Toxics RELEASE INVENTORY
RELATIVE RISK-BASED
ENVIRONMENTAL INDICATORS METHODOLOGY
Nicolaas W. Bouwes, Ph.D.
Steven M. Hassur, Ph.D.
Economics, Exposure and Technology Division
Office of Pollution Prevention and Toxics
U.S. Environmental Protection Agency
June 1997
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TRI Relative Risk-Based Environmental Indicators Methodology
ERRATA
The sorted compilation of toxicity weights for scored TRI chemicals found in Appendix C,
Table C-l has several omissions and errors. Since the toxicity weights for various TRI chemicals are
undergoing further review, and modifications of the scores and the addition of new chemicals are
likely, the reader should consult the most recent listing of the toxicity weights used in the TRI
Environmental Indicators. Please contact the authors to obtain the most recently published listing.
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Contractor Support:
Abt Associates, Inc.
4800 Montgomery Lane
Bethesda, MD 20814
For further information or inquiries, please contact:
Nicolaas W. Bouwes, Ph.D.
(202) 260-1622
bouwes.nick@epamail.epa.gov
or
Steven M. Hassur, Ph.D.
(202) 260-1735
hassur.steven@epamail.epa.gov
Economics, Exposure and Technology Division (7406)
Office of Pollution Prevention and Toxics
U.S. Environmental Protection Agency
401 M St., SW
Washington, D.C. 20460
in
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ACKNOWLEDGMENTS
This report is one of several products of the TRI Relative Risk-Based Environmental Indicators
Project. This project was initiated in 1991 and is presently being implemented within the Office of Pollution
Prevention and Toxics (OPPT). We feel that this unique and powerful analytical tool has the potential to make
a significant contribution to environmental improvement. This is very gratifying to us as both scientists and
environmentalists. The project has had the good fortune to benefit from the contributions of many highly
qualified individuals. In particular, Susan Keane and Brad Firlie of Abt Associates, Incorporated who have
provided superior and creative contractor support to the project throughout its entire period of development;
and Loren Hall of the Environmental Assistance Division of OPPT, who has provided invaluable insights and
direction to the proj ect. Also, we wish to express our thanks to the individuals who served on the Indicators
Workgroup that developed the early framework of the methodology. The management team of the Economics,
Exposure and Technology Division (EETD) and OPPT are also to be commended for their full support and
conviction regarding the importance of this project: Bob Lee, Chief of the Economic and Policy Analysis
Branch, has been actively involved in project development and had the foresight to appreciate the potential
economic applications of the Indicators; Roger Garrett, former Chief of the Industrial Chemistry Branch (ICB)
directly assisted us in formulating our first approach while Russ Farris, Section Chief, and Paul Anastas,
Chief of ICB, have provided valuable advice; and Mary Ellen Weber, Director, always found us the support
to maintain this project's momentum and focus. Finally, we wish to recognize Michael Shapiro, Director of
the Office of Solid Waste, who as past Director of EETD had the intuition to conceive the basic premise of a
national set of indicators reflecting risks associated with TRI emissions. The proj ect management team later
developed this concept into the multi-media, relative risk-based approach described here.
Work Group Members
Nicolaas Bouwes, Chair
Steven Hassur
Loren Hall
Nancy Beach
David Brooks
Daniel Bushman
Karen Hammerstrom
Sondra Hollister
John Leitzke
Patrick Miller
Samuel Sasnett
Nestor Tirado
Sylvon Vonderpool
Andrew Wheeler
Thanks to these individuals for providing
exposure-related support:
Bob Boethling
David Lynch
Project Managers: Nick Bouwes and Steve Hassur
Abt Associates Project Staff
Susan Egan Keane, Project Manager
Brad Firlie, Deputy Project Manager
Lisa Akeson
Amy Benson
Kathy Cunningham
Jonathan Kleinman
Michael Miiller
Alexandra Varlay
Carol Wagett
Richard Walkling
Richard Wells
Michael Conti (technical reviewer)
IV
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TABLE OF CONTENTS
ACKNOWLEDGMENTS
EXECUTIVE SUMMARY ES-1
Introduction ES-1
How Indicator Toxicity Weightings Differ from EPCRA Section 313 Statutory
Criteria ES-2
Emergency Planning and Community Right-to-Know Act Section 313 Statutory
Criteria ES-3
Relative Toxicity Weighting of Chemicals in the TRI Relative Risk-Based Chronic
Human Health Indicator ES-4
General Description of the TRI Relative Risk-based Environmental Indicators ES-4
Methods for Calculating Toxicity Weights ES-6
Chronic Human Toxicity Weights ES-6
Chronic Ecological Toxicity Weights ES-7
Methods for Adjusting Releases and Transfers for Chronic Human Exposure
Potential ES-8
Quantitative Data Used in Evaluating Chronic Human Exposure Potential ES-8
Qualitative Data Used in Evaluating Chronic Human Exposure Potential ES-9
Methods to Adjust for Size of Population Exposed ES-9
Computing the TRI Relative Risk-based Environmental Indicators ES-10
Adjusting the Indicators for Changes in the TRI ES-11
Generating "Subindicators" ES-12
Current Implementation of the TRI Relative Risk-based Environmental
Indicators Method ES-12
Computer Program to Calculate the Indicators ES-13
Chemicals and Facilities Currently Included in the Indicators ES-13
Issues for Future Consideration and Conclusions ES-13
I. INTRODUCTION 1
How Indicator Toxicity Weightings Differ from EPCRA Section 313 Statutory
Criteria 3
Emergency Planning and Community Right-to-Know Act Section 313 Statutory
Criteria 4
Relative Toxicity Weighting of Chemicals in the TRI Relative Risk-Based Chronic
Human Health Indicator 5
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II. GENERAL DESCRIPTION OF THE TRI RELATIVE RISK-BASED
ENVIRONMENTAL INDICATORS 5
Approaches Used to Adjust Releases and Transfers in Other Existing Screening
Systems 5
General Approach Used for the TRI Relative Risk-based Environmental Indicators .... 6
III. METHODS FOR CALCULATING TOXICITY WEIGHTS 9
Chronic Toxicity Weights — Human 9
Qualitative Data Used in Chronic Human Toxicity Weighting 9
Quantitative Data Used in Chronic Human Toxicity Weighting 12
Types of Data 12
Sources of Data 12
General Format for Combining Weight-of-Evidence and Slope Factors to Assign
Weights 13
The Human Health Toxicity Weighting Schemes 17
Carcinogenic Effects 17
Noncancer Effects 19
Selecting the Final Chronic Human Health Toxicity Weight for a Chemical 19
Chronic Toxicity Weights — Ecological 20
Data Used in Chronic Aquatic Toxicity Weighting 21
The Aquatic Toxicity Weighting Matrices 21
IV. METHODS FOR ADJUSTING RELEASES AND TRANSFERS FOR CHRONIC
EXPOSURE POTENTIAL 23
Evaluating chronic Human Exposure Potential — General Description 23
Quantitative Data Used in Evaluating Chronic Human Exposure Potential 23
Qualitative Data Used in Evaluating Chronic Human Exposure Potential 26
Pathway-specific Methods to Evaluate Chronic Human Exposure Potential 27
GIS Basis Common to All Pathways 27
Stack and Fugitive Air Releases 27
Direct Surface Water Releases 33
On-site Land Releases 35
Releases to POTWs 41
Off-site Transfers 43
Evaluating Ecological Exposure Potential — General Strategy for Aquatic Systems ... 49
V. METHODS TO ADJUST FOR SIZE OF POPULATION EXPOSED 49
Estimating Population Size and Representing Rural Populations 49
VI. COMPUTING THE INDICATORS 50
Integrating Toxicity, Exposure, and Population Adjustments to Obtain Indicator
Elements 50
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Chronic Human Health Indicator 50
Chronic Ecological Indicator 51
Combining Elements to Obtain the Overall Indicators 52
Other Methods of Calculation Considered 53
Using the indicator approach to investigate environmental justice issues 53
Scaling the Indicators for Changes in TRI reporting 55
Generating "Subindicators" 56
VII. CURRENT IMPLEMENTATION OF THE INDICATORS METHOD 56
Computer Program to Calculate the Indicators 56
Chemicals and Facilities Currently Included in the Indicators 57
VIII. ISSUES FOR FUTURE CONSIDERATION AND CONCLUSIONS 57
IX. REFERENCES 59
Appendix A. Survey of Ranking and Scoring Systems
Appendix B. Options for a TRI Indicator Ranking/Scoring System
Appendix C. Available Toxicity Data for TRI Chemicals
Appendix D. Physicochemical Properties of Chemicals Included in the Indicators
Appendix E. Considerations for Including Underground Injection in the TRI Risk-Related
Chronic Human Health Indicator
Appendix F. Waste Volumes by Industry
Appendix G. Options for Indicator Computation and Normalization
Appendix H. Additional Exposure Scenarios
Appendix I. Description of the Computer Program
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EXECUTIVE SUMMARY
INTRODUCTION
In 1989, EPA outlined the goals for establishing strategic planning processes at the Agency.
Underlying this approach was the Agency' s desire to set priorities and direct resources to areas with
the greatest opportunity to achieve health and environmental risk reductions. As part of this initiative,
the Administrator set forth a plan to develop indicators to track changes in environmental health
impacts over time. Tracking these changes would allow the Agency to measure its progress in
implementing environmental protection and pollution prevention programs. In addition, comparing
the relative contribution of particular chemicals, industries and geographic regions through the
indicators would allow the Agency (and other users) to establish priorities for improving future
environmental health.
To efficiently track changes in human health and environmental impacts overtime, the Agency
would need to take advantage of existing data sources that reflect multimedia trends in environmental
contaminant releases. The Toxics Release Inventory (TRI) is arguably one of the Agency's most
relevant source of continuous data for developing indicators of change in environmental impacts over
time. The TRI is mandated by the Emergency Planning and Community Right-to-Know Act (EPCRA)
Title III Section 313 and requires that U.S. manufacturing facilities file annual reports documenting
multimedia environmental releases and off-site transfers for over 606 chemicals and chemical
categories which are of concern to the Agency. The Agency had recently added 286 new chemicals
and chemical categories to the Section 313 list of toxic chemicals, effective for the reporting year
1995 (that is, the first reports on these chemicals were due on July 1, 1996) (59 Federal Register
61432, November 30, 1994). These additions have significantly expanded the scope of coverage of
the TRI.
In response to the need for environmental indicators, and to take advantage of the rich data
source offered by the TRI, the Office of Pollution Prevention and Toxics (OPPT) convened a
workgroup that included members from several divisions within the Office, as well as individuals from
other Agency Offices. The purpose of the workgroup was to explore the development of an indicator
or indicators based on the TRI that could track changes in human health and environmental impacts
better than reports of pounds of releases alone, specifically an approach that would integrate toxicity,
exposure and population considerations into the evaluation of releases. This document presents the
results of that effort, a method for developing TRI Relative Risk-based Environmental Indicators
(referred to as "Indicators") plus additional developments and decisions that have transpired over
time. The Indicators may eventually consist of a set of four indicators to separately track: (1) chronic
human health, (2) acute human health, (3) chronic ecological and (4) acute ecological impacts. The
focus of this report is the development of indicators of chronic human health impacts and aquatic life
impacts; the development of corresponding acute effects indicators is not feasible now, since the data
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to support such indicators are not available.1 Furthermore, to the extent possible, the method is based
on currently available, already-reviewed EPA approaches, data sets and models, in order to minimize
duplication of effort and to maximize consistency with other Agency efforts to evaluate human health
and environmental impacts.
This report explains how the proposed Indicators are constructed, and includes discussions
of the conceptual methodology, data sources, and the computational approach. Since the Indicators
are based on risk-related scores, the report discusses the similarities and distinctions between the
relative risk-based approach of the Indicators method and conventional quantitative risk assessments.
It also describes a PC-based, stand-alone computer model developed to allow users to compute the
Chronic Human Health Indicator and to easily perform complex diagnostics of Indicator components,
as well as subindicator calculations.
In developing the Indicators, many approaches to assessing and ranking the potential impact
of chemicals were reviewed. Numerous techniques to score the relative significance of TRI chemicals
and facilities have been and continue to be developed, underscoring the widespread need for such
methods. One objective of this report is to explain the Indicators to a variety of agencies and groups
that may wish to use or adapt the Indicators or the methodologies to their own needs. A related
objective is to describe the benefits of the Indicators approach in terms of flexibility, power and utility
as an analytical and strategic policy planning tool.
How Indicator Toxicity Weightings Differ from EPCRA Section 313 Statutory Criteria
The TRI Relative Risk-Based Environmental Indicators utilize Toxics Release Inventory
(TRI) chemical reporting data. All of the TRI chemicals included in the Indicators are listed on the
TRI because they meet one or more statutory criteria regarding acute or chronic human toxicity, or
environmental toxicity. The goal of the Indicators is to use data reported to the Agency to investigate
the relative risk-based impacts of the releases and transfers of these chemicals on the general, non-
worker population.
To do this, the Indicators must differentiate the relative toxicity of listed chemicals and rank
them in a consistent manner. The ranking of each chemical reflects its toxicity only relative to other
chemicals which are included in the Indicators; not to some benchmark or absolute value.
The TRI Relative Risk-Based Chronic Human Health Indicator addresses only the single, most
sensitive chronic human health toxicity endpoint. Unlike the statutory criteria used for listing and
delisting chemicals, the Chronic Human Health Indicator does not address the absolute chronic
toxicity of chemicals on the TRI (e.g., multiple effects or the severity of effects); nor does it attempt
to reflect the statutory criteria for these chemicals.
To appropriately evaluate potential acute effects, one would need to know the distribution of releases over time (peak
release data), and these data are not currently reported through the TRI. However, possible future changes in reporting
requirements may allow for the development of separate acute indicators for human and ecological effects.
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It is important that the public not confuse the use of this Indicator as a screening-level tool
for investigating relative risk-based impacts related to the releases and transfers of TRI chemicals,
with the very different and separate activity of listing/delisting chemicals on the TRI using statutory
criteria. The toxicity weightings provided in the Indicator method cannot be used as a scoring system
for evaluating listing/delisting decisions.
Emergency Planning and Community Right-to-Know Act Section 313 Statutory Criteria
The Emergency Planning and Community Right-to-Know Act of 1986 (EPCRA) section
313(d)(2) sets out criteria for adding chemicals to the list of chemicals subject to reporting under
EPCRA section 313(a). For a chemical (or category of chemicals) to be added to the EPCRA section
313(c) list of toxic chemicals, the Administrator must judge whether there is sufficient evidence to
establish any one of the following:
Acute Human Toxicity §313(d)(2)(A) - The chemical is known to cause or can reasonably
be anticipated to cause significant adverse acute human health effects at concentration levels that are
reasonably likely to exist beyond facility site boundaries as a result of continuous, or frequently
recurring, releases.
Chronic Human Toxicity §313(d)(2)(B) - The chemical is known to cause or can reasonably
be anticipated to cause in humans—
(i) cancer or teratogenic effects, or
(ii) serious or irreversible—
(I) reproductive dysfunctions,
(II) neurological disorders,
(III) heritable genetic mutations, or
(IV) other chronic health effects.
Environmental Toxicity §313(d)(2)(C) - The chemical is known to cause or can reasonably
be anticipated to cause, because of—
(i) its toxicity,
(ii) its toxicity and persistence in the environment, or
(iii) its toxicity and tendency to bioaccumulate in the environment, significant adverse effect
on the environment of sufficient seriousness, in the judgement of the Administrator, to
warrant reporting under this section.
To remove a chemical from the section 313(c) list, the Administrator must determine that
there is not sufficient evidence to establish any of the criteria described above as required by EPCRA
section 313(d)(3).
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The EPA examines all of the studies available for a chemical to decide if the chemical is
capable of causing any of the adverse health effects or environmental toxicity in the criteria. Agency
guidelines describe when a study shows such effects as cancer (EPA, 1986a), developmental toxicity
(teratogenic effects) (EPA, 199 Ib), or heritable genetic mutations (EPA, 1986b). The review makes
a qualitative judgment regarding the potential of each chemical to meet at least one of the criteria and
the chemical is added to the list if this judgment is positive. If a chemical is on the list and it is not
possible to make a positive judgment regarding any of the criteria, then the chemical can be removed.
There is no correlation between the toxicity criteria and methodology used to make listing decisions
under EPCRA section 313 and the methodology used to rank chemicals for the Indicators.
Relative Toxicity Weighting of Chemicals in the TRl Relative Risk-Based Chronic Human Health
Indicator
In order to help the Agency make decisions, comparisons can be made among chemicals once
they are listed under EPCRA section 313. The TRI Chronic Human Health Indicator is based on
aspects of the adverse health effects (cancer and noncancer), as well as on exposure and population
factors, to permit the chemicals to be ranked relative to one another. These aspects are available in
public Agency-generated databases. Uncertainty reflecting the quality and adequacy of the data is
incorporated into a toxicity weighting each chemical receives. The approach is intended to
differentiate the relative toxicity of these chemicals in a uniform manner, provide a clear and
reproducible scoring system based upon easily accessible and publicly available information, and
utilize EPA consensus opinion to the greatest extent possible.
A complete discussion of the methods used in deriving the toxicity weightings for the
Indicator, as well as the chemical-specific data summaries and scores, is provided in TRI Relative
Risk-based Environmental Indicators Project: Toxicity Weighting Summary Document (EPA, 1997).
GENERAL DESCRIPTION OF THE TRI RELATIVE RISK-BASED ENVIRONMENTAL INDICATORS
This report describes the method for constructing the TRI Chronic Human Health Indicator
and a draft method for the TRI Chronic Ecological Indicator. For both, the objective is to calculate
a unitless value that reflects the overall risk-related impacts of releases and transfers of all included
TRI chemicals from all reporting facilities to each environmental medium for a given year or years.
To construct Indicators that are related to risk, the reported quantity of TRI releases and
transfers must be adjusted in a manner that relates to the risks associated with each media-specific
release or transfer of each chemical. The risk potentially posed by a chemical release depends on the
inherent toxicity of the chemical, the environmental fate and transport of the chemical in the medium
to which it is released, the degree of contact between the contaminated medium and the human or
ecological receptors, and the size of exposed population. Differences in these factors influence the
relative contribution each release makes to each Indicator. Transfers to off-site locations such as
sewage treatment plants (POTWs) require an additional estimate of the impact of treatment
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technologies on the magnitude of releases. Such transfers are modeled based upon the exposure and
population parameters associated with the off-site location.
In order to incorporate these factors into the Indicators, four main components are used to
compute each Indicator. These are:
D the quantity of chemicals released or transferred,
D adjustments for chemical-specific toxicity,
D adjustments for pathway-specific exposure potential, and
D an adjustment to the Chronic Human Health Indicator to reflect size of the potentially
exposed population.2'3
The TRI Chronic Human Health Indicator uses these components to perform a separate
assessment for each unique combination of a chemical, facility, and release or transfer medium. Each
of these releases or transfers results in a calculated Indicator "Element," a unitless value proportional
to the potential risk-based impact of each media-specific release or transfer. The value for the TRI
Chronic Human Health Indicator is simply the sum of all the applicable Indicator Elements. Similarly,
for the TRI Chronic Ecological Indicator, a separate assessment is made for each unique chemical-
facility combination affecting the water medium, yielding the Ecological Indicator elements. The
overall TRI Chronic Ecological Indicator is the sum of these elements.
The Indicators are calculated for each year in the TRI data set, beginning with 1988. These
values can be compared in a number of ways. For example, one of the early years of TRI reporting,
such as 1988, may be selected as the "base year" and later years' Indicator values are compared to
it. For the base year, the unitless score is scaled to 100,000; subsequent years' data are scaled by
the same factor to provide a relative comparison to the base year. This comparison allows assessment
of the changes in estimated risk-related impacts of TRI releases and transfers from year to year.
Importantly, the Indicators can be aggregated or disaggregated in various ways, offering a
vast number of possible combinations and views of the Indicators' subcomponents. Each facility-
chemical-media Indicator Element is retained by the computer program and thus can be evaluated by
users wishing to investigate the structure of the Indicators. OPPT, other EPA Offices, Regions,
States, or individuals could use these Indicator Elements to create their own queries that examine
relative impacts from alternative perspectives, such as chemicals, industries, or geographic regions
(among other parameters).
The method is focused on general populations: individuals, particularly highly exposed individuals, are not the focus of
the Chronic Human Health Indicator. Furthermore, worker exposures are not addressed. Additional Indicators based upon
highly exposed or sensitive subpopulations may be developed in the future.
The Ecological Indicator does not consider populations.
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The TRI Relative Risk-based Environmental Indicators method is not intended to be a
quantitative risk assessment and does not calculate risk estimates. The method follows the same
general paradigm often applied in quantitative assessments, but in a relative way. The Indicators are
by their nature only intended to reflect the direction and the general magnitude of the change in
releases over time, weighted by toxicity, exposure potential, and population factors that relate to
potential risk. As such, an Indicator value has only relative rather than absolute meaning; it can only
be used in comparisons to other Indicator values at different points in time, or in identifying the
relative size of contributing factors to the overall Indicator.
Though this document presents conceptual methods for both the TRI Chronic Human Health
Indicator and the TRI Chronic Ecological Indicator, the method is currently only being implemented
for the Chronic Human Health Indicator. Further method development, and further data collection
and analysis, will be required for the implementation of the TRI Chronic Ecological Indicator.
METHODS FOR CALCULATING TOXICITY WEIGHTS
Chronic Human Toxicity Weights
To weight a release based on potential toxicity, several factors could be considered, including
the number of effects that the chemical causes, the relative severity of the effects it causes, the
potency of the chemical for one or more of these effects, and the uncertainly associated with
characterizing individual effects. The method used by the Indicators is patterned after EPA's Hazard
Ranking System (HRS) (EPA, 1990b); this method focuses on the two latter factors. That is, toxicity
scores are assigned based on quantitative potency data, with the additional consideration of a
qualitative classification of the uncertainty (weight-of-evidence, or WOE) associated with data
pertaining to carcinogen!city.
For this project, quantitative data on the human health effects on the TRI chemicals are
compiled primarily from the Integrated Risk Information System (IRIS). Values available in IRIS
include upper-bound cancer slope factor estimates (q^) or inhalation unit risk values for carcinogenic
effects as well as Reference Doses (RfDs) or Reference Concentrations (RfCs) for noncancer effects.
Data contained in IRIS have been peer-reviewed and represent Agency consensus. If IRIS data are
not available, another source of toxicity data is the Health Effects Assessment Summary Tables
(HEAST). These tables are constructed for use in both the Superfund program and in the RCRA
program but do not represent Agency consensus. In cases where IRIS or HEAST do not have
toxicity values and WOE classifications, several other sources for data were used to assign weights
for use in the TRI Relative Risk-based Environmental Indicators method. Summaries of these other
data, and suggested toxicity scores based on them, were provided for selected chemicals to a group
of OPPT expert health scientists charged with reviewing toxicity data. After their review, this group
then approved or disapproved the suggested scores through a disposition process. A complete
discussion of the methods used in these evaluations, as well as the chemical-by-chemical data
summaries and score assignments, are provided in TRI Relative Risk-based Environmental Indicators
Project: Toxicity Weighting Summary Document (EPA, 1997).
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The quantitative data is used in conjunction with qualitative weight-of-evidence information
for carcinogenicity. The TRI Relative Risk-based Environmental Indicators method relies on
categorical definitions from the EPA Guidelines for Carcinogen Risk Assessment (EPA, 1986a,
currently being revised), which are related to the likelihood of a chemical's carcinogenicity in humans.
For noncancer effects, since weight of evidence is considered in the development of quantitative
toxicity values, the TRI Relative Risk-based Environmental Indicators method does not explicitly
consider it again in assigning toxicity weights.
To assign toxicity weights to chemicals with carcinogenic effects, the TRIRelative Risk-based
Environmental Indicators method uses a matrix to evaluate a chemical based on WOE and potency
simultaneously. The columns of the matrix qualitatively classify chemicals with potential carcinogenic
effects into two general WOE categories: known/probable (A/B) and possible (C). The rows of the
matrix describe the ranges of slope factors considered. The particular ranges of slope factor values
selected to represent each category correspond to the ranges presented in the HRS. The actual
numerical weights assigned to the matrix cells correspond to the scores assigned in the HRS to these
slope factor ranges. In certain cases, ranges presented in the matrix extend beyond those presented
in the HRS because the range of slope factors for the TRI chemicals is broader than that covered by
the HRS. The weights in the cells increase by an order of magnitude for each order of magnitude
increase in slope factor and increase in the WOE category.
For chemicals with noncancer effects, toxicity weights are assigned based on the RfD. The
actual values of the weights assigned are taken directly from the HRS, with the exception of the
highest weighting category. The addition of an extra category was necessary because the RfD values
for TRI chemicals extend beyond the ranges presented in the HRS.
The TRI Chronic Human Health Indicator weights a chemical based on the single most
sensitive adverse effect for a given exposure pathway (either oral or inhalation). Inhalation and oral
toxicity weights are developed separately. In general, if values are available for only one route, the
same toxicity weight is applied for both routes. In rare instances, toxicity studies are available to show
that a given chemical causes no health effects via one route; in these instances, the toxicity weight is
assigned only to the route that results in effects. If a chemical exhibits both carcinogenic and
noncarcinogenic effects, the higher of the associated cancer or noncancer weights is assigned as the
final weight for the chemical for the given pathway. The method does not consider differences in the
severity of the effects posed by the chemicals, nor does it adjust the weight if a chemical appears to
demonstrate more than one adverse effect.
Chronic Ecological Toxicity Weights
For ecological effects, the TRI Ecological Chronic Effects Indicator focuses on aquatic life
impacts only. Very little data are available for most chemicals on effects to terrestrial or avian
species; we assume the Chronic Human Health Indicator will provide some predictor of impacts on
these species.
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Aquatic toxicity weighting differs from human health toxicity weighting in two important
respects. First, WOE is not considered a factor in the weighting scheme, since direct evidence of
chemical toxicity is available from tests on aquatic species. Second, the aquatic toxicity weighting
scheme simultaneously considers toxicity and bioaccumulation potential. Both of these measures are
considered important when evaluating impacts on aquatic ecosystems.
Common numerical aquatic toxicity data include the Acute or Chronic Ambient Water Quality
Criteria (AWQC), developed by the Office of Water, which may serve as the basis for water quality
standards; the lethal concentration, 50 percent (LC50) - the chemical concentration in water at which
50 percent of test organisms die; and life-cycle or chronic No Observable Adverse Effect Levels
(NOAELs). The measures of bioaccumulation potential that can be used are the bioconcentration
factor (BCF) or bioaccumulation factor (B AF), the log of the octanol water partition coefficient (log
Kow), and the water solubility of the chemical.
The aquatic toxicity weight assigned to a chemical is a function of both its aquatic toxicity
values and bioaccumulation potential values. Separate weights are assigned based on each of these
measures; the chemical's final toxicity weight is the product of these individual weights.
METHODS FOR ADJUSTING RELEASES AND TRANSFERS FOR CHRONIC HUMAN EXPOSURE
POTENTIAL
Both qualitative and quantitative elements are considered when weighting chronic exposure
potential. Quantitatively, generic exposure models are used to derive a "surrogate" dose level to
characterize exposure potential on a exposure pathway-specific basis. Qualitatively, a level of
uncertainly associated with the surrogate measures of exposure potential is assigned to each exposure
pathway. The uncertainty estimates are then used to adjust the surrogate doses to derive the final
exposure potential adjustment factor.
Quantitative Data Used in Evaluating Chronic Human Exposure Potential
For the first step of deriving chronic exposure potential adjustment factors, quantitative
measures of exposure potential must be estimated. In this methodology, comparisons across media
can be made because a common quantitative exposure measure for each medium is derived, i.e., an
estimate of "surrogate dose" — a measure related to the amount of chemical contacted by an
individual per kilogram body weight per day.
To estimate the surrogate dose, a separate exposure evaluation is conducted for each media-
specific emissions pathway (e.g., stack air, direct water, off-site transfer to landfills, etc.). In this
methodology, the exposure evaluations combine data on media-specific and pathway-specific
volumes, physicochemical properties and, where available, site characteristics; with models to
determine an estimate of the ambient concentration of contaminant in the medium into which the
chemical is released or transferred. The ambient media concentrations are then combined with
standard human exposure assumptions to estimate the magnitude of the surrogate dose.
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It must be emphasized that while this methodology uses the EPA exposure assessment
paradigm to evaluate exposure potential, the results should not be construed as an actual numerical
estimate of dose resulting from TRI releases, since limited facility-specific data and the use of generic
models prevent the calculation of an actual dose. Instead, the purpose is to obtain an order of
magnitude estimate of surrogate dose resulting from release of TRI chemicals relative to the
surrogate dose resulting from other releases included in the Indicator., so that these releases can be
weighted appropriately in the Indicator.
The exposure evaluation methods used for each type of release or transfer are specific to that
type of release or transfer and depend on the models and data available to evaluate that emissions
pathway. In some cases, models will be combined with some site-specific data to estimate exposure;
in other cases, generic reasonable worst-case models may be used in the absence of any site-specific
data.
Qualitative Data Used in Evaluating Chronic Human Exposure Potential
Consideration of uncertainty in the exposure evaluation is necessary for making comparisons
across emissions pathways, since the exposure evaluation methods for various pathways differ
significantly in their level of refinement. For the purposes of calculating surrogate doses, the method
defines uncertainty categories. The categories are defined so that surrogate dose estimates in a lower
category are those more likely to overestimate exposure when compared to the next higher category
and can correspondingly be adjusted. In general, surrogate dose estimates are placed in lower
categories when they are developed using generic models and data that require many assumptions and
extrapolations. These assumptions and extrapolations tend to be conservative, so that more generic
modeling tends to yield overestimates of exposure. The initial surrogate dose estimate may be
reduced by a factor of 5 or 10, depending on the uncertainty category to which it is assigned.
METHODS TO ADJUST FOR SIZE OF POPULATION EXPOSED
The TRI Relative Risk-based Environmental Indicators method uses current 1990 U.S.
Census data together with pathway-specific methods to estimate the size of exposed populations.
The algorithms to determine the size of the population exposed to TRI releases vary substantially
depending on the medium to which the chemical is released or transferred. The document discusses
methods for estimating the size of the exposed population separately for each pathway.
For small populations, the method uses default numbers rather than absolute numbers to avoid
undervaluing potentially high impacts on rural populations. Using default numbers assures small
populations of a minimum weighting. In effect, this inclusion gives more weight per capita to small
populations. For the air pathway, the Chronic Human Health Indicator method adjusts exposed
populations below 1,000 persons to equal a value of 1,000. For the surface water pathway, the
minimum population size is 10, while for groundwater, the minimum population size is 1.
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Because of major difficulties in estimating sizes of the populations of ecological receptors,
the TRI Ecological Indicator does not include a population weight. In effect, this approach assumes
that all aquatic emissions occur in equally vulnerable locations. In actuality, the populations may
differ among areas; thus, the Indicators method may either underestimate or overestimate impacts in
a given area.
COMPUTING THE TRI RELATIVE RISK-BASED ENVIRONMENTAL INDICATORS
To calculate the Chronic Human Health Indicator, the toxicity, exposure potential and
population components are first combined multiplicatively to obtain a facility-chemical-medium
specific element:
Indicator Elementc fm =UToxicity Weightcm Surrogate Dosecfm -UExposedPopulationftn
where:
c = subscript for chemical c,
f = subscript for facility f, and
m = subscript for medium m.
The components are multiplied because each component (toxicity, exposure, and population)
contributes in a multiplicative way to the overall magnitude of the impact. The result of the
multiplication of the components is a facility-chemical-medium-specific "Indicator Element." It must
be reiterated that this unitless element is not a physically meaningful measure of quantitative risk
associated with the facility, but is a relative measure that is comparable to approximate measures for
other facilities (or chemicals, media, etc.) calculated using the same methods.
For the Chronic Ecological Indicator, the following general equation combines toxicity and
exposure potential components for each facility and for each chemical (only the water medium is
evaluated):
Indicator Elementcf =UToxicity Weightc Surrogate Dosecf
where:
c = subscript for chemical c, and
f = subscript for facility f.
As with the Chronic Human Health Indicator, the components are multiplied in this setting because
each component (toxicity and exposure) contributes multiplicatively to the overall magnitude of the
impact. The result of the multiplication of the components is a facility-chemical-water-specific
"Indicator Element." The Elements should not be interpreted as actual quantitative measures of risk.
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The method for calculating the Chronic Human Health Indicator and the Chronic Ecological
Indicator is the same. Each is calculated by combining the individual TRI chemical-facility-media
Indicator elements. A simple sum of the component values is used:
where:
I = TRI Relative Risk-based Environmental Indicator of interest and
IEC f m = facility-chemical-medium-specific Indicator Element.
As many as 400,000 Indicator Elements for a given reporting year for the TRI will be summed
to yield just one year's score for one of the TRI Relative Risk-based Environmental Indicators (e.g.,
the Chronic Human Health Indicator). In this method, each component score makes a contribution
proportional to its size. The resulting Indicator Value can be used in a number of ways, including
tracking changes over time. As noted earlier, the base-year Indicator is scaled to 100,000, and
subsequent Indicators are scaled to this value to compare changes over time. It must be reiterated
that while changes in scores over the years would imply that there have been changes in risk-based
environmental impacts, the actual magnitude of any specific risk or change in risk is unknown in
absolute terms.
Adjusting the Indicators for Changes in the TRI
When a change occurs in the number of chemicals and facilities represented in TRI, the
numerical value of the Indicators will almost certainly be altered if no adjustments are made to the
method of calculation to account for the change. However, a difference in the Indicator value would
not necessarily represent a sudden shift in actual environmental impact, but rather might reflect a
broader understanding of the impacts that had existed all along. To maintain comparability in the
Indicators' scores over time, the Indicators would have to be adjusted in some manner when such
changes in the TRI occur.
A change in the number of chemicals and facilities in TRI can occur through several
mechanisms. The addition to or deletion of chemicals from the TRI chemical list will occur as EPA
responds to petitions or initiates its own action through the chemical listing or delisting process.
Several additions and deletions to the dataset have already occurred since 1987, the first year of TRI
reporting. Furthermore, as mentioned earlier, in November 1994 the Agency added 245 chemicals
and chemical categories to the TRI chemical list, effective for the reporting year 1995. The deletion
of chemicals would presumably have a minor effect since such chemicals would be deleted due to
their low risk; these chemicals are likely to make only a minimal contribution to the Indicators.
Compliance with TRI reporting has changed over time, which had led to more facilities
reporting. Increases in the number of reporting facilities may also occur as a result of changes in
reporting requirements. For instance, in first two years of reporting, facilities that manufactured or
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processed more than 50,000 pounds were required to report their releases. However, EPCRA
lowered this threshold to 25,000 pounds in 1989. All of these modifications can act to alter the total
emissions reported under TRI and the Indicator's estimate of the associated relative risk-based
impacts.
To account for changes in the representation of chemicals and facilities in the TRI data base,
the TRI Relative Risk-based Environmental Indicators method may create new Indicators when
significant new additions are made to the TRI chemical list. "Significant" additions could be several
minor additions that have been made over the course of a few years that eventually constitute a
significant change, or a single maj or influx of new chemicals (due to Congressional or Agency action,
for example). These new Indicators would include both old and new chemicals and facilities.
However, to track trends for the initial set of chemicals and facilities, EPA would also retain a
separate Indicator consisting of only the "original" facilities and chemicals.
While deletions from the chemical list of TRI chemicals probably would not result in any
significant change to the Indicator value in most cases, the possibility of a change in value due solely
to deletions makes adoption of adjustment methods important. Thus, when major deletions occur,
the Indicator will be modified, excluding deleted chemicals, and then recomputed for all reporting
years.
Finally, the yearly TRI data for a given chemical list of chemicals and facilities are the subject
of ongoing quality control review and correction. As a result, yearly comparisons could be flawed
if such revisions in reported data were not included in each previous year's Indicator. Therefore, the
TRI Relative Risk-based Environmental Indicator will be recomputed for all years in the data base
on an annual basis in order to incorporate revisions to the reporting data.
Generating "Subindicators"
In addition to computing an overall Indicator value, the individual Indicator Elements can be
combined in numerous other ways for further analysis. The detailed calculations used to create the
Indicator Elements allow computation of "subindicators" for a wide variety of individual chemicals,
geographic regions, industry sectors, facilities, exposure pathways and other parameters. These
subindicators, like the overall Indicator, cannot be compared to some absolute level of concern, but
can help identify the relative contribution of various components to the overall estimate of relative
risk-based impacts of emissions. The ability of users to create these "subindicators" makes the TRI
Relative Risk-based Environmental Indicators system a powerful tool for risk-based targeting,
prioritization and strategic policy analysis.
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CURRENT IMPLEMENTATION OF THE TRI RELATIVE RISK-BASED ENVIRONMENTAL INDICATORS
METHOD
Computer Program to Calculate the Indicators
The TRI Chronic Human Health Indicator is currently implemented in a Microsoft Windows-
based, stand alone, PC computer program. The program allows users to calculate the overall Chronic
Human Health Indicator for all years of data and to present the results in various graphical and tabular
formats, as well as save selected data to spreadsheet and database formats (e.g., Microsoft Excel and
dBase). The computer program also allows the users to create "subindicators" based upon specified
parameters pertaining to the full complement of Indicator elements or upon selected subsets of
reported data, or both of these approaches. The program includes on-line help for all of the program
functions. A Users Guide will also be available.
Chemicals and Facilities Currently Included in the Indicators
Conceptually, the Indicators method is intended to include all chemicals that are reportable
to the Toxics Release Inventory. However, for the current version, some chemicals are excluded
because they have not yet been assigned toxicity weights (many of these have had little or no
reporting) or are missing physicochemical data. For the 1995 reporting year, there are 578 discrete
chemicals and 28 separate chemical categories (including 39 additional chemicals in two delimited
categories). In 1995, over 73,000 reports were filed from approximately 22,000 TRI facilities. Of
these chemicals and chemical categories on the TRI List, 336 have been assigned toxicity scores; 288
of these are based on IRIS and HEAST values, and 48 based on expert review within OPPT. Scoring
for all of the current TRI Indicators chemicals is discussed in the Interim Toxicity Weighting
Summary Document (EPA, 1997) and is summarized in Appendix C of this document. For many
chemicals that do not have toxicity scores, current reporting is zero. The evaluation of TRI chemicals
with regard to aquatic toxicity will be conducted when the TRI Chronic Ecological Indicator is
implemented.
ISSUES FOR FUTURE CONSIDERATION AND CONCLUSIONS
There are two general types of issues to consider for future effort: specific methodological
issues for the Indicators developed to date, and development of additional Indicators. The
methodological questions associated with the Indicators developed to date include the following:
•D how to compute the Acute Human Health and Acute Ecological Indicators given the current
reporting under TRI;
•D extending the Ecological Indicators beyond consideration of only aquatic life;
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•D whether severity of effect or multiple effects should be considered in the toxicity score for a
chemical;
•D for off-site transfers, how to better match TRI transfers to particular treatment practices (e.g.,
which TRI chemicals are sent to hazardous or nonhazardous waste management facilities; or
which specific treatment practices are used at identified POTWs);
•D how to incorporate information and/or estimates on changes in population for each year rather
than using 1990 Census data for all years; and
•D how to estimate the potential impact of non-landfill, non-incineration treatment (e.g.,
landfilling) or recycling.
The flexibility of the current TRI Relative Risk-based Environmental Indicators method and
computer program allows accommodation of data from other sources besides the TRI data base.
With additional data, the system could be used to develop additional Indicators that provide
information on measures of environmental impacts other than risk alone. For example, Indicators that
explicitly incorporate consideration of environmental justice issues could be developed using the
Chronic Human Health Indicator as the foundation.
As an indication of improvements in environmental quality over time, the TRI Relative Risk-
based Environmental Indicators will provide the EPA with a valuable tool to measure general trends
based upon relative risk-related impacts of TRI chemicals. Though these Indicators do not capture
all environmental releases of concern, they do generally relate changes in releases to relative changes
in chronic human health and ecological (aquatic life) impacts from a large number of toxic chemicals
of concern to the Agency. Importantly, the Indicators also provide an ability to analyze the relative
contribution of chemicals and industrial sectors to environmental impacts, and serve as an analytical
basis for setting priorities for pollution prevention, regulatory initiatives, enforcement targeting, and
chemical testing.
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I. INTRODUCTION
In 1989, the EPA outlined the goals for establishing strategic planning processes at the
Agency. Underlying this approach was the Agency's desire to set priorities and shift resources to
areas with the greatest opportunity to achieve health and environmental risk reductions. As part of
this initiative, the Administrator set forth a plan to develop indicators to track changes in
environmental health impacts over time. Tracking these changes would allow the Agency to measure
its progress in implementing environmental protection and pollution prevention programs. In
addition, comparing the relative risk contribution of chemicals, industries and geographic regions
through the indicators would allow the Agency (and other users) to establish priorities for improving
environmental health.
Because one goal of such indicators is to allow EPA to track changes in human health and
environmental impacts over time, the Agency would need to take advantage of existing data sources
that reflect multimedia trends in environmental contaminant releases. One such database, the Toxics
Release Inventory (TRI), is currently the Agency's most relevant source of continuous/regularly
reported data for developing indicators of change in environmental impacts over time. The TRI is
mandated by the Emergency Planning and Community Right-to-Know Act (EPCRA) Title III Section
313 and requires that U.S. manufacturing facilities file annual reports documenting multimedia
environmental releases and off-site transfers for over 600 chemicals and chemical categories which
are of concern to the Agency. The Agency had recently added 286 new chemicals and chemical
categories to the Section313 list of toxic chemicals, effective for the reporting year 1995 (that is, the
first reports on these chemicals were due on July 1, 1996) (59 Federal Register 61432, November
30, 1994). These additions have significantly expanded the scope of coverage of the TRI.
In response to the need for environmental indicators, and to take advantage of the rich data
source offered by the TRI, the Office of Pollution Prevention and Toxics (OPPT) convened a
workgroup that included members from several divisions within the Office, as well as individuals from
other Agency Offices. The purpose of the work group was to explore the development of an
indicator or indicators based on the TRI that could track changes in human health and environmental
impacts better than reports of pounds of releases alone.
In particular, the intent of the effort was to introduce a relative risk-based perspective in
examining the trends in TRI reporting over time. When evaluating the local and community impacts
of TRI chemicals, it is important to not only consider the number of pounds of a chemical released
to the environment, but also the toxicity of the chemical, its exposure potential, and the size of the
receptor population. The TRI Relative Risk-Based Environmental Indicators integrates these factors
and provides a relative risk-based perspective of chemical releases and transfers.
This document presents the results of this effort, a method for developing TRI Relative Risk-
based Environmental Indicators. The "TRI Relative Risk-based Environmental Indicators" may
eventually consist of a set of four indicators to separately track: (1) chronic human health, (2) acute
human health, (3) chronic ecological impacts and (4) acute ecological impacts. The focus of this
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report is the development of meaningful indicators of chronic human health impacts and aquatic life
impacts; the development of corresponding acute effects indicators is not feasible now, since the data
to support such indicators are not available.1 Furthermore, to the extent possible, the method
presented is based on currently available, already-reviewed EPA approaches, data sets and models,
in order to minimize duplication of effort and to maximize consistency with other Agency efforts to
evaluate human health and environmental impacts.
This report explains how the proposed TRI Relative Risk-based Environmental Indicators are
constructed, and includes discussions of the conceptual methodology, data sources, and the
computational approach. Since the Indicators are based on risk-related scores, the report discusses
the similarities and distinctions between the relative risk-based approach of the Indicators and
conventional quantitative risk assessments. It also describes a PC-based, stand-alone computer model
developed to allow users to compute the Chronic Human Health Indicator and to easily perform
complex diagnostics of Indicator components, as well as subindicator calculations.
In developing the TRI Relative Risk-based Environmental Indicators, many approaches to
assessing and ranking the potential impact of chemicals were reviewed. Numerous techniques to
score the relative significance of TRI chemicals and facilities have been and continue to be developed,
underscoring the widespread need for such methods. One objective of this report is to explain the
Indicators to a variety of agencies and groups that may wish to use or adapt the Indicators or the
methodologies to their own needs. A related obj ective is to describe the advantages of the Indicators
approach in terms of flexibility, power and usefulness as an analytical and strategic policy planning
tool.
This document was preceded by an earlier draft method document. The earlier document was
described and released at a public meeting in September of 1992, and has been distributed to over 450
interested parties. It has received both internal and external review from a number of commenters.
The current draft reflects a number of modifications to the original method, based on those comments
and additional development work.
While the TRI database is the Agency's single best source of consistently reported release
data, there are several limitations to any indicator that uses TRI data for tracking environmental
health. The TRI data includes releases only from manufacturers in SIC codes 20-39 that employ
more than ten full-time employees and manufacture or process more than 25,000 pounds or use more
than 10,000 pounds of a chemical on the TRI chemical list. (In earlier years, the limitations were
even broader.) Therefore, small manufacturers and many industrial sectors cannot be represented in
a TRI-based indicator. Non-manufacturing activities for which releases are not required to be
reported (but that may result in the emission of toxic chemicals) include dry cleaning, mining, the use
and disposal of consumer products, the use of chemicals for agriculture, and operation of mobile
To appropriately evaluate potential acute effects, it is necessary to know the distribution of releases over time (peak release
data), and these data are not currently reported through the TRI. However, possible future changes in reporting requirements
may allow for the development of separate acute indicators for human and ecological effects.
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sources (such as automobiles) (EPA, 1991a). In addition to exclusion of certain industrial sectors,
not all toxic chemicals are reported to the Toxics Release Inventory. Also, companies do not need
to verify the release data they submit, which results in data of unknown accuracy, although EPA is
providing guidance for quality control. Finally, some companies required to report releases may not
be reporting, resulting in an overall underreporting of total releases.
Despite the fact that the TRI database does not capture all chemicals, industrial sectors, or
releases of concern to both OPPT and the Agency as a whole, EPCRA Section 313 explicitly provides
for the expansion of TRI to cover additional chemicals and industries. As mentioned earlier, EPA
recently added nearly 300 chemicals to the original reporting requirements. Moreover, with
continued reporting, the quality of data reported to the Toxics Release Inventory is assumed to be
improving (EPA, 199la), and OPPT also performs quality control/ quality assurance activities.
Finally, the TRI Relative Risk-based Environmental Indicators computer program allows the user to
import other types of data to be used in conjunction with (or in place of) TRI data, if chemical
toxicity, physicochemical properties and release quantities and locations are known.
A limitation to the interpretation of the TRI Relative Risk-based Environmental Indicators is
identifying the underlying causes of changes in the Indicator values. Although the Indicator will track
reductions that result from both government regulations and from voluntary industry actions, it is not
possible to discern the relative magnitude of reductions attributable to a particular type of action,
unless specific reductions in emissions can be attributed to particular actions.
How INDICATOR TOXICITY WEIGHTINGS DIFFER FROM EPCRA SECTION 313 STATUTORY
CRITERIA
The TRI Relative Risk-Based Environmental Indicators utilize Toxics Release Inventory
(TRI) chemical reporting data. All of the TRI chemicals included in the Indicators are listed on the
TRI because they meet one or more statutory criteria regarding acute or chronic human toxicity, or
environmental toxicity. The goal of the Indicators is to use data reported to the Agency to investigate
the relative risk-based impacts of the releases and transfers of these chemicals on the general, non-
worker population.
To do this, the Indicators must differentiate the relative toxicity of listed chemicals and rank
them in a consistent manner. The ranking of each chemical reflects its toxicity only relative to other
chemicals which are included in the Indicators; not to some benchmark or absolute value.
The TRI Relative Risk-Based Chronic Human Health Indicator addresses only the single, most
sensitive chronic human health toxicity endpoint. Unlike the statutory criteria used for listing and
delisting chemicals, the Indicator does not address the absolute chronic toxicity of chemicals on the
TRI (e.g., multiple effects or the severity of effects); nor does it attempt to reflect the statutory
criteria for these chemicals.
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It is important that the public not confuse the use of the Indicator as a screening-level tool for
investigating relative risk-based impacts related to the releases and transfers of TRI chemicals, with
the very different and separate activity of listing/delisting chemicals on the TRI using statutory
criteria. The toxicity weightings provided in the Indicator method cannot be used as a scoring system
for evaluating listing/delisting decisions.
Emergency Planning and Community Right-to-Know Act Section 313 Statutory Criteria
The Emergency Planning and Community Right-to-Know Act of 1986 (EPCRA) section
313(d)(2) sets out criteria for adding chemicals to the list of chemicals subject to reporting under
EPCRA section 313(a). For a chemical (or category of chemicals) to be added to the EPCRA section
313(c) list of toxic chemicals, the Administrator must judge whether there is sufficient evidence to
establish any one of the following:
Acute Human Toxicity §313(d)(2)(A) - The chemical is known to cause or can reasonably
be anticipated to cause significant adverse acute human health effects at concentration levels that are
reasonably likely to exist beyond facility site boundaries as a result of continuous, or frequently
recurring, releases.
Chronic Human Toxicity §313(d)(2)(B) - The chemical is known to cause or can reasonably
be anticipated to cause in humans—
(i) cancer or teratogenic effects, or
(ii) serious or irreversible—
(I) reproductive dysfunctions,
(II) neurological disorders,
(III) heritable genetic mutations, or
(IV) other chronic health effects.
Environmental Toxicity §313(d)(2)(C) - The chemical is known to cause or can reasonably
be anticipated to cause, because of—
(i) its toxicity,
(ii) its toxicity and persistence in the environment, or
(iii) its toxicity and tendency to bioaccumulate in the environment, significant adverse effect
on the environment of sufficient seriousness, in the judgement of the Administrator, to
warrant reporting under this section.
To remove a chemical from the section 313(c) list, the Administrator must determine that
there is not sufficient evidence to establish any of the criteria described above as required by EPCRA
section 313(d)(3).
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The EPA examines all of the studies available for a chemical to decide if the chemical is
capable of causing any of the adverse health effects or environmental toxicity in the criteria. Agency
guidelines describe when a study shows such effects as cancer (EPA, 1986a), developmental toxicity
(teratogenic effects) (EPA, 199 Ib), or heritable genetic mutations (EPA, 1986b). The review makes
a qualitative judgment regarding the potential of each chemical to meet at least one of the criteria and
the chemical is added to the list if this judgment is positive. If a chemical is on the list and it is not
possible to make a positive judgment regarding any of the criteria, then the chemical can be removed.
There is no correlation between the toxicity criteria and methodology used to make listing decisions
under EPCRA section 313 and the methodology used to rank chemicals for the Indicators.
Relative Toxicity Weighting of Chemicals in the TRI Relative Risk-Based Chronic Human
Health Indicator
In order to help the Agency make decisions, comparisons can be made among chemicals once
they are listed under EPCRA section 313. The TRI Chronic Human Health Indicator considers
aspects of the adverse health effects (cancer and noncancer), along with exposure and population
weighting factors, to permit the chemicals to be ranked relative to one another. These aspects are
available in public Agency-generated databases. Uncertainty reflecting the quality and adequacy of
the data is incorporated into a toxicity weighting each chemical receives. The approach is intended
to differentiate the relative toxicity of these chemicals in a uniform manner, provide a clear and
reproducible scoring system based upon easily accessible and publicly available information, and
utilize EPA consensus opinion to the greatest extent possible.
A complete discussion of the methods used in deriving the toxicity weightings for the
Indicator, as well as the chemical-specific data summaries and scores, is provided in the document,
TRI Relative Risk-Based Environmental Indicators Project: Interim Toxicity Weighting Summary
Document (EPA, 1997).
II. GENERAL DESCRIPTION OF THE TRI RELATIVE RISK-BASED
ENVIRONMENTAL INDICATORS
APPROACHES USED TO ADJUST RELEASES AND TRANSFERS IN OTHER EXISTING SCREENING
SYSTEMS
Offices within EPA and organizations outside the Agency have developed numerous systems
for scoring or weighting chemicals based on potential toxicity and/or exposure. The usual purpose
of such activities is to prioritize chemicals for further study or for closer regulatory scrutiny, or to
target chemicals or industries for enforcement. A review of chemical scoring and ranking procedures
is presented in Appendix A. These systems were reviewed (before the TRI Relative Risk-based
Environmental Indicators method was developed), to learn from the successes and problems of earlier
efforts.
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Previous scoring systems have used a variety of methods to weight chemicals. The actual
numerical weights applied to chemicals can be qualitative, ordinal, proportional or calculated, or some
combination of these approaches. The relative severity of the effects posed by chemicals can also be
included, as can considerations of the quality of the toxicity data and exposure estimates. Based on
our review of these scoring systems, several options for an evaluation method emerged. Alternative
methods, and their advantages and disadvantages, were considered by the TRI Relative Risk-based
Environmental Indicators Work Group and are summarized in Appendix B. This report presents a
method based on the research described in Appendices A and B and based on Work Group
deliberations. While the method described in this document contains elements of the options
described in Appendix B, the TRI Relative Risk-based Environmental Indicators method combines
these elements in a manner that is not presented explicitly in that appendix.
GENERAL APPROACH USED FOR THE TRI RELATIVE RISK-BASED ENVIRONMENTAL INDICATORS
This report describes the method for constructing the TRI Chronic Human Health Indicator
and a draft method for the TRI Chronic Ecological Indicator. For both, the objective is to calculate
a unitless value that reflects the relative risk-related impacts of releases and transfers of all included
TRI chemicals from all reporting facilities to each environmental medium for a given year or years.
To construct Indicators that are related to risk, the reported quantity of TRI releases and
transfers must be adjusted in a manner that relates to the risks associated with each media-specific
release or transfer of each chemical. The risk potentially posed by a chemical release depends on the
inherent toxicity of the chemical, the environmental fate and transport of the chemical in the medium
to which it is released, the degree of contact between the contaminated medium and the human or
ecological receptors, and the size of the exposed population. Differences in these factors influence
the relative contribution each release or transfer makes to each Indicator. Transfers to off-site
locations such as sewage treatment plants (POTWs) require an additional estimate of the impact of
treatment technologies on the magnitude of release and are modeled based upon exposure and
population parameters associated with that site.
In order to incorporate these factors into the Indicators, three main components are used to
compute each Indicator. These are:
•D the quantity of chemicals released or transferred,
•D adjustments for chemical-specific toxicity (described in chapter III), and
•D adjustments for pathway-specific and chemical-specific exposure potential (described in
chapter IV).
An additional adjustment is applied to the Chronic Human Health Indicator to reflect size of the
potentially exposed population2 (see chapter V). This basic outline is illustrated in Exhibit 1.
The method focuses on general populations: individuals, particularly highly exposed individuals, are not the focus of the
Chronic Human Health Indicator. Furthermore, worker exposures are not addressed. Additional Indicators based upon highly
exposed or sensitive subpopulations may be developed in the future.
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EXHIBIT 1. Calculation of TRI Chronic Human Health Indicator
POTW transfers 1 emissions 1 1 emissions
off-site T f
incineration ^^^
PUT W sludge A11 ^
incineration ^^^
^^^
T
Toxicity Data Evaluation
Population Data Evaluation ^
(See Chap. V) ^
1
Air
IndeXfacility.chemical
on-site land POTW transfers 1 1 discharges transfers 1
f
Vnlntili-ntinn ' Ground POTW sliiHpe land
|
, Water disposal
T T
Exposure Evaluation
1
T
Exposure Weight 1
X
1 T • •«, iir • u^^^~^^^
X
i D • T^^^^^^I
1 1
Groundwater
Indexfacilltyj chemicai
Surface Water
.IldeX faclilty) chemical
Sum over all Chemicals, Facilities and Media
t
TRI CHRONIC HUMAN HEALTH INDICATOR
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The TRI Chronic Human Health Indicator uses these components to perform a separate
assessment for each unique combination of a chemical, facility, and release or transfer medium. Each
of these releases or transfers results in a calculated "Indicator Element," a unitless value proportional
to the potential risk-based impact of each specific release or transfer. The value for the TRI Chronic
Human Health Indicator is simply the sum of all the applicable Indicator Elements. Similarly, for the
TRI Chronic Ecological Indicator, a separate assessment is made for each unique chemical-facility
combination affecting the water medium, yielding the Ecological Indicator elements. The overall TRI
Chronic Ecological Indicator is the sum of these elements. Chapter VI presents the specific equations
for the calculation of each of these Indicators.
The overall Indicators are calculated for each year in the TRI data set, beginning with 1988.
These values can be compared in a number of ways. For example, one of the early years of TRI
reporting, 1988 for example, may be selected as the "base year" and later years' Indicator values are
compared to it. For the base year, the unitless score is scaled to 100,000 by dividing the summation
of the Indicator Elements and multiplying by 100,000; subsequent years' data are scaled by the same
factor (i.e., normalized) to provide a relative comparison. This comparison allows assessment of the
changes in estimated risk-related impacts of TRI releases and transfers from year to year.
Importantly, the TRI Relative Risk-based Environmental Indicators method offers unlimited
combinations and views of the Indicators' subcomponents. Each facility-chemical-media Indicator
Element is retained by the computer program and thus can be evaluated by users wishing to
investigate the structure of the Indicators. OPPT, other EPA Offices, Regions, States, or individuals
could use these individual elements to create their own "subindicators" that examine the Indicator
from alternative perspectives, such as chemicals, industries, or geographic regions (among other
parameters).
It must be emphasized that the TRI Relative Risk-based Environmental Indicators method is
not intended to be a quantitative risk assessment and does not calculate risk estimates. The method
follows the same general paradigm often applied in quantitative assessments, but in a relative way.
The TRI Relative Risk-based Environmental Indicators are by their nature only intended to reflect
the direction and the general magnitude of the change in releases over time, scaled by factors
(toxicity, exposure potential, and population size) that relate to potential risk. As such, an Indicator
value has only relative rather than absolute meaning; it can only be used in comparisons to other
Indicator values at different points in time, or in identifying the relative size of contributing factors
to the overall Indicator score.
The following four chapters of this report describe the methods used for making toxicity,
exposure potential and population adjustments to the emissions data, and also present the equations
for calculating the overall Indicators values. Subsequent chapters discuss implementation issues
related to the use of the TRI Relative Risk-based Environmental Indicators, as well as ideas for future
improvements and/or additions to the set of Indicators.
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Though this document presents conceptual methods for both the TRI Chronic Human Health
Indicator and the TRI Chronic Ecological Indicator, the method has only been implemented for the
TRI Chronic Human Health Indicator. Further method development, and further data collection and
analysis, will be required for the implementation of the TRI Chronic Ecological Indicator.
III. METHODS FOR CALCULATING TOXICITY WEIGHTS
CHRONIC TOXICITY WEIGHTS — HUMAN
The Section 313 criteria list several human toxicity parameters that EPA must consider when
evaluating a chemical for addition to TRI, including acute toxicity, cancer or teratogenic effects,
serious or irreversible reproductive dysfunctions, neurological disorders, heritable genetic mutations,
or other chronic health effects, and environmental toxicity. Some chemicals have toxicity data for
only one effect, while others will have evidence of effects within several of these toxicity categories.
The definition of these parameters, as given in Section 313, are given in Exhibit 2. A release could
be weighted based upon the number of these effects that it causes, the relative severity of the effects
it causes, the potency of the chemical for one or more of these effects and the uncertainty inherent
in characterizing effects.
The TRI Relative Risk-based Environmental Indicators method for developing chronic human
health toxicity weights focuses on the latter two factors. It thus considers both qualitative and
quantitative elements to judge the relative toxicity of chemicals. There is uncertainty inherent in
determining both whether exposure to a chemical will cause an effect in humans and the potency of
the chemical. Quantitative potency data must be considered in the context of a qualitative
classification of the uncertainty associated with that data. In the case of noncancer effects, this
classification is considered in the development of the quantitative toxicity values (e.g., Reference
Dose values). However, for chemicals with carcinogenic effects, the TRI Relative Risk-based
Environmental Indicators method uses existing qualitative weight-of-evidence (WOE) measures in
addition to quantitative toxicity values to assign toxicity weights.
Qualitative Data Used in Chronic Human Toxicity Weighting
Risk assessors use a variety of data to evaluate the potential toxicity of a chemical to humans,
including epidemiological data, data from acute and chronic animal studies, and in vitro toxicity tests.
Together, these data form a body of evidence regarding the potential for toxic chemicals to cause a
particular health effect in humans. The risk assessor can judge qualitatively the strengths of this body
of evidence when determining the probability of the occurrence of the effect in humans. Based on
this judgment, the chemical is assigned a WOE classification. Weight-of-evidence schemes can be
designed to indicate whether a chemical either causes a specific health effect in
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EXHIBIT 2. Toxicity Endpoints
Endpoint
Carcinogenicity
Heritable Genetic and
Chromosomal Mutation
Developmental Toxicity
Reproductive Toxicity
Acute Toxicity
Chronic Toxicity
Neurotoxicity
Definition
This toxicity endpoint concerns the ability of a chemical to produce cancer in
animals or humans.
Chemicals which affect this endpoint can cause at least three separate modes of
failure to transmit genetic information: gain or loss of whole chromosomes
(aneuploidization), rearrangement of parts of chromosomes (clastogenesis), and
addition or deletion of a small number of base pairs (mutagenesis).
Any detrimental effect produced by exposures to developing organisms during
embryonic stages of development, resulting in: prenatal or early postnatal death,
structural abnormalities, altered growth, and functional deficits (reduced
immunological competence, learning disorders, etc.).
This endpoint concerns the development of normal reproductive capacity.
Chemicals can affect gonadal function, the estrous cycle, mating behavior,
conception, parturition, lactation, and weaning.
Acute toxicity indicates the potential for a short-term exposure (typically hours or
days) by inhalation, oral, or dermal routes to cause acute health effect or death.
Chronic toxicity indicates the potential for any adverse effects other than cancer
observed in humans or animals resulting from long-term exposure (typically
months or years) to a chemical.
This endpoint concerns the central and/or peripheral nervous system. Changes to
the system may be morphological (biochemical changes in the system or
neurological diseases) or functional (behavioral, electrophysiological, or
neurochemical effects).
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general, or specifically in humans. The carcinogenicity WOE system presented in this methodology
relies on categorical definitions from the EPA Guidelines for Carcinogenic Risk Assessment (EPA,
1986a, currently being revised), which are related to the potential for a chemical's carcinogenicity in
humans. These Guidelines define the following six WOE categories, as shown in Exhibit 3:
EXHIBIT 3. Weight of Evidence Categories for Carcinogenicity
Category
A
Bl
B2
C
D
E
Weight of Evidence
Sufficient evidence from epidemiological studies to support a causal relationship
between exposure to the agent and cancer.
Limited evidence from epidemiological studies and sufficient animal data.
Sufficient evidence from animal studies but inadequate or no evidence or no data
from epidemiological studies.
Limited evidence of carcinogenicity in animals and an absence of evidence or data
in humans.
Inadequate human and animal evidence for carcinogenicity or no data.
No evidence for carcinogenicity in at least two adequate animal tests in different
species or in both adequate epidemiological and animal studies, coupled with no
evidence or data in epidemiological studies.
For noncancer effects, weight-of-evidence is considered qualitatively in the hazard
identification step of determining a Reference Dose (RfD) (see below for discussion of RfD). The
WOE evaluation for noncancer effects is different from that for carcinogenic effects. For exposure
to chemicals with potential carcinogenic effects, current EPA policy assumes no threshold exposure
below which cancer risk is zero; thus, determining a chemical to be a known, probable, or possible
human carcinogen implies some risk associated with any exposure. Therefore the WOE
determination focuses on whether the chemical may or may not cause cancer in humans. In contrast,
the judgment that a chemical is a systemic toxicant is dose-dependent; the WOE evaluation focuses
on the dose where chemical exposure would be relevant to humans (Dourson, 1993). The focus of
the WOE evaluation, and the expression of the level of confidence in the RfD, is a judgment of the
accuracy with which the dose relevant to humans has been estimated. The WOE evaluation is
included qualitatively in the RfD, but does not affect its numerical calculation. Since weight of
evidence has been considered in developing RfDs, the TRI Relative Risk-based Environmental
Indicators method does not consider WOE separately for noncancer effects.
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Quantitative Data Used in Chronic Human Toxicity Weighting
Types of Data
Quantitative data on the relative potencies of chemicals are needed for toxicity weighting.
For cancer risk assessment, EPA has developed standard methods for predicting the incremental
lifetime risk of cancer per dose of a chemical. EPA generally uses a linearized multistage model of
carcinogenesis to quantitatively model the dose-response function of a potential carcinogen. The
upper bound of the linear term of this model is called the qt*. This slope factor is a measure of cancer
potency. Cancer risk can also be expressed as a unit risk factor, that is, the incremental lifetime risk
of cancer per mg/m3 in air or per mg/L in water. Although the level of conservatism inherent in these
slope factors and unit risk factors varies by chemical, unit risk factors and q^s nonetheless are the
best readily available values that allow us to compare the relative cancer potency of chemicals.
For noncancer risks, data on dose-response are more limited; generally, a risk assessor
evaluates dose compared to a Reference Dose (RfD) or Inhalation Reference Concentration (RfC).
Both the RfD and RfC are defined as "an estimate (with uncertainty spanning perhaps an order of
magnitude) of a daily exposure to the human population (including sensitive subgroups) that is likely
to be without an appreciable risk of deleterious effects during a lifetime" (EPA, 1988a; EPA, 1990g).
The units of RfD are mg/kg-day, while the units of the Inhalation Reference Concentration are mg/m3.
A chemical's reference dose or reference concentration is based on aNo Observable Adverse Effect
Level or Lowest Observable Adverse Effect Level, combined with appropriate uncertainty factors to
account for intraspecies variability in sensitivity, interspecies extrapolation, extrapolation from
LOAELs to NOAELs, and extrapolation from subchronic to chronic data. In addition, a modifying
factor can be applied to reflect EPA's best professional judgment on the quality of the entire toxicity
database for the chemical. By definition, exposures below the RfD are unlikely to produce an adverse
effect; above this value, an exposed individual may be at risk for the effect. Empirical evidence
generally shows that as the dosage of a toxicant increases, the severity and/or incidence of effect
increases (EPA, 1988a), but for a given dose above the RfD, the specific probability of an effect is
not known, nor is its severity. For purposes of the TRI Relative Risk-based Environmental Indicator
method, we assume that noncancer risk varies as the ratio of the estimated dose to the RfD.
Sources of Data
Information regarding the human health effects data on the TRI chemicals was compiled from
a number of sources. The primary source of these data was the Integrated Risk Information System
(IRIS). This computerized data source includes information on EPA evaluations of chemical toxicity
for both cancer and noncancer effects of chemicals. IRIS provides both background information on
the studies used to develop the toxicity evaluations and the numerical toxicity values used by EPA
to characterize risks from these chemicals. These values include upper-bound slope factors (q^) or
inhalation unit risk values for chemicals with carcinogenic effects as well as RfDs or RfCs for
chemicals with noncancer effects. Data contained in IRIS have been peer-reviewed and represent
12
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Agency consensus. The peer-review process involves literature review and evaluation of a chemical
by individual EPA program offices and intra-Agency work groups before inclusion in IRIS.
When IRIS values are not available for TRI chemicals, an alternate source of toxicity data is
the Health Effects Assessment Summary Tables (HEAST). These tables are constructed for use in
both the Superfund program and in the RCRA program but do not represent overall Agency
consensus. However, these tables are publicly available from the Superfund program. The tables
include slope factor estimates and unit risks as well as WOE categorizations for chemicals with cancer
effects, and RfDs and RfCs for noncancer effects.
In cases where IRIS or HEAST do not have toxicity values and WOE classifications, we have
relied on several other sources for data from which to assign weights for use in the Indicators method.
Although individual literature searches for toxicological and epidemiological data for each chemical
were beyond the scope of this project, data bases such as the Hazardous Substances Data Base
(HSDB), as well as various EPA and ATSDR summary documents, provided succinct summaries of
toxic effects and quantitative data, toxicological and epidemiological studies, and, in some cases,
regulatory status data. Summaries of these data, and suggested toxicity scores based on the
summaries, were provided for selected chemicals to a group of OPPT health scientists charged with
reviewing toxicity data. After their review, this group then approved or disapproved the suggested
scores through a disposition process. A complete discussion of the methods used in these
evaluations, as well as the chemical-by-chemical data summaries and score assignments, are provided
in the document TRI Relative Risk-based Environmental Indicators Project: Interim Toxicity
Weighting Summary Document (EPA, 1997b).
General Format for Combining Weight-of-Evidence and Slope Factors to Assign Weights
Several methods for deriving toxicity weights were considered during the development of the
Indicator, including using low, medium, and high categories; using ordinal scores; using order of
magnitude scores for categories of toxicity; or using specific numerical risk values, such as RfDs and
slope factors. The merits and disadvantages of each of these methods is discussed in Appendix B.
The method chosen is applies order of magnitude weights based on categories of toxicity.
The method uses different schemes to weight the toxic effects of a chemical, depending on whether
the effect is carcinogenic or noncarcinogenic. For carcinogenic effects, the method uses a matrix to
evaluate a chemical based on WOE and slope factor simultaneously. Rows and columns form matrix
cells to which a toxicity weight is assigned. The rows of the matrix are defined by the ranges of the
slope factor, while the columns of the matrix are defined by the weight-of-evidence categorization.
The toxicity values are assigned to each slope factor range-WOE combination. For noncarcinogenic
effects, weights are applied based on ranges of noncancer risk values alone.
Using categorical weights for toxicity has several advantages over calculating specific, unique
numerical weights for chemical releases. First, unique weights would imply that we know the toxicity
of the chemical with enough accuracy to distinguish among relatively small differences in these values.
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In fact, there are significant uncertainties associated with the assessment of a chemical's slope factor
and even weight-of-evidence. In fact, the definition of the RfD contains the expression "within an
order of magnitude." Weighting a release based on broader categories of toxicity into which it falls
avoids the impression of accuracy where such accuracy does not exist. Second, when general
categories are used, chemicals are likely to remain in the broad toxicity category to which they are
originally assigned, unless significant new and different toxicity data become available. Broad
categories are also likely to be more robust as new methods for evaluating the toxicity of chemicals
(such as new approaches to cancer risk assessment) develop over time. Thus, categorical weights
applied to these chemicals are not likely to be revised frequently, lending stability to the Indicators
over time. Finally, defining broad categories of weights allows EPA analysts to use a wide variety
of qualitative and quantitative toxicity information, including consideration of chemicals that are
policy priorities for the Agency, to make approximate judgments about the relative level of concern
with respect to toxicity for chemicals where specific slope factors and RfD values have not yet been
developed by the Agency. This more flexible approach to allows more chemicals to be included in
the Indicator than would be possible if specific unique numeric risk values were required for the
development of toxicity weights.
Either ordinal or proportional weights could be assigned to the categories defined by the
matrix cells. Ordinal weights delineate the relative toxicity rank among emissions and are useful for
setting priorities. They do not, however, provide information on the magnitude of the toxicity of
chemicals relative to one another. For example, an ordinal rank of 3 for chemical A and 1 for
chemical B does not mean chemical A is three times worse than chemical B. Since ordinal weights
do not reflect proportional differences in toxicity, the ability of the Indicator to reflect changes in
health and environmental impacts could be limited if ordinal weights are used. In fact, if ordinal
weights are used, it is possible that the Indicator could decrease over a period when actual risk
increases. An example of this possibility is illustrated in Exhibit 4, which compares the direction of
the trend illustrated by an ordinal-based indicator to the trend shown in a hypothetical quantitative
risk assessment.
Unlike ordinal systems, proportional scoring systems use numerical scores that reflect the
magnitude of difference between the impacts associated with chemical releases. Exhibit 5 shows how
the Indicator value developed in Exhibit 4 would change if proportional rather than ordinal weights
are assigned to the categories. In the TRI Relative Risk-based Environmental Indicators method,
weights increase by an order of magnitude for each order of magnitude increase in toxicity and for
each increase in WOE category.
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EXHIBIT 4. Use of an Ordinal Weighting System
Assume that the following ordinal weighting system is used to calculate the TRI Chronic Human Health
Indicator. This example Indicator addresses the releases of carcinogens to air:
q/ Value
50 or greater
5
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EXHIBIT 5. Use of a Proportional Weighting System
Assume that the following proportional weighting system is used to calculate the TRI Chronic Human Health
Indicator. As in Exhibit 4, the example Indicator addresses the releases of carcinogens to air:
ci,* Value
50 or greater
5
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The Human Health Toxicity Weighting Schemes
The preceding discussion presented the general framework for weighting the toxicity of TRI
releases. This section describes and explains the specific weighting schemes developed from this
framework. Two separate toxicity weighting schemes, for carcinogenic effects and noncancer effects,
are discussed (see Exhibits 6 and 7).
Carcinogenic Effects
When EPA-derived values are available regarding the carcinogenicity of a chemical, the
following matrix for chemicals with potential carcinogenic effects is applied:
EXHIBIT 6. Toxicity Weighting Matrix for Carcinogenic Effects
Range of
Oral Slope Factor
(risk per mg/kg-day)
< 0.005
0.005 to < 0.05
0.05 to < 0.5
0.5 to < 5
5 to < 50
> 50
Range or
Inhalation Unit Risk
(risk per mg/m3)
< 0.0014
0.0014 to < 0.014
0.014 to < 0.14
0.14 to < 1.4
1.4 to < 14
> 14
Weight of Evidence Category
A/B
(Known/Probable)
10
100
1000
10,000
100,000
1,000,000
c
(Possible)
1
10
100
1000
10,000
100,000
The rows of the matrix describe the ranges of slope factors used by the Indicators. The
particular ranges of slope factor values selected to represent each category correspond to the ranges
presented in EPA's Hazard Ranking System (HRS) (EPA, 1990b)3. The HRS is a multipathway
scoring system "used to assess the threat associated with actual or potential releases of hazardous
substances at sites" (EPA, 1990b). The HRS score determines whether a site will be included on the
National Priorities List (NPL). Part of the HRS scoring system rates the inherent toxicity of
chemicals based on measures of cancer slope factor, RfDs, and/or acute toxicity. Ranges of slope
factors that differ by an order of magnitude are assigned scores that differ by an order of magnitude.
The actual numerical weights assigned to the matrix cells in Exhibit 6 correspond to the scores
Note that only the toxicity weighting schemes (for human health and aquatic toxicity) from HRS are used. No other
weighting schemes from the HRS are used in the Indicators method.
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assigned in the HRS to these slope factor ranges. [Recall that slope factors are expressed as risk per
unit dose in mg/kg-day.] In certain cases, ranges presented in the Indicator's matrix extend beyond
those presented in the HRS because the range of slope factors for the TRI chemicals is broader than
that covered by the HRS. Chemicals with slope factors smaller than a risk of 0.005 per mg/kg-day
are assigned the lowest toxicity weight while those with slope factors greater than 50 are assigned
the highest toxicity weight.
The columns of the matrix qualitatively classify the potential carcinogen! city of a chemical into
two general categories: known/probable and possible. Weight-of-evidence categories A, B1 and B2
of the EPA Cancer Risk Assessment Guidelines are placed in the "known/probable" category. Class
C is placed in the "possible" category. Categories D and E are not considered in this weighting
scheme. The combination of the A and B categories represents a modification of the HRS scoring
system, where A, B and C categories are each scored separately. This modification and one other
(see below) were made based upon comments received from two of the 1992 peer reviewer's: Adam
Finkel, Sc.D. (Resources for the Future) and John Graham, Ph.D. (Harvard Center for Risk Analysis).
These reviewers felt that this may reduce the potential of a false dichotomy between the A and B
categories, which would be inappropriate for quantitative potency adjustments of this type; and
because it has the advantage of stabilizing the Indicator against changes induced by chemicals
shuttling between the A and B categories.4
The cells in the first WOE Category column of the matrix (that is, the column that
corresponds to the "known/probable" WOE category) were assigned the weights based on the HRS
values. Weights in the other column (i.e., the "possible" WOE category) were assigned by dividing
the weights in the first column by a factor of 10, because evidence that they cause cancer in humans
is less certain. The choice of applying a factor of 10 is on the advice of peer review; an order of
magnitude is an arbitrary uncertainty factor.
This scoring system also differs from HRS in that it does not assign a toxicity weight of 10,000 to asbestos and to lead.
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Noncancer Effects
When RfD or RfC values are available, the following table is used to assign toxicity weights
to chemicals associated with noncancer endpoints:
EXHIBIT 7. Toxicity Weights for Noncancer Effects
RfD Range
(mg/kg-day)
0.5
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a weight based on the number of endpoints may undervalue some poorly studied but still risky
chemicals. For these reasons, the options for applying additional weights based on number and
severity of endpoints were rejected.5
Although choosing the most sensitive endpoint to weight a given chemical does not explicitly
consider severity of cancer and noncancer effects within each of these groups, the method of
separately weighting carcinogenic and noncarcinogenic effects cannot avoid equating toxicity values
between these groups. For example, the weighting scheme equates a qt* value of 0.1 risk per mg/kg-
day for a known/probable carcinogen with an RfD of 0.001 mg/kg-day, since both are assigned a
weight of 1000 (as is done in the FIRS scoring system). If one were to use this weighting scheme to
evaluate actual doses, this weighting would imply that a cancer risk of 1 x 10"4 would be equated to
a noncancer risk at the RfD.6
Inhalation and oral toxicity weights are developed separately. If values are available for each
route, then separate values are assigned to each route. If data are available for only one route, the
same toxicity weight generally is applied for both routes. In rare instances, toxicity studies are
available to show that a given chemical causes no effects via one route; in these instances, we assign
the toxicity weight only to the route that results in effects. Although assigning the same weight to
both routes is not an ideal method, it is sufficient for the TRI Relative Risk-based Environmental
Indicators method, which relies on order-of-magnitude weights. The alternative would be to leave
out chemicals with no toxicity data for a given exposure route; this would be undesirable, since one
aim of the Indicators method is to include as many chemicals as possible.
Scoring for all of the current TRI Indicators chemicals is discussed in the Toxicity Weighting
Summary Document (EPA, 1997) and is summarized in Appendix C of this document.
CHRONIC TOXICITY WEIGHTS — ECOLOGICAL
For ecological effects, the TRI Ecological Chronic Effects Indicator focuses on aquatic life
impacts only. Very little data are available for most chemicals on effects to terrestrial or avian
species; we assume the Chronic Human Health Indicator will provide some predictor of these.
Aquatic toxicity weighting differs from chronic human health toxicity weighting in two
important respects. First, WOE is not considered a factor in the weighting scheme, since direct
evidence of chemical toxicity is available from tests on aquatic species. Second, the aquatic toxicity
weighting scheme simultaneously considers toxicity and bioaccumulation potential. Both of these
measures are considered important when evaluating impacts on aquatic ecosystems.
Although we do not apply subjective weights based on number and severity of effects, the assignment of weights based
on the most sensitive effect is a subjective decision in itself.
At a dose of 0.001 mg/kg-day, a chemical with a q/ ofO.l (kg-day/mg) would yield a risk of 1 x 10"4.
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Data Used in Chronic Aquatic Toxicity Weighting
The preferred numerical aquatic toxicity data to use for weighting are the Chronic Ambient
Water Quality Criteria (AWQC), developed by the Office of Water. However, Acute AWQC may
be used if chronic values are not available. If neither of these values are available, the lowest LC50
(the chemical concentration in water at which 50 percent of test organisms die) may be used for
scoring.
The preferred measure of bioaccumulation potential is the bioconcentration factor (BCF). The
BCF values are derived from laboratory tests that compare the contaminant concentration in the
environmental medium (i.e., water)tothe concentration in the tissues of a test organism (usually fish).
Several researchers have found that for organic contaminants, the BCF can be approximated as a
function of the log of the octanol water partition coefficient (log Kow). The Kow is a physicochemical
property that describes the partitioning of organic chemicals between an organic solvent (octanol) and
water. If BCF values are not available, the Kow can be used instead for scoring organic chemicals.
Finally, when neither of these measures are available, the bioaccumulation potential can also be
approximated by the water solubility of the chemical. Generally, the less soluble a chemical, the
greater its potential for bioaccumulation. Values for all of these measures of bioaccumulation
potential are available from a variety of sources, including the AQUIRE database, as well as a number
of EPA Office of Water references, the Environmental Effects Division chemical properties data base
and standard chemical reference books.
The Aquatic Toxicity Weighting Matrices
The aquatic toxicity weight assigned to a chemical is a function of both its aquatic toxicity
values and bioaccumulation potential values (see Exhibits 8 and 9). Separate weights are assigned
based on each of these measures; the chemical's final toxicity weight is obtained by multiplying these
individual weights (giving toxicity weights ranging from 0.5 to 500,000,000).
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The individual weights assigned based on the measures of bioaccumulation potential are the
following:
EXHIBIT 8. Bioaccumulation Weights
Water Solubility
(mg/1)
> 1,500
_
_
>500-1,500
25-500
<25
Log Kow
<0.8
0.8-<2
2-<3.2
3.2-<4.5
4.5-<5.5
5.5-<6.0
BCF (L/kg)
<1
1-<10
10-<100
100-<1,000
1,000-<10,000
>10,000
Weight
0.5
5
50
500
5,000
50,000
Note: If BCF values are available, they should be used; If not, log of the octanol water partition coefficient (log Kow) can be
used for organic contaminants. When neither of these measures can be used, the bioaccumulation potential can also be
approximated by the water solubility of the chemical. Note that Kow is not used for scoring if its value exceeds 6.0.
Individual weights based on aquatic toxicity measures are the following:
EXHIBIT 9. Aquatic Toxicity Weights
LC50 (|ig/l)
>1,000
100-1,000
10-100
1-10
<1
Acute AWQC (|ig/l)
>100,000
10,000-100,000
1,000-10,000
100-1,000
<100
Chronic AWQC
(US/1)
>1,000
100-1,000
10-100
1-10
<1
Weight
1
10
100
1,000
10,000
Note: The preferred numerical aquatic toxicity data to use for weighting are the Chronic Ambient Water Quality Criteria
(AWQC). Acute AWQC may be used if chronic values are not available. If neither of these values are available, the lowest
LC50 may be used for scoring. As shown in the table, HRS does not assign scores of 5 or 50 based on water solubility.
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As with the chronic human health toxicity weighting, the quantitative measures used to represent
chronic aquatic toxicity, the value ranges used to define the categories of toxicity, and the numerical
weights assigned to each category were taken from the Hazard Ranking System.
Exhibit 10 presents the combined toxicity weighting system for aquatic toxicity. The rows of
the matrix are defined by the bioaccumulation potential categories and the columns of the matrix are
defined by the aquatic toxicity categories. The cells of the matrix are the product of the chemical's
bioaccumulation potential and aquatic toxicity weights. We take the product of these values (rather
than the sum or the average) because both contribute multiplicatively to the overall impact. For
instance, a chemical with a toxicity weight of 10 and a bioaccumulation potential of 10 is considered
to be 10 times worse than a chemical with toxicity weight of 10 and bioaccumulation potential of 1,
since the potential exposure through the food chain is 10 times higher for the chemical with
bioaccumulation potential of 10 versus the chemical with a bioaccumulation potential of 1.
IV. METHODS FOR ADJUSTING RELEASES AND TRANSFERS FOR CHRONIC
EXPOSURE POTENTIAL
EVALUATING CHRONIC HUMAN EXPOSURE POTENTIAL — GENERAL DESCRIPTION
As with toxicity weighting, both qualitative and quantitative elements are considered when
weighting chronic exposure potential. Quantitatively, release data are combined with generic
exposure models to derive a "surrogate" dose level to characterize exposure potential on an exposure
pathway-specific basis. Qualitatively, a level of uncertainty associated with the surrogate measures
of exposure potential is assigned to each exposure pathway. The uncertainty estimates are then used
to adjust the surrogate doses to derive the final exposure potential adjustment factor.
Quantitative Data Used in Evaluating Chronic Human Exposure Potential
The TRI release and transfer data are the initial source of quantitative data on potential
chronic human exposure. However, the EPA has an open revision policy that allows TRI reporting
facilities to submit changes and corrections to their TRI data at any time. To avoid the effects of
these fluctuations on Indicator values, the TRI Indicators model extracts release and transfer data
during the two week period each year when EPA Headquarters "freezes" the data, that is, when no
changes are allowed.
To adjust releases and transfers to reflect exposure potential, several existing scoring systems
take the approach of ordinally ranking the volume of each release by some physical measure of the
chemical's ability to move through the environmental medium into which it is released. However,
because the exposure potential rankings would have different physical meanings for different
pathways, comparisons among different media would be difficult, and weighted releases from
different pathways could not be added to obtain a single indicator value.
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EXHIBIT 10. Aquatic Toxicity Matrix
BIOACCUMULATION(a)
Water
Solubility
(mg/1)
>1500
tftfstSiSsSI
s|SS|&l;|*8fl
^SSiS^'^isS'
>500 to
1500
25 to 500
<25
LogKow
<0.8
0.8-2
2-3.2
3.2-4.5
4.5-5.5
5.5-6.0
BCF (I/kg)
<1
1-10
10-100
100-1000
1000-10,000
>10,000
AQUATIC TOXICITY CATEGORY (ng/l)(b)
>1000
>1000,000
>1000
0.5
5
50
500
5000
50,000
100-1000
10,000-100,000
100-1000
5
50
500
5000
50,000
500,000
10-100
1000-10,000
10-100
50
500
5000
50,000
500,000
5,000,000
1-10
100-1000
1-10
500
5000
50,000
500,000
5,000,000
50,000,000
<1
<100
<1
5000
50,000
500,000
5,000,000
50,000,000
500,000,000
LC50
Acute AWQC
Chronic AWOC
Notes:
(a) If BCF values are available, they should be used; If not, log of the octanol water partition coefficient (log Kow) can be used for organic
contaminants. When neither of these measures can be used, the bioaccumulation potential can also be approximated by the water solubility of
the chemical. Note that Kow is not used for scoring if its value exceeds 6.0.
(b) The preferred numerical aquatic toxicity data to use for weighting are the Chronic Ambient Water Quality Criteria (AWQC). Acute AWQC
may be used if chronic values are not available. If neither of these values are available, the lowest LC50 may be used for scoring. As shown in
the table, HRS does not assign scores of 5 or 50 based on water solubility.
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In this methodology, comparisons across media can be made because a common
quantitative exposure measure for each medium is derived: an estimate of "surrogate dose" — a
measure related to the amount of chemical contacted by an individual per kg body weight per day.
Limited facility-specific data and the use of generic models (described below) prevent the
calculation of an actual dose.
To estimate the magnitude of exposure potential from TRI releases, a separate exposure
evaluation is conducted for each environmental medium to which chemicals are emitted. The
ideal derivation of a dose would involve a site-specific exposure assessment for each release
medium and for each exposure pathway. However, such an effort is well beyond the scope of this
project and well beyond the intended use of the TRI data. These data are frequently estimates of
emissions, not precise measured values. Notably, they are not estimates of environmental
concentrations that result from the emissions from the plant. Furthermore, reporting of extensive
site-specific information relevant for exposure modeling is not part of a TRI data submission. For
example, EPA Form R (Toxic Release Inventory Reporting Form) does not require submission of
data on groundwater flow, soil conditions, and other factors that affect groundwater
contamination from land releases. It is not the intent of this project to gather additional data or
measurements that would be needed to perform these calculations. The need to accurately reflect
exposure characteristics in the Chronic Human Health Indicator must be balanced by the need for
a simple and understandable Indicator that is easily communicated to the public and that is based
on currently available data. Therefore, in this methodology, the exposure evaluations combine
data on media-specific emission volumes, physicochemical properties and, where available, site
characteristics with site-specific or generic exposure models to determine an estimate of the
ambient concentration of contaminant in the medium into which the chemical is released. (Again,
the use of submitter-estimated TRI emission data and generic models with many default
assumptions make this only a surrogate related to actual environmental concentration). For the
Chronic Human Health Indicator, the ambient media concentrations are then combined with
standard human exposure assumptions to estimate the magnitude of the surrogate dose. The
physicochemical property data used for the exposure potential evaluation is found in Appendix D.
It must be emphasized that while this methodology uses the EPA exposure assessment
paradigm to evaluate exposure potential, the results should not be construed as an actual absolute
numerical estimate of dose resulting from TRI releases. Instead, the purpose is to obtain an order
of magnitude estimate of surrogate dose resulting from release of TRI chemicals relative to the
surrogate dose resulting from other releases included in the Indicator, so that these releases can
be weighted appropriately in the Indicator.
Another limitation to note is that products of decay are not modeled. Exclusion of these
decay products from the Indicators may underestimate or overestimate the risk impact of releases,
since the decay product may be more or less toxic than the parent compound.
25
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The exposure evaluation methods used for each type of release are specific to that type of
release and depend on the models and data available to evaluate that pathway. In some cases,
models will be combined with some site-specific data to estimate exposure; in other cases, generic
reasonable worst-case models may be used in the absence of any site-specific data. (Specific
pathway calculations are discussed below.)
Qualitative Data Used in Evaluating Chronic Human Exposure Potential
Consideration of uncertainly in the exposure evaluation is necessary for making
comparisons across pathways, since the exposure evaluation methods for various pathways differ
significantly in their possible level of refinement. For the purposes of calculating surrogate doses,
the following uncertainty categories have been defined for use in this methodology (Exhibit 11):
EXHIBIT 11. Uncertainty Categories for Evaluating Human Exposure Potential
Category
Explanation
Adjustment Factor
A
Combines modeling with some generic and
some reasonable site-specific data to generate
exposure estimates.
1
B
Combines modeling with some generic and
some site-specific data, but identification of
appropriate site-specific data subject to error
and will often be filled in with generic
assumptions.
C
Extrapolates generic exposure estimates from
actual data from other sites to exposure at TRI
sites (e.g., groundwater modeling).
10
The categories are defined so that surrogate dose estimates in a lower category are more likely to
overestimate exposure when compared to the next higher category. In general, surrogate dose
estimates are placed in lower categories when they are developed using generic models that
require many assumptions and extrapolations. These assumptions and extrapolations tend to be
conservative, so that more generic modeling tends to yield overestimates of exposure. The initial
surrogate dose estimate is reduced by a factor of 5 if assigned to category B, and by an order of
magnitude if assigned to category C.
26
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PATHWAY-SPECIFIC METHODS TO EVALUATE CHRONIC HUMAN EXPOSURE POTENTIAL
This section describes the algorithms for modeling exposure for each of the following
exposure pathways: (1) stack and fugitive air releases, (2) direct surface water releases, (3) on-
site land releases, (4) releases to POTWs, and (5) off-site transfers. An overview of the pathways
and methodologies used for each pathway is presented in Exhibit 12.
The following discussions of exposure modeling frequently mention concentration and
surrogate dose. This is not meant to imply that the risk assessment process can be supplanted nor
that cases can be accurately calculated. These terms are referred to only in the abstract. The
exposure algorithms are simple ways to gauge relative risks from releases to different media in a
congruent, defensible way. In some cases, the modeling will be purposely simple, given our lack
of site-specific data. The differences in the level of refinement of exposure modeling are
addressed by using the uncertainty weighting scheme discussed above.
GIS Basis Common to All Pathways
The algorithms for calculating surrogate doses rely on the ability to locate facilities
geographically (including those to which off-site transfer is made) and to associate their locations
with their demographic and physical characteristics. To accomplish this, the computer algorithm
describes the U.S. as a 1 km-by-1 km grid system. For each cell in the grid, the computer assigns
a location "address" based on latitude and longitude. It then assigns information on the
demographics and physical characteristics of that cell to that address. (Physical characteristics
include: wind speed and direction, the occurrence of a water body in the cell, and the flow rate of
such a water body). When a facility is located on the grid, the associated data for that location
are then automatically available for use in the modeling.
Stack and Fugitive Air Releases
Ideally, reported stack and fugitive air releases from the TRI database would be modeled
using site-specific data (such as stack height or source area). Because TRI does not contain such
facility-specific information, default values are used to model TRI facilities using established EPA
air dispersion models.
27
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EXHIBIT 12. Overview of Exposure Pathways
Stack and Fugitive
Air Release
Off-site
Transfer
On-site Land
Release
Release to
POTW
Direct Surface
Water Release
Incineration
Landfilling
Sludge
Effluent
Air Release
Methodology -
See Exhibit 13
Land Disp
Volatilization
- | to Air
osal
Groundwater
Methodology -
See Exhibit 17
Surface Water
Methodology -
See Exhibit 15
28
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This method uses an algorithm based on the Industrial Source Complex Long Term
(ISCLT) model developed by the Office of Air Quality Planning and Standards (OAQPS). ISCLT
is a steady-state Gaussian plume model used to estimate long-term pollutant concentrations
downwind of a source. The concentration is a function of site-specific parameters (stack height,
stack gas velocity) and chemical-specific air decay rates. To use the model, the facilities are first
located on the grid using their latitude and longitude coordinates. Next, their emission rates in
pounds per year are directly converted to grams per second by the following equation:
n -n 453-6 1
31,536,000
where:
Q = pollutant emission rate (g/sec),
q = pollutant emission rate (Ib/yr),
453.6 = constant to convert (Ib) to (g), and
31,536,000 = constant to convert (yr) to (sec).
These emissions rates are then used in the following equation that determines the concentration at
a distance r greater than 1 meter away from a point source:7
C
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For each facility in the TRI data set, a stack height of 10 meters8 is assumed to be located at the
latitude and longitude of the source.
Based on the ISCLT equations, concentrations are calculated at each of the 441 cells (21
km x 21 km total area, or 10 kilometers in each direction) nearest to the facility. The
concentrations are combined with standard assumptions regarding inhalation rate and human body
weight to arrive at a surrogate dosage:
DOSEair
BW
where:
DOSEair = surrogate dose of contaminant from air (mg/kg-day),
Cair = air concentration in cell (|ig/m3),
Iair = inhalation rate (m3/day),
BW = human body weight (kg),9 and
1000 = constant to convert (jig) to (mg).
These surrogate doses are then multiplied by the toxicity weight for the chemical and by the
population in the cell to arrive at an Indicator sub-element for each cell. If the total population in
the 441 surrounding cells is less than 1000 persons, then the number of persons in the cells is
adjusted such that the total population surrounding a facility is at least 1000. This is done to
avoid under-weighting rural communities. The overall indicator element for the chemical and
facility is determined by adding the sub-elements for all 441 cells. Exhibit 13 graphically describes
the air modeling portion of the Chronic Human Health Indicator, and Exhibit 14 lists the default
parameters for the air model.
For the air release pathway, a combination of generic inputs and reasonable site-specific
data (e.g., wind speed) are used. Therefore, we use uncertainty category A to classify the air
exposure potential.
Additional information is currently being collected on industry-specific stack heights; if possible, this information will
be incorporated into the model.
This method uses an average adult body weight (70 kg). For certain health endpoints (e.g., female reproductive effects),
a different body weight value may be more appropriate (e.g., average adult female body weight). However, for simplicity, the
method uses the average value for all endpoints.
30
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EXHIBIT 13. Calculation of Surrogate Dose and Indicator Element from
Stack and Fugitive Air Releases
Release
of TRI Chemicalc at Facilityf (Ib/year)
ISCLT algorithm
I Pollutant Concentration in Cellx (ug/m3) I
Standard Exposure
Assumptions
(Inhalation Rate,
Body Weight)
Surrogate Dose of Chemicalc for Cellx from
Facilityf (mg/kg-day)
Population Data
for Cellx,
Toxicity Weight
I Indicator Sub-element for Cellx from Facilityf I
Sum over All 441
Cells
Indicator Element for Air Release of
Chemicalc from Facilityf
31
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EXHIBIT 14. Air Modeling Parameters
Parameter
Stack height
Exit velocity
Stack diameter
Exit gas temperature
Area source size
Area source height
Decay rate
Body weight
Pollution emission rate
Frequency of wind speed and direction
Sector width
Wind speed
Smoothing function
Vertical term
Population-weighted average air cone.
Inhalation rate
Value
10m
0.01 m/s
1m
293 K
10m2
3m
varies by
pollutant
70kg
site-specific
site-specific
0.393 radians,
or 22.5°
site-specific
calculated
calculated
calculated
20 m3/day
Source/Comment
EPA (1992)
EPA (1992)
EPA (1992)
EPA (1992)
EPA (1992)
EPA (1992)
EPA Exposure Factors
Handbook (EPA, 1990a); value is
for adults; lifetime age-weighted
average (male and female
combined) is about 62 kg
TRIS (Ibs/yr)
STAR
3 60° divided by 16 wind
directions
STAR (m/s)
mg/kg-day
EPA Exposure Factors
Handbook (EPA, 1990a)
32
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Direct Surface Water Releases
As with the air pathway, the first step in assessing surface water discharges is to locate the
discharging facility on the grid. Facilities are matched to a waterbody within 6 kilometers based
on latitude and longitude. In the future, this match will be achieved using the NPDES (National
Pollutant Discharge Elimination System) numbers provided in TRI reporting. Direct surface
water discharges are assessed using a simple first-order decay equation along with water volume
and velocity estimates to calculate concentrations resulting from contaminant releases at a
distance x at time t. The pollutant-specific decay coefficient may be due to either abiotic
hydrolysis or microbial biodegradation; on occasion, it may be due to photooxidation. The
general form of the equation is as follows:
C =r\T P ^a"rt
^x uv-o
where:
Cx = concentration at distance x meters (mg/L) (up to 200 kilometers
from release point),
C0 = initial concentration (mg/L), which equals chemical release
(mg/day) divided by water flow volume (L/day),
kwater = decay coefficient (sec"1),
t = time at which Cx occurs (sec), which equals X/M, and
u = water velocity (m/sec).
This methodology considers two chronic human health exposure pathways from surface
water releases. First, exposures from drinking water are calculated. As the pollutant passes
through the stream network, concentrations at public drinking water intakes are noted. The
population served at each intake is assumed to be the population exposed to that concentration.
If a cell contains no drinking water intake, the exposed population is zero. The water
concentration in reaches with intakes is combined with standard exposure parameters to yield the
following surrogate dosage:
DOSEdw =D water'avg
BW
where:
DOSEdw = surrogate dose of contaminant in drinking water (mg/kg-day),
CWater,avg = population-weighted average water concentration (mg/L),
Iwater = drinking water ingestion rate (L/day), and
BW = human body weight (kg).
33
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The Indicator sub-element for individual reaches for the drinking water pathway is calculated
using the surrogate dose in the reach, drinking water population in that reach, and the toxicity
weight of the chemical. For the drinking water pathway, we use uncertainty category B for
exposure potential weighting for several reasons. First, the calculation of water concentrations
does not consider partitioning of the chemical between the water column and suspended solids,
settling of the suspended solids, volatilization of the chemical, or other processes that may affect
the fate and transport of contaminants along a surface water body. Furthermore, there is no
consideration of the removal of contaminants during treatment of drinking water at the utility.10
All of these factors would tend to inflate the exposure potential evaluation.
A second potential exposure pathway is from consumption of contaminated fish. Each
segment of the affected water body may contain contaminated fish which could be caught and
eaten by recreational fishers. As described above, the program tracks the concentration of the
chemical as it travels down the waterway; in each U.S.G.S. -defined stream reach, the
concentration in fish is derived by the following equation:
fish,reach water,reach
where:
Cf1Sh, reach = concentration in fish in the specified stream reach11, (mg/kg),
Cwater reach = average water concentration in the specified stream reach (mg/L),
and
BCF = bioconcentration factor for chemical (L/kg).
Next, the fish concentration value is combined with standard exposure assumptions regarding fish
consumption rates to determine the surrogate dose from this pathway:
fc BW
where:
DOSEfc = surrogate dose of contaminant (mg/kg-day),
Cfish = fish tissue concentration (mg/kg),
Ifish = fish ingestion rate (kg/day), and
BW = human body weight (kg).
Because specific data on people fishing in a reach are not available, the exposed
population is modeled as a percentage of the drinking water population. We derived state-specific
Removal of contaminants during treatment could be incorporated into the analysis if data are available.
UA stream reach is defined by the U.S.G.S. as the stretch of water between an upstream confluence and the next
downstream confluence. There is no constant length attributed to reach segments.
34
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fractions of persons who eat fish from state-specific fishing rates found in the U.S. Fish and
Wildlife Service's 1991 National Survey of Fishing, Hunting, and Wildlife Associated Recreation
(U.S. DOT, FWS, 1993). This estimate of exposed population, combined with the calculated
surrogate dose and the toxicity weight of the chemical, gives an Indicator sub-element for fish
consumption for each reach.
The total Indicator Element for surface water releases of a chemical from a facility is
calculated by adding the drinking water sub-element and the fish consumption sub-element for
each reach and summing over all reaches.
Exhibit 15 shows the recommended surface water approach for the Chronic Human
Health Indicator, and Exhibit 16 lists model parameters for surface water modeling.
For the fish consumption exposure pathway, the method uses uncertainty category C for
exposure potential for several reasons. First, as with the drinking water pathway, the estimated
water concentrations are probably an overestimate because the method does not consider all fate
and transport processes in surface water that affect concentrations. Second, fish tissue
concentrations are dependent on the type of species, particularly its lipid content and its position
in the food chain. Finally, the actual probability of recreational fishing in the particular stream
reach being modeled is unknown, as is the actual quantity offish consumed from that particular
reach.
On-site Land Releases
On-site land releases include releases to landfills, surface impoundments, land treatment
units and underground injection. This section describes methods to evaluate exposure from these
releases, except for underground injection. Under well-managed conditions, underground
injection facilities are designed to pose minimal risks to human health or the environment.
However, certain conditions can lead to the failure of these facilities and the release of chemicals
to the environment. An exposure analysis for these releases would have to include an evaluation
of the likelihood of the failure as well as a sophisticated hydrogeological evaluation of the
exposure impacts of such a failure. Such an evaluation is beyond the scope of this method; at
present, only the pounds of releases and transfers to underground injection releases are tracked in
the computer algorithm of the Indicator. Considerations for other approaches to including
underground injection in the Indicator are discussed in Appendix E.
Facilities releasing chemicals to land are located on the grid using latitude and longitude.
For these releases, two major exposure pathways are considered for on-site land releases:
chemicals may volatilize to air or leach to groundwater. Volatilization of chemicals from on-site
landfills is reported to TRI under the fugitive emission estimate for the facility and does not have
to be modeled (in contrast with volatile emissions from off-site landfills). Volatilization is thus
handled as a direct air release for on-site land releases.
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EXHIBIT 15. Calculation of Surrogate Dose and Indicator Element from
Surface Water Release
Release
of TRI Chemicalc at Facilityf (Ib/year)
Water Volume and Velocity
Estimates; Decay Equation
Pollutant Concentration in Surface Water Reachx (mg/L)
Bioconcentration
Factor
Standard Exposure
Assumptions
(Drinking Water Ingestion
Rate, Body Weight)
Pollutant Concentration in Fish in Reachx
(mg/kg)
Surrogate Dose from Drinking Water in
Reachx (mg/kg-day)
Standard Exposure
Assumptions
(Fish Ingestion Rate, Body
Weight)
Surrogate Dose from Fish Consumption
in Reachx (mg/kg-day)
Population
Served by
Drinking Water
Intakes in Reachx
(if any); Toxicity
Data
Drinking Water
Population in Reach
(if any) and
Statewide Data on
Recreational Fishers;
Toxicity Data
V
Indicator Sub-element for Fish
Consumption for Reachx
Indicator Sub-element for Drinking
Water for Reach
Sum over All Reaches and Both Pathways
Indicator Element for Surface Water
Release of Chemicalc from Facilityf
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EXHIBIT 16. Surface Water Modeling Parameters
Parameter
Decay rate
Dilution rate
Water volume and velocity
Population-weighted average
water concentration
Drinking water ingestion rate
Body weight
Average chemical concentration in
stream
Bioconcentration factor
Fish tissue concentration
Fish ingestion rate
Value
varies by pollutant
site-specific
site-specific
calculated
2 liters
70kg
calculated
varies by pollutant
calculated
0.0065 kg/day
Source/Comment
REACH (EPA, 1987)
REACH (EPA, 1987)
mg/L
EPA Exposure Factors Handbook
(EPA, 1990a)
EPA Exposure Factors Handbook
(EPA, 1990a); value is for adults;
lifetime age-weighted average
(male and female combined) is
about 62 kg
mg/L
L/kg
mg/kg
Exposure Factors Handbook
(EPA, 1990a)
37
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Groundwater contamination is also a concern for land releases. However, the modeling of
groundwater releases depends on the regulatory status of the unit in which the chemical is
released. Chemicals could be deposited in an on-site RCRA-regulated, subtitle C hazardous
waste unit, or in an on-site nonhazardous solid waste management unit. RCRA standards for
hazardous waste units are, by regulation, designed to include technical controls to prevent release
of contaminants into groundwater; if chemicals are placed in such regulated units, it is assumed
that releases to groundwater are negligible. If chemicals are placed in nonhazardous land disposal
units, we model the release of chemicals to groundwater. This analysis assumes that if the TRI
form reports a RCRA ID number for the facility, then the on-site land releases are assumed to go
to a RCRA hazardous waste regulated unit. Otherwise, the on-site land release is assumed to
occur in a nonhazardous land disposal facility. This assumption introduces additional uncertainty
to the analysis; some of the onsite disposal may go to a nonhazardous waste unit on the site.
However, the TRI reports shed no light on this matter, and the magnitude of the uncertainty
introduced is not known.
The TRI forms do not provide site-specific information that aids in the evaluation of
groundwater transport, such as hydrogeological data. Unfortunately, these data are extremely
site-specific and are not amenable to characterization by state or region of the country.
Nonetheless, to maintain a concentration/exposure measure consistent with the approaches for
direct air and water releases, we derive a surrogate dose using generic, conservative assumptions.
This approach requires two steps: estimating leachate concentration (a measure of the amount of
chemical that partitions from the waste to pore water) and estimating the dilution and attenuation
of leachate from the disposal site to the well location.
Leachate concentrations can be estimated using a modeling approach with chemical-
specific parameters. The general form of this estimate is as follows:
D£
where:
Q = chemical concentration in leachate (kg/L),
Cs = chemical concentration in landfill solids (mg/kg),
10"6 = constant to convert (mg) to (kg), and
Kd = chemical-specific soil/water partition coefficient (L/kg).
Since we lack data about how materials are disposed onsite, all onsite land disposal is assumed to
occur in landfills. It must be noted that the concentration in the leachate, Cb must be compatible
with the chemical-specific solubility (i.e. leachate concentration cannot exceed water solubility),
so the smaller of the two values is used.
38
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The average contaminant concentration in the landfill solids, Cs, can be estimated by
dividing the total mass of contaminant disposed (converted from pounds per year to mg per year)
by the total mass of waste disposed in the unit each year:
' A/.
where:
Mc = total mass loading of contaminant to landfill (mg per year), and
Mw = total mass of waste disposed in landfill (kg per year).
The value for Mc is available in the TRI database; the value for Mw is a national number taken
from an Agency source (EPA, 1988b). This report to Congress summarizes the distribution (by
number of facilities and by industry type) of the tons per year of waste disposed in industrial
nonhazardous solid waste landfills. Data are also reported for surface impoundments, waste piles
and land treatment facilities. These summaries are reproduced in Appendix F.
Once leachate concentrations are estimated, the next step is to determine the magnitude of
dilution and attenuation of contaminants that occur as the contaminant travels from the source to
the well. The Office of Solid Waste (OSW) performed an analysis of dilution and attenuation of
contaminants in groundwater during the development of the Toxicity Characteristic Leaching
Procedure (TCLP) rulemaking (55 (61) Federal Register 1 1798). For that rule, OSW used
Monte Carlo analysis to evaluate dilution and attenuation factors (DAFs) for 44 chemicals. In the
Monte Carlo analysis, multiple iterations of a groundwater model were performed. For each
model run, model parameter values were drawn randomly from their distributions.12 The result of
the analysis was a distribution of model results, where each model result was a DAF. OSW then
selected the 85th percentile DAF for use in its regulatory calculations. For most chemicals
modeled, the 85th percentile DAF was approximately 100. For this methodology, we use a DAF
of 100 to estimate groundwater contaminant concentrations at the well due to contaminant
leaching from on-site land releases. The concentrations are then used to calculated surrogate
doses as shown below. Because OSW's DAFs do no reflect the effect of groundwater pumping
on the concentration of chemicals in groundwater, the calculation of TRI surrogate dosages is
oversimplified.
Distance to the well was one of the parameters varied in the analysis: the distribution of distance between a source and
a well was derived from a survey of Subtitle D facilities.
39
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C =D-- -DlO6
gw 100
where:
Cgy, = concentration in groundwater (mg/L),
Q = concentration in leachate (kg/L)
100 = dilution and attenuation factor (unitless), and
106 = constant to convert (kg) to (mg).
The surrogate dose for exposure to contaminated groundwater from the facility is
calculated as follows using standard exposure assumptions:
C -D/
DOSE =
BW
where:
= surrogate dose of contaminant in groundwater (mg/kg-day),
C^ = concentration in groundwater (mg/L),
Iwater = drinking water ingestion rate (L/day), and
BW = human body weight (kg).
The population exposed to contaminated groundwater is calculated from the number of
persons receiving drinking water from groundwater within one kilometer of the facility. The
population of persons served by well water is available for each county from the National Well
Water Association data files. From these data, we can derive a "well water drinker" population
density for each county (i.e., the percent of persons in the county who drink well water). This
density is multiplied by the number of persons living within one kilometer of the landfill site to
obtain the exposed population. [It is of course possible that chemicals migrate beyond one
kilometer of the site, so this assumption may underestimate the population exposed. However,
this is a typical distance for groundwater modeling that reflects the distances at which important
parameters such as DAFs are derived. Confidence levels are lower at greater distances.] The
Indicator Element for the groundwater pathway for the chemical is calculated by combining the
surrogate dose, exposed population, and toxicity weight of the chemical. Off-site landfills are
similarly modeled.
40
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A summary of the values used in the groundwater calculation and the sources of these
values appear in Exhibit 17. The approach to evaluating exposure from on-site land disposal for
the Chronic Human Health Indicator is summarized in Exhibit 18.
EXHIBIT 17. Groundwater Modeling Parameters
Parameter
Concentration in leachate
Partition coefficient
Value
calculated
varies by
pollutant
Source/Comment
mg/L
For the groundwater pathway, we use uncertainty category C, because the exposure
estimate is based on a conservative, steady-state estimate of leachate concentration and on a
conservative, generic dilution and attenuation factor.
Releases to POTWs
In 1991, 311 million pounds of TRI chemicals were discharged to the country's Publicly
Owned Treatment Works (POTWs) compared with 271 million pounds discharged directly to
surface waters. Modeling exposure from TRI discharges to POTWs requires: (1) location of the
POTW to which the chemicals are discharged, (2) consideration of overall removal efficiencies of
POTWs and resulting effluent discharges from POTWs, and (3) consideration of residuals
management at POTWs:
•D Location of the POTW. The latitude and longitude of POTWs receiving TRI transfers are
not included in the TRI data base. However, the ZIP codes for the POTWs are available.
For a given facility, the POTW is located on the grid based on the latitude and longitude
of the ZIP code centroid.
•D Overall POTW removal rates. POTWs cannot remove completely all of the chemicals in
the influent; some of the chemical loading in the influent will be released in the POTW
effluent. To calculate the fraction of transferred chemical removed by the POTW, the
overall typical POTW contaminant removal rate for that chemical is applied to the transfer
volume.
•D Partitioning within the POTW. Chemical loadings may be removed by the POTW
treatment processes through biodegradation, volatilization, and adsorption to sludge.
Using average removal and partitioning rates, chemicals within POTWs are partitioned
among effluent, biodegradation, air and sludge.
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EXHIBIT 18. Calculation of Surrogate Dose and Indicator Element from
On-site Land Releases
On-site Land Release
of TRI Chemicalc at Facilityf (Ib/year)
Volatilization
Reported under Fugitive Emission
Estimate; Handled as Air Release
V
Groundwater Methodology
Deposition in I I
Nonhazardous J L
Unit \ /
Deposition in
RCRA Hazardous
Waste Unit
Release to Groundwater
Partitioning Data and
Industry Average Waste
Volume Data
No Release to
Groundwater Assumed
Leachate Concentration (kg/L)
EPA/OSW Monte
Carlo Analysis of
Dilution and
Attenuation Factors
Pollutant Concentration in Groundwater (mg/L)
Standard Exposure
Assumptions
(Drinking Water Ingestion
Rate, Body Weight)
Surrogate Dose of Chemicalc from Facilityf
(mg/kg-day)
Well Water-Drinking
Population within 1 km of '
Facility; Tox. Data
Indicator Element for On-Site Land Releases
of Chemicalc from Facilityf (mg/kg-day)
42
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Various data bases and literature references were used to estimate typical POTW removal
efficiencies and within-POTW partitioning rates for many TRI chemicals. The references and
methods used for each chemical are described in Appendix D.
Once the fates of chemicals entering the POTW are estimated, the exposure levels
associated with chemical loadings to each compartment will be estimated. Chemicals discharged
in the POTW effluent are modeled using the surface water evaluation methods described above.
Chemicals that biodegrade are assumed to degrade to chemicals that do not pose risk. POTW
volatilization releases are treated like area-source air releases, as described above.
For chemicals that partition to sludge, the model used to estimate exposure should ideally
depend on the sludge disposal method employed by the POTW. However, sludge disposal
practices at a POTW receiving a TRI transfer cannot be determined from the TRI database.
Therefore, the TRI Environmental Indicators algorithm currently models all POTW sludge as
being landfilled at the POTW, a common method of sludge disposal. Landfilling of sludge is
modeled as a land release using methods described above. Populations surrounding the POTW
are modeled as the exposed population. POTWs may in reality use other methods of sludge
disposal, such as incineration of sludge. If sludge were incinerated by a POTW, for example, this
would result in different exposure levels and a different, larger exposed population.
The uncertainty-adjusted indicator sub-elements from POTW effluent, volatilization at the
POTW, volatilization of land disposed sludge, and groundwater contamination from land-
disposed sludge are combined to yield a single facility-chemical-POTW transfer Indicator
Element.
A summary of the approach to modeling POTW emissions used to calculate the Chronic
Human Health Indicator is found in Exhibit 19.
Off-site Transfers
In 1993, over 42 percent of TRI emissions were transferred to off-site locations for
storage or disposal. TRI reporters are required to supply the name and address of the receiving
facility. From these data, we must determine if wastes are sent to a hazardous or nonhazardous
waste management facility. Submissions indicating transfer to a RCRA hazardous waste facility
are not included in the Chronic Human Health Indicator; as described above, RCRA standards for
hazardous waste units are, by regulation, designed to include technical controls to prevent release
of contaminants into groundwater. If chemicals are placed in such regulated units, it is assumed
that releases to groundwater are negligible. Therefore, only transfers to nonhazardous facilities
are modeled.
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EXHIBIT 19. Modelling of Exposure from POTW Releases
Release to Designated POTW
of Chemicalc from Facilityf (Ibs/year)
POTW Located via ZIP Code Centroid
POTW Removal
Rate
POTW Residual (Fate Determined by Partitioning Rate)
Biodegradation
No Risk Assumed
Sludge - Deposition
in POTW On-Site
Landfill Assumed
POTW Effluent
Volatilization
Handled as On-Site Land
Release at POTW - See
Groundwater Methodology in
Exhibit 17
Handled as Air
Release
at POTW -
See Exhibit 13
Handled as Surface
Water Release
at POTW -
See Exhibit 15
Combined with Pathway-Specific Toxicity Weights
and Exposed Populations
Indicator Sub-element for a
specific POTW Release of
Chemicalc from Facilityf for
Groundwater
Indicator Sub-element
for a specific POTW
Release of Chemicalc
from Facilityffor
Volatilization
Indicator Sub-element
for a specific POTW
Release of Chemicalc
from Facilityffor
Surface Water
Indicator Element
44
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As with POTW transfers, to assess the exposure potential associated with off-site
transfers, we must have information about the off-site facility location and some of its
characteristics. The ZIP code for the off-site facility is contained in the TRI data base; we locate
the facility using the ZIP code centroid. Once we have located the off-site facility, the Indicators
methodology requires: (1) the regulatory status of the unit to which the material is transferred,
and (2) the treatment/disposal technologies used by the off-site facility.
The TRI forms require the reporting facility to indicate the treatment/disposal method
used at the off-site facility. If this information is not reported (despite the requirement), the
transfer is not evaluated in the algorithm, but is flagged as a missing value and assigned a zero.
Once the treatment method is established, we model exposure potential using the methods
described above. If the treatment method is incineration, then destruction and removal
efficiencies (DREs) are applied to the transfer amount. For organics, the DREs are assumed to be
99 percent, except for PCBs, which are assumed to have a DRE of 99.9999 percent, as required
by TSCA regulation. For inorganics, values are taken from multiple hearth sludge incinerator
studies (EPA, 1993). Once DREs have been applied, the releases are modeled using air modeling
algorithms described above.
For off-site landfills, two major exposure pathways are considered. The groundwater
pathway is modeled for off-site releases in the same manner as for on-site land releases.
Volatilization, however, is modeled differently. For on-site releases, volatilization is included in
reported fugitive emissions and thus exposure is modeled with on-site air releases. In contrast,
for off-site land releases, volatilization emissions from land disposal must be estimated before
exposure can be modeled.
The first step in estimating volatilization emissions is to estimate the concentration of
chemical in the liquid phase (i.e., leachate). This equation was given earlier in the "On-site Land
Releases" section:
where:
C, = concentration in leachate (liquid phase) (kg/L),
Cs = concentration in landfill solids (mg/kg),
10"6 = constant to convert (mg) to (kg), and
Kd = soil/water partition coefficient (L/kg).
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The second step is to estimate the vapor phase concentration from the liquid phase
concentration using the chemical's Henry's Law constant (the ratio of the chemical concentration
in the vapor to the concentration in the liquid phase):
C =UH C,
v i
where:
Cv = contaminant concentration in vapor phase (kg/L),
Q = contaminant concentration in leachate (liquid phase) (kg/L), and
H = Henry's Law Constant (dimensionless).
Once the contaminant vapor concentration has been estimated, the flux of volatilizing contaminant
may be estimated as:
Vol Flux =0tvo/ -DCv -DlO3
where:
Vol Flux = flux of volatilizing contaminant (kg/m2-sec),
kvol = contaminant volatilization transfer velocity (m/sec),
Cv = contaminant concentration in vapor phase (kg/L), and
103 = constant to convert (L) to (m3).
The volatilization transfer velocity, or speed at which a contaminant is transported through a
stagnant air layer immediately above the land disposal site, is taken from an EPA (1985) equation
for uncovered landfills:
, 0.17 u (0.994)
*vol ~
(T -020)
JMW
where:
0.17 = an empirical constant,
u = wind speed (m/s),
T = ambient air temperature (°C), assumed to be 15 °C,
MW = molecular weight (g/mol), and
0.944 = an empirical constant.
These formulae may be combined to express the volatilization flux as a function of the
contaminant concentration in the solid phase:
0.17 u (0.994)(r~20) H C 10~3
Vol Flux = s-
Kd
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This flux estimate of volatilizing chemical is multiplied by an estimate of the area of the
landfill to obtain an estimate of total emissions (mass per time). These emissions are then
combined with weather data and data on populations surrounding the off-site disposal facilities to
obtain population-weighted concentrations, using the same algorithms as those used for direct air
releases from TRI facilities. Exposure uncertainty category C (that is, a factor of 10) is used for
this pathway, because substantial assumptions and modeling are required to derive the exposure
potential estimate. The data on population surrounding the off-site facility are extracted using the
ZIP code of the off-site facility. Volatilization parameters are summarized in Exhibit 20.
EXHIBIT 20. Volatilization Modeling Parameters
Parameter
Kd
Molecular weight
Henry's Law constant
Average area of source:
municipal solid waste landfill
Median area of source:
industrial nonhazardous land
disposal
Mean wind speed
Value
varies by pollutant
varies by pollutant
varies by pollutant
32.5 acres
landfill: 3 acres
surface impoundment: 0.5 acres
land treatment: 15 acres
waste pile: 0.5 acres
site-specific
Source/Comment
Chemical properties
database (Appendix
D)
Chemical properties
database (Appendix
D)
Chemical properties
database
(Appendix D)
EPA(1988c)
EPA (1988d)
m/s; from STAR
data
The resulting sum of the uncertainty-adjusted indicator sub-elements from incineration,
volatilization and groundwater exposures yields the facility-chemical-off-site transfer Indicator
Element.
Exhibit 21 presents a summary of the method used to model off-site transfers.
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EXHIBIT 21. Modeling of Exposure from Off-site Transfers
Transfer to Off-site Facility
of Chemicalc from Facilityf (Ib/year)
Off-site Facility Located via ZIP Code
Transfer to
Nonhazardous
Waste Facility
Treatment Method Determined from TRI Form
Transfer to RCRA
Hazardous Waste
Facility
No Risk Assumed
Incineration
Landfilling
OSW
Analysis of
Destruction
and Removal
Efficiencies
Potential
Groundwater
Contamination
Chemical
Partitioning
Data; Wind
Speed Data
Air Release Estimate
Volatilization Rate
Handled as Air Release
- See Exhibit 13
Handled as On-site Land
Release - See Ground-
water Methodology in
Exhibit 17
Handled as Air Release
- See Exhibit 13
Combined with Pathway-Specific Toxicity Weights
and Exposed Populations
dicator Sub-element
fi ir a specific Off-site
Transfer of Chemicalc
from Facilityffor
Incinerators
Indicator Sub-element
for a specific Off-site
Transfer of Chemicalc
from Facilityffor
Groundwater
Indicator Sub-eleme: it
for a specific Off-sil 3
Transfer of Chemica
from Facilityffor
Volatilization
Indicator Element
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EVALUATING ECOLOGICAL EXPOSURE POTENTIAL — GENERAL STRATEGY FOR AQUATIC
SYSTEMS
The estimated ambient water concentration value is used directly to evaluate potential
exposures to aquatic life. The method for evaluating ambient surface water concentrations
resulting from TRI releases is discussed above. Since the Chronic Ecological Indicator includes
only one exposure pathway, there is no reason to use an uncertainty adjustment for cross-pathway
uncertainty. Therefore, these surrogate values are used directly as the exposure potential for
aquatic life.
V. METHODS TO ADJUST FOR SIZE OF POPULATION EXPOSED
ESTIMATING POPULATION SIZE AND REPRESENTING RURAL POPULATIONS
Several options were considered for including the size of potentially exposed human
populations in the Chronic Human Health Indicator. One option was to use the absolute
population numbers, if reliable population data are available for an area. However, for small
populations, the method uses rounded numbers rather than absolute numbers to avoid
undervaluing potentially high impacts on rural populations. Using rounded numbers assures small
populations of a minimum weighting. In effect, this inclusion gives more weight per capita to
small populations.
For the air pathway, the Chronic Human Health Indicator method rounds exposed
populations below 1000 persons up to a value of 1,000. For the surface water pathway, the
minimum population size is 10, while for groundwater, the minimum population size is 1.
The determination of the size of the population exposed to TRI releases and transfers
varies substantially depending on the medium to which the chemical is released. The methods for
estimating the size of the exposed population are discussed for each pathway in chapter IV.
The method uses the most current Census population information (1990); thus, impacts to
future populations are not modeled. For the groundwater pathway, modeled concentrations at
the well could occur far in the future; in most cases, releases would not reach the point of
exposure (i.e., the well) during the given year of TRI reporting. In this case, these future
exposures are matched to the current population size. At present, the same population definition
is applied to each year of TRI reporting, but project staff are attempting to define estimates of
population between major (decennial) census dates.
Because of major difficulties in estimating sizes of the populations of ecological receptors,
the TRI Ecological Indicator does not include a population weight. In effect, this approach
assumes that all aquatic emissions occur in equally vulnerable locations. In actuality, the
populations may differ among areas; thus, the Indicators method may either underestimate or
overestimate impacts in a given area.
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VI. COMPUTING THE INDICATORS
This section of the report summarizes the actual computation of the TRI Environmental
Indicators and the adjustments that will be made to the Indicators when chemicals or facilities are
added to or deleted from the original set of TRI chemicals and facilities. The methods of
calculating the Indicators are presented first; subsequent discussion focuses on methods to
accommodate additions/deletions of both chemicals and facilities to the Indicators.
INTEGRATING TOXICITY, EXPOSURE, AND POPULATION ADJUSTMENTS TO OBTAIN
INDICATOR ELEMENTS
Chronic Human Health Indicator
The previous chapters described how each component of the Chronic Human Health
Indicator (toxicity, exposure potential, population size) is developed as an input to the calculation
of Indicator elements. The following equation shows how these components are combined to
obtain a facility-chemical-medium specific element:
Indicator Elementcfm =\HToxicity Weightcm -[^Surrogate Dosecfm -[^Population.
where:
c = subscript for chemical c,
f = subscript for facility f, and
m = subscript for medium m.
The components are multiplied because each component of risk (toxicity, exposure, and
population) contributes in a multiplicative way to the overall magnitude of the impact. The result
of the multiplication of the components is a facility-chemical-medium-specific "Indicator
Element." This element should be considered unitless, because each of the components (the
toxicity weighting, surrogate dose and population) are all used as unitless weights, that are
relevant only when compared to each other. It is reiterated that this unitless element is not a
physically meaningful measure of quantitative risk associated with the facility, but is an
approximate measure of relative risk impacts that is comparable to approximate measures for
other facilities calculated using the same methods.
For chemicals with cancer effects, multiplying the weights associated with cancer toxicity
and exposure to the chemical seems intuitive, since this is similar to the calculation of cancer risk
with a slope factor or unit risk value and dose or exposure level. However, for chemicals with
noncancer effects, the multiplicative nature of the toxicity and exposure weights may not seem
intuitive, because in risk assessments, risk is usually characterized as the estimated exposure
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divided by the RfD. However, because of the manner in which the toxicity weights have been
constructed, the product of toxicity weight and surrogate dose varies in the same direction and
degree as the ratio of exposure to RfD. This is because the toxicity weight is inversely related to
the magnitude of the RfD. Thus, for a given exposure level, a chemical with a more stringent
(i.e., lower) RfD will receive a higher Indicator value than a chemical with a less stringent (i.e.,
higher) RfD, as shown in the following example:
EXHIBIT 22. Example of Weighting for Noncancer Effect
Scenario 1
Scenario 2
RfD
(mg/kg-day)
0.1
0.01
Toxicity
Weight
10
100
Surrogate dose
(mg/kg-day)
1
1
Exposure/RfD
Ratio
1/0.1 = 10
1/0.01 = 100
Toxicity
Weight *
Surrogate
Dose
10*1 = 10
100*1 =100
In addition, since no adverse effects are expected to occur below the RfD, one could argue that
releases which result in surrogate doses below the RfD should be excluded from the Indicator.
However, this approach was not pursued for the following reasons: first, the estimation of
surrogate dose is only a crude approximation for the purposes of comparing one release to
another in a relative way, and should never be considered an actual estimate of exposure. To
exclude releases resulting in surrogate doses below the RfD would incorrectly imply that the
method could predict precisely when doses would occur below the RfD. Second, exposure to the
same chemical from multiple facilities, or multiple chemicals from one or more facilities affecting
the same health endpoint could act additively to pose risk, even if each release individually did not
result in an exceedence of the RfD. Finally, it should be kept in mind that the if the surrogate dose
is low, this will be reflected by a correspondingly low score relative to other releases for that
chemical in the Indicator.
Chronic Ecological Indicator
The methods for determining aquatic toxicity weight and surrogate dose were described in
previous chapters. Again, effects on terrestrial wildlife are not considered in this Indicator. The
following general equation combines these components for each facility and each chemical (only
the water medium is evaluated):
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Indicator Element cf =\HToxicity Weight c -[^Surrogate Dosecf
where:
c = subscript for chemical c, and
f = subscript for facility f
As with the Chronic Human Health Indicator, the components are multiplied in this setting
because each component (toxicity and exposure) contributes multiplicatively to the overall
magnitude of the impact. The result of the multiplication of the components is a facility-chemical-
water-specific "Indicator Element." As with the Indicator Elements of the Chronic Human Health
Indicators, these Chronic Ecological Indicator Elements should not be interpreted as actual
quantitative measures of risk.
COMBINING ELEMENTS TO OBTAIN THE OVERALL INDICATORS
For both the Chronic Human Health Indicator and the Chronic Ecological Indicator, the
overall Indicator value is calculated by combining the individual TRI chemical-facility-media
Indicator elements. A simple sum of the component scores is used:
where:
I = TRI Environmental Indicator of interest and
Ec f m = facility-chemical-medium-specific Indicator Element.
As many as 400,000 Indicator Elements for a given reporting year for the TRI will be
summed to yield just one year's score for a specific TRI Relative Risk-Based Environmental
Indicator (e.g., the Chronic Human Health Indicator). In this method, each component score
makes a contribution proportional to its size. The resulting Indicator value can be used in a
number of ways, including tracking changes over time. For this purpose, one of the early years of
TRI reporting is selected as the "base year" (e.g., 1988) and later years' Indicator values
compared to it. For the base year, the unitless score is scaled to a convenient round number such
as 100,000 by dividing the base year Indicator value by itself and multiplying by 100,000;
subsequent years' data would be scaled by the same factor to provide a relative comparison. The
magnitude of the final number to which the score is scaled depends on the size of the year to year
change in the Indicator value, since very small changes in the basic Indicator would not be as
discernable if the scaling number chosen for the base year is too small. It must be reiterated that
while changes in scores over the years would imply that there have been changes in environmental
impacts, the actual magnitude of the risk increase or decrease is unknown in absolute terms.
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This approach considers together impacts from all types of health risks and exposure
pathways. For example, impacts from releases for chemicals with cancer effects are not
considered separately from those with noncancer effects. Because the Indicators model is a
screening tool to be used for priority-setting, among other objectives, it is desirable to have an
overall measure that integrates considerations of the impacts of releases, rather than having
multiple disaggregated measures. However, the computer algorithm also allows the user to
disaggregate the Indicator according to different attributes of the risk-related impacts. Therefore,
particular users can examine different aspects of the impacts that are of interest to them.
Other Methods of Calculation Considered
Alternative means of calculating the Indicators were considered, as discussed in Appendix
G. Some of these included the arithmetic mean of the Element scores, the geometric mean of the
scores, and the least-square difference of the scores. Each of these methods generates a score
that will fluctuate as the individual components of the Indicator fluctuate. However, the methods
do not produce readily interpretable results, and detecting fluctuations is less obvious than with
more straightforward methods. To avoid aggregating element values to the point where
important changes are not discernable, as well as for the greatest ease in calculation and
interpretation, OPPT has concluded that the chemical-facility-media specific elements should
simply be added and then adjusted to a manageable level.
USING THE INDICATOR APPROACH TO INVESTIGATE ENVIRONMENTAL JUSTICE ISSUES
When calculating the full TRI Relative Risk-based Chronic Human Health Environmental
Indicator, each Indicator Element is keyed to the facility from which the release is emitted, rather
than the location where the impact of the release(s) occurs. The Indicator is designed in this
manner so that all risk-related impacts from a given facility or set of facilities can be tracked.
Because the Indicator is oriented toward tracking facilities, an analyst can use it to identify
industrial sources that pose the relatively greater risk-related impacts, to examine changes in the
performance of industrial sectors over time, and to suggest priority industrial sectors for further
environmental management policies.
Another useful way to consider the impacts of TRI releases is to evaluate the total impacts
from all facilities that affect a given geographic location. This orientation allows the analyst to
assess risk-related environmental impacts of multiple releases on a given population. Combined
with additional demographic information on affected populations, such as race, income,
educational level, or age, the Indicator can be used to investigate environmental justice issues
related to the distribution of environmental impacts across segments of the population.
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When using the Environmental Justice Module to examine a defined geographic area, Grid
Cell Elements are calculated separately for each location where the impact of a TRI release
occurs. In the Indicator algorithm, the U.S. is divided into a grid of 1 km by 1 km cells: Grid
Cell Elements are calculated for each release in each grid cell where an impact occurs13'14:
Grid Cell Elementcf m =\HToxicity Weightcm -[^Surrogate Dosecf m -[^Population
where:
c = subscript for chemical c,
f = subscript for facility f,
g = subscript for grid cell, and
m = subscript for medium m.
When using the Environmental Justice Module, the user has the option of examining
discrete Grid Cell Elements, aggregated Grid Cell Elements or averaged Grid Cell Elements to
investigate the relative risk-based impacts on either the defined population or, for comparative
purposes, populations in distinct geographic areas.
To implement such calculations in the current version of the Indicators computer program,
the analyst must first define a geographic area(s) of interest (creation of a subset is currently
necessary because of computer memory limitations). The defined geographic area can measure up
to approximately 2500 km2.
Once the geographic area of interest is defined, the model looks for facilities within the
defined region, and any facilities 10 km outside the border of the defined region in any direction.
The 10 km distance is used because it is the current distance to which air releases are modeled
within the Indicator computer model. By including facilities within a 10 kilometer buffer, the
model can account for air releases originating outside of the defined region but affecting cells
within the defined region. In this instance, the term "facility" refers to both TRI reporting
facilities, and any facilities that receive transfers from TRI reporting facilities, such as POTWs or
waste treatment facilities. The Grid Cell Elements are then calculated for each grid cell-facility-
chemical-medium combination. Summing across chemicals, facilities and media for each grid cell
gives a value representing the total risk-related impacts in that grid cell.
The sum of the Grid Cell Elements for a given chemical release to a single media by a single facility would equal the
Indicator Element routinely calculated by the Indicator algorithm.
For those instances when Grid Cell Elements are to be exported for use in a GIS model containing a census data base
the population weight is omitted.
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This description of the Environmental Justice Module applies only to investigation of
impacts from air releases, and transfers that result in air emissions, but the capability for
evaluating impacts of additional release media can also be developed. The computer algorithm is
currently being revised to include the capability to investigate environmental justice issues related
to air impacts, and may be revised later to include other pathways.
SCALING THE INDICATORS FOR CHANGES IN TRI REPORTING
When a change occurs in the number of chemicals and facilities represented in TRI, the
numerical value of the Indicators will certainly be altered if no adjustments are made to the
method of calculation to account for the changes. However, such changes would not necessarily
represent a sudden change in actual environmental impact, but rather would reflect a broader
understanding of the impacts that had existed all along. To maintain comparability in the
Indicators' scores over time, the Indicators would have to be adjusted in some manner when such
modifications in reporting occur.
A change in the number of chemicals and facilities in TRI can occur through several
mechanisms. First, the addition to or deletion of chemicals from the TRI chemical list will occur
as EPA responds to petitions or initiates its own action through the chemical listing or delisting
process. Several additions and deletions to the dataset have already occurred since 1987, the first
year of TRI reporting. Furthermore, as mentioned earlier, in November 1994, the Agency added
245 chemicals and chemical categories to the TRI chemical list, effective for the reporting year
1995. The deletion of chemicals would presumably have a minor effect since such chemicals
would be deleted due to their low risk; these chemicals are likely to make only a minimal
contribution to the Indicators.
Compliance with TRI reporting has improved over time. Effective for the 1998 reporting
year the addition of certain SIC codes to TRI has also been approved, adding to the universe of
reporting facilities15. Increases in the number of reporting facilities may also occur as a result of
changes in reporting requirements. For instance, in first two years of reporting, facilities that
manufactured or processed more than 50,000 pounds were required to report their releases.
However, EPCRA lowered this threshold to 25,000 pounds in 1989. All of these modifications
can act to alter the total emissions reported under TRI and the Indicator's estimate of the
associated relative risk-based impacts.
To account for changes in the representation of chemicals and facilities in the TRI data
base, the TRI Environmental Indicators method may create new Indicators when significant new
This facility expansion rule will require the affected facilities to report their releases in the year 2000 for the 1998
reporting year. The affected SIC codes are: codes 10 (except 1011, 1081, and 1094), 12 (except 1241), industry codes 4911,
4931 and 4939 (limited to facilities that combust coal and/or oil for the purpose of generating power for distribution in
commerce, 4953 (limited to facilities regulated under RCRA), 5169, 5171, and 7389 (limited to facilities engaged primarily
in solvent recovery services on a contract or fee basis) (U.S. EPA 1997a).
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additions are made to the TRI chemical list. "Significant" additions could be several minor
additions that have been made over the course of a few years that eventually constitute a
significant change, or a single major influx of new chemicals (due to Congressional or Agency
action, for example). These new Indicators would include both old and new chemicals and
facilities. However, to track trends for the initial set of chemicals and facilities, EPA would also
retain a separate Indicator consisting of only the "original" facilities and chemicals. The Work
Group considered a variety of other options to adjust for additions to the set of chemicals and
facilities; details of these options, and their advantages and disadvantages, are found in Appendix
G.
While deletions from the TRI chemical list probably would not result in any significant
change to the Indicator value in most cases, the possibility of a change in Indicator value due
solely to deletions in the year the deletion takes effect, makes adoption of adjustment methods
important. Thus, when major deletions occur, the Indicator will be recomputed, excluding
deleted chemicals in all years.
Finally, the yearly TRI reporting data for a given list of chemicals and facilities are the
subject of ongoing quality control review and revision. As a result, yearly comparisons could be
flawed if ongoing revisions by individual facilities were not included in each year's Indicator.
Therefore, the TRI Environmental Indicator will be recomputed for all years in the data base on
an annual basis in order to incorporate revisions to the reporting data.
GENERATING "SUBINDICATORS"
In addition to computing an overall Indicator, the individual Indicator Elements can be
combined in numerous other ways for further analysis. The detailed calculations used to create
the Indicator Elements allow computation of "subindicators" for individual chemicals, geographic
regions, industry sectors, facilities, exposure pathways and other parameters. These
subindicators, like the overall Indicator, cannot be compared to some absolute level of concern,
but can help identify the relative contribution of various components to the overall estimate of
relative risk-based impacts of emissions. The ability of users to create these "subindicators"
makes the TRI Environmental Indicators system a powerful tool for risk-based targeting,
prioritization and policy analysis.
VII. CURRENT IMPLEMENTATION OF THE INDICATORS METHOD
COMPUTER PROGRAM TO CALCULATE THE INDICATORS
The TRI Chronic Human Health Indicator is currently implemented in a Microsoft
Windows-based, stand alone PC computer program. The program allows users to calculate the
overall Chronic Human Health Indicator for all years of data and to present the results in various
graphical and tabular formats, as well as save selected data to spreadsheet and data base formats
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(e.g., Microsoft Excel and dBase). The computer program also allows the users to specify
particular subsets of data, for the creation of "subindicators." The program includes on-line help
for all of the program functions. The program will be documented in the [TRI Environmental
Indicators computer program documentation]. A User's Guide will also be made available.
CHEMICALS AND FACILITIES CURRENTLY INCLUDED IN THE INDICATORS
Conceptually, the Indicators method is intended to include all chemicals that are reportable
to the Toxics Release Inventory. However, for the current version, some chemicals are excluded
because they have not yet been assigned toxicity weights (many of those have little or no reported
emissions) or are missing physicochemical data. Currently 345 of the 656 TRI chemicals listed as
of the 1995 reporting year have been assigned toxicity scores; 296 of these are based on IRIS and
HEAST values and 49 based on expert review within OPPT. Scoring for all of the current TRI
chemicals is discussed in the Toxicity Weighting Summary Document (EPA, 1997) and is
summarized in Appendix C of this document. The evaluation of TRI chemicals with regard to
aquatic toxicity will have to be conducted when the TRI Ecological Indicator is implemented.
In designing the TRI Chronic Human Health Indicator method, the use of a subset of
chemicals and/or facilities was considered. There may be reasons to exclude certain facilities from
the Indicators. For example, the reliability of reporting from certain facilities may be
questionable. There may also be concerns about the resource and computing requirements for
including all facilities in the Indicators. Ultimately, based on the recommendation of the peer
reviews, the Work Group decided to include all facilities emitting chemicals reportable to the
Toxics Release Inventory, since there were substantial difficulties in ensuring the selection of a
representative set of facilities.
VIII. ISSUES FOR FUTURE CONSIDERATION AND CONCLUSIONS
There are two general types of issues to consider for future effort: specific methodological
issues for the Indicators developed to date, and development of additional Indicators. The
methodological questions associated with the Indicators developed to date include the following:
•D how to compute the Acute Human Health and Acute Ecological Indicators given the
current reporting under TRI;
•D extending the Ecological Indicator beyond consideration of only aquatic life;
•D whether severity of effect should be considered in the toxicity score for a chemical;
•
D for off-site transfers, how to better match TRI transfers to particular treatment practices
(e.g., which TRI chemicals are sent to hazardous or nonhazardous waste management
facilities; or which specific treatment practices are used at which POTWs);
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•D how to incorporate information and/or estimates on changes in population for each year
rather than using 1990 Census data for all years; and
•D how to estimate the potential impact of non-landfill, non-incineration treatment (e.g., land
application).
The flexibility of the current TRI Environmental Indicators method and computer program
allows accommodation of data from other sources besides the TRI data base. With additional
data, the system could be used to develop additional Indicators that provide information on
measures of environmental impacts other than risk alone. For example, an Indicators model that
explicitly incorporates consideration of environmental justice issues is being developed using the
TRI Relative Risk-Based Chronic Human Health Indicator as the foundation.
Appendix H discusses expanding the TRI Environmental Indicators to reflect indirect
health and environmental impacts from TRI chemicals, such as global climate change, acid
deposition, stratospheric ozone depletion, tropospheric ozone formation, and particulate
deposition. While many of these impacts have health-related effects, the complexity and
uncertainty in modeling them may make it impossible to incorporate them into the present set of
Indicators.
As an indication of improvements in environmental quality over time, the TRI
Environmental Indicators will provide EPA with a valuable tool to measure general trends based
upon relative risk-related impacts of TRI chemicals. Though these Indicators do not capture all
environmental releases of concern, they do generally relate changes in releases to relative changes
in chronic human health and ecological (aquatic life) impacts from a large number of toxic
chemicals of concern to the Agency. Importantly, the Indicators also provide an ability to analyze
the relative contribution of chemicals and industrial sectors to environmental impacts, and serve as
an analytical basis for setting priorities for pollution prevention, regulatory initiatives, enforcement
targeting and chemical testing.
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IX. REFERENCES
Dourson, M. Environmental Criteria and Assessment Office, U.S. Environmental Protection
Agency. Personal communication, October 19,1993.
U.S. Department of the Interior, Fish and Wildlife Service (DOT, FWS). 1993. 1991 National
Survey of Fishing, Hunting, and Wildlife Associated Recreation. U.S. Department of
Commerce, Bureau of the Census. U.S. Government Printing Office, Washington D.C.
U.S. Environmental Protection Agency (EPA). 1985. "Exposure to Airborne Contaminants
Released from Land Disposal Facilities — A Proposed Methodology." Prepared for the
Office of Solid Waste by Environmental Science and Engineering, Inc. ESE Document
Number 85-527-0100-2140. August.
U.S. Environmental Protection Agency (EPA). 1986a. Guidelines for Carcinogen Risk
Assessment. 51 Federal Register 33992 (September 24, 1986).
U.S. Environmental Protection Agency (EPA). 1986b. Guidelines for Mutagenicity Risk
Assessment. 51 Federal Register 34006 (September 24, 1986).
U.S. Environmental Protection Agency (EPA). 1987. Graphical Exposure Modeling System
(GEMS) User's Guide. Prepared for the Office of Pesticides and Toxic Substances,
Exposure Evaluation Division by General Sciences Corporation under Contract No.
68023970. February.
U.S. Environmental Protection Agency (EPA). 1988a. IRIS Background Document #1.
Reference Dose (RfD): Description and Use in Health Risk Assessments. Integrated Risk
Information System (IRIS). Online. Maintained by Environmental Criteria and
Assessment Office, Cincinnati, OH.
U.S. Environmental Protection Agency (EPA). 1988b. Report to Congress: Solid Waste
Disposal in the United States. Volume 2. April.
U.S. Environmental Protection Agency (EPA). 1988c. National Survey of Solid Waste
(Municipal) Landfill Facilities. Office of Solid Waste EPA/530-SW88-034. September.
U.S. Environmental Protection Agency (EPA). 1988d. "Industrial Subtitle D Risk Screening
Analysis Results." Prepared for the Office of Solid Waste by ICF, Inc. December 30.
U.S. Environmental Protection Agency (EPA). 1990a. Exposure Factors Handbook. Office of
Health and Environmental Assessment. EPA/600/8-89/043. March.
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U.S. Environmental Protection Agency (EPA). 1990b. Hazard Ranking System: Final Rule. 55
Federal Register 241. pp. 51532-51667.
U.S. Environmental Protection Agency (EPA). 199la. Toxics in the Community. National and
Local Perspectives. The Office of Pesticides and Toxic Substances. EPA 560/4-91-014.
September.
U.S. Environmental Protection Agency (EPA). 1991b. Guidelines for Developmental Toxicity
Risk Assessment. 56 Federal Register 63798 (December 5, 1991).
U.S. Environmental Protection Agency (EPA). 1992. User's Guide for the Industrial Source
Complex (ISC2) Dispersion Models. Volume 2. Description of Model Algorithms.
Prepared for the Office of Air Quality, Planning and Standards, Technical Support
Division. March.
U.S. Environmental Protection Agency (EPA). 1993. Human Health Risk Assessment for the
Use and Disposal of Sewage Sludge: Benefits of Regulation. Prepared for the Office of
Water. January.
U.S. Environmental Protection Agency (EPA). 1997a. Addition of Facilities in Certain Industry
Sectors. 62 Federal Register 84, pp.23833-23892.
U.S. Environmental Protection Agency (EPA). 1997b. TRI Relative Risk-based Environmental
Indicators Project: Interim Toxicity Weighting Summary Document. Prepared for the
Office of Pollution Prevention and Toxics, Economics, Exposure and Technology
Division, Regulatory Impacts Branch. Prepared by Abt Associates under Contract # 68-
D2-0175.
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Appendix A
Survey of Ranking and Scoring Systems
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I. Survey of EPA Scoring and Ranking Efforts
Scoring and ranking of chemicals is not a new undertaking. Numerous efforts have
focussed on categorizing and ranking chemicals for a number of purposes. The most common
purpose is devising a methodology to choose from among a vast number of chemicals those that
merit further scrutiny. The following is a review of sixteen EPA scoring and ranking systems that
have been or are used by OTS and other Agency Offices.
A. OTS Efforts
1. Screening Methodology for Pollution Prevention Targeting
USEPA (date unknown), Prepared for the Office of Toxic Substances
The Office of Toxic Substances prepared a screening methodology as a tool for targeting
chemicals for pollution prevention. A three step scoring system, based on the toxicity (both
potency and type of risk posed) and on the release/production ratio of the chemical, was used.
Several risk classifications were evaluated; within each classification, a chemical was given a
preliminary score of 3, 2, or 1 for high, medium, or low concern, respectively. The first risk area
evaluated was cancer potency. All chemicals designated as B2 carcinogenic were given a
preliminary score of 3 (high). Oncogenicity received an additional weighting factor of 3 to arrive
at a raw score for cancer potency. General chronic toxicity and ecotoxicity were scored; these
scores were given an overall weighting factor of 2. Reproductive effects, neurotoxicity, and
developmental toxicity were also scored, but these scores were given a weighting factor of 1. The
raw scores for all four risk groups were added together and multiplied by the release/production
ratio to arrive at a composite score. For each chemical the composite score was calculated as:
Release
cst =D(o/D3 +ttRDNi-ui +Dc/.-D2 +DE.-D2) -D-
Production
where:
CSt = Composite score for chemical /
Ot = Oncogenicity concern for chemical /
RDNj = Reproductive, developmental, neurotoxicity concern for chemical /
Ct = Chronic toxicity concern for chemical /
Et = Ecological toxicity concern for chemical /
This methodology was used for internal EPA chemical targeting. It has not been, to our
knowledge, publicly reviewed.
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Pros: Method is simple. Broadly accounts for potency and severity of risk posed. Having three
broad categories of potency allows the use of structure-activity and professional judgment to
score chemicals lacking extensive toxicological databases. Includes consideration of both cancer
and noncancer effects.
Cons: Method groups chemicals very broadly, limiting the variation in potencies that can be
expressed. Method ranks chemicals ordinally, not proportionately, which does not allow for
accounting of the magnitude of differences among the chemicals. Does not have an exposure
component. Assumes that carcinogenic effects are more serious than reproductive effects. To
our knowledge, method has not been reviewed outside of the Agency.
2. TSCA's TRI Chemical Risk Assessment Pre-screening Methodology
USEPA (date unknown), Memo from the Office of Toxic Substances (date unknown)
The objective of this exercise was to select the most likely candidates among TRI
chemicals for possible regulation under TSCA. Of the 309 TRI chemicals, 193 were eliminated
outright because they were already being assessed or regulated by another EPA division, they
were not subject to TSCA, or no reports of use were received by EPA.
The remaining 116 chemicals were preliminarily ranked by exposure assessment and
hazard assessment. The two assessments were used in concert with the investigators' knowledge
to judge which chemicals presented the most significant risks to human health. This group of
roughly 20 chemicals received top priority for more extensive and rigorous investigation,
including exposure and hazard assessments, to determine which of them should be considered for
regulation under TSCA.
Preliminary Exposure Ranking
One hundred sixteen TRI chemicals were ranked using the Exposure Scoring System for
Existing Chemicals. The system was used to rank each chemical in four pathways: surface water
(drinking water), environmental (aquatic organisms), ambient air, and groundwater. These
rankings were not combined in a final ranking. To perform the rankings, two measures were
estimated in each pathway for each chemical.
The first measure, potential of exposure, is a measure of the presence of the chemical in
the environment. If the chemical is not expected to be released to a particular pathway, it is
assigned a score of "none" for no potential of exposure. Otherwise, if the chemical does not
exceed thresholds for physical and chemical properties (half-life, Henry's Law constant, vapor
pressure), it is assigned a "low" or "none". Those that are expected to be released in a particular
pathway and exceed the thresholds are assigned "high", "medium", or "low" potential of exposure
depending on the level of potential exposure that is calculated by the program. This calculation is
a function of release and concentration levels at sites. Rough estimates are used if only partial
information is available.
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The second measure, population, is a score of the number of people that might be exposed
to the chemical. It is calculated for each pathway and chemical. The system simply adds up the
populations surrounding production sites, or if exposure mostly occurs during industrial use,
extrapolates exposed populations from the number of industrial use sites. The final
"high/medium/low/none" score is based on population thresholds.
The final score for each pathway area uses the following determination matrix:
Final Exposure Score
Exposure
Measure
High
Medium
Low
None
Population Measure
High
High
High
Medium
None
Medium
High
Medium
Low
None
Low
Medium
Low
Low
None
None
None
None
None
None
Preliminary Hazard Ranking
EPA intended to develop a Hazard Ranking System to rank the TRI chemicals based on
measures of toxicity. However, only a preliminary search system was developed. It allowed the
user to score all TRI chemicals that fit given criteria, e.g. all those with an RQ over 1000 Ibs.
This system was used to develop simple lists of high toxicity chemical groups. Using this
information and their best judgement, the pre-screeners selected roughly 30 chemicals which they
determined to be the most hazardous.
Note that this ranking system has only been used within EPA's Office of Toxic Substances
and has not been publicly reviewed.
Pros: Exposure screening includes four pathways of exposure. Modelling approach is used to
evaluate exposure potential. Population surrounding TRI site is also included as a measure of
exposure potential.
Cons: Although modelling is used for exposure evaluation, the results are used to group the
chemicals into low, medium and high exposure potential groups. Pathway-specific scores are not
combined, thus requiring further judgments to evaluate overall exposure potential of a chemical.
To our knowledge, method has not been reviewed outside of the Agency.
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3. Chemical Scoring System for Hazard and Exposure Identification
O'Bryan, T. R. and Ross, R. H. (1988) Journal of Toxicology and Environmental Health,
Vol(l): 119-134
This system was developed by the Office of Toxic Substances and by the Oak Ridge
National Research Laboratory. It combines expert judgement and objective scores to screen
chemicals for further investigation for potential regulation under TSCA. Chemicals are scored in
eleven areas:
Oncogenicity Genotoxicity
Developmental toxicity Acute and chronic mammalian toxicity
Aquatic toxicity Bioconcentration
Chemical production volume Occupational exposure
Consumer exposure Environmental exposure
Environmental fate
Scores are assigned by and reconciled between two independent experts. While the scores
are based on delineated parameters, they can be adjusted in accordance with expert opinion.
Scores for oncogenicity, genotoxicity, developmental toxicity and the exposure measures are
based on weight-of-evidence. Scores for the others are based on thresholds (e.g. a
bioconcentration score of 9 is assigned for BCF levels above 1000.) Tables 1 through 3 in our
August 26 memorandum delineates the numerical ranges that comprise these scoring methods. In
some cases, structure activity relationships were used to supplement available data. Individual
scores generally range from 0 to 10 and are intended for comparison across areas and chemicals
but not as weights for the calculation of a final chemical score. In fact, the methodology does not
develop a final score. Instead, the scores from all eleven areas are presented as a score profile to
which expert judgement is applied to determine whether a chemical presents a great enough
hazard to undergo further investigation under TSCA. Note that this methodology has been
published in a peer-reviewed journal.
Pros: System considers a large number of health endpoints (cancer, developmental toxicity,
genotoxicity) in the evaluation. Makes use of both available data and expert judgment, allowing
for coverage of a large number of chemicals. Published in a peer-reviewed j ournal.
Cons: System does not combine scores for overall judgment on relative toxicity of a chemical. In
fact, the method explicitly states that scores can be used for comparisons across areas, but are not
intended as weights for combination into a final score. Method does not include an exposure
component.
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4. CERCLA Section 104 "Third Priority List" of Hazardous Substances that will be the
Subject of Toxicology Profiles
USEPA 1990, Prepared for the Office of Toxic Substances, February
EPA is using this system to select and rank the 275 most hazardous chemicals from among
all substances found at National Priority List sites. Three principal criteria determine how
hazardous a chemical is: 1) frequency of occurrence atNPL sites, 2) chemical toxicity, and 3)
potential for human exposure. Measures of these criteria are used to calculate site and exposure
ranks for each chemical, which determine the chemical's final ranking.
Frequency of occurrence is measured as the percent of sites at which the chemical is
known to occur. Toxicity of the chemical is measured by its Reportable Quantity (the lowest of
the mammalian, acute and chronic toxicity RQs was used.) When these ratings were not
available, the chemical was assigned an RQ equivalent by the EPA Structure Activity Team. A
site index was calculated for each chemical as:
~. , , ^Frequency of occurrence (percent)
RQ
The chemicals were assigned ordinal site ranks beginning with 1 for the chemical with the highest
site index, 2 for the chemical with the next highest site index, etc.
The measurement of chemical exposure is considerably more involved. First, an exposure
index value is calculated for each chemical as:
Exposure index = WCR + WFR + SCR + SFR + (2 x BPR)
where:
WCR = the geometric mean of chemical concentration in water at all sites where the
chemical occurred, ranked ordinally
WFR = percent of sites at which the chemical occurred in water / percent of sites at
which the chemical occurred in any media, ordinally ranked
SCR = the geometric mean of chemical concentration in soil at all sites where the
chemical occurred, ranked ordinally
WFR = percent of sites at which the chemical occurred in soil / percent of sites at
which the chemical occurred in any media, ordinally ranked
BPR = boiling point of the chemical, ordinally ranked
For WCR, the geometric mean as indicated is calculated for each chemical. The chemicals are then
ranked ordinally according to this value; WCR equals the rank assigned to the chemical.
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This method holds for each of the five variables listed above. Note that boiling point values
are used as a correlate of potential for air migration.
Because NPL site concentration data are not available for many chemicals, a second
methodology to calculate exposure was developed to complement the first. This method takes
advantage of the fact that a chemical's status as a chemical of concern gives some indication of the
chemical's exposure potential. Thus chemicals were ranked ordinally by the number of NPL sites at
which they were listed as chemicals of concern. The lesser of this measure and the exposure index
described above was used as the exposure rank.
Finally, these ranks were adjusted based on existing exposure information compiled in six data
bases: NRC, AHE, DOT/HMIS, NEXIS, NHATS and RTS. Because of source and methodological
disparities between the databases, the data they contained were not in themselves useful. However,
because the simple occurrence of a chemical in one of the databases implies some degree of exposure,
the number of databases in which a chemical was listed was used to determine the adjustments made
to the exposure ranks. (Note that because the first four databases contained data from overlapping
sources, multiple occurrences of a chemical in these databases was taken as a single listing.) The
adjustment was made as follows. The exposure rank was multiplied by a factor of 0.9 if a chemical
was listed in only one database, by 0.8 if in two databases, and by 0.7 if in three databases.
The site and exposure ranks of each were combined using the following formula:
Hazard Index = 2/3 x Site Rank + 1/3 x Exposure Rank
The weights reflect the fact that the site rank represents two of the three principal criteria mentioned
initially, while the exposure rank represents only one. The chemicals were assigned final ordinal
hazard ranks beginning with 1 for the chemical with the lowest hazard index, 2 for the chemical with
the next lowest site index, etc.
Pros: Uses a peer-reviewed, well-established measure of relative toxicity (RQ) for toxicity ranking.
Combines all measures (toxicity, exposure, frequency of occurrence) into a single index for each
chemical.
Cons: Exposure component relies on availability of site-specific concentration data for exposure
potential evaluation, which is not available for our purposes. Toxicity and exposure ranked ordinally,
so that proportional differences in potency and exposure potential are not captured. Use of RQ also
does not capture severity of effects.
5. Toxic Chemical Release Inventory Risk Screening Guide
USEPA 1989, Prepared by the Office of Toxic Substances, Volume 1, July
The Risk Screening Guide serves to explain both the meaning of Toxic Release Inventory
(TRI) data and ways of interpreting that data. Volume One of the document is divided into five
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sections. The first section details the advent of the TRI program as well as the nature of, limitations
on, and modes of access to the TRI data. Section Two details and explains the elements of risk
assessment. Section Three presents the guide's qualitative methodology for risk assessment for each
exposure route, incorporating the elements detailed in Section Two. Section Four proposes options
for acting on the results of the assessment and Section Five lists a host of resources that can be used
to answer any further questions.
The Risk Screening System presented in Section Three merits special attention. The system
centers itself around qualitative measurements of different chemical-specific and site-specific factors.
The user of the system first selects an exposure route (either air, land, surface water or POTW). The
next step is to record the location of release, the zones of effect (inner and outer), and the population
of interest. The user then delineates different "exposure factors" which depend upon the exposure
route chosen (i.e. wind direction for air or bioconcentration factors for surface water). The scores
for these factors depends upon the factor being discussed. For example, a water discharge receives
a "+" if it flows to a small lake or stream and a "-" if it flows to a large body of water. Next, the user
should select a toxic measure for each chemical from among a set of measures presented in Appendix
A (discussed below). The user selects the lowest ranking among all of the different toxicological
ranks. Next, the quantity of release should then be listed as either "high," "moderate," or "low"
through the use of data presented in Appendix C. The user compares the releases as recorded in TRI
to either the table of median emissions or by to local releases. Exposure factors should then be
recorded as detailed in Appendix D (discussed below), including high/low environmental
transformation, release rate, and any other factors which may seem relevant.
The result of the risk screening system is a profile of scores. From this information it is
possible to assess the relative severity of industrial practices in the area. The user can consult local
experts in order to get a feel for the individual risk.
Volume Two includes appendices which provide data and examples to facilitate the
assessment process. Appendix A ranks toxicological information on chemicals according to the
following scheme:
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Toxicological
Measure
TPQ
(Ibs.)
RQ
(Ibs.)
RfD
(mg/kg-day)
WQC
(mg/L)
Cancer Potency
Group 1
1 10 100
1 10 100
<0.01
< 1
All
Group 2
500
1,000
0.01 -0.1
1 - 10
Group 3
1,000 10,000
5,000
>= 1.0
>= 10
These ranking boundaries are used for each of the RQs (aquatic, chronic, acute, and carcinogenic),
RfDs (inhalation and oral), and WQCs (chronic and acute).
Appendix B aids users in assessing air releases. It discusses a generic air modelling exercise
which uses the Industrial Source Complex Long-Term (ISCLT) model. It provides two graphs which
display the results of generic model runs, the first plotting concentration versus distance from the
release site for various stack heights, and the second plotting concentration versus distance from the
release site for various durations of release. Multiplying data points on the graph by the actual
release quantities provides an estimate of the concentration at different distances of concern.
Appendix C assists users in assessing the severity of chemical releases. It provides
information on median chemical release data and actual TRI chemical release data (classified by SIC
code) to assist in assigning a "severe," "moderate," or "low" score to the quantity of release (see the
discussion on the Risk Screening System in Volume One).
Appendix D provides information on environmental fate characteristics of different chemicals
to provide rankings. The characteristics used to evaluate fate in different environmental media and
their rankings are listed below:
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Factor
Volatilization
Leaching &
Soil Mobility
Bioconcentration
Air Abiotic
Persistence
Water Abiotic
Persistence
Air Biotic
Persistence
Water Biotic
Persistence
Biological
Treatment
Measure
Henry's Constant
(atm-m3/mol)
Log10 (KJ
BCF
Atmospheric
Half-life
Aquatic
Half-lives
Degradation Rate
Degradation Rate
Rate of removal in
bio. treatment
High Concern
(+)
> ID'2
< 1.5
> 1,000
> 1 year
> 1 year
many months to
years
many months to
years
Loglo(Kow)<1.5
Hc < ID'5
resistant to degr.
Low Concern
(-)
< ID'6
> 4.5
< 250
< 1/2 day
< 1/2 day
1 to 7 days
1 to 7 days
rapidly removed:
-P for phys/chem
-B for biodegr.
The measure for water abiotic persistence stems from the longest of the hydrolysis, direct photolysis,
and indirect photoreaction.
Appendix H presents and describes the Roadmap database as well as other databases that
contain information on Section 313 chemicals. The Roadmap database includes the following
information for each chemical in tabular form:
! Federal regulations that apply to the chemical, along with relevant regulatory levels
! States that have drinking water standards or recommendations, along with relevant
regulatory levels, as reported in the Federal-State Toxicology and Regulatory Alliance
Committee (FSTRAC)
! States that have ambient air information, including ambient air standards or guidelines,
pollutant research information, source testing information, monitoring data, emissions
inventory information, and permitting information, as reported in the National Air
Toxics Information Clearinghouse (NATICH).
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! States that have water monitoring information, as reported in the Storage and
Retrieval Systems (STORET).
! General sources of information, including on-line data bases, and documents from
EPA and other sources.
This appendix includes expanded descriptions of these information sources. ROADMAPS has since
been updated to include additional data. Its "Carcinogenicity Matrix" includes results from the
National Toxicology Program bioassay tests (either positive or negative for carcinogenicity); the
National Toxicology Program's carcinogenicity ranking; the carcinogenicity rating assigned by the
International Agency for Research on Cancer; the EPA's carcinogenicity rating; and the GENETOX
carcinogenicity evaluation. It also now contains a "Health and Environmental Effects" table which
indicates whether a chemical is at a level of concern for heritable mutations, developmental toxicity,
reproductive toxicity, acute toxicity, and chronic toxicity, as well as the references for this data
(among EPA databases).
The remaining appendices contain other information to guide a use through the risk
assessment process. Appendix E presents information concerning the different types of releases, the
release frequency, existing controls, and estimation methods for the releases. Appendix F presents
a case study using the risk screening method (described below). Appendix I presents a sample EPA
Hazardous Substance Fact Sheet. Each of these sheets discusses one of the Section 313 chemicals,
providing information on typical modes of exposure, means of protection, proper handling, etc.
Appendix J provides an example of an EPA Chemical Profile which provides physiochemical
information on the Section 313 chemicals and which also discusses topics covered on the EPA
Hazardous Substance Fact Sheet.
Pros: Appendix A of the Risk Screening Guide allows grouping of chemicals according to any of five
measures of toxicity; using alternative measures of toxicity allows a larger number of chemicals to
be scored than if only a single measure was used. Appendix D groups chemicals into groups of "high
concern" and "low concern" based on environmental fate characteristics. The Risk Screening Guide
has been peer reviewed and is published.
Cons: The grouping approach allows only broad characterization of toxicity and exposure, and does
not consider severity or potency. Exposure evaluation does not explicitly consider populations
(although this can be considered on a site-by-site basis).
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B. Other Agency Scoring Systems that Use TRI Data
1. Targeting Pollution Prevention Opportunities Using the 1988 Toxics Release Inventory
USEPA 1990, Prepared for the Office of Policy, Planning and Evaluation, Pollution
Prevention Division, September 29
OPPE's Pollution Prevention Division (PPD) developed a method to rank chemicals and
facilities based on total volume of a subset of TRI chemicals. A list of high-priority chemicals was
established for air, land, and water releases based on toxicity and exposure potential (based on the
mobility of the chemical) in the TRI Risk Screening Guide. After a list was established for each
media, the release volume of those chemicals became the ranking instrument. While no exposure-
based adjustments were actually made to the rankings, possible methods for such adjustments were
discussed in some detail in the text. The population considered at risk for each pathway varies by the
mobility of the chemical. Thus, only populations relatively close to the facility are considered for low
mobility chemicals, while at greater distances are included for high mobility chemicals. The table
below shows how distance from facility and chemical persistence affect PPD choice of populations.
PPD also proposed a method to adjust for the exposure potential of aquatic ecosystems for discharges
to surface waters. Similar to human populations within circles of given radii from the facility, the
stream volume acts as a proxy for aquatic exposure. The water-volume proxy assumes that densities
and types of aquatic organisms are constant among all streams and are strongly positively correlated
with total volume of water. Proposed methods for accounting for ecological risk from discharges to
other media were resource intensive and did not lend themselves to computer automation.
This method was used for internal EPA chemical evaluation and has not been publicly
reviewed.
Concentric Ring Radius From Facility For Population Count
Pathway
Point and Non-Point Air Release
Underground and Land Releases
Surface Water Releases
Mobility of Chemical
High
4 miles
1 mile
15 miles
Medium
2 miles
1/2 mile
10 miles
Low - No Data
1 mile
1/4 mile
5 miles
Note: Surface water distances are downstream distances from the facility.
Pros for exposure evaluation: Combines Risk Screening Guide environmental fate groupings with
simple rules for defining the size of the potentially exposed population. This is a straightforward
approach that allows quick, rough weighting of emissions by potential exposure.
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Cons for exposure evaluation: Does not consider factors affecting differences in media concentrations
among sites as part of exposure evaluation. Selection of distances to consider for exposed population
is somewhat arbitrary.
2. Ranking the Relative Hazards of Industrial Discharges to POTWs and Surface Waters
USEPA 1991, Prepared for the Office of Policy Analysis, February 4
The Office of Policy Analysis developed a population weighted hazard index that ranked
water bodies and POTWs reported in TRI. OPA used Reportable Quantities as proxies for three risk
classes for which ranks were provided. Cancer potency, chronic toxicity, and aquatic toxicity were
treated separately in deriving indexes and ranks. For each risk class, each chemical release was
divided by the RQ for that risk class. The weighted releases were summed over a selected set such
as state or county to arrive at an unadjusted index.
The equation for calculating the unadjusted Hazard Index is:
where:
Ht = Hazard Index for set /'
Rx = Pounds released of chemical x
RQX = Reportable Quantity for chemical x
For each state or county, unadjusted indices were calculated for cancer, chronic, and aquatic
toxicity. The indices for cancer potency and chronic toxicity were adjusted using the size of the
exposed population to reflect human exposure potential:
where:
P = Persons per square mile in the county of release Rx
Aquatic toxicity indices were not adjusted using this method due to inadequate data about the
size of the exposed aquatic population. Thus, the OPA work does not address the difficult question
of adjusting indices based on exposure potential to aquatic life and habitats.
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For releases to POTWs, the analysis addressed the hazard of POTW residuals as well as
effluent. Average removal rates were applied to chemicals released to POTWs. Standard partitioning
rates were applied to the portion removed by the POTW. Hazard indices were then generated for
each partitioning pathway (sludge, volatilization) within the POTW.
This methodology was used within the EPA and has not been publicly reviewed.
Pros: Uses peer-reviewed, publicly available toxicity measure (RQs) that are available for a fairly
large percentage of TRI chemicals. Also considers county population density as a surrogate measure
of exposure potential.
Cons: Does not consider environmental fate of chemicals in exposure evaluation. Use of RQs does
not include consideration of severity of effects. RQs do incorporate some consideration of potency,
but groupings according to potency are broad.
3. Review of Region VII TRI Strategy
USEPA 1991, Memo from Dermont Bouchard, EPA Region VII to Loren Hall, OTS,
July 9
Region VII is developing strategies to utilize TRI data. One strategy ranks geographic areas
by human health and aquatic ecological risks to determine areas most in need of investigation for
further enforcement, remediation, technical assistance, or other purposes. The human health risk
analysis, which is separate from the ecological risk analysis, is measured by relative daily toxic
loadings (RDTLs). For a given site, an RDTL is estimated for the following categories:
Non-cancer acute toxicity by ingestion
Chronic inhalation cancer
Chronic ingestion cancer
Chronic inhalation non-cancer
Chronic ingestion non-cancer
A toxicity measure (for example, the inverse of the RfD for chronic ingestion non-cancer) is
multiplied by the site loading to the appropriate media (surface water emission in this case) for each
category. These RDTLs are not to be added, unless they are added within a category across the
various chemicals present at a site. Because RDTL units are different for each category, they are
comparable across sites only within categories.
Aquatic ecological risk for a site is determined in a similar manner. A multi-trophic analysis
is used to identify an LC50 that is the lowest, most protective value for the site. The RDTL is
calculated as:
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RDTL =chemical loading volume x LC50 / stream volume
Total risk for a site is the sum of the RDTLs across chemicals released at that site.
The Region VII TRI strategy is currently under peer review within the EPA.
Pros: Considers acute and chronic toxic endpoints and multiple exposure pathways. The toxicity
measures used (RfDs, q*, WQC) reflect the relative potencies of chemicals. For ecological risk, more
than one trophic level is considered.
Cons: Scores are not combined across sites for a single chemical index; however, scores may be
combined within a single site. The human health evaluation categories do not consider environmental
fate or population exposure potential. This system is oriented more toward identifying problem sites
than in characterizing overall risk from all sites.
C. OSWER Scoring and Ranking Systems
1. Hazard Ranking System; Final Rule
55 Federal Register No. 241, pp. 51532-51667, December 14, 1990
The Hazard Ranking System (HRS) is the principal mechanism used by the EPA to place sites
on the National Priorities List (NPL). It provides a methodology for scoring a site based on various
site characteristics. It incorporates information representing four exposure pathways: ground water,
surface water, soil and air. If the site's score exceeds an established threshold, the site qualifies for
the NPL.
Hazard Ranking Score
The hazard ranking score is calculated as:
HRS = (S2^ + S2^ + S2S + S2J'/2
where:
S = is the scores for each of the four pathways delineated below.
Using the root-mean-square calculation, low migration pathways scores yield a low HRS.
However, the HRS score could be relatively high even if only one pathway score was high. This is
an important requirement for HRS scoring because some extremely dangerous sites pose threats
through only one migration pathway.
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While the scoring system for each pathway is quite sophisticated, the pathway scores follow
this general methodology:
Likelihood of Release x Quantity of waste at the site x Measure of toxicity x Measure of exposure
The pathway scoring systems demonstrate how toxicity and exposure characteristics can be scored
(i.e. weighted). They are much more sophisticated than ordinal scoring systems that implicitly weight
characteristics without any underlying justification.
Ground Water Migration Pathway
The pathway score is the product of the following three categories (divided by a scaling factor
of 82,500) for the aquifer and contaminant yielding the highest pathway score.
Likelihood of Release x
Highest of:
Observed release = 550
or
Potential to release =
Contaminant Score x
(Net precipitation score +
Depth to aquifer score +
Travel time score)
Waste Characteristics x
Score of [(Score of
Toxicity score and
Mobility score) x
Weighted Hazardous waste
quantity]
Targets
Nearest well score +
Weighted Population +
Resources score +
Wellhead score
The scores for these individual components are assigned based on conditions set by the Rule.
For example, the contaminant score is 10 if a liner is not present in the containment system, 9 if one
is present. The toxicity score is the highest of 1) chronic toxicity score based on ranges for RfDs, 2)
carcinogenicity score based on ranges for human carcinogenicity slope factors and weight-of-
evidence, and 3) acute toxicity score based on ranges for oral LD50, dermal LD50, and various LC50s.
Mobility is scored based on ranges for water solubility and the distribution coefficient (which is based
on soil type) of the contaminant. Table 1 of our August 26 memorandum delineates the numerical
ranges that compose this scoring method.
The numerous inputs for the groundwater pathway analysis include both chemical- and site-
specific measures. Many of these measures are not available for the sites listed on the TRI (for
example, chemical waste containment conditions or the characteristics of the geology of surrounding
strata.) The following list delineates those measures that are available for many of the TRI chemicals
and sites:
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Chronic toxicity (human) RfD
Human carcinogenicity slope factor
Human carcinogenicity weight-of-evidence
Oral LD50
Dermal LD50
Dust or mist LC50
Gas or vapor LC50
Water solubility
Distribution coefficient Kd
Quantity or volume of waste
Population
Net precipitation
Depth to the aquifer
Nearest well
Surface Water Migration Pathway
There are two components for likelihood of release, overland/flood and groundwater to
surface water. Each is the higher of an observed or potential release. The component that yields the
highest score when multiplied by the sum of the threat scores is the likelihood of release that is used
in the HRS score for this pathway. Threats are composed of three categories: drinking water, human
food chain, and environmental. The score of each threat is the product of the waste characteristics
and targets for that threat.
As with the groundwater migration pathway, surface water migration pathway is based on
scoring different conditions regarding site, pathway, environmental, chemical, quantity, and
population characteristics. The internal scores are used as weights, not ordinal ranks, for these
parameters. The methodology is designed so that worst case conditions determine the final HRS
rank. Thus if two exposure routes within a media migration pathway exist for a given site, the most
damaging route (as scored) is used to calculate the rank. For example, if the risk of exposure through
drinking water is worse than that through fish consumption, the surface water score for the site will
be based on risks from drinking water.
The surface water migration pathway scoring system utilizes a combined rating factor to score
combinations of toxicity and persistence of a chemical. The factor matrix scores twenty four
combinations yielding scores that range eight orders of magnitude.
Like the analysis of the groundwater pathway, the surface water pathway analysis
incorporates many measures that are not available for the sites listed on the TRI (for example, the
area over which a chemical drains into the surrounding environment.) The following list delineates
those measures that are available for many of the TRI chemicals and sites:
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Quantity or volume of waste
Chronic toxicity (human) RfD
Human carcinogenicity slope factor
Human carcinogenicity weight-of-evidence
Oral LD50
Dermal LD50
Dust or mist LC50
Gas or vapor LC50
Half-life in water from combined effects of:
hydrolysis
biodegradation
photolysis
volatilization
Log Kow
Stream volume in cubic feet per second
BCF
EPA chronic and acute Ambient Water Quality Criteria
EPA chronic and acute Ambient Aquatic Life Advisory Concentrations
Population
Air Migration Pathway
The methodology for this pathway considers gas releases and particulate releases separately.
A site which has both kinds of releases is assigned an air pathway score based on whichever kind of
release poses the higher risk (as determined by this methodology.) As with the two pathways
described above, a release score is based either on an observed release, if present, or on the potential
of the site to release. The release score is multiplied by the waste characteristic score and the target
score to yield the overall pathway score.
The air water migration pathway methodology is based on scoring different conditions
regarding site, pathway, environmental, chemical, quantity, and population characteristics.
Specifically, the waste characteristic score comprises measures of toxicity, mobility, and quantity of
the chemical released. The target score comprises measures of the nearest individual, surrounding
population, natural resources and sensitive environments. Many of the criteria on which scores of
these qualities are based are not appropriate for the TRI indicator methodology (e.g. acreage of a
nearby sensitive wetland environment.) However, many physical and chemical properties of the
chemicals are used as criteria to measure toxicity, mobility, and migration potential. The numerical
ranges of these criteria are presented in our August 26 memorandum.
As with the groundwater and surface water migration pathways, internal scores of the air
migration pathway are used as weights, not ordinal ranks, in the calculation of the pathway score.
In addition, as with the other pathways, the air pathway methodology is designed so that worst case
conditions determine the final HRS rank.
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Like the analyses of the first two pathways, the air migration pathway analysis incorporates
many measures that are not available for the sites listed on the TRI (for example, containment
measures in effect and their degree of effectiveness.) The following list delineates those measures that
are available for many of the TRI chemicals and sites:
Vapor pressure
Henry's constant
Quantity or volume of waste
Chronic toxicity (human) RfD
Human carcinogenicity slope factor
Human carcinogenicity weight-of-evidence
Oral LD50
Dermal LD50
Dust or mist LC50
Gas or vapor LC50
Population
Note that this ranking system has been published in the Federal Register and has been publicly
reviewed.
Pros: A reviewed and published method for evaluating and ranking hazardous waste sites. Evaluates
four exposure pathways and adds the scores to yield a single site score. Considers many relevant site
and chemical characteristics when scoring exposure. Toxicity score is based on highest of cancer,
noncancer and acute toxicity subscores, thereby incorporating consideration of a range of health
endpoints. Scores are used as weights, not ranks, so magnitude of exposure and toxicity can be
considered.
Cons: Exposure evaluation requires much more detailed site-specific data than are available for TRI
sites.
2. Application of the Hazard Ranking System to the Prioritization of Organic Compounds
Identified at Hazardous Waste Remedial Action Sites
Hallstedt, P. A., Puskar, M. A., and Levine, S. P (1986) Hazardous Waste and Hazardous
Materials, Vol (3):2, pp. 221-232
This system ranks chemicals by relative risk to target those chemicals that are of highest
concern with respect to hazardous waste cleanup and the reduction of hazards to human health. The
authors' measure of relative risk incorporates the methodology of the first (unrevised) EPA Hazard
Ranking System to score chemical toxicity and persistence.
The risk formula that determines the ranking score is straightforward:
Score = Measure of Hazard x Exposure
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The measure of hazard is based on a chemical's toxicity and persistence characteristics. Each
characteristic is ranked from 0 to 3, 3 representing the highest order of toxicity or persistence. The
methodologies underlying these rankings are referenced and can be explored if necessary. The overall
measure of hazard reflects a synergistic effect between toxicity and persistence and is summarized in
the following table:
Measure of Hazard
Toxicity
0
1
2
O
Persistence
0
0
3
6
9
1
0
6
9
12
2
0
9
12
15
3
0
12
15
18
Exposure is measured as the percentage of the sample sites that release a chemical weighted
by the concentration of each release. Thus, exposure is not an absolute measure of population
exposure but a relative measure that is a function of the sample of sites that is used. Concentration
of release was used in lieu of volume of release, because data on the latter was unavailable.
Note that this methodology has been published in a peer-reviewed journal.
Pros: Simple, straightforward assignment of chemicals to categories based on toxicity and persistence.
Provides relative ranks of chemicals based on toxicity-persistence matrix. Allows for categorization
of large number of chemicals, based on available data, SAR, and Best Professional Judgment. Has
been published in peer review journal.
Cons: Broad groupings do not permit refined accounting of relative toxicity or persistence of
chemicals. Exposure component inappropriate for our purposes, since it considers only the frequency
of occurrence of chemicals, and not their concentrations or volumes. Populations exposed are not
considered.
D. Office of Water Scoring and Ranking Systems
1. A Ranking System for Clean Water Act Section 307(a) List of Priority Pollutants
USEPA 1985, July 3 (Office unknown)
This methodology was developed to determine which chemicals should be added to or
subtracted from the Priority Pollutants List, a list of chemicals that pose the greatest hazard to human
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health and the environment nationwide in surface water bodies. Chemicals are list candidates if they
are either very toxic or exposed to a large population. This system does not attempt to rank
chemicals, but simply provides the decision rule for inclusion or exclusion in the list. However,
because the chemicals are scored in the process of determining exclusion or inclusion, this system is
relevant to the ranking discussion. It is unknown whether this methodology has been peer-reviewed
or made available for public comment.
To evaluate toxicity, the following five categories are considered, followed by the variables
considered in each category:
1) Aquatic Toxicity
acute (LC50), chronic (MATC)
2) Mammalian Toxicity
acute oral (LD50), acute dermal (LD50), chronic/sub-chronic (LDLo and TDLo)
3) Human Health
Evidence of carcinogenicity, mutagenicity and teratogenicity
4) Bioaccumulation
BCF, BAF, Log P
5) Environmental Persistence
environmental half-life, hydrolysis rate, Henry's constant, KD value
Because the variables in a category are often well-correlated, they are considered together to
avoid biasing the system by considering the same topic twice. A score is developed for each category
by considering the most potent effect of any of the variables in that category. For example, the
scoring system for Aquatic Toxicity is:
Acute (LC50) Chronic (MATC)
Score (mg/L) (mg/L)
12 <0.1 <0.01
10 0.1 to 1.0 0.01 to 0.1
5 1.0 to 10.0 0.1 to 1.0
3 10.0 to 100 1.0 to 10.0
0 >100 >10
* Insufficient information
The values of the scores assigned to each category were based on expert judgment. The
scoring systems are similar for the other categories. One of the advantages of this method is that data
gaps in one variable may be filled by data from another within the same category. Note that in the
Human Health category, weight of evidence classes, not numeric measures (such as q*), are assigned
score values. If the sum of the scores over the five categories is greater than 10, then the chemical
is listed.
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National exposure potential is evaluated in a similar manner. The following categories are
individually scored on a scale of 0 to 10 based on numerical thresholds as above:
1) Amount of discharge nationwide (metric tons per year)
2) Number of sites of discharge having detectable concentrations
3) Frequency of detection in ambient waters (percent)
4) Frequency of detection in aquatic sediments (percent)
5) Frequency of detection in industrial or municipal effluents (percent)
If the sum of the scores over the five categories is greater than 10, then the chemical should
be listed.
Pros: Considers a range of acute and chronic toxicities. Includes persistence and bioaccumulation.
Allows for more than one measure to be used to rank a chemical within one category, thus allowing
a wider range of chemicals to be scored. Allows use of expert judgment to fill in data gaps.
Cons: Toxicity ranks are ordinal, not proportional. Since this system was not intended for site-
specific use, it is limited in its consideration of exposure potential; exposure potential is based only
on environmental fate properties of the chemicals and frequency of occurrence.
2. Screening Procedure for Chemicals of Importance to the Office of Water
USEPA 1986, Prepared by the Office of Health and Environmental Assessment,
November 14
This screening method was developed by ORD for the Office of Water to differentiate quickly
and inexpensively between higher and lower risk chemicals so that the Office could set priorities for
more intensive review of a small set of chemicals. Each chemical is identified as having "high", "low"
or "unknown" toxicity and "high", "low" or "unknown" exposure. Chemicals are categorized using
this matrix:
Rank Categories
Exposure
High
Low
Unknown
Toxicity
High
1
3
O
Low
2
4
4
Unknown
2
4
4
A fifth and lowest category is reserved for chemicals that are clearly not an environmental
problem. Chemicals in this category must either 1) have a half-life of less than a few minutes and not
be highly toxic (acute only), 2) be easily treatable, or 3) have not been shown to be toxic at high
concentrations.
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The criteria for labeling a chemical as having "high" toxicity is different depending on the
exposure pathway and exposed population. For example, a chemical exposed to human populations
is "highly" toxic if it is a definite, probable or possible carcinogen, or it is developmentally toxic. A
chemical exposed to aquatic life populations is "highly" toxic if LC50 < 100 mg/1 or chronic toxicity
< 1 mg/1.
The criteria for labeling a chemical as having "high" exposure is also different depending on
the exposure pathway and exposed population. Usually several conditions must be met. Among
these, for example, are BCF thresholds and whether or not the chemical has been detected (at any
level) in a relevant water pathway.
While "high" criteria are not comparable across pathways and populations, this method
succeeds in grouping chemicals roughly by risk. Chemicals notlabeled "high" fortoxicity or exposure
are labeled "low", unless information is unavailable. Data gaps are minimized by using chemical
estimation models (ENPART, a fate model; CHEMFATE; CHEMEST.)
It is unknown whether this methodology has undergone peer review or public comment.
Pros: Quick, easy to understand. Assigns rank based on toxicity and exposure potential
simultaneously rather than considering these elements separately. Allows scoring of a large number
of chemicals based on available data, SAR, and Best Professional Judgment. Considers a range of
health endpoints. Implicitly weights cancer and noncancer by automatically assigning "high" ranks
to cancer and developmental toxicity.
Cons: Consideration of potency, severity and weight of evidence are implicit, not explicit, in
assignment of chemical to one of the toxicity categories. Limited consideration of exposure, based
on environmental fate properties and the frequency of detection in U.S. waters.
E. Air Office Scoring and Ranking Systems
1. The Source Category Ranking System: Development and Methodology
USEPA 1990, Prepared for the Office of Air Quality Planning Standards, Chemicals and
Petroleum Branch, February 16
This system was devised to rank sources of different emissions in order to prioritize air
pollutant source categories. The scoring system looks at both long- and short-term effects of
pollutants, taking into consideration pollutant concentrations, maximum and average exposure, the
total exposed population, and health risks associated with the exposure. To our knowledge, this
system has only been used internally by the EPA and has not been publicly or peer reviewed.
Health effects scores are based upon carcinogen!city, reproductive and developmental toxicity,
acute toxicity data, and nonlethal health effects. Before calculating health risk scores, all health
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effects are scaled by dividing by the respective maximum health score so that the maximum equals
one. Scores for a particular site are then added across pollutants.
Exposure scores were calculated using an algorithm integrated with the Industrial Source
Complex Long-Term Model (ISCLT). Exposures per unit loss rates were calculated for both long-
term (average) and short-term (peak) chemical releases. These were then scaled by dividing by the
maximum exposure score such that the greatest exposure would equal one.
Pros: System was devised to rank air pollutant source categories. It utilizes data on acute and
chronic toxicity, pollutant concentrations (as obtained from air modelling), populations exposed and
human health risk. Scores are developed for carcinogenicity and other health end points. Scores are
summed across pollutants to obtain source specific values. Normalizes scores by dividing each score
by maximum value possible in that category.
Cons: System is media-specific to EPA's Air program. The system neither incorporates severity of
health effects nor does it allow weight of evidence considerations in scoring. Unknown if system has
been peer reviewed. The system also does not include non-human health effects in establishing a
source-specific score.
2. Measuring Air Quality: The New Pollutants Standards Index
USEPA 1978, Prepared for the Office of Policy Analysis, July
This index measures air quality based on the potential acute human health effects of five major
pollutants: carbon monoxide, photochemical oxidants, nitrogen dioxide, sulfur dioxide, and
particulate matter. The index is formed by calculating the following subindex for each pollutant:
0 7. , n 100 x Observed Concentration
Subindex =U-
National Ambient Air Quality Standard (NAAQS)
The Index value (ranging from 0 to 500) is equal to the highest of the five subindices. The
pollutant responsible for the highest subindex and all pollutants with subindices greater than 100 are
named (a subindex greater than 100 indicates that the pollutant concentration violates the NAAQS.)
Because of the limited definition, indices calculated in this way on a regional or local basis are not
comparable because variables such as area of effect, duration of concentration, and exposed
population are not controlled.
This index has been published and was designed specifically for public use.
Pros: This index provides a measure of overall air quality based on the potential acute human health
effects of five criteria air pollutants. The index is simple and easy to understand. Subindices are
calculated for each pollutant by dividing the observed concentration by the relevant National Ambient
Air Quality Standard.
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Cons: This index is severely limited to just the five criteria air pollutants. The index only
incorporates acute health effects data along with ambient air concentration data. It does not look at
chronic health effects, ecological effects, populations exposed, weight of evidence considerations, or
severity of effects. Additionally, the index does not allow for combining values into a single score.
3. National Emissions Standards for Hazardous Air Pollutants for Source Categories:
Proposed Regulations Governing Compliance Extensions for Early Reductions of Hazardous
Air Pollutants
USEPA 1991, Prepared for the Office of Air Quality Planning Standards
This proposed rule will implement provisions of the Clean Air Act Amendments of 1990 that
allow a source to obtain an extension for compliance with air emissions standards if the source has
achieved an overall emission reduction of 90% or more by specified dates. Reductions are calculated
based on overall emissions from the source; therefore, a source can use greater than 90% reductions
from some pollutants to offset less than 90% reductions for other pollutants to achieve the overall
90% reduction. However, certain rules govern this practice of offsetting for "high-risk" pollutants.
Offsetting of these "high-risk" pollutants with lower risk pollutants is calculated based on the relative
toxicity of the chemicals. For carcinogens, weighting factors are applied to the emissions of these
"high-risk" chemicals, so that every 1 pound of these carcinogens equals between 10 and 1,000,000
pounds of lower risk carcinogens. For noncarcinogens, weighting factors are not developed; rather,
chemicals are categorized into two groups, high risk and low risk. Fligh risk noncarcinogens can be
traded on a one-to-one basis with other high risk noncarcinogens and with carcinogens on a ten-to-
one basis. Reductions in high-risk noncarcinogens can offset low risk noncarcinogens, but not vice
versa.
To identify high-risk chemicals in both the carcinogen and noncarcinogen categories, OAQPS
first gathered available health data on the chemicals. For carcinogens, potency data was taken from
IRIS and from CERCLA Reportable Quantities. Weight-of-evidence classifications and CERCLA
hazard ranking (low, medium, high) was also recorded. IRIS was also used to obtain data for
noncarcinogens. IRIS was supplemented by RTECS, where IRIS data were not available.
After health data were gathered, OAQPS performed generic exposure modelling based on
average meteorologic conditions. If the chemical concentration 500 meters from the source posed
greater than 1 x 10"4 risk, or if the concentration exceeded the reference dose (or the LOEL/100 or
LD50/1000, if no RfD was available) by an order of magnitude or more, the chemical was
preliminarily designated "high-risk". The weighting factors for carcinogens were determined based
on the ratio of the potency estimates of the high-risk chemicals to the potency estimates of the lower
risk chemicals. In contrast, noncarcinogens were simply placed into high and low risk groups,
without specific weighting factors. The last step in the analysis was to determine if any U.S. facilities
actually emit these chemicals in sufficient quantities to reach the health effects benchmark of concern.
This determination was based on TRI emissions data and other sources of emissions data. If at least
one facility released the chemical in sufficient quantities to reach the benchmark exposure level, the
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chemical was included on the final "high-risk" list. Note that these emissions standards will be
published in the Federal Register.
Pros: The relevant aspect of this proposal is the identification of chemicals that will count toward
early emission reduction goals. Importantly, chemicals are ranked as high or low risk using generic
air exposure modelling; this would support our use of such a generic approach. Secondly, the system
implicitly ranks carcinogens against noncarcinogens by allowing weighted trading among the tow
types of chemicals. The relative emission trading amounts would support a cancer versus noncancer
severity weighting. The approach will be published in the Federal Register.
Cons: System considers only air emissions. System is tailored to a particular requirement of The
Clean Air Act Amendments. The system does not address ecological effects.
F. Other Agency Scoring and Ranking Systems
1. USEPA Unfinished Business Report: A Comparative Assessment of Environmental
Problems
USEPA 1987, Prepared for the Administrator by
Richard Morgenstern, Director, Office of Policy Analysis
Don Clay, Deputy Assistant Administrator for Air and Radiation
Gerald Emison, Director, Office of Air Quality Planning and Standards
Rebecca Hanmer, Deputy Assistant, Administrator for Water
Marcia Williams, Director, Office of Solid Waste
PB88-127048, February 1987
This EPA report assesses 31 prominent environmental problems currently facing the United
States. It attempts to rank them by the risk each poses to society in an effort to prioritize how EPA
should use its resources. The environmental problems were defined along existing program lines, e.g.
criteria air pollutants, hazardous air pollutants, contaminants in drinking water, Superfund sites,
pesticide residues on food, worker exposure to toxic chemicals, etc. The ranking system that the
authors employed has been published and peer reviewed by the Scientific Advisory Board.
Four different types of risks were evaluated for each environmental problem: cancer risks,
non-cancer health risks, ecological effects, and welfare effects (visible impairment, materials damage,
etc.). These risk evaluations did not consider the economic or technical controllability of the risks
or the benefits to society of the activities causing the environmental problems. No attempt was made
to combine the risk evaluations, so in effect four separate rankings of the 31 problems were
generated.
The risk assessments were based on pollutant exposure and effects data. However, because
the data were largely incomplete and the methodologies for evaluating them are undeveloped or
crude, assessments were ultimately based on the collective informed judgement of the experts
involved. Wherever possible, these judgements were made using formal and systematic methods.
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Cancer Risk
To assess carcinogenic risk, EPA relied on the Carcinogen Assessment Group's evaluation
of the magnitude of risk. However, final rankings were based on judgment of the weight of evidence
as well as magnitude.
Non-Cancer Health Risk Evaluation
Each environmental problem was ranked based on the incidence of effects of the chemicals
associated with each problem and weighted by the severity of the effects. The methodology began
by selecting a few representative chemicals, for which incidence of exposure was estimated:
Incidence = number of people exposed X chemical potency
(potency = exposure dose divided by reference dose)
Data was often unavailable, in which case the authors' judgement was used. Incidences were
summed, weighted by an effect severity index. The final rank was determined by scaling the sum by
the authors' estimate of how much of the problem was not captured by the representative chemicals.
Ecological Risk
The authors attempted a broad assessment of environmental impacts on all kinds of
ecosystems from terrestrial and freshwater types to marine and estuarine types. However, their
assessment was the least rigorous of the four. Each environmental problem was ranked by subj ective
consensus as high, medium or low for each type of ecosystem. The rankings were based on expert
judgement of 1) potential anthrogenic impact on the environment at the local, regional and biospheric
levels and, 2) the severity of the impact in terms of number of years required for ecosystem recovery
once the stress was removed.
The judgements for a particular environmental problem were systematically aggregated across
ecosystems to generate a high, medium or low overall ranking for the problem. However, the authors
felt that their method was too inexact to try to establish relative rankings within these categories.
Welfare Risk
A full range of welfare effects were considered, including soiling and other material damages,
recreation, natural resources, damages to other public and commercial property and ground water
supplies, and losses in aesthetics and non-user values. The environmental problems were ranked by
consensus through a subjective review of the extent and cost of existing and potential damage.
Pros: Method is simple. Incorporates four broad risks/effects categories, being cancer risks, non-
cancer risks, ecological effects, and welfare effects. These categories allow and require professional
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judgment in score determination. The cancer risk score uses both magnitude of risk as well as the
weight of evidence. The non-cancer risk score uses exposure as well as severity of effect. This
system has been published and reviewed by the Scientific Advisory Board.
Cons: The four different categories cannot be combined into a unified score. The professional
judgment went into the score determination rather than the data selection, a process which would
prove too unwieldy for the entire TRI database. Both the ecological and welfare ranks were
subjective and relied upon site-by-site judgment rather than a rigorous method for calculation.
2. Integrated Environment Management Program
USEPA 1986, Prepared for the Environmental Criteria and Assessment Office, March
The IEMP is one system which seeks to incorporate the severity of the toxicity effect into a
chemical release ranking system. The ranking of the chemical release is based upon its relative risk
index score, calculated as:
RRIS = (Dose) x (Est. Potency for Human Health Effect) x (Weighting Factor)
Though the algorithm for determining the dose is not specified, the calculation is based upon:
(1) pollutant loadings; (2) an exposure analysis using established Agency fate and transport models;
(3) the population base identified; and (4) assumptions about body weight and routes of uptake.
Human health effects are divided into eight different categories, i.e. carcinogenicity,
mutagenicity, etc. The health score is a function of the probability that the effect occurs in humans
(T - based upon a set of decision rules regarding weight of evidence) and the probability of
occurrence of the toxic effect (P). For carcinogens, P equals the risk per unit dose. For non-
carcinogens,
P = I/MED
where /is the observed incidence of effects above the control incidence at the minimum effective dose
(MED) expressed as (mg/kg/day).
The weighting factor is actually a severity factor for each toxic effect. They are intended to
reflect the significance of the quality of life lost, years of life lost, and economic cost of the disease.
To the best of our knowledge, this system has been used only within the EPA and has not
been publicly reviewed.
Pros: Method is simple. It uses both exposure and routes of exposure in its dose calculation. It
incorporates eight different health effects in its health score and relies upon the weight of evidence.
It can use one or all of these effects, allowing for gaps in the data. It contains a weighting factor for
the severity of effect. It also generates a single score for carcinogens and non-carcinogens.
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Cons: The system has not, to our knowledge, been peer reviewed. The specifics of the determination
of the dose score and health score are not specified in the literature. The allowance of one to all of
the health effects in the scoring makes a "fair" comparison among chemicals uncertain.
3. Examination of the Severity of Toxic Effects and Recommendation of a Systematic
Approach to Rank Adverse Effects
USEPA 1986, Prepared for the Environmental Criteria and Assessment Office, March
Although this paper did not present a scoring system, it presents information on one aspect
of scoring: the weighting of severity among different types of health noncancer effects. Note that it
is an internal EPA document and has not undergone public review. The purpose of this paper is to
differentiate the effects of chemicals upon the human body and then to rank those effects. For
example, two different chemicals may have identical LOELs (Lowest Observable Effect Level) but
that the "effects" may be entirely different, i.e. slight changes in the liver versus kidney and/or heart
failure. Thus, while current research focusses on comparing chemicals according to these quantities,
the author believes in the necessity of a simultaneous ranking system based upon both the type and
magnitude of different toxic effects. This paper presents two ranking systems, one for
histopathological lesions (direct physical impact upon organs) and one for biochemical effects.
The histopathological scheme lists the severity of effect as a function of the severity of the
lesion, modified by any additional non-histopathological effects, and the affected organ. The
expression for the severity score is:
Score = ((Lesion Severity) + (Non-hist. Modifier)) x Organ Factor
The lesion severity is determined from a table which lists eight possible ranges of effects and
then assigns a score from one to eight (eight being the most severe) for that range. The modifier is
simply an addend for three different non-histopathological effects: organ weight change, biochemical
change, and organ system impairment. For an observed effect in each category, the modifier is one.
For no observable effect, the modifier is zero. If it is unknown whether these effects accompany the
lesion, the modifier is one-half A value is assigned to the organ factor according to a table which
ranks each of the four "Organ Categories" defined in the report.
The algorithm for the endpoint toxicity scheme is similar. The severity score may be
expressed as:
Score = ((Endpoint Severity) + (Endpoint Modifier)) x Organ Factor
The endpoint severity is determined from a table which lists seven possible ranges for the
biochemical change or system impairment as well as the category of the affected organ. The table
assigns a score, from one to seven, for each range, with seven being the most severe. The modifier,
as in the first scheme, is equal to one, zero, or one-half, depending upon an observed, non-observed,
or uncertain accompanying histopathological lesion or organ weight change. For example, a body
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weight change in an organism receives a score of one, the absence of organ weight change and lesions
creates a modifier of zero for both and therefore a total modifier of zero. No effect in category one
organs (lung, heart, brain, etc.) is an organ factor of one, yielding a total score of one.
The author cautions that these proposed schemes are not suitable for use in the comparison
of chemicals because, since factors such as duration of exposure and route of exposure were not
variables in the derivation of the schemes, these would need to be held as fixed in comparing
chemicals, a situation which never occurs in toxic releases.
Pros: A relatively simple method. It examines the differences in the severity of effects. It includes
rankings according to the organs affected, biochemical effects, and histopathological effects.
Cons: This is not an overall scoring system. The author even cautions against its integration into a
scoring system because certain site-specific variables, such as duration or route of exposure, were not
incorporated into the scheme. This system has not been peer reviewed.
In developing this severity ranking scheme, the authors of this paper reviewed several other
systems that use severity as a factor in the comparison of chemicals. The following describes systems
used by the author to develop their scoring systems.
Assessment of Air Emissions from Hazardous Waste Treatment Storage, and Disposal
Facilities
One hundred of the 501 RCRA wastes handled by treatment, storage, and disposal facilities
(TSDFs) were ranked according to two types of health data, toxic effects and carcinogenic effects.
Two factors were created, the toxicity hazard factor and the carcinogen!city hazard factor. These are
described as:
THF = (gas-phase equil. cone.) / (Threshold Limit Value)
CHF = (gas-phase equil. cone.) / (max allow, cone, at the 1E-5 Risk Level)
The maximum allowable concentration at the 100,000 risk level is the concentration at which there
is a 95% confidence that the limit on the cancer risk is one in one hundred thousand people. Each
of these factors is then multiplied by the wastes' aqueous and nonaqueous disposal volumes in order
to generate volume-weighted hazard scores.
In addition to the determination of these factors, a weighting factor is created from
carcinogenicity, teratogenicity, and acute toxic effects of each contaminant (using data from RTECS).
The score for each lies between zero and three. This weighting factor was then multiplied by the
scores.
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Pros: Simple system. Incorporates two different health effects, toxic effects and carcinogenic effects.
It uses the volume of release directly in the score determination. Includes a weighting factor based
upon carcinogenicity, teratogenicity, and acute toxic effects.
Cons: The two scoring factors for toxic and carcinogenic effects cannot be combined. The factors
rely upon the Threshold Limit Value and the Maximum Allowable Concentration at the 1E-5 Risk
Level respectively, data which exists for few chemicals. Does not have an exposure component.
RCRA Risk-Cost Analysis Model
This model follows a five-step process in order to determine human health risks resulting from
releases of chemicals. After chemical selection, concentrations of the contaminants are estimated for
three transport processes (air, surface water, and groundwater). The model then estimates the total
human intake, calculates the risk to an individual, and then estimates the population risk by
multiplying by the total population in a given area. This process assigns a risk score which then ranks
the releases.
Two equations were developed in order to model the process. They are:
Care. Risk = (riskper unit dose) x (severity index) x (dose)shape x (population exposed)
Non-Care. Risk = (risk per unit dose) x (dose) x (population exposed)
The severity index follows from a 1984 EPA ranking system developed to quantify statutory
reportable quantities of hazardous substances. It assigns a value of 0.1 for severities 1-2, 0.5 for 3-7,
and 1.0 for 8-10. The shape is merely an exponent to determine the shape of the curve.
Pros: Simple System, requiring only a dose for mammalian species based upon either human or
animal chronic or acute doses. Considers three different routes of exposure, oral, inhalation, and
dermal.
Cons: Relies upon a narrow range of health effects. Does not have an exposure or a volume
component (it ranks chemicals, not releases). Though the score only requires the dose, the
calculation of the dose is a cumbersome and difficult to understand process.
Toxicity Scoring System Using RTECS Data Bases
Though the scoring algorithm is simple, requiring only a dose, the methodology requires
detailed toxicity data for input into the algorithm.
The only dose considered are those for mammalian species. This method only considers oral,
inhalation and dermal routes of exposure, assuming each of equal importance and the absorption to
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be 100%. Four subscores are considered for each substance: human acute, animal acute, human
chronic, and animal chronic. The final score is taken from the following hierarchy:
! minimum of human and animal chronic doses, if both have entries;
! chronic dose for humans or animals, if only one has entry;
! minimum of human and animal acute doses, if both have an entry and there are
no chronic entries; and
! acute dose for humans or animals, if this is the only category with any entries
In using RTECS, chronic exposures are those resulting in effects other than death or are
effects such as cancer which may result in mortality. Selecting a human chronic effect requires
comparison in the RTECS data bases, where carcinogenic effects are classified as a carcinogenic
response (CAR), a neoplastic response (NEO), or an equivocal tumorigenic agent (ETA). The lowest
effect level for carcinogenicity is chosen by selecting the lowest dose of CAR or NEO. If neither
exists, the lowest ETA is multiplied by two. The selected dose is modified when there are multiple
carcinogenicity entries by decreasing the selected dose 10 percent per additional positive result, to
a maximum of 50%. Teratogenic doses from individual studies are ranked and the dose at the 20th
percentile is selected as the teratogenic dose. This dose is lowered in the same manner as the
carcinogenic dose.
Pros: Simple system. Incorporates exposure data for three different routes, air, surface water, and
groundwater. It also incorporates the severity of effect according to a 1984 EPA ranking system,
making its inclusion simple and straightforward.
Cons: Relies strictly upon the cancer slope of a chemical, limiting the number of allowable chemicals
by available data. The two separate scores calculated, carcinogenic and non-carcinogenic, may not
be compared.
II. Survey of TRI Ranking and Indexing Efforts Outside EPA
A number of organizations outside of the Agency have also developed ranking/scoring
systems for their own purposes, such as targeting chemicals for state regulation; identifying chemicals
for pollution prevention projects; and assessing the hazard of TRI emissions in particular
communities.
Abt Associates contacted a number of organizations which have utilized TRI data in
publications. The organizations were asked about the scope and methodology used in their reports.
Rhone-Poulenc in Paris developed an Environmental Index (El) to access the aqueous effluent
impact of wastes. They computed a raw indicator as a weighted average of the daily mass of six
types of wastes (toxic materials, suspended solids, nitrogen, phosphorus, salts, and chemical
organics). No justification is given for these weights. The raw indicator is multiplied by 100 and
divided by the average from the prior year to arrive at the final El for the month. This transformation
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is intended to make comparisons easy. If the index is greater than 100 the impact has been greater,
values less that 100 indicate improvement.
(Rhone-Poulenc memo July 25, 1991)
Chemicals on Which Data Are Currently Inadequate: Selection Criteria for Health and
Environmental Purposes
Organization for Economic Co-operation and Development, Berlin, March 1985
This report itself did not present a chemical ranking system. Rather, the purpose of this task
was to develop a rational methodology by which countries could select chemicals that most urgently
need attention. The elements of this methodology were: identifying selection elements, exploring
ways of weighting and combining elements and reviewing data sources. Selection elements identified
included workplace exposure, general population exposure, environmental exposure, human and
environmental effects. OECD also included recommendations for applying these elements.
Importantly, OECD emphasized the importance of clarifying the purpose and scope of the selection
exercise in order to define limits and interpretations. OECD also supported the use of expert
judgment to fill in data gaps. Finally, OECD strongly urged consideration of data quality in the
ranking and selection of chemicals.
For each of the elements of the methodology, OECD broke the approach down into four
steps: compilation, screening, refinement and review. The report then suggested topics to consider
in each of the four phases.
Polaroid Corporation has developed a 5-category scheme for all chemicals that they use. Chemicals
in categories i and ii are highly toxic (known and possible carcinogens). Category V chemicals are
non-toxic solid waste. Chemical categories have been used to establish goals for 50 percent reduction
in chemical use by category. The focus on chemical use reduction rather than chemical release
reduction is based on the Massachusetts Toxics Use Reduction Act. Category specific goals are
designed to prevent strategies that claim a "50 percent use reduction" but are based exclusively on
reductions in use of low toxicity wastes.
(Conversation with Polaroid Corporation representatives, June 1991)
The Boston Herald published a series of articles under the heading of "111 wind," covering
environmental releases of toxic chemicals in Massachusetts. The Herald concentrated mostly upon
volumetric data but also developed an algorithm for ranking the chemical releases according to
volume and toxicity. The algorithm multiplied the volume of release by a decimal number derived
from the inhalation risk number. This enabled the article to rank individual emitters by order of
"cancer risk." The Herald acknowledged that the ranking did not incorporate human exposure into
its calculation and cautioned against using their calculation as an "actual measurement of risk"
(The Boston Herald. Monday, May 13, 1991, p. 8).
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Air Toxic "Hot Spots" Program Risk Assessment Guidelines
California Air Pollution Control Officers Association, March 1990
This system is designed to prioritize facilities in accordance with the Air Toxics "Hot Spots"
Information and Assessment Act of 1987. According to this act, any facility which qualifies as a
"high priority" facility must perform a health risk assessment. Localities determine the priority level
(high, intermediate, or low) of the facilities in their district based upon the facility's reported emissions
of one or more of some 500 chemicals. Separate calculations and priority levels are used for
carcinogenic and noncarcinogenic substances. The higher of the two levels as calculated is assigned
to the facility.
The score for a facility emitting carcinogens is equal to the sum of the scores generated for
each carcinogen. Each contaminant's score is calculated as
TS = emissions [Ibs/yr] x unit risk [jug/m3]'1 x distance factor x normalization factor
The distance factor is determined from the distance from the source of the emissions to the
nearest populated area. That quantity corresponds to a value relating the change in concentration
with distance through the use of a Gaussian plume dispersion model. A total score of ten roughly
corresponds to a risk of one in ten thousand and a total score of one similarly corresponds to a risk
of one in one hundred thousand. This methodology places any facility scoring above ten in the "high
priority" category and those scoring below one in the "low priority" category. A score between one
and ten requires further analysis.
The score for a facility emitting non-carcinogens is determined much in the same way. The
total score for the facility is the sum of the scores of each substance emitted by the facility. The
substance score may be expressed as:
TS =emissions [Ibs/yr16] x distance factor x normalization/acceptable exposure level [^ig/m3]
The non-carcinogenic scores are considered identically to the carcinogenic scores, with "high
priority" assignment to facilities with totals over ten and "low priority" assignment to facilities with
total scores below one. Note that the carcinogenic and non-carcinogenic scores are not added
together.
maximum Ibs/yr for substances associated with acute toxicity and average Ibs/yr for substances associated with chronic
toxicity
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Louisiana's Environmental Action Plan "Leap to 2000"
Public Advisory and Steering Committee Risk Ranking Retreat Briefing Material
March 26, 1991
Louisiana formed a Political Advisory Committee (PAC) to rank 33 environmental issues by
the severity of risks they posed to the State. Risks were divided into three categories, human health,
ecological effects, and quality of life. The issues were ranked separately within each of these
categories based upon available scientific information and the judgement of assembled experts.
Informed by the three rankings, the PAC settled the final comprehensive risk ranking by voting on
the issues.
Health Effects
This method estimates risk to human health from the cancer and non-cancer effects. Cancer
risk was calculated based on chemicals representative of each issue:
Risk = Environmental Concentration x Potency x Population Exposed
Thus the issues were ranked by estimated cancer cases that would be caused by a particular
environmental problem. The issues were categorized as high, medium or low based on breaks in the
data of these results.
Non-cancer health risk was estimated from chemicals representative of each issue. Three
exposure pathways were considered: air inhalation, food and liquid ingestion, and skin adsorption.
Risk presented by each issue was calculated for each applicable exposure scenario as:
Risk = Severity Index x Dose x Population Score
The severity index is a standard ordinal ranking of body organs affected by a chemical and the
severity of those affects. Dose is an ordinal score based on ranges of RfD divided by average
contaminant concentration in the population's environment. Population score is an ordinal rank of
ranges of population sizes.
Non-cancer health risk for an issue is calculated as the average of the risks posed by each
exposure pathway. Issues were again ranked high, medium or low based on breaks in the data of
these results.
The final issue ranking placed equal weight on the cancer and non-cancer effects. The nine
possible combinations of the elements of the two categories were assigned very high, high, medium
high, medium and low ranks based on a committee consensus.
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Ecological Effects
The ranking committee ranked the environmental issues based on the degree to which nine
ecosystems were affected by each issue. Impacts on each of the nine ecosystems were evaluated on
an issue by issue basis by examining how stressors associated with an issue impacted the stress
indicators in an ecosystem. For example, for the Terrestrial Habitat Loss issue, stressors like
industrial development and proposed road construction were rated on a scale of 0 to 10 for how they
affect such stress indicators as Changes in Nutrient Cycling and Loss of Habitat. A stressor's score
was the weighted average of ratings across stress indicators, the weights reflecting the committee's
assessment of relative importance of the stress indicators. Stressor scores were averaged to
determine the final rating of the importance of the issue to the particular ecosystem.
The rank of the issue was calculated as the weighted average of these ecosystem-specific
ratings, the weights reflecting the committee's assessment of the value of each ecosystem. Breaks in
the ranking figures determined how the issues were divided into five categories (very high through
low.) Separately, committee members voted on the ecological importance of each issue using the
same five categories and compared this ranking to the quantitative one. The four issues that were
not placed in the same categories by the two systems were recategorized by consensus.
Quality of Life
This analysis attempted to rank the issues into high, medium and low categories based on the
costs associated with damages not accounted for in the two other rankings. Among these costs are
health care costs, recreation losses, materials damage and aesthetic losses. The issues were first
ranked based on the dollar value estimates of costs as determined by various relevant economic
studies. The issues were ranked again based on qualitative assessments of changes in quality of life
using such measures as the number of people suffering damages, and the reversibility of those
damages. Equal weight was given to the quantitative and qualitative rankings in determining the final
ranking (again using the very high through low categories.)
Purposes of and Criteria for Development of Chemical Hazard Lists from Ten Domestic and
International Organizations
USEPA 1985, Prepared for the Office of Pesticides and Toxic Substances, Economics and
Technology Division, December 31
This report reviewed various systems by which different organizations have compiled lists of
chemicals which they believe ought to be monitored. Each of these steps involved selecting criteria
in order to determine their placement upon the list as well as ranges. The following summarizes the
findings of this report:
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The European Communities Council Directive Chemical Hazard List:
82/501/EEC, OJNoL230, 5.3.82, pp. 1-18 (June 24, 1982)
The EC has mandated that any industry must list their use of any of the 178 chemicals upon
this list. The chemicals on this list fall into two toxic categories, very toxic substances, other toxic
substances. The qualifications for these categories are as follows:
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"Very Toxic" Substances
Other Toxic Substances
LD50 (oral) <= 5; or
LD50(cutaneous) <= 10; or
LC50 (inhalation) <= 0.1
25 < LD50 (oral) <= 200; or
50 < LD50 (cutaneous) <= 400; or
0.5 < LC50 (inhalation) <= 2
or
5< LD50 (oral) <= 25; or
10 < LD50 (cutaneous) <= 50; or
0.1 < LC50 (inhalation) <= 0.1
and
Physical and chemical properties which cause
effects similar to those caused by chemicals
which fall into the above criteria
California Air Resource Board Toxic Chemical List & NIOSH/OSHA Pocket Guide:
Air Resources Board of the State of California
The NIOSH/OSHA Pocket Guide to Chemical Hazards is a list of 380 chemicals, all under
federal regulation, which includes information on and recommendations concerning each of these
chemicals. The object of this list is to compile chemicals most likely to travel downwind in the event
of an accidental release. The California Air Resources Board included on its list any chemical from
the guide with an IDLH (Immediately Dangerous to Life and Health - maximum concentration of a
substance from which one could escape within 30 minutes without any escape-impairing symptoms
or any irreversible health effects) below 2000 ppm and a vapor pressure greater than 20 mmHg.
New Jersey Department of Environmental Protection Highly Toxic Substances List:
State of New Jersey Department of Environmental Protection, Division of
Environmental Quality
The divi si on of Environmental Quality in the Department of Environmental Protection in New
Jersey sought to prepare a list of chemicals which would cause acute health effects if released into
the air. Their toxicity criterion was based upon a Threshold Limit Value (TLV - time-weighted
average concentration to which nearly all workers may be repeatedly exposed without adverse effect)
of one pm. An additional criterion for inclusion on the list was reactivity. Volatility and usage were
used to rank the chemicals, but the methodology is not included in the report.
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Department of Transportation Poisonous Substances List:
DOT Hazardous Materials Regulations 49 CFR 172.101
The DOT's Hazardous Materials Table includes two categories for poisonous substances,
Poison A and Poison B. Poison B materials meet the following requirements:
LD50(oral) <= 50 mg/kg
LC50 (inhalation) <= 2 mg/l (if such a cone, is likely)
LD50 (cutaneous) < = 200 mg/kg
The Poison List has 153 chemicals of which 141 are Poison B materials.
Philadelphia Air Pollution Control Board Toxic Air Contaminants List:
Air Management Regulation VI: Control of Emissions of Toxic Air Contaminants, Air
Pollution Control Board of the Philadelphia Department of Public Health, 1981
Two lists were developed in order to require emissions reports from industry. The criteria
for the development of Schedule A are not specified, though the methodology incorporated risk of
immediate harm, carcinogenicity, mutagenicity, teratogenicity, bioaccumulative effects, and whether
the chemical is known to be present in the Philadelphia area. The criteria for schedule B are identical
and also meet the definition of "pollutant" as established by the EPA. The two schedules encompass
a total of 104 chemicals.
Union Carbide Corp. Industrial Hygiene Sampling and Monitoring Program List
Union Carbide Institute plant, 1984
Union Carbide developed a list of priority chemicals for their monitoring program at their
plant in Institute, West Virginia. The chemicals have been ranked ordinally from one to four in the
following system:
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Rating 4
Have OSHA,
ACGIH, or UCC
standards (whichever
is lower) including
permissible exposure
limits (PEL) of less
than 5 pm or less
than 0.1 mg/m8 as
TWA8 (time
weighted average for
normal 8 hr. day)
known carcinogens
result in
mutagenesis,
teratogenesis, or
fertility impairment
in humans
result in irreversible
nerve damage
result in irreversible
long-term organ
toxicity
are fast-acting and
can produce major
injury
Rating 3
5200
or
TWA8>5
classified as simple
asphyxiants or
nuisances
have generally low
risk effects
The ranking of the chemical determines how often they are to be sampled within the plant.
As can be noted, each of these systems represents a methodology for chemical selection and
presents, at best, a simplistic means for ranking chemicals according to different properties.
Nonetheless, it presents a large sample of properties (PEL, IDLH, etc.) which have been used in the
differentiation of chemical toxicity.
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Other Systems
Our research has uncovered three systems for which we are still trying to obtain
documentation. They are an Office of Water TRI chemical ranking system, an EPA compound
evaluation system, and the National Air Toxics Information Clearinghouse pollutant selection and
prioritization method. We also found two systems that were not relevant to this TRI indicator
discussion. The documents supporting these systems are titled 1) Existing Chemicals of
Environmental Relevance (German Chemical Society, October 1985) and 2) Chemical Scoring
System Development (Oak Ridge National Laboratory.)
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III. REFERENCES
Air Resources Board of California. No date. California Air Resource Board Toxic Chemical List
& NIOSH/OSHA Pocket Guide.
California Air Pollution Control Officers Association. 1990. Air Toxics "Hot Spots " Program Risk
Assessment Guidelines. March.
Department of Transportation. No date. Department of Transportation Poisonous Substances List.
49 CFR 172.101.
European Communities Council. 1982. The European Communities Council Directive Chemical
Hazard List. 82/501/EEC, OJNo. L 230, 5.3.82. pp. 1-18.
Hahn, R. and A. McGartland. 1989. "The Political Economy of Instrument Choice: An Examination
of the U.S. Role in Implementing the Montreal Protocol." Northwestern University Law
Review. 83 (3): 597.
Hallstedt, P.A., M.A. Puskar, and S.P. Levine. 1986. "Application of the Hazard Ranking System
to the Prioritization of Organic Compounds Identified at Hazardous Waste Remedial Action
Sites." Hazardous Waste and Hazardous Materials. Vol. 3:2. pp.221-232.
New Jersey Department of Environmental Protection. No date. New Jersey Department of
Environmental Protection Highly Toxics Substance List.
O'Bryan, T.R., and R.H. Ross. 1988. "Chemical Scoring System for Hazard and Exposure
Identification." Journal of Toxicology and Environmental Health. 1:119-134.
Organization for Economic Co-operation and Development (OECD). 1985. Chemicals on Which
Data Are Currently Inadequate: Selection Criteria for Health and Environmental Purposes.
March.
Philadelphia Department of Health. 1981. Philadelphia Air Pollution Control Board Toxic Air
Contaminants List.
Public Advisory and Steering Committee. 1991. Louisiana's Environmental Action Plan "Leap to
2000." March.
Union Carbide Institute. 1984. Union Carbide Corporation Industrial Hygiene Sampling and
Monitoring Program List.
U.S. Environmental Protection Agency (EPA). Date unknown. Screening Methodology for
Pollution Prevention Targeting. Prepared for the Office of Toxic Substances.
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U.S. Environmental Protection Agency (EPA). Date unknown. Memo from the Office of Toxic
Substances.
U.S. Environmental Protection Agency (EPA). 1978. Measuring Air Quality: The New Pollutants
Standards Index. Prepared for the Office of Policy Analysis. July.
U.S. Environmental Protection Agency (EPA). 1985a. Exposure to Airborne Contaminants
Released from Land Disposal Facilities — A Proposed Methodology. Prepared for the
Office of Solid Waste by Environmental Science and Engineering, Inc. ESE Document
Number 85-527-0100-2140. August.
U.S. Environmental Protection Agency (EPA). 1985b. A Ranking System for Clean Water Act
Section 307 (a) List of Priority Pollutants. July 3.
U.S. Environmental Protection Agency (EPA). 1985c. Purposes of and Criteria for Development
of Chemical Hazard Lists from Ten Domestic and International Organizations. Prepared
for the Office of Pesticides and Toxic Substances, Economics and Technology Division.
December 31.
U.S. Environmental Protection Agency (EPA). 1986a. Report to Congress on the Discharge of
Hazardous Wastes to Publicly Owned Treatment Works (the Domestic Sewage Study). Office of
Water Regulations and Standards. EPA/530-SW-86-004. February.
U.S. Environmental Protection Agency (EPA). 1986b. Screening Procedure for Chemicals of
Importance to the Office of Water. Prepared by the Office of Health and Environmental
Assessment. November 14.
U.S. Environmental Protection Agency (EPA). 1986c. Integrated Environment Management
Program. Prepared for the Environmental Criteria and Assessment Office. March.
U.S. Environmental Protection Agency (EPA). 1986d. Examination of the Severity of Toxic Effects
and Recommendation of a Systematic Approach to Rank Adverse Effects. Prepared for the
Environmental Criteria and Assessment Office. March.
U.S. Environmental Protection Agency (EPA). 1987a. Municipal Solid Waste Combustion Study
Report to Congress. Office of Solid Waste. EPA/530-SW-87-021a. June.
U.S. Environmental Protection Agency (EPA). 1987b. Integrated Risk Information System
Supportive Documentation, Volume 1, Appendix A. Office of Health and Environmental
Assessment, Office of Research and Development. EPA/600/8-86/032a. March.
U.S. Environmental Protection Agency (EPA). 1987c. USEPA Unfinished Business Report: A
Comparative Assessment of Environmental Problems. PB88-127048. February.
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U. S. Environmental Protection Agency (EPA). 1988a. National Survey of Solid Waste (Municipal)
Landfill Facilities. Office of Solid Waste. EPA/530-SW88-034. September.
U.S. Environmental Protect on Agency (EPA). 1988b. Industrial Subtitle D Risk Screening Analysis
Results." Prepared for the Office of Solid Waste by ICF, Inc. December 30.
U.S. Environmental Protection Agency (EPA). 1989. Toxic Chemical Release Inventory Risk
Screening Guide. Prepared by the Office of Toxic Substances. Volume 1. July.
U.S. Environmental Protection Agency (EPA). 1990a. Policy Options for Stabilizing Global
Climate: Report to Congress. Main Report. Prepared by the Office of Policy, Planning and
Evaluation. EPA Document No. 21P-2003.1. December.
U.S. Environmental Protection Agency (EPA). 1990b. CERCLA Section 104 "Third Priority List"
of Hazardous Substances That Will Be the Subject of Toxicology Profiles. Prepared for the
Office of Toxic Substances. February.
U. S. Environmental Protection Agency (EPA). 1990c. Targeting Pollution Prevention Opportuni-
ties Using the 1988 Toxics Release Inventory. Prepared for the Office of Policy, Planning,
and Evaluation, Pollution Prevention Division. September 29.
U.S. Environmental Protection Agency (EPA). 1990d. The Source Category Ranking System:
Development and Methodology. Prepared for the Office of Air Quality Planning Standards,
Chemicals and Petroleum Branch. February 16.
U.S. Environmental Protection Agency (EPA). 1990e. Interim Methods for Development of
Inhalation Reference Concentrations. Office of Research and Development. EPA/600/8-
90/066A.
U.S. Environmental Protection Agency (EPA). 1991 a. Ranking the Relative Hazards of Industrial
Discharges to POTWs and Surface Waters. Prepared for the Office of Policy Analysis. February 4.
U.S. Environmental Protection Agency (EPA). 1991b. Review of VIITRIStrategy. Memo from D.
Bouchard to L. Hall, Office of Toxic Substances. July 9.
U.S. Environmental Protection Agency (EPA). 1991c. National Emissions Standards for
Hazardous Air Pollutants for Source Categories: Proposed Regulations Governing
Compliance Extensions for Early Reductions of Hazardous Air Pollutants. Prepared for the
Office of Air Quality Planning Standards.
U.S. Environmental Protection Agency (EPA). 1992. "Description of Model Algorithms." User's
Guide for the Industrial Source Complex (ISC2) Dispersion Models. Volume 2. Prepared
for the Office of Air Quality, Planning and Standards, Technical Support Division. March.
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Appendix B
Options for a TRI Indicator Ranking/Scoring System
B-l
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Appendix B
OPTIONS FOR A TRI INDICATOR RANKING/SCORING SYSTEM
I. Elements of a Scoring System B-3
a. Selecting measures on which the ranking will be based B-4
b. Selecting a method to score the measures B-4
c. Selecting ranges over which measures are assigned scores B-5
d. Factoring data quality into the index B-23
e. Using severity indices to weight chemical scores within a category B-23
f. Ranking individual chemicals versus forming subindices B-23
g. Methods of establishing the relative importance of risks among categories B-24
h. Weighting scores: an alternative to methods presented in Section I.g B-25
II. Options for Ranking of Chemicals B-27
Option 1 B-30
Option 2 B-38
Option 3 B-47
B-2
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I. Elements of a Scoring System
Appendix A summarizes a number of chemical scoring and ranking procedures used by
Offices within the Agency and by organizations outside of the Agency. From the review of these
scoring systems, several common issues emerge. These issues must be considered for the
development of a ranking system for the TRI Indicator. These issues include:
a. Selecting measures on which the ranking will be based
Choosing measures to describe a chemical's toxicity and potential exposure
b. Selecting a method to score the measures. Options include:
Qualitative - high, medium or low
Ordinal - 1, 2, 3
Weighted Categories - 10, 100, 1,000
Calculated - continuous values
c. Defining criteria for weighted categories
For example, an chemical may be scored a 1 if its RfD falls between 0.5 to 5 and a 10
if its RfD falls between 0.05 and 0.5
Weight-of-evidence categories might also be scored
d. Factoring data quality into the indicator
e. Using severity of effect to weight chemical scores
f Ranking individual chemicals or forming sub-indices
Each chemical can cause a range of effects (e.g. acute toxicity, neurotoxicity, cancer).
If the relative importance of effects is established, a chemical can be scored on each
type of effect that it causes, then its scores can be combined across effect categories
to form a single score for that chemical. If the relative importance of risks cannot be
established, a separate indicator for each type of toxicity can be generated, or the
weight can be based on the most sensitive effect caused by the chemical.
g. Methods of establishing the relative importance of categories
If different categories are used, the relative importance can be reflected by the
methodology used to combine the category scores. Various methods include simple
summation, multiplication, other mathematical functions, matrices, taking the worst
score, and establishing decision rules
h. Weighting scores: an alternative to methods presented in Section I.g.
B-3
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The review of the scoring systems within and outside of the Agency has suggested a number
of approaches for handling each of these issues. Several alternative approaches for each issue, and
their advantages and disadvantages, are described below.
A. SELECTING MEASURES ON WHICH THE RANKING WILL BE BASED
Measures upon which to base scoring include those that describe the toxicity and
physicochemical properties of a chemical (e.g., LD50, RfD, solubility), and others that describe
exposure at a site (e.g., volume of release, population, site environments). The Section 313 criteria
lists ten parameters that EPA must consider when evaluating a chemical for addition to TRI:
carcinogenicity, chronic toxicity, acute toxicity, reproductive toxicity, heritable gene and
chromosomal mutations, developmental toxicity, neurotoxicity, environmental toxicity, persistence
and bioaccumulation. Most of the scoring systems reviewed consider at least some of these
categories, although they are frequently merged into fewer parameters.
The indicator could also incorporate measures of potential exposure including media-specific
emissions volumes, site characteristics and physicochemical properties. Site characteristics include
the potential population exposed through different media, and factors such as stream volume and
wind speed that influence the transport and dispersion of a chemical in the environment.
Physicochemical properties typically include partitioning, dilution, and dispersion coefficients of
contaminants.
B. SELECTING A METHOD TO SCORE THE MEASURES
A system for evaluating the measures of toxicity and exposure potential must be chosen. The
goal is to derive some way of scoring chemicals relative to one another within each category.
Possible categories might be human carcinogenicity, human chronic toxicity, mammalian acute
toxicity, chronic toxicity for aquatic species, and physicochemical exposure potential.
One possible system uses qualitative divisions to score chemicals within a category. For
example, the carcinogenicity of a chemical might be scored "high", "medium", or "low." An
advantage to using qualitative scores is that a broad range of information, qualitative and quantitative,
can be used to evaluate chemicals; this would allow assignment of scores to chemicals without
specific toxicity or exposure data. A disadvantage of qualitative scores is that they only broadly
distinguish toxicity and exposure potentials and limit the usefulness of the Indicator as a priority-
setting system. Ordinal systems (e.g. 1, 2, or 3) use numbers rather than "low," "medium" or "high"
to rank chemicals. Note that ranking formulas that incorporate ordinal scores should not be used to
attribute proportional meaning to the ordinal scores. Because assigning an ordinal rank of 3 to
chemical A and 1 to chemical B does not mean chemical A is three times worse than chemical B,
mathematical functions involving these two scores only convey information on order, not on
proportional magnitude.
B-4
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Unlike ordinal systems, that simply rank relative attributes of chemicals, order-of-magnitude
scoring systems (e.g. 1, 10, 100, 1000) still use numerical scores, but attempt to incorporate more
information about the proportional differences between chemicals. For example, proportional scores
for toxicity could reflect the proportional magnitudes of cancer potencies among chemicals.
Weighting chemicals using proportional categories of toxicity uses more information about the
chemicals but also avoids the impression of accuracy where such accuracy does not exist. Also,
defining categories of weights allows EPA analysts to use all relevant toxicity information about
chemicals to make approximate judgments about relative order of magnitude of toxicity, even for
chemicals where specific slope factors and RfD values have not yet been developed by the Agency,
thus allowing more chemicals to be included in the Indicator. Finally, chemicals are likely to remain
in the order-of-magnitude toxicity category to which they are originally assigned, unless significant
new and different toxicity data become available. Thus, the weights applied to these chemicals are
not likely to be revised frequently, lending stability to the Indicators over time.
Another way to score chemicals within a category is to use an actual numerical value of a
measure or mathematical function of the measure. For example, carcinogenicity might be scored by
using the actual slope factor of each chemical. Such a system compares chemicals on a continuous
scale and allows for the greatest use of quantitative data and results in the greatest distinction among
chemicals. However, continuous weights based upon specific information (based on qx* or on
chemical-specific decay rates, for example) have some disadvantages. First, continuous weights
would imply that we know the toxicity of the chemical with enough accuracy to distinguish among
relatively small differences in these values. In fact, there are significant uncertainties associated with
the assessment of a chemical's slope factor and even weight-of-evidence. In fact, the definition of
the RfD contains the expression "within an order of magnitude." Second, it would limit the number
of chemicals in the Indicator to those for which the specific information is available, and limits the use
of qualitative information and professional judgment.
c. SELECTING RANGES OVER WHICH MEASURES ARE ASSIGNED SCORES
If a proportional, order-of-magnitude system is used to rank chemicals, then the categories
must be assigned to a range of values of the underlying measure. For example, the 307(a) Priority
Pollutants Chemical Ranking methodology used the following ranges to score the aquatic toxicity of
chemicals:
Score LC;o (mg/L)
12 <0.1
10 0.1-1.0
5 1.0-10.0
3 10.0-100
0 > 100
B-5
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The categories can be defined using ranges of a number of types of data; for toxicity weights, for
example, RfDs (non-carcinogens) and qx* (carcinogens), RQs (or TPQs where RQs not available),
and occupational levels could be used.1 The selection of ranges forces a tradeoff between 1) using
a large number of narrow ranges, which might imply that the data is more refined than it really is, and
2) using a small number of broad ranges which inflates or diminishes the importance of the boundaries
and the measures that fall near them.
More than one kind of measure can be used to score chemicals within a category. This
approach takes advantage of a broader data set to score chemicals, including structure activity
relationships. For example, for acute mammalian toxicity, we may have several kinds of toxicity data
that describe a chemical's potency, such as acute oral LD50 and acute dermal LD50. If only one
measure were available, it would be used to determine the chemical's rank in that category. If both
were available, the more restrictive value could be used. Alternatively, a hierarchy of preferred
measures could be established; for example, RfDs may be preferred over RQs. The advantage is that
a larger number of chemicals can be assigned a weight.
The selection measures, boundaries for scoring measure ranges, and category scores are
presented in Tables 1,2,3 and 4 for selected scoring systems reviewed. The review demonstrates that
vast effort and expertise has already been devoted to scoring and categorizing chemicals, both within
the Agency and externally. This expertise could be built upon in the development of the TRI
Indicator.
Edward J. Calabrese and Elaina M. Kenyon, "The Perils of State Air Toxic Programs," Environmental Science and
Technology, Vol. 23, No. 11 (November 1989), 1326-9. This article warns against using occupational levels for general
population risk screening, for several reasons: (a) occupational levels consider a recovery period between exposures; (b)
occupational levels consider the "healthy worker" effect (that is, the levels are set for protection of relatively healthy
populations), (c) the ACGIH levels are set based on data of unknown quality (d) the levels do not account for environmental
fate (persistence, bioconcentration) and multiple exposure sources.
B-6
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Table 1: Human Toxicity Parameter Ranges
Ranking Systems
Screening Methodology
for Pollution Prevention
Targeting (USEPA, date
unknown, prepared for
Office of Toxic
Substances)
Ranking the Relative
Hazards of Industrial
Discharges to POTWs and
Surface Waters (USEPA
1991, prepared for the
OP A, February)
Hazard Ranking System;
Final Rule (55 Federal
Register No. 241,
pp.51532-667, 12/14/90)
Human Acute Toxicity
LD50 LD50
(oral) (dermal) Ranking:
<5mg/kg <2mg/kg 1,000
5-50 2-20 100
50-500 20-200 10
> 500 > 200 1
not available not available 0
Human Chronic Toxicity
Carcinogenicity:
high = 3
med = 2
low= 1
all B2 care.
given a score
of 3
Carcinogenicity:
Cancer RQ
Value Used
Directly
Carcinogenicity:
Class A,
Slope Factor
0.5 <
0.05-0.5
<0.05
-
not available
Neuro:
high = 3
med = 2
low= 1
Developmental:
high = 3
med = 2
low = 1
Non-cancer chronic:
Chronic RQ
Value Used
Directly
Class B,
Slope Factor
5<
0.5-5
0.05-0.5
<0.05
not available
Class C,
Slope Factor
50 <
5-50
0.5-5
<0.5
not available
Ranking:
10,000
1,000
100
10
0
B-7
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Ranking Systems
Hazard Ranking System;
Final Rule (55 Federal
Register No. 241,
pp.51532-667, 12/14/90)
(concluded)
USEPA Unfinished
Business Report
"Hot Spots" Program
Human Acute Toxicity
LC50 LC50
(dust or mist) (gas or vapor) Ranking:
< 0.2 mg/1 < 20 mg/1 1,000
0.2-2 20-200 100
2-20 200-2,000 10
> 20 > 2,000 1
not available not available 0
Human Chronic Toxicity
Non-cancer chronic:
RfD
<0.0005
mg/kg/day
0.0005-0.005
0.005-0.05
0.05-0.5
0.5 <
not available
Dose/RfD
1-10
10-100
100-1,000
> 1,000
Air:
Carcinogenicity:
q*
Used
Directly
Ranking:
10,000
1,000
100
10
1
0
Score
1
2
3
4
Non-cancer chronic:
RfD
Used
Directly
B-8
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Ranking Systems
Land Disposal Branch
Office of Solid Waste
European Communities
Council Directive
Chemical Hazard List
A Ranking System for
Clean Water Act Section
307(a) List of Priority
Pollutants (USEPA 1985,
July)
Human Acute Toxicity
LD50 LD50 LC50
(oral) (cutaneous) (inhala-
tion)
"very "very "very
toxic" toxic" toxic"
<= 25 <= 50 <= 0.5
"other "other "other
toxic" toxic" toxic"
25-200 50-400 0.5-2
Human Chronic Toxicity
Threshold Limit Value (TLV)
Used Directly
(Concentration Units)
Score Carcinogenicity:
12 Proven human carcinogen
10 Potential human carcinogen, proven animal
carcinogen
5 Potential animal carcinogen, proven mutagen,
proven teratogen
2 Potential mutagen, potential teratogen
0 No carcinogenic, mutagenic, or teratogenic
crorjerties
B-9
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Ranking Systems
Human Acute Toxicity
Human Chronic Toxicity
TSCA Chemical Scoring
System for Hazard and
Exposure Identification
Inhalation Dermal
LC50 LD50
<50
mg/m3
50-500
>500
<200
mg/kg
200-500
>500
Oral Exposure
LD50 Level Score
< 50 mg/kg Low 7-9
50-500 Medium 4-6
> 500 High 1-3
Score Genotoxicity:
9 Evidence of mammalian mutagenicity/clastogenicity, interaction with
mammalian
germ cell DNA, or epidemiological data suggesting genotoxicity in humans
8 Evidence of genotoxicity in non-mammalian germ cell assays, or evidence of
mammalian dominant lethality
5-7 Evidence of genotoxicity in more than one test system, other than above
2-4 Limited evidence of genotoxicity, including mixed positive and negative
results
1 Limited evidence of nongenotoxicity
0 Negative test results indicating lack of known genotoxicity
Score Carcinogenicity:
8-9 Evidence of oncogenicity from epidemiological studies or positive results
in two or more mammalian species
6-7 Evidence of oncogenicity in either sex of a single mammalian species
4-5 Suggestive evidence of oncogenic potential from epidemiological studies,
mammalian bioassays, cell transformation in vitro, or
promoter/carcinogenic activity
3 Evidence of genotoxic potential
1 -2 Limited evidence of lack of oncogenic potential
0 No evidence of oncogenic potential from well-conducted and well-designed
mammalian studies in two or more animal species
B-10
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Ranking Systems
TSCA Chemical Scoring
System for Hazard and
Exposure Identification
(continued)
Toxic Chemical Release
Inventory Risk Screening
Guide (USEPA 1989,
prepared by the Office of
Toxic Substances, Volume
1, July)
Human Acute Toxicity
Acute RQ
Ranking
<=100 Group 1
Ibs
1,000 Group 2
5,000 Group 3
Human Chronic Toxicity
Score Developmental Effects:
8-9 Evidence of adverse developmental effects in humans or
at least two other mammalian species
6-7 Evidence of adverse developmental effects in one
mammalian species
5 Developmental effects at doses accompanied by maternal
toxicity or otherwise equivocal test results
4 Adverse developmental effects in nonmammalian species
or in vitro test systems
3 Indirect evidence suggesting possible adverse
developmental effects
2 Indirect evidence of lack of adverse developmental effects
1 Limited evidence of lack of developmental effects
0 No evidence of developmental toxicity potential
Inhalation or Cancer or
Oral Rfd Chronic RQ TPQ
<0.01 mg/kg-day Ql* <=1001bs =100 Ibs
0.01-0.1 All 1,000 500
>=1.0 5,000 >=1,000
Ranking
Group 1
Group 2
Group 3
B-ll
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Ranking Systems
Louisiana's Environmental
Action Plan "Leap to
2000" (Public Advisory
and Steering Committee
Risk Ranking Retreat
Briefing Material March
26, 1991)
Human Acute Toxicity
Human Chronic Toxicity
Dose/Rfd
1-2
2-10
10-100
>100
Score
1
2
3
4
B-12
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Table 2: Environmental Toxicity Ranges
Ranking Systems
Ranking the Relative
Hazards of Industrial
Discharges to POTWs
and Surface Waters
(USEPA 1989, prepared
for OP A, February)
Hazard Ranking
System; Final Rule (55
Federal Register No.
241, pp. 51532-667,
12/14/90)
TSCA Chemical
Scoring
System for Hazard
and Exposure
Evaluation
Aquatic Toxicity
RQ
Used
Directly
Life cycle
Acute or Chronic
LC50 or EC50 NOEL Score
<1 <0.1 8-9
1-10 0.1-1 6-7
10-100 1-10 4-5
100-1,000 10-100 1-3
> 1,000 > 100 0
Ecotoxicity
Surface Water:
Acute Chronic
AWQC or AWQC or Assigned
AALAC AALAC Value
< 1 ug/1 < 100 ug/1 10,000
1-10 100-1,000 1,000
10-100 1,000-10,000 100
100-1,000 10,000-100,000 10
> 1,000 > 100,000 1
Mammalian Toxicity
B-13
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Ranking Systems
Toxic Chemical Release
Inventory Risk
Screening
Guide (USEPA 1989,
prepared by the Office
of Toxic Substances,
Volume 1, July)
Aquatic Toxicity
Aquatic
WQS RQ Ranking
<= 100 Ibs <= 100 Ibs Group 1
500 1,000 Group 2
>=1000 Ibs 5,000 Group 3
Ecotoxicity
Mammalian Toxicity
TPQ Ranking
<= 100 Ibs Group 1
500 Group 2
> = 1,000 Group 3
B-14
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Table 3: Exposure Parameter Ranges
Ranking Systems
Hazard Ranking
Exposure Potential
Surface Water:
Half Life Half Life Assigned
(Lakes) (Other) Log Kow Value
< 0.02 days < 0.2 days < 3.5 0.0007
0.02-2 0.2-0.5 3.5-4 0.07
2-20 0.5-1.5 4-4.5 0.4
>20 >1.5 >4.5 1
Surface Water:
Use priority: availability of BCF,
LogKow, water solubility
Assigned
Value BCF LogKow Water Solubility
50,000 > 10,000 5.5-6.0 < 25 mg/1
5,000 1,000-10,000 4.5-5.5 25-500
500 100-1,000 3.2-4.5 500-1,500
50 10-100 2.0-3.2
5 1-10 0.8-2.0
0.5 <1 <0.8 > 1.500
Exposure Level
Population Level
B-15
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Ranking Systems
Hazard Ranking
System: Final Rule
(concluded)
Exposure Potential
Air:
Assigned
Vapor Pressure Henry's Constant Value
>10Torr > 0.001 3
atm-m3/mol
10-0.001 10E-5 to 0.001 2
0.001-0.00001 10E-7tolOE-5 1
< 0.00001 < 10E-7 0
Ground Water:
Water Distribution Coefficient (Kd) (ml/g)
Solubility Karst < 10 10-1,000 > 1,000
Liquid 1 1 0.01 0.0001
>100mg/l 1 1 0.01 0.0001
1-100 0.2 0.2 0.002 2.0e-05
0.01-1 0.002 0.002 2.0e-05 2.0e-07
<0.01 2.0e-05 2.0e-05 2.0e-07 2.0e-09
Exposure Level
Population Level
B-16
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Ranking Systems
USEPA Unfinished
Business Report: A
Comparative
Assessment of
Environmental
Problems (USEPA,
1987, prepared by
OP A, OAR,
OAQPS, OW, and
OSW, February)
TSCA's TRI
Chemical
Risk Assessment
Pre-Screening
Methodology
TSCA's TRI
Chemical
Risk Assessment
Pre-Screening
Methodology
(concluded)
Exposure Potential
none = no
expected
release
Exposure Level
Criteria Score
> 700 mg/yr 3
70 to 700 2
<70 1
Population Level
Non-Cancer Effects:
People
Exposed Score
<1,000 1
1,000- 10E5 2
10E5-10E7 3
> 10E7 4
Surface Water:
Criteria Score
> 10E6 people 3
10E5-10E6 2
< 10E5 1
Ambient Air:
Criteria Score
> 10E5 people 3
10E4-10E5 2
< 10E4 1
B-17
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Ranking Systems
TSCA's TRI
Chemical
Risk Assessment
Pre-Screening
Methodology
TSCA's TRI
Chemical
Risk Assessment
Pre-Screening
Methodology
(concluded)
California Air
Resource Board
Toxic Chemical List
& NIOSH/OSHA
Pocket Guide (Air
Resources Board of
the State of
California)
A Ranking System
for Clean Water Act
Section 307(a) List
of Priority Pollutants
(USEPA 1985, July)
Exposure Potential
Air:
Dangerous:
IDLH < 2000 ppm
and
vapor pres. > 20 mmHg
Hydrolysis
Half Life Rate Score
>12mo - 8
6-12 mo - 5
3-6 mo > 3 mo 2
48 hr - 3 mo 48 hr - 3 mo 0
24-48 hr < 48 hr -5
< 24 hr - -8
Exposure Level
Population Level
Ground Water:
Criteria Score
> 25,000 people 3
5,000-25,000 2
< 5,000
1
B-18
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Ranking Systems
A Ranking System
for Clean Water Act
Section 307(a) List
of Priority Pollutants
(USEPA 1985, July)
TSCA Chemical
Scoring
System for Hazard
and Exposure
Identification
(O'Bryan, T.R. and
Ross, R.H. 1988,
Journal of
Toxicology and
Environmental
Health, Vol(l): 119-
134)
Exposure Potential
Henry's
Constant KD value Score
<10E-3 <0.01 2
0.001-0.01 10E2-10E4 0
>0.01 >10E4 -5
BAF Log P Score
< 4,000 < 6 8
700-4,000 4.5-6 5
300-700 4-4.5 2
> 300 >4 0
Half-life Score
>lyr 5
8-52 wk 4
2-8 wk 3
1-14 days 2
< 1 day 1
BCF Log P Score
> 1,000 >4.35 9
200-1,000 3.5-4.35 7
100-200 3.18-3.5 5
10-100 2.0-3.18 3
< 10 <2.0 0
Exposure Level
Population Level
B-19
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Ranking Systems
Louisiana's
Environmental
Action Plan "Leap to
2000" (Public
Advisory and
Steering Committee
Risk Ranking
Retreat Briefing
Material, March 26,
1991)
Screening Procedure
for Chemicals of
Importance to the
Office of Water
(USEPA 1987,
prepared by OP A,
OAR, OAQPS, OW,
and OSW, February)
Exposure Potential
For human and aquatic
populations:
BCF Score
> 1,000 High
< 1,000 Low
Exposure Level
Population Level
Population Exposed Score
1-400 1
400-4,000 2
4,000-40,000 3
40,000-400,000 4
> 400,000 5
B-20
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Table 4: Severity of Measured Effects
Ranking Systems
Severity of Effect
Examination of the Severity of
Toxic Effects and Recommendation
of a Systematic Approach to Rank
Adverse Effects (USEPA 1986,
prepared for ECAO, March)
Organ
Loss of which is fatal and
are irreplaceable (I)
= 1.5
Loss of which may be fatal yet
are replaceable or organs
which are necessary for
proper function of immunity (II)
= 1.0
Loss of which is not fatal but
may result in functional or
emotional handicap (III)
= 0.5
Not found in humans and toxic
lesions found may not transfer
to humans (IV)
= 0.25
Histopathological Severity
No change
= 1.0
Effects evident only at EM
level
= 2.0
Swelling, degeneration, fatty
change, pigment
= 3.0
Atrophy, hypertrophy,
cytomegaly, hemorrhage
= 4.0
Necrosis, mineralization,
emphysema, infarction
= 5.0
Fibrosis/regeneration, atypia
hyperplasia/proliferation
= 6.0
Teratogenesis with maternal
toxicity, fetotoxicity w/o
maternal toxicity
= 7.0
Teratogenesis w/o maternal
toxicity
= 8.0
Toxicity Endpoint
Body wt. change, food and/or
water cons, change, impairment of
organs (IV)
= 1.0
Small hematological changes,
impairment of organs (III), weight
change in organs (II, III, IV)
= 2.0
mild impairment of organs (II),
severe impairment of organs (III),
minor organ weight change (I)
= 3.0
mild impairment of organs (I),
major impairment of organs (II),
major organ weight change (I)
= 4.0
Functional impairment of organs (I),
= 5.0
Major degree of funct'l impairment
in organs (I)
= 6.0
Nervous System, respiratory, or
cardiovascular depression, mortality,
developmental toxicity w/o maternal
toxicity
=7.0
B-21
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Ranking Systems
Severity of Effect
USEPA Unfinished Business Report:
A Comparative Assessment of
Environmental Problems (USEPA
1987, prepared by OP A, OAR,
OAQPS, OW, and OSW, February)
Ranking of Organs
Category I
Includes organs, impairment or loss of which is fatal and cannot be compensated for at all, or only heroic measures (i.e. expensive
mechanical devices, transplantation). Also includes gonads, loss of which prevents reproductions.
Lung, heart, brain/spinal cord, kidney, liver, bone marrow, gonads
Category II
Includes organs whose loss or impairment may be fatal, but which can be compensated for by replacement therapy. Also includes
organs, impairment or loss of which indicates as adverse effect on immune function or hematopoietic function which may be life
threatening. Adrenal, thyroid, parathyroid, pituitary, pancreatic islets, pancreas, esophagus, stomach, small intestine, large intestine,
lymph node, spleen, thymus, trachea, pharynx, urinary bladder, skin
Category III
Impairment or loss of any of these organs is not life threatening but may result in severe functional or emotional handicaps. Accessory
reproductive organs (oviduct, epididymis, uterus, prostate, coagulating gland, seminal vesical, ductus deferens, penis, vagina), eye,
bone, nose, nerve, muscle, urinary bladder, blood vessel, ear, gall bladder, harderian and lacrimal gland, larynx, mammary gland,
salivary gland, tongue, tooth, ureter, urethra
Category IV
These organs are not found in humans and toxic lesions (noncarcinogenic) in these organs are not readily extrapolable to humans.
Clitoral/preputial gland, zymbal's gland, anal glands
B-22
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D. FACTORING DATA QUALITY/UNCERTAINTY INTO THE INDEX
There are differences among chemicals in the supporting health effects and exposure data.
Health data for one type of effect (e.g., cancer) may be based on animal studies, while evidence of
other types of effects may be derived from epidemiology (e.g. neurological effects of lead). Even
specific numerical estimates of a single type of effect, cancer potency, have varying levels of evidence
to support the estimate. For some chemicals without any specific toxicity data, other information,
such as structure-activity relationships, could be used to estimate the relative rankings. There will
also be differences in levels of uncertainty associated with exposure scenarios. For example, it may
be possible to model air and water emissions from certain facilities, but have less information on
releases from TSDFs and POTWs.
One system reviewed that attempted to measure and incorporate any element of data
uncertainty was the method for determining carcinogenicity RQ. This system employs an ordinal
scoring for carcinogenic weight-of-evidence. This score is combined with a score based on qx* using
a matrix in which each cell is assigned a high, medium or low rank. This same approach could be
used to weight ranks in the noncancer toxicity categories, as well as in exposure categories.
Alternatively, numerical uncertainty scores could be used to adjust chemical scores within a category.
E. USING SEVERITY INDICES TO WEIGHT CHEMICAL SCORES WITHIN A CATEGORY
Several systems develop human health effects scores that are comparable across different
kinds of non-cancer risks. These systems employ effect severity indices to weight different effects
by the relative risks they pose. For example, a report done for EPA/ECAO develops two scales that
ordinarily rank noncarcinogenic toxic effects, one by lesion severity, another by type of effect. Both
scales rank the effects relative to each other, but do not measure the magnitude of the overall risk.
No attempt was made to rank these effects relative to cancer; nor did the report focus on
reproductive or mutagenic effects. These scales would therefore be useful for ranking only
noncarcinogenic human health risks.
F. RANKING INDIVIDUAL CHEMICALS FOR TOXICITY OR FORMING SUBINDICES
Once chemicals are scored relative to one another within each category, each chemical can
be characterized by its profile of scores. At this point, a chemical's scores can be combined across
categories to form a rank for that chemical in each area of interest (e.g., cancer risk, noncancer risk,
environmental risk). These ranks would be used to calculate the Indicator. One advantage to this
method is that such ranks indicate the relative importance of a chemical with a single number. Many
systems, however, do not aggregate scores across categories (see the Region 7 and the OTS/ORNL
scoring systems) because this requires making the difficult judgement about the relative importance
of different kinds of risk.
Alternatively, scores can be aggregated within a category across chemicals to form a category
subindicator. For example, mammalian acute toxicity scores of all chemicals might be added together
B-23
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(possibly weighted by exposure scores) to calculate the 'mammalian acute toxicity subindex.' This
could be done for each category, creating an aggregate profile of all of the TRI chemicals.
Movements within these subindices would provide measures of environmental improvement.
G. METHODS OF ESTABLISHING THE RELATIVE IMPORTANCE OF RISKS AMONG
CATEGORIES
If a single rank is to be calculated for each chemical from the various categorical scores, one
of several calculation methods could be used. The simplest ways to combine numerical scores is to
multiply or add them together. The flaw in this approach is that ordinal scores have no specific
numerical meaning except within the categories, and even then they do not reflect the magnitude of
the differences, but only the order of the ranks (see above.)
Another approach is to scale the scores then multiply or add them together so that the scores
have a common denominator. For example, we could divide the exposure value at a facility by the
maximum exposure value observed over all facilities. We can then add the scores in different
categories because they have a similar scale.
A third approach is to create a matrix of categories and then rank each cell of the matrix
separately. The cells may (but do not have to) reflect a mathematical function of the individual ranks
of row and column that make up the cell. In this approach, individual chemicals would notbe ranked;
only the categories into which they fell would have ranks. This method is particularly appropriate for
combining several qualitative (i.e. high, medium, low) scores. For example:
Aquatic Risk Rank
Acute
Aquatic
Toxicity
Low
Medium
High
Very High
Persistence
0
0
3
6
9
1
0
6
9
12
2
0
9
12
15
3
0
12
15
18
A fourth option is simply to select the worst score that a chemical has in any category and use
that value as the chemical's rank. This would require that all of the scores be of the same type, i.e.
qualitative or numerical. It also implies that scales of the scores can be equated. The methods for
determining scores in each of the categories would have to meet these criteria.
B-24
-------
Ranks in one category could also be conditional on a rank in a different category. For
example, noncarcinogenic chronic toxicity might only be meaningful if exposure is above threshold
RfD. Criteria for ranking a chemical might require that the noncarcinogenic toxicity score and
exposure score meet separate criteria at the same time.
Special decision rules may be applied in conjunction with the overall scoring system. This
may be useful in cases in which a particular score category is of overwhelming importance given
certain conditions. For example, an extreme carcinogenicity score, regardless of other scores, might
automatically classify a chemical as "high". A de minimis emissions score might eliminate the
chemical from further consideration regardless of toxicity scores. Chemicals with very low toxicity
in all categories might also be eliminated.
H. WEIGHTING SCORES: AN ALTERNATIVE TO METHODS PRESENTED IN i.e.
One option discussed in Section I.e. was to combine scores across categories to derive a
single score for the chemical. A scoring algorithm to combine a chemical's scores across categories
into a single rank requires the assignment of weights to each of the scoring elements. This is probably
the most controversial and difficult step in the process because of the difficulty in evaluating the
relative importance of different kinds of risk. In fact, some of systems we reviewed avoided this step
altogether. However, in order to develop a single index that encompasses different kinds of risk (e.g.
a human health index which incorporates both carcinogenic and noncarcinogenic risks), a weighting
system which implies relative importance of effects will have to be used.
The primary issue in comparing two risks of different nature centers on attributing a common
unit of value to the risks so that their relative magnitude can be compared. Of the EPA and non-EPA
ranking systems reviewed under this assignment, only the Office of Toxic Substances Production-
Based Targeting Methodology explicitly assigns relative values to different kinds of risks. Risks from
oncogenicity, reproductive and neurotoxicity, chronic toxicity, and ecotoxicity were assigned relative
weights of 3,1,2 and 2, respectively. Outside of the Agency, Louisiana's Environmental Action Plan
gave equal weight to human cancer and non-cancer risks.
Other ranking systems implicitly weight different toxicity risks. For example, RQs indirectly
address disparate risk comparisons by restricting the possible scores depending on the particular RQ
being developed: cancer RQs can only range from 1-100, while aquatic toxicity RQs can range from
1-5000. The Hazard Ranking System employs a toxicity scale from 0 to 10,000 that enters into the
calculation of site ranking without adjustment for the kind of toxic risk measured. The scale is based
on various measures depending on the kind of toxicity being incorporated:
B-25
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Human Chronic
Toxicity
Reference dose
(RfD) (mg/kg-
day)
< 0.0005
0.0005 to 0.005
0.005 to 0.05
0.05 to 0.5
0.5 <
Human Carcinogenicity
Weight-of-Evidence and
Slope Factor (SF) (mg/kg-day)
A
0.5 <
0.5 to 0.05
<0.05
NA
NA
B
5<
5 to 0.5
0.5 to 0.05
<0.05
NA
C
50 <
50 to 5
5 to 0.5
<0.5
NA
Acute Human Toxicity
Oral LD50
(mg/kg)
NA
<5
5 to 50
50 to 500
500 <
Dermal
LD50
(mg/kg)
NA
<2
2 to 20
20 to 200
200 <
Dust or
mist
LC50
(mg/1)
NA
<0.2
0.2 to 2
2 to 20
20 <
Gas or Vapor
LC50 (ppm)
NA
<20
20 to 200
200 to 2,000
2,000 <
Assigned
Value
10,000
1,000
100
10
1
This system implies that risk from a class B carcinogen with a slope factor between 5 and 0.5 is ten
times greater than the risk posed by a chronic toxic effect with an RfD between 0.005 and 0.05. The
307(a) Priority Pollutant Chemical Ranking System employs a similar method to develop toxicity
scores.
There are also several approaches described in the economics literature that could be used to
develop the relative severity ranking. First, economists use various techniques to determine the
willingness to pay to avoid various health effects. Other studies examine direct risk/risk tradeoffs.
One methodology involves asking respondents to choose between a number of hypothetical scenarios,
two at a time. A point of indifference can be established between two scenarios through multiple
iterations of questioning. This value determines a relative weight for the health effect being
measured. Another method, the health status index, measures health effects in terms of changes in
quality of life. While the scope of this project does not allow for original research, we could examine
the available economics literature for results that would be applied in this context.
B-26
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II. Options for Ranking of Chemicals
Section I has described the elements of a scoring system. The components described in that
section can be combined in numerous ways to produce an index. The following is a discussion of
three possible options The options presented below should in no way be considered the
universe of possible options. Rather, they should be considered as points of departure for
discussion of an appropriate algorithm for constructing the TRI index. The elements of each of the
options were drawn from (or are modifications of) scoring systems discussed in the review
memorandum entitled "Previous Work on Scoring Systems and Chemical Indices." However, none
of the options presented below follows one system in its entirety; the specific combinations of
components are original to this exercise. Option 1 ranks chemicals ordinally, based on selected
measures of the toxicity and exposure potential of a chemical. These ranks are combined with
population and emissions data to determine the final TRI indicator. Option 2 takes the same general
approach but instead of ordinal ranks uses actual toxicity data values to develop unique rankings for
each chemical. Option 2 also uses modelling to evaluate exposure potential. Option 3 describes an
approach where categories of chemicals are defined based on relevant toxicity and exposure potential
combinations. The categories (rather than the chemicals themselves) are assigned relative ranks.
Chemicals are then assigned to the categories. Site-specific population and emissions data are then
combined with the categorical ranks to calculate the indicator.
Step-by-step descriptions of each of these options are presented below. For each step, we
identify previous EPA or other scoring systems that have used similar approaches. Summaries of
other EPA and non-EPA scoring systems are presented in the memorandum entitled "Previous
Scoring and Ranking Systems" (hereafter referred to as the scoring system review memo). To
illustrate the use of these options, we have created a sample data set of six hypothetical chemicals and
three hypothetical facilities. The chemical-specific and site-specific data for these six chemicals are
shown in Tables 5 and 6. For each of the options proposed, we provide an example of how the
indicator would be constructed based on the sample data set.2 The sample data set is kept simple
intentionally, since our current focus is the conceptual structure of the indicator rather than the
vagaries of our data set. Of course, the actual data set will be far more complicated, uncertain and
incomplete than the sample data presented here. Once the Work Group has had the opportunity to
review and discuss the conceptual approaches, we can explore the details of implementing potential
options using an actual subset of the TRI data set.
While the examples provided show how a human-health based indicator would be developed, the same principles can
be applied to the development of an ecological indicator.
B-27
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Table 5: Chemical Specific Data
Chemical
A
B
C
D
E (metal)
F (metal)
Toxicity Data
Cancer
WOE
B2
B2
B2
A
C
B2
ql*
(kg-day/mg)
10
0.001
1
0.03
5
45(1)
Chronic Toxicity Other Than Cancer
RfD
(mg/kg-day)
0.1
0.2
0.02
0.05
0.005
0.001
Chronic Effect of Concern
liver hypertrophy
nerve damage
spontaneous abortion
liver toxicity
slowed neural response
decreased spermatogenesis
Physicochemical Data
Volatility
Vapor
Pressure
(torr)
3.00e+03
l.OOe+02
4.00e-03
4.00e-04
0
0
Henry's Law
Constant
(atm-m3/mol)
2.00e-07
2.00e-02
l.OOe-05
l.OOe-03
0
0
Partitioning
Koc
(cm3/g)
4.00e+01
2.00e+02
1.10e+03
3.00e+03
na
na
BCF
10
50
200
1000
0
0
Solubility
(mg/1)
4.00e+05
8.00e+02
5.00e+00
2.00e-01
5.00e-01
5.00e+01
Persistence
Photolysis
(1/hr)
5.00e-03
3.00e-08
4.00e-03
l.OOe-05
0
0
Hydrolysis
(1/hr)
6.80e-05
4.00e-08
4.00e-02
7.00e-03
0
0
B-28
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Table 6: Site-Specific Exposure Data
Facility
and
Chemicals
Facility 1
A
B
C
E
Facility 2
C
D
F
Facility 3
A
C
D
E
Emissions
Air Water
(Ibs/yr) (Ibs/yr)
1000 6000
2000 4000
2000 1000
4000 3000
3000 1000
4000 5000
10000 2000
2000 4000
4000 2000
6000 10000
1000 6000
Population Exposed
Air Water
(no. people) (no. people)
3000 500
3000 500
3000 500
3000 500
1000 6000
1000 6000
1000 6000
2000 2000
2000 2000
2000 2000
2000 2000
Characteristics of Facility
Air
High
Dispersion
Low
Dispersion
Medium
Dispersion
Water
Low
Stream
Flow
Medium
Stream
Flow
High
Stream
Flow
B-29
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Option 1
Step 1. Using an ordinal scale, rank chemicals within each toxicity evaluation criterion.
Ordinal ranking is a common approach in a number of ranking systems. Often, ranks are assigned
on an ordinal scale (from 0-10, for example) rather than assigning unique values to each chemical.
The ranking of the chemicals is based on quantitative dose-response information if possible. Several
systems we reviewed used ordinal scales for ranking toxicity, including the TRI Risk Screening
Guide, OTS pollution prevention screening, the OTS/ORNL chemical ranking scheme, and the
Louisiana Environmental Action Plan.
Step 2a. Within each of these toxicity categories, assign severity rank (e.g., cellular change
versus organ damage) for noncarcinogens. Chemicals that have similar reference doses may pose
dissimilar health risks. Severity ranking attempts to weight chemicals based on the relative gravity
of the noncancer health effects risks posed. Severity ranking has been used in several previous
ranking/scoring efforts, such as the OTS pollution prevention screening, the Integrated Environmental
Management Program, and the Louisiana Environmental Action Plan. A scheme for severity ranking
was presented in the ECAO report entitled "Examination of the Severity of Toxic Effects and
Recommendations of a Systematic Approach to Rank Adverse Effects," which is presented in detail
in the scoring systems review memo.
Step 2b. Assign ranks based on weight-of-evidence (e.g., substantial evidence versus suggestive
evidence) ranks for carcinogens. This step is an attempt to recognize the uncertainty in the
classification of a chemical as a human carcinogen. This step uses the CAG weight- of-evidence
(WOE) classification scheme (where A = known human carcinogen; B = probable human carcinogen;
and C = possible human carcinogen) to weight carcinogens. Ranking based on weight-of-evidence
classification has been used in the OTS pollution prevention screening and in the Integrated
Environmental Management Program, and has played a role in other schemes that use "best
professional judgment" to assign ranks to chemicals (such as the Unfinished Business report).
Step 3. Determine relative weights for each toxicity category relative to other categories (e.g.,
hepatic effects versus cancer). This is likely to be among the most controversial steps in the
process. Many scoring systems have avoided combining dissimilar risks and have instead developed
separate scores for different types of risks. For example, the Region VII TRI strategy is to derive
separate indices for chemicals based on acute effects, chronic noncancer, cancer and aquatic toxicity.
However, a few weighting schemes (notably, two regulatory efforts) have compared different types
of toxicity. The Hazard Ranking System (used to place sites on the NPL) implicitly assigns relative
weights to cancer and non-cancer effects by using the same scale to score chemicals on these
attributes (see the scoring systems review memo for further detail). Also, OAQPS has proposed a
scheme for establishing off-setting emissions credits in the program governing early emissions
reductions of hazardous air pollutants. The scheme explicitly allows emissions trading among
carcinogens and other chemicals, where emissions from carcinogens are (numerically) weighted more
heavily than noncarcinogens.
B-30
-------
Step 4. The categorical toxicity rank for each chemical is the product of the raw toxicity rank,
the severity/WOE rank and the categorical rank. The overall toxicity rank for a chemical is
the average of its ranks in the four toxicity categories. Another possible approach would be to
take the root mean square of the four toxicity category ranks (an approach used in the Hazard
Ranking System).
Step 5. For the exposure evaluation criteria, use photolysis rate, solubility, and
bioconcentration factor to rank chemicals for the inhalation, drinking water, and fish ingestion
exposure pathways, respectively. A number of systems use relevant physicochemical values to
evaluate exposure potential in various media. The Risk Screening Guide used selected
physicochemical parameters to qualitatively evaluate mobility of chemicals in each media. The
Hazard Ranking System also uses selected parameters to score exposure potential, although a greater
number of parameters are included in the HRS exposure evaluation because some site-specific data
are generally available for HRS evaluations.
Step 6. Multiply the media-specific exposure rank and toxicity rank by population exposed
and emissions for that pathway for each facility. This step combines the toxicity considerations
with the factors that determine exposure potential (i.e., the chemical's exposure rank and emissions,
and population size). Size of exposed population is used as a ranking criterion in many of scoring
systems we reviewed, including: the PPD TRI pollution prevention targeting; OP A ranking of
discharges to POTWs and surface waters; OTS TSCA prescreening of TRI chemicals; the Hazard
Ranking System; the Integrated Environmental Management Program; the Louisiana Environmental
Action Plan; and the California Air Toxics Hotspots Program.
The use of population size as a prominent weighting factor may be unacceptable to those who feel
that such an emphasis undervalues risks to rural populations. Furthermore, various regulatory efforts
in the Agency focus risks to the Most Exposed Individual (MEI); a TRI indicator method which does
not consider MEI risks would conflict with this philosophy. There are also difficulties associated with
characterizing the size of exposed populations for certain exposure pathways (such as solid waste
disposal). These difficulties will result in unequal levels of uncertainty in the exposure potential
evaluation across exposure pathways.
On the other hand, overall population risk has been used elsewhere (notably, in the Unfinished
Business report) to characterize general environmental progress; avoidance of population risk, not
MEI risk, is also used in cost-benefit analyses to describe potential benefits of implementing
environmental regulations.
B-31
-------
Step 7. The final index is the sum of the weighted volumes for all TRI chemicals for all
pathways across all facilities.
A step-by-step example demonstrating Option 1 for the sample data set is found in Figure
1.
Advantages - This option allows fine-scale tracking of subtle differences among chemicals.
Importantly, by calculating media-chemical-facility subindices, we can easily identify underlying
reasons for changes in the overall index by tracking individual media, industries, or chemicals.
However, the final calculation yields a single index rather than a series of subindices across categories
that may be hard for the public to interpret.
Disadvantages - Determining appropriate and sensible weighting factors for the different elements
is difficult. Retaining a proportional scoring system based largely on ordinal ranks and performing
mathematical functions on them may give the false impression that the absolute magnitude of the
ranks have numerical meaning.
B-32
-------
Figure 1. Example Calculation for Option 1 Ranking System
Step 1. Using an ordinal scale, rank chemicals within each selected toxicity evaluation criteria.
For this and subsequent steps, ranks are ordered low to high.
Chemical
A
B
C
D
E (metal)
F (metal)
Cancer
5
1
3
2
4
6
Chronic Toxicity Other Than Cancer
Liver
1
2
Neurologic
1
2
Reproductive
1
2
Step 2. Within each of these categories, assign severity and weight of evidence rank to each chemical.
2.a. For this step, we use weights from 1 to 3 to rank the relative severity of chronic effects.
Chemical
A
B
C
D
E (metal)
F (metal)
Chronic Toxicity Other Than Cancer
Liver
1
o
J
Neurologic
3
1
Reproductive
2
1
B-33
-------
2.b. We use weights from 1 to 3 for assigning carcinogens by their weight of evidence classification.
Chemical
A
B
C
D
E (metal)
F (metal)
Cancer
(WOE)
2
2
2
3
1
2
Step 3. Determine weights for each toxicity category.
For the purposes of this example, the relative weights are:
Cancer
Reproductive Effects
Neurological Effects
Other Chronic Effects
10
7
5
2
Step 4. Derive categorical toxicity rank by multiplying toxicity rank, effect-specific severity rank,
weight of evidence rank and cross-category severity rank. To get overall rank, average the
chemical's rank in each category.
Chemical
A
B
C
D
E (metal)
F (metal)
Cancer
(a)
5x2x10= 100
1 x 2 x 10 = 20
3 x 2 x 10 = 60
2 x 3 x 10 = 60
4 x 1 x 10 = 40
6x2x10= 120
Chronic Toxicity Other Than Cancer
(b)
Liver
1x1x2=2
2x3x2= 12
Neurologic
1x3x5= 15
2x1x5= 10
Reproductive
1x2x7= 14
2x1x7= 14
OVERALL
AVERAGE
(a+b)/2
51
17.5
37
36
25
67
B-34
-------
Step 5. Derive Rank for each exposure pathway based on salient physicochemical parameter.
Chemical
A
B
C
D
E (metal)
F (metal)
Air
Based on
Photosynthesis
1
4
2
3
5
5
Drinking Water
Based on
Solubility
6
5
3
1
2
4
Fish Ingestion
Based on BCF
3
4
5
6
1
1
Step 6. Combine exposure and toxicity ranks with population and emissions data to obtain
media-specific indices.
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
Chemical
A
A
B
C
C
C
D
D
E
E
F
Emissions
(Ibs/yr)
(a)
1000
2000
2000
2000
3000
4000
4000
6000
4000
1000
1000
Pop. Exposed
(no. people)
(b)
3000
2000
3000
3000
1000
2000
1000
2000
3000
2000
1000
Toxicity
Rank
(c)
51
51
17.5
37
37
37
36
36
25
25
67
Exposure
Rank
(d)
1
1
4
2
2
2
o
J
o
J
5
5
5
TOTAL:
AIR INDEX
e=axbxcxd
1.5E+08
2.0E+08
4.2E+08
4.4E+08
2.2E+08
5.9E+08
4.3E+08
1.3E+08
1.5E+09
2.5E+08
3.4E+09
8.9E+09
B-35
-------
FOR WATER:
We obtain an average rank for water exposures using the following formula:
Total exposure to water sources is expressed as : 2L drinking water + [0.14 kg fish x BCF (L/kg)]
Average rank for water = (Rank for drinking water x (2 L/total exp.)) + (Rank for fish x (0.14 x BCF)/total exp.)
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
TOTAL:
Chemical
A
A
B
C
C
C
D
D
E
E
F
Emissions
(Ibs/yr)
(a)
6000
4000
4000
1000
1000
2000
5000
10000
500
2000
6000
Pop.
Exposed
(no. people)
(b)
500
2000
500
500
6000
2000
6000
2000
500
2000
6000
Toxicity
Rank
(c)
51
51
17.5
37
37
37
36
36
25
25
67
Drinking
Water
Exposure Rank
(d)
6
6
5
3
3
3
1
1
2
2
4
Fish Ingestion
Exposure Rank
(e)
3
3
4
5
5
5
6
6
1
1
1
BCF
Value
(f)
10
10
50
200
200
200
1000
1000
0
0
0
Average Water Rank
(g)=(d)x2L/tot exp
+(e)x0.14(f)/totexp
5
5
4
5
5
5
6
6
2
2
4
WATER
INDEX
h=axbxcxg
7.3E+08
1.9E+09
1.5E+08
9.0E+07
1.1E+09
7.2E+08
6.4E+09
4.3E+09
7.5E+07
6.0E+08
3.2E+09
1.9E+10
B-36
-------
Step 7. Sum media-specific indices for overall TRI index.
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
Chemical
A
A
B
C
C
C
D
D
E
E
F
TOTAL:
AIR
INDEX
(a)
1.5E+08
2.0E+08
4.2E+08
4.4E+08
2.2E+08
5.9E+08
4.3E+08
1.3E+09
1.5E+09
2.5E+08
3.4E+09
8.9E+09
WATER
INDEX
(b)
7.3E+08
1.9E+09
1.5E+08
9.0E+07
1.1E+09
7.2E+08
6.4E+09
4.3E+09
7.5E+07
6.0E+08
3.2E+09
1.9E+10
TOTAL
INDEX
c=(a+b)
8.8E+08
2.1E+08
5.7E+08
5.3E+08
1.3E+09
1.3E+09
6.8E+09
5.6E+08
1.6E+09
8.5E+08
6.6E+09
2.8E+10
B-37
-------
Option 2.
Step 1. Rank chemicals using actual proportional measures for the categories of concern. For
carcinogens, use qt* values. The qt* expresses risk to an individual per milligram (mg) of chemical
per kilogram of body weight per day (mg/kg-day). For noncarcinogens, use the inverse of the RfD.
The RfD is the dose (expressed as mg of chemical per kg body weight per day) below which no
adverse effects are expected to occur. Using proportional measures for toxicity ranking is a common
approach in other ranking systems. For example, RQs were used by OPA in ranking discharges to
POTWs and to surface water bodies; OTS TSCA prescreening of TRI chemicals used RQ as a cutoff
for high concern chemicals. RfDs and Q* are proposed as the basis for toxicity ranking in Region
VII's TRI strategy. Outside the Agency, the California Air Toxic Hotspots program uses actual dose-
response data (in conjunction with exposure modelling - discussed below) in their identification and
ranking of air toxics problems in the state.
Step la. Since toxicity values in different categories have dissimilar units (e.g., cancer potency
estimate versus an RfD), normalize the values by expressing the chemical's toxicity value in a
given category as a fraction of the maximum value possible in that category. The resulting
fraction is the chemical's rank in that category. Expressing the ranks in this manner will also allow
us to combine the ranks with exposure potential ranks that have been normalized in a similar manner
(see below). This normalizing approach was used in OAQPS' Source Category Ranking System,
which ranks potential air toxics problems across industries.
Once the toxicity ranks within categories are determined, the next three steps are the same as those
described in Option 1.
Step 2a and 2b. Within each toxicity category, assign severity and weight-of-evidence (WOE)
ranks to each chemical.
Step 3. Determine relative weights for each toxicity category relative to other categories.
Step 4. Determine the categorical toxicity rank for each chemical. The categorical rank is the
product of the raw toxicity rank, the severity rank, the WOE rank and the categorical rank. The
overall toxicity rank is the average of its ranks in the four toxicity categories.
Step 5. For the exposure evaluation, model the fate and transport of the chemicals To do so,
use the emissions data, site-specific environmental characteristics (or default values where these are
not available), and physicochemical properties to obtain ambient media concentrations at specified
distances. These data can be weighted by the number of persons at each distance (that is, the number
of persons exposed to each estimated concentration) to obtain population-weighted average
exposures for each site where chemical is emitted.
As mentioned earlier, specific methods for applying exposure modelling to the TRI database are
discussed in a separate memo and will not be expanded on here. However, it should be noted that
B-38
-------
generic exposure modelling to rank exposure potential is used by a number of other scoring/ranking
systems. For example, Appendix B of the Risk Screening Guide presents results of generic air
modelling to assist readers in the evaluation of air releases. OTS' TSCA prescreening of TRI
chemicals used generic air and water exposure modelling to place chemicals in categories of low,
medium and high concern. Furthermore, generic air modelling was used by OAQPS to identify high
risk chemicals as part of defining offsets credits for early emissions reductions of hazardous air
pollutants. Other scoring methods using generic modelling approaches include the California Air
Toxics Hotspots program and OAQPS' Source Category Ranking System.
Step 6. For each chemical-facility combination, express the exposure estimate as a fraction of
the maximum exposure observed to obtain an exposure index. Normalizing the exposure values
allows us to combine the exposure ranks with the toxicity rankings in later steps. Otherwise, we
would be combining ranks with dissimilar scales. The exposure index is then combined with the
toxicity rank to derive the medium-specific index. The final index is the sum of the media-specific
indices.
(A modification to this approach would be to use the RfDs and q^s in concert with the exposure
models to estimate cancer cases and/or number of individuals above the RfD. The "cases" could then
be scaled by the maximum number of "cases" observed at each facility to obtain a unique subindex
for each chemical-facility combination by exposure pathway. The index for the chemical would be
the sum of the subindices across all facilities. The overall index would be the sum of the chemical
indices.)
An example demonstrating Option 2 for the sample data set is found in Figure 2.
Advantages - The use of location-dependent exposure indices allows the index to reflect changes in
where chemicals are released, as well as changes in volume. Normalizing toxicity ranks allows the
use of structure-activity relationships to fill in data gaps; if a particular toxicity value is not known,
the chemical can still be assigned a rank relative to the highest value in the category.
Disadvantages - The lack of toxicity data for many of the TRI chemicals would hinder this approach.
This approach presents some programming challenges for performing multiple chemical, multiple site
analyses. This option has the same difficulties as Option 1 in assigning appropriate sensible
weighting factors to different elements. Furthermore, the option relies on normalizing the ranks based
on a "reference chemical" which has the maximum value in the ranking category. A danger in this
approach is the possibility that the underlying data (toxicity or physicochemical information) may
change over time. Since all other chemical ranks are keyed to the values for this chemical, a change
in the reference chemical would change the entire index. Therefore, rather than selecting the chemical
with the maximum value, we may want to select as the reference chemical a well-known, well-
characterized chemical for which underlying data is unlikely to change. Using this approach, the
reference chemical rank would still be 1, while chemicals with values greater than the reference
chemical would be assigned ranks proportionally greater than 1.
B-39
-------
Figure 2. Example Calculation for Option 2 Ranking System
Step 1. Using inverse of RfD value and actual q* values, rank chemicals within each selected toxicity
evaluation criteria.
For this and subsequent steps, ranks are ordered low to high.
Chemical
A
B
C
D
E (metal)
F (metal)
Cancer
(q*)
10
0.001
1
0.03
5
45
Chronic Toxicity Other Than Cancer
(1/RfD)
Liver
10
20
Neurologic
5
200
Reproductive
50
1000
Step la. Since the raw toxicity ranks are on different scales, express the rank in each category as a
fraction of the maximum rank observed in that category. The maximum rank is 1.
Chemical
A
B
C
D
E (metal)
F (metal)
Cancer
2.2E-01
2.2E-05
2.2E-02
6.7E-04
1.1E-01
l.OE+00
Chronic Toxicity Other Than Cancer
Liver
0.5
1
Neurologic
0.025
1
Reproductive
0.05
1
B-40
-------
Step 2. Within each of these categories, assign severity and weight of evidence rank to each chemical.
2.a. As in Option 1, we use weights from 1 to 3 to rank the relative severity of chronic effects.
Chemical
A
B
C
D
E (metal)
F (metal)
Chronic Toxicity Other Than Cancer
Liver
1
o
J
Neurologic
3
1
Reproductive
2
1
2.b. We use weights from 1 to 3 for assigning carcinogens by their weight of evidence classification.
Chemical
A
B
C
D
E (metal)
F (metal)
Cancer
(WOE)
2
2
2
3
1
2
Step 3. Determine severity weights for each toxicity category.
This step is also the same as Option 1. For the purposes of this example, the relative weights are:
Cancer
Reproductive Effects
Neurological Effects
Other Chronic Effects
10
7
5
2
B-41
-------
Step 4. Derive categorical toxicity rank by multiplying toxicity rank, severity rank and category rank.
To get overall rank, average the chemical's rank in each category.
Chemical
A
B
C
D
E (metal)
F (metal)
Cancer
(a)
2e-lx2xlO = 4
2e-5 x 2 x 10 = 4e-4
2e-2 x 2 x 10 = 4e-l
7e-4 x 3 x 10 = 2e-2
le-lxlxlO= 1
1 x 2 x 10 = 20
Chronic Toxicity Other Than Cancer
(b)
Liver
0.5x1x2= 1
1x3x2=6
Neurologic
0.025 x 3 x 5 =
4e-l
1x1x5=5
Reproductive
0.05x2x7 =
7e-l
1x1x7=7
OVERALL
AVERAGE
(a+b)/2
2.7
0.2
0.6
3.0
3.1
13.5
Step 5. Derive rank for each exposure pathway using modelling approach.
For this step, we use computer programs to estimate population-weighted average in each medium,
for each chemical at each facility.
The steps are as follows:
INPUTS:
OUTPUTS:
Emissions (Ibs/yr)
Chemical-specific model inputs
Site -specific model parameters
Default model parameters
Media concentrations at varying
distance from source
Population exposed at each distance
Population-weighted
average exposure
B-42
-------
For the purposes of this example, we assume that these models yield the following results:
FOR AIR:
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
Chemical
A
A
B
C
C
C
D
D
E
E
F
Emissions
(Ibs/yr)
1000
2000
2000
2000
3000
4000
4000
6000
4000
1000
10000
Pop. Exposed
(no. people)
3000
2000
3000
3000
1000
2000
1000
2000
3000
2000
1000
Population- Weighted
Average Exposure
(calculated with model)
5.0E-04
3.3E-03
9.0E-03
2.0E-03
3.3E-03
8.0E-03
3.3E-02
2.0E-02
2.0E-02
1.7E-02
1.7E-01
FOR WATER:
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
Chemical
A
A
B
C
C
C
D
D
E
E
F
Emissions
(Ibs/yr)
6000
4000
4000
1000
1000
2000
5000
10000
3000
6000
2000
Pop. Exposed
(no. people)
500
2000
500
500
6000
2000
6000
2000
500
2000
6000
Population- Weighted
Average Exposure
(calculated with model)
3.5E-02
9.4E-03
1.2E-02
2.9E-04
7.1E-04
4.7E-04
2.8E-02
4.7E-04
1.8E-04
7.1E-03
7.1E-02
B-43
-------
Step 5a. Take the exposures as a fraction of the maximum in order to get exposure indices for the
chemicals.
FOR AIR:
FOR WATER:
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
Chemical
A
A
B
C
C
C
D
D
E
E
F
Exposure Index
3.0E-03
2.0E-02
5.4E-02
1.2E-02
2.0E-02
4.8E-02
2.0E-01
1.2E-01
1.2E-01
l.OE-01
l.OE+00
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
Chemical
A
A
B
C
C
C
D
D
E
E
F
Exposure Index
5.0E-01
1.3E-01
1.7E-01
4.2E-03
l.OE-02
6.7E-03
4.0E-01
6.7E-03
2.5E-03
l.OE-01
l.OE+00
B-44
-------
Step 6. To derive media-specific indices, multiply toxicity ranks and exposure indices. To derive
final index, add media-specific indices.
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
TOTAL-
Chemical
A
A
B
C
C
C
D
D
E
E
F
Air Exposure
Index
(from Step 5a)
(a)
3.0E-03
2.0E-02
5.4E-02
1.2E-02
2.0E-02
4.8E-02
2.0E-01
1.2E-01
1.2E-01
l.OE-01
l.OE+00
Toxicity
Rank
(from Step 4)
(b)
2.7
2.7
0.2
0.6
0.6
0.6
o
J
o
J
3.1
3.1
13.5
AIR INDEX
c=(axb)
8.10E-03
2.72E+00
2.54E-01
6.12E-01
6.20E-01
6.48E-01
3.20E+00
3.12E+00
3.22E+00
3.20E+00
1.45E+01
32 1
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
TOTAL:
Chemical
A
A
B
C
C
C
D
D
E
E
F
Water
Exposure Index
(from Step 5a)
(a)
5.0E-01
1.3E-01
1.7E-01
4.2E-03
l.OE-02
6.7E-03
4.0E-01
6.7E-03
2.5E-03
l.OE-01
l.OE+00
Toxicity
Rank
(from Step 4)
(b)
2.7
2.7
0.2
0.6
0.6
0.6
3
3
3.1
3.1
13.5
WATER INDEX
c=(axb)
1.35E+00
2.83E+00
3.67E-01
6.04E-01
6.10E-01
6.07E-01
3.40E+00
3.01E+00
3.10E+00
3.20E+00
1.45E+01
33.6
B-45
-------
Facility
Facility 1
Facility 3
Facility 1
Facility 1
Facility 2
Facility 3
Facility 2
Facility 3
Facility 1
Facility 3
Facility 2
TOTAL:
Chemical
A
A
B
C
C
C
D
D
E
E
F
AIR
INDEX
(a)
8.10E-03
2.72E+00
2.54E-01
6.12E-01
6.20E-01
6.48E-01
3.20E+00
3.12E+00
3.22E+00
3.20E+00
1.45E+01
32.1
WATER
INDEX
(b)
1.35E+00
2.83E+00
3.67E-01
6.04E-01
6.10E-01
6.07E-01
3.40E+00
3.01E+00
3.10E+00
3.20E+00
1.45E+01
33.6
OVERALL INDEX
c=(a+b)
1.4
5.6
0.6
1.2
1.2
1.3
6.6
6.1
6.3
6.4
29.0
65.7
B-46
-------
Option 3
Step 1. From among the various toxicity categories, choose the category which yields the lowest
dose. This is the limiting dose. This decision rule was used in the ranking of chemicals for inclusion
as priority pollutants under the Clean Water Act.
Step 2. Establish criteria for placing chemicals in categories of low, medium and high toxicity
based on the limiting dose, and classify chemicals based on these criteria. A number of scoring
systems have provided criteria that could be used to place chemicals in categories of low, medium
and high concern. The human and environmental toxicity categories into which chemicals were
divided and the criteria used to place chemicals in these categories for each scoring system were
summarized in Tables 1 and 2 of this memo.
Step 3. To assess exposure potential, use photolysis rate, solubility, and bioconcentration factor
for the inhalation, drinking water, and fish ingestion exposure pathways, respectively to place
chemicals in categories of low, medium and high for exposure potential. Classify chemicals
based on these criteria. As with the toxicity ranking, a number of scoring systems have provided
criteria that could be used to place chemicals in categories of low, medium and high exposure
potential. The exposure potential categories into which chemicals were divided and the criteria used
to place chemicals in these categories for each scoring system were summarized in Table 3 of this
memo.
Step 4. Construct human hazard and exposure potential matrices for each medium of concern;
assign chemicals to each cell according to their toxicity and medium-specific classifications.
An example of such a matrix is given in ORD's "Simplified Approach for Screening and Categorizing
Toxic Chemicals." A toxicity/exposure matrix was also used in the University of Michigan's
application of the Hazard Ranking System to the prioritization of organic compounds at hazardous
waste sites.
Step 5. Assign weights to the low, medium and high categories for exposure potential and
toxicity. In our example, the rank for each cell in the matrix is the product of the toxicity weight and
the exposure weight for the row and column that define the cell. The ORD simplified approach to
classifying toxic chemicals provides an example of values assigned to matrix cells. OTS's TSCA
prescreening of TRI chemicals also presents an exposure/toxicity matrix, but assigns ranks of low,
medium or high to each cell, rather than numerical weights.
Step 6. Individual chemical-facility indices are derived for each medium by multiplying the
rank for the cell in which the chemical falls, the population exposed via that medium, and the
emissions to that medium.
Step 7. The overall index is the sum of the media-specific indices across all chemicals and
across all facilities. An example demonstrating Option 3 for the sample data set is found in Figure
3.
B-47
-------
Advantages - This method avoids combining toxicity categories. It provides a simple but informative
rank for each chemical based on a two-way classification scheme. The final index weightings are
explicit and understandable.
Disadvantages - This approach assumes that all of the toxicity categories are of equal importance.
In this approach, chemicals do not get specific exposure-toxicity ranks; only the categories to which
they belong are ranked. The use of three broad categories within the scoring elements does not
allow fine-scale differentiation among values for chemicals within a scoring element. This particular
flaw would prevent us from distinguishing changes in chemicals with very high toxicities from
changes in "border" chemicals with marginally high toxicities. Options to address this problem
include (a) eliminating "border" chemicals from the index calculation; and (b) performing more
explicit analysis on the "border" chemicals to evaluate how different the index would be if they
switched into different categories.
B-48
-------
Figure 3. Example Calculation for Option 3 Ranking System
Step 1. From among the toxicity criteria of interest, choose the lowest dose for each chemical among
all the categories. This is the limiting dose.
Chemical
A
B
C
D
E
F
Cancer
Risk-specific Dose
at 1E-4 Risk Level
(mg/kg-day)
(lE-4/q*)
1E-05
1E-01
1E-04
3E-03
2E-05
2E-06
Chronic Toxicity Other Than Cancer
Liver
RfD
(mg/kg-day)
1E-01
5E-02
Neurologic
RfD
(mg/kg-day)
2E-01
5E-03
Reproductive
RfD
(mg/kg-day)
2E-02
1E-03
LIMITING
DOSE
(mg/kg-day)
1E-05
1E-01
1E-04
3E-03
2E-05
2E-06
Step 2. Place chemicals into high, medium and low categories.
For this step, we need to develop criteria for what constitutes a high, medium, or low toxicity. For
the purposes of this example, we assign the following values to these categories:
Category Range
High Dose < 1E-4
Medium 1E-4 < Dose < 1E-2
Low
1E-2 < Dose
B-49
-------
Using these criteria, we classify the chemicals:
Chemical
A
B
C
D
E
F
LIMITING
DOSE
(mg/kg-day)
1E-05
1E-01
1E-04
3E-03
2E-05
2E-06
TOXICITY
CATEGORY
High
Low
Medium
Medium
High
High
B-50
-------
Step 3. Based on salient physicochemical properties, assign chemicals to high, medium and low
exposure potential categories.
For this step, we must establish media-specific criteria for assigning chemicals to high, medium and
low categories.
For the purposes of this example, we make the following assignments:
Exposure Medium
Air
Drinking Water
Fish
Criterion
Low
photolysis < 1E-7
solubility < 10
BCF < 50
Medium
1E-6 < photolysis < 1E-4
10 < solubility < 500
50 < BCF < 500
High
1E-4 < photolysis
500 < solubility
500 < BCF
Using these criteria, we classify the chemicals:
Chemical
A
B
C
D
E
F
Air
High
Low
High
Medium
Low
Low
Drinking Water
High
High
Low
Low
Low
Medium
Fish
Low
Medium
Medium
High
Low
Low
B-51
-------
Step 4. Using the exposure and toxicity ranks, create a toxicity-exposure matrix for each medium.
Toxicity-Exposure Matrix
Toxicity
Low
Medium
High
Air Exposure
Low
B
E,F
Medium
D
High
C
A
Drinking Water Exposure
Low
C
E
Medium
D
F
High
B
A
Fish Ingestion Exposure
Low
A,E,F
Medium
B
C
High
D
Step 5. Assign values to each cell in the matrix.
For this step, ranks are assigned the following values:
Category
High
Medium
Low
Exposure Rank
0.4
0.2
0.1
Toxicity Rank
5
o
5
i
The value for the cell is the product of the toxicity times the exposure rank.
Toxicity-Exposure Matrix Values
Toxicity
Low
Medium
High
Air Exposure
Low
0.1
0.5
Medium
0.6
High
1.2
2
Drinking Water Exposure
Low
0.3
0.5
Medium
0.6
1
High
0.4
2
Fish Ingestion Exposure
Low
0.5
Medium
0.2
0.6
High
1.2
B-52
-------
Step 6. Combine facility-specific emissions and population data to obtain media-specific chemical
scores.
EMISSION-EXPOSURE SCORES
(FOR AIR:)
Facility
1
2
3
Chemical
A
B
C
E
C
D
F
A
C
D
E
TOTAL:
Air Emissions
(Ib/yr)
1000
2000
2000
4000
3000
4000
10000
2000
4000
6000
1000
Population
Exposed
Via Air
3000
3000
3000
3000
1000
1000
1000
2000
2000
2000
2000
Matrix Value
2
0.1
1.2
0.5
1.2
0.6
0.5
2
1.2
0.6
0.5
AIR SCORE
6.0E+06
6.0E+05
7.2E+06
6.0E+06
3.6E+06
2.4E+06
5.0E+06
8.0E+06
9.6E+06
7.2E+06
l.OE+06
5.7E+07
(FOR WATER:)
Facility
1
2
3
Chemical
A
B
C
E
C
D
F
A
C
D
E
TOTAL:
Water
Emissions
(Ib/yr)
6000
4000
1000
3000
1000
5000
2000
4000
2000
10000
6000
Population
Exposed
Via Water
500
500
500
500
6000
6000
6000
2000
2000
2000
2000
Drinking
Water Matrix
Value
2
0.4
0.3
0.5
0.3
0.6
1
2
0.3
0.6
0.5
Fish
Matrix
Value
0.5
0.2
0.6
0.5
0.6
1.2
0.5
0.5
0.6
1.2
0.5
Average
Matrix
Value
1.3
0.3
0.5
0.5
0.5
0.9
0.8
1.3
0.5
0.9
0.5
WATER
SCORE
3.8E+06
6.0E+05
2.3E+05
7.5E+05
2.7E+06
2.7E+07
9.0E+06
l.OE+07
1.8E+06
1.8E+07
6.0E+06
8.0E+07
B-53
-------
Step 7. Combine the media-specific ranks to obtain overall rank.
Facility
1
2
3
Chemical
A
B
C
E
C
D
F
A
C
D
E
TOTAL:
AIR SCORE
6.0E+06
6.0E+05
7.2E+06
6.0E+06
3.6E+06
2.4E+06
5.0E+06
8.0E+06
9.6E+06
7.2E+06
l.OE+06
5.7E+07
WATER
SCORE
3.8E+06
6.0E+05
2.3E+05
7.5E+05
2.7E+06
2.7E+07
9.0E+06
l.OE+07
1.8E+06
1.8E+07
6.0E+06
8.0E+07
OVERALL
SCORE
9.8E+06
1.2E+06
7.4E+06
6.7E+06
6.3E+06
2.9E+07
1.4E+07
1.8E+07
1.1E+07
2.5E+07
7.0E+06
1.4E+08
B-54
-------
Appendix C
Available Toxicity Data for TRI Chemicals
C-l
-------
Sorted Compilation of Toxicity Weights for Scored TRI Chemicals
Table C-l contains all TRI chemicals on the 1995 roster which have been assigned toxicity weights, by
sorted toxicity weight category.
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
Chemical Name
Toxicity Weight
Inhalation
Oral
Source
Chemicals With One or More Toxicity Weights of 1,000,000
92-87-5
542-88-1
106-93-4
77-78-1
759-73-9
55-18-5
62-75-9
75-55-8
1314-20-1
Benzidine
Bis(chloromethyl)ether
Dibromoethane, 1,2-
Dimethyl sulfate
N-Nitroso-N-ethylurea
N-Nitrosodiethylamine
N-Nitrosodimethylamine
Propyleneimine
Thorium dioxide
1000000
1000000
10000
1000000
1000000*
1000000
100000
1000000*
10000
1000000
1000000
1000000
1000000*
1000000
1000000
1000000
1000000
1000000
IRIS
IRIS
IRIS
interim derived
HEAST
IRIS
IRIS
final derived
final derived
Chemicals With One or More Toxicity Weights of 100,000
107-02-8
309-00-2
319-84-6
7429-90-5
7440-38-2
N020
98-07-7
N050
7440-41-7
56-35-9
2602-46-2
1937-37-7
Acrolein
Aldrin
alpha-Hexachlorocyclohexane
Aluminum (fume or dust)
Arsenic
Arsenic compounds
Benzo trichloride
Beryllium compounds
Beryllium
Bis(tributyltin) oxide
C.I. Direct Blue 6
C.I. Direct Black 38
100000
100000
100000
100000
100000
100000
100000*
100000
100000
100000*
100000*
100000*
100000*
100000
100000
10000
10000
100000
10000
10000
100000
100000
100000
IRIS
IRIS
IRIS
interim derived
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
HEAST
HEAST
C-2
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
16071-86-6
7440-43-9
N078
532-27-4
7440-48-4
N096
25376-45-8
764-41-0
119-93-7
302-01-2
78-84-2
N420
7439-92-1
109-77-3
7439-96-5
N450
150-50-5
624-83-9
924-16-3
621-64-7
7723-14-0
N575
1336-36-3
62-74-8
7550-45-0
584-84-9
Chemical Name
C.I. Direct Brown 95
Cadmium
Cadmium compounds
Chloroacetophenone, 2-
Cobalt
Cobalt compounds
Diaminotoluene (mixed isomers)
Dichloro-2-butene, 1,4-
Dimethylbenzidine, 3,3'-
Hydrazine
Isobutyraldehyde
Lead compounds
Lead
Malonitrile
Manganese
Manganese compounds
Merphos
Methyl isocyanate
N-Nitrosodi-n-butylamine
N-Nitrosodi-n-propylamine
Phosphorus (yellow or white)
Polybrominated Biphenyls (PBBs)
Fob/chlorinated biphenyls
Sodium fluoroacetate
Titanium tetrachloride
Toluene-2,4-diisocyanate
Toxicity Weight
Inhalation
100000*
100000
100000
100000
100000
100000
100000*
100000
100000*
100000
100000
100000
100000
100000*
100000
100000
100000*
100000
100000
100000*
100000*
100000*
1000
100000*
100000
100000
Oral
100000
10000
10000
100000*
100000*
100000*
100000
100000*
100000
10000
100000*
100000
100000
100000
10
10
100000
100000*
100000
100000
100000
100000
100000
100000
100000*
100
Source
HEAST
IRIS
IRIS
IRIS
interim derived
interim derived
interim derived
HEAST
HEAST
IRIS
interim derived
interim derived
interim derived
HEAST
IRIS
IRIS
IRIS
final derived
IRIS
IRIS
IRIS
HEAST
IRIS
IRIS
interim derived
final derived
C-3
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
91-08-7
26471-62-5
78-48-8
Chemical Name
Toluene-2,6-Diisocyanate
Toluenediisocyanate
Tributyltrithiophosphate (DBF), S,S,S-
Toxicity Weight
Inhalation
100000
100000
100000*
Oral
100
100
100000
Source
final derived
IRIS
IRIS
Chemicals With One or More Toxicity Weights of 10,000
79-06-1
79-10-7
107-13-1
107-05-1
20859-73-8
62-53-3
7440-36-0
NO 10
111-44-4
106-99-0
141-32-2
57-74-9
10049-04-4
95-80-7
96-12-8
542-75-6
62-73-7
64-67-5
60-51-5
534-52-1
606-20-2
122-66-7
Acrylamide
Acrylic acid
Acrylonitrile
Allyl chloride
Aluminum phosphide
Aniline
Antimony
Antimony compounds
Bis(2-chloroethyl)ether
Butadiene, 1,3-
Butyl acrylate
Chlordane
Chlorine dioxide
Diaminotoluene, 2,4-
Dibromo-3-chloropropane (DBCP), 1,2-
Dichloropropylene, 1,3-
Dichlorvos
Diethyl sulfate
Dimethoate
Dinitro-o-cresol, 4,6-
Dinitrotoluene, 2,6-
Diphenylhydrazine, 1,2-
10000
10000
1000
10000
10000*
10000
10000*
10000*
10000
10000
10
10000
10000
10000*
10000
100
10000
10000*
10000*
10000
10000*
10000
10000
10
10000
10000*
10000
100
10000
10000
10000
10000*
10000
10000
10000*
10000
10000*
10000
10000
10000
10000
10000
10000
10000
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
interim derived
IRIS
IRIS
HEAST
IRIS
IRIS
IRIS
final derived
IRIS
interim derived
IRIS
IRIS
C-4
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
106-89-8
96-45-7
75-21-8
76-44-8
118-74-1
70-30-4
67485-29-4
7783-06-4
58-89-9
99-65-0
7439.97-6
N458
126-98-7
94-74-6
298-00-0
1313-27-5
98-95-3
55-63-0
90-04-0
528-29-0
100-25-4
7803-51-2
88-89-1
91-22-5
No CASRNb
Chemical Name
Epichlorohydrin
Ethylene thiourea
Ethylene oxide
Heptachlor
Hexachlorobenzene
Hexachlorophene
Hydramethylnon(Tetrahydro-5,5-di-methyl-
2(1H)- pyrimidinone[3-[4-
(trifluoromethyl)phenyl]-l-[2-[4-(trifluoromet
Hydrogen sulfide
Lindane
m-Dinitrobenzene
Mercury
Mercury compounds
Methacryonitrile
Methoxone ((4-Chloro-2-methylphenoxy)acetic
acid) (MCPA)
Methyl parathion
Molybdenum trioxide
Nitrobenzene
Nitroglycerin
o-Anisidine
o-Dinitrobenzene
p-Dinitrobenzene
Phosphine
Picric acid
Quinoline
Strychnine and salts
Toxicity Weight
Inhalation
10000
10000*
10000*
10000
10000
10000*
10000*
10000
10000*
10000*
10000
10000
10000*
10000*
10000*
10000
10000*
10000*
10000
10000*
10000*
10000
10000
10000*
10000*
Oral
100
10000
10000
10000
10000
10000
10000
1000
10000
10000
10000*
10000*
10000
10000
10000
1000
10000
10000
1000
10000
10000
10000
10000
10000
10000
Source
IRIS
IRIS
HEAST
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
interim derived
IRIS
interim derived
interim derived
HEAST
HEAST
IRIS
final derived
HEAST
IRIS
C-5
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
7664-93-9
62-56-6
8001-35-2
75-01-4
81-81-2
Chemical Name
Sulfuric acid
Thiourea
Toxaphene
Vinyl chloride
Warfarin and salts
Toxicity Weight
Inhalation
10,000
10000*
10000
10000*
10000*
Oral
1
10000
10000
10000
10000
Source
final derived
final derived
IRIS
HEAST
IRIS
Chemicals With One or More Toxicity Weights of 1,000
30560-19-1
75-07-0
116-06-3
107-18-6
33089-61-1
1332-21-4
100-44-7
74-83-9
156-62-7
1563-66-2
56-23-5
79-11-8
67-66-3
80-15-9
135-20-6
68085-85-8
2303-16-4
101-80-4
91-94-1
Acephate (Acetylphosphoramidothioic acid O,S-
dimethyl ester)
Acetaldehyde
Aldicarb
Allyl alcohol
Amitraz
Asbestos (friable)
Benzyl chloride
Bromomethane (Methyl Bromide)
Calcium cyanamide
Carbofuran
Carbon tetrachloride
Chloroacetic acid
Chloroform
Cumene hydroperoxide
Cupferron
Cyhalothrin (3 -(2-Chloro-3 ,3 ,3 -trifluoro- 1 -
propenyl)-2,2-Dimethylcyclopropanecarboxylic
acidcyano(3 -phenoxypheny
Diallate
Diaminodiphenylether, 4,4'-
Dichlorobenzidine, 3,3'-
1000*
1000
1000*
1000*
1000*
1000
1000*
1000
1000*
1000*
1000
1000*
1000
1000
1000*
1000*
1000*
1000*
1000*
1000
1000*
1000
1000
1000
n/a
1000
1000
1000
1000
1000
1000
100
1000*
1000
1000
1000
1000
1000
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
final derived
IRIS
IRIS
HEAST
IRIS
final derived
final derived
IRIS
HEAST
final derived
IRIS
C-6
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
75-27-4
107-06-2
120-83-2
78-87-5
576-26-1
88-85-7
51-28-5
121-14-2
330-54-1
2439-10-3
67-72-1
74-90-8
77501-63-4
330-55-2
12427-38-2
93-65-2
72-43-5
74-88-4
101-14-4
90-94-8
2212-67-1
121-69-7
300-76-5
100-02-7
95-53-4
Chemical Name
Dichlorobromomethane
Dichloroethane, 1,2-
Dichlorophenol, 2,4-
Dichloropropane, 1,2-
Dimethylphenol, 2,6-
Dinitrobutyl phenol (Dinoseb)
Dinitrophenol, 2,4-
Dinitrotoluene, 2,4-
Diuron
Dodine (Dodecylguanidine monoacetate)
Hexachloroethane
Hydrogen cyanide
Lactofen (5-(2-Chloro-4-
(trifluoromethyl)phenoxy)-2-nitro-2-ethoxy- 1 -
methyl-2-oxoethyl ester)
Linuron
Maneb
Mecoprop
Methoxychlor
Methyl iodide
Methylenebis(2-chloroaniline), 4,4'-
Michlers Ketone
Molinate (IH-Azepine-l carbothioicacid,
hexahydro-S-ethyl ester)
N,N-Dimethylaniline
Naled
Nitrophenol, 4-
o-Toluidine
Toxicity Weight
Inhalation
1000*
1000
1000*
1000
1000*
1000*
1000*
1000*
1000*
1000*
10
1000
1000*
1000*
1000*
1000*
1000*
1000*
1000
1000*
1000*
1000*
1000*
1000
1000*
Oral
1000
1000
1000
1000*
1000
1000
1000
1000
1000
1000
1000
100
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
Source
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
interim derived
HEAST
final derived
IRIS
IRIS
IRIS
final derived
HEAST
C-7
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
636-21-5
19666-30-9
42874-03-3
106-47-8
120-71-8
106-44-5
1910-42-5
87-86-5
79-21-0
7664-38-2
7287-19-6
709-98-8
107-19-7
114-26-1
75-56-9
110-86-1
82-68-8
7782-49-2
N725
7440-22-4
N740
122-34-9
26628-22-8
137-26-8
79-00-5
Chemical Name
o-Toluidine hydrochloride
Oxydiazon (3-[2,4-Dichloro-5-(l-
methy lethoxy )pheny 1] -5 -( 1 , 1 -dimethy lethy 1)-
l,3,4-oxadiazol-2(3H)-one)
Oxyfluorfen
p-Chloroaniline
p-Cresidine
p-Cresol
Paraquat dichloride
Pentachlorophenol
Peracetic acid
Phosphoric acid
Prometryn (N,N'-Bis( 1 -methy lethy l)-6-
methylthio- 1 ,3 ,5 -triazine-2,4-diamine)
Propanil (N-(3 ,4-Dichlorophenyl)propanamide)
Propargyl alcohol
Propoxur
Propylene oxide
Pyridine
Quintozene
Selenium
Selenium compounds
Silver
Silver compounds
Simazine
Sodium azide
Thiram
Trichloroethane, 1,1,2-
Toxicity Weight
Inhalation
1000*
1000*
1000*
1000*
1000*
1000*
1000*
1000*
1000
1000
1000*
1000*
1000*
1000*
100
1000*
1000*
1000*
1000*
1000*
1000*
1000*
1000*
1000*
100
Oral
1000
1000
1000
1000
1000
1000
1000
1000
1000*
1
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
Source
HEAST
IRIS
IRIS
IRIS
interim derived
HEAST
IRIS
IRIS
interim derived
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
C-8
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
121-44-8
95-63-6
593-60-2
75-35-4
Chemical Name
Triethylamine
Trimethylbenzene, 1,2,4
Vinyl bromide
Vinylidene chloride
Toxicity Weight
Inhalation
1000
1000
1000
100
Oral
1000*
1000
1000*
1000
Source
IRIS
final derived
IRIS
IRIS
Chemicals With One or More Toxicity Weights of 100
94-82-6
94-75-7
75-05-8
62476-59-9
15972-60-8
834-12-8
7664-41-7
1912-24-9
17804-35-2
71-43-2
82657-04-3
92-52-4
75-25-2
1689-99-2
1689-84-5
106-88-7
463-58-1
120-80-9
2,4-DB
Acetic acid (2,4-D((2,4-dichlorophenoxy)))
Acetonitrile
Acifluorfen, sodium salt [5-(2-Chloro-4-
(triflouromethyl)phenoxy)-2-nitrobenzoic acid,
sodium salt]
Alachlor
Ametryn (N-Ethyl-N'-( 1 -methylethyl)-6-
(methylthio)-l,3,5,-triazine- 2,4 diamine)
Ammonia
Atrazine (6-Chloro-N-ethyl-N'-( 1 -methylethyl)-
1,3,5, -triazine-2 ,4 -diamine)
Benomyl
Benzene
Bifenthrin
Biphenyl
Bromoform (Tribromomethane)
Bromoxynil octanoate (Octanoic acid,2,6-
dibromo-4-cyanophenyl ester)
Bromoxynil (3,5-Dibromo-4-hydroxybenzonitrile)
Butylene oxide, 1,2-
Carbonyl sulfide
Catechol
100*
100*
100*
100*
100*
100*
100
100*
100*
100
100*
100*
10
100*
100*
100
100
100
100
100
100
100
100
100
100*
100
100
100
100
100
100
100
100
100*
100*
100
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
interim derived
interim derived
C-9
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
133-90-4
90982-32-4
108-90-7
510-15-6
1897-45-6
64902-72-3
98-82-8
N106
68359-37-5
1163-19-5
117-81-7
1918-00-9
541-73-1
25321-22-6
540-59-0
75-09-2
111-42-2
35367-38-5
55290-64-7
119-90-4
105-67-9
123-91-1
Chemical Name
Chloramben
Chlorimuron ethyl (Ethyl-2-[[[(4-chloro-6-
methoxyprimidin-2-yl)-carbonyl] -
amino] sulfonyljbenzoate)
Chlorobenzene
Chlorobenzilate
Chlorothalonil
Chlorsulfuron(2-Chloro-N-[[(4-methoxy-6-
methyl-l,3,5-triazin-2-
yl)amino]carbonyl]benzenesulfonamide)
Cumene
Cyanide compounds
Cyfluthrin (3 -(2,2-Dichloroethenyl)-2,2-
dimethylcyclopropanecarboxylic acid,cyano(4-
fluoro-3 -phenoxyphenyl)methy
Decabromodiphenyl oxide
Di(2-ethylhexyl) phthalate
Dicamba (3 ,6-Dichloro-2-methyoxybenzoicacid)
Dichlorobenzene, 1,3-
Dichlorobenzene (mixed isomers)
Dichloroethylene, 1,2-
Dichloromethane
Diethanolamine
Diflubenzuron
Dimethipin(2,3,-Dihydro-5,6-dimethyl-l,4-
dithiin 1,1,4,4-tetraoxide)
Dimethoxybenzidine, 3,3'-
Dimethylphenol, 2,4-
Dioxane, 1,4-
Toxicity Weight
Inhalation
100*
100*
100*
100*
100*
100*
100*
100*
100*
100*
100*
100*
10
10
100*
10
100*
100*
100*
100*
100*
100*
Oral
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Source
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
interim derived
interim derived
HEAST
IRIS
interim derived
IRIS
IRIS
HEAST
IRIS
IRIS
C-10
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
957-51-7
122-39-4
759-94-4
140-88-5
39515-41-8
51630-58-1
2164-17-2
69409-94-5
72178-02-0
50-00-0
87-68-3
77-47-4
51235-04-2
7647-01-0
123-31-9
35554.44-0
80-05-7
108-39-4
121-75-5
109-86-4
96-33-3
Chemical Name
Diphenamid
Diphenylamine
Ethyl dipropylthiocarbamate (EPTC)
Ethyl acrylate
Fenpropathrin (2,2,3, 3-Tetramethylcyclopropane
carboxylicacid cyano(3-
phenoxyphenyl)methylester)
Fenvalerate (4-Chloro-alpha-(l-
methylethyl)benzeneacetic acid cyano(3-
phenoxyphenyl)methyl ester)
Fluometuron
Fluvalinate (N-[2-Chloro-4-
(trifluoromethyl)phenyl] -DL-valine(+)-cyano (3 -
phenoxyphenyl)methyl ester)
Fomesafen (5-(2-Chloro-4-
(trifluoromethyl)phenoxy)-Nmethylsulfonyl)-2-
nitrobenzamide)
Formaldehyde
Hexachloro- 1 ,3 -butadiene
Hexachlorocyclopentadiene
Hexazinone
Hydrochloric acid
Hydroquinone
Imazalil(l-[2-(2,4-Dichlorophenyl)-2-(2-
propenyloxy)ethyl] - IH-imidazole)
Isopropylidenediphenol, 4,4'-
m-Cresol
Malathion
Methoxyethanol, 2-
Methyl acrylate
Toxicity Weight
Inhalation
100*
100*
100*
100*
100*
100*
100*
100*
100*
100
100
100*
100*
100
100*
100*
100*
100*
100*
100
100*
Oral
100
100
100
100
100
100
100
100
100
10
100
100
100
100*
100
100
100
100
100
100*
100
Source
IRIS
IRIS
IRIS
HEAST
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
HEAST
IRIS
IRIS
IRIS
IRIS
IRIS
HEAST
C-ll
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
74-95-3
101-61-1
21087-64-9
88671-89-0
68-12-2
7697-37-2
139-13-9
99-59-2
99-55-8
79-46-9
27314-13-2
95-48-7
19044-88-3
56-38-2
40487-42-1
52645-53-1
108-45-2
29232-93-7
1918-16-7
2312-35-8
Chemical Name
Methylene bromide
Methylenebis(N,N-dimethylbenzenamine), 4,4'-
Metribuzin
Myclobutanil (.alpha.-Butyl-.alpha.-(4-
chlorophenyl)- 1H- 1 ,2,4-triazole- 1 -propanenitrile)
N,N-Dimethylformamide
Nitric acid
Nitrilotriacetic acid
Nitro-o-anisidine, 5-
Nitro-o-toluidine
Nitropropane, 2-
Norflurazon (4-Chloro-5-(methylamino)-2-[3-
(trifluoromethyl)phenyl] -3 (2H)-pyridazinone)
o-Cresol
Oryzalin (4-(Dipropylamino)-3,5-
dinitrobenzenesulfonamide)
Parathion
Pendimethalin (N-( 1 -Ethylpropyl)-3 ,4-dimethyl-
2,6-dinitrobenzenamine)
Permethrin(3-(2,2-Dichloroethenyl)-2,2-
dimethy Icyclopropanecarboxylic acid, (3 -
phenoxyphenyl)methyl ester)
Phenylenediamine, 1,3-
Pirimiphos methyl (O-(2-(Diethylamino)-6-
methyl-4- pyrimidinyl)-O,O-
dimethylphosphorothioate)
Propachlor (2-Chloro-N-( 1 -methylethyl)-N-
phenylacetamide)
Propargite
Toxicity Weight
Inhalation
100*
100*
100*
100*
100
100
100*
100*
100*
100
100*
100*
100*
100*
100*
100*
100*
100*
100*
100*
Oral
100
100
100
100
100*
100*
100
100
100
100*
100
100
100
100
100
100
100
100
100
100
Source
HEAST
IRIS
IRIS
IRIS
IRIS
final derived
interim derived
HEAST
HEAST
IRIS
IRIS
IRIS
IRIS
HEAST
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
C-12
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
60207-90-1
76578-14-8
10453-86-8
5902-51-2
630-20-6
79-34-5
127-18-4
961-11-5
28249-77-6
43121-43-3
2303-17-5
101200-48-0
120-82-1
88-06-2
96-18-4
1582-09-8
7440-62-2
50471-44-8
12122-67-7
Chemical Name
Propiconazole (l-[2-(2,4-Dichlorophenyl)-4-
propy 1-1,3 -dioxolan-2-yl] -methyl- 1H- 1,2,4,-
triazole)
Quizalofop-ethyl(2-[4-[(6-Chloro-2-
quinoxalinyl)oxy]phenoxy] propanoicacid ethyl
ester)
Resmethrin ([5-(Phenylmethyl)-3-furanyl]methyl
2,2-dimethyl-3 -(2 -methyl- 1-
propenyl)cyclopropanecarboxylate])
Terbacil (5-Chloro-3-(l, l-dimethylethyl)-6-
methyl- 2,4 (lH,3H)-pyrimidinedione)
Tetrachloroethane, 1,1,1,2-
Tetrachloroethane, 1,1,2,2-
Tetrachloroethylene (Perchlorethyle
Tetrachlorvinpho s
Thiobencarb (Carbamic acid, diethylthio-, S-(p-
chlorobenzyl))
Triadimefon ( 1 -(4-Chlorophenoxy)-3 ,3 -dimethyl-
l-(lH-l,2,4-triazol-l-yl)-2-butanone)
Triallate
Tribenuron methyl (2-(4-Methoxy-6-methyl-l,3,5-
triazin-2-yl)-
methylamino)carbonyl)amino)sulfonyl)-,methyl
ester)
Trichlorobenzene, 1,2,4-
Trichlorophenol, 2,4,6-
Trichloropropane, 1,2,3-
Trifluralin
Vanadium (fume or dust)
Vinclozolin (3-(3,5-Dichlorophenyl)-5-ethenyl-5-
methyl-2,4-oxazolidinedione)
Zineb
Toxicity Weight
Inhalation
100*
100*
100*
100*
10
100
100*
100*
100*
100*
100*
100*
100*
100
100*
100*
100*
100*
100*
Oral
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Source
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
HEAST
IRIS
IRIS
C-13
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
Chemical Name
Toxicity Weight
Inhalation
Oral
Source
Chemicals With One or More Toxicity Weights of 10
98-86-2
120-12-7
N040
7440-39-3
1861-40-1
133-06-2
63-25-2
75-15-0
5234-68-4
75-69-4
75-71-8
7782-50-5
74-87-3
84-74-2
106-46-7
95-50-1
110-80-5
100-41-4
7782-41-4
133-07-3
108-31-6
67-56-1
80-62-6
78-93-3
Acetophenone
Anthracene
Barium compounds
Barium
Benfluralin(N-Butyl-N-ethyl-2,6-dinitro-4-
(trifluoromethyl)benzenamine)
Captan
Carbaryl
Carbon disulfide
Carboxin (5,6-Dihydro-2-methyl-N-phenyl-l,4-
oxathiin-3 -carboxamide)
CFC-11
CFC-12
Chlorine
Chloromethane
Dibutyl phthalate
Dichlorobenzene, 1,4-
Dichlorobenzene, 1,2
Ethoxyethanol, 2-
Ethylbenzene
Fluorine
Folpet
Maleic anhydride
Methanol
Methyl methacrylate
Methyl ethyl ketone
10*
10*
10*
10*
10*
10*
10*
10
10*
10*
10*
10*
10
10*
10
10*
10
10
10*
10*
10*
10*
10*
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10*
10
10*
10
10
10
10
10
10
1
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
HEAST
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
HEAST
IRIS
C-14
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
108-10-1
71-36-3
110-54-3
86-30-6
106-50-3
1918-02-1
23950-58-5
74051-80-2
100-42-5
34014-18-1
23564-05-8
108-88-3
95-95-4
108-05-4
7440-66-6
Chemical Name
Methyl isobutyl ketone
n-Butyl alcohol
n-Hexane
N-Nitrosodiphenylamine
p-Phenylenediamine
Picloram
Pronamide
Sethoxydim(2-[l-(Ethoxyimino)butyl]-5-[2-
(ethylthio)propy 1] -3 -hy droxy 1-2-cy clohexen- 1 -
one)
Styrene
Tebuthiuron (N-[5-(l, l-Dimethylethyl)-l,3,4-
thiadiazol-2-yl)-N,N'-dimethylurea)
Thiophanate-methyl
Toluene
Trichlorophenol, 2,4,5-
Vinyl acetate
Zinc (fume or dust)
Toxicity Weight
Inhalation
10*
10*
10
10*
10*
10*
10*
10*
10
10*
10*
10
10*
10
10*
Oral
10
10
10*
10
10
10
10
10
10
10
10
10
10
10*
10
Source
HEAST
IRIS
IRIS
IRIS
HEAST
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
IRIS
Chemicals with Toxicity Weights of 1 for Both Exposure Pathways
6484-52-2
75-68-3
75-00-3
7440-50-8
110-82-7
107-21-1
74-85-1
64-18-6
76-13-1
Ammonium nitrate (solution)
Chloro- 1 , 1 -difluoroethane, 1 -
Chloroethane (Ethyl chloride)
Copper
Cyclohexane
Ethylene glycol
Ethylene
Formic acid
Freon 113
1*
1
1
1*
1
1*
1
1*
1*
1
1*
1*
1
1*
1
1*
1
1
final derived
IRIS
IRIS
HEAST
interim derived
IRIS
final derived
HEAST
IRIS
C-15
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
108-38-3
1634-04-4
No CASRNa
95-47-6
108-95-2
90-43-7
85-44-9
115-07-1
1330-20-7
Chemical Name
m-Xylene
Methyl tert-butyl ether
Nitrate compounds (water dissociable)
o-Xylene
Phenol
Phenylphenol, 2-
Phthalic anhydride
Propylene (Propene)
Xylene (mixed isomers)
Toxicity Weight
Inhalation
1*
1
1*
1*
1*
1*
1*
1
1*
Oral
1
1*
1
1
1
1
1
1*
1
Source
HEAST
IRIS
IRIS
HEAST
IRIS
HEAST
IRIS
final derived
IRIS
Chemicals with No Toxicity Weights
71751412
60-35-5
53-96-3
107119
134-32-7
1344-28-1
82-28-0
117-79-3
60-09-3
92-67-1
61-82-5
101053
492-80-8
22781233
98-87-3
Abamectin (Avermectin B 1)
Acetamide
Acetylaminofluorene, 2-
Allylamine
alpha-Naphthylamine
Aluminum oxide (fibrous forms)
Amino-2-methyl-anthraquinone, 1-
Aminoanthraquinone, 2-
Aminoazobenzene, 4-
Aminodiphenyl, 4-
Amitrole
Anilazine (4,6-Dichloro-N-(2-chlorophenyl)-
1,3,5 -triazin-2-amine)
Auramine
Bendiocarb (2,2-Dimethyl-l,3-benzodioxol-4-ol
methylcarbamate)
Benzal chloride
new chemical, not derived
low priority chemical
low priority chemical
new chemical, not derived
low priority chemical
new chemical, derived, not
reviewed
low priority chemical
low priority chemical
low priority chemical
low priority chemical
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
insufficient data
C-16
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
55-21-0
98-88-4
94-36-0
91-59-8
57-57-8
108-60-1
111-91-1
7637072
10294345
314409
53404196
7726956
35691657
52517
353-59-3
75-63-8
357573
1929733
94804
123-72-8
842-07-9
97-56-3
128-66-5
Chemical Name
Benzamide
Benzoyl chloride
Benzoyl Peroxide
beta-Naphthylamine
beta-Propiolactone
Bis(2-chloro- 1 -methethyl)ether
Bis(2-chloroethoxy)methane
Boron trifluoride
Boron trichloride
Bromacil (5-Bromo-6-methyl-3-(l-methylpropyl)-
2,4(lH,3H)-pyrimidinedione)
Bromacil lithium salt (2,4(1H,3H)-
Pyrimidinedione, 5-bromo-6-methyl-3 (1-
methylpropyl), lithium salt)
Bromine
Bromo- 1 -(bromomethyl)- 1 ,3 -
propanedicarbonitrile, 1-
Bromo-2-nitropropane- 1 ,3 -diol(Bronopol), 2-
Bromochlorodifluoromethane (Halon 1
Bromotrifluoromethane (Halon 1301)
Brucine
butoxyethyl ester, 2,4-D
butyl ester, 2,4-D
Butyraldehyde
C.I. Solvent Yellow 14
C.I. Solvent Yellow 3
C.I. Vat Yellow 4
Toxicity Weight
Inhalation
Oral
Source
low priority chemical
insufficient data
insufficient data
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, derived, not
reviewed
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
low priority chemical
low priority chemical
low priority chemical
C-17
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
989-38-8
569-64-2
3761-53-3
6459945
81-88-9
2832-40-8
4680-78-8
28407376
3118-97-6
76-14-2
76-15-3
2439012
115286
75887
354-25-6
460355
2837-89-0
563473
4080313
2971382
74-45-6
107-30-2
N084
76062
126-99-8
Chemical Name
C.I. Basic Red 1
C.I. Basic Green 4
C.I. Food Red 5
C.I. Acid Red 114
C.I. Food Red 15
C.I. Disperse Yellow 3
C.I. Acid Green 3
C.I. Direct Blue 2 18
C.I. Solvent Orange 7
CFC 114
CFC 115
Chinomethionat (6-Methyl-l,3-dithiolo[4,5-
b]quinoxalin-2-one)
Chlorendic acid
Chloro-l,U-trifluoroethane (HCFC-133a), 2-
Chloro-l,l,2,2-tetrafluoroethane, 1-
Chloro-1 , 1 , 1 -trifluoropropane(HCFC-253fb), 3 -
Chloro-l,l,l,2-tetrafluoroethane, 2-
Chloro-2-methyl-l-propene, 3-
Chloroallyl)-3,5,7-triaza-l-azoniaadamantane
chloride, l-(3-
chlorocrotyl ester, 2,4-D
Chlorodifluoromethane (HCFC-22)
Chloromethyl methyl ether
Chlorophenols
Chloropicrin
Chloroprene
Toxicity Weight
Inhalation
Oral
Source
low priority chemical
low priority chemical
low priority chemical
new chemical, not derived
low priority chemical
low priority chemical
low priority chemical
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
new chemical, not derived
new chemical, not derived
insufficient data
C-18
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
542767
63938-10-3
75729
5598130
7440-47-3
N090
N100
8001-58-9
1319-77-3
4170303
21725462
1134232
108930
28057489
533744
53404607
13684565
39156-41-7
615-05-4
333415
334-88-3
132-64-9
124-73-2
Chemical Name
Chloropropionitrile, 3-
Chlorotetrafluoroethane
Chlorotrifluoromethane (CFC-13)
Chlorpyrifos methyl (O,O-Dimethyl-O-(3,5,6-
trichloro-2-pyridyl)phosphorothioate)
Chromium
Chromium compounds
Copper compounds
Creosote, coal tar
Cresol (mixed isomers)
Crotonaldehyde
Cyanazine
Cycloate
Cyclohexanol
d-trans-Allethrin [d-trans-Chrysanthemic acid of
d-allethrone]
Dazomet (Tetrahy dro-3 , 5 -dimethy 1-2H- 1,3,5-
thiadiazine-2-thione)
Dazomet sodium salt (2H-l,3,5-Thiadiazine-2-
thione, tetrahydro-3,5-dimethyl-, ion(l-), sodium)
Desmedipham
Diaminoanisole sulfate, 2,4-
Diaminoanisole, 2,4-
Diazinon
Diazomethane
Dibenzofuran
Dibromotetrafluoromethane (Halon 24
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
insufficient data
insufficient data
new chemical, not derived
insufficient data
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
low priority chemical
new chemical, not derived
low priority chemical
insufficient data
new chemical, derived, not
reviewed
C-19
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
99309
422560
1649087
507551
812-04-4
111512562
422480
90454-18-5
136013791
13474889
431867
422446
128903219
354-23-4
306-83-2
1717-00-6
612839
64969342
75434
127564925
97234
Chemical Name
Dichloran (2,6-Dichloro-4-nitroaniline)
Dichloro- 1 , 1 , 1 ,2,2-pentafluoropropane (HCFC-
225ca), 3,3-
Dichloro-U-difluoroethane (HCFC-132b), 1,2-
Dichloro-1, 1,2,2,3 -pentafluoropropane (HCFC-
225cb), 1,3-
Dichloro-l,2,2-trifluoroethane (HCFC-123b), 1,1-
Dichloro-l,2,3,3,3-pentafluoropropane (HCFC-
225eb), 1,1-
Dichloro- 1 , 1 , 1 ,2,3 -pentafluoropropane (HCFC-
225ba), 2,3-
Dichloro- 1 , 1 ,2-trifluoroethane
Dichloro-1, 1,2,3,3-pentafluoropropane (HCFC-
225ea), 1,3-
Dichloro-l,2,2,3,3-pentafluoropropane (HCFC-
225cc), 1,1-
Dichloro-1, 1,3,3,3-pentafluoropropane (HCFC-
225da), 1,2-
Dichloro-1, 1,2,3,3-pentafluoropropane (HCFC-
225bb), 1,2-
Dichloro- 1 , 1 , 1 ,3 ,3 -pentafluoropropane (HCFC-
225aa), 2,2-
Dichloro-l,l,2-trifluoroethane, 1,2-
Dichloro-l,l,l-trifluoroethane, 2,2-
Dichloro- 1 -fluoroethane, 1,1-
Dichlorobenzidine dihydrochloride, 3,3'-
Dichlorobenzidine sulfate, 3,3'-
Dichlorofluoromethane (HCFC-21)
Dichloropentafluoropropane
Dichlorophene (2,2'-Methylenebis(4-
chlorophenol)
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
C-20
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
78-88-6
34077-87-7
51338273
115-32-2
77736
1464-53-5
38727558
101906
94-58-6
No CASRN
20325400
111984099
2524030
57-14-7
131-11-3
2300665
124403
60-11-7
612828
41766750
79-44-7
25321-14-6
39300453
Chemical Name
Dichloropropene, 2,3-
Dichlorotrifluoroethane
Diclofop methyl (2-[4-(2,4-
Dichlorophenoxy)phenoxy]propanoicacid, methyl
ester)
Dicofol
Dicyclopentadiene
Diepoxybutane
Diethatyl ethyl
Diglycidyl resorcinol ether
Dihydrosafrole
Diisocyanates
Dimethoxybenzidine dihydrochloride(o-
Dianisidine dihydrochloride), 3,3'-
Dimethoxybenzidine hydrochloride(o-Dianisidine
hydrochloride), 3,3'-
Dimethyl chlorothiophosphate
Dimethyl Hydrazine, 1,1-
Dimethyl phthalate
Dimethylamine dicamba
Dimethylamine
Dimethylaminoazobenzene, 4-
Dimethylbenzidine dihydrochloride(o-Tolidine
dihydrochloride), 3,3'-
Dimethylbenzidine dihydrofluoride(o-Tolidine
dihydrofluoride), 3,3'-
Dimethylcarbamyl chloride
Dinitrotoluene (mixed isomers)
Dinocap
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
insufficient data
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
C-21
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
2164070
136458
138932
541537
120365
13194484
541-41-3
53404378
N1000
151-56-4
1928434
75-34-3
52857
60168889
13356086
66441234
72490018
55389
14484641
Chemical Name
Dipotassium endothall (7-
Oxabicyclo(2.2. l)heptane-2,3-dicarboxylic acid,
dipotassium salt)
Dipropyl isocinchomeronate
Disodium cyanodithioimidocarbonate
Dithiobiuret, 2,4-
DP (Dichlorprop), 2,4-
Ethoprop (Phosphorodithioic acid O-ethyl S,S-
dipropyl ester)
Ethyl chloroformate
ethyl-4-methyrpentyl ester, 2,4-D 2-
Ethylenebisdithiocarbamic acid, salts and esters
Ethyleneimine (Aziridine)
ethylhexyl ester, 2,4-D 2-
Ethylidene dichloride
Famphur
Fenarimol (.alpha.-(2-Chlorophenyl)-.alpha.-4-
chlorophenyl)-5-pyrimidinemethanol)
Fenbutatin oxide (hexakis(2-methyl-2-
phenylpropyl)distannoxane)
Fenoxaprop ethyl (2-(4-((6-Chloro-2-
benzoxazolylen)oxy)phenoxy)propanoicacid,ethyl
ester)
Fenoxycarb (2-(4-
Phenoxyphenoxy)ethyl]carbamic acidethyl ester)
Fenthion (O,O-Dimethyl O-[3-methyl-4-
(methylthio) phenyl] ester,phosphorothioic acid)
Ferbam(Tris(dimethylcarbamodithioato-
S,S')iron)
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
insufficient data
low priority chemical
new chemical, not derived
insufficient data
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
C-22
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
69806504
51218
N230
1335-87-1
680-31-9
10034-93-2
7664-39-3
55406536
13463406
465736
25311711
94111
67-63-0
120-58-1
554132
149304
137428
20354261
2032657
3653483
556616
60-34-4
74-93-1
Chemical Name
Fluazifop butyl (2-[4-[[5-(Trifluoromethyl)-2-
pyridinyl]oxy]-phenoxy]propanoic acid, butyl
ester)
Fluorouracil (5-Fluorouracil)
Glycol Ethers
Hexachloronaphthalene
Hexamethyrphosphoramide
Hydrazine sulfate
Hydrogen fluoride
Iodo-2-propynyl butylcarbamate, 3-
Iron pentacarbonyl
Isodrin
Isofenphos (2-[[Ethoxyl[(l-
methylethyl)amino]phosphinothioyl]oxy]benzoic
acid 1-methylethyl ester)
isopropyl ester, 2,4-D
Isopropyl alcohol
Isosafrole
Lithium carbonate
Mercaptobenzothiazole (MET), 2-
Metham sodium (Sodiummethyldithiocarbamate)
Methazole (2-(3,4-Dichlorophenyl)-4-methyl-
l,2,4-oxadiazolidine-3,5-dione)
Methiocarb
Methoxone sodium salt ((4-Chloro-2-
methylphenoxy) acetate sodium salt)
Methyl isothiocyanate
Methyl hydrazine
Methyl mercaptan
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
new chemical, not derived
insufficient data
low priority chemical
low priority chemical
insufficient data
insufficient data
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
interim derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
new chemical, not derived
C-23
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
79-22-1
101-77-9
75865
109-06-8
75796
9006422
7786347
150685
505-60-2
872504
924425
684-93-5
4549.40-0
59-89-2
16543-55-8
100-75-4
142596
7440-02-0
N495
No CASRN
1929824
92-93-3
1836-75-5
51-75-2
88-75-5
134-29-2
Chemical Name
Methyl chlorocarbonate
Methylenedianiline, 4,4'-
Methyllactonitrile, 2-
Methyrpyridine, 2-
Methyltrichlorosilane
Metiram
Mevinphos
Monuron
Mustard gas
N-Methyl-2-pyrrolidone
N-Methylolacrylamide
N-Nitroso-N-methylurea
N-Nitrosomethylvinylamine
N-Nitrosomorpholine
N-Nitrosonornicotine
N-Nitrosopiperidine
Nabam
Nickel
Nickel compounds
Nicotine and salts
Nitrapyrin(2-Chloro-6-(trichloromethyl)pyridine)
Nitrobiphenyl, 4-
Nitrofen
Nitrogen mustard
Nitrophenol, 2-
o-Anisidine hydrochloride
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
insufficient data
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
low priority chemical
low priority chemical
low priority chemical
low priority chemical
low priority chemical
new chemical, not derived
insufficient data
insufficient data
new chemical, not derived
new chemical, not derived
low priority chemical
low priority chemical
low priority chemical
insufficient data
low priority chemical
C-24
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
2234-13-1
20816-12-0
301122
10028156
104-94-9
95692
104121
100016
156-10-5
123-67-7
1114712
76-01-7
57330
594423
85018
26002802
615281
624180
95545
57410
75-44-5
51036
No CASRN
No CASRN
Chemical Name
Octachloronaphtahlene
Osmium tetroxide
Oxydemeton methyl (S-(2-(Ethylsulfinyl)ethyl)
O,O-dimethylester phosphorothioic acid)
Ozone
p-Anisidine
p-Chloro-o-toluidine
p-Chlorophenyl isocyanate
p-Nitroaniline
p-Nitrosodiphenylamine
Paraldehyde
Pebulate (Butylethylcarbamothioic acidS-propyl
ester)
Pentachloroethane
Pentobarbital sodium
Perchloromethyl mercaptan
Phenanthrene
Phenothrin (2,2-Dimethy 1-3 -(2-methyl- 1 -
propenyl) cyclopropanecarboxylic acid(3-
phenoxyphenyl)methyl ester)
Phenylenediamine dihydrochloride, 1,2-
Phenylenediamine dihydrochloride, 1,4-
Phenylenediamine, 1,2-
Phenytoin
Phosgene
Piperonyl butoxide
Fob/chlorinated alkanes
Polycyclic aromatic compounds
Toxicity Weight
Inhalation
Oral
Source
low priority chemical
low priority chemical
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
C-25
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
7758012
137417
128030
41198087
1120-71-4
31218834
123-38-6
1320189
106-51-4
81-07-2
94-59-7
78-92-2
2702729
132274
7632000
1982690
128041
131522
96-09-3
2699798
35400432
3383968
75-65-0
Chemical Name
Potassium bromate
Potassium N-methyldithiocarbamate
Potassium dimethyldithiocarbamate
Profenofos (O-(4-Bromo-2-chlorophenyl)-O-ethyl-
S-propyl phosphorothioate)
Propane sultone
Propetamphos (3-
[(Ethylamino)methoxyphosphinothioyl]oxy]-2-
butenoic acid, 1-methylethylester)
Propionaldehyde
propylene glycol butyl etherester, 2,4-D
Quinone
Saccharin (manufacturing)
Safrole
sec -Butyl alcohol
sodium salt, 2,4-D
Sodium o-phenylphenoxide
Sodium nitrite
Sodium dicamba (3,6-Dichloro-2-methoxybenzoic
acid, sodium salt)
Sodium dimethyldithiocarbamate
Sodium pentachlorophenate
Styrene oxide
Sulfuryl fluoride (Vikane)
Sulprofos (O-Ethyl O-[4-
(methylthio)phenyl]phosphorodithioicacid S
propyl ester)
Temephos
tert-Butyl Alcohol
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
new chemical, not derived
low priority chemical
low priority chemical
low priority chemical
insufficient data
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
C-26
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
354143
354110
64755
7696120
7440-28-0
N760
148798
62-55-5
139-65-1
59669260
23564069
79196
10061026
110576
68-76-8
2155706
1983104
52-68-6
76028
79-01-6
57213691
26644462
2655154
Chemical Name
Tetrachloro-l-fluoroethane(HCFC-121), 1,1,2,2-
Tetrachloro-2-fluoroethane(HCFC- 12 la), 1,1,1,2-
Tetracycline hydrochloride
Tetramethrin (2,2-Dimethyl-3 -(2 -methyl- 1 -
propenyl) cyclopropanecarboxylicacid
(l,3,4,5,6,7-hexahydro-l,3-dioxo-2
Thallium
Thallium comounds
Thiabendazole (2-(4-Thiazolyl)-lH-
benzimidazole)
Thioacetamide
Thiodianiline, 4,4'-
Thiodicarb
Thiophanate ethyl ([1,2-
Phenylenebis(iminocarbonothioyl)]biscarbamic
acid diethyl ester)
Thiosemicarbazide
trans- 1 , 3 -Dichloropropene
trans- 1 ,4-Dichloro-2-butene
Triaziquone
Tributyltin methacrylate
Tributyltin fluoride
Trichlorfon
Trichloroacetyl chloride
Trichloroethylene
Triclopyr triethylammonium salt
Triforine(N,N'-[l,4-Piperazinediylbis-2,2,2-
trichloroethylidene)]bisformamide)
Trimethylphenyl methylcarbamate, 2,3,5-
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
insufficient data
new chemical, not derived
low priority chemical
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
insufficient data
new chemical, not derived
new chemical, not derived
new chemical, not derived
C-27
-------
Table C-l. Toxicity Weights for all TRI Chemicals, by Toxicity Weight
CAS Number
76879
639587
126-72-7
72-57-1
51-79-6
87-62-7
N982
Chemical Name
Triphenyltin hydroxide
Triphenyltin chloride
Tris(2,3 -dibromopropyl)phosphate
Trypan blue
Urethane (Ethyl Carbamate)
Xylidine, 2,6-
Zinc Compounds
Toxicity Weight
Inhalation
Oral
Source
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
new chemical, not derived
low priority chemical
insufficient data
Toxicity weight is adopted from the other exposure pathway.
C-28
-------
Appendix D
Physicochemical Properties of Chemicals Included in the Indicators
D-l
-------
Physicochemical Properties of Chemicals Included in the Indicators
The Toxics Release Inventory (TRI) model requires a database of physicochemical properties and
destruction/removal efficiencies to predict the fate and transport of the 370 TRI chemicals. The
physicochemical properties of interest include rates of chemical decay in air and water; organic carbon-water
and octanol-water partition coefficients (Koc andK^ respectively); water solubilities; bioconcentration factors;
Henry's Law constants (KH); and molecular weights. To evaluate the effects of treatment and disposal, the
model requires removal efficiencies for publicly owned treatment works (POTWs), within-POTW partitioning
percentages among volatilization, biodegradation, and sorption to sludge, and incinerator destruction and
removal efficiencies (DREs). Values for all of these parameters are included in a database called
CHEMICAL.DB. The information in this database was originally documented in November, 1992. Sincethat
time, better data have become available, particularly for POTW removal efficiencies and within-POTW
partitioning percentages. The most significant new data sources are the Environmental Fate Data Base
(Syracuse Research Corporation, 1995) and the RREL Treatability Database Version 5.0, maintained by the
U.S. EPA Risk Reduction Engineering Laboratory (U.S. EPA, 1994).
This appendix describes the methods used to update CHEMICAL.DB and provides the sources for all
of the data. The 370 TRI chemicals are divided among five tables, depending on the dominant source of the
data or the primary method used to estimate parameter values if no data were available. This appendix also
provides a summary of the resolution of certain TRI reporting issues which affect the exposure modeling.
Update of Physicochemical and Destruction/Removal Efficiencies Data
Table 1: Organic Chemicals
Table 1 contains data on 303 organic chemicals of the 370 TRI chemicals. Originally, values for six
of the physicochemical parameters (log^^), Koc, water solubility, Henry's Law constant, molecular weight,
and bioconcentration factor) were obtained from a dBase file called 313PROPB.dbf This file, provided by
the Exposure Assessment Branch, was created for an earlier project using TRI data. This file includes the
references used for those values taken from the literature and the estimation method used for those values that
were calculated. Additional values of molecular weights came from the CRC Handbook (CRC, 1990) and the
Merck Index (Budavari, 1989). Note that throughout the tables, if a compound is infinitely soluble in water,
a value of 107 mg/L was entered.
Air decay and water decay rates were estimated by arithmetically averaging the high and low first-order
rate constants derived from the high and low half-lives reported in Howard et al. (1991). A full description
of how the half-lives were obtained is given in the reference. A few additional water decay rates were obtained
from the EPA database PIRANHA (U.S. EPA, 1991),
D-2
-------
for chloramben, tetrachlorvinphos, trifluralin, chlorothalonil, and fluometuron. An air decay rate for trifluralin
was also obtained from U.S. EPA (1991).
The POTW removal efficiencies and the within-POTW partitioning values were obtained from U.S.
EPA, 1986. The portion of the chemical that neither partitions to air nor sludge nor escapes in POTW effluent
is assumed to biodegrade.
The values for incinerator destruction/removal efficiencies (DREs) were difficult to obtain. Because
the TRI model uses the incinerator DRE to estimate the fraction of the chemical fed to the incinerator that is
released to the air, the DRE should be written as a percent of the incinerator feed. However, for organics, this
methodology ignores the fact that chemicals of concern, such as dioxins, may be formed during the incineration
process. We assume that the typical municipal waste combustor destruction/removal efficiency for organics
is 99 percent. The exceptions to this rule are PCBs, which are assumed to have a DRE of 99.9999 percent,
as required by TSCA regulation.
Many data on logf^J, water solubility, hydrolysis half-lives, Henry's Law constants, POTW removal
efficiencies, and within-POTW partitioning values were updated with values from the Environmental Fate Data
Base (Syracuse Research Corporation, 1995). These values were provided by David Lynch of the Exposure
Assessment Branch. This database also includes values for vapor pressure but these data were not used for
this analysis. The database file includes references for those data taken from the literature and the method used
for those values that were estimated.
For this analysis, two modifications to the data in the Environmental Fate Data Base were necessary.
First, the hydrolysis half-lives were converted to rates by assuming first-order decay. Secondly, the within-
POTW partitioning values were converted to percentages of the total POTW removal efficiency before
incorporation into CHEMICAL.DB. For example, if ten percent of a particular chemical volatilized, 20
percent biodegraded, 40 percent sorbed to sludge, and 30 percent was in the POTW effluent, the first three
percentages were scaled to sum to 100 percent of the total POTW removal efficiency of 70 percent. Thus,
in CHEMICAL.DB for this example, 14 percent (10/70) of the total removal efficiency would be attributed
to volatilization, 29 percent (20/70) would be attributed to biodegradation, and 57 percent would be attributed
to sorption to sludge.
Additional values of Koc and bioconcentration factors were estimated using regression equations in
Lyman et al. (1990). If solubility values were available, the following equation (Eq. 4-5 in the reference) was
used to estimate Koc values:
log(^oc) = -0.55 log(5) + 3.64
Note that in this equation, solubility (S) must be entered in units of milligrams per liter (mg/L). If only log^^,)
data were available, Eq. 4-8 in the reference was used:
lo^ = 0.544 lo* + 1.377
D-3
-------
To predict bioconcentration factors, Eq. 5-2 in the reference, which requires log^K^) values, was used:
logBCF =D0.76 log(Kow) -D0.23
For limitations on the range of values of dependent variables appropriate for these equations, the reader
is referred to Lyman et al., 1990.
Table 2: Inorganic Chemicals
Table 2 contains data on 36 inorganic chemicals and classes of inorganic chemicals. Classes of
inorganic compounds are assumed to behave like the elemental inorganic compound. Because inorganics do
not decay in air or water, or appreciably sorb to organic carbon, values for these parameters are assumed to
be zero. Except for ammonia, values for within-POTW partitioning to volatilization and biodegradation are
also assumed to be zero, and therefore the partitioning percentage to sludge is 100 percent for 35 compounds.
Given that ammonia can be a gaseous or aqueous species, it was not possible to predict within-POTW
partitioning percentages for this chemical. The Henry's Law constant for ammonia was estimated from stability
constants presented in Morel, 1983.
BCF values for these inorganics were predominantly obtained from the dBase file described above,
313PROPB.dbf, with five exceptions: aluminum (U.S. EPA, 1988a); antimony (U.S. EPA, 1988b); cobalt
(J0rgensen and Johnsen, 1981); silver (U.S. EPA, 1987); and, thallium (Tetra Tech, 1985).
It is impossible to accurately predict metal solubility without knowing the concentrations of other metal
ions and ligands in the water. Currently, water solubilities of zero are entered for all inorganics except copper,
ammonia, and phosphorus. The solubility of phosphorus (yellow or white) is from Merck (Budavari, 1989).
A more realistic estimate of metal solubility could be obtained by assuming particular water characteristics,
such as pH and major ligand concentrations, and estimating the concentrations of complexed metals, which
would remain dissolved in the water and potentially bioavailable. At this time, however, water solubilities of
inorganic compounds are not used for any modeling purposes in the TRI model.
POTW removal efficiencies were available from the RREL Treatability Database maintained by the U.S.
EPA Risk Reduction Engineering Laboratory. This database was also supplied by David Lynch of the
Exposure Assessment Branch. For any given chemical, the RREL Treatability Database provides a list of
removal efficiencies published in the scientific literature. Each value is characterized by the technology used,
the type of influent, and the scale of the experiment. For all values associated with activated sediment and full
scale experiments, a geometric mean was derived and used as the POTW removal efficiency. The RREL
Treatability Database did not provide within-POTW partitioning values, and therefore the default partitioning
value of 100 percent to sludge was used (except for ammonia), as discussed above.
Another physicochemical property required to model the fate and transport of inorganic compounds
is the soil-water partition coefficient, Kd. Kd values are needed to estimate leachate concentrations from
landfills. For all the metals in Table 2, except aluminum, we used Kd values measured in column studies by
Gerritse et al. (1982) for sand with an foc value of 0.0355 g/g, a cation exchange capacity of 0.22 meq/g, zero
D-4
-------
clay content, and a solution pH of 5. (The assumption that the waste in landfills is like sand yields a
conservative estimate of leachate concentration, because the low clay content and the relatively low pH will
tend to increase movement of metals.) The median of the range of Kd values for each metal was taken,
assuming a log-normal distribution. The same values were used for classes of inorganic compounds as for the
elemental inorganic compound. For aluminum, the Kd value is based on Langmuir isotherm data presented in
Bodeketal., 1988.
For incinerator destruction/removal efficiencies, values were taken from multiple hearth sludge
incinerator studies, as reported in U.S. EPA, 1992.
Table 3: Chemicals Missing POTW Removal Efficiencies
Table 3 shows the three TRI chemicals for which POTW removal efficiencies and within-POTW
partitioning percentages were not available. To derive POTW removal efficiencies and within-POTW
partitioning percentages, we first categorized the chemicals for which values were available (from Table 1) into
chemical classes; we then derived average values for these parameters for each chemical class. The average
class values were then applied to chemical class members with no data. Chemicals were divided into nine
classes based on their Km and KH values (U.S. EPA, 1986):
Kow < 100, KH < ID'3 atm • m3/mol
Kow < 100, ID'3 < KH < ID'2 atm • m3/mol
Kow < 100, KH > 1C'2 atm • m3/mol
100 < Kow < 10,000, KH < 1C'3 atm • m3/mol
100 < Kow < 10,000, 10'3 < KH < 10'2 atm • nrVmol
100 < Kow < 10,000, KH > 1C'2 atm • m3/mol
Kow > 10,000, KH < 10'3 atm • nrVmol
Kow > 10,000, ID'3 < KH < 1C'2 atm • m3/mol
Kow > 10,000, KH > 1C'2 atm • m3/mol
The POTW removal efficiency values, percent volatilization values, and average sludge partitioning
percentages were averaged for the chemicals within each class. (The percent that biodegrades is calculated
by subtracting the percent that volatilizes and the percent that partitions to sludge from 100 percent). The
chemicals lacking these values were divided into the same classes using the same KM and KH criteria; the
average class values were then assigned to these chemicals based on the class into which they fell.
Table 4: Chemicals Missing Some Physicochemical and Removal Efficiencies Data
Table 4 shows the two TRI chemical groups without data from the Environmental Fate Data Base or
RREL Treatability Database.
Chlorophenols: Because 2-chlorophenol is a priority pollutant, we used available water
solubility, Km, and Koc data (Mabey et al., 1982) for that compound to represent the class. A
KH value was estimated based on the methods of Hine and Mookerj ee (1975). POTW removal
D-5
-------
efficiencies and partitioning percentages were then obtained by placing chlorophenols in the
appropriate Km and KH class, as described above.
Cyanide compounds: According to Bodek et al. (1988), hydrogen cyanide "is believed to be
the most toxic component of cyanide solutions." Therefore, solubility and KH data for HCN
are provided in Table 4. Sorption of HCN is fairly weak, so no Koc or Km values were
available; thus removal efficiencies or partitioning percentages could not be estimated.
Table 5: Chemicals Missing Significant Amounts of Data
Table 5 presents the 25 chemicals for which the least information was found. Sources for data are as
described for Table 1. Solubilities for ammonium sulfate, hydrogen sulfide, molybdenum trioxide, paraldehyde,
and thorium dioxide were obtained from the Merck Index (Budavari, 1989). The 26 chemicals were not
included in the Environmental Fate Data Base; if they were included in the RREL Treatability Database, there
was insufficient information to estimate POTW removal efficiencies and partitioning percentages.
Summary of Resolution of Certain TRI Reporting Issues
In March 1996, several reporting issues pertaining to the TRI chemicals ammonia, ammonium sulfate,
and mineral acids were resolved. These issues and the corresponding agreed modifications or
recommendations are summarized below.
Ammonia and Ammonium Sulfate
Effective for the 1994 reporting year, only the ammonia or a fraction of the water-dissociable portion
of ammonia in a compound will be reportable to TRI. This includes anhydrous ammonia, aqueous ammonia,
and ammonia from water-dissociable ammonium salts and other sources (the latter includes ammonium sulfate).
The total quantity of ammonia is calculated, but only 10% of this counts towards threshold levels for reporting
and it is this 10% which is actually reported. To re-calculate the original quantity of ammonia, one must
multiply the reported quantity of releases and transfers (e.g., POTW) to water and land by 10 (air emissions
are reported at 100%).
In order to make the ammonium sulfate reporting from 1988 to 1994 (erroneous reports will be
accepted for 1994) comparable to the reporting change that will occur in 1994, the Indicators will calculate
the ammonia fraction of this chemical and this reporting will be combined with ammonia reporting (and will
use the toxicity ranking for ammonia) for these years. Ammonium sulfate will not appear in the Indicators.
Releases and transfers to air will be multiplied by 0.273 (ammonium sulfate has a molecular weight of 132 g,
of which 36 g are ammonia). All 1988-1994 releases and transfers of ammonium sulfate to water or land will
be multiplied by the factor 0.0273. This will permit cross-year comparisons of this modified ammonia listing.
For all years, the unmodeled pounds will reflect exactly what is reported under TRI (i.e., 10% of water
and land emissions). However, the modeled pounds and all other modeled analyses will use a 10X multiplier
for releases/transfers to water and land (air emissions are already accurately reflected in reporting) beginning
D-6
-------
in 1994 (this multiplier will also need to be used for modeled pounds of ammonium sulfate, i.e., wherever the
factor of 0.0273 was used - this does not apply to ammonia reporting from 1988-1993).
Mineral Acids
This includes sulfuric and hydrochloric acid. The Agency has made the decision to modify reporting
to include only the more highly toxic exposures to aerosol releases of certain of these acids. The acid aerosols
include mists, vapors, gas, fog and other airborne forms of any particle size. For sulfuric acid, this change in
reporting takes place in 1994, while for hydrochloric acid the change takes place for reporting year 1995. The
very high decay rate in water of these acids will greatly reduce any risk-based impacts associated with releases
or transfers to water.
References
Bodek, I, W. J. Lyman, W. F. Reehl, andD. H. Rosenblatt (eds.). 1988. Environmental Inorganic Chemistry:
Properties. Processes and Estimation Methods. Pergamon Press, New York.
Budavari, S. (ed.). 1989. The Merck Index. Merck & Co., Inc., Rahway, New Jersey.
Gerritse, R. G., R. Vriesema, J. W. Dalenberg, and H. P. De Roos (1982). Effect of sewage sludge on trace
element mobility in soils. J. Environ. Qual. ll(3):359-364.
Hine, J. and P. K. Mookerjee (1975). The intrinsic hydrophilic character of organic compounds. Correlations
in terms of structural contributions. J. Org. Chem. 40(3):292-298.
Howard, P. H., R. S. Boethling, W. F. Jarvis, W. M. Meylan, and E. M. Michalenko. 1991. Handbook of
Environmental Degradation Rates. Chelsea, MI. Lewis Publishers, Inc.
J0rgensen, S. E. and I. Johnsen. 1981. Principles of Environmental Science and Technology. Elsevier, New
York.
Lyman, W. J., W. F. Reehl, and D. H. Rosenblatt. 1990. Handbook of Chemical Property Estimation
Methods. American Chemical Society. Washington, D.C.
Mabey, W. R., J. H. Smith, R. T. Podoll, H. L. Johnson, T. Mill, T.-W. Chou, J. Gates, I. W. Partridge, H.
Jaber, andD. Vandenberg. 1982. Aquatic Fate Process Data for Organic Priority Pollutants. Chapter
4, EPA Report No. 440/4-81-014.
Mackay, D. andW. Y. Shiu. 1981. A critical review of Henry's Law constants for chemicals of environmental
interest. J. Phys. Chem. Ref. Data 10:1175-1199.
Morel, F.M.M. 1983. Principles of Aquatic Chemistry. John Wiley & Sons. New York.
D-7
-------
O'Connor, G. 1992. Professor and Chairman, Soil and Water Science Dept, University of Florida. Personal
Communication.
Syracuse Research Corporation. 1995. Environmental Fate Data Base. Syracuse, New York.
TetraTech. 1985. Bioaccumulation Monitoring Guidance: 1. Estimating the Potential for Bioaccumulation
of Priority Pollutants and 301(h) Pesticides Discharged into Marine and Estuarine Waters. Final
Report. Office of Marine and Estuary Protection, U.S. EPA.
U.S. EPA. 1986. Report to Congress on the Discharge of Hazardous Wastes to Publicly Owned Treatment
Works. Office of Water Regulations and Standards. EPA/530-SW-86-004. February.
U.S. EPA. 1987. Ambient Aquatic Life Water Quality Criteria for Silver. Draft. Environmental Research
Laboratories, Duluth, MN and Narragansett, RI. September.
U.S. EPA. 1988a. Ambient Water Quality Criteria for Aluminum-1988. EPA 440/5-86-008. August.
U.S. EPA. 1988b. Ambient Aquatic Life Water Quality Criteria for Antimony (III). Draft. Environmental
Research Laboratories, Duluth, MN and Narragansett, RI. August.
U.S. EPA. 1991. PIRANHA, Pesticide and Industrial Chemical Risk Analysis and Hazard Assessment,
Version 2.0. Environmental Research Laboratory, Office of Research and Development.
U.S. EPA. 1992. Human Health Risk Assessment for the Use and Disposal of Sewage Sludge: Benefits of
Regulation. Prepared by Abt Associates Inc., Cambridge, MA, for the U.S. EPA Office of Water.
U.S. EPA. 1994. RREL Treatability Database, Version 5.0. Risk Reduction Engineering Laboratory. U.S.
EPA, Cincinnati, OH.
Weast, R.C. (ed.). 1990. CRC Handbook of Chemistry and Physics. CRC Press, Inc. Boca Raton, FL.
D-8
-------
Table 1
CAS
Number
100027
100254
100414
100425
100447
100754
101144
101611
101688
101779
101804
103231
104949
105679
106423
106445
106467
106503
106514
106887
106898
106934
106990
107028
107051
107062
107131
107186
107211
107302
108054
: Organic Chemicals
Chemical
4-Nitrophenol
p-Dinitrobenzene
Ethylbenzene
Styrene
Benzyl chloride
N-Nitrosopiperidine
4,4'-Methylenebis
(2-chloroaniline)
4,4'-Methylenebis
(N,N-dimethylbenzenamine)
Methylenebis(phenylisocyanate)
4,4'-Methylenedianiline
4,4'-Diaminodiphenylether
Bis(2-ethylhexyl)adipate
p-Anisidine
2,4-Dimethylphenol
p-Xylene
p-Cresol
1 ,4-Dichlorobenzene
p-Phenylenediamine
Quinone
1,2-Butylene oxide
Epichlorohydrin
1 ,2-Dibromoethane
1,3-Butadiene
Acrolein
Allyl chloride
1 ,2-Dichloroethane
Acrylonitrile
Allyl alcohol
Ethylene glycol
Chloromethyl methyl ether
Vinyl acetate
Air Decay
(hr1)
0.114188095
0.044536326
0.432557601
0.017343132
0.153104799
1.31458948
1.906154747
0.65729474
1.411966479
1.270769831
0.146627288
0.719303678
0.320362142
0.090769274
0.254153966
0.00190045
1.361539105
0.57762265
0.012499375
0.0026115
0.00148355
0.500450394
0.112217492
0.126414528
0.00130571
0.027697423
0.17
0.04593144
0.016794315
Koc
(mL/g)
236
143
250
920
139
9
8000
9140
16470
98
315
15500
17
18
260
49
600
13
26
8
10
98
116
5
50
32
9
1.47
4
36
19
H2O Decay
(hr1)
0.021105443
0.006257579
0.001547204
0.04621
0.155573034
0.011378973
0.013309681
0.0693147
0.016503504
0.005653654
0.018566442
0.006069798
0.016503504
0.002578673
0.36823444
0.00059596
0.011695528
0.349461704
0.003180917
0.003522
0.00059596
0.002578673
0.002578673
0.015444
0.00022463
0.012180304
0.017
0.008423664
23.10491
0.003956
LOGKow
1.91
1.46
3.15
2.95
2.3
0.36
3.91
4.37
5.22
1.59
2 22
8.12
0.95
2.3
3.15
1.94
3.44
-0.3
0.2
0.86
0.45
1.96
1.99
-0.01
1.93
1.48
0.25
0.17
-1.36
0.32
0.73
Kd Water
(L/kg) Solubility
(mg/L)
16000
500
206
320
525
76480
13.9
1.3
1000
139
0.1
24706
7870
162.4
21520
81.3
37000
11130
95000
65900
4152
735
212500
3370
8608
74500
1000000
20000
POTW
Partition
(Removal)
99.48
45.75
89.8
94.89
78.03
45.46
81.57
92.73
99.99
75.38
76.37
99.93
92.09
76.63
96.12
92.34
75.34
45.43
51.81
75.95
46.05
54.38
97.32
92.18
84.36
58.03
92.19
92.07
92.06
100
92.4
POTW
Partition
(Sludge)
0.42219541616
2.55737704918
3.93095768374
2.11824217515
1.38408304498
2.39771227453
20.6448449185
31.7373018441
3.1803180318
0.95516052003
1.34869713238
38.2567797458
0.38006298187
1.46156857628
2.97544735747
0.56313623565
9.848685957
2.37728373322
1.91082802548
0.81632653061
2.34527687296
2.24347186466
0.50349362926
0.35799522673
0.82977714557
1.68878166466
0.3579563944
0.36928424025
0.35846187269
0
0.36796536797
POTW
Partition
(Volat)
92.390430237
0
38.240534521
8.2727368532
6.4334230424
0.065992081
0
0
0
0
0
0
0
0.052198878
15.574282147
0.010829543
32.505972923
0
21.250723798
3.5418038183
2.1715526602
25.78153733
85.665844636
1.008895639
81.86344239
37.342753748
1.1172578371
0.054306506
0
0.01
3.0735930736
POTW
Partition
(Biod)
7.1773220748
97.442622951
57.817371938
89.609020972
92.169678329
97.558293005
79.355155082
68.251914159
96.829682968
99.04483948
98.651302868
61.743220254
99.609078076
98.499282265
81.450270495
99.436863764
57.64534112
97.60070438
76.838448176
95.641869651
95.504885993
71.974990805
13.830661734
98.622260794
17.306780465
60.968464587
98.513938605
99.587270555
99.630675646
99.98
96.558441558
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
79
7.6
15
13.5
33
1.1
575
2400
5460
9.5
97
2260
3.1
150
15
17.6
214
1
0.84
1
1.2
10
19.16
344
7.45
2
48
10
1
9
Henry's
(atm-
mVmol)
0.415
0
0.00788
0.00275
0.000412
0
0
0
0
0
0
0
0
0
0.00753
0
0.0024
0
0.000479
0.00018
0.00003
0.000667
0.0736
0.000122
0.011
0.00118
0.000138
0
0
0.000304
0.000511
Molecular
Weight
139
168.11
106
104
127
350.27
267.16
254
250
198
200
370
123.15
122
106
108
147
108
108.09
72
92
188
54
56
76.53
99
53
58
62
80.51
86
D-9
-------
Table 1
CAS
Number
108101
108316
108383
108394
108601
108883
108907
108952
109068
109773
109864
110805
110827
110861
111422
111444
111911
1120714
114261
115071
115322
1163195
117793
117817
118741
119904
119937
120127
120581
120718
120809
120821
: Organic Chemicals
Chemical
Methyl isobutyl ketone
Maleic anhydride
m-Xylene
m-Cresol
Bis(2-chloro-l-methethyl)ether
Toluene
Chlorobenzene
Phenol
2-Methylpyridine
Malonitrile
2-Methoxyethanol
2-Ethoxyethanol
Cyclohexane
Pyridine
Diethanolamine
Bis(2-chloroethyl)ether
Bis(2-chloroethoxy)methane
Propane sultone
Propoxur
Propylene (Propene)
Dicofol
Decabromodiphenyl ether
2-Aminoanthraquinone
Di(2-ethylhexyl) phthalate
Hexachlorobenzene
3,3'-Dimethoxybenzidine
3,3'-Dimethylbenzidine
Anthracene
Isosafrole
p-Cresidine
Catechol
1 ,2,4-Trichlorobenzene
Air Decay
(hr1)
0.082959087
0.146627288
0.345737129
0.082696518
0.037989797
0.00522951
0.167206557
0.066882623
0.071258121
0.043819649
0.00297752
0.52948743
0.039505798
0.096027947
0.536944999
0.22916416
0.00103325
0.165752587
0.131458948
0.0001016
1.098648269
1.427831271
0.801407491
0.32
1.31458948
0.146627288
0.00296909
Koc
(mL/g)
19
181
166
34.6
73
95
275
16
9.6
6.6
9
21
482
5
4
79
31
2.04
160
219
46900
37530
11800
87420
14100
230
447
16000
540
42
118
1430
H2O Decay
(hr1)
0.016503504
69.31472
0.002578673
0.007718234
0.00088248
0.004266531
0.00030863
0.071525289
0.001375
0.002578673
0.002578673
0.00059596
0.016503504
0.026130548
0.00059596
0.0000693
0.081547
0.001805
0.002578673
0.00011979
0.006069798
0.003518247
0.0000218
0.011307308
0.016503504
0.801407491
0.0026
0.005634289
0.016503504
0.00059596
LOGKow
1.31
1.62
3.2
1.96
2.48
2.73
2.84
1.46
1.11
-0.6
-0.77
-0.32
3.44
0.65
-1.43
1.29
1.3
-0.28
1.52
1.77
5.02
12.11
2.43
7.6
5.73
1.81
2.34
4.45
3.37
1.74
0.88
4.02
Kd Water
(L/kg) Solubility
(mg/L)
19000
161
22700
1700
526
497.9
82800
10000000
133000
1000000
1000000
55
1000000
1000000
17200
8100
1140000
1859
200
1.32
0.02
0.16
0.34
0.0062
60
1300
0.0434
4721
461400
49
POTW
Partition
(Removal)
92.25
100
96.25
92.35
50.47
94.96
85.32
92.15
92.11
45.42
92.06
92.06
88.74
92.09
92.06
22.77
22.57
70.61
92.17
98.91
98.37
99.07
48.36
99.93
98.43
46.15
76.76
94.15
64.08
46.05
92.08
86.46
POTW
Partition
(Sludge)
0.40108401084
0
3.25194805195
0.56307525717
3.86368139489
1.43218197136
2.47304266292
0.42322300597
0.39083704267
2.37780713342
0.35846187269
0.35846187269
6.98670272707
0.36920403953
0.35846187269
6.58761528327
6.69029685423
0.9347117972
0.43398068786
0.38418764533
45.2678662194
62.4709801151
3.90818858561
38.2467727409
60.6319211622
2.77356446371
1.51120375195
33.4466277217
11.1735330836
2.71444082519
0.38010425717
22.1952347907
POTW
Partition
(Volat)
1.1165311653
0
14.379220779
0.01082837
6.2017039826
18.260320135
28.633380216
0
0.097709261
0
0.010862481
0.010862481
9.139057922
0.1085894234
0
3.3816425121
2.2596366859
0.0708115
0
90.830047518
0
0
0
0
0.4571776897
0
0
2.1879978757
0.1872659176
0
0
9.5998149433
POTW
Partition
(Biod)
98.482384824
100
82.379220779
99.426096373
89.934614623
80.318028644
68.893577121
99.576776994
99.511453697
97.622192867
99.630675646
99.630675646
83.885508226
99.511347595
99.630675646
90.030742205
91.05006646
99.008639003
99.555169795
8.7958750379
54.732133781
37.518926012
96.091811414
61.753227259
38.910901148
97.226435536
98.488796248
64.365374403
88.639200999
97.263843648
99.619895743
68.216516308
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
2.4
10
15
20
9.3
37
447
39
4.1
0.21
0.2
0.5
242
2
0.05
11
5.7
0.24
8.41
13.18
13900
1720
114
14500
14.12
35.48
675
72
10
3
1202
Henry's
(atm-
mVmol)
0.000138
0
0.00718
0
0.000112
0.00664
0.00377
0
0
0
0
0
0.0015
0.00001
0
0.00002
0.00001
0
0
0.196
0
0
0
0.00001
0.0017
1.8e-13
0
0.00072
0
0
0
0.00142
Molecular
Weight
100
98
106
108
171
92
112
94
93.13
66.06
76
90
84
79
105
143
173.1
112.14
209.24
42.08
370.47
959.17
223
390
285
254.43
212.28
178
162.18
137.18
110
181
D-10
-------
Table 1
CAS
Number
120832
121142
12122677
121697
122667
123319
123386
123728
123911
124732
126727
126987
126998
127184
128665
131113
1319773
132649
1330207
133062
1335871
1336363
133904
134292
134327
135206
137268
139139
139651
140885
141322
: Organic Chemicals
Chemical
2,4-Dichlorophenol
2,4- Dinitro toluene
Zmeb
N,N-Dimethylaniline
1 ,2-Diphenylhydrazine
Hydroquinone
Propionaldehyde
Butyraldehyde
1 ,4-Dioxane
1 ,2-Dibromotetrafluoroethane
Tris
(2,3-dibromopropyl)phosphate
Methacrylonitrile
Chloroprene
Tetrachloroethylene
(Perchloroethylene)
C.I. Vat Yellow 4
Dimethyl phthalate
Cresol (mixed isomers)
Dibenzofuran
Xylene (mixed isomers)
Captan
Hexachloronaphthalene
Polychlorinated biphenyls
Chloramben
o-Anisidine hydrochloride
alpha- Naphthylamine
Cupferron
Thiram
Nitrilotriacetic acid
4, 4'-Thiodi aniline
Ethyl acrylate
Butyl acrylate
Air Decay
(hr1)
0.017982592
0.08664
0.144864093
1.270769831
0.146576216
0.11552453
0.13615391
0.047065549
0.397115572
0.13197481
0.0009927
0.024282226
0.0034044
0.33672775
0.200647868
0.141174207
0.119134672
0.00116584
1.305585443
0.272307821
0.470655493
1.089231284
0.161501141
0.165752587
Koc
(mL/g)
126
201
1230
80
947
9.3
4
9.4
17
1202
1390
16.5
312
238
19100
40
81
8128
1738
198
32000
29495
190
104
3213
2.7
890
286
109
22
67
H2O Decay
(hr1)
0.548741518
0.01612
0.693147
0.018137219
0.03
0.906607412
0.016503504
0.016503504
0.001598777
0.14
0.016503504
0.00059596
0.00012034
0.00059596
0.016503504
0.347071541
0.002578673
0.002578673
0.231049
0.00011979
0.000007
0.69
0.005653654
0.00059596
0.005449
0.002578673
0.011623862
0.016503504
0.016503504
LOGKow
3.06
1.98
0.17
2.31
2.94
0.59
0.59
0.88
-0.27
2.96
4.29
0.68
2.53
3.4
6.28
1.56
1.99
4.12
3.16
2.35
7.04
6.4
1.9
1.18
2.25
-1.73
1.7
-3.81
2.18
1.32
2.36
Kd Water
(L/kg) Solubility
(mg/L)
4500
270
10
1454
68
72000
306000
71000
1000000
8
25400
480
200
0.08
4000
20900
4.22
168
3.3
0.0015
0.031
700
1698
10000000
18
59060
822
15000
2000
POTW
Partition
(Removal)
94.76
46.5
97.61
48.68
54.01
92.07
92.15
92.2
45.53
98.48
99.5
76.17
95.71
88.85
98.89
92.18
92.37
96.39
96.07
76.84
99.04
98.93
46.32
45.63
76.46
21.97
75.47
92.06
47.11
92.4
93.02
POTW
Partition
(Sludge)
2.62769100886
2.94623655914
0.1331830755
3.45110928513
6.62840214775
0.36928424025
0.36896364623
0.37960954447
2.37206237646
2.38627132413
14.3819095477
0.80084022581
1.1597534218
6.98930782217
61.9678430579
0.44478194836
0.58460539136
18.2902790746
3.02904132403
1.52264445601
62.3788368336
62.0843020317
2.8713298791
2.47644093798
1.38634580173
6.55439235321
0.98052206175
0.35846187269
3.26894502229
0.40043290043
0.84927972479
POTW
Partition
(Volat)
0.021105952
0
0
3.5332785538
0
0
0.6619641888
0.9652928416
0.3514166484
96.303818034
0.040201005
4.5949849022
92.82206666
85.413618458
0
0
0.010826026
0.2282394439
14.031435412
0.1691827173
0
0.030324472
0
0.1314924392
0.013078734
0
0.013250298
0
0
2.5108225108
2.6230918082
POTW
Partition
(Biod)
97.340650063
97.032258065
99.866816925
92.995069844
93.371597852
99.63071576
98.969072165
98.655097614
97.254557435
1.3099106418
85.577889447
94.591046344
6.0181799185
7.5970737198
38.032156942
99.555218052
99.415394609
81.491856002
82.939523264
98.308172827
37.611066236
37.895481654
97.128670121
97.392066623
98.600575464
93.445607647
99.00622764
99.630675646
96.731054978
97.077922078
96.516878091
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99.9999
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
100
19
170
10
100
39.8
1.66
2.75
0.4
141.3
2.75
1.9
21.38
48.98
6760
57.5
19.2
1349
2.17
10
346736
43053
15.49
4.6
30.2
0.029
11.5
1.26
20.42
5.89
8.49
Henry's
(atm-
mVmol)
0
0
0
0.00006
0
0
0.00007
0.000115
0
0.162
0.00002
0.000247
0.0523
0.0177
8.3e-12
0
0
0.00005
0.00663
0
0.00009
0.000415
0
0
0
0
0
1.2e-16
3.9e-12
0.000393
0.00046
Molecular
Weight
163
182
275.73
121.18
184
110
58.08
72
88
260
697.61
67.09
88.54
166
332.36
194.19
108.14
168.19
106.17
300
334.84
371.22
206.03
159.61
143.18
156.19
240.41
191
216
100
128.17
D-ll
-------
Table 1
CAS
Number
1464535
151564
156105
1582098
16071866
1634044
16543558
1717006
1836755
1897456
1937377
2164172
2234131
2303164
23950585
25321146
25321226
25376458
2602462
26471625
2832408
2837890
306832
309002
3118976
334883
34077877
353593
354234
354256
: Organic Chemicals
Chemical
Diepoxybutane
Ethyleneimine (Aziridine)
p-Nitrosodiphenylamine
Trifluralin
C.I. Direct Brown 95
Methyl tert-butyl ether
3-(l-nitroso-
2-pyrrolidinyl)pyridine
1 , 1 -Dichloro- 1 -fluoroethane
Nitrofen
Chlorothalonil
C.I. Direct Black 38
Fluometuron
Octachloronaphthalene
Diallate
Pronamide
Dinitrotoluene (mixed isomers)
Dichlorobenzene
(mixed isomers)
Diaminotoluene
(mixed isomers)
C.I. Direct Blue 6
Toluenediisocyanate
C.I. Disperse Yellow 3
2-Chloro- 1,1,1 ,2-tetrafluoroethane
2,2-Dichloro- 1,1,1 -triiluoroethane
Aldrm
C.I. Solvent Orange 7
Diazomethane
Dichlorotrifluoroethane
Bromochlorodifluoromethane
l,2-Dichloro-l,l,2-triiluoroethane
1 -Chloro- 1 , 1 ,2,2-tetrafluoroethane
Air Decay
(hr1)
0.00508308
0.036307709
1.524923797
0.058
0.01805051
0.0002371
0.65729474
0.0766
0.00309
1.411966479
1.188
0.423166777
Koc
(mL/g)
2.5
6
1890
11070
187085
11.2
25
464
4370
5780
11031
175
782000
273
984
201
1700
61
959
2580
3985
245
361
48500
28575
292
361
346
361
245
H2O Decay
(hr1)
0.007001
0.000188
0.005653654
0.078
0.00059596
0
0
0.00011979
0.001535743
0.13
0.000596
0.011378973
0.693147
0.00071205
0.18
LOGKow
-0.28
-0.28
3.16
5.34
7.16
0.94
0.32
2.37
4.64
3.05
4.9
2.42
8.24
4.08
3.57
2.18
3.47
0.16
2.95
3.74
3.98
1.86
2.17
6.5
6.6
0
2.17
1.9
2.17
1.86
Kd Water
(L/kg) Solubility
(mg/L)
1000000
1000000
7.43
8.11
51000
14.43
1
0.6
85
14
15
270
119.2
35
1.18
0.18
0.0237
POTW
Partition
(Removal)
75.07
45.67
58.45
97.4
99.68
52.94
45.44
90.83
96.14
82.82
97.89
48.3
99.07
86.49
70.37
47.12
75.23
84.56
54.18
99.48
83.69
99.53
97.43
98.96
99.66
92.38
97.43
97.39
97.43
99.53
POTW
Partition
(Sludge)
0.82589583056
2.36479089118
8.65697177074
58.4496919918
52.8691813804
1.87004155648
2.39876760563
1.06792909832
38.2255044726
3.88794977059
43.3752170804
3.89233954451
62.4709801151
24.5230662504
14.153758704
3.26825127334
10.46125216
0.56764427625
6.71834625323
2.03055890631
22.2009798064
0.42198332161
0.6568818639
62.1564268391
52.6891430865
0.58454210868
0.6568818639
0.48259574905
0.6568818639
0.42198332161
POTW
Partition
(Volat)
0.026641801
0.8977446902
0
0.030800821
0
24.348318852
0
95.3759771
0
0.036223135
0
0
0
0.046248121
0.1563166122
0.042444822
29.482919048
82.887890255
0
0.010052272
0
98.854616698
97.998563071
0.030315279
0
0
97.998563071
98.182564945
97.998563071
98.854616698
POTW
Partition
(Biod)
99.160783269
96.759360631
91.343028229
41.509240246
47.13081862
73.781639592
97.623239437
3.5560938016
61.774495527
95.12195122
56.62478292
96.128364389
37.529019885
75.430685628
85.689924684
96.689303905
60.055828792
16.544465468
93.281653747
97.959388822
77.799020194
0.7233999799
1.3445550652
37.813257882
47.310856914
99.415457891
1.3445550652
1.3245713112
1.3445550652
0.7233999799
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
0.02
0.08
269
3415
1.5
0.62
37
1549
501
3100
28
44668
140
300
27
260
103
410
623
15.3
26.3
3890
11749
19.5
26.3
24.7
26.3
15.3
Henry's
(atm-
mVmol)
0
0.00001
0
0.00003
l.Oe-24
0.000587
0
0.0241
0
0
8.2e-40
0
0.00019
0
0
0
0.00215
0.0113
l.Oe-24
0.00001
0
0.54
0.0955
0.000493
0
0
0.0955
0.094
0.0955
0.54
Molecular
Weight
86.09
43
198.22
335
88
177.2
116.95
284.1
265.9
783.74
232.21
403.73
270.24
256.14
182.15
147
122.17
174
269.3
136.48
152.93
365
276.32
42.04
152.93
165
152.93
136.48
D-12
-------
Table 1
CAS
Number
3761533
39156417
4549400
463581
4680788
492808
50000
505602
510156
51285
51752
51796
52686
528290
532274
534521
53963
540590
541413
541731
542756
542881
55185
55210
55630
56235
56382
569642
57147
57578
57749
584849
: Organic Chemicals
Chemical
C.I. Food Red 5
2,4-Diaminoanisole sulfate
N-Nitrosometriylvinylamine
Carbonyl sulfide
C.I. Acid Green 3
Auramine
Formaldehyde
Mustard gas
Chlorobenzilate
2,4-Dinitrophenol
Nitrogen mustard
Urethane (Ethyl Carbamate)
Trichlorfon
o-Dinitrobenzene
2-Chloroacetophenone
4,6-Dinitro-o-cresol
2-Acetylaminofluorene
1 ,2-Dichloroethylene
Ethyl chloroformate
1 ,3-Dichlorobenzene
1 ,3-Dichloropropylene
Bis(chloromethyl)ether
N-Nitrosodiethylamine
Benzamide
Nitroglycerin
Carbon tetrachloride
Parathion
C.I. Basic Green 4
1 , 1 -Dimethyl Hydrazine
beta-Propiolactone
Chlordane
Toluene-2,4-diisocyanate
Air Decay
(hr1)
0.113098473
1.935182484
0.335021137
0.020496288
0.029325458
0.00343339
0.428349381
0.127076983
0.350005012
0.00515874
0.00122985
0.52948743
0.014964716
0.00856699
0.00427869
0.078688
1.945055864
0.129965096
0.122977726
0.216608494
0.000024
8.3
10.21717166
0.478226545
0.00211795
0.073352318
Koc
(mL/g)
546
16.2
20
88
64.1
2030
37
120
1065
55.6
91
20
6
1.47
76
238
1380
35
52.4
293
26
17.9
43
13.4
468
110
10654
97.7
4
4
38000
2580
H2O Decay
(hr1)
0.00059596
0.00059596
0.016503504
9.902103
0.001375
0.004591209
1.386294
0.0000693
0.010315
0.002578673
0.005188602
0.00059596
0.00059596
1.019542329
0.00059596
0.002556
69.31472
0.129965096
0.008182988
0.009283221
0.00012607
0.000722
0.00059596
0.00246146
0.204468
0.0000711
0.693147
LOGKow
2.5
-0.31
-0.28
-1.33
0.79
2.68
0.35
2.41
4.74
1.67
0.91
-0.15
0.51
1.69
1.93
2.12
3.12
2.09
0.63
3.53
2.03
0.57
0.48
0.64
1.62
2.83
3.83
0.8
-1.19
-0.8
6
3.74
Kd Water
(L/kg) Solubility
(mg/L)
30000
1220
11.02
400000
684
13
2787
46700
480000
154000
133
1572
198
5.29
3500
125
2800
22000
93000
13500
1380
804.8
6.54
1000
1000000
370000
0.056
POTW
Partition
(Removal)
48.85
45.43
51.08
96.18
45.49
50.47
92.07
99.99
96.95
75.45
99.1
45.43
92.07
45.98
46.45
46.93
57.53
72.25
81.95
77.5
82.99
100
22.14
92.07
75.4
92.57
98.36
45.49
75.12
95.91
98.72
99.48
POTW
Partition
(Sludge)
4.15557830092
2.37728373322
17.5998433829
0.30151798711
2.41811387118
4.95343768575
0.36928424025
0.0300030003
40.3713254255
0.98078197482
0.0706357215
2.37728373322
0.36928424025
2.67507612005
2.88482238967
3.15363307053
8.25656179385
1.39792387543
0.63453325198
10.4
0.9157729847
0
6.54923215899
0.36928424025
0.9549071618
2.11731662526
8.92639284262
2.41811387118
0.82534611289
0.21895527057
61.5174230146
2.03055890631
POTW
Partition
(Volat)
0
0
19.068128426
82.855063423
0
0
0
0.010001
0
0.01325381
0.010090817
0
0
0
0.2583423036
0.1065416578
0
64.179930796
30.762660159
31.393548387
32.341245933
0
0.7678410117
0
0
87.57696878
0
0
0.2396166134
0
0.01012966
0.010052272
POTW
Partition
(Biod)
95.844421699
97.60070438
78.993735317
16.84341859
97.581886129
95.046562314
99.619854459
99.969997
59.628674575
99.005964215
99.919273461
97.60070438
99.63071576
97.303175294
96.856835307
96.739825272
91.760820442
34.422145329
68.602806589
57.432258065
66.730931438
100
92.682926829
99.63071576
99.045092838
10.305714594
91.063440423
97.581886129
98.935037274
99.770618288
38.482576985
97.959388822
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
46.8
0.6
11.2
288
1
15.5
145
9
4
0.5
0.71
0.97
9.77
23.99
171
15.1
580
7
1
1.8
10
19.95
478
0.043
0.45
38018
410
Henry's
(atm-
mVmol)
4.0e-23
0
0.00041
0.0492
4.8e-29
0
0
0.00003
0
0
0
0
0
0
0
0
0
0.00408
0.00312
0.00263
0.00355
0.000206
0
0
0
0.0276
0
1.9e-14
0
0
0.00005
0.00001
Molecular
Weight
482.43
234.23
86.1
60.07
690.8
267.37
30
159.08
325.2
184
156
89
257
168
154.59
198
223
96.95
108.53
147
111
114.97
88
121
227
154
291.27
364.9
60
72
409.8
174.15
D-13
-------
Table 1
CAS
Number
58899
593602
59892
60093
60117
60344
60355
606202
615054
61825
621647
624839
62533
62555
62566
62737
62759
630206
63252
636215
63938103
64186
64675
67561
67630
67641
67663
67721
680319
684935
68768
70304
: Organic Chemicals
Chemical
Lindane
Vinyl bromide
N-Nitrosomorpholine
4-Aminoazobenzene
4-Dimetriylaminoazobenzene
Methyl hydrazine
Acetamide
2,6-Dinitro toluene
2,4-Diaminoanisole
Amitrole
N-Nitrosodi-n-propylamine
Methyl isocyanate
Aniline
Thioacetamide
Thiourea
Dichlorvos
N-Nitrosodimethylamine
1,1,1 ,2-Tetrachloroethane
Carbaryl
o-Toluidine hydrochloride
Chlorotetrafiuoroethane
Formic acid
Diethyl sulfate
Methanol
Isopropyl alcohol
Acetone
Chloroform
Hexachloroethane
Hexamethylphosphoramide
N-Nitroso-N-methylurea
Triaziquone
Hexachlorophene
Air Decay
(hr1)
0.041258761
0.040556484
0.404335855
0.393021597
1.319138233
6.712911884
0.119134672
0.034249625
0.119
2.385241768
0.204962876
0.119237168
0.238269343
0.016632
1.039720771
0.00017
4.667815473
0.00286
0.105897486
0.0053674
0.060712488
0.00136642
0.0006119
0.00001
0.722028313
0.560633749
0.0113
Koc
(mL/g)
1081
170
1.14
618
7388
6
5
100
20.4
4.4
28
64.1
13.6
6
7
150
12
92.7
390
124
245
12.1
33.5
9
25
18
45
2188
34
22.5
20.2
288
H2O Decay
(hr1)
0.00111034
0.00059596
0.205905486
0.006069798
0.011695528
0.001712503
0.016503504
0.193673477
0.000596
2.385241768
4.620981
0.016503504
0.016503504
0.002666
1.039720771
0.0219
0.002063
0.0165
0.400663
0.016503504
0.016503504
0.016503504
0.00059596
0.00059596
26.75852797
0.007967
0.000102
LOGKow
3.72
1.57
-0.44
3.41
4.58
-1.05
-1.26
2.1
-0.31
-0.86
1.36
0.79
0.9
-0.26
-1.08
1.16
-0.57
2.93
2.36
1.32
1.86
-0.54
1.14
-0.77
0.05
-0.24
1.97
3.91
0.28
-0.03
-0.13
7.54
Kd Water
(L/kg) Solubility
(mg/L)
7.3
4180
861527
34.6
160
1000000
705000
182
19500
280000
9894
36000
163000
142000
10000
1000000
1100
82.6
10000000
7000
1000000
1000000
1000000
7950
50
1000000
14430
140
POTW
Partition
(Removal)
75.38
94.65
45.43
65.22
95.55
75.08
92.06
46.85
45.43
45.42
45.79
99.95
92.09
45.56
75.06
75.26
45.46
58.8
93.29
45.7
99.53
92.06
95.12
92.07
92.07
92.11
70.8
77.49
45.44
45.43
45.43
99.06
POTW
Partition
(Sludge)
16.7949058106
0.22187004754
2.37728373322
11.7295308188
36.8602825746
0.82578582845
0.35846187269
3.13767342583
2.37728373322
2.37780713342
2.51146538546
0.020010005
0.38006298187
2.37050043898
0.82600586198
0.86367260165
2.37571491421
5.76530612245
0.84682173866
2.51641137856
0.42198332161
0.35846187269
0.22077375946
0.35842293907
0.36928424025
0.35826728911
1.3418079096
23.0094205704
2.39876760563
2.37728373322
2.37728373322
62.4470018171
POTW
Partition
(Volat)
0.039798355
27.871104068
0
0
0
0.079914758
0
0.064034152
0
0
0.3930989299
0.140070035
0.021717885
0.4828797191
0
0.3454690407
0.1319841619
68.758503401
5.788401758
0.1531728665
98.854616698
0
0.052565181
0.043445205
0.086890409
0.3799804581
62.231638418
43.799199897
0
0
0
0
POTW
Partition
(Biod)
83.152029716
71.907025885
97.60070438
88.270469181
63.139717425
99.10761854
99.630675646
96.81963714
97.60070438
97.622192867
97.095435685
99.83991996
99.598219133
97.146619842
99.173994138
98.790858358
97.492300924
25.476190476
93.364776503
97.352297593
0.7233999799
99.630675646
99.72666106
99.587270555
99.554686651
99.250895668
36.426553672
33.191379533
97.601232394
97.622716267
97.60070438
37.552998183
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
1259
9.18
0.27
87
1778
0.09
0.06
12.02
0.48
6.31
19.9
0.71
0.1
7.76
0.22
99.3
33.9
5.93
15.3
4.37
3.02
0.65
0.39
8.3
138
0.96
0.56
Henry's
(atm-
mVmol)
0
0.0123
0
0
0
0.00003
0
0
0
0
0
0.000926
0
0
0
0.00001
0
0.00242
0.00131
0
0.54
0
0
0
0
0.00004
0.00367
0.00389
0
0
9.3e-16
8.6e-13
Molecular
Weight
291
106.95
116.12
197
225
46
59
182
138.17
84.08
130
57.05
93.12
75
76.12
220.98
74.08
167.85
201.22
143.61
136.48
46.03
154
32.04
60.09
58.08
119.39
236.74
179
103.09
231.25
406.92
D-14
-------
Table 1
CAS
Number
71363
71432
71556
72435
72571
74839
74851
74873
74884
74931
74953
75003
75014
75058
75070
75092
75150
75218
75252
75274
75343
75354
75445
75558
75569
75638
75650
75683
75694
: Organic Chemicals
Chemical
n-Butyl alcohol
Benzene
1,1,1 -Trichloroethane
Methoxychlor
Trypan blue
Bromomethane
(Methyl Bromide)
Ethylene
Chloromethane
Methyl iodide
Methyl mercaptan
Methylene bromide
Chloroethane (Ethyl chloride)
Vinyl chloride
Acetonitrile
Acetaldehyde
Dichloromethane
Carbon disulfide
Ethylene oxide
Bromoform (Tribromomethane)
Dichlorobromomethane
Ethylidene dichloride
Vinylidene chloride
Phosgene
Propyleneimine
Propylene oxide
Bromotrifluoromethane (Halon
1301)
tert-Butyl Alcohol
1 -Chloro- 1 , 1 -difluoroethane
CFG- 11
(trichlorofluoromethane)
Air Decay
(hr1)
0.043335171
0.0076094
0.000071
0.340384776
0.0002335
0.06208778
0.000259
0.0007126
0.000448
0.00238215
0.03930216
0.0002935
0.0008323
0.0004157
0.0002935
0.038518817
0
0.347762522
0.00646154
0
Koc
(mL/g)
72
31
179
80000
20.5
106
98
74
158
21.7
25
37.6
135
0.28
2.19
28
65
16
52
51
38.3
343
9.8
11
25
245
37
81.3
97.7
H2O Decay
(hr1)
0.016503504
0.003790649
0.00015604
0.221713745
0.001444
0.014956301
0.002578673
0.002578673
0.0000693
0.00076
0.00059596
0.002578673
0.002578673
0
0.002407
0.00059596
0
0.0000693
0.00059596
7.28
0.008023
0.001978
0.00059596
0.00012
LOGKow
0.88
2.13
2.49
5.08
-0.12
1.19
1.13
0.91
1.51
0.78
1.7
1.43
1.62
-0.34
-0.34
1.25
2.14
-0.3
2.4
0
1.79
2.13
-0.71
0.13
0.03
1.86
0.35
2.05
2.53
Kd Water
(L/kg) Solubility
(mg/L)
63200
1790
1495
0.04
15220
131
5325
13848
15390
11930
5678
8800
74000
1000000
13030
1185
1000000
3100
6735
5500
2250
1000000
400000
320
1000000
1397
1000
POTW
Partition
(Removal)
92.09
94.09
87.75
98.56
45.43
77.45
99.06
87.66
75.27
81.97
55.71
84.39
92.41
75.27
92.13
82.2
87.17
92.2
54.51
64.24
76.2
92.02
100
75.16
92.16
99.46
45.74
96.62
97.48
POTW
Partition
(Sludge)
0.38006298187
0.61643107663
1.37891737892
46.1038961039
2.37728373322
0.81342801808
0.28265697557
0.50193931097
0.94327089146
0.63437843113
1.93861066236
0.65173598768
0.49778162537
0.82370134184
0.35818951482
0.66909975669
0.90627509464
0.3579175705
3.1370390754
1.68119551681
1.01049868766
0.74983699196
0
0.82490686535
0.35807291667
0.42228031369
2.36117184084
0.57959014697
1.10791957325
POTW
Partition
(Volat)
0.086871539
18.344138591
93.823361823
0
0
73.699160749
91.490006057
53.593429158
70.346751694
30.779553495
30.766469216
82.450527314
90.996645385
0.8237013418
0.6078367524
31.435523114
84.730985431
1.1822125813
21.060355898
49.673100872
71.299212598
90.056509454
0
0.3459286855
0.87890625
98.833701991
1.049409707
97.847236597
97.466146902
POTW
Partition
(Biod)
99.533065479
81.039430333
4.7977207977
53.90625
97.60070438
25.487411233
8.2273369675
45.916039243
28.709977415
68.573868488
67.294920122
16.897736699
8.5055729899
98.352597316
99.033973733
67.128953771
14.374211311
98.449023861
75.802605027
48.630136986
27.690288714
9.1936535536
100
98.829164449
98.763020833
0.7440176956
96.56755575
1.562823432
1.4259335248
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
2.75
4.27
8.91
8317
4.68
4.27
2.88
8.32
3.09
7.24
10
0.87
0.4
5.25
11.5
0.35
3.24
22.9
13.5
24.5
0.204
0.62
15.3
1.1
21.3
25
Henry's
(atm-
mVmol)
0
0.00555
0.0172
0
l.Oe-24
0.00624
0.228
0.00882
0.00526
0.00313
0.000861
0.0111
0.0278
0.00003
0.00007
0.00325
0.0144
0.000148
0.000535
0.00212
0.00562
0.0261
0.00892
0.00001
0.000103
0.465
0.00001
0.0719
0.097
Molecular
Weight
74.12
78.11
133.42
345.65
960.83
94.95
28.05
50.49
141.95
48.11
174
64
62.5
41.05
44.05
84.94
76.14
44.05
252.77
163.8
98.96
96.95
98.92
57
58.08
149
74.12
100.5
137
D-15
-------
Table 1
CAS
Number
75718
759739
76017
76131
76142
76153
764410
76448
77474
77781
78842
78875
78886
78922
78933
79005
79016
79061
79107
79118
79210
79221
79345
79447
79469
8001352
80057
80159
80626
81072
: Organic Chemicals
Chemical
CFG- 12
(dichlorodifiuoromethane)
N-Nitroso-N-ethylurea
Pentachloroethane
Freonll3
CFG 1 14 (l,2-dichloro,l, 1,2,2-
tetrafluoroethane)
CFC 115 (chloropentafluoroethane)
1 ,4-Dichloro-2-butene
Heptachlor
Hexachlorocyclopentadiene
Dimethyl sulfate
Isobutyraldehyde
1 ,2-Dichloropropane
2,3-Dichloropropene
sec-Butyl alcohol
Methyl ethyl ketone
1 , 1 ,2-Trichloroethane
Trichloroethylene
Acrylamide
Acrylic acid
Chloroacetic acid
Peracetic acid
Methyl chlorocarbonate
1 , 1 ,2,2-Tetrachloroethane
Dimethylcarbamyl chloride
2-Nitropropane
Toxaphene
4,4'-Isopropylidenediphenol
Cumene hydroperoxide
Methyl methacrylate
Saccharin (manufacturing)
Air Decay
(hr1)
0.00018
0.763989878
0
0.387931885
0.385514443
0.010444684
0.158846229
0.00586839
0.08
0.052948743
0.00593818
0.00194542
0.014110227
0.153191352
0.00185966
0.027625431
0.00178974
0380551393
0.078281509
0.0058
0.515176959
0.029325458
0.350796136
0.381230949
Koc
(mL/g)
200
23.84
146.3
372
815
708
619
3475
2000
16
8
27
77
5.6
5.2
79
104
50
2.19
0.81
7.5
28.4
79
9.7
20
6000
1288
23
22
46
H2O Decay
(hr1)
0.000596
26.75852797
0.00012034
0.17
0.009025
0.006447
0.002063
0.577623
0.016503504
0.0000977
0.00107
0.016503504
0.016503504
0.00014578
0.00012034
0.016503504
0.016503504
0.088706336
2.038668
0.03271825
69.31472
0.00059596
0.00019
0.014530985
0.002578673
0.002578673
0.002578673
LOGKow
2.16
0.23
3.22
3.16
2.82
2.47
2.6
5.5
5.04
0.16
0.74
2.25
2.42
0.61
0.29
1.89
2.42
-0.67
0.35
0.22
-1.07
0.14
2.39
-0.72
0.93
6.79
3.32
2.16
1.38
0.91
Kd Water
(L/kg) Solubility
(mg/L)
280
480
170
130
58
0.18
3.4
28000
89000
2700
2750
181000
223000
4420
1100
640000
1000000
6140000
712610
2962
17000
0.55
120
13900
15000
4000
POTW
Partition
(Removal)
99.27
45.44
57.89
99.53
99.91
99.9
90.12
99.3
98.78
96.97
92.23
67.88
65.86
92.08
92.13
39.79
80.97
92.06
92.07
92.06
92.06
99.63
33.23
100
75.73
99.01
85.68
76.21
92.38
75.13
POTW
Partition
(Sludge)
0.59433867231
2.39876760563
9.84626014856
3.47633879232
1.75157641878
0.93093093093
1.48690634709
50
44.826888034
0.14437454883
0.36864360837
1.82675309369
2.30792590343
0.36924413553
0.36904374254
3.59386780598
1.51908114116
0.35846187269
0.36928424025
0.36932435368
0.35846187269
0.050185687
6.37977730966
0
0.83190281262
62.3169376831
5.99906629318
1.28592048288
0.41134444685
0.85185678158
POTW
Partition
(Volat)
98.579631309
0
57.591984799
95.468702904
97.507756981
98.408408408
82.279183311
0.2819738167
9.8602956064
0.020624936
1.3878347609
55.362404243
49.559672032
0.097741095
0.5318571584
54.486051772
90.971964925
0
0.010861301
0
0.021724962
0.8230452675
34.84802889
0
2.4957084379
0
0
0
2.2299198961
0
POTW
Partition
(Biod)
0.8159564823
97.601232394
32.561755053
1.054958304
0.7406665999
0.6606606607
16.222814026
49.718026183
45.31281636
99.835000516
98.243521631
42.810842664
48.147585788
99.543874891
99.109953327
41.920080422
7.5089539336
99.641538127
99.619854459
99.641538127
99.619813165
99.126769045
58.80228709
100
96.659183943
37.683062317
94.000933707
98.714079517
97.358735657
99.148143218
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
26
0.88
165
148
82
61
55.7
9550
465
79.43
7.9
10
1.2
1.71
1
10
17
1
0.8
0.9
0.12
8
10
5012
10
8.51
6.6
2.88
Henry's
(atm-
mVmol)
0.343
0
0.00194
0.526
2.8
2.66
0.0188
0.00148
0.027
0
0.00018
0.00282
0.00228
0
0.00006
0.000824
0.00985
0
0
0
0
0.00235
0.000367
0
0.000119
0
9.2e-12
0
0.000337
0
Molecular
Weight
121
117.1
202.29
187.38
171
154
125
373.35
273
126
72
113
111
74.12
72
133
131
71
72
94
76.05
94.5
168
107.54
110
431.8
228
152
100
183.18
D-16
-------
Table 1
CAS
Number
812044
81889
82280
82688
842079
84662
84742
85449
86306
87627
87683
87865
88062
88755
88891
90040
90437
90454185
90948
91087
91203
91225
91598
91941
924163
92524
92671
92875
92933
94360
94586
: Organic Chemicals
Chemical
1 , 1 -Dichloro- 1 ,2,2-trifluoroethane
(HCFC-123b)
C.I. Food Red 15
1 -Amino-2-methyl-anthraquinone
Quintozene
C.I. Solvent Yellow 14
Diethyl phthalate
Dibutyl phthalate
Phthalic anhydride
N-Nitrosodiphenylamine
2,6-Xyhdine
Hexachloro-l,3-butadiene
Pentachlorophenol
2,4,6-Trichlorophenol
2-Nitrophenol
Picric acid
o-Anisidine
2-Phenylphenol
Dichloro- 1 , 1 ,2-trifluoroethane
Michlers Ketone
Toluene-2,6-Diisocyanate
Naphthalene
Quinoline
beta-Naphthylamine
3,3'-Dichlorobenzidine
N-Nitrosodi-n-butylamine
Biphenyl
4-Aminodiphenyl
Benzidine
4-Nitrobiphenyl
Benzoyl Peroxide
Dihydrosafrole
Air Decay
(hr1)
0.173286795
0.000043
0.116942009
0.018138285
0.051517696
0.0007861
0.544615642
1.155245301
0.0001331
0.00273873
0.00308939
0.054391831
0.000596
0.719303678
3.481489248
1.906154747
1.187635356
0.12879424
0.038158102
1.274753436
18.48392481
0.872382035
0.047583181
0.635384916
1.221894068
0.014067563
0.00747512
0.497
Koc
(mL/g)
361
274
8005
6060
3795
98
160
36
1200
0
37153
900
620
113
23.6
35
119
361
162
2580
871
43
203.7
190000
88.4
1500
185.8
227000
2688
1296
2111
H2O Decay
(hr1)
0.006069798
0.0000885
0.002604459
0.005071389
0.015472035
1.540327
0.001868779
0.005653654
0.00059596
0.349724259
0.176896937
0.002578673
0.00059596
0.005634289
0.016503504
0.011623862
0.693147
0.029603161
0.006257579
0.005689487
18.48392481
0.129965096
0.011689982
0.016503504
0.012913199
0.014956301
0.016503504
0.00258
LOGKow
2.17
1.95
4.07
4.64
5.51
2.47
4.72
1.6
3.13
2.17
4.78
5.12
3.69
1.79
1.33
1.18
3.09
2.17
3.87
3.74
3.3
2.03
2.28
3.51
1.92
3.98
2.86
1.34
3.82
3.46
3.58
Kd Water
(L/kg) Solubility
(mg/L)
0.33
0.55
1.29
1080
13
6200
35
8240
3.2
14
800
2185
13200
6460
700
400
31
6110
263
3.11
1200
7.1
311
360
7.36
9.1
POTW
Partition
(Removal)
97.43
46.43
86.22
89.86
99.31
92.95
99.22
99.3
57.77
47.12
94.82
96.2
91.33
53.42
22.17
75.19
94.89
97.43
60.21
99.48
95.99
75.94
76.56
68.37
46.62
98.86
52.74
75.24
93.12
96.7
70.75
POTW
Partition
(Sludge)
0.6568818639
2.90760284299
24.2983066574
48.3529935455
50.1057295338
1.01129639591
29.6109655311
0.0805639476
8.34343084646
3.24702886248
47.5427125079
56.2681912682
10.5113325304
2.15275177836
6.85611186288
0.87777630004
2.76109179049
0.6568818639
31.7389138017
2.03055890631
3.93791019898
1.17197787727
1.4237199582
13.2075471698
2.85285285285
10.6716568885
6.04854000758
0.89048378522
12.6181271478
5.18097207859
14.3038869258
POTW
Partition
(Volat)
97.998563071
0
0
0.5230358335
0
0
0
0
0.051930068
0.1697792869
18.487660831
0
0.076645133
23.961063272
0
0
0.010538518
97.998563071
0
0.010052272
1.7085113033
0.065841454
0
0
0.9438009438
0.6170341898
0
0
0.010738832
0.020682523
0.3392226148
POTW
Partition
(Biod)
1.3445550652
97.070859358
75.701693343
51.135099043
49.894270466
98.988703604
70.378955856
99.909365559
91.604639086
96.583191851
33.969626661
43.731808732
89.412022337
73.886184949
93.143888137
99.1222237
97.217831173
1.3445550652
68.277694735
97.959388822
94.353578498
98.762180669
98.563218391
86.777826532
96.203346203
88.711308922
93.951459992
99.109516215
87.371134021
94.798345398
85.356890459
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
26.3
17.9
1148
590
1202
117
20.89
9.68
217
28
11400
766
310
13.5
1
4.6
15.5
26.3
20.9
410
426
7.94
31.6
495
17
436
79.4
110
436.5
251
310
Henry's
(atm-
mVmol)
0.0955
l.Oe-24
1.2e-12
0.00008
0
0
0
0
0
0
0.0103
0
0
0.000589
0
0
0
0.0955
0
0.00001
0.000483
0
0
0
0.00001
0.000408
0
0
0
0
0.00001
Molecular
Weight
152.93
479
237.25
295.5
248.28
222
278
148
192
121
261
266.5
197.5
160
229.11
123.16
170.2
152.93
268.35
174.15
128
129.15
143.18
253
158.24
154
169.22
184
199.2
242
164.22
D-17
-------
Table 1
CAS
Number
94597
94757
95476
95487
95501
95534
95636
95807
95954
96093
961115
96128
96333
96457
97563
98077
98828
98862
98873
98884
989388
98953
99558
99592
99650
: Organic Chemicals
Chemical
Safrole
2,4-D
((2,4-dichlorophenoxy)acetic acid)
o-Xylene
o-Cresol
1,2 Dichlorobenzene
o-Toluidine
1,2,4 Trimethylbenzene
2,4-Diaminotoluene
2,4,5-Trichlorophenol
Styrene oxide
Tetrachlorvinphos
1 ,2-Dibromo-3-chloropropane
(DBCP)
Methyl acrylate
Ethylene thiourea
C.I. Solvent Yellow 3
Benzo trichloride
Cumene
Acetophenone
Benzal chloride
Benzoyl chloride
C.I. Basic Red 1
Nitrobenzene
5-Nitro-o-toluidine
5-Nitro-o-anisidine
m-Dinitrobenzene
Air Decay
(hr1)
0.635384916
0.211794972
0.086643398
0.238269343
0.00249497
0.967591242
0.238269343
1.411966479
0.01266548
0.030994386
0.00261133
0.141196648
0.766886242
0.464915792
0.00219477
0.039221291
0.014119665
0.00373623
0.700792186
0.193
0.175682465
0.000184
Koc
(mL/g)
670
109
129
103
280
100
2712
36
1500
53
1167
102
11
50
347
492
454
38.3
209
145
38121
229
248
63.2
1.39
H2O Decay
(hr1)
0.002578673
0.010830425
0.002578673
0.016503504
0.00059596
0.019537237
0.002578673
0.011378973
0.69417865
0.015753
0.00061
0.00059596
0.016503504
0.002578673
0.006069798
69.31472
0.009025354
6.931472
17.32868
0.001149618
0.015
0.014956301
0.00111
LOGKow
3.45
2.81
3.12
1.95
3.43
1.32
3.78
0.14
3.72
1.61
3.53
2.96
0.8
-0.66
4.29
3.9
3.66
1.58
2.97
1.44
5.89
1.85
1.87
1.47
1.49
Kd Water
(L/kg) Solubility
(mg/L)
810.67
890
178
25950
83.96
16600
57
300
1200
3000
11
1230
49400
20000
100
53
49.9
5500
250
1900
2206
533
POTW
Partition
(Removal)
66.53
93.8
95.78
92.35
73.77
99.92
94.11
45.44
75.39
75.49
88.9
33.45
92.25
45.43
91.29
100
98.07
92.2
99.99
100
99.54
92.32
46.26
45.76
45.78
POTW
Partition
(Sludge)
12.2801743574
1.70575692964
2.83984130299
0.56307525717
10.0040666938
0.28022417934
11.4653065562
2.39876760563
16.792678074
0.95376871109
8.29021372328
13.0343796712
0.36856368564
2.37728373322
29.7294336729
0.03
6.93382277965
0.44468546638
0.100010001
0.01
51.7078561382
0.51993067591
2.831820147
2.55681818182
2.57754477938
POTW
Partition
(Volat)
0.3006162633
0
12.00668198
0.01082837
28.371966924
93.975180144
16.523217511
0
0.092850511
0.384156842
0
15.216741405
1.4850948509
0.022011886
0
0
11.349036403
0.1084598698
0.040004
0.01
0
0.2274696707
0
0
0.0218436
POTW
Partition
(Biod)
87.419209379
98.29424307
85.163917311
99.426096373
61.637522028
5.7445956765
72.000850069
97.601232394
83.101207057
98.662074447
91.709786277
71.77877429
98.135501355
97.60070438
70.281520429
99.97
81.70694402
99.436008677
99.859985999
99.98
48.292143862
99.241767764
97.168179853
97.443181818
97.400611621
Incinerator
ORE
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
99
BCF
(L/kg)
61.6
10
21
18
270
5.9
439.5
1.07
1905
10
283
11
2.4
10
562.3
98
35
9.35
27
7.32
17600
15
15.5
7.67
0.93
Henry's
(atm-
mVmol)
0
0
0.00518
0
0.0019
2.72
0.00616
0
0
0.00002
0
0.000147
0.000197
0
0
0.00002
0.0115
0.00001
0.000526
0.000132
3.0e-14
0.00002
0
0
0
Molecular
Weight
162.18
221
106
108
147
107
120.19
122
197.5
120
365.95
236.5
86
96
225.28
195
120
120.15
161
141
479.02
123
152.15
152.71
168
D-18
-------
Table 2
CAS
Number
7429905
7439921
7439965
7439976
7440020
7440224
7440280
7440360
7440382
7440393
7440417
7440439
7440473
7440484
7440508
7440622
7440666
7664417
7723140
7782492
N010
N020
N040
N050
N078
N090
N096
N100
N420
N450
: Inorganic Chemicals
Chemical
Aluminum (fume or dust)
Lead
Manganese
Mercury
Nickel
Silver
Thallium
Antimony
Arsenic
Barium
Beryllium
Cadmium
Chromium
Cobalt
Copper
Vanadium (fume or dust)
Zinc (fume or dust)
Ammonia
Phosphorus (yellow or white)
Selenium
Antimony compounds
Arsenic compounds
Barium compounds
Beryllium compounds
Cadmium compounds
Chromium compounds
Cobalt compounds
Copper compounds
Lead compounds
Manganese compounds
Air Decay
(h-1)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Koc
(mL/g)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
H2O Decay
(hr1)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
LOGKow Kd
(L/kg)
0 4
0 582
0 5
0 4084
0 27
0 539
0
0 9
0 38
0 31
0 170
0 32
0 344
0 10
0 147
0 68
0 31
-2
0
0 22
0 9
0 38
0 31
0 170
0 32
0 344
0 10
0 147
0 582
0 5
Water
Solubility
(mg/L)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10000
0
0
899000
3.3
0
0
0
0
0
0
0
0
10000
0
0
POTW
Partition
(Removal)
66.39
63.48
38.85
68.57
38.28
66.47
53.55
31.51
48.57
69.02
37.44
68.15
76.4
32.06
72.47
31.81
66.15
59.9
59.8
43.66
31.51
48.57
69.02
37.44
68.15
76.4
32.06
72.47
63.48
38.85
POTW
Partition
(Sludge)
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
POTW
Partition
(Volat)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
POTW
Partition
(Biod)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Incinerator
ORE
91.6
99
97.5
97.3
88.5
99
99.9
99.9
99.8
97.5
97.3
88.5
99
99.9
91.6
BCF Henry's
(L/kg) (atm-
mVmol)
79
1250
0
40000 0.0085
250
25
15
0.25
17
0
0
6000
4000
4425
14000
0
12000
0 0.00002
0
2000
0.25
17
0
0
6000
4000
4425
14000
1250
0
Molecular
Weight
26.98
207.19
54.93
200.59
58.71
107.87
204.37
121.75
74.9
137.34
9.01
112.4
52
58.93
63.55
50.94
65.38
17.03
30.97
78.96
121.75
74.9
137.34
9.01
112.4
52
58.93
63.55
207.19
54.93
D-19
-------
Table 2: Inorganic Chemicals
CAS Chemical
Number
N458
N495
N725
N740
N760
N982
Mercury compounds
Nickel compounds
Selenium compounds
Silver compounds
Thallium compounds
Zinc compounds
Air Decay
(hr1)
Koc
(mL/g)
H2O Decay
(hr1)
LOGKow Kd Water POTW POTW
(L/kg) Solubility Partition Partition
(mg/L) (Removal) (Sludge)
4084
27
68.57
38.28
100
66.47
53.55
66.15
100
100
0
100
100
100
POTW
Partition
(Volat)
POTW
Partition
(Biod)
Incinerator BCF
ORE
99
99.8
99.9
(L/kg)
Henry's
(atm-
mVmol)
0.0085
Molecular
Weight
200.59
58.71
78.96
107.87
204.37
65.38
Table 3
CAS
Number
74908
85687
12427382
Chemicals Missing POTW Removal Efficiencies
Chemical
Hydrogen cyanide
Butyl benzyl phthalate
Maneb
Air Decay
(hr-1)
0.00017823
0.063538492
Koc
(mL/g)
17.4
17000
550
H2O Decay
(hr1)
0.00059596
0.016503504
LOGKow
-0.25
4.91
0.62
Kd Water
(L/kg) Solubility
(mg/L)
1000000
2.69
6
POTW
Partition
(Removal)
71.98
96.76
71.98
POTW Partition
(Sludge)
1.64
43.42
1.64
POTW
Partition
(Volat)
1.84
0.1
1.84
POTW
Partition
(Biod)
96.63
56.48
96.63
Incinerator
ORE
0
99
99
BCF
(L/kg)
0.38
663
Henry's
(atm-
mVmol)
0.00013
3
0
0
Molecular
Weight
27
312
265.3
Table 4: Chemicals Missing Some Physicochemical and Removal Efficiencies Data
CAS
Number
N084
N106
Chemical
Chlorophenols
Cyanide compounds
Air Decay Koc H2O Decay
(h-1) (mL/g) (hr1)
73
LOGKow Kd Water
(L/kg) Solubility
(mg/L)
2.18 28500
10000000
POTW
Partition
(Removal)
72.87
POTW
Partition
(Sludge)
6.53
POTW
Partition
(Volat)
1.86
POTW
Partition
(Biod)
91.6
Incinerator
ORE
99
BCF Henry's
(L/kg) (atm-
mVmol)
0.00001
0.000122
Molecular
Weight
128.56
D-20
-------
Table 5
CAS
Number
10034932
10049044
123677
1313275
1314201
1332214
1344281
156627
20816120
302012
6484522
74456
7550450
7647010
7664382
7664393
7664939
7697372
7782505
7783064
8001589
81812
N230
N575
Nonel
Chemicals Missing Significant Amounts of Data
Chemical Air Decay Koc H2O Decay
(hr1) (mL/g) (hr1)
Hydrazine sulfate
Chlorine dioxide
Paraldehyde
Molybdenum trioxide
Thorium dioxide
Asbestos (friable)
Aluminum oxide (fibrous forms)
Calcium cyanamide 0.119134672 8.53 0.002578673
Osmium tetroxide
Hydrazine 0.57642561 4.28 0.016503504
Ammonium nitrate (solution)
Chlorodrfluoromethane (HCFC-22)
Titanium tetrachloride
Hydrochloric acid
Phosphoric acid 0.38
Hydrogen fluoride
Sulfuric acid
Nitric acid
Chlorine
Hydrogen sulfide
Creosote, coal tar
Warfarin and salts
Glycol Ethers
Polybrominated Biphenyls (PBBs) 0.06 37535 0.06
Ethylenebisdithiocarbamic acid, salts and
esters
LOGKow Kd Water POTW POTW
(L/kg) Solubility Partition Partition
(mg/L) (Removal) (Sludge)
34150
125000
490
0
0.98
-0.82 0
57000
-1.37 1000000
1183000
-0.44 10000000
10000000
10000000
9460
4132
0
7.8 0.02 92 24
POTW POTW Incinerator BCF Henry's Molecular
Partition Partition DRE (L/kg) (aim- Weight
(Volat) (Biod) nrVmol)
130.13
67.45
99 132.16
143.95
264.05
554.22
102
80.11
254.1
0.02 32
80.04
99 86.47
189.73
36.46
98
20.01
98.08
63.01
70.9
34.08
99
308.32
10 66 99 18200 628
D-21
-------
Appendix E.
Considerations for Including Underground Injection in the TRI Risk-Related Chronic Human
Health Indicator
E-l
-------
Considerations for Including Underground Injection in the TRI Risk-Related Chronic Human
Health Indicator
1. Background Information on Underground Injection
Underground injection refers to the placement of fluids into permeable rock strata in the subsurface
environment using wells. Disposal of industrial wastes through the use of underground injection began in the
1930's. This practice is based on simple hydrogeological principles and has been considered a useful method
of isolating wastes from the accessible environment by placing them into deep formations where they will
remain for millions of years.
EPA classifies five types of underground injection wells. These are:
Classification
Definition3
1992 Inventory4
Class I
wells that inject municipal or
industrial waste water
(including hazardous waste)
below the lowermost
underground sources of
drinking water (USDW)5
517 active wells (170
hazardous)
Class II
wells that inject fluids related
to oil and gas production,
including saltwater disposal,
enhanced oil recovery and
liquid hydrocarbon storage
177,047 active wells
Class III
wells that inject fluids for the
extraction of minerals
35,668 active wells
Class IV
wells that inject hazardous
waste into or above a USDW
(these wells have been
banned)
409 abandoned wells
Definitions taken from U.S. EPA Fact Sheet: Underground Injection Control, Office of Drinking Water.
Underground Injection Control Program, Injection Well Inventory, 1992, Office of Groundwater and Drinking Water.
A USDW is defined as an aquifer that is currently serving as a public drinking water supply, or those that have the
potential to serve as a public drinking water supply, and have less than 10,000 mg/L total dissolved solids.
E-2
-------
Classification
Class V
Definition6
wells that do not fit into any
of the above categories,
including industrial dry wells
and aquifer remediation wells
1992 Inventory7
190,443 active wells
The Underground Injection Control (UIC) program was established in 1974 to protect USDWs from
contamination due to underground injection practices and is administered under the Safe Drinking Water Act
(SDWA). Many types of underground injection, however, are also defined as a form of hazardous waste land
disposal and thus are subject to the land disposal restrictions imposed by the Hazardous and Solid Waste
Amendments of 1984 (HSWA). The HSWA banned all injections into Class I Hazardous Waste (Class 1H)
wells. However, EPA may allow injections to continue if it determines that the prohibition is not required to
protect human heath and the environment.
Pursuant to HSWA requirements, in 1985 EPA conducted an inventory of Class I facilities and summarized
their results in the Report to Congress on Underground Injection8. In 1986, EPA evaluated reported failures
and incidents of noncompliance using data gathered in Report to Congress and studies conducted by
Engineering Enterprises9, and the Underground Injection Practices Council (UIPC), an independent coalition
of industry, government, and consulting professionals. From these reports, EPA concluded that "most USDWs
are adequately separated from injection zones and that contamination of USDWs from injection operations is
insignificant."10 When contamination incidents did occur, the problems were the result of improper well design
and construction, or poor operation standards and/or monitoring requirements. EPA believes that these failures
would not have occurred under better management standards. To further protect USDW from potential
underground injection failures, in July of 1988 EPA promulgated more stringent technical requirements for
Class 1H wells. These regulations are published in 40 CFR parts 124, 144, 145, 146, and 148, and are
summarized below.
Most of the 1988 regulations stipulate safe practices for operating Class 1H wells that will prevent
contamination of USDWs. Before a Class 1H well can begin operations, however, the operator must prove
to EPA that the inj ection operations will not endanger human health and the environment by submitting a "no-
Definitions taken from U.S. EPA Fact Sheet: Underground Injection Control, Office of Drinking Water.
Underground Injection Control Program, Injection Well Inventory, 1992, Office of Groundwater and Drinking Water.
8U.S. EPA 1985. Report to Congress on Injection of Hazardous Waste. Office of Drinking Water. EPA 570/9-85-003.
Q
Class I Hazardous Waste Well Failure Study Prepared for U.S. Environmental Protection Agency. Prepared by
Engineering Enterprises, Inc., Geraghty & Miller, Inc., and Ken E. Davis Associates, September, 1986.
U.S. EPA, Office of Drinking Water (1986). Class I Hazardous Waste Injection Wells Evaluation of Non-compliance
Incidents.
E-3
-------
migration" petition demonstrating that the waste will not migrate from the injection zone for as long as it
remains hazardous. Well operators that do not submit petitions must either treat to remove the banned
substances or cease injection of the waste. The "no-migration" petitions are comprehensive, typically several
volumes long and containing thousands of pages of technical data. Petitions are required to address every
technical aspect of well siting, construction, operation, and a detailed analysis of the injected waste streams.
EPA has established a rigorous Class 1H petition review process; approximately 2000 hours are spent on each
petition review. Prior to the approval of any petition, EPA reviews the construction, operation, compliance
history, and closure plans for the well. In addition, they evaluate the chemical compatibility of the waste with
the materials of the well construction, and the injection and confining zone rocks and fluids. Information for
the Area of Review (AOR) is studied to ensure that no migration could occur through unplugged or improperly
completed wells which penetrate the confining zone.
The Class 1H operating requirements were designed to control underground inj ection contamination pathways.
The following summary of the technical requirements has been taken directly from the EPA's Office of Ground
Water and Drinking Water publication, Analysis of the Effects of EPA Restriction on the Deep Injection of
Hazardous Waste11.
The controls to prevent well failure include:
• The well materials must be compatible with wastes they are likely to contact and operators are required
to conduct corrosion monitoring.
• The wells must be adequately cased and cemented to protect USDWs and isolate the injection zone.
• The long string casing, inj ection tubing, and annular seal must be pressure-tested at least annually, and
whenever there is a well workover. The bottom-hole cement must be tested annually by a radioactive
tracer survey (RTS). Also, a test for fluid movement along the bore hole must be conducted at least
once every five years using a noise, temperature, or other EPA-approved logging method. Finally, for
certain Class I wells, casing inspection logs must be maintained. These logs are predictive tools to
assess developing weaknesses in the well's casing.
• The operator must install and use continuous recording devices to monitor the waste inj ection pressure,
flow rate and pressure. He must also install and use an automatic alarm and shut-down system designed
to alert the operator and shut-in the well when pressures, flow rates, or other parameters exceed the
allowable limits.
• If loss of mechanical integrity is found during an automatic shutdown or during routine MIT, the
operator must notify the EPA, cease injecting fluids, and preform the well workover and remediation
plan specified by the director.
U. S. EPA 1991. Analysis of the Effects of EPA Restrictions on the Deep Injection of Hazardous Waste. Office of Ground
Water and Drinking Water. EPA 570/9-91-031.
E-4
-------
Controls to prevent fluid migration up improperly plugged wells that penetrate the confining zone include:
•D The operator must identify all wells within a two-mile radius of the well bore. In some cases a larger
area of review (AOR) may be required if pressure analysis shows that the injection well has a greater
radius of influence.
•D All wells on the AOR must be examined to determine whether they are adequately completed or
plugged, or that there is no potential for fluid movement.
•D A description of each well and any records of its plugging or completion must be submitted to EPA.
A remediation plan must be submitted for wells that EPA determines are improperly plugged,
completed, or abandoned, or for which plugging or completion information is inadequate. The plan
must consist of steps or modifications that will be taken to ensure that fluids will not move up the
wells. The plan is be a condition of the operating permit.
Controls to prevent fluid migration through faults or fractured confining strata include:
• Wells must be completed such that the injection zone which receives the waste is confined above and
below by an impermeable confining zone.
• Injection pressure must be controlled so that new fractures are not created or propagated in the
injection zone or the confining strata.
• The confining zone must be laterally continuous and free of faults and transmissive fractures.
• The waste must be chemically compatible with the confining zone, so that dissolution of the confining
zone rock does not allow waste to migrate out of the injection zone.
•D The operator must conduct an annual pressure transient test to measure any changes in reservoir
characteristics and the pressure increase in the reservoir over time.
Controls to prevent lateral displacement of fluids include:
• The injection zone must have sufficient permeability, porosity, thickness, and areal extent to prevent
fluid movement into USDWs.
• Information must be provided by the operator on faults, the continuity of inj ection and confining zones,
and the proximity of USDWs to the injection well.
2. Human Health Risk Analysis
The fundamental problem with analyzing the human health risks from current underground injection practices
is that well-maintained and well-operated facilities in theory pose little or no human health risks since the
E-5
-------
potential for exposure is removed. In fact, a letter from the UIPC urged EPA not to consider injection into
deep wells as a "release" to the environment for this reason12. In fact, there are only a few documented cases
of well failures where underground sources of drinking water have been contaminated. For example, EPA and
state regulatory agencies have identified two cases where injected wastes contaminated USDWs, and one case
where an injection well was suspected of causing contamination of an USDW. All three cases occurred prior
to the implementation of a State or Federal UIC program. EPA has also identified eight cases where leakage
from Class 1H wells entered non-USDW formations and two cases of surface contamination due to blowouts.
Both cases of known USDW contamination from Class 1H injection wells occurred prior to the existence of
the UIC program. Both wells failed due to the same problem; they were constructed without a tubing and
packer and without a surface casing set to protect the area's USDWs. Corrosion of the long string casing (the
only layer of protection for these wells) allowed the unobserved leakage of wastes into USDWs. The UIC
regulations currently in effect would never have allowed this method of completion for Class 1H wells. As was
stated above, UIC regulations require three redundant layers of protection: a surface casing set and cemented
through all USDWs, a cemented long-string casing, and a tubing with a packer (or an equivalent). These three
levels of protection and the requirement for continuous annulus pressure (mechanical integrity) monitoring
would make these cases of contamination impossible today.
In another incident, Class 1H injection wells operated by Hammermill Paper were suspected as the cause of
USDW contamination near Erie, PA in 1972. It was suspected, but never proven, that the increase in injection
zone pressure attributable to the Hammermill wells caused injected waste or formation fluid to migrate up an
unplugged well into an USDW, five miles form the injection site. The current UIC regulations require that the
pressure effects of an injection well be thoroughly examined. Also, in an area where injection pressures are
found to be sufficient to cause migration to an USDW, the operator is required to identify and evaluate all
artificial penetrations of the confining zone. Furthermore, the Land Disposal Restrictions regulations require
a detailed analysis of the fate and transport of the injected waste, and an evaluation of its potential for
confinement in the injection zone for 10,000 years. Given the relatively shallow injection zone of the
Hammermill wells, it is highly unlikely that the petitions for these wells would have been approved under the
current UIC program.
Hazardous waste leakage out of the injection zone into non-USDWs also occurred in the past. Eight facilities
between 1975 and 1984 reported such incidents. Most of these failures occurred prior to the implementation
of UIC programs and were relatively minor leaks in the area immediately adjacent to the well bore. All
incidents were caused by tubing and casing corrosion. The most notable of these cases involved the unobserved
deterioration of the long-string casing in wells without packers at the Chemical Waste Management site in
Vickery, Ohio in 1983. This type of failure is easily detected with continuous annulus pressure monitoring.
However, the Chem Waste wells were designed in such a manner that it was not possible to conduct this type
of continuous monitoring. Current UIC regulations require either a packer or a system that allows comparable
protection and a capability for continuous monitoring of mechanical integrity. In all eight cases where leakage
into non-permitted zones occurred, the current UIC program's construction, monitoring, and MIT requirements
would have either prevented the failure or detected its occupance in time to prevent significant leakage.
Letter from L. Wilcher to R. Thomas Segall, President of Underground Injection Practices Council, September 30,1991.
E-6
-------
In addition, there have been two cases of well blowouts which resulted in soil contamination at the surface.
Both of these cases were caused by the buildup of CO, gas that was generated in the injection zone due to the
incompatibility of the inj ected waste with the formation. The two blowouts occurred before the implementation
of a UIC program in the states where the incidents occurred. As was stated previously, current UIC regulations
require that an operator demonstrate the compatibility of the waste with the materials of well construction and
with the injection formation. The regulations also require the operator to demonstrate the capability for
emergency shut-in in case of well failure or in response to conditions such as those encountered in these two
examples.
An analysis of potential health risks from the failure of a Class 1H injection well would have to involve a
calculation of both the probability of a failure event occurring and the level of exposure should the failure
occur. As has been illustrated from an explanation of past well failures, the probability for such events to occur
while the Class 1H injection facilities are under the management of an UIC program are extremely small. In
fact, the UIC program controls are so protective, that if the program is operating properly, these risks are most
certainly negligible. However, because some TRI wastes are not regulated under RCRA as hazardous wastes,
some TRI facilities that release waste fluids through underground injection are not Class 1H. In addition, some
TRI facilities may be operating underground injection wells that are classified as Class V. Thus, these "RCRA-
non-Haz Waste" TRI facilities as well as any TRI Class V wells are not subject to the stringent UIC
requirements outlined above and may pose some risk of human exposure due to failure.
3. Evaluating Underground Injection in Indicator
The current Indicators model tracks only pounds of releases to underground inj ection. Proj ect staff is currently
investigating other possibilities for including these releases in the Indicator. One possibility is to include the
releases only in the version of the computer algorithm that multiples the pounds released times the toxicity
weighting factor for the chemical. This would track changes in underground injection practices over time.
However, the interpretation of such an Indicator would have to be considered carefully. If in fact underground
injection represents a more safe way of handling toxic chemicals than other releases, then an increase in a
pounds-times-toxicity weight Indicator may actually represent a decrease in overall health and environmental
impacts, if toxic chemicals were being moved to underground injection from media with higher potential for
impacts.
Another possibility would be to try to include exposure potential for underground injection in the Indicator.
Beginning with the 1996 reporting year, facilities must report whether releases to underground injection are
placed in Class I facilities or in Class II-V facilities. Some modeling has been performed for Class I
underground injection failures for different geographical settings and for different failure scenarios where a
ratio between the injected concentration and the concentration in the drinking water aquifer were obtained.
These ratios could be applied to the TRI releases to Class I facilities to estimate aquifer concentrations, and
subsequently surrogate doses through drinking water. The probability of failure could be estimated from the
failure rates reported in the UIPC report and a consideration of current practices. However, exposure potential
for other types of facilities would remain unknown.
E-7
-------
Project staff will obtain additional updated information regarding underground injection. With new
information, additional alternatives will be developed and evaluated for including underground injection in the
Indicator.
E-8
-------
Appendix F
Waste Volumes by Industry
F-l
-------
Number of Landfills by Amount of Waste Received in 1984
Waste Type
Municipal Solid
Waste
Industrial
Waste
Demolition
Waste
Other Waste
Survey
Response
Rate
85%
82%
83%
85%
Quantity of Waste Received
<30,000 cu yds
(<30,000 tons/day)
5,309
(67%)
2,289
(79%)
1,608
(75%)
790
(93%)
30,000-600,000 cu yds
(30-50 tons/day)
2,211
(28%)
523
(18%)
468
(22%)
51
(6%)
>600,000 cu yds
(>500 tons/day)
408
(5%)
72
(2.5%)
78
(3.6%)
11
(1.3%)
Total Landfills
Per Waste
Type*
7,925
(100%)
2,884
(100%)
2,154
(100%)
852
(100%)
Source: U.S. EPA. 1988. Report to Congress: Solid Waste Disposal in the United States, Volume 1, Draft Final (Revised), April 15, 1988.
* = Percentages may not total 100 percent due to rounding.
F-2
-------
Number of Industrial Establishments with Landfills by Annual Waste Quantity Disposed in Them in 1985
Industry Type
Organic Chemicals
Primary Iron and Steel
Fertilizer & Agricultural
Chemicals
Electrical Power
Generation
Plastics and Resins
Manufacturing
Inorganic Chemicals
Stone, Clay, Glass, &
Concrete
Pulp & Paper
Primary Non-ferrous
Metals
Food and Kindred
Products
Water Treatment
Petroleum Refining
Rubber and Misc.
Products
Transportation
Equipment
Selected Chem. and
Allied Products
Textile Manufacturing
Leather and Leather
Products
Total"
Number of Establishments by Annual Quantity of
Waste Disposed of in Landfills in 1985
(thousand tons)
Less
than 0.5
2
69
25
23
18
30
873
26
32
127
33
21
2
37
6
12
8
1,344
0.5-5
4
55
2
13
6
31
129
14
35
22
33
9
22
8
6
6
0
396
5.1-20
4
29
0
6
2
10
85
83
7
17
0
8
2
7
6
7
1
274
21-100
2
13
0
23
2
9
46
44
13
12
3
1
10
7
1
0
0
181
101-
1,000
1
9
2
57
0
0
10
12
2
11
0
1
0
1
0
0
0
105
More than
1,000
0
0
1
3
0
1
0
0
0
0
0
0
0
0
0
39
0
5
Total Establishments
Per Industry Type"
13
176
30
126
28
81
1,143
179
90
189
69
40
36
54
19
25
9
2,305b
Source: U.S. EPA. 1988. Report to Congress: Solid Waste Disposal in the United States, Volume 1, Draft Final
(Revised), April 15, 1988.
a = These are the correct totals. Table entries may not add to their respective totals due to rounding.
b = Overall response rate for this table is 99.3%.
F-3
-------
Number of Industrial Establishments with Surface Impoundments by
Industry and Waste Quantity Disposed in Them in 1985
Industry Type
Organic Chemicals
Primary Iron and Steel
Fertilizer & Agricultural
Chemicals
Electrical Power
Generation
Plastics and Resins
Manufacturing
Inorganic Chemicals
Stone, Clay, Glass, &
Concrete
Pulp & Paper
Primary Non-ferrous
Metals
Food and Kindred
Products
Water Treatment
Petroleum Refining
Rubber and Misc.
Products
Transportation
Equipment
Selected Chem. and
Allied Products
Textile Manufacturing
Leather and Leather
Products
Total"
Number of Establishments by Waste Quantity Disposed of
in Them in 1985 (tons)
Less
than 3
1
1
3
5
3
3
42
9
6
13
0
30
41
7
2
1
0
168
3-9
2
1
1
3
2
1
106
23
5
30
0
4
1
0
0
16
0
197
10-99
2
37
37
29
4
25
419
0
38
105
34
60
22
19
2
39
3
877
100-
499
12
18
9
29
6
34
594
29
18
215
34
12
1
29
3
1
3
1,049
500-
999
1
3
3
7
1
14
194
3
2
54
5
10
10
2
4
11
1
325
1,000-
4,999
11
24
6
20
8
83
217
19
51
353
17
70
1
9
4
21
0
916
5,000-
10,000
13
10
3
7
2
32
76
15
10
129
32
8
3
8
5
16
1
369
Greater
than
10,000
45
89
47
207
50
145
290
201
55
799
207
117
46
44
33
283
18
2,677
Total
Establish-
ments Per
Industry
Type"
86
182
110
306
77
340
1,939
301
186
1,700
329
310
126
118
52
388
27
6,578b
Source: U.S. EPA. 1988. Report to Congress: Solid Waste Disposal in the United States, Volume 1,
Draft Final (Revised), April 15, 1988.
a = These are the correct totals. Table entries may not add to their respective totals due to
rounding.
b = Overall response rate for this table is 98.5%.
F-4
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Number of Establishments with Waste Piles by Industry Type
and Waste Quantity Disposed of in Them in 1985
Industry Type
Organic Chemicals
Primary Iron and Steel
Fertilizer & Agricultural
Chemicals
Electrical Power
Generation
Plastics and Resins
Manufacturing
Inorganic Chemicals
Stone, Clay, Glass, &
Concrete
Pulp & Paper
Primary Non-ferrous
Metals
Food and Kindred
Products
Water Treatment
Petroleum Refining
Rubber and Misc.
Products
Transportation
Equipment
Selected Chem. and
Allied Products
Textile Manufacturing
Leather and Leather
Products
Total"
Number of Establishments According to Amount of Waste Disposed in Them (thousand tons)
Less
than 0.5
21
202
19
77
19
30
1,549
51
198
297
41
112
76
213
33
90
37
3,064
0.5-5
15
74
2
8
1
12
184
63
41
28
1
21
21
70
6
10
3
558
5.1-20
2
24
4
0
2
4
131
38
14
4
0
2
1
15
0
0
0
242
21-100
0
14
1
8
0
2
57
7
4
11
0
0
0
2
0
0
0
106
101-
1,000
0
2
3
1
0
7
21
2
3
0
0
0
0
1
0
0
0
40
More than
1,000
0
2
1
0
1
4
0
0
1
0
0
0
0
0
0
0
0
9
Total Establishments
Per Industry Type"
37
317
30
93
23
60
1,942
162
261
340
42
135
98
300
39
99
39
4,0 19b
Source: U.S. EPA. 1988. Report to Congress: Solid Waste Disposal in the United States, Volume 1, Draft Final
(Revised), April 15, 1988.
a = These are the correct totals. Table entries may not add to their respective totals due to rounding.
b = Overall response rate for this table is 99.3%.
F-5
-------
Appendix G
Options for Indicator Computation and Normalization
G-l
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I. Options for Indicator Computation
The TRI indicator will be calculated by combining the individual scores of the TRI chemical-facility-
media components. Each component's value is related to a chemical's risk to either human health or the
environment (depending on the indicator). The value is calculated based on measures of the volume of release
from a facility, the chemical's toxicity, and the potential exposed population for the media of release.
This appendix discusses the two leading methodologies considered for calculating the TRI indicator.
The method of calculation will influence the ways we can adjust the indicator and how the indicator will change
in response to the adjustments as facilities and chemicals are added over time.
Simple Sum of the Component Scores:
where:
/ = TRI indicator
S = facility-chemical-medium-specific subindicator
In this method, each component score makes a contribution proportional to its size. Simply, it is the
total "risk" resulting from all chemical-facility-media releases. It should be noted that subscores for particular
chemicals, industries, and regions can also be calculated for indicator diagnostics.
Simple Sum Normalized to a Base Year:
...
/ =D - present year .
( S, +US2 +US3 +D... +USn )
base year
Like the simple sum method, this method represents each component score proportionately. Its
primary advantage is that it is a dimensionless ratio that tracks progress over time and continuously looks back
at the beginning of the indicator record. A score of 60 indicates that the overall chemical-facility-media risk
has been reduced by 40 percent since the TRI indicator began. Hence, each individual score has meaning, as
does the change from year to year.
G-2
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Other Methods of Calculation
We considered alternative means of calculating the indicator. Some of these included the arithmetic
mean of the component scores, the geometric mean of the scores, and the least-square difference of the scores.
Although each of these methods generates a score that will fluctuate as the individual components of the risk,
the methods do not produce readily interpretable results.
For the greatest sensitivity in the actual indicator score, as well as for the greatest ease in calculation
and interpretation, we recommend that the chemical-facility-media scores simply be added and then adjusted
to a manageable level.
II. Normalizing the Indicator
This section discusses options considered for modifying the indicator to accommodate the addition of
SIC codes and chemicals for TRI reporting purposes. We discuss how the failure to report chemical release
data as well as data errors can affect the calculation of the indicator. We also present an example to illustrate
both the necessity of designing a method of normalization and the implications of the methods presented here.
As discussed previously, the indicator should be designed to accommodate an increase in the number
of components of the TRI. This increase can occur through any of three mechanisms: an addition of chemicals
to the TRI list, an increase in the number of facilities by enhancing the SIC code list, and an increase in facility
compliance with existing reporting requirements. Each of these scenarios enhances the accuracy of the report
because they supply missing information. However, this addition changes the scope of the indicator (from a
small subset to a larger subset), thereby limiting the effectiveness of comparison between current and past
values.
The addition to or deletion of chemicals from the TRI roster will occur as EPA responds to petitions
or initiates its own action through the chemical listing or delisting process. The deletion of chemicals will
presumably have a minor effect since such chemicals would be deleted due to their low risk; by definition these
chemicals will make only a minimal contribution to the indicator. Deletion will most likely occur in batches
every few years. The addition of SIC codes will likely follow investigations of the TRI chemicals revealing
other industries that emit the listed chemicals. Compliance could also increase in the future. In 1989, the
Office of Toxic Substances studied compliance with TRI reporting requirements. The study found that the
compliance rate was 81.7 percent in the first year of reporting. Follow up studies have not been done to
determine the improvement in compliance with Section 313. However, the OTS study stated that under full
compliance, the estimated number of respondents would be over 29,000. In the last two years of reporting,
the number of reporting facilities has not approached that figure, despite a lowering of reporting thresholds.
The fundamental problem in maintaining a single, continuous indicator is that there is no way to
differentiate between fluctuations due to changes in actual environmental risk and those due to changes in the
chemical or facility roster. Therefore, to maintain the integrity of the indicator when chemicals are added to
the roster, each addition to the indicator should be accompanied by some kind of adjustment. Methodologies
G-3
-------
for accommodating the addition of chemical-facility-media components are presented below along with
discussions of their impact on the accuracy of the indicator. First, we present a hypothetical example of
indicator values over a five year period and then articulate a number of options for normalizing the index.
Example:
The calculation of the indicator begins in 1988, and we select the Simple Sum method of calculating
the indicator. For the first 5 years the indicator scores are as follows:
Year
1988
1989
1990
1991
1992
Indicator Score
1,000
950
850
800
775
In 1993, the Agency adds another 200 chemicals to the TRI list as well as five SIC codes. The 1993 score of
the original set of TRI chemicals and SIC codes is 750, meaning that the risks associated with those chemicals
and facilities have decreased. The score for the additional set of chemicals and facilities is 500.
Do Nothing
The Do-Nothing scenario is important to examine since the benefits of lost continuity may outweigh
the disadvantages and the effort required to work around them. For this method, the score will rise when
components are added and will no longer describe the environmental progress as compared to the previous
roster. In our example, the indicator score will read 775 in 1992 and 1,250 in 1993. It will be impossible to
recalculate the previous years' scores with the new chemicals because release data will not be available. Thus,
information on progress since the initial roster will be lost.
The Do-Nothing scenario could be viewed as a more accurate representation of the "complete picture"
of environmental risk. If, for example, the indicator score for the universe of all chemicals and all facilities
were actually 4,000, and this initial TRI setup provides a score of 1,000, then the subsequent addition of
components to the TRI will fill in the additional 3,000 points for which no information exists. Yet for the
public to understand the severity of a change, increases in the indicator score from new chemicals ought to
occur on the same scale as that of the original set. As discussed earlier, the public will perceive the indicator
score presented with the first set of TRI chemicals and facilities as representing the risk associated with all
chemicals and facilities. The public will believe that the new score of 1250 means that the risks posed to them
have risen by 475 points; actually, the risk to them has not increased at all, they are just better represented.
An increase in the number of components should not actually increase risk but should redistribute the individual
contributions to the total risk.
G-4
-------
Creation of a Separate Indicator
Chemicals could be added to the TRI roster one or two at a time each year or in a large number once
every five years. If the latter occurs exclusively, we could establish an indicator consisting solely of the new
chemicals and allow the scores of the old indicator to continue as before. In our example, the TRI indicator
would be reported as two scores: in 1993 it would be 750 for the original set of TRI chemicals and facilities
and 500 for the new set of chemicals and facilities. This approach has two advantages. First, this system could
accurately track the progress of the original roster as well as the new roster. Second, the indicator for each
roster could be compared and the program could establish priority for alleviating environmental problems
associated with the new or old list.
The primary disadvantage of two indicators is the loss of a single instrument. Chemicals and SIC codes
will be added to the TRI more than once, and each time another four indices (human health and environmental
risk; chronic and acute effects) will be needed. Each of these indices is also compared at regional, state and
local levels. Maintaining a number of indicators will create public confusion, as people try to keep track of
each separate indicator change from the previous year. A second disadvantage follows from the Do-Nothing
scenario: if people add these scores together to get the "total" score, they will perceive an increase in overall
risk. Finally, if TRI chemicals are added continuously in small amounts, this method will be extraordinarily
difficult to implement as new indices are created each year.
Ratio Adjustment
The ratio adjustment method is used with the Dow Jones Industrial Average, the Producer Price Index,
the Consumer Price Index, and the New York Stock Exchange Composite Index. The underlying components
of each of these indices are updated periodically to reflect fundamental shifts in what is being measured. For
example, this year the Dow substituted three service sector stocks for three industrial stocks to reflect the U. S.
economy's shift toward the service sector. The Producer and Consumer Price indices revise their basket of
goods decennially to reflect the caprice of consumer taste. The NYSE Composite Index, which encompasses
every stock on the New York Stock Exchange, is revised every time companies start up, merge, or fail.
The adjustment is straightforward. On the first day that the revised components are employed, the
index is calculated twice, once based on the old components and again based on the revised components.
Thereafter, the ratio between these two index values is used to adjust the index as it is calculated from the
revised components:
T _r\r . old, last day
revised components T
new, first day
G-5
-------
In our example, the old system yielded a score of 750 and the new system yields a score of 1,250. To
scale down the new score to maintain continuity, we multiply the new score by (750/1,250) = 0.6. All
subsequent scores (1994, 1995, and so on) will also be calculated in the same manner and then multiplied by
0.6, until another addition requires the determination of another multiplication factor.
One disadvantage of this method is the loss of information concerning the original set of chemicals and
facilities in the presentation of one indicator that integrates all scores. Even if the indicator publishes the scores
associated with each set of chemicals, the scale will have changed, prohibiting direct comparison. (Compare
this to the method where original and supplemental indices are both tracked.)
Another disadvantage is the misrepresentation of the behavior of the new set of chemicals and facilities.
The TRI indicator is distinct from the Dow in a way that affects the applicability of this system. The Dow uses
a few stocks to model the entire market and assumes that the behavior of these stocks reflects the general
behavior of all stocks. This implies that substitution of one stock for another in the Dow fits conceptually with
its purpose. The TRI indicator seeks to reflect the levels of risk to human health and the environment by
including a subset of the universe of all chemicals and facilities. The behavior of risks posed by all chemicals
and facilities cannot be said to match the behavior of the set of TRI chemicals and facilities. The inclusion in
TRI focuses a facility's attention upon particular chemicals and presumably results in changes of releases of
TRI chemicals by TRI facilities. By fitting the combined score of new and old TRI chemicals and facilities to
the score of the old, we inherently assume that the new have experienced reductions in risk identical to the old.
In truth, we have no way of knowing the past pattern of releases for new additions. Emissions may have not
changed at all since these chemicals have not yet been targeted by TRI; on the other hand, emissions may have
been reduced more than emissions of old TRI chemicals because the new chemicals may have already been
regulated by certain EPA programs or by states, or companies may have reduced emissions voluntarily.
Normalization to a Base Level
This method reflects the Do-Nothing approach except for taking necessary adjustments for the use of
normalization. Instead of using the score resulting from a base year, base levels could be used, defined as the
sum of the component scores at the first year that each list is added to the TRI Indicator. For example, upon
the first addition to the TRI (combining the initial roster, list 1, and the addition, list 2), the indicator could be
calculated as follows:
T _n
"
present year
( S, +0$; +D... +QS ) +D( S ni +D... +QS )
12 m first year of list \ m +U1 " first year of 'list 2
where:
S = each chemical-facility-media component score,
n = total number of TRI chemicals,
G-6
-------
m = number of TRI chemicals in the first list, and
m-n = number of chemicals added to the roster.
Following the example, the score for 1988 would be (1,000/1,000)* 100 = 100. The following scores
would be (950/1,000) = 95, (850/1,000) = 85, (800/1,000) = 80, and (775/1,000) = 77.5. In 1993, the score
would be calculated as follows:
750 +D500
1000 +D500
While this score represents an increase, it is not as drastic as using the simple sum method, and it can
be explained to the public as resulting from the addition of TRI chemicals and facilities to the indicator. This
equation can also be used to indicate relative percentages of the two different sets of chemicals and facilities
(750/1,500 = 50 for the original and 500/1,500 = 33.3 for the new). However, as with ratio adjustment, the
original set cannot be said to have improved by (77.5 - 50) = 27.5 points.
Variations on the Previous Methods
Improvements in the way in which the smaller TRI chemical universe models the larger one would lead
to more meaningful comparisons between the old and new indices. One way to improve this modeling ability
is to employ data on the new chemicals for the period predating their addition to TRI. If we had the release
data, we could calculate exactly how inaccurate the small TRI chemical universe was as a model and adjust
it accordingly. Although these data will not exist except as part of a state inventory, we could approximate
them through the correlation of releases of other chemicals. For example, if a facility reports the release of
a chemical because of its addition to the TRI, it is very likely that the chemical had been released at that level
all along. A rough approximation would be to look at changes in releases from that facility and then correlate
the release of the new chemical in back years.
Yet another possibility is to combine more than one of the above examples. For example, it may be
appropriate to maintain one "primary" indicator score while also maintaining "subscores" for each of the sets
of TRI chemicals (i.e., the original set and each additional set). The main score could be calculated using the
simple sum and normalized with the ratio adjustment each time an additional set of chemicals is added. The
subscores could be calculated for each set of TRI chemicals using the normalization to a base year; each of
these subscores could be maintained separately. In our example, after the addition of chemicals, the main
indicator score would be 750 while the subscores would be (750/1,000) = 75 and (500/500) = 100. As in the
discussion of the creation of separate indices, this combination depends upon the addition of TRI chemicals
in large groups every number of years. If routine additions occur, the main indicator could be calculated as
above and only one subscore, that of the original set of chemicals, could be maintained.
G-7
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Start Over
The last system that may be used is to announce the beginning of a new indicator. Once every 5 years
the Agency could integrate all of the additions to and deletions from TRI that had occurred since the beginning
of the previous indicator. EPA could announce that to better assess the risks to the environment posed by
chemical releases, certain chemicals have been deleted or added based upon TRI criteria and that a new
indicator, calculated in the same manner at the same scale, has begun. It is also quite possible that experience
with the indicator may suggest a new mode of calculation by the time more chemicals and facilities are ready
to be added.
G-8
-------
Appendix H
Additional Exposure Scenarios
H-l
-------
It has been suggested that the TRI Indicator be expanded to include additional exposure scenarios.
These scenarios result from either the direct exposure to TRI chemicals or exposure to an indirect effect of
the chemicals. A primary example of another direct exposure not currently incorporated into the indicator is
the deposition of airborne chemicals into other pathways, such as groundwater. The most renown examples
of indirect exposures include the greenhouse effect, acid rain, the ozone "hole," and smog.
Since each of these scenarios poses a level of risk to human health and the environment, it would seem
necessary to include them in an indicator which measures risk. However, the complexity of and uncertainty
in modelling these scenarios makes direct insertion into the Indicator extremely difficult. The following
endpoints are discussed for their potential inclusion into the TRI Indicator, the creation of a separate indicator
for the endpoint, or difficulties in accomplishing either.
Global Warming
Some of the TRI chemicals are considered "greenhouse gases." These chemicals, when released into the
atmosphere, can absorb infra-red radiation which the earth emits as it establishes radiative equilibrium with the
solar system. The potential result of this "effect" is the increase of the average temperature of the earth's
surface, an increase which could lead to higher sea levels, droughts, floods, and climate changes.
The quantification of these risks is a hotly contested topic in academic, political and industrial circles. The
temperature rise has been predicted to be anywhere between zero and eight degrees Celsius. The direction of
the climate change resulting from the accumulation of greenhouse gases can be offset by natural occurrences
such as volcanic eruptions or the appearance of El Nino, a circulating body of abnormally warm water in the
Pacific Ocean. Since the results of the buildup of greenhouse gases have not been, and quite possibly cannot
be, quantified, it is impossible to assign a greenhouse effect risk to the unit emission of a greenhouse gas. Thus
the greenhouse effect cannot effectively be incorporated into the TRI Indicator.
This is not to say that the release of greenhouse gases, and their relative threat, cannot be traced with a
separate indicator. In attempting to quantify the climate change potential associated with gaseous emissions,
greenhouse gases have been weighted relative to their capacity to absorb infra-red radiation and their half-life
in the atmosphere. These weights have been normalized to CO2, the greenhouse gas greatest in both presence
in the atmosphere and rate of addition to the atmosphere. The other major greenhouse gases are listed below:
H-2
-------
Trace Gas
Lifetime
(Years)
Global Wanning Potential
(Integration Time Horizon)
20 vrs. IQOvrs. 500 vrs.
Carbon Dioxide (120) 1 1 1
Methane 10 63 21 9
Nitrous Oxide 150 270 290 190
CFC-11* 60 4500 3500 1500
CFC-12* 130 7100 7300 4500
HCFC-22 15 4100 1500 510
CFC-113* 90 4500 4200 2100
CC14* 50 1900 1300 460
CH3CC13 6 350 100 34
CF3Br 110 5800 5800 3200
CO <1 732
* - TRI Chemical
Source: IPCC, 1990.
The emissions of greenhouse gases can be reported by their relative weight of contribution to the greenhouse
effect and reported in a simple indicator.
Acid Rain
Acid Rain results from the deposition of sulfur- and nitrogen- containing compounds, particularly sulfur dioxide
and nitrous oxides, into clouds. The sulfur and nitrogen react with the water to form sulfuric and nitric acid
which then accompany water during precipitation, leading to corrosion of structures and reductions in the pH
of soils and water. Some researchers have attributed the elimination of habitat in different parts of the world
to acid rain, particularly in areas where coal provides the primary energy source for combustion processes.
Like the greenhouse effect, it is extremely difficult to determine the effect caused by the unit emission of an
"acid rain" chemical. The amount of sulfur and nitrogen which may combine to form an acid depends upon
equilibrium concentrations in the area of concern. Although the acidity of sulfuric acid and nitric acid may be
compared directly by their respective pH at a given concentration, and although the number of sulfur or
nitrogen atoms present in a compound may determine the ability of a chemical to contribute to the creation of
these acids, site-specific conditions will determine the quantity and concentration of the acids.
Like the risks associated with global warming, the risks posed to human health and the environment have not
been quantified in terms of individual toxic risks. Some work has been done on health conditions and
H-3
-------
respiratory problems. However, most work concerning acid rain has focused on population-based economic
risks, a different perspective than the one used to determine the TRI indicator. The health effects seem to have
been precursors to determining factors such as days lost at work and other economic inputs.
Stratospheric Ozone Depletion
The depletion of the stratospheric ozone layer results from the reaction of chlorine and fluorine atoms in
chlorofluorocarbons with ozone, breaking the ozone down into diatomic oxygen and oxygenated compounds.
Since ozone absorbs incoming ultraviolet radiation, the deterioration of the ozone layer is resulting in dramatic
increases in environmental exposure to UV radiation. This high-energy end of the spectrum has been shown
to cause cataracts, suppress the immune system and induce cancer in humans. It has also been shown to
adversely affect plant and animal life. Thus the risks to humans could lie anywhere from actual health hazards
to loss of agriculture.
A major project at EPA, in conjunction with ICF, focused on determining the risks associated with CFCs and
their alternatives in order to formulate policy options. The model tracks emissions into the atmosphere, models
the reduction in the ozone layer, and calculates risks and damage associated with skin cancer, cataracts, aquatic
impacts, crop loss, immunosuppression, and even a qualitative assessment to the food chain (starting with
oceanic plankton). The model is complicated but could be used to determine risks associated with the
emissions of CFCs.
A weighting scheme has been developed to determine the effectiveness of different CFCs at depleting the
ozone layer. These weights are detailed below:
H-4
-------
Domestic Weighted
Substance 1986 Use Weight Production
(millions kg)
CFC-11* 91.3 1 91.3
CFC-12* 146.2 1 146.2
CFC-113* 71.1 0.8 56.9
CFC-114* 4.1 1 4.1
CFC-115* 4.61 0.6 2.8
* - TRI Chemicals: Chlorinated Fluorocarbons are a category in the TRI.
Source: U.S. EPA (1987)
A separate indicator could be managed for ozone depletion through the use of these weights.
Tropospheric Ozone
The creation of tropospheric (low atmosphere) ozone, one of the main constituents, results from the reaction
of a radical oxygen atom with an oxygen molecule. This maverick oxygen atom is produced when ultraviolet
radiation in sunlight breaks apart a nitrogen dioxide atom into nitrous oxide and oxygen. In normal
circumstances, the ozone will react with the nitrous oxide in order to reform the nitrogen dioxide and the
diatomic oxygen, the preferred state of being. However, the presence of volatile organic compounds (VOCs)
in the air prevent this elimination of ozone by reacting with the nitrous oxide, creating nitrogen dioxide before
the molecule can react with ozone. Thus it is the presence of both NOX and VOCs which lead to the formation
of ozone in the troposphere.
The presence of ozone in the troposphere poses human health and environmental risks since it is this level of
the atmosphere in which we live. Ozone causes respiratory ailments, particularly in the older and younger
populations, and is an eye irritant.
The difficulty with pinning down the effects of emissions of either nitrous oxides or VOCs is their dependence
upon one another for the creation and destruction of ozone. Rural and urban areas will have different impacts
from increased or decreased emissions of VOCs. Some work has been done in modelling ozone formation at
ORD, and these models can be consulted.
Particle Deposition
Particle deposition differs from the volatilization pathway currently analyzed in the TRI indicator by tracing
airborne emissions through exposure scenarios other than inhalation. Particles can land on clouds and
precipitate, entering water bodies and exposing populations through drinking water. Particle deposition can
also produce risks to wildlife through direct ingestion.
Many models have been developed at ORD to determine the exposure posed by particle deposition. The office
would need to be contacted in order to consider the exposure scenarios which these cover.
H-5
-------
Appendix I
Description of the Computer Program
1-1
-------
This appendix describes the computer algorithm and the mathematical exposure modeling used to
calculate the indicator elements. The computer algorithm used to calculate the TRI Environmental Indicators
can be thought of as a three-part process; input, exposure modeling, and element calculation. First, we
describe the fundamental data input files common to all of the element calculations. Next, we provide a step-
by-step description of how these data files are linked with mathematical models and the exposure and toxicity
weighting matrices in order to calculate the elements. The step-by-step description also delineates the
mathematical steps used to model exposure and discusses the format and content of additional data files that
are specific to the analysis of particular release pathways. A summary of the step-by-step process of
computation is provided in Appendix G. Overall computation is replicable and verifiable, since it is performed
completely within one computer program.
Programming Language and General Data Input
Before we begin to construct an algorithm for indicator calculation, we must first select a programming
language in which to implement the algorithm. We use the Statistical Analysis System (SAS). SAS is a data
management and analysis programming language widely used in government and industry. In fact, an
outstanding TRI analysis system, TRIPQUIC, uses SAS code to provide a rich set of exploratory tools. Its
flexibility and power are unsurpassed among major data management systems. The choice to use SAS allows
greater control of the input and output sequences and easily allows virtually limitless views of an indicator's
make-up.
To support the calculation of the indicators, we created or used a variety of data files.1 The program
accesses these data files to obtain model input parameters as the models are run. All of the TRI Environmental
Indicators calculations rely on three major data input files. First, the RELEASE2 file contains information on
releases for each facility-chemical combination in the TRI data base. The RELEASE file contains values for
releases to all media and is the core of the indicators calculation. Emissions data can be presented as numerical
point estimates, or, if releases are below 1,000 pounds, as an estimated range of emissions. To produce a
conservative estimate of exposure potential, we will use the upper bound of the range as our estimate of
emissions, since this value is the maximum that the facility could be emitting. Because the TRI database is
continually updated and so fluctuates over time, we will use data from the two week period each year when
EPA freezes the database for analysis. At that time all data for previous years are re-calculated in the model
to accommodate revisions in the reported information. In the input process, data will be checked for errors
and, if possible, corrected (if errors cannot be addressed, the data is flagged and the associated records are not
scored with the model). Variables essential to the Indicator calculation that are contained in the file are listed
below.
We refer to data files by a capitalized one word file name. This is only for clarity in the discussion; the actual locations
and names of files appear in footnotes.
2Text file - TRIS.PROD.CHEMICAL.FILE89. This file was created to assist in creating the TRI National report. The
entire file format is available from EPA.
1-2
-------
Variable
TRI ID
DCN
ZIPCODE
NPDES
LATITUDE
LONGITUDE
SIC
CAS
TRIRCRA
Comment
Unique facility identifier
Identification number used for
matching facility with data in
other data files
ZIP code of the facility
NPDES permit number of the
facility
Latitude for facility
Longitude for facility
SIC code of facility
CAS number of chemical
RCRA ID number of TRI
facility (if it has one)
Variable
ACTFLAG
FUGAIR
STKAIR
WATER
LAND
UI
POTW
TRANSFER
BASIS1-
BASIS5
Comment
Activity /use flags
Fugitive air emission of
chemical from the facility
(pounds per year)
Stack air emission of chemical
from the facility (pounds per
year)
Direct water discharge emission
from facility (pounds per year)
On-site land release from
facility (pounds per year)
Release from facility to
underground injection (pounds
per year)
Discharge of chemical from
facility to POTW (pounds per
year)
Transfer of chemical off-site
from facility (pounds per year)
(other than POTW discharges)
Basis/method for estimating the
quantity of release (separate
variable for each type of
release)
The ACTFLAG variable indicates how the chemical is used at the TRI facility. Although this variable
has no direct role in indicator calculation, it will be useful for performing diagnostics on the indicators.
Similarly, the method for estimating the quantity of the release is included as the variable BASIS and can be
used for performing diagnostics on the indicators.
The second fundamental input file is the BGREACH file, which contains information on the populations
and geographies of areas surrounding TRI facilities.3 The BGREACH file was inspired by the current efforts
to develop a GIS (Geographic Information System) at EPA. The file is a two-dimensional digital
representation of the United States. As seen in Figure 1, the country is divided into 1 kilometer square cells.4
For each of these cells, a variety of geographical information about the location can be stored. Storing
information in this manner allows us to access all of the relevant geographical information for each TRI facility
FBXTRIS.TRIDENT .BGREACH - This file is a SAS housed on the EPA mainframe developed for this project.
The choice of 1 kilometer is somewhat arbitrary. The size of each square can be set to any value. However, halving the
length of one side of a square quadruples the size of the file.
1-3
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by simply accessing the BGREACH cell that matches the location of the facility. This approach has significant
advantages over having to access a number of different data files to retrieve different pieces of geographical
information. Although the BGREACH file is not an exact reproduction of the geography and demographics
of the U. S., it is a reasonably good approximation for our purposes. The variables contained in the BGREACH
file are listed below.
Variable
CELLXY
POP
NEARSTAR
WELL
Comment
Cartesian location of the cell
Population in the cell
Nearest Weather Station ID
Well density in cell
Variable
FLOW
WATERPOP
FIPS
NEXTXY
Comment
Water volume (million liters
per day)
Population at intake
State-County FIPS Code
Next cell for stream
Other variables can be added to the file if necessary. To build the BGREACH file, we extracted data
from a variety of sources. Enumerated below are explanations of each variable, sources used to obtain data
on the variable, and the weaknesses of each variable.
1 . CELLXY - This value describes the relative location of the cell on the grid. This variable is the basic
identifier that is used to link the information in BGREACH file with information from the RELEASE
file and other data files. We link BGREACH to the RELEASE data by using the latitude and longitude
data of the TRI facilities. To link the location of a TRI facility to a CELLXY value, the equivalent
cartesian (x and y) distances of the TRI facility latitude and longitude are first calculated from a central
point in the continental United States (96 degrees longitude and 37 degrees latitude). After these
distances are calculated, a cell address can be directly calculated as follows:
Cellx =D(y+1600)-104 +D(jt+1600)
where
y
x
= cell address or location file,
= north/south distance (km) to center of US, and
= east/west distance (km) to center of US.
Adding 1600 (km) to the x and y distances guarantees positive values.
1-4
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Surface Water Body
The U.S. is carved into
squares 1 kilometer wide,
each referenced as an x and y
distance from a center point.
Facility locations can
be pinpointed on the
grid by converting
their longitude and
latitude to a cell
address.
The entire grid
system, containing 10
million cells, is kept
in a file, and each cell
can be directly
accessed.
Each Cell Contains Information* on:
Location Water Volume
Population Water Direction
Weather Stations Well Density
*Other variables may be added.
Figure 1. How the TRI indicator program views the United States
1-5
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2. POP - This variable represents the number of people living in the cell. Information on populations
were extracted from the Census Bureau's Block Group/EnumerationDistrict (BG/ED) file. The BG/ED
file reports population and longitude/latitude pairs for centroids of Block Groups and Enumeration
Districts.5 Each centroid was converted into a cell address (Cell^) based on the above equation.
Populations with equivalent cell addresses were summed. This exercise yielded a population number
for each inhabited square kilometer in the United States.
One problem in this approach is that the land area of rural districts can be larger than a square
kilometer. These areas are treated the same as a city block. In other words, a cell in the BGREACH
file may contain a population that is actually spread over several kilometers. One way to adjust for this
is to assume a uniform population distribution and allot populations to surrounding cells based on the
reported size of the Enumeration District. However, since we propose in our methodology to set
populations to a minimum value of 1,000, and since the population in an Enumeration District is usually
less than 1,000, uniformly distributing populations is not necessary.
3. NEARSTAR - This variable identifies the location of nearby weather stations. It contains an
identification value for the nearest weather station from the STAR (STability ARray) database. Using
this identification number, the most probable prevailing weather conditions can quickly be fetched from
a companion weather data file.
4. WELL - Variable WELL is a percentage of cell occupants who receive their drinking water from
groundwater sources. It comes from a National Well Water Association (NWWA) county level file
with counts of persons and homes either having private wells or receiving water from a utility that uses
groundwater as its source. The NWWA file is catalogued using state and county FIPS codes. To
insert these data into our BGREACH file, we first matched the FIPS codes to the Census BG/ED data.
We then matched the BG/ED data to the cell identifier (CELLXY) as described above.
5. FLOW - This variable contains the flow volume of the surface water body in the cell. We obtained
data on the continental stream network from the REACH file which is part of the Routing and
Graphical Display System (RGDS). The stream network was mapped onto the BGREACH grid system
based on longitude and latitude coordinates of stream segments in the REACH file. Since segment
lengths are often larger than our 1 km grid network, care was taken to assure consecutive segments
align within our grid. Essentially, the path of a surface water body was tracked at 1-km intervals
instead of the multiple mile intervals in REACH. This did not increase precision, however, since each
grid cell that is part of a stream segment will contain the flow properties of the segment itself in million
liters per day.
6. WATERPOP - This variable contains the size of the population served by a drinking water utility
that has an intake within the cell's boundaries. Using this variable, we are able to estimate the
population exposed to chemicals in surface water in that cell. Data on the population served by
drinking water utilities was derived from FRDS.
Block Groups and Enumeration Districts are terms used by the Census Bureau to describe very small units or blocks
within metropolitan areas and rural areas generally containing not more than 800 people.
1-6
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7. NEXTXY - This variable contains the address of the cell into which the surface water body flows
next. It is the link that allows us to follow the movement of chemical discharges through the surface
water network.
The final fundamental input data file is the TOX file. This file contains chemical-specific toxicological
and chemical properties data. These data are linked via the chemical's CAS number to the RELEASE file and
another data file.6 The variables contained in the TOX file are listed below.
Variable
CAS
WOE
QSTAR
RFD
LOAEL
NOAEL
MED
Comment
CAS number
EPA cancer WOE
category
Cancer potency
estimate (kg-
day/mg)
WOE
Reference dose
(mg/kg-day)
Lowest
Observable
Adverse Effect
Level (mg/kg-day)
No Observable
Adverse Effect
Level (mg/kg-day)
Minimum
effective dose
(mg/kg-day)
Variable
AQNOAEL
LOGKOW
SOL
AIRDECAY
WATERDECAY
KOC
POTWREMOVE
POTWVOL
POTWSLUDGE
POTWDEG
ORE
Comment
Life cycle or chronic No
Observable Adverse Effect
Level for aquatic life
Log of the octanol water
partition coefficient
Water solubility (mg/1)
Decay rate in air (hr1)
Decay rate in water (hr"1)
Soil-water partition
coefficient
POTW removal efficiency
Percent of chemical that
volatilizes at the POTW
Percent of chemical that
partitions to sludge
Percent of chemical that
degrades in the POTW
Removal efficiency for
municipal waste
incinerator
"FBXTRIS.TRIDENT.TOX.PHYSCHEM - SAS file housed on the EPA mainframe. This file will also be available in
dBase III and Lotus 1-2-3.
1-7
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Variable
LC50
AAWQC
CAWQC
Comment
Lethal
concentration, 50
percent
(concentration
lethal to 50% of
test organisms
Acute Ambient
Water Quality
criteria or
Ambient Aquatic
Life Advisory
Concentration
Chronic Ambient
Water Quality
Criteria or
Ambient Aquatic
Life Advisory
Concentration
Variable
HC
MW
BCF
Comment
Henry's Law constant
Molecular weight
Bioconcentration factor
Chapter IV of the methodology describes the meaning and the sources of information for some of these
variables. In addition, Appendix D presents the values for some of the TOX file variables for many of the TRI
chemicals. In this section, we discuss the mathematics behind modeling exposure for each of the following
exposure pathways: (1) stack and fugitive air releases, (2) direct surface water releases, (3) on-site land
releases, (4) releases to POTWs, and (5) off-site transfers. We also outline the mechanics of combining the
data files described above with (a) the mathematical equations that predict exposure and (b) with the weighting
schemes used to derive the toxiciry and exposure potential weights. The final facility-chemical-medium-
specific element is the product of the toxiciry weight, exposure weight and estimated population size in the case
of the human health chronic indicator. The ecological indicator is the product of the toxicity and exposure
weights.
The following discussions of exposure modeling frequently mention concentration and surrogate dose.
We do not mean to imply that we somehow supplanted the risk assessment process and can accurately
calculate cases. We speak of those terms only in the abstract. The method is a simple way to gauge relative
risks from releases to different media in a congruent, defensible way. In some cases, the modeling will be
purposely simple, given our lack of site-specific data. The differences in the level of refinement of exposure
modeling are addressed by using the uncertainty weighting scheme discussed in Chapter IV.
Stack and Fugitive Air Releases
Ideally, reported stack and fugitive air releases from the TRI database would be modeled using site-
specific data (such as source area or stack height). Since TRI does not contain such facility-specific
information, we must use default values to model TRI facilities with established EPA air dispersion models.
For this methodology, we will use the Industrial Source Complex Long Term (ISCLT) model
developed by the Office of Air Quality Planning and Standards (OAQPS). ISCLT is a steady-state Gaussian
plume model used to estimate long-term pollutant concentrations downwind of a source. The concentration
-------
is a function of site-specific parameters (stack height, stack velocity) and chemical specific decay rates.7 To
use the model, facilities directly releasing to air are first located on the BGREACH grid. Emissions rates in
pounds per year are directly converted to grams per second by the following equation:
=D
31,536,000
where
Q = pollutant emission rate (in g/s), and
q = pollutant emission rate (in Ib/yr).
These emissions rates are then used in the following equation that determines the concentration at a distance
r greater than 1 meter away from a point source8:
2K
where
Cair = concentration at distance r (|ig/m3),
Q = pollutant emission rate (g/s),
f = frequency of occurrence of wind speed and direction,
@D = sector width (radians),
S = smoothing function used to smooth discontinuities at sector boundaries,
u = mean wind speed (m/sec),
oz = standard deviation of vertical concentration distribution (m),
V = vertical term (m),
D = pollutant-specific decay in air (edistmce*decay »^^™
-------
direction around a given source. The weather data are stored in the STAR9 data file and described in the table
below.
Variable
ID
LONGITUDE
LATITUDE
Comment
STAR Station ID
Longitude of the station
Latitude of the station
Variable
MEANWIND
CATEGORY
F1-F16
Comment
Mean wind speed
Stability category
16 frequencies of occurrence
The NEARSTAR variable in the BGREACH file is matched with the ID variable in the STAR data file.
Based on the ISCLT equations, concentrations are calculated at each of the 100 cells (10 km x 10 km
total area) nearest to the facility. These concentrations are then weighted by the population in the cell to derive
a population-weighted average concentration over all 100 cells. If a cell contains no population, a value of 10
is used in the cell to assure that the population surrounding a facility is at least 1000 (i.e., there will be 100 cells
with at least 10 persons in each cell). The program then combines the weighted concentrations with standard
assumptions regarding inhalation rate and human body weight to arrive at a surrogate dosage:
DOSE =[fair'avz ' air
BW
where
DOSE =
r
air,avg
BW
surrogate dose of contaminant (mg/kg-day),
= population-weighted average air concentration (mg/m3),
= inhalation rate (m3 per day), and
= human body weight (kg).10
Figure 2 graphically describes the air modeling portion of the indicator, and Table 1 lists the default parameters
for ISCLT.
The program then uses the exposure weighting matrices (presented in Chapter IV for humans and
aquatic life) to assign a weight to the calculated surrogate dose, either. For the air release pathway, we
propose to use uncertainty category A to classify the air exposure potential (see Chapter IV discussion of
exposure potential uncertainty).
Finally, the program accesses the TOX data file to assign a toxicity weight. The toxicity weighting
matrix used by the program is presented in Chapter III. The product of the aquatic life exposure and toxicity
scores yields an aquatic life indicator element for the facility-chemical-air release combination. For the human
FBXTRIS.TRIDENT. STAR - SAS file containing weather information used in air modeling. The file was converted to
SAS for this project. It contains the same data used by ISCLT.
This method uses the average adult body weight (male and female combined), for certain health endpoints (e.g., female
reproductive effects), a different body weight value may be more appropriate (e.g., average adult female body weight).
1-10
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health indicator, the exposure score, toxicity score, and the size of the population over the 100 cells are
multiplied to yields an indicator element.
Direct Surface Water Releases
The Graphical Exposure Modeling System (GEMS) contains capabilities for estimating concentrations
in surface water from direct chemical discharges (EPA, 1987a). We adopt GEMS data and methods for
modeling surface water exposures. GEMS uses water volume data (from the GAGE database) and a routing
database (the REACH database) that maps the path of the chemical to determine concentration. Another
database Federal Reporting Data System (FRDS) is accessed to determine the populations at drinking water
intakes.11
This database has a limitation in that it generally captures only those public systems that serve populations greater than
2500. Locations for community systems serving smaller populations are sporadically available.
1-11
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Figure 2. Calculation of Surrogate Dose and Indicator Element from
Stack and Fugitive Air Releases
Release
of TRI Chemicalc at Facilityf(lb/year)
ISCLT algorithm
Pollutant Concentration in Cellx (ug/m3)
Standard Exposure
Assumptions
(Inhalation Rate,
Body Weight)
Surrogate Dose of Chemicalc for Cellx from
Facilityf (mg/kg-day)
Population Data
for Cel^,
Toxicity Weight
Indicator Sub-element for Cellx from Facility f
Sum over All 441
Cells
Indicator Element for Air Release of
Chemicalc from Facilityf
1-12
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Table 1. Air Modeling Parameters
Parameter
Stack height
Exit velocity
Stack diameter
Exit gas temperature
Area source size
Area source height
Decay rate
Body weight
Pollution emission rate
Frequency of wind speed and direction
Sector width
Wind speed
Smoothing function
Vertical term
Population-weighted average air cone.
Inhalation rate
Value
10m
0.01 m/s
1m
293 K
10m2
3m
varies by
pollutant
70kg
site-specific
site-specific
0.393 radians,
or 22.5°
site-specific
calculated
calculated
calculated
20 m3/day
Source/Comment
EPA (1992)
EPA (1992)
EPA (1992)
EPA (1992)
EPA (1992)
EPA (1992)
EPA Exposure Factors
Handbook (EPA, 1990); value is
for adults; lifetime age-weighted
average (male and female
combined) is about 62 kg
TRIS (Ibs/yr)
STAR
3 60° divided by 16 wind
directions
STAR (m/s)
mg/kg-day
EPA Exposure Factors
Handbook (EPA, 1990)
1-13
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GEMS uses a simple first-order decay equation along with volume and water speed estimates to
calculate concentrations resulting from contaminant releases at a distance at time t. The general form is as
follows12:
where
Ct = concentration at time t,
C0 = initial concentration, and
kwater = decay coefficient.
Using the REACH database, which contains information on the stream network of the United States,
discharges are modeled as they make their way through the surface water network. Facilities are matched to
appropriate streams using their latitude and longitude coordinates provided in TRI.
A facility discharging to water is located on the BGREACH grid. Using the water volume data
contained in the BGREACH file, an initial concentration is calculated at the cell containing the facility. The
surface water body network is stored in a separate file. The discharge from a facility is then matched to the
grid cell containing the nearest surface water body. Then the surface water body is traversed and the
concentration is adjusted along the water body.
This methodology considers two human health exposure pathways from surface water releases. First
exposures from drinking water are calculated. As the pollutant passes through the stream network,
concentrations at public drinking water intakes are noted. The population served (which is the variable
WATERPOP in the BGREACH file) functions as the exposed population at that concentration. If a cell
contains no drinking water intake, the WATERPOP variable is zero; otherwise, the WATERPOP variable is
non-zero. The population-weighted water concentration is combined with standard exposure parameters to
yield the following surrogate dosage:
DOSE ~D water' avg water
BW
where
DOSE = surrogate dose of contaminant (mg/kg-day),
CWater,avg = population-weighted average water concentration (mg/1),
Iwater = drinking water ingestion rate (I/day), and
BW = human body weight (kg).
Chemicals with extremely short half-lives in water will not be modeled using this procedure. Such chemicals will be
assumed to degrade before significant exposure occurs.
1-14
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As with the air releases, the program then uses the exposure weighting matrix to assign an exposure
weight to the calculated population-weighted surrogate dose. For the drinking water pathway, we propose
to use uncertainty category B for exposure potential weighting for several reasons. First, the calculation of
water concentrations does not consider partitioning of the chemical between the water column and suspended
solids, deposition of the sediments along the water course, or other processes that may affect the fate and
transport of contaminants along a surface water body. Furthermore, there is no consideration of the removal
of contaminants during treatment of drinking water at the utility. All of these factors would tend to inflate the
exposure potential evaluation.
Finally, the program accesses the TOX data file to assign a toxicity weight based on the toxicity matrix
presented in Chapter III. The product of the exposure score, the toxicity score and the population for all of
the cells with drinking water intakes yields a facility-chemical-drinking water element.
A second potential exposure pathway is from consumption of contaminated fish. Each segment of the
affected water body may contain contaminated fish which could be caught and eaten by recreational fishers.
As described above, the program tracks the concentration of the chemical as it traverses down the waterway;
at each cell, the concentration in fish is derived by the following equation:
Cfish =^water -UBCF
where
Cfish = concentration in fish, (mg/kg),
Cwater = average water concentration in stream (mg/1), and
BCF = bioconcentration factor for chemical (I/kg).
Next, the fish concentration value is combined with standard exposure assumptions regarding fish consumption
rates to determine surrogate dose from this pathway:
DOSE =UCfish ' Ifish
BW
where
DOSE = surrogate dose of contaminant (mg/kg-day),
Cfish = fish tissue concentration (mg/kg),
Ifish = fish ingestion rate (kg/day), and
BW = human body weight (kg).
The calculated surrogate dose in each cell is then weighted by the population of recreational fishers assumed
to reside in that cell to yield a population-weighted average surrogate dose for all cells. The number of fishers
is estimated as the total population in the cell times a fraction of persons who are assumed to fish for
recreation. We derived state-specific fractions of persons who eat fish from state-specific fishing rates found
in the 1991 National Survey of Fishing, Hunting, and Wildlife Associated Recreation (U.S. FWS, 1993).
As with the drinking water pathway releases, the program then uses the exposure matrix to assign a
weight to the calculated population-weighted surrogate dose. For this exposure pathway, we propose to use
1-15
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uncertainty category C for exposure potential for several reasons. First, as with the drinking water pathway,
the estimated water concentrations are probably an overestimate because we don't consider all processes in
surface water that affect concentrations. Second, fish concentrations are actually dependent on the type of
species, particularly its lipid content and its position in the food chain. Finally, the actual probability of
recreational fishing in the particular stream reach being modeled is unknown, as is the actual quantity offish
consumed from that particular reach.
Next, the program accesses the TOX data file to assign a toxicity weight based on the toxicity
weighting matrix presented in Chapter III. The product of the exposure score, the toxicity score and the
population for all of the cells traversed by the contaminated surface water yields an element for the facility -
chemical-fish ingestion combination.
Figure 3 shows our recommended surface water approach, and Table 2 lists model parameters for
surface water modeling.
1-16
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Figure 3. Calculation of Surrogate Dose and Indicator Element from
Surface Water Release
Release
of TRI Chemicalc at Facilityf (Ib/year)
Water Volume and Velocity
Estimates; Decay Equation
Pollutant Concentration in Surface Water Reachx (mg/L)
Bioconcentration
Factor
Standard Exposure
Assumptions
(Drinking Water Ingestion
Rate, Body Weight)
Pollutant Concentration in Fish in
(mg/kg)
Surrogate Dose from Drinking Water in
x (mg/kg-day)
Standard Exposure I I
Assumptions r j
(Fish Ingestion Rate, Body ^/
Weight)
Surrogate Dose from Fish Consumption
in Reachx (mg/kg-day)
Population
Served by
Drinking Water
Intakes in Reachx
(if any); Toxicity
Data
Drinking Water
Population in Reach
(if any) and
Statewide Data on
Recreational Fishers;
Toxicity Data
V
Indicator Sub-element for Fish
Consumption for
Indicator Sub-element for Drinking
Water for
Sum over All Reaches and Both Pathways
Indicator Element for Surface Water
Release of Chemicalc from Facilityf
1-17
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Table 2. Surface Water Modeling Parameters
Parameter
Decay rate
Dilution rate
Water volume and velocity
Population-weighted average
water concentration
Drinking water ingestion rate
Body weight
Average chemical concentration in
stream
Bioconcentration factor
Fish tissue concentration
Fish ingestion rate
Value
varies by pollutant
site-specific
site-specific
calculated
2 liters
70kg
calculated
varies by pollutant
calculated
0.0065 kg/day
Source/Comment
REACH (EPA, 1987a)
REACH (EPA, 1987a)
mg/L
EPA Exposure Factors Handbook
(EPA, 1990)
EPA Exposure Factors Handbook
(EPA, 1990); value is for adults;
lifetime age-weighted average
(male and female combined) is
about 62 kg
mg/L
L/kg
mg/kg
Exposure Factors Handbook
(EPA, 1990)
1-18
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On-Site Land Releases
On-site land releases include releases to landfills, surface impoundments, land treatment units and
underground injection. This section describes methods to evaluate exposure from these releases. For
simplicity, the following discussion will focus on landfill disposal, but the same evaluation principles will apply
to the other types of land releases, with the exception of underground injection13.
Two major pathways are considered for on-site land releases: chemicals may volatilize to air or leach
to groundwater. Volatilization of chemicals from on-site landfills is reported under the fugitive emission
estimate for the facility and is thus handled as a direct air release.
Groundwater contamination is also a concern for land releases. However, the modeling of groundwater
releases will depend on the regulatory status of the unit in which the chemical is released. Chemicals could
be deposited in an on-site RCRA-regulated hazardous waste unit, or in an on-site nonhazardous solid waste
management unit. RCRA standards for hazardous waste units are, by regulation, designed to include technical
controls to prevent release of contaminants into groundwater; if chemicals are placed in such regulated units,
it will be assumed that releases to groundwater are negligible. If chemicals are placed in RCRA nonhazardous
land disposal units, we will model the release of chemicals to groundwater. This analysis assumes that if the
TRI form reports a RCRA ID number for the facility, then the on-site land releases are assumed to go to a
RCRA regulated unit. Otherwise, the on-site land release is assumed to occur in a nonhazardous land disposal
facility.
The TRI forms do not provide site-specific information that aids in the evaluation of groundwater
transport, such as geohydrological data. Unfortunately, these data are extremely site-specific and are not
amenable to characterization by state or region of the country. To maintain a concentration/exposure measure
consistent with the approaches suggested for direct air and water releases, we propose an approach that gives
a concentration at the exposure point (the well) to be combined with exposure assumptions to yield a surrogate
dose. This approach requires two steps: estimating leachate concentration (a measure of the amount of
chemical that partitions from the waste to water) and estimating the dilution and attenuation of leachate from
the disposal site to the well location. The approach to evaluating exposure from landfilling is summarized in
Figure 4.
The methodology proposes an alternate approach to evaluate exposure from underground injection of TRI chemicals.
Under well-managed conditions, these facilities are designed to pose minimal risks to human health or the environment.
However, certain conditions can lead to the failure of these facilities and the release of chemicals to human and environmental
exposure pathways. An exposure analysis for these releases would have to include an evaluation of the likelihood of the failure
as well as an evaluation of the exposure impacts of such a failure.
1-19
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Figure 4. Calculation of Surrogate Dose and Indicator Element from
On-site Land Releases
On-site Land Release
of TRI Chemicalc at Facilityf (Ib/year)
Volatilization
Reported under Fugitive Emission
Estimate; Handled as Air Release
V
Groundwater Methodology
Deposition in
Nonhazardous <
Unit
Deposition in
RCRA Hazardous
Waste Unit
Release to Groundwater
Partitioning Data and
Industry Average Waste
Volume Data
No Release to
Groundwater Assumed
Leachate Concentration (kg/L)
EPA/OSW Monte
Carlo Analysis of
Dilution and
Attenuation Factors
Pollutant Concentration in Groundwater (mg/L)
Standard Exposure
Assumptions
(Drinking Water Ingestion
Rate, Body Weight)
Surrogate Dose of Chemicalc from Facilityf
(mg/kg-day)
Well Water-Drinking
Population within 1 km of '
Facility; Tox. Data
Indicator Element for On-Site Land Releases
of Chemicalc from Facilityf (mg/kg-day)
1-20
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Leachate concentrations can be estimated using a modified modeling approach with chemical-specific
parameters. The general form of this estimate is as follows:
C, =
where
Q
c
concentration in leachate (kg/1 or 1 x 106 mg/kg),
concentration in landfill solids (kg/m3 or 1000 mg/kg),
soil/water partition coefficient (I/kg), and
bulk density of material in landfill (kg/m3).
This equation assumes that the landfill material essentially contains close to 100% solids. This assumption (and
the equation) will have to be modified for use for surface impoundments. It must be noted that the
concentration in the leachate, Cb must be compatible with the chemical-specific solubility so that the smaller
of the two values is used.
The concentration in the landfill solids, Cs, can be estimated by dividing the total mass of contaminant
disposed (mg/yr) by the total mass of waste disposed in the unit each year:
M(mg per yr)
C =D-
where:
Mc
Mw
Mw(kg per year}
total mass loading of contaminant to landfill (mg per year), and
total mass of waste disposed in landfill (kg per year).
The value for Mc is available in the TRI database; the value for Mw will be taken from EPA (1988a). This
report summarizes the distribution (by number of facilities and by industry type) of the tons per year of waste
disposed in industrial nonhazardous solid waste landfills. Data are also reported for surface impoundments,
waste piles and land treatment facilities. These summaries are reproduced in Appendix F. This appendix was
converted to a data file WASTE14, with the following content:
Variable
SIC
WASTEVOL
Comment
SIC code for which the
waste volume is
applicable
Industry-specific waste
volume disposed per year
Variable
UNITTYPE
Comment
Type of management
unit into which waste is
placed
14
FBXTRIS.TRIDENT. WASTE - SAS file containing waste volume information.
1-21
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It should be noted that using Mw as the divisor in landfill concentration may underestimate the total
concentration of the TRI chemical, since the landfill may include some of the same chemicals from sources
other than TRI facilities.
A summary of the values used in the groundwater calculation and the sources of these values appear
in Table 3.
Table 3. Groundwater Modeling Parameters
Parameter
Concentration in leachate
Partition coefficient
Value
calculated
varies by
pollutant
Source/Comment
mg/L
Once leachate concentrations are estimated, the next step is to determine the magnitude of dilution and
attenuation of contaminants that occur as the contaminant travels from the source to the well. The Office of
Solid Waste performed an analysis of dilution and attenuation of contaminants in groundwater during the
development of the Toxicity Characteristic Leaching Procedure (TCLP) rulemaking (55 (61) Federal Register
11798). For that rule, OSW used Monte Carlo analysis to evaluate dilution and attenuation factors (DAFs)
for 44 chemicals. In the Monte Carlo analysis, multiple iterations of a groundwater model were performed.
For each model run, model parameter values were drawn randomly from their distributions. (It should be
noted that distance to the well was one of the parameters varied in the analysis: the distribution of distance
between a source and a well was derived from a survey of Subtitle D facilities). The result of the analysis was
a distribution of model results, where each model result was a DAF. OSW then selected the 85 percentile DAF
for use in its regulatory calculations. For most chemicals modeled, the 85th percentile dilution and attenuation
factor was approximately a factor of 100. For this methodology, we will use the OSW 85th percentile dilution
and attenuation factor of 100 to estimate groundwater concentrations at the well from land releases. The
concentrations are then used to calculated surrogate doses. It should be noted that OSW's DAFs are not
intended to reflect the effect of pumping in drinking water wells on the concentration of chemicals in
groundwater, and thus calculation of TRI surrogate dosages are oversimplified.
The program then uses the exposure matrix to assign a weight to the calculated surrogate dose. For
the groundwater pathway, we propose to use uncertainty category C, since the exposure estimate is based on
a conservative, steady-state estimate of leachate concentration, and on a conservative, generic dilution and
attenuation factor.
The program then accesses the TOX data file to assign a weight based on the toxicity matrix presented
in Chapter III. The proposed population exposed to contaminated groundwater is calculated from the number
of persons receiving drinking water from groundwater within 4 square kilometers of the facility. The
population of persons served by well water is available for each county from the National Well Water
Association data files. From these data, we can derive a "well water drinker" population density for each
county. We will then calculate the population of well water drinkers within 4 km2 of the landfill site as our
exposed population. This value is included in the BGREACH file as the WELL variable. The product of the
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exposure score, the toxicity score and the population over 4 km2 yields an element for the facility-chemical-
groundwater combination.
Releases To POTWs
In 1988, 570 million pounds of TRI chemicals were discharged to the country's Publicly Owned
Treatment Works (POTWs) compared with 360 million pounds discharged directly to surface waters.
Modeling exposure from TRI discharges to POTWs requires consideration of (1) overall removal efficiencies
of POTWs and resulting effluent discharges from POTWs and (2) residuals management at POTWs. A
summary of our proposed approach to modeling POTW emissions is found in Figure 5.
To store POTW-specific information, we use a data file called POTW.15 The appropriate POTW file
is matched to the TRI transfer via the DCN (Document Control Number) variable in the RELEASE data file.
Variables contained in the POTW file are shown below.
Variable
DCN
BASIS6
Comment
ID used for matching with TRI
transferring facility
Basis/Method for estimate of
quantity of release to POTW
Variable
ZIPCODE
SLUDGE
Comment
ZIP code of the POTW facility
Sludge disposal method
employed by the POTW
The ZIP code of the POTW is provided on the TRI form of the facility making the transfer. Using this data
file, POTWs are located on the BGREACH grid based on the latitude and longitude of the ZIP code centroid.
To do so, we must match the ZIP code centroid with a latitude and longitude. This information is stored in
a data file called ZIPCODE.16 The format of the ZIPCODE file is given below.
15TRIS.PROD.POTW.FILE89 - This file is also part of the national report family of files. The full record layout is
available from EPA.
16FBXTRIS.TRIDENT.ZIPCODE.CENTROID - SAS file containing FIPS, zipcode, longitude/latitude, and census
information for all ZIP codes in the United States.
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Figure 5. Modelling of Exposure from POTW Releases
Release to Designated POTW
of Chemicalc from Facilityf (Ibs/year)
POTW Located via ZIP Code Centroid
POTW Removal
Rate
POTW Residual (Fate Determined by Partitioning Rate)
Biodegradation'
No Risk Assumed
Sludge - Deposition
in POTW On-Site
Landfill Assumed
POTW Effluent
Volatilization
Handled as On-Site Land
Release at POTW - See
Groundwater Methodology in
Exhibit 17
Handled as Air
Release
at POTW -
See Exhibit 13
Handled as Surface
Water Release
at POTW -
See Exhibit 15
Combined with Pathway-Specific Toxicity Weights
and Exposed Populations
Indicator Sub-element for a
specific POTW Release of
Chemicalc from Facilityf for
Groundwater
Indicator Sub-element
for a specific POTW
Release of Chemicalc
from Facilityf for
Volatilization
Indicator Sub-element
for a specific POTW
Release of Chemicalc
from Facilityf for
Surface Water
Indicator Element
1-24
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Variable
ZIPCODE
LONGITUDE
POP
Comment
ZIP code
Longitude of the ZIP code
centroid
ZIP code population
Variable
FIPS
LATITUDE
Comment
State-County FIPS CODE
Latitude of the ZIP code
centroid
Once we have located the POTW, the next step is to apply the overall POTW contaminant removal rate (stored
in the TOX file) to the release.
POTWs are not completely effective at removing all of the chemicals in the influent; some of the
chemical loading in the influent will be released in the POTW effluent. Typical overall POTW removal
efficiencies vary by chemical. Chemical loadings that are removed by POTW treatment processes partition to
several pathways within the POTW, including biodegradation, volatilization, and adsorption to sludge. Using
average removal and partitioning rates, chemicals will be divided among effluent, biodegradation, air and
sludge pathways. The Domestic Sewage Study (EPA 1986) gives both typical POTW removal efficiencies and
within-POTW partitioning rates for many TRI chemicals. These values will be used in this methodology.
Chemicals lacking partitioning rates will be assigned rates based on their chemical class. To do so, each
chemical having partitioning rates in the Domestic Sewage Study will be assigned to a class (halo-organic,
metal, etc.), and an average determined for each class. The average rate will be applied to other TRI chemicals
in that class lacking specific partitioning rates.
This overall removal rate allows the program to calculate the loading of contaminant remaining in the
POTW effluent and the loading that remains in the POTW. Contaminants remaining in the POTW are
partitioned within the POTW, using partitioning rates stored in the TOX file. The partitioning rates allow us
to estimate the amount of contaminant in the POTW sludge and in the POTW volatile emissions, as well as
the amount that degrades.
Once the fates of chemicals entering the POTW are determined, the exposure levels associated with
chemical loadings to each compartment will be estimated. Chemicals that escape in the POTW effluent will
be modeled using the surface water evaluation methods described above. Since ZIP code centroids are used
to locate the POTW, it is possible that a POTW may be placed on a BGREACH grid cell without a water body
running through it. In this case, the water body receiving the POTW effluent is determined by finding the
nearest water body to the ZIP code centroid. We could improve this estimate if we could find longitude and
latitude information for POTWs from a source other than ZIP codes. Chemicals that biodegrade will be
assumed to cause no further exposure. POTW volatilization releases will be treated like area-source air
releases, as described above.
For chemicals that partition to sludge, the models used to depict exposure will depend on the sludge
disposal method employed by the POTW. The remaining problem is to determine which POTWs engage in
which sludge disposal practices since it cannot be determined from the TRI database. A database does exist
(the National Sewage Sludge Survey) that describes the sludge disposal methods employed by POTWs in the
United States. If we can identify methods used at specific POTWs from this database, the exposure levels from
POTW sludge contaminants can be modeled using the same methods used to model direct releases of
contaminants, depending on the POTW sludge disposal practice (incineration, landfilling, land application,
etc.). For incinerated sludge, destruction and removal efficiencies from the TOX file are applied and then air
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modeling is performed as described in the Air Releases section above. Land disposal of sludge can be modeled
as a land release using methods described above. Populations surrounding the disposal facility or disposal area
will be modeled as the exposed population. If extracting data on disposal practices is too cumbersome or if
a match cannot be found, other methods for modeling these exposures will have to be adopted. One possible
method is to use results from the national aggregate population risk assessment for municipal sludge performed
in support of upcoming municipal sludge rules. From this risk assessment, we could obtain average exposures
per ton of sludge disposed, by disposal method. These results could be used for this analysis by weighting
these unit exposures by the amount of sludge disposed by each practice (either regionally or nationally), then
multiplying by the tons of sludge disposed by the POTW (which can be estimated based on flow to the
POTW).
The resulting sum of the uncertainty-adjusted, population-weighted surrogate doses from POTW
effluent, volatilization at the POTW, incineration of sludge, volatilization of land disposed sludge, and
groundwater contamination from land-disposed sludge are combined with the chemical-specific toxicity score
to yield a facility-chemical-POTW release element.
Off-Site Transfers
In 1988, over 17 percent of TRI volume was transferred to off-site locations for storage or disposal.
Figure 6 presents a summary of our proposed method to model off-site transfers. TRI reporters are supposed
to supply the name and address of the receiving facility. From these data, we must determine if wastes are sent
to a hazardous or nonhazardous waste management facility. Efforts are currently underway between OSW
and OPPT to match facilities reported in TRI with RCRIS reporting to aid in making this determination.
Chemical submissions indicating transfer to a RCRA hazardous waste facility will not be included in the
indicator; for the purposes of simplifying the indicator calculation, these transfers are assumed to pose no
further risk in a regulated disposal facility. Only transfers to nonhazardous facilities will be modeled.
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Figure 6. Modeling of Exposure from Off-site Transfers
Transfer to Off-site Facility
of Chemicalc from Facilityf (Ib/year)
Off-site Facility Located via ZIP Code
Transfer to
Nonhazardous
Waste Facility
Treatment Method Determined from TRI Form
] [
Transfer to RCRA
Hazardous Waste
Facility
No Risk Assumed
Incineration
] [
Landfilling
osw
Analysis of
Destruction
and Removal
Efficiencies
Air Release Estimate
Potential
Groundwater
Contamination
Chemical
Partitioning
Data; Wind
Speed Data
Volatilization Rate
Handled as Air Release
-See Exhibit 13
Handled as On-site Land
Release - See Ground-
water Methodology in
Exhibit 17
Handled as Air Release
-See Exhibit 13
Combined with Pathway-Specific Toxicity Weights
and Exposed Populations
dicator Sub-element
r a specific Off-site
•ansfer of Chemicalc
from Facilityf for
Incinerators
Indicator Sub-element
for a specific Off-site
Transfer of Chemicalc
from Facilityf for
Groundwater
Indicator Sub-eleme:
for a specific Off-sii;
Transfer of ChemicE
from Facilityf for
Volatilization
Indicator Element
1-27
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As with POTW transfers, to assess exposure potential associated with off-site transfers, we must have
information on the off-site facility location and some of its characteristics. To store off-site facility information,
we constructed the data file OFF SITE.17 Variables necessary from the file are shown below.
Variable
DCN
ZIPCODE
TREAT
Comment
ID used for matching TRI facility
ZIP code of off-site facility
Type of treatment
Variable
RCRA-ID
BASIS?
Comment
RCRA ID number (if it has one)
Basis/Method for estimating
quantity of chemical transferred
off-site
We match data in the RELEASE file to this file via the DCN (Document Control Number) variable.
The ZIP code for the off-site facility to which chemicals are transferred is contained in the TRI data base. The
ZIP code serves, in conjunction with the ZIPCODE data file, to locate our facility on the BGREACH grid, as
was described for locating POTWs. It should be noted that OSW and OPPT are jointly working on a tracking
system to match TRI releases to the RCRIS data base. If this effort is completed before we implement the TRI
Environmental Indicator, we may be able to use the fruits of that effort for more precise tracking of the off-site
releases. Once we have located the off-site facility, we also need to know (a) the regulatory status of the unit
to which the material is transferred and (b) the treatment/disposal technologies used by the off-site facility.
The regulatory status of the off-site units could be determined in a number of ways. The TRI form requires
the reporting facility to give the RCRA-ID number of the off-site facility to which the chemical is being
transferred. We could assume that if such a number is reported, then the chemical is being transferred to a
RCRA-regulated unit. Otherwise, we will assume that it is a RCRA Subtitle D nonhazardous management
unit.
The TRI forms also require the reporting facility to indicate the treatment/disposal method used at the
off-site facility. Where this information is reported, it is stored as the TREAT variable in the OFFSITE data
file; the method reported will be assumed to be the treatment/disposal method employed by the off-site facility.
If this information is not reported (despite the requirement), we will have to assume a distribution of
treatment/disposal methods, based on the frequency of treatment/disposal methods reported for that chemical
practiced at nonhazardous Treatment, Storage or Disposal Facilities (TSDFs) where the treatment/disposal
method is known. Using this distribution, we will assign the appropriate proportion of the release to each
reported treatment/disposal method.
Once the treatment method is established, we model exposure potential using the methods described
above. The exposure evaluation for off-site transfers will obviously depend on the type of treatment/disposal
employed off-site. We are still investigating methods for evaluating exposures from various treatment and
disposal technologies, including underground inj ection. We currently have methods to evaluate exposure from
two offsite disposal technologies: waste incineration and landfilling.
17r,
TRIS.PROD.OFFSITE.FILE89 - This file is also part of the national report family of files. The full record layout is
available from EPA.
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Air releases from off-site nonhazardous waste incinerators can be modeled like direct air releases. We
have obtained destruction and removal efficiencies (DREs) for nonhazardous waste incinerators from an OSW
analysis of municipal solid waste combustion (EPA, 1987b); these values are included in the TOX data file.
For inorganics, values are taken from multiple hearth sludge incinerator studies (EPA, 1993).
For landfills, two major pathways will be considered. The groundwater pathway will be modeled for
off-site releases in the same manner as for on-site land releases. Volatilization, however, will be handled
differently. For on-site releases, volatilization is included in reported fugitive emissions and thus exposure is
modeled with air releases. For off-site land releases, volatilization emissions from land disposal must be
estimated before exposure can be modeled. Since the volatilization rate is a function of vapor concentration,
the vapor concentration must be calculated. This involves two steps: partitioning from the solid to the water,
and then water to air. Simple steady-state relationships can be used to approximate these partitioning
processes if certain chemical-specific data are known.
The equation for determining the concentration of chemical in the liquid phase (i.e., leachate) was given
earlier in the "On-Site Land Release" section:
where
C, = concentration in leachate (liquid phase) (kg/1),
Cs = concentration in landfill solids (kg/m3),
Kd = soil/water partition coefficient (I/kg), and
Bd = bulk density of material in landfill (kg/m3).
The second calculation determines the vapor phase concentration from the liquid phase concentration using
Henry's Law Constant (the ratio of the contaminant concentration in the vapor to the concentration in the
liquid phase):
cv =UH cl
where
Cv = concentration in vapor phase (kg/1) and
H = Henry's Law Constant (dimensionless).
Now that an equilibrium vapor concentration has been determined, the rate of volatilization may be estimated
from a first-order rate equation:
Vol Rate =Dfevo/ Cv
where
kvol = volatilization rate constant.
The volatilization rate constant is taken from a EPA (1985) equation for uncovered monofills:
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, _ 0.17 u (Q.994f -
Kvol )=
JMW
where
u = wind speed (m/s),
T = ambient air temperature, assumed to be 15 ° C,
MW = molecular weight (g/mol) and
0.17 and 0.944 are empirical constants.
All of these formulae may be combined to express the volatilization rate as a function of the chemical
concentration in the solid phase:
0.17 u (0.994)(^20) H C
Vol Rate = '-
These volatilization emissions estimates, along with weather and data on populations surrounding the
off-site disposal facilities, will be used to arrive at population-weighted concentrations in the same way as
fugitive direct air releases from TRI facilities. Population data will be extracted using the zip code of the
facility receiving the waste. Volatilization parameters are summarized in Table 4.
The resulting sum of the uncertainty-adjusted, population-weighted surrogate doses from incineration,
volatilization and groundwater exposures are combined with the chemical-specific toxicity score to yield a
facility-chemical-off-site transfer element.
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Table 4. Volatilization Modeling Parameters
Parameter
Kd
Molecular weight
Henry's Law constant
Average area of source:
municipal solid waste landfill
Median area of source:
industrial nonhazardous land
disposal
Mean wind speed
Value
varies by pollutant
varies by pollutant
varies by pollutant
32.5 acres
landfill: 3 acres
surface impoundment: 0.5 acres
land treatment: 15 acres
waste pile: 0.5 acres
site-specific
Source/Comment
Chemical properties
database (Appendix
D)
Chemical properties
database (Appendix
D)
Chemical properties
database
(Appendix D)
EPA(1988b)
EPA(1988c)
m/s; from STAR
data
Evaluating Exposure Potential -- Ecological
The estimated ambient water concentration value is used directly to evaluate potential exposures to
aquatic life. The method for evaluating ambient surface water concentrations resulting from TRI releases is
discussed in Chapter IV of the methodology. Since the Chronic Ecological Indicator includes only one
exposure pathway, there is no reason to use an uncertainty adjustment for cross-pathway uncertainty.
Therefore, these surrogate values are used directly as the exposure potential weights for aquatic life.
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U.S. Environmental Protection Agency (EPA). 1986. Report to Congress on the Discharge of Hazardous
Wastes to Publicly Owned Treatment Works (the Domestic Sewage Study). Office of Water
Regulations and Standards. EPA/530-SW-86-004. February.
U.S. Environmental Protection Agency (EPA). 1987a. Graphical Exposure Modeling System (GEMS) User's
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U.S. Environmental Protection Agency (EPA). 1988b. National Survey of Solid Waste (Municipal) Landfill
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U.S. Environmental Protection Agency (EPA). 1993. Human Health Risk Assessment for the Use and
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