the estimated number of area cancer cases
across the study area. Home heating appears to be the most significant such
source type. Although some of this estimated risk is from combustion by-products
(polycyclic organic matter and formaldehyde) from gas furnaces, the bulk of
this contribution to risk 1s from wood combustion in fireplaces and wood stoves.
Although the actual quantity of wood burned in the study's source area is
small, a significant fraction of this wood is transformed during combustion
into polycyclic organic matter. This pollutant is sufficiently toxic, so that
wood combustion emerges as a relatively significant source category.
-------
Figure 6. Breakdown by Source Category
of Contributions to Estimated Cases
Consumer Sources (7.958) STPs (°
Roadway Veh (16 0«)
Waste Facil. (0.2*)
Bkgd. Carbon Tet, (58*)
Bkgd. Formaldehyde (14.
51 eel Mills (37.1*)
Other industry (1.3*)
CO
-•J
Chrome Platers (16.8*)
-------
Figure 7. Contributions to Estimated
Cases from Consumer—Oriented Sources
Miscellaneous (16
Gas Mdrket. (15.4SB)
Home Hedling (45-S5<)
CO
00
Cooling (22.2*)
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39
Figure 7 also shows contributions from other types of consumer-oriented source
categories. TTie activities aggregated as "miscellaneous activities" each are
estimated to contribute less than 0.3 cases over 70 years (about 4 cases in
1,000 years), and include, in order of estimated significance: sterilizing
operations at hospitals using ethylene oxide, chloroform from chlorinated
drinking water, formaldehyde in miscellaneous consumer products, dry cleaning,
methylene chloride in aerosol cans and paint stripping, various minor constituents
of house paint, and asbestos from demolition and renovation of asbestos-containing
structures. The total contribution of these "miscellaneous activities" is esti-
mated to be about 1 case over 70 years.
Figure provides more detailed information on contributions to estimated cancer
cases from subcategories of waste handling facilities. Although waste handling
facilities contribute only a small fraction of overall impacts, this information
is provided because few studies provide this information and because of general
interest in these source types. As seen in Figure 8, TSDFs are estimated to
contribute almost three quarters of the total impact of waste handling facilities
(about 0.11% out of the waste handling contribution of 0.15% of total estimated
cancer cases). Abandoned hazardous waste sites and active municipal waste landfills
roughly split the remainder of waste facility impacts (each contributing about
0.02% of total estimated cancer cases).
Collectively, the impacts of steel mills, other industrial operations, back-
ground pollutants, consumer sources, and roadway vehicles contribute all but
0.3% of the total estimated number of cancer cases attributable to air pollution.
Using more narrowly drawn source categories, the collective impact of steel mills,
chrome plating, background formaldehyde, background carbon tetrachloride, and
roadway vehicles contribute over 90% of the total estimated air pollution
related cancer cases. (Other industrial sources and consumer sources contribute
the remainder of the 99.7% referenced above ("all but 0.3%").)
Figures 4 and 6 and Table 7 also suggest what source categories make relatively
minor contributions to estimated risks. In particular, both wastewater treatment
plants and waste handling facilities (including both hazardous waste and municipal
solid waste facilities and including abandoned hazardous waste sites) are each
estimated to cause only about 0.1 air pollution-related cancer
cases per 70 years (about 2 cases per 1000 years). (Although Figure 4 suggests
that the contributions to total air pollution cancer cases from waste handling
and from wastewater treatment plants are respectively 0.2% versus 0.1%, this
apparent difference is largely the result of rounding. With an additional
significant figure, the respective contributions are 0.15% versus 0.14%.)
Figures 4 and 6 and Table 7 suggest a variety of additional statements on the
contribution of various air pollution source types to cancer incidence in the
Southeast Chicago area. One proposition supported by these data is that
while steelmaking 1s the most significant contributor to estimated lifetime
risk, several other specific source categories also make significant contributions.
These source categories include chrome platers, background pollutants, and
roadway vehicles, each estimated to contribute between about 10 to 20% of the
total incidence. The remaining 5% of risks are divided among a wide range of
additional source types.
Another finding is that while the most significant pollutant is coke oven
emissions, several other pollutants also make significant contributions to air
pollution-related cancer risks. This point is illustrated in Figure 9, showing
-------
Figure 8. Contributions of Various
Types of Solid Waste Handling
Abandoned Sites (15 695)
ivl W Landfills (10.65K)
TSDFs (73.8*)
-------
Figure 9. Contribulions to Estimated
Cases by Pollutant
Orher Poll. (5 5SK) B^nznne (55*)
POM (B.4H)
Gas, Vapors (4.4SK)
Formaldehyde (17.05B)
Carbon Tel. (5.8*.)
Butadiene (2.9%)
Chromium (19.1
Coke Oven Em. (31.3SK)
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42
a pie chart of the contributions of various pollutants to total estimated number
of cases across the study area. This figure illustrates the fact that the
combined contribution of the five most significant pollutants yields only 82%
of the total estimated number of cancer cases. The contributions from the 10
most significant pollutants must be included to explain 97% of the cases.
A second means of examining cancer impacts of air pollution in Southeast Chicago
is to evaluate individual risks. Figure 10 presents a map of the individual
risks estimated in the Southeast Chicago area. This same information is
presented in a different format in Figure 11. These figures include background
pollutants, which are assumed to be uniform throughout the area, representing
a risk of 4xlO~5 in each grid square.
The highest estimated lifetime risk in the study area is about 5xlO~3 (5 chances
in 1,000), at the square centered near 114th Street and Torrence Avenue.
However, this grid is indicated by Census Bureau data to have no residents.
(If this grid in fact has any residents, these residents would be included in
exposure estimates for a neighboring grid. Note that this study does not address
exposure in nonresidential locations such as workplaces in this or other grids.)
The grid with the greatest estimated number of cancer cases attributed to air
pollution is a grid where individual risks are somewhat lower but where sub-
stantial population lives. Specifically, the grid square with the highest
estimated number of cancer cases is centered on the UTM coordinates at 4616 N/
455 E (ranging from about 107th Street to 112th Street and from about Burley
Avenue to Avenue J). Risk in this grid square is estimated to be about 9xlO-4
(9 in 10,000). The incidence at this site is estimated to be almost 4 cases
(about 3.8) over 70 years. The estimated average risk across the entire study
area is about 2.0xlO'4 (about 2 chances in 10,000).
Table 8 summarizes the various contributions to risk at the grid with the
highest incidence location, showing the components of the risks in terms of
source type and pollutant. Clearly steel sources, particularly coke ovens,
are the dominant source of estimated risk at this location. Figure 12 shows
contribution to risk at the peak incidence locations in another format.
Figures 10 and 11 also suggest findings about the spatial distribution of risk
in the Southeast Chicago area. Although the spatial resolution in this study
is insufficient for a detailed examination of spatial variations, these figures
do suggest that the highest risks are generally in the predominant downwind
direction (northeast) of the steel mills near Lake Calumet, and that risks in
the southern and western parts of the area are more uniform and relatively lower.
Figures 10 and 11 may also be compared with Figure 5. Figure 5 shows estimated
cancer cases, which reflect population exposed as well as individual risks.
Figure 5 shows the most cases in the northern and northeastern parts of the
study area.
The risk estimates presented in this report should be regarded as only rough
approximations, and should be considered in the context of the substantial
uncertainties that are inherent in state-of-the-art of risk assessment techniques.
The discussions of emissions estimates, dispersion analysis, and estimation of
unit risk factors have each identified various uncertainties. A useful illus-
tration of these unavoidable uncertainties is the improvements that have become
-------
5xlO-3 -
4xlO-3 -
3xlO-3 -
2xlO-3
IxlO-3 -
u
*^e
^
Figure 10, Map of Estimated Lifetime Cancer Risks from Air Pollutants
in Southeast Chicago Area (in probability units)
- max.
St.
Sibley Blvd.
VN
-------
SOUTHEAST CHICAGO STUDY AREA Figure n
Estimated Lifetime Cancer Risks from Air Pollutants
87th St.
Sibtey Blvd.
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45
Table 8. Estimated Contributions to Lifetime Cancer Risk at the
Grid with the Highest Estimated Number of Cancer Cases
Other
Steel Industrial
rnmnnund* Mi 11 s Sources
L,uni uuunu • i < » < **
Acrylamide
Acrylonitrile
Arsenic 2E-5
Asbestos
Benzene 6E-5
Be ryl 1 i urn
Butadiene m
Cadmium 1E-5
Carbon Tet.
Chloroform
Chromium 4E-7
Coke Oven Em. 7E-4
Dioxin
Epichlorohydrin
Eth. Di bromide
Eth. Dichloride
Eth. Oxide
Formaldehyde m
Gas. Vapors
Hex-chl-benz
Methyl Chi.
Methyl ene Chi .
Perch! oroeth.
PCB's
POM
Prop Oxide
Styrene
Trichloroeth.
Vinyl Chi.
Vinyl idene Chi .
m**
m
6E-7
3E-7
m
m
4E-8
m
m
4E-5
5E-7
m
1E-7
5E-7
m
m
m
m
2E-;
2E-7
m
m
m
m
8E-7
m
Consumer
Sources
9E-8
2E-7
4E-7
3E-6
2E-7
8E-7
2E-6
3E-8
3E-7
2E-7
5E-6
Sewage
Mobile Waste Treatment
Sources Handling Plants
m
2E-7 m
4E-6 2E-8 m
m
4E-6 1E-8
2E-8 m
2E-7
m m
m
1E-8 3E-8
m
9E-8
1E-8 m
2E-6 m
5E-6
9E-7 2E-7
m m
4E-8 m
m m
8E-6 2E-8
mm
HI
1E-7 m
7E-8
9E-8 m
Background
Pollutants Total
m
m
2E-5
3E-7
6E-5
m
4E-6
1E-5
1E-5 1E-5
4E-7
5E-5
7E-4
6E-7
m
9E-8
2E-7
7E-7
3E-5 4E-5
7E-6
1E-6
3E-8
5E-7
4E-7
m
3E-5
m
m
9E-7
6E-8
6E-8
TOTAL
*Abbreviations:
Carbon Tet.
Eth.
Gas.
Hex-chl-benz.
8E-4
5E-5
1E-5
Carbon tetrachloride
Ethylene
Gasoline
Hexachlorobenzene
2E-5
Chi.
PCB's
POM
Prop.
2E-6 2E-7 4E-5 9E-4
or 9xlO'4
Chloride
Polychlorinated biphenyls
Polycyclic organic matter
Propylene
fie A~C II I — UCII£ • "" nCAOWII IWlVfc/^'tfc^"*- - - _ r - ,,
**To emphasize the higher contributions to risk, three formats are used:
m - minor - designates risks below lxlO'8 (0.00000001)
exponential format used for risks above 1x10-8; for example 6E-5 = 6x10
.00006
BECAUSE OF UNCERTAINTY IN PROCEDURES, METHODS, ASSUMPTIONS AND DATA THESE RISK NUMBERS SHOULD
BE REGARDED AS ONLY ROUGH APPROXIMATIONS AND ARE BEST USED IN A RELATIVE SENSE -ESTIMATES FOR
INDIVIDUAL POLLUTANTS ARE HIGHLY UNCERTAIN AND SHOULD BE USED WITH PARTICULAR CAUTION.
-------
Figure 1 2. Contributions to Estimated
Risk at the Peak incidence Location
Consumer Sees (l
Roadway Veh. (2.6*)
VVcsie Facilities (02*)
Bkgd. Pollutcnts (4 5%) \
Other Industry (5 39B)
+ 4
STPs (0.02%)
CT>
Stee! Mills (86
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47
available even during the last six months. In estimating emissions, recent
information suggested that chrome plating facilities emit 25% more than pre-
viously thought, and information was recently discovered that permitted the
estimation of asbestos emissions from two types of sources. In unit risk factors,
recent revisions indicated a roughly two-fold increase in the PCB unit risk
factor, a nine-fold reduction in the methylene chloride unit risk factor, and
deletion of melamine from consideration as a carcinogen. It is reasonable to
presume that even the best estimates that can be developed today are prone to
have errors of these general magnitudes.
A further indication of the degree of uncertainty in this study can be obtained
by reviewing the comparison of modeled versus monitored concentrations. This
comparison suggests that some pollutants (particularly the metals) seem to be
reasonably accurately characterized, some pollutants are suggested to be
underestimated two- to four-fold, and a few pollutants appear to be understated
by as much as two or three orders of magnitude.
Unfortunately, the five pollutants contributing the most to estimated area
cancer cases are either not measured directly or are strongly affected by
background concentrations: coke oven emissions and polycyclic organic matter
can only be evaluated by comparing an arbitrary benzo(a)pyrene percentage of
these modeled pollutants against benzo(a)pyrene measurements; chromium can be
evaluated with respect to total chromium but not directly with respect to
hexavalent chromium; and formaldehyde and carbon tetrachloride have only a
small direct emissions (and model estimable) component. Indeed, the ten
pollutants for which a direct comparison between modeling and monitoring results
may be made (including two pollutants treated as noncarcinogens) contribute
about 9% of the total estimated cancer incidence. Any broader interpretation
of these comparisons requires an assumption that the same suggested degree of
reliability also applies to other pollutants for which no comparison of modeling
versus monitoring results is possible.
A more definitive assessment of the actual health effects attributable to air
pollution in the study area could only be obtained by an epidemiological
study. Unfortunately, epidemiological studies often produce inconclusive
results, due to a variety of complicating factors. In any case, an epidemi-
ological analysis was outside the scope of this study. Thus, it is only
possible to make qualitative statements about the uncertainties inherent in
the risk factors. For example, risk factors based on human data will
generally have less uncertainty than risk factors based on animal data.
A related issue is whether this study is likely to understate or overstate
actual risks. The comparison of modeling and monitoring data suggests that
this study may understate exposure for many pollutants. On the other hand, the
risk factors are designed to be more likely too high than too low, particularly
those risk factors designed as 95% upper confidence limits. Indeed, for some
pollutants the risk may even be zero, since some of the 30 pollutants in this
study may not actually be carcinogenic to humans at ambient air concentrations.
However, the net effect of these causes of understatement and overstatement of
risk is not clear.
An additional perspective on uncertainty is to review the relative significance
of those groups of pollutants which are more or less uncertain. A measure of
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48
uncertainty of the health data, at least a measure of the uncertainty that
specific pollutants are indeed carcinogenic, are the classifications of weight
of evidence of carcinogenicity. Thus, one means of addressing the uncertainty
with respect to health data is to sum the estimated number of cancer cases
estimated for each group of pollutants (i.e. known human carcinogens, probable
human carcinogens, and possible human carcinogens). A means of addressing the
uncertainty in exposure estimates can be derived from the comparison of modeling
versus monitoring concentration estimates. Using the results in Table 7, the 6
known human carcinogens contribute almost 53? of the estimated cases, the 22
probable human carcinogens contribute 47% of the estimated cases, and the 2
possible human carcinogens contribute less than 0.02% of the estimated cases.
Thus the pollutants with the least uncertainty (at least with respect to the
fact of being carcinogenic) are the most significant, and the pollutants with
the most uncertainty (at least with respect to being carcinogenic) appear to
be relatively insignificant pollutants.
The discussion comparing modeled and monitored concentrations suggested that
some source types may be more reliably assessed than other source types, which
would suggest a shift in the relative significance of different source types.
A priori, the more studied, more traditional source types would be expected to
be reasonably well characterized, whereas impacts of the less studied, less
traditional source types would be expected to be underestimated. The comparison
of modeled versus monitored results tends to support this hypothesis. The
earlier discussion noted relatively good comparisons for metals (most emitted
by steel mills), benzene (most emitted by steel mills and mobile sources), and
degreasing solvents (emitted by "other industry"). However, no firm conclusions
on this issue can be reached, because it is not clear which source types might
be affected by remedies for poor modeling versus monitoring comparisons, and
because the most significant pollutants do not have directly comparable modeling
and monitoring results.
The modeling-monitoring comparison suggests that the pollutants which appear
to be most underestimated also appear relatively insignificant. For example,
even if concentrations of PCBs and chloroform were arbitrarily assumed to be
100 times higher, PCBs would still only contribute 0.08% of total air toxics-
related cancer cases and chloroform would be increased to about 30% of these
cases, producing only a modest increase in the total estimate of air toxics
related cases per year. Combining this review with the review of carcinogeni-
city, it appears that while some pollutants and some source types may be signi-
ficantly mischaracterized, the most significant pollutants and source types in
this study may have relatively more reliable risk estimates than the less
significant pollutants and source types in this study.
A further indication of uncertainties and potential biases may be gleaned from
comparing this study's results versus a study by USEPA's Office of Mobile
Sources (QMS). As described previously, the QMS study used an exposure model
which considered the various exposure environments encountered by typical mobile
individuals and which relies ultimately en monitoring data, in contrast with
the use of fixed exposure points and reliance principally on dispersion modeling
in this study. The QMS study generally showed two to three times higher exposure
than this study. In addition to implying the level of uncertainty (and potential
underestimation) of this study's exposure estimates, this comparison also
suggests that exposure as assessed at a fixed point is reasonably comparable to
exposure as assessed for mobile individuals.
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49
Conclusions
The risk estimates presented in this report should be regarded as only rough
approximations of total cancer cases and individual lifetime risks, and are
best used in a relative sense. Estimates for individual pollutants are highly
uncertain and should be used with particular caution.More detailed discus-
sions of the uncertainties are included in the respective individual sections
on Emission Estimation, Estimation of Concentrations by Atmospheric Dispersion
Modeling, Evaluation of Cancer Risk Factors and Incidence and Risk Estimates.
This project found atmospheric emissions of 30 pollutants in the study area
which USEPA considers carcinogenic. Some of these pollutants have been shown
to be carcinogenic based on human exposure data, and others have been impli-
cated by animal studies.
This study suggests that about 77 cases of cancer over 70 years or about 1
cancer case per year in this study area may be attributable to air pollution.
Further, a peak lifetime risk of about 5x10'3 (or about 5 chances in 1,000) is
estimated in the study area. However, Census Bureau information does not
indicate any residents in this area. The square kilometer with the highest
estimated number of cancer cases has an estimated lifetime risk of about
9xlO-4 (9 in 10,000). There is some geographic variability in the
risks across the study area. In general, risks are greatest in the northeast
part of the area and are relatively lower in the southern and western part of
the area. An average lifetime risk across the area is about 2.0x10-^
(2 in 10,000).
In evaluating the sources of airborne risk in this area, steel mills contribute
to about 29 cancer cases over a 70 year lifetime (37% of the total). Emissions
from other industrial facilities, primarily chrome platers, are estimated to
cause approximately 14 cancer cases over a 70 year lifetime (approximately
182 of the total), and roadway vehicles are estimated to cause about 12 cases
over 70 years (about 16% of the total). Consumer-oriented area sources (e.g.,
home heating and gasoline marketing) contribute approximately 6 cancer cases
over 70 years (about 8% of the total). Furthermore, the background pollutant
impacts from formaldehyde and carbon tetrachloride, which contribute an estimated
16 cases of cancer over 70 years (almost the entire remaining 21% of the
total incidence) may also be attributed principally to industrial facilities,
consumer-oriented sources, and roadway vehicle emissions. In total, these
source categories contribute about 99.7% of the risk.
Correspondingly, there are some source categories which appear to contribute
relatively little to airborne risk in this area. This study suggests that the
sum of air toxic based risks attributable to the handling of both hazardous
and municipal wastes equals less than 0.2% of the total air pollution related
cancer risk 1n the area, or about 0.1 cases over 70 years (1 case in 1,000
years). Thus, these sources are estimated to pose considerably less air
toxic risks than other source types evaluated in this study.
Another relatively minor source type is air emissions from wastewater treatment
plants, which were also estimated to lead to about 0.1 cancer cases over 70 years
(about 1 case in 1,000 years), or about 0.1% of the total area's air pollution-
related incidence. The risks from the two such plants in the study are almost
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50
equal to the sum of the impacts from all the facilities with from handling
hazardous and municipal solid wastes, but are still much smaller than several
other source types evaluated in this study.
It is useful to apportion the estimated total number of cancer cases according
to the weight of evidence that the pollutants are carcinogenic. According to
USEPA's review of the weight of evidence of carcinogenicity, the 30 pollutants
for which risks were estimated in this study include 6 "known human carcinogens",
22 "probable human carcinogens, and 2 "possible human carcinogens". Of the
estimated 77 cancer cases per 70 years, about 58? are attributable to "known
human carcinogens," almost 42% are attributable to "probable human carcinogens,"
and about 0.03% are attributable to "possible human carcinogens."
To put the air toxics risk in perspective, it would be desirable to discuss
cancer risks due to other forms of environmental pollution. However, this
study focused on air pollution risks and did not evaluate risks from other
forms of exposure to environmental contamination. Other exposure routes
include exposure through drinking water, skin contact, eating fish or swimming
in lakes (e.g., Wolf Lake) which may contain contaminants, and exposure to
indoor air contaminants including radon. Also complicating any review of the
relative significance of air pollution is the potential for other air pollutants
which cannot currently be quantitatively evaluated but nevertheless cause signi-
ficant risks. Air pollution appears to be an important cause of environmental
pollution-related cancer cases in this area, but a comparison of airborne risks
to risks from other environmental exposures is outside the scope of this study.
Although specific estimates of individual risks and area-wide cancer cases have
been given in this report, the uncertainties underlying these estimates dictate
that these estimates be used cautiously. The specific types of uncertainty
inherent in these estimates have been described in various sections of the
report, and include various uncertainties in estimating emissions, uncertainty
in quantifying atmospheric dispersion, and various uncertainties in developing
unit risk factors from available human or animal data. Also, evidence in this
study suggests that concentrations may generally be understated, whereas unit
risk factors are designed to be more likely to overstate than to understate
risks. Thus, this study may either overstate or understate risks, and in either
case may provide estimates which differ substantially from true risks.
This study was designed as a screening study of a broad range of source types
and air pollutants, rather than as a more intensive study of any single source
type or pollutant. As such, more reliable results could be obtained by further
investigation of several elements of the study. Given the evolving nature of
knowledge for the pollutants in this study, a new review of the literature
would likely suggest several modifications in the emissions estimates used in
the study.
The evolutionary nature of these types of study is illustrated by the numerous
improvements that became available during the course of this study. In parti-
cular, the emissions inventory update documents several source categories for
which improvements became available between mid-1987 and the end of 1988.
Similar improvements were developed during the same period for several unit
risk factors. It is likely that similar improvements for various source cate-
gories and pollutants will be discovered in the future.
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51
Other relevant studies are becoming available which will complement this study.
As mandated by the Illinois General Assembly, the Illinois Cancer Council
will be conducting an epidemiological investigation of leukemias and lymphomas.
As discussed previously, epidemiological results cannot be expected to be
directly comparable to risk assessment results. In brief, differences arise
because: (1) epidemiological studies are commonly too insensitive to identify
overall health risks from air pollution, and are not even designed o assess
source- or pollutant-specific impacts; (2) epidemiological studies are
retrospective, whereas risk assessments are prospective; and (3) the exposure
conditions are different (epidemiological studies are complicated by population
mobility, indoor/outdoor and workplace/residential exposures, whereas this risk
assessment assesses the impact outdoor exposure at fixed locations). Nevertheless,
a qualitative comparison of the two studies will enhance the value of both studies.
A second relevant study nearing completion is an assessment of noncancer impacts
of air pollution in Cook County. THis study was conducted by USEPA's Office of
Air Quality Planning and Standards to assess the extent to which air pollutant
concentrations may be high enough to cause health impacts such as liver or
heart damage.
In addressing the risks identified in this study, the USEPA is subject to some
important limitations in the legal authority provided in the Clean Air Act and
other legislation for air toxics regulations. The development of regulations
under these statutes requires intensive investigations. Also, USEPA's policy
is to address source categories which are significant from a national perspec-
tive, not to address individual sources which are significant in a given local
area. Thus, State and local air pollution agencies in the area have an impor-
tant role in identifying and adopting regulations to address the risks estimated
in this study. At the same time, the State and local air pollution agencies
are also subject to limitations in statutory authority for addressing these
issues.
Despite its limitations on authority, USEPA is developing regulations at a
national level for numerous categories. For coke ovens, USEPA has proposed
regulations to require more control of leaks from doors, lids, offtakes, and
from charging. For coke oven by-product recovery plants, USEPA has proposed
regulations to require numerous measures to reduce benzene emissions. For
chrome platers, the Agency is nearing completion of a background information
document which is necessary to provide technical support for regulating these
sources. For gasoline vapor emissions from automobile refueling, the Agency
has proposed two alternatives (controlling these vapors either with equipment
built into automobiles or with equipment installed at gasoline stations) and
is working to resolve technical concerns about these alternatives. For facili-
ties that treat, store, and dispose of hazardous waste, an assortment of
regulations are being developed for proposal. For chromium emissions from
comfort cooling towers, the Agency has proposed banning the use of chromium in
these units and, thereby, eliminating these emissions.
An important relevant type of State activity is the adoption of regulations
designed to reduce emissions of volatile organic pollutants and particulate
matter and thus reduce air toxics emissions. One example of such a regulation
is the regulation for the coke by-product recovery plants adopted by Indiana,
which was designed to reduce volatile organic compound emissions for ozone
control, but which will significantly reduce benzene emissions. A second
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52
example is motor vehicle' inspection and maintenance programs adopted by both
Illinois and Indiana which again was designed to reduce volatile organic
compound emissions in general, but which will also simultaneously reduce emis-
sions of several individual organic species. Reductions in organic emissions
also have the effect of reducing the risks from formaldehyde which is photo-
chemical^ created in the atmosphere. Note that for both of these examples,
the required emission reductions have not been reflected in the emissions and
risk estimates in this study because these programs had not been effectively
started up in the year selected for this study. A third example is enforcement
of existing regulations controlling volatile organic compound and particulate
matter emissions. Illustrative of this activity are enforcement negotiations
which are leading to improved control of one of the coke batteries in the
area. Further reductions in emissions of volatile organic compounds and
particulate matter are mandated both for Southeast Chicago and for Northwest
Indiana, which can be expected to further reduce emissions and risks from the
pollutants in this study.
Other State programs more directly address air toxics issues. Illinois currently
considers air toxics in reviewing companies' air pollution permit applications,
and both Illinois and Indiana are in the process of developing more formalized
air toxics programs. USEPA believes this report documents sufficient risk to
warrant investigation of possible means for its reduction. It is hoped that
this study will lead to informed discussions on how to design USEPA's and the
States' control programs to achieve effective reductions to cancer risks in the
Southeast Chicago area.
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53
References
Emissions Estimation
Many references were used in developing emissions estimates. The
inventory is described in the following two reports, which provide
detailed data on references:
J. Summerhays, H. Croke, "Air Toxics Emission Inventory for the Southeast
Chicago Area," Region V, U.S. Environmental Protection Agency, July 1987.
J. Summerhays, "Update to an Air Toxics Emission Inventory for the
Southeast Chicago Area," Region V, U.S. Environmental Protection Agency,
January 1989.
Dispersion Modeling
Guideline on Air Quality Models (Revised), EPA-450/2-78-027R, Office of
Air Quality Planning and Standards, U.S. Environmental Protection Agency,
1986.
Industrial Source Complex (ISC) Dispersion Model User's Guide - Second
Edition (Revised), EPA-450/4-88-002. Office of Air Quality Planning
and Standards, U.S. Environmental Protection Agency, December 1987.
J. Irwin, T. Chico, J. Catalano, COM 2.0 - Climatological Dispersion
Model User's Guide, EPA-600/8-85-029, Atmospheric Sciences Research
Laboratory, U.S. Environmental Protection Agency, 1985.
Monitoring
1988 Urban Air Toxics Monitoring Program. Radian Corp., January 1989.
Toxic Air Monitoring System Status Report. Office of Air Quality Planning
and Standards, U.S. Environmental Protection Agency, February 1988.
P. Aronian, P. Scheff, R. Wadden, "Winter Time Source-Reconciliation
of Ambient Organics," Illinois Institute of Technology/University
of Illinois at Chicago, Paper presented at Annual Meeting of Air
Pollution Control Association, June 1988.
C. Sweet, D. Gatz, Atmosphere Research and Monitoring Study of Hazardous
Substances: Third Annual Report, Hazardous Waste Research and Information
Center, Illinois Department of Energy and Natural Resources, November 1987,
An Interim Report on the Results of PCS Sampling in the Lake Calumet
Area of Southeast Chicago, Division of Air Pollution Control, Illinois
Environmental Protection Agency, May 1987.
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54
Unit Risk Factor Data
Each pollutant in this study has a body of literature that was considered
in the development of the unit risk factor. However, Region V. in con-
ducting this study, did not itself develop any unit risk factor and
did not conduct any associated literature review. Readers interested
in the literature relevant to unit risk factors for particular
pollutants are advised to consult the office identified in Table 6
as the source of the factor.
General References
E- Haemisegger, A. Jones. B. Steigerwald. V. Thomson. The Air Toxics
Problem in the United States: An Analysis of Cancer Risks for Selected
Pollutants. Office of Air and Radiation/Office of Policy. Planning and
Evaluation, U.S. Environmental Protection Agency, May 1985.
The Risk Assessments Guidelines of 1986, U.S. Environroenta1 Protection
Agency, originally published in 51 Federal Register 33992-34052,
September 24, 1986, and reprinted as EPA Report #600/8-87-045 in
August 1987.
J.J. Wind, T. Lahre, PIPQUIC User's Guide, Version 4.0. American
Management Systems, Inc. and Office of Air Quality Planning and
Standards, September 1088.
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