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

-------
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

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                                      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%.

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                                      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

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                                       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

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                                        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

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                                       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-

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                                       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.

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Figure 2.   Map of Estimated Coke Oven Pollutant Concentrations
                        2
                (in ug/m )
                                                                          max.
                                                                           87th St.
                                                                              Sibley Blvd.

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                            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

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                       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

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                                       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

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                                       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

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                     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

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                                       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.

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                                       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-

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                                       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.

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                      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

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                                           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.

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                                       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

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               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.

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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.

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                                       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

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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.

-------
                                                  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.

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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

-------
                                     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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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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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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