v>EPA
Office of Pollution Prevention
Environmental Protection and Toxics
Agency Washington, DC 20460 March 2023
EPA's Risk-Screening
Environmental Indicators
(RSEI) Methodology
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Preface and Acknowledgments
Preface
In 1989, the United States Environmental Protection Agency (EPA) outlined the goals for
establishing strategic planning processes at the Agency. Underlying these goals 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 human health and environmental 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 and stakeholders to establish
priorities for improving future environmental health.
To efficiently 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. The Toxic Chemical Release Inventory (i.e., Toxics Release
Inventory (TRI)) is one of the Agency's most relevant sources of continuous data for developing
indicators of change in environmental impacts over time. In response to the need for
environmental indicators, and to take advantage of the rich data source offered by the TRI, the
Agency convened a workgroup that included members from several different offices and
divisions. 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
hazard, exposure, and population considerations into the evaluation of environmental releases of
toxic chemicals. The Risk-Screening Environmental Indicators (RSEI) method was subsequently
developed in response to this initiative.
This document presents the results of that effort, a methodology for developing RSEI plus
detailed description on how the RSEI model is constructed, and includes discussions of the
conceptual basis, data sources, and the computational approach. One main objective of this
document is to explain the RSEI method to a variety of agencies and groups that may wish to use
or adapt the RSEI model or the methodologies to their own needs. A related objective is to
describe the benefits of a relative risk-based indicators approach in terms of flexibility, power,
and utility as an analytical, screening, prioritization, and strategic planning tool. As an indication
of improvements in environmental quality over time, the RSEI model will provide the Agency
with a valuable tool based upon relative risk-related impacts of TRI-listed toxic chemicals.
Importantly, RSEI also provides an ability to analyze relative contributions of chemicals to
potential health impacts, and RSEI results can serve as an analytical basis for setting priorities
for further investigation and analysis, pollution prevention activities, regulatory initiatives,
compliance and enforcement targeting, and chemical testing requirements and research.
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Preface and Acknowledgments
Acknowledgments
Many people have contributed to the RSEI project over the years. We would especially like to
acknowledge the contributions of Nicolaas Bouwes and Steven Hassur, who were the originators
of the model and instrumental to its design, development, and implementation; Gary Cole,
Richard Engler, Lynne Blake-Hedges, Wayne Davis, and Mitchell Sumner for their oversight
and leadership in managing and directing updates and enhancements made to the tool. In
addition, we wish to express our thanks to the individuals on the Indicators workgroups that
developed the early framework of the methodology and to those who contributed valuable
insights, advice, and contributions to the project along the way.
We would also like to acknowledge the contractor and development support team that has been
provided by Abt Associates Inc. since 1991; Susan Keane, Brad Firlie, and Elizabeth Levy, who
were included in the original Abt Associates development team, and Cynthia Gould for her
steadfast dedication to maintaining and modernizing RSEI over the years.
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Table of Contents
Table of Contents
Contents
Executive Summary 1
1. Organization of this Document 20
2. General Description of the RSEI Model 21
2.1 General Description 21
2.2 Summary of the Strengths and Limitations of the RSEI Model 26
2.2.1 Strengths 26
2.2.2 Limitations 26
3. TRI Data Used in the Model 28
4. Methods for Calculating Toxicity Weights 31
4.1 Toxicity Weighting Scheme for Carcinogens and Non-carcinogens 32
4.1.1 Qualitative Data 32
4.1.2 Quantitative Data 34
4.1.3 Method for Calculating Toxicity Weights 35
4.2 Selecting the Final Toxicity Weights 36
4.3 Chemical Categories 38
4.4 Sources of Toxicity Data 40
4.5 How RSEI Toxicity Weightings Differ from EPCRA Section 313 Criteria 43
5. Exposure and Population Modeling 45
5.1 Geographic Basis of the RSEI Model 46
5.1.1 The RSEI Model Grid Cell System 46
5.1.2 Locating Facilities on the Grid 48
5.1.3 Locating People on the Grid 49
5.1.4 Surface Water Network 51
5.2 Pathway-specific Methods to Evaluate Human Exposure Potential 52
5.3 Modeling Air Releases 52
5.3.1 Stack Air Emissions: Method 53
5.3.2 Fugitive Air Emissions: Method 57
5.3.3 Calculating Surrogate Dose for Air Releases 57
5.3.4 Estimating Population Size for Air Releases 58
5.3.5 Calculating the RSEI Score for Air Releases 58
5.3.6 Stack and Fugitive Air Emissions: Data 60
5.4 Modeling Water Releases 65
5.4.1 Water Releases: Methods 65
5.4.2 Calculating the RSEI Score for Water Releases 70
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5.4.3 Water Releases: Data 72
5.5 Modeling Transfers to POTWs 76
5.5.1 Transfers to PO TWs: Method 78
5.5.2 Transfers to POTWs: Data 82
5.6 Modeling Other Off-site Transfers 83
5.6.1 Transfers Off Site to Incineration: Method 83
5.6.2 Transfers Off Site to Incineration: Data 85
5.7 Modeling Land Releases 85
6. Calculating RSEI Results 86
6.1 Combining RSEI Scores 88
6.2 Adjusting RSEI Results for Changes in TRI Reporting 89
7. Dissemination of RSEI Data and RSEI Model Results 91
7.1 EasyRSEI Dashboard 91
7.2 RSEI Geographic Microdata 92
7.3 Other RSEI Data Products 92
8. References 93
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Executive Summary
ES-1. Introduction
EPA's Risk-Screening Environmental Indicators (RSEI) is a screening-level, multimedia model
that incorporates EPA's Toxics Release Inventory (TRI) information together with other data
sources and risk factor concepts as an aid to evaluate the potential impacts of industrial
emissions of TRI-listed chemicals from a relative risk-based perspective. To this end, RSEI
produces different types of RSEI model results including hazard estimates and unitless risk-
related scores that provide context on the relative hazard and relative potential for health risks,
respectively, resulting from certain waste management activities of TRI chemicals (e.g., from
releases to the environment). The RSEI model is particularly useful for examining trends that
compare potential impacts from year to year, or for ranking and prioritizing chemicals, industry
sectors, or geographic regions for strategic planning purposes. In conjunction with other data
sources and information, RSEI can ultimately be used to help policy makers, researchers, and
communities establish priorities for further investigation and to look at changes in potential
health impacts over time.
When evaluating potential impacts involving toxic chemicals, it is important to not only consider
the quantities and circumstances of chemicals that are used, managed, or released to the
environment, but to also consider their potential toxicity and the likelihood of exposure for a
given scenario. The magnitude of the quantities of a chemical (or chemicals) released from an
industrial source to the environment is a practical indicator of the environmental performance of
that industry, however, it has limited use as an indicator of the potential health impacts that may
be posed by the released chemical(s) as it does not represent other important factors that
contribute to potential human health outcomes or environmental impact. Typical analyses that
rely on using only quantities of chemical releases as a descriptor for the identification of
associated potential health and environmental impacts are usually limited by the assumptions that
all chemicals are equally toxic and that all people are equally exposed. Factors such as the
seriousness of the toxic effect(s) caused by the chemical, the ultimate environmental fate of the
chemical, and the extent and duration of exposure to individuals from the chemical must also be
considered to assess its potential impacts and chance of causing an adverse effect.
Expression of chemical quantities adjusted for their relative ability to elicit toxic effect(s)
provides additional insight to the extent to which changes in quantities of a chemical or
chemicals may impact human health, and allows for a more meaningful analysis of aggregated
quantities than adding absolute quantities of chemicals alone. Toxicity-adjusted quantities give
more context and greater significance to the more toxic chemicals. These toxicity-weighted
quantities account for their magnitude (e.g., how much is released to the environment) and also
their relative toxicities (e.g., how hazardous and potent are the chemical(s)). These quantities are
calculated by multiplying the mass quantities (e.g., pounds released into the air) by a quantitative
value that expresses the toxic potential of the chemical(s) involved. They are descriptors of
relative hazard and these hazard-based results (i.e., toxicity-weighted pounds) are named RSEI
Hazard in the RSEI model.
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While not a descriptor of relative potential risk, RSEI hazard-based results enable one to
delineate the change in relative overall hazard for quantities aggregated for a single chemical or
for multiple chemicals. For example, a large increase or decrease in total aggregate
environmental release quantities of multiple chemicals from one year to the next does not mean
there is a corresponding large increase or decrease in relative overall hazard. However, a
toxicity-weighted value determined for each year would provide quantitative expressions of any
year-to-year changes in relative overall hazard.
Although toxicity-weighted quantities (such as RSEI hazard-based metrics) improve on a
quantities-only view by accounting for the relative toxicity of each chemical, these values still do
not account for what happens to the chemical(s) in the environment, where the chemical(s) might
travel to, and who might become potentially exposed to the chemical(s), and at what level.
Differences in these scenarios all influence the relative contribution and significance a chemical
release may make toward potential risk and potential health and environmental impacts. The risk
or chance of harmful effects to human health or to ecological systems resulting from exposure to
a chemical release depends on many factors, including 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. To account for these factors related to risk and to help
quantify the relative potential impacts that may result from chemical releases, adjustments must
be made in a consistent manner to assign components of potential risk to each environmental
media-specific release of each toxic chemical.
The RSEI method uses models and computations that incorporate these components of risk and
performs a separate screening-level assessment for each unique combination of a chemical, facility,
and environmental release. As a result, different numerical RSEI result values and metrics are
produced from modeling that can then be further analyzed in various ways to assess the potential
geographic impacts and relative potential hazard and risk of chemicals, facilities, industries, and
many other variables.
Risk-related result values (named RSEI Score in the RSEI model) are the generated scoring
metrics that are intended to be the primary descriptors of relative potential risk to human health
for use in comparative analysis. RSEI Scores are calculated as unitless values that account for the
magnitude of a chemical release, the fate and transport of the chemical within the environment,
the size and location(s) of potentially exposed populations, and the chemical's relative toxicity
weight. Chemical releases to air or water are modeled and are combined with exposure
assumptions and estimates, toxicity information, and population estimates to calculate these risk-
related scores.
The components that comprise the RSEI Score calculus (chemical toxicity, exposure, and
population) are multiplied together for score generation because each of these components of
potential risk is assumed to contribute in a multiplicative way to the overall magnitude of the
impact that may be posed by any given chemical release. Since RSEI Scores are unitless, they
are not physically meaningful measures of quantitative risk associated with a chemical release,
facility, or geographic area. RSEI Scores are rather approximate measures that are meant to be
compared to approximate measures for other chemicals (or facilities, geographies, etc.)
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calculated using the same methodology. These risk-related score results (along with other RSEI
model results such as RSEI Hazard) are thus relative and are by their nature not intended to have
absolute meaning. Regarding RSEI Scores generally, they are calculated to be linearly related
where a computed RSEI Score value that is 10 times higher than another RSEI Score value
suggests that the potential for risk-related impacts is 10 times higher. This same concept also
applies to RSEI Hazard values when comparing from a relative hazard-based perspective.
As relative values, RSEI result values can be used only in comparisons to other similar RSEI
result metrics at different points in time, or in identifying the relative size of contributing factors
or components that make up their RSEI-modeled value(s). Because they are inherently relative,
RSEI Scores or RSEI Hazard values are often expressed as percentiles, as in, "This chemical is
in the 90th percentile for RSEI Score nationally", which means that 90 percent of all modeled
chemicals nationwide have lower scores than this chemical, and this chemical may warrant
further investigation due to its potential for human health impacts.
Both RSEI Score and RSEI Hazard provide greater insight on potential impacts than
consideration of chemical release quantities alone. The U.S. EPA developed the RSEI model in
the early 1990s specifically to enable characterization of trends in the potential hazards and
relative potential risks of chemical releases from TRI reported information, and to compare and
help identify geographic areas, industry sectors, and chemical releases that may be associated
with significant potential human health risks. It should be emphasized, however, that RSEI
model results are not a detailed site-specific or conventional risk assessment. Formal risk
assessments are more detailed and accurate, however, they are also complicated, time
consuming, and resource intensive, often requiring specific data and other information that are
not always available, and the results are often limited in scope and geographic area.
The RSEI methodology augments chemical quantities released to the environment with toxicity
and exposure considerations, but does not address all of the potential factors and components
that would have to be included and analyzed in a more comprehensive evaluation and
characterization of risk. The values generated by the RSEI model are for comparative purposes
and only meaningful when compared to other results produced by RSEI. RSEI Scores do not
describe a level of risk (such as the number of excess cancer cases), in which a more refined
assessment using different tools and information would be needed to determine actual risks and
the significance of the risks. To this effect, the RSEI model is not a stand-alone source of
information for making conclusions or decisions about the risks posed by any particular facility
or environmental release of a TRI chemical. RSEI model results should only be used as a
potential starting point to identify situations of potential concern that may warrant further
investigation.
RSEI model results, however, do offer a screening-level, risk-related perspective for relative
comparisons of potential impacts resulting from certain waste management activities of TRI-
listed toxic chemicals. The generated results serve as a practical means that can be used to
identify general trends in the ways in which potential risk-related impacts from TRI-listed
chemicals differ over time, or from one geography to another. RSEI Scores (as well as with other
RSEI model results such as pounds-based and hazard-based results) are also designed to be
additive so that users can combine and disaggregate results for different types of groups (such as
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chemicals, facilities, industry sectors, geographies, environmental media, etc.) and different
aggregation levels for comparative purposes. For instance, when a facility has a relatively high
RSEI Score, it indicates that aggregated modeled waste management activities involving TRI
chemicals from the facility may pose greater potential risk than from a facility that has a
relatively lower RSEI Score in comparison.
RSEI enables one to quickly and easily screen large amounts of chemicals and chemical
emissions and transfer data and importantly, provides an ability to analyze the relative difference
in how different quantities of chemicals being released, facilities, and industry sectors contribute
to potential adverse human health impacts within different demographics and geographic
regions. The utility of the RSEI method itself is very flexible, fit-for-purpose, and can be
implemented in many ways. The use of the RSEI model is not limited to any specific set of
chemicals; in principle, the adaptable method can model any chemical if toxicity data,
physicochemical properties, waste management activity quantities, and release and transfer
locations are known or can be estimated. To the extent possible, the RSEI model is based on
existing EPA approaches, guidelines, data, and models, to minimize duplication of effort and to
maximize consistency with other Agency efforts to evaluate human health and environmental
impacts. The current version of the RSEI model tracks changes in human health impacts
resulting from chronic exposure to TRI-listed toxic chemicals. Ultimately, the model may be
expanded to track acute human health and acute and chronic ecological impacts.
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ES-2. General Description of the RSEI Model
The RSEI model calculates numeric values that reflect potential relative risk-related health
impacts that may be posed by TRI chemicals. These calculated values do not provide absolute
estimates of risk or benchmark concern levels and can only be interpreted as relative measures to
be compared with other such calculated values (reflecting the direction and the general
magnitude of changes at different points in time when analyzing trends, or comparing
contributing factors and variables when screening for situations of potential concern).
The model uses reported data and information associated with each TRI toxic chemical release1
reporting form (such as the amount of a chemical released to air or the amount transferred off
site for further waste management) to estimate potential risk-related impacts that may result. The
risk-related impacts potentially posed by a TRI chemical are a function of chemical toxicity, the
fate and transport of the chemical in the environment, the pathway, route, and extent of exposure,
and the number of the potentially exposed population.2
Most RSEI model results are designed to be additive so that users can combine and disaggregate
results for different types of groups (such as chemicals, facilities, industry sectors, geographies,
environmental media, etc.) and different aggregation levels. For example, the RSEI model result
for a given county is the sum of all the RSEI model results that make up that county. The sum of
the RSEI model results for all of the counties in a given state is the RSEI model result for that
state. In this way, users can rank by one dimension, such as by state, and then drill down into the
list of county results to see which counties account for the majority of the modeled result for that
state. Users can examine RSEI model results for one year or over a period of time. All of the
RSEI facility-level model results, including pounds-based results, hazard-based results, and risk-
related results are proportional and can be combined in the same way; however, concentration
and toxicity-weighted concentration results that are distributed in the RSEI Geographic
Microdata are not additive in this way.
RSEI does not perform a detailed or quantitative risk assessment, but offers a screening-level,
risk-related perspective for relative comparisons of certain waste management activities (e.g.,
releases to the environment) of TRI chemicals. The RSEI model does not estimate actual risk to
individuals. RSEI results are only meaningful when compared to other results produced by RSEI.
The current version of the RSEI model calculates risk-related results for the air and water release
pathways only (i.e., from stack and fugitive air emissions, discharges to receiving streams or
waterbodies, transfers off site to publicly owned treatment works (POTW) facilities, and
transfers off site to incineration). Hazard-based results are available for other kinds of waste
1 Release means any spilling, leaking, pumping, pouring, emitting, emptying, discharging, injecting, escaping,
leaching, dumping, or disposing into the environment (including the abandonment or discarding of barrels,
containers, and other closed receptacles) of any toxic chemical.
2 The RSEI method is focused on general populations: individuals, particularly highly exposed or susceptible
individuals are not the focus of the model.
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management activities for TRI chemicals and chemical categories with assigned toxicity data.3 In
cases where toxicity data are not available, only pounds-based results can be viewed.
ES-2.1 Geographic Basis of the RSEI Model
The RSEI model relies on the ability to locate facilities, environmental releases, and people
geographically and attribute characteristics of the physical environment such as meteorology and
hydrography on surrounding areas once they are located to estimate potential exposure and
relative impacts. In order to accomplish this, the RSEI model describes the U.S. and its
territories4 using a grid-based system. For each grid cell in the grid system, a location "address"
in terms of (x,y) coordinates is assigned based on latitude and longitude (lat/long). Facility- and
chemical-specific data retrieved from Agency-reported informational data sources (such as site
addresses and lat/long coordinates) are then geographically indexed to their corresponding grid
cell. A surface water network made up of connected flowlines2 is associated with the grid system
and used for water modeling.
To locate population geographically, the RSEI model uses decennial U.S. Census data for 1990,
2000, and 2010 at the Census block level. These data5 are used to create detailed age-sex-defined
population groups for each of the Census blocks for 1990, 2000, and 2010. The following
population groups are used in the model:
• Males Aged 0 through 9 years
• Males Aged 10 through 17 years
• Males Aged 18 through 44 years
• Males Aged 45 through 64 years
• Males Aged 65 Years and Older
• Females Aged 0 through 9 years
• Females Aged 10 through 17 years
• Females Aged 18 through 44 years
• Females Aged 45 through 64 years
• Females Aged 65 Years and Older
3 TRI chemicals and chemical categories that have assigned toxicity data in RSEI account for 99% of the total
environmental release and transfer quantities reported to TRI in 2021.
4 The model also includes Puerto Rico, the U.S. Virgin Islands, Guam, American Samoa, and the Northern Mariana
Islands.
5 1990 U.S. Census data were provided by GeoLytics, Inc., East Brunswick, NJ. For 1990, not all of the variables
were available at the block level for the Continental U.S, Alaska, and Hawaii. For those variables that were only
available at the block group level, block group ratios were calculated and applied to the data at the block level. For
2000 and 2010, all of the required data were available at the block level. For the U.S. Virgin Islands and the
territories, data from larger geographic units (block groups or county-equivalents) were used. For Puerto Rico, block
group data were used for 1990 and block level data for 2000 and 2010.
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Because the Census block boundaries change between decennial Census years, each set of
Census block level data is first transposed onto the RSEI model grid, which is unchanging, using
an area-weighted method. Once populations for 1990, 2000, and 2010 are placed on the grid, the
RSEI model uses a linear interpolation for each grid cell to create annual estimates of the
population sizes for each year between 1990 and 2000, and again between 2000 and 2010. The
straight-line plot between 1990 and 2000 is extrapolated backward to estimate population sizes
for 1988-89 and the straight-line plot between 2000 and 2010 is extrapolated forward to estimate
population sizes for the years after 2010.6
ES-2.2 RSEI Results
Once facilities and people are located on the RSEI model grid, three main components are used
to compute risk-related results. These components are:
• The quantity of chemicals released or transferred for further waste management,
• Adjustments for toxicity, and
• Adjustments for potential exposure and population size.
These components and the method used to combine them are described in the following sections.
Chemical Waste Management Activity Quantities. The RSEI model uses reported data and
information on facilities' on-site chemical releases to the environment and chemical waste
transfers from these facilities to off-site facilities (such as to publicly owned treatment works
(POTW) facilities and to off-site incinerators) to model RSEI risk-related results. Other kinds of
chemical waste management activities, such as underground injection or transfers off site to
recycling, are not currently modeled to produce risk-related results, but users can view RSEI
model hazard-based results (toxicity-weighted pounds) or pounds-based results for these other
waste management activity quantities. These chemical waste management activity quantities are
reported by facilities to EPA's TRI Program as mandated by section 313 of the Emergency
Planning and Community Right-to-Know Act and by section 6607 of the Pollution Prevention
Act. As of the 2021 TRI reporting year, there are over 800 chemicals and chemical categories
subject to reporting.
Adjustments for Toxicity. The RSEI model is based on current Agency methodologies for
assessing toxicity. RSEI reflects the toxicities of chemicals relative to one another using a
proportional and continuous system of numerical weights. Toxicity weights for chemicals
increase as their inherent ability to cause adverse health effect(s) increase. The method the
Agency has chosen for assigning toxicity weights to chemicals and to chemical categories is
clear and reproducible, based upon easily accessible and publicly available information, and uses
expert Agency-wide judgments to the greatest extent possible.
6 The decennial U.S. Census data for 2020 is now available and will be incorporated into the RSEI model
environment for a future model release.
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Toxicity values developed by Agency experts are used to differentiate the degrees and types of
adverse effects posed by chemicals. Oral slope factors (OSFs) and inhalation unit risks (IURs)7
provide information pertaining to toxicity for chemicals that may cause cancer. Reference doses
(RfDs) and reference concentrations (RfCs) provide toxicity information that typically pertain to
noncancer health effects.8 Where these values are not available from EPA, other data sources
may be used.
The following data sources are used, in the order of preference:
• EPA's Integrated Risk Information System (IRIS);
• EPA's Air Toxics Screening Assessment (AirToxScreen), formerly known as the
National Air Toxics Assessment (NATA), which generally obtains data from the other
sources listed in this list, but in some cases uses values derived by EPA's Office of Air
Quality Planning and Standards (OAQPS);
• EPA's Office of Pesticide Programs' (OPP) Acute and Chronic Reference Doses Table,
List of Chemicals Evaluated for Carcinogenic Potential, and Pesticide Reregi strati on
Eligibility Decisions;
• Final, published Minimal Risk Levels (MRLs) from the Agency for Toxic Substances
and Disease Registry (ATSDR);
• Final, published toxicity values from the California Environmental Protection Agency
(CalEPA), Office of Environmental Health Hazard and Assessment;
• EPA's Provisional Peer-Reviewed Toxicity Values (PPRTVs), which include toxicity
values that have been developed by EPA's Office of Research and Development (ORD),
Center for Public Health and Environmental Assessment (CPHEA), formerly known as
the National Center for Environmental Assessment (NCEA), Superfund Health Risk
Technical Support Center;
• EPA's Health Effects Assessment Summary Tables (HEAST); and
• Final Derived/Interim Derived Toxicity Weights estimated by EPA's Office of Pollution
Prevention and Toxics (OPPT).
RSEI collects the following four values for each chemical, where possible:
• Oral slope factors (OSFs) in risk per mg/kg-day,
• Inhalation unit risks (IURs) in risk per mg/m3,
• Reference doses (RfDs) in mg/kg-day, and
7 The oral slope factor represents an upper-bound (approximating a 95% confidence limit) estimate on the increased
cancer risk from a lifetime oral exposure to a chemical, usually expressed in units of proportion (of a population)
affected per mg/kg-day. The inhalation unit risk is the upper-bound excess lifetime cancer risk estimated to result
from continuous exposure to a chemical at a concentration of 1 (ig/m3 in air.
8 RfDs and RfCs are estimates (with uncertainty spanning perhaps an order of magnitude) of daily exposure [RfD],
or continuous inhalation exposure [RfC], to the human population (including sensitive subgroups) that are likely to
be without an appreciable risk of deleterious effects during a lifetime.
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• Reference concentrations (RfCs) in mg/m3
Each value is transformed into a toxicity weight, so that as the toxicity weight increases, the
potential for a toxic effect also increases. Each chemical is assigned up to four toxicity weights,
according to the availability of its RfC, RfD, IUR, and OSF.
The algorithms used to assign toxicity weights are shown below in Exhibit ES. 1.
Exhibit ES.l
Algorithms for Assigning Toxicity Weights
Route of Exposure
Inhalation
Oral
Type of Effect
Cancer*
IUR / 2.8e-7
OSF / le-6
Noncancer
3.5 /RfC
1 /RfD
*If the Weight of Evidence (WOE) Category is equal to C, each weight is divided by an additional factor of
10 to account for uncertainty.
The RSEI model results may use different toxicity weights, depending on the data. RSEI Hazard,
toxicity-weighted concentration (distributed in the RSEI Geographic Microdata), and RSEI
Score results use the higher cancer or noncancer toxicity weight for each exposure route (i.e.,
oral and inhalation), and if one exposure route is missing both toxicity weights, then the other
exposure route's toxicity weight is used. The RSEI Cancer Hazard and RSEI Cancer Score
results use only the cancer toxicity weights (i.e., the IUR for the inhalation exposure route or the
OSF for the oral exposure route), and do not use the RfC- or RfD-based toxicity weights even if
the IUR or OSF is missing. Similarly, the RSEI Noncancer Hazard and RSEI Noncancer Score
results only use the RfC- or RfD-based toxicity weights.
In addition, the toxicity-weighted concentration, RSEI Score, RSEI Cancer Score, and RSEI
Noncancer Score all use the inhalation route toxicity weight (RfC or IUR as appropriate) for the
portion of the publicly owned treatment works (POTW) transfer quantity that is estimated to be
released to air and the oral route toxicity weight (RfD or OSF as appropriate) for the portion of
the POTW transfer quantity that is estimated to be released to water.9 The three RSEI model
hazard-based results do not account for POTW partitioning, and use the oral toxicity weight
(RfD or OSF as appropriate) for the entire chemical transfer. Exhibit ES.2 below summarizes the
selection of toxicity weights for each kind of RSEI result.
9 To predict the environmental fate of TRI-listed chemicals and chemical categories transferred to POTWs, EPA
uses data on chemical removal efficiencies at POTWs and of the ultimate fate of the chemical amount removed. The
amount of the chemical(s) removed by POTWs is divided into the percentages removed by (1) sorbing to sludge, (2)
volatilizing into the air, or (3) degradation. The remaining amount (i.e., the portion not removed by POTWs) is the
percentage of the influent TRI chemical(s) that remains in POTW effluent untreated and ultimately discharged into
surface waters.
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Exhibit ES.2
Selection of Toxicity Weights for Each RSEI Model Result
RSEI Result
Air Releases
Water
Releases
Transfers to POTWs
Fill in Toxicity Data
Gaps?
RSEI Score
Higher of IUR
tox weight or
RfC tox weight.
Higher of OSF
tox weight or
RfD tox
weight.
For portion of transfer
that is estimated to be
released to air, use higher
of IUR tox weight or RfC
tox weight. For portion of
transfer that is estimated
to be released to water,
use higher of OSF tox
weight or RfD tox weight.
Yes. If a chemical has no
tox weight in one exposure
route, use tox weight from
other exposure route. For
instance, if a chemical has
no IUR or RfC tox weight,
use higher of RfD or OSF
tox weight for air releases.
RSEI Cancer
Score
IUR tox weight.
OSF tox
weight.
For air release portion,
use IUR tox weight. For
water release portion use
OSF.
No. If no route-specific
cancer tox weight, then
cancer score is zero.
RSEI
Noncancer
Score
RfC tox weight.
RfD tox
weight.
For air release portion,
use RfC tox weight. For
water release portion, use
RfD tox weight.
No. If no route-specific
noncancer tox weight, then
noncancer score is zero.
RSEI Hazard
Higher of IUR
tox weight or
RfC tox weight.
Higher of OSF
tox weight or
RfD tox
weight.
Higher of OSF tox weight
or RfD tox weight.
Yes. If a chemical has no
tox weight in one exposure
route, use data from other
exposure route.
RSEI Cancer
Hazard
IUR tox weight.
OSF tox
weight.
OSF tox weight.
No. If no route-specific
cancer tox weight, then
cancer hazard is zero.
RSEI
Noncancer
Hazard
RfC tox weight.
RfD tox
weight.
RfD tox weight.
No. If no route-specific
noncancer tox weight, then
noncancer hazard is zero.
Toxicity-
weighted
Concentration
Higher of IUR
tox weight or
RfC tox weight.
Higher of OSF
tox weight or
RfD tox
weight.
For portion of transfer
that is estimated to be
released to air, use higher
of IUR tox weight or RfC
tox weight. For portion of
transfer that is estimated
to be released to water,
use higher of OSF tox
weight or RfD tox weight.
Yes. If a chemical has no
tox weight in one exposure
route, use tox weight from
other exposure route. For
instance, if a chemical has
no IUR or RfC tox weight,
use higher of RfD or OSF
tox weight for air releases.
The distribution of toxicity values used for TRI chemicals and chemical categories corresponds
to a range of toxicity weights from approximately 0.02 to 1,400,000,000. However, toxicity
weights are not bounded. Continuous toxicity weights are expressed as values with two
significant figures.
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There are over 800 chemicals and chemical categories on the 2021 TRI toxic chemical list.
Toxicity weights are available for over 400 of these chemicals and chemical categories.10 TRI
chemicals and chemical categories that have assigned toxicity data in RSEI account for 99% of
the total environmental release and transfer quantities reported to TRI in 2021.
Adjustments for Potential Exposure and Population Size. Quantitatively, exposure potential
is estimated using a "surrogate" dose. To estimate the surrogate dose, a separate exposure
evaluation is conducted for each pathway-specific chemical waste management activity that
RSEI models to produce risk-related results. The exposure scenario evaluations use models that
incorporate data on chemical releases to the environment and chemical transfers off site,
physicochemical properties, and where available, site-specific characteristics to estimate the
ambient chemical concentrations in the environmental medium into which the chemical is
ultimately released. The ambient chemical concentrations are then combined with exposure
assumptions and estimates of the potentially exposed population size specific to age and sex.
The algorithms used for calculating surrogate doses rely on the ability to locate facilities and
people geographically on the RSEI grid as described earlier. While this approach to calculate
surrogate doses uses EPA exposure assessment guidelines to evaluate exposure potential, the
RSEI-modeled surrogate doses should not be definitively construed as an actual numerical dose
resulting from TRI chemical waste management activities. Limited site-specific data and the use
of screening-level modeling that relies on default values and conservative assumptions for many
input parameters prevent the derivation of an actual numerical dose. The purpose of this
methodology, rather, is to generate as accurate a surrogate dose as possible without conducting a
more detailed, in-depth, and resource-intensive exposure assessment. The estimates of surrogate
doses resulting from a given waste management activity involving a TRI chemical are relative to
the estimated surrogate doses resulting from other waste management activities included in the
RSEI model. Please note that not all chemical waste management activities and potential
resulting exposures from these activities are currently modeled in RSEI to produce risk-related
results.
Because of the multifunctional nature of the RSEI model, a variety of results can be generated.
The three main kinds of RSEI results are described below.
Exhibit ES.3
Description of RSEI Results
Risk-related results (scores)
Estimated Dose x Toxicity Weight x Potentially
Exposed Population
Hazard-based results
Pounds x Toxicity Weight
Pounds-based results
Waste management activity quantities
10 Elemental metals and metal compound categories (e.g., "lead" and "lead compounds") are separately listed for
TRI reporting purposes. RSEI combines these separate listings into one category (e.g., "lead and lead compounds").
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Risk-related results (scores). The exposure route-specific chemical toxicity weight, estimated
dose, and potentially exposed population components are multiplied to obtain a risk-related
score. The estimated (surrogate) dose is determined through pathway-specific modeling of the
fate and transport of the chemical through the environment, combined with population-specific
exposure factors and assumptions. The final score generated is a unitless value that is not
independently meaningful, but is a risk-related measure that can be compared to other risk-
related values calculated using the same methodology. If toxicity data or other data required for
risk-related modeling are absent or zero, or if the waste management activity or exposure
pathway is not currently modeled in RSEI, then the risk-related score generated is zero. RSEI
risk-related scores are only calculated for certain types of chemical releases and transfers (RSEI
modeled media). The current RSEI modeled media are for stack and fugitive air emissions,
discharges to receiving streams or waterbodies, transfers off site to publicly owned treatment
works (POTW) facilities, and transfers off site to incineration.
• RSEI Score- Product of estimated dose, potentially exposed population, and the higher
toxicity weight for each exposure route (see Exhibit ES.2 for details).
• Cancer Score- Product of estimated dose, potentially exposed population, and the IUR or
OSF toxicity weight (see Exhibit ES.2 for details).
• Noncancer Score- Product of estimated dose, potentially exposed population, and the
RfC or RfD toxicity weight (see Exhibit ES.2 for details).
Hazard-based results. Hazard-based results are calculated by multiplying the TRI chemical
waste management activity quantities (in pounds) by the appropriate chemical-specific toxicity
weight (the toxicity weight also depends on the exposure-specific pathway). The inhalation
toxicity weight is used for air releases of fugitive and stack emissions, and for transfers to off-
site incineration. The oral toxicity weight is used for water releases, land releases, and for
transfers to POTWs. For other types of chemical waste management activities (such as
recycling), the higher of the inhalation toxicity weight or the oral toxicity weight for the
chemical is used. For these hazard-based results, no exposure modeling or population estimates
are involved. If there is no toxicity weight available for the chemical, then the hazard-based
results are zero. Hazard-based results can be calculated for RSEI modeled media (RSEI Modeled
Hazard) or for any TRI waste management activity quantity. RSEI model hazard-based results
provide an alternative perspective to pounds-based results or full risk-related results, and are
especially valuable when necessary data for risk-related modeling are not available.
• RSEI Hazard- Product of TRI Pounds and the higher toxicity weight for each exposure
route (see Exhibit ES.2 for details).
• RSEI Modeled Hazard- Product of TRI Pounds and the higher toxicity weight for each
exposure route (see Exhibit ES.2 for details). Same as RSEI Hazard, but calculated for
RSEI modeled media only.
• Cancer Hazard- Product of TRI Pounds and the IUR toxicity weight or the OSF toxicity
weight (see Exhibit ES.2 for details).
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• Noncancer Hazard- Product of TRI Pounds and the RfC toxicity weight or the RfD
toxicity weight (see Exhibit ES.2 for details).
Pounds-based results. These results only reflect the waste management activity quantities as
reported to TRI and do not consider adjustments for toxicity or for exposure potential and
population size.
• TRI Pounds- Waste management activity quantity (e.g., chemical quantity released to
the environment or transferred off site for further waste management) in pounds per year.
This result includes quantities reported to all environmental media, whether or not they
are modeled by RSEI.
• RSEI Modeled Pounds- Waste management activity quantity (e.g., chemical quantity
released to the environment or transferred off site for further waste management) in
pounds per year, calculated only for RSEI modeled media, or the kinds of releases and
transfers that RSEI models.11
Once all of the RSEI results are calculated, they can be combined and analyzed in many different
ways. All of the results shown in Exhibit ES.3 are designed to be additive, so a result for a
specific set of given parameters is calculated by summing the results for all of the relevant
chemical waste management activity quantities.12 This method is very flexible, allowing for
countless variations in the resulting outputs for data user needs. For example, RSEI results can
be generated for various subsets of parameters (e.g., chemicals, industry sectors, geographic
areas) and compared to each other to assess the relative contribution of each subset to the total
proportional impact. Or, RSEI results for the same subset of parameters for different years can be
produced, to assess the general trends in pounds-based, hazard-based, or risk-related results and
potential impacts over time.
It must be reiterated that while relative differences in RSEI results compared between years
would imply that there have been changes in potential hazard-based or risk-related impacts, the
actual magnitude of any specific change or the reason for the differences may not be necessarily
obvious. Although the RSEI results themselves may be useful in identifying chemicals or
geographic areas with the highest relative potential for hazard or risk, the values themselves do
not represent a quantitative estimate or provide an exact indication of the magnitude of
associated individual hazard or risk.
11 For transfers off site to incineration, RSEI Modeled Pounds also reflects an adjustment made for double counting,
whereby quantities are dropped if the receiving facility is determined to also report to TRI.
12 Separate results can also be calculated for each exposure pathway component of an environmental release, such as
the drinking water or fish ingestion components of a given water release; however, in most user-facing applications
the RSEI model results are presented at the overall environmental release level.
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ES-2.3 Adjusting RSEI Results for Changes in TRI Reporting
A change in the number of chemicals and/or facilities subject to TRI reporting can occur through
several mechanisms. The addition to or deletion of chemicals from the TRI list of toxic
chemicals will occur as EPA responds to petitions or initiates its own regulatory actions such as
through the chemical listing or delisting process. The largest revision to the TRI chemical list
occurred in November 1994, when the Agency added 245 chemicals and chemical categories to
the existing list, effective for the 1995 TRI reporting year. Other revisions to the TRI list have
occurred since, with one of the latest revisions being the additions of certain per- and
polyfluoroalkyl substances (PFAS) to the TRI list by the National Defense Authorization Act.13
Compliance with TRI reporting has changed over time, which has led to more facilities
reporting. Increases in the number of reporting facilities may also occur as a result of changes in
TRI reporting requirements. For instance, chemical activity threshold requirements for subject
facilities were decreased over the first few years of TRI reporting, in addition to lowered
thresholds for persistent bioaccumulative toxic (PBT) chemicals. The TRI Program has also
expanded the set of industrial facilities required to report such as including electric utilities,
mining facilities, commercial hazardous waste facilities, solvent recovery facilities, and
wholesale chemical and petroleum terminal facilities. All of these modifications can act to alter
the total chemical waste management activity quantities reported to the TRI Program and in turn
result in alterations to the RSEI model's computation of the associated relative risk-based
impacts and result values.
Such TRI reporting changes would not necessarily represent a large change in actual
environmental impacts, but rather would reflect a broader understanding of the impacts that may
have always existed prior to the reporting requirement changes. To maintain comparability in the
calculated RSEI results over time for purposes of meaningful time-series analyses, the RSEI
model must be adjusted in some manner when such changes to TRI reporting occur. Otherwise,
differences in reporting requirements over the years may skew or bias RSEI generated results
(e.g., increases in the number of reportable chemicals may erroneously imply increases in
potential risk-related impacts). To allow data users this ability to pursue meaningful trend
analyses, the RSEI model maintains and provides lists of data elements and flags that denote
changes to TRI reporting requirement over the years (such as "core chemicals" lists and a "new
industry" flag) that can be used to create consistent time-series analytical results. In addition, the
RSEI model also produces specific datasets that can be then be viewed and filtered to research
RSEI results for which the TRI reporting requirements have not changed during a certain time
period.
When deletions from the TRI chemical list occur, RSEI's chemical database is modified to
remove all RSEI results from previous TRI reporting years of the deleted chemical(s). Also, the
data in the TRI database are subject to ongoing data quality review and corrective actions by
both EPA and by TRI-reporting facilities. As a result, yearly comparisons could be flawed if
13 Section 7321 of the National Defense Authorization Act for Fiscal Year 2020 immediately added certain PFAS to
the list of chemicals covered by TRI and provided a framework for additional PFAS to be added to TRI on an annual
basis.
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such corrective actions to reported data (e.g., withdrawn, revised, or newly submitted reporting
forms) were not included in each previous RSEI model year's results. Therefore, RSEI model
results are recomputed every year, for all TRI reporting years on an annual basis in order to
incorporate chemical deletions, modifications, and reporting requirement changes to the reported
data that are contained in the TRI database.
ES-2.4 RSEI Data Products
Users can access RSEI data products in a variety of ways. Facility-level RSEI results are
included in EPA data tools such as Envirofacts14, TRI Toxics Tracker, and the TRI National
Analysis. These results are also currently distributed in the EasyRSEI dashboard, accessible
through an internet browser15 or through https://www.epa.gov/rsei. The EasyRSEI dashboard
allows users to view and query RSEI model results for the last 10 years of TRI reporting. A
separate dashboard is also available for users who are interested in the full TRI reporting time
series (1988-current), and a RSEI Queries database for users comfortable in Microsoft Access is
also available for download.16 Users of the EasyRSEI dashboard can quickly and easily view
trends and rankings, and also filter by dimensions such as state, chemical, industry, year, etc.,
with no downloading required. Preformatted reports are also available for printing. Results can
be used for screening-level prioritization for strategic planning purposes, risk-related targeting,
pollution prevention opportunities, and for comparative trend analyses. Considerable resources
can be saved by conducting preliminary analyses with RSEI to identify risk-related situations of
potential concern, which may warrant further investigation and evaluation.
RSEI Geographic Microdata17 datasets are also produced at various levels of aggregation, spatial
geographies, and time periods for data users. These detailed air and water modeling results allow
for a flexible ability to analyze RSEI model outputs and results from a receptor-based
perspective of potentially impacted geographic areas. In contrast to the suite of RSEI results that
are distributed in tools such as EPA's EasyRSEI dashboard and in EPA's Envirofacts data
warehouse,18 RSEI Microdata are not aggregated and assigned to the facility level, but rather
include values resulting from where the chemical releases and potential impacts may occur. With
the Microdata, geographic-based analyses are more intuitive; a state ranking is based on the
potential impacts that may occur within the geographic confines of each state, regardless of
where the chemical releases or generated wastes originate. The Microdata are provided for
looking at small-scale geographic areas, and users can examine the potential impacts that
14 RSEI results are located in TRI Search, a query built into the TRI section of Envirofacts
(https://www. epa. gov/enviro/tri-search). under the heading "Risk Screening" after performing a search.
15 EasyRSEI is available at https://edap.epa.gov/public/extensions/EasvRSEI/EasvRSEI.html. The All Years version
is available at https://edap.epa.gov/public/extensions/EasvRSEI AllYears/EasvRSEI AllYears.html.
16 RSEI Queries and other data products are available at https://www.epa.gov/rsei/wavs-get-rsei-results.
17 The use of the word "Microdata" throughout this document should be interpreted to be synonymous and
interchangeable with the words "RSEI-GM" and "Geographic Microdata".
18 In order to make the RSEI results small enough to work with in EasyRSEI and other applications, potential
impacts from certain waste management activities involving TRI chemicals are summed and attributed to the
facilities of origin.
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environmental releases of toxic chemicals from multiple facilities may have on a particular area
from a relative risk-related perspective. RSEI Microdata are made available in a variety of data
and file formats to meet analytical needs. More information about downloading the RSEI
Microdata can be found on the RSEI website.
As noted above, users can evaluate RSEI information using a number of variables, such as
chemical, environmental medium, geographic area, or industry. For instance, the following types
of questions can be investigated:
• How do industry sectors compare to one another from a relative risk-related perspective?
• What is the relative contribution of chemicals within a given industry sector?
• What exposure pathways for a particular chemical pose the greatest potential risk-related
impacts?
More information regarding RSEI data products is available on the RSEI website. Complete
documentation, frequently asked questions, and contact information are all posted on the site.
Periodic updates and troubleshooting information are also available for users.
ES-2.5 How the Toxicity Data Used in RSEI Differ from EPCRA Section 313
Statutory Listing Criteria
As previously described, the RSEI model uses TRI chemical reporting data as one of the primary
data sources. However, it is important that the public not confuse the use of the RSEI model as a
screening-level tool for investigating relative risk-based impacts pertaining to the waste
management activities of TRI chemicals, with the very different and separate regulatory activity
of listing/deli sting chemicals on the TRI chemical list using statutory criteria.
One of the goals of the RSEI method and model is to use data reported to the Agency to
investigate the relative risk-based impacts of certain waste management activities (e.g., releases
to the environment) of toxic chemicals. The RSEI model differentiates the relative toxicities of
TRI-listed chemicals and weights them in a consistent and transparent manner. The weighting of
each chemical reflects its toxicity only relative to other chemicals that are included in the RSEI
model. Toxicity is not compared to some "absolute" or benchmark criteria as is required when
adding or removing a chemical from the TRI list of toxic chemicals established under section
313 of the Emergency Planning and Community Right-to-Know Act (EPCRA). In addition, the
EPCRA statutory criteria used for listing and delisting TRI chemicals also consider acute and
chronic human toxicity, as well as environmental toxicity, as well as considerations for multiple
effects and the severity of those effects.
Because of these differences, the toxicity weightings used in the RSEI model cannot be used as a
scoring system for evaluating listing/delisting decisions under EPCRA section 313. The RSEI
model does not attempt to reflect the statutory criteria for these TRI-listed chemicals and
chemical categories.
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ES-3. Important Caveats Regarding the RSEI Model
The RSEI model is a screening-level tool that provides different perspectives in assessing the
potential impacts of certain waste management activities involving TRI chemicals. Risk-related
results (scores), toxicity-weighted concentrations, and chemical concentrations are available for
certain environmental exposure pathways (i.e., air and water releases), and hazard- and pounds-
based results are available for other chemical waste management activities. RSEI results
combine estimates of chemical toxicity, exposure potential, and potentially exposed populations
to provide for relative risk-related comparisons, but do not provide a detailed or quantitative
assessment of risk. Resulting risk-related scores (RSEI Score) are also not designed as a
substitute for more comprehensive, inclusive, and site-specific risk assessments. There are a
number of important caveats associated with each component of the RSEI model, as described in
the following sections.
Release Component. The following caveat should be considered regarding the TRI data and
information incorporated into the model:
• The RSEI model uses facility-reported TRI data, which may contain some reporting
issues and errors. The TRI Program does not alter or change any reported data in the
official TRI database until the reporting facility submits an official correction to their TRI
chemical reporting form. In certain instances, reporting errors by facilities result in
modeled results so large as to overwhelm annual RSEI values. In these cases where a
reporting error has clearly been made, the reporting error (e.g., chemical release quantity)
is retained in the RSEI data, but the hazard-based and risk-related scores are set to zero.
The reporting error is then further investigated by EPA for data quality, compliance,
and/or enforcement purposes.
Toxicity Component. The following caveats should be considered regarding the toxicity
component of the model:
• The toxicity weights used are not designed to (and may not) correlate with EPCRA
section 313 statutory criteria used for listing and delisting chemicals on the TRI chemical
list. RSEI risk-related model results account for estimated potential exposure and may not
correlate with regulatory listing or delisting decisions.
• The RSEI model currently only addresses chronic human toxicity (cancer effects and
noncancer effects, such as developmental toxicity, reproductive toxicity, neurotoxicity,
etc.) associated with chronic (long-term) exposure and does not address concerns for
either acute human toxicity or for environmental toxicity.
• RSEI toxicity weights are based upon the single, most sensitive chronic human health
endpoint for inhalation or oral exposure pathways, and do not reflect severity of effects or
multiple health effects.
• Estimated RfDs and RfCs for noncancer effects incorporate uncertainty factors which are
reflected in the RSEI toxicity weights that are based upon these values.
• Toxicity weights for TRI-listed chemical categories are based on the toxicity of the most
toxic member of the chemical category. One exception to this is for the polycyclic
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aromatic compounds (PACs) chemical category, where the toxicity weight is based on
18% of the toxicity for benzo(a)pyrene, its most toxic member. This is based on
speciation information and follows the method used by EPA's National Air Toxics
Assessment (NATA) evaluation for polycyclic organic matter (POM).19
• Several significant assumptions are made regarding metals and metal compounds,
because important data regarding these chemicals are not subject to TRI reporting. Metals
and metal compounds are assumed to have the same toxicity weight, although the toxicity
of some metal compounds may be lower or higher. Metals and metal compounds are
assumed to be released in the valence (or oxidation state) associated with the highest
chronic toxicity. There are two exceptions to this: (1) For chromium and chromium
compounds, it is assumed that facilities may release some combination of hexavalent
chromium and trivalent chromium. Facility-specific and industry-level estimates specific
to 4- or 6-digit North American Industry Classification System (NAICS) codes from the
2017 National Emissions Inventory (NEI) are used to estimate the fraction of each type.20
As trivalent chromium has a very low toxicity, only the hexavalent chromium fraction is
modeled in RSEI, using a toxicity weight specific to that valence state; and (2) For
mercury and mercury compounds, toxicity for the oral pathway is based on methyl
mercury, and toxicity for the inhalation pathway is based on elemental mercury.
• Being that the physical form of released metals or metal compounds can affect toxicity,
reasonable assumptions are made regarding the most likely form of releases (e.g., the
noncancer toxicity weight for chromic acid mists and dissolved hexavalent chromium
aerosols is much higher than for hexavalent chromium particulates, but releases of these
chemicals as mists and acid aerosols are not expected to be typical so the toxicity weight
for the inhalation of hexavalent chromium particulates is used). RSEI data users need to
consider these assumptions, and whether the gathering of additional data is warranted
when examining model results for metals and metal compounds.
Exposure Component. The following caveats should be considered regarding the exposure
component of the model:
• Like other screening-level scenario evaluation models, RSEI estimates potential exposure
levels. It does not yield actual on-the-ground exposures. The RSEI model provides
estimated air concentrations in each affected grid cell and surface water concentrations in
each affected stream segment/flowline.
• The model uses some generic assumptions for facility air releases: default median stack
heights, stack diameters, and exit-gas velocities related to 4- or 6-digit NAICS codes or a
nationwide median used when facility-specific data are unavailable. For large facilities
19 The documentation on modeling polycyclic organic matter (POM) from EPA's NATA model can be found in the
Technical Methods Document at https://www.epa.gov/sites/default/files/2015-10/documents/2005-nata-tmd.pdf .
RSEI assumes that PAC emissions reported to TRI are most like NATA's "7-PAH" category.
20 A default assumption of 34% hexavalent, 66% trivalent chromium speciation is used where facility or NAICS-
based data are unavailable. The NEI is available at https://www.epa.gov/air-emissions-inventories/2017-national-
emissions-inventorv-nei-data
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with multiple stacks, the median height for all stacks is used as the stack height for the
entire facility.
• In the current version of the RSEI model, only air and surface water releases are
modeled.
• The model does not account for population activity scenarios or patterns.
• The model does not account for indirect exposure such as air deposition of chemicals to
other media, or absorption of chemicals through the skin.
Population Component. The following caveats should be considered regarding the population
component of the model:
• Population values for non-decennial years are estimated based on linear interpolations at
the block level between the 1990 and 2000 and between the 2000 and 2010 U.S. Census
datasets, and on extrapolation back to 1988 and forward to 2021.
• Drinking water populations are estimated by using the total drinking water populations
associated with individual downstream drinking water intakes. Estimated populations for
the fish ingestion pathway are based upon U.S. Fish and Wildlife Service surveys.
• Because RSEI results reflect changing population size at the local level, a facility's
relative contribution to potential impacts could increase or decrease even without changes
in its chemical waste management quantities over time. While the model is designed to
reflect the overall risk-related impacts on the local population, such population changes
should be considered when examining a facility's environmental management and
performance practices.
ES-4. New Features in Version 2.3.11
• Includes TRI data and information from reporting years 1988 to 2021.
• Toxicity weights have been updated with the most recent toxicity data.
• Modeling parameters for stack air releases have been updated with the most recent
triennial 2017 National Emissions Inventory (NEI) data.
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Chapter 1: Organization of this Document
1. Organization of this Document
Chapter 2 of this document gives a brief description of the RSEI methodology and model, as
well as a discussion of their overall strengths and limitations. Chapter 3 describes the TRI data
used in the model. Chapter 4 describes the methods used to adjust the data for chemical toxicity,
and Chapter 5 provides a discussion of the geographic basis of the model, as well as pathway-
specific descriptions of adjustments made for exposure potential and population size. Chapter 6
presents the equations and calculus for deriving RSEI results, Chapter 7 describes how the RSEI
model results and data products are disseminated, and Chapter 8 lists references cited throughout
the document.
There are also six technical appendices that accompany this methodology document and provide
additional information on the data used in the RSEI model. The technical appendices are as
followed:
Technical Appendix A - Toxicity Weights for TRI Chemicals and Chemical Categories
Technical Appendix B - Physicochemical Properties for TRI Chemicals and Chemical
Categories
Technical Appendix C - Derivation of Model Exposure Parameters
Technical Appendix D - Locational Data for TRI Reporting Facilities and Off-site Facilities
Technical Appendix E - Derivation of Stack Parameter Data
Technical Appendix F - Summary of Differences between RSEI Data and the TRI National
Analysis
In addition, other background and supporting information are also made available on the RSEI
Documentation and Help web page. For example, Analyses Performedfor the Risk-Screening
Environmental Indicators contains three parts: Part A describes the result of a ground-truthing
analysis performed to determine the accuracy of the air pathway modeling; Part B contains
additional analyses performed on the air pathway to determine optimal modeling parameters; and
Part C describes the results of an analysis of Standard Industrial Classification (SIC) code-based
stack parameter data. Developing the Risk-Screening Environmental Indicators describes the
development of the model, and outlines options that were considered for several important
aspects of the method. The RSEI documentation and help webpage also contains historical
reference documents, a bibliography, data dictionary, and access to other information for data
users.
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Chapter 2: General Description of the RSEI Model
2. General Description of the RSEI Model
2.1 General Description
The RSEI model is a screening-level tool that assesses the potential impacts of certain waste
management activities of TRI-listed toxic chemicals (e.g., from releases to the environment)
from pounds-based, hazard-based, and risk-related perspectives. A basic outline of the modeling
approach is illustrated in Exhibit 2.1.
Three main components are used in the model to calculate results:21
• The TRI database, maintained by EPA, provides the data on the quantities of TRI-listed
chemicals released to air, water, disposed of to land, and transferred off site to facilities
for further waste management activities for more than 800 toxic chemicals and chemical
categories. Reporting by facilities to the TRI Program began in 1987, and has continued
each year since then (RSEI uses TRI reporting data beginning in reporting year 1988).
Chemical waste management activity quantities (e.g., releases to the environment) are
reported to the TRI Program in pounds per year.
• Toxicity weights are assigned to each chemical for which adequate toxicity data are
available. These weights are assigned using quantitative toxicity values developed by
EPA scientists and additional qualitative assessments.
• Exposure and population modeling are performed for the air and surface water
pathways to model the movement of each chemical release through the environment to
the exposed population. A surrogate (potential) dose, the amount of chemical that a
human may ingest or inhale, is then estimated. The estimation of a surrogate dose allows
comparisons across exposure pathways. Then the population exposed to each chemical
release is estimated using decennial U.S. Census data.
RSEI produces three main kinds of results; risk-related, hazard-based, and pounds-based. Risk-
related scores require the most information to calculate (e.g., environmental fate and transport,
toxicity, chemical release and transfer quantities, and population exposure information) and are
not available for all kinds of waste management activities reported to TRI. Hazard-based results
are calculated using only chemical release and transfer quantities and toxicity information, and
are available for all chemical waste management activities. Pounds-based results are simply the
chemical waste management activity quantities reported to TRI and require no additional
information or data.
All of these RSEI results are designed to be additive so that users can combine and disaggregate
results by chemical, facility, industry, region, etc. For instance, the score for a facility is the sum
of the scores for all of the modeled releases and transfers from that facility. The sum of the
scores for all of the facilities in a state is the score for that state. In this way, users can rank by
21 The method is focused on the general population; individuals, particularly highly exposed or susceptible
individuals, are not the focus of the model. Furthermore, worker exposures are not addressed.
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one dimension, such as by state, and then drill down into the list of facility scores in that state to
see which facilities account for the majority of the score. Users can examine results for groups of
chemicals or facilities, for one year or over a certain period of time. All of the results, including
pounds-based results and hazard-based results, are proportional and work in the same way.
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Exhibit 2.1
RSEI Modeling Approach
(1> indicates media code 1: Fugitive (non-point) Air Emissions
(2> indicates media code 2: Stack (point) Air Emissions
(750> indicates media code 750: Off-site Transfers to Incineration (Thermal Treatment)
(754> indicates media code 754: Off-site Transfers to Incineration (Insignificant Fuel Value)
(6)
indicates media code 6: Discharges to Publicly Owned Treatment Works (POTW)
(3> indicates media code 3: Discharges to Receiving Streams or Water Bodies
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Exhibit 2.2
Description of RSEI Results
Risk-related results (scores)
Estimated Dose x Toxicity Weight x Potentially
Exposed Population
Hazard-based results
Pounds x Toxicity Weight
Pounds-based results
TRI Pounds Released/Transferred
Risk-related results (scores). The exposure route-specific chemical toxicity weight, estimated
dose, and potentially exposed population components are multiplied to obtain a risk-related
score. The estimated (surrogate) dose is determined through pathway-specific modeling of the
fate and transport of the chemical through the environment, combined with population-specific
exposure factors and assumptions. The final score generated is a unitless value that is not
independently meaningful, but is a risk-related measure that can be compared to other risk-
related values calculated using the same methodology. If toxicity data or other data required for
risk-related modeling are absent or zero, or if the waste management or exposure pathway is not
currently modeled in RSEI, then the risk-related score generated is zero. RSEI risk-related scores
are only calculated for certain types of TRI chemical releases and transfers (RSEI modeled
media). The current RSEI modeled media are for stack and fugitive air emissions, discharges to
receiving streams or waterbodies, transfers off site to publicly owned treatment works (POTW)
facilities, and transfers off site to incineration.
• RSEI Score- Product of estimated dose, potentially exposed population, and the higher
toxicity weight for each exposure route (see Exhibit 4.4 for details).
• Cancer Score- Product of estimated dose, potentially exposed population, and the IUR or
OSF toxicity weight (see Exhibit 4.4 for details).
• Noncancer Score- Product of estimated dose, potentially exposed population, and the
RfC or RfD toxicity weight (see Exhibit 4.4 for details).
Hazard-based results. Hazard-based results are calculated by multiplying the TRI chemical
waste management activity quantities released or transferred (in pounds) by the appropriate
chemical-specific toxicity weight (the toxicity weight also depends on the exposure-specific
pathway). The inhalation toxicity weight is used for air releases of fugitive and stack emissions,
and for transfers to off-site incineration. The oral toxicity weight is used for water releases, land
releases, and for transfers to POTWs. For other types of chemical waste management activities
(such as recycling), the higher of the inhalation toxicity weight or the oral toxicity weight for the
chemical is used. For these results, no exposure modeling or population estimates are involved.
If there is no toxicity weight available for the chemical, then the hazard-based results are zero.
Hazard-based results can be calculated for RSEI modeled media (RSEI Modeled Hazard) or for
any TRI waste management activity quantity. RSEI model hazard-based results provide an
alternative perspective to pounds-based results or full risk-related results, and are especially
valuable when necessary data for risk-related modeling are not available.
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• RSEI Hazard- Product of TRI Pounds and the higher toxicity weight for each exposure
route (see Exhibit 4.4 for details).
• RSEI Modeled Hazard- Product of TRI Pounds and the higher toxicity weight for each
exposure route (see Exhibit 4.4 for details). Same as RSEI Hazard, but calculated for
RSEI modeled media only.
• Cancer Hazard- Product of TRI Pounds and the IUR toxicity weight or the OSF toxicity
weight (see Exhibit 4.4 for details).
• Noncancer Hazard- Product of TRI Pounds and the RfC toxicity weight or the RfD
toxicity weight (see Exhibit 4.4 for details).
Pounds-based results. These results only reflect the waste management activity quantities
reported to TRI for each waste management activity, and do not consider adjustments for toxicity
or for exposure potential and population size. In some user-facing applications, there can be
more than one pounds value reported at any level of aggregation, and the RSEI Modeled Pounds
value will always be less than or equal to the TRI Pounds value.
• TRI Pounds- Waste management activity quantity (e.g., chemical quantity released to
the environment or transferred off site for further waste management) in pounds per year.
This result includes quantities reported to all environmental media, whether or not they
are modeled by RSEI.
• RSEI Modeled Pounds- Waste management activity quantity (e.g., chemical quantity
released to the environment or transferred off site for further waste management) in
pounds per year, calculated only for RSEI modeled media, or the kinds of releases and
transfers that RSEI models.22
All facility-level23 RSEI results are designed to be additive so that users can combine and
disaggregate results by chemical, facility, industry, region, etc. For instance, the score for a
facility is the sum of the scores for all of the modeled releases and transfers from that facility.
The sum of the scores for all of the facilities in a state is the score for that state. In this way, users
can rank by one dimension, such as by state, and then drill down into the list of facility scores in
that state to see which facilities account for the majority of the score. Users can examine results
for groups of chemicals or facilities, for one year or over a certain period of time. All of the
results, including pounds-based results and hazard-based results, are proportional and work in the
same way.
It must be reiterated that while relative differences in RSEI results compared between years
would imply that there have been changes in potential hazard-based or risk-related impacts, the
actual magnitude of any specific change or the reason for the differences may not be necessarily
22 For transfers off site to incineration, RSEI Modeled Pounds also reflects an adjustment made for double counting,
whereby quantities are dropped if the receiving facility is determined to also report to TRI.
23 The concentrations and toxicity-weighted concentrations distributed in the RSEI Geographic Microdata are not
additive in this way.
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obvious. Although the RSEI results themselves may be useful in identifying chemicals or
geographic areas with the highest relative potential for hazard or risk, the values themselves do
not represent a quantitative estimate or provide an exact indication of the magnitude of
associated individual hazard or risk.
2.2 Summary of the Strengths and Limitations of the RSEI Model
2.2.1 Strengths
The following are strengths of the RSEI model:
• The screening-level model provides important hazard-based and risk-related perspectives
from a relative standpoint regarding potential health impacts that may be posed by certain
TRI chemical waste management activities (e.g., releases to the environment).
• The model quickly organizes and evaluates complex and large streams of data. For
example, the air exposure model is combined with U.S. Census data to directly estimate
the size of potentially exposed populations and the magnitude of their potential exposure,
rather than assuming that all individuals surrounding a facility are equally exposed.
• The model allows for greatly increased speed in performing screening and targeting
analyses, thereby conserving resources for conducting more precise, site-specific risk
evaluations and impact assessment. In addition, its use as a priority-setting tool allows
resources to be focused in areas that may provide the greatest potential risk reduction.
• The model can perform single and multimedia analyses.
• Custom-tailored and ad hoc selections and filtering can be accomplished based upon a
wide range of parameters.
• This adaptable and fit-for-purpose method can model any chemical if toxicity data,
physicochemical properties, waste management quantities, and release and transfer
locations are known or can be estimated.
• The model considers both cancer and noncancer chronic human health endpoints.
• The RSEI method has been subject to repeated expert scientific peer review.
• The model's methodology, assumptions, caveats, and limitations are clear and
transparent. Complete and detailed documentation and supporting information of the
RSEI model are available and made available to the public.
2.2.2 Limitations
The following are limitations of the RSEI model:
• RSEI results do not provide users with quantitative risk estimates (such as excess cases of
cancer).
• RSEI results do not evaluate individual risk.
• The model does not account for all sources of toxic chemicals; it only accounts for the
TRI chemicals and chemical categories reported by facilities to the TRI Program.
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• The model also does not generate risk-related scores and other RSEI model results for all
TRI-listed chemicals and chemical categories.
• The model assumes that chemical air concentrations are the same for indoor and outdoor
exposures, and that potential populations are continuously exposed.
• Dermal and food ingestion pathways (other than fish consumption), and some other
indirect exposure pathways are not evaluated in the model.
• Health effects associated with short-term exposure to TRI-listed chemicals and chemical
categories are not addressed in the model.
• Ecological effects of these same chemicals are also not addressed in the model.
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3. TRI Data Used in the Model
The RSEI model uses facility information and data on toxic chemical waste management activity
quantities (e.g., releases to the environment, transfers to off-site locations) reported by facilities
to the Toxics Release Inventory (TRI). The TRI was established by Congress under section 313
of the Emergency Planning and Community Right-to-Know Act of 1986 (EPCRA),24 largely as a
result of the tragic accidental release of methyl isocyanate that occurred in December, 1984 at a
facility in Bhopal, India, and another serious accidental chemical release at a chemical
manufacturing plant in Institute, West Virginia, in August of 1985. These incidents underscored
growing demands by communities, public interest, and environmental organizations for
information on the toxic chemicals being used, managed, and released by facilities in their
communities. In response, EPCRA was enacted in 1986 and TRI reporting began for calendar
year 1987, with the first reports due by July 1st, 1988. This information was made publicly
available by EPA in June of 1989. In 1990, Congress passed the Pollution Prevention Act
(PPA)25 which required that additional information on toxic chemical waste management and
source reduction activities be reported to the TRI under section 6607.
The annual cycle of facilities reporting toxic chemical release forms and pollution prevention
and waste management information to EPA's TRI Program and EPA compiling and making the
information available to the public has continued ever since. The TRI data are made available to
the public, so that the public is kept aware of the quantities of the toxic chemicals that are
released or otherwise managed as waste in their communities, and empowered to make informed
decisions regarding the consequences of these waste management practices on human health and
the environment. Coupled with other provisions provided under EPCRA,26 information disclosure
helps increase the knowledge and access to information on chemicals at individual facilities and
helps support informed decision making to improve chemical safety and further protect public
health and the environment at all levels by industry, government, non-governmental
organizations, and the public.
EPA compiles the TRI data each year in the TRI database and makes it available through several
data access tools, including several through EPA's Envirofacts data warehouse. Subject TRI
facilities must report the quantities of routine and accidental releases, and releases resulting from
catastrophic or other one-time events of TRI-listed chemicals, as well as the maximum amount
of the chemical on site during the calendar year and the amount contained in wastes managed on
site or transferred off site. The TRI release and transfer data reported each year are the initial
source of quantitative data used for evaluating potential human exposure in the RSEI model.
As the TRI database itself is dynamically updated throughout the year, EPA has a data quality
policy that allows facilities reporting to the TRI to submit changes and corrections to their TRI
reporting forms at any time. The data in the TRI database are subject to ongoing data quality
24 Title III of the Superfund Amendments and Reauthorization Act of 1986, 42 U.S.C. § 11023, Public Law 99-499.
25 Title VI of the Omnibus Budget Reconciliation Act of 1990, 42 U.S.C. § 13101 et seq., Public Law 101-508.
26 For example, sections 311 and 312 of EPCRA require facilities that handle or store any hazardous chemicals to
submit inventory forms, as well as Material Safety Data Sheets (MSDSs) or Safety Data Sheets (SDSs) to state and
local officials and to local fire departments.
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review and corrective actions by both EPA and by TRI-reporting facilities. To limit the effects of
these continuous changes on RSEI modeling results, the RSEI model extracts data contained in
the TRI database at a given point in time each year in the autumn season following the July TRI
reporting deadline for toxic chemical release reporting forms. This extraction point is when EPA
"freezes" the TRI data contained in the TRI database and is a cutoff point that the Agency uses
so that it can prepare official EPA analyses of the TRI data such as for the TRI National Analysis
and other Agency deliverables. Changes to TRI reporting forms and submitted data during or
after this data freeze will continue to be processed by EPA, but will not be reflected in some of
the public data access tools or official EPA analyses until the end of the data freeze and/or until
the next update to the TRI access points or official EPA analyses occur.27 To ensure that each
RSEI model update is current on all revisions submitted to the TRI, data for all reporting years
are extracted once a year during this TRI data freeze, and added to the model, replacing the
previous data.28
Even though the TRI National Analysis and the RSEI model both use the same annual TRI data
freeze data, there are some important distinctions between the two Agency data products:
• RSEI performs considerable additional processing on the set of on-site and off-site
facilities, including quality assuring their locations, and identifying duplicate records of
off-site facilities.
• The TRI National Analysis adjusts its data to account for "double counting" of waste
management quantities29, where the RSEI model does not make that adjustment.
However, beginning with RSEI model version 2.3.5, RSEI does adjust transfers to off-
site incineration for possible double counting scenarios, by dropping any facility off-site
transfer quantities for incineration to a receiving facility that also reports to the TRI and
is in NAICS code 562211 (Hazardous Waste Treatment and Disposal).30
• Each year there may be several corrections to individual facility releases that may be
made in one database but not the other.
27 Updated TRI data contained in the TRI database are made available to the public the following spring season after
the data freeze occurs.
28 In reporting year 2018, RSEI data were updated twice (i.e., once with the autumn TRI data freeze dataset and once
with the following spring TRI update dataset). Data quality revisions made were for more recent reporting years, and
thus only the last five years were updated. RSEI data sets for that reporting year 2018 include "rsei2018" and
"rsei2018_spring" to reflect the two updates. RSEI Geographic Microdata and user-facing tools like EasyRSEI were
updated with the spring dataset, and the "rsei2018_spring" data set should be considered the final reporting year
2018 RSEI data.
29 Some reported quantities are counted twice for TRI aggregate total waste management activity statistics, where
"double counting" is when the chemical waste quantities are reported as both transferred off site by a facility for
further waste management and as managed on site by another TRI reporting facility (e.g., a TRI industrial facility
reporting sending a chemical waste off site for disposal to a regulated hazardous waste treatment, storage, and
disposal facility (TSDF) that also reports on-site disposal quantities of the same chemical to TRI).
30 See section 5.6 for more information.
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For more detail on these distinctions and any year-specific differences, please see Technical
Appendix F, "Summary of Differences between RSEI Data and the TRI National Analysis."
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4. Methods for Calculating Toxicity Weights
The EPCRA section 313 listing criteria establish several human toxicity endpoints that EPA
must consider when evaluating a chemical for addition to the TRI chemical list, including acute
toxicity, cancer or teratogenic effects, serious or irreversible reproductive dysfunctions,
neurological disorders, heritable genetic mutations, or other chronic health effects. Some
chemicals have toxicity data available for only one effect, while other chemicals will have
evidence of effects within several of these toxicity endpoints. The toxicity endpoints and their
definitions as prescribed in EPCRA section 313 are presented in Exhibit 4.1.
The RSEI model focuses on carcinogenicity and other types of toxic endpoints that are typically
associated with chronic exposures31 and relies heavily on current EPA methodologies for
assessing toxicity. The RSEI toxicity weighting methodology separately evaluates certain
exposure routes (inhalation and ingestion) and classes of effects (cancer and noncancer), and will
be continually updated to reflect any changes in these methodologies.
Exhibit 4.1
Toxicity Endpoints
Endpoint
Definition
Carcinogenicity
The ability of a chemical to produce cancer in animals or humans.
Heritable Genetic and
Chromosomal Mutation
The failure to transmit genetic information. This can involve at least
three separate modes of action: the 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).
Developmental Toxicity
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.).
Reproductive Toxicity
Interference with the development of normal reproductive capacity.
Chemicals can affect gonadal function, the estrous cycle, mating
behavior, conception, parturition, lactation, and weaning.
Acute Toxicity
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
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.
31 Chronic effects are those that generally persist over a long period of time whether or not they occur immediately
after exposure or are delayed. Chronic exposure refers to multiple exposures occurring over an extended period of
time, or a significant fraction of an individual's lifetime.
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Exhibit 4.1
Toxicity Endpoints
Endpoint
Definition
Neurotoxicity
Changes to the central and/or peripheral nervous system, which may be
morphological (biochemical changes in the system or neurological
diseases) or functional (behavioral, electrophysiological, or
neurochemical effects).
4.1 Toxicity Weighting Scheme for Carcinogens and Non-
carcinogens
The RSEI method uses a proportional system of numerical weights that reflect the toxicities of
chemicals relative to one another. The toxicity weights of chemicals increase as the toxicological
potential to cause chronic human health effects increases. The method EPA has chosen for
assigning toxicity weights to chemicals is clear, transparent, and reproducible, based upon easily
accessible and publicly available information, and uses expert EPA-wide judgments to the
greatest extent possible.
Factors that could be used to weight a chemical's toxicity include: the number of effects that the
chemical causes; the relative severity of the effect(s); the potency of the chemical to elicit the
effect(s); and the uncertainty inherent in characterizing the effect(s). The RSEI method focuses
on the latter two factors (potency and uncertainty inherent in characterizing effect(s)), and thus
considers both quantitative and qualitative elements to judge the relative toxicity of chemicals.
The types of data required and the method used to combine these data into toxicity weights are
described below.
4.1.1 Qualitative Data
Uncertainty reflecting the quality and adequacy of the data are incorporated into the underlying
toxicity values or in the toxicity weights themselves. The RSEI method is intended to
differentiate the relative toxicity of TRI chemicals in a uniform manner.
When evaluating the potential toxicity of a chemical to humans, toxicologists and risk assessors
use a variety of data, including epidemiological data, in vivo acute and chronic animal studies,
and in vitro and in silico toxicity testing methods. Together, these data form a body of evidence
regarding the potential for toxic chemicals to cause particular health effect(s). Experts can judge
qualitatively the strengths of this body of evidence when evaluating the probability of the
occurrence of the effect(s) happening in humans. Based on this scientific judgment, the chemical
is assigned a weight-of-evidence (WOE) classification. Weight-of-evidence schemes can be
designed to indicate whether a chemical either causes specific health effect(s) in general, or
specifically in humans.
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For cancer effects, the WOE system presented in this RSEI method relies on categorical
definitions from the 1986 EPA Guidelines for Carcinogen Risk Assessment (EPA, 1986a), which
are related to the potential for a chemical to be carcinogenic to humans.32 The cancer guidelines
define the six WOE categories shown in Exhibit 4.2 in which WOE categories A, Bl, and B2
(known and probable carcinogens) are combined in the RSEI model. The combination of the A
and B categories represents a modification of the Hazard Ranking System (HRS), which is used
by EPA's Office of Superfund Remediation and Technology Innovation (OSRTI) and is the
principal mechanism that the Agency uses to place uncontrolled waste sites on the National
Priorities List (NPL). Under the HRS scheme, A, B, and C categories are each considered
separately. This revision reduces the dichotomy between the A and B categories, a dichotomy
that may be inappropriate in the context of assigning toxicity weights. Also, combining
categories A and B stabilizes the model results against changes induced by chemicals switching
between the A and B designations. Class C chemicals (possible carcinogens) are assigned
toxicity weights by dividing the calculated toxicity weights by a factor of 10 (see Section 4.1.3),
because evidence that they cause cancer in humans is less certain. The choice of applying an
uncertainty factor is based on the advice of expert peer review and the HRS, where an order of
magnitude difference is an arbitrary uncertainty factor. Categories D and E are not considered in
this toxicity weighting scheme (i.e., no toxicity weights are assigned).
Exhibit 4.2
Weight-of-Evidence Categories for Carcinogenicity
Category
Weight-of-Evidence
A
Sufficient evidence from epidemiological studies to support a causal relationship
between exposure to the agent and cancer.
Bl
Limited evidence from epidemiological studies and sufficient animal data.
B2
Sufficient evidence from animal studies but inadequate or no evidence or no data from
epidemiological studies.
C
Limited evidence of carcinogenicity in animals and an absence of evidence or data in
humans.
D
Inadequate human and animal evidence for carcinogenicity or no data.
E
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.
Source: 51 FR 33996
32 EPA's cancer guidelines were updated in 2005 (EPA, 2005). The 2005 EPA WOE categories are not grouped by
letter as are the EPA's 1986 WOE categories. The new 2005 categories are translated into 1986 designations in the
following way:
• Carcinogenic to humans: A
• Likely to be carcinogenic to humans: B
• Suggestive evidence of carcinogenic potential: C
• Inadequate information to assess carcinogenic potential: D
• Not likely to be carcinogenic to humans: E
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For noncancer effects, WOE is considered qualitatively in the hazard identification step of
determining a reference dose (RfD) or a reference concentration (RfC). The WOE evaluation for
noncancer effects is different from the WOE evaluation for carcinogenic effects. The WOE
judgment for noncancer effects focuses on the dose or concentration where chemical exposure
would be relevant to humans (Dourson, 1993). That is, the focus of the WOE evaluation and the
expression of the level of confidence in the RfD or RfC is a judgment of the accuracy with which
the dose or concentration relevant to humans has been estimated. The WOE evaluation is
included qualitatively in the RfD or RfC, but does not affect its numerical calculation. Since
WOE has been considered in developing RfDs and RfCs, RSEI does not consider WOE
separately for noncancer effects.
4.1.2 Quantitative Data
Quantitative data on the relative toxic potencies of chemicals are needed for toxicity weighting.
These data generally result from analyses done during the dose-response assessment step of a
risk assessment. This step involves describing how the likelihood and severity of health effects
(the responses) are related to the amount and condition of exposure to a chemical (the dose
provided). Risk posed by exposure to a chemical cannot be described without quantitative dose-
response data. Dose-response data are derived from animal studies or, less frequently, from
studies in exposed human populations. There may be many different dose-response relationships
for a chemical if the chemical produces different toxic effects under different conditions of
exposure.
For cancer risk assessment, EPA has developed standard methods for predicting the
incremental lifetime risk of cancer per exposure of a chemical. EPA quantitatively models the
dose-response function of a potential carcinogen and typically provides estimates of oral slope
factors (OSFs) or inhalation unit risks (IURs). The OSF is a measure of cancer potency and
represents an upper-bound (approximating a 95% confidence limit) estimate of the slope of the
dose-response curve in the low-dose region for carcinogens. This estimate on the increased
cancer risk from a lifetime oral exposure to a chemical is usually expressed in units of proportion
(of a population) affected per milligram (mg) of chemical per kilogram (kg) of body weight per
day ((risk per mg/(kg-day)). The IUR is the upper-bound excess lifetime cancer risk estimated to
result from continuous exposure to a chemical at a concentration of 1 microgram (|ig) of
chemical per cubic meter (m3) in air (risk per (j,g/m3).33 Although the level of conservatism
inherent in the OSFs and unit risks varies by chemical, OSFs and IURs nonetheless are the best
readily available values that allow for a comparison of the relative cancer potency of chemicals.
RSEI's oral cancer toxicity weight (OTWc) represents how toxic a chemical is relative to a
chemical that produces a 1 in 1 million risk34 (above background, over a lifetime) at an average
lifetime daily dose of 1 mg/kg-day. If the OSF is greater than this arbitrary slope factor (i.e., the
chemical is more toxic than the arbitrary slope factor), the OTWc is greater than 1.
33 IUR values are expressed as risk per mg/m3 in calculating RSEI toxicity weights.
34 EPA programs commonly use a risk management range corresponding to an excess individual lifetime risk of
cancer of 1 in 10"6 to 10"4 (EPA, 1999a).
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OTWc=OSFk^mg 4])
10 kg-dayl mg
For noncancer risk assessment, data on dose-response are typically (though not always) more
limited; generally, a risk assessor evaluates dose compared to a reference dose (RfD) and a
concentration compared to a 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 [oral
exposure for RfD or continuous inhalation exposure for RfC] to the human population (including
sensitive subgroups) that is likely to be without an appreciable risk of deleterious [noncancer]
effects during a lifetime" (EPA, 1988a; EPA, 1990b). The units of RfD are mg/kg-day, while the
units of the RfC are mg/m3. A chemical's RfD or RfC is typically based on a no-observed-
adverse-effect level (NOAEL) or lowest-observed-adverse-effect level (LOAEL), 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 data reference for the chemical. By definition,
exposures below the RfD/RfC 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 measured response (e.g., severity and/or incidence of effect)
also increases (EPA, 1988a), but for a given exposure level above the respective RfD or RfC, the
specific probability or severity of an effect is not known. For purposes of the RSEI model, it is
assumed that noncancer risk varies as the ratio of the estimated exposure dose or concentration to
its respective RfD or RfC.
RSEFs oral noncancer toxicity weight (OTWnc) represents how toxic a chemical is relative to an
arbitrary dose of 1 mg/kg-day. If the RfD is greater than this arbitrary dose (i.e., the chemical is
less toxic than the arbitrary dose), the OTWnc is less than 1.
OTW„c= (Eq42)
RfD mg / kg-day
4.1.3 Method for Calculating Toxicity Weights
The RSEI method uses several different algorithms in assigning chemical toxicity weights. RSEI
model toxicity weights are designed to be proportional to a chemical's toxicity. The more toxic a
chemical is, the higher its toxicity weight.
Toxicity values for the inhalation pathway are typically expressed in units of exposure, that is,
mg of chemical per m3 of air. The RSEI toxicity weighting method uses standard adult human
exposure factors for inhalation rate (20 m3/day) and body weight (70 kilogram (kg)) to modify
toxicity values expressed in units of exposure. This adjustment means that different constants are
used to calculate the toxicity weights when inhalation toxicity values are used rather than oral
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toxicity values35 (3.5 versus 1.0 for non-carcinogens, and 2.8*10"7 versus 1*10"6 for carcinogens).
All RSEI toxicity weights are expressed as reciprocal units of mg/kg-day.
As these calculations show, noncancer toxicity weights are proportional to the reciprocal of the
RfD or RfC for the oral and inhalation exposure pathways, respectively. Cancer toxicity weights
are proportional to the OSF or IUR, for the oral and inhalation exposure pathways, respectively.
When multiplied by the surrogate dose estimated by RSEI, the risk-related scores calculated by
the model are unitless, and should be used only for comparative purposes within RSEI.
Exhibit 4.3 below shows the algorithms used to calculate RSEI chemical toxicity weights.
Chemicals classified as WOE category C are assigned the same algorithm as those in WOE
categories A and B, but the OSF or IUR is divided by an additional uncertainty factor of 10
because the evidence of cancer causation in humans is uncertain.
Exhibit 4.3
Algorithms for Assigning Toxicity Weights
Exposure Route
Inhalation
Oral
Type of Effect
Cancer*
IUR / 2.8e-7
OSF/ le-6
Noncancer
3.5/RfC
1 / RfD
*If the Weight of Evidence (WOE) Category is equal to C, each weight is divided by an additional factor of
10 to account for uncertainty.
4.2 Selecting the Final Toxicity Weights
Each chemical is assigned up to four toxicity weights, according to the availability of the RfC,
RfD, IUR, and OSF. The RSEI model results may use different toxicity weights, depending on
the data available.
RSEI Hazard, RSEI Score, and toxicity-weighted concentration use the higher cancer or
noncancer toxicity weight for each exposure route (i.e., oral and inhalation), and if one exposure
route is missing both toxicity weights, then the other exposure route's toxicity weight is used.
Cancer Hazard and Cancer Score results use only the cancer toxicity weights (i.e., the IUR for
the inhalation exposure route or the OSF for the oral exposure route), and do not use the RfC- or
RfD-based toxicity weights even if the IUR or OSF is missing. Similarly, the Noncancer Hazard
and Noncancer Score results only use the RfC- or RfD-based toxicity weights.
In addition, the RSEI risk-related results (RSEI Score, Cancer Score, Noncancer Score) and
toxicity-weighted concentration all use the inhalation route toxicity weight (RfC or IUR as
appropriate) for the portion of the publicly owned treatment works (POTW) transfer that
volatilizes during wastewater treatment and the oral route toxicity weight (RfD or OSF as
35 Non-carcinogens are multiplied by 3.5, derived from the inhalation rate and body weight adjustment (70/20).
Carcinogens are multiplied by 1/3.5, which, when multiplied by le-6, equals 2.8e-7.
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appropriate) for the portion of the POTW transfer that is released from the POTW as effluent.36
The three hazard-based results do not account for partitioning, and use the oral toxicity weight
(RfD or OSF as appropriate) for the entire chemical transfer. The table below summarizes the
selection of toxicity weights for each kind of RSEI result.
Exhibit 4.4
Selection of Toxicity Weights for Each RSEI Model Result
RSEI Result
Air Releases
Water
Releases
Transfers to POTWs
Fill in Toxicity Data
Gaps?
RSEI Score
Higher oflUR
tox weight or
RfC tox weight.
Higher of OSF
tox weight or
RfD tox weight.
For portion of transfer that
is estimated to be released
to air, use higher of IUR tox
weight or RfC tox weight.
For portion of transfer that
is estimated to be released
to water, use higher of OSF
tox weight or RfD tox
weight.
Yes. If a chemical has no
tox weight in one
exposure route, use tox
weight from other
exposure route. For
instance, if a chemical has
no IUR or RfC tox weight,
use higher of RfD or OSF
tox weight for air releases.
RSEI Cancer
Score
IUR tox weight.
OSF tox
weight.
For air release portion, use
IUR tox weight. For water
release portion, use OSF.
No. If no route-specific
cancer tox weight, then
cancer score is zero.
RSEI
Noncancer Score
RfC tox weight.
RfD tox weight.
For air release portion, use
RfC tox weight. For water
release portion, use RfD tox
weight.
No. If no route-specific
noncancer tox weight,
then noncancer score is
zero.
RSEI Hazard
Higher oflUR
tox weight or
RfC tox weight.
Higher of OSF
tox weight or
RfD tox weight.
Higher of OSF tox weight
or RfD tox weight.
Yes. If a chemical has no
tox weight in one
exposure route, use data
from other exposure route.
RSEI Cancer
Hazard
IUR tox weight.
OSF tox
weight.
OSF tox weight.
No. If no route-specific
cancer tox weight, then
cancer hazard is zero.
RSEI
Noncancer
Hazard
RfC tox weight.
RfD tox weight.
RfD tox weight.
No. If no route-specific
noncancer tox weight,
then noncancer hazard is
zero.
Toxicity-
weighted
Concentration
Higher oflUR
tox weight or
RfC tox weight.
Higher of OSF
tox weight or
RfD tox weight.
For portion of transfer that
is estimated to be released
to air, use higher of IUR tox
weight or RfC tox weight.
For portion of transfer that
is estimated to be released
to water, use higher of OSF
tox weight or RfD tox
weight.
Yes. If a chemical has no
tox weight in one
exposure route, use tox
weight from other
exposure route. For
instance, if a chemical has
no IUR or RfC tox weight,
use higher of RfD or OSF
tox weight for air releases.
36 Chemical-specific POTW removal and within-POTW partitioning rates are used to determine the portion of each
transfer to a POTW that degrades, adsorbs to sludge, or volatilizes. The remainder is assumed to be released from
the POTW as effluent.
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RSEI Hazard, RSEI Score, and toxicity-weighted concentration use the higher cancer or
noncancer toxicity weight for each exposure route (i.e., oral and inhalation), and if one exposure
route is missing both toxicity weights, then the other exposure route's toxicity weight is used. If
data are available for only one route, the same toxicity weight is applied for both routes,
provided there is no evidence the effects are route-specific or limited to the "portal of entry" into
the body. In rare instances, toxicity studies are available to show that a given chemical causes no
adverse effects via one exposure route; in these instances, a toxicity weight is assigned only to
the route that results in chronic human health adverse effects. Although assigning the same
weight to both routes is not an ideal method, it is appropriate for a screening-level tool like the
RSEI model.
Although a given chemical can cause several types of toxic effects, the RSEI model assigns the
chemical's toxicity weight based on the single most sensitive adverse effect for the given
exposure route (oral or inhalation). If the chemical exhibits both carcinogenic and non-
carcinogenic adverse effects, the higher of the associated cancer and noncancer toxicity weights
is assigned as the final toxicity weight for the chemical for the given route for RSEI Hazard,
RSEI Score, and toxicity-weighted concentration. For the other results, cancer and noncancer
effects are not mixed.
The approach of toxicity weighting based on the most sensitive adverse effect does not consider
differences in the type, number, or molecular target of the adverse effects posed by the chemical.
For example, liver toxicity is weighted in the same way that neurotoxicity is weighted; in
principle, chemicals causing a certain type of adverse effect could be assigned additional weights
if special concern(s) existed for that type of effect. However, applying such additional toxicity
weights would require a subjective evaluation and assignment of the severity of the adverse
health effects. Also, chemicals with a broad range of adverse health effects are weighted the
same as a chemical causing only one adverse effect. This approach may appear to underestimate
the risk of chemicals with a wide spectrum of adverse effects relative to chemicals with one or
few adverse effects. However, a chemical may only appear to demonstrate just one adverse effect
because there are no data on other toxic endpoints; thus, applying an additional weight based on
the number of endpoints may undervalue some poorly studied yet still hazardous chemicals. For
these reasons, the options for applying additional toxicity weights based on the number and
relative severity of toxic endpoints were not adopted for the RSEI method.
4.3 Chemical Categories
Along with information for individually-listed TRI chemicals, the TRI Program also collects
information for some chemicals as part of a chemical category listing. For example, the TRI
Program has separate reporting requirements for both elemental metals and for metal compound
categories, as well as reporting requirements for other chemical categories such as certain glycol
ethers, diisocyanates, and polycyclic aromatic compounds (PACs). In the case of most metal
compound categories, TRI regulations define the category members to include any unique
chemical substance that contains the named metal (e.g., lead, antimony, nickel, etc.) as part of
that chemical's composition, however, TRI reporting facilities do not need to disclose the
specific category member's identity in their TRI reporting forms.
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To simplify toxicity weight calculations due to the identity uncertainties behind the metal
compound category members that are reported to the TRI Program, the RSEI model combines
TRI-listed metal compound categories (e.g., nickel compounds) together with separately listed
TRI elemental metals (e.g., nickel) into one RSEI chemical category (e.g., nickel and nickel
compounds). Both nickel and nickel compounds are reported to TRI to reflect the quantities of
the nickel parent metal that is ultimately released to the environment, where in some cases,
reporting facilities may combine the two into a single report and report their release quantities to
TRI as nickel compounds. For RSEI modeling purposes, the model combines the reported metal
release quantities into one entry listed as "nickel and nickel compounds" and assumes that the
elemental metal and metal compound category members have the same toxicity weight. It is also
assumed that elemental metals and metal compounds are released in the valence or oxidation
state associated with the highest chronic toxicity value, although in reality it may be that certain
metal compounds may have differing associated chronic toxicity values due to environmental
releases of less toxic valence or oxidation states.
For both metal and non-metal TRI chemical categories, the RSEI model uses toxicity data for the
most toxic member of the chemical category to represent the toxicity of the entire chemical
category, with a few noted exceptions. The first exception is for chromium and chromium
compounds, for which the RSEI model assumes that TRI reporting facilities may release some
combination of both hexavalent chromium (Cr VI) and trivalent chromium (Cr III). Facility-
specific and industry NAICS-code specific estimates derived from the 2017 NEI are used to
estimate the speciation fraction of each type.37 As trivalent chromium has a very low toxicity,
only the hexavalent fraction is modeled in RSEI, using a toxicity weight specific to that valence
state (Cr VI). The second exception is for mercury and mercury compounds. The toxicity for the
oral pathway is based on methyl mercury, and the toxicity for the inhalation pathway is based on
elemental mercury. The third exception is for polycyclic aromatic compounds (PACs), for which
the RSEI model assumes that the overall toxicity for the chemical category is 18% of the toxicity
for benzo(a)pyrene, the most toxic member of the group. This value is based on the methodology
used by EPA's National Air Toxics Assessment (NATA) model for polycyclic organic matter
(POM), which is based on emissions factors for representative processes used in industries that
emit large amounts of POM. RSEI assumes that PACs emissions reported to TRI are most like
NATA's "7-PAH" category.38
The fourth exception is for dioxin and dioxin-like compounds. EPA first required reporting of
this chemical category beginning with reporting year 2000. Along with transfer information and
waste management activity quantities, TRI reporting facilities were required to report total
dioxin and dioxin-like compound quantities released (in units of grams) to each environmental
medium, as a single representative distribution of the 17 members of the chemical category
based on releases to all media combined or to a specific environmental medium. EPA changed
the reporting requirements for reporting year 2008, where reporting facilities were then subject to
provide more specific distributions of each individual member of the chemical category to each
environmental release medium, transfer off site, and waste management activity. These new
37 The NEI is available at https://www.epa.gov/air-emissions-inventories/national-emissions-inventorv-nei.
38 The documentation on modeling polycyclic organic matter (POM) from EPA's NATA model can be found in the
Technical Methods Document at https://www.epa.gov/sites/default/files/2015-10/documents/2005-nata-tmd.pdf
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reporting requirements were reflected in TRI's Form R Schedule 1, which was submitted as an
adjunct to the Form R if reporting facilities had this information.
Toxicity information is only available for one member of the dioxin and dioxin-like compounds
chemical category, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). However, EPA has determined
a toxic equivalence factor (TEF) for each congener member of the chemical category, based on
its toxicity relative to TCDD39. The RSEI model combines the reported distributions of each
individual member of the chemical category with EPA's TEFs to calculate a weighted average
TEF for each waste management activity quantity (e.g., releases to the environment). When
multiplied by the toxicity weight for TCDD, this provides a comparable toxicity weight for each
dioxin and dioxin-like compound category member. For waste management activity quantities
where the reported distributions of each category member are blank or invalid, the RSEI model
adopts mean distribution TEFs for each category member using the reporting facility's 4-digit
NAICS code. If a 4-digit NAICS code for the reporting facility is not available, the overall mean
TEF for the specific environmental medium is used. Because the specific individual category
member distributions to each environmental release medium, transfer off site, and waste
management activity are only available starting with reporting year 2008 and on, RSEI hazard-
based and risk-related modeling results are only available for these years, however, users can
examine RSEI pounds-based results for dioxin and dioxin-like compounds for reporting year
2000 and later.
4.4 Sources of Toxicity Data
Information regarding the toxicity data on TRI chemicals and chemical categories is compiled
from the following sources:
IRIS. The primary (and most preferred) source of these data is EPA's Integrated Risk
Information System (IRIS). The IRIS program is available on the internet (at
https://www.epa.gov/iris\ and supports EPA's mission by identifying and characterizing the
health hazards of chemicals found in the environment. IRIS 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 OSF or IUR 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 Agency-wide expert scientific judgments. The peer-review process
involves literature review and evaluation of a chemical by individual EPA program offices and
intra-Agency workgroups before inclusion in IRIS.
AirToxScreen/NATA. EPA's Air Toxics Screening Assessment (AirToxScreen), formerly
known as the National Air Toxics Assessment (NATA). This program generally obtains data
39 TEFs are consensus estimates of compound-specific toxicity/potency relative to the toxicity/potency of an index
chemical. TEFs are the result of expert scientific judgment using all of the available data and taking into account
uncertainties in the available data. For more detail on the dioxin and dioxin-like compound TEFs, see
https://www.epa.gov/risk/documents-recommended-toxicitv-equivalencv-factors-human-health-risk-assessments-
dioxin-and.
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from the other sources listed in this list, but in some cases uses values derived by EPA's Office
of Air Quality Planning and Standards (OAQPS).
OPP. EPA's Office of Pesticide Programs' (OPP) Acute and Chronic Reference Doses Table
lists OPP's evaluations of the non-carcinogenic potential of chemicals that are of interest to OPP.
OPP also publishes the List of Chemicals Evaluated for Carcinogenic Potential, which examines
carcinogens. Both of these lists are updated periodically. Individual Pesticide Reregi strati on
Eligibility Decisions (REDs) are also used.
ATSDR. The Agency for Toxic Substances and Disease Registry (ATSDR) is an agency of the
U.S. Department of Health and Human Services (HHS), which deals with the effect on public
health of hazardous substances in the environment. ATSDR develops Minimal Risk Levels
(MRLs) for chemicals on the Comprehensive Environmental Response, Compensation, and
Liability Act (CERCLA) National Priorities List (NPL). MRLs are an estimate of the daily
human exposure to a hazardous substance that is likely to be without appreciable risk of adverse
noncancer health effects over a specified duration of exposure. RSEI uses data from MRLs
developed for chronic exposure only. MRLs are intended to serve as screening levels only, and
are useful in identifying contaminants and potential health effects that may be of concern at
hazardous waste sites. See https://www.atsdr.cdc.gov/minimalrisklevels/index.html for more
information on MRLs and specific values.
CalEPA. The California Environmental Protection Agency (CalEPA), Office of Environmental
Health Hazard and Assessment (OEHHA) is responsible for developing and distributing
toxicological and medical information needed to protect public health. RSEI uses final toxicity
values published by CalEPA in the Consolidated Table of OEHHA & California's Air Resources
Board (ARB) Approved Risk Assessment Health Values. The table is continuously updated and
can be found at https://ww3.arb.ca.gov/toxics/healthval/contable.pdf.
PPRTVs. EPA's Provisional Peer-Reviewed Toxicity Values (PPRTVs) include toxicity values
developed by EPA's Office of Research and Development (ORD), Center for Public Health and
Environmental Assessment (CPHEA), formerly known as the National Center for Environmental
Assessment (NCEA), Superfund Health Risk Technical Support Center (STSC).
HEAST. EPA's Health Effects Assessment Tables (HEAST) are constructed for use in the
CERCLA and Resource Conservation and Recovery Act (RCRA) programs but do not represent
Agency-wide expert scientific judgments. These tables are publicly available from CERCLA's
Superfund program. The tables include OSFs, IURs, and WOE categorizations for chemicals
with cancer effects, and RfDs and RfCs for noncancer effects.
Derived Values. For a prioritized group of chemicals for which sufficient data were not found in
the above sources, a group of EPA expert health scientists reviewed other available data to derive
appropriate toxicity weights. Although individual literature searches for toxicological and
epidemiological data for each chemical were beyond the scope of the RSEI project, sources such
as the Hazardous Substances Data Bank (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 information. When the available
data on chronic human toxicity were sufficient to derive values, a toxicity weighting summary
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was developed summarizing the information used to develop each of these values. The
summaries are available in Technical Appendix A - Toxicity Weights for TRI Chemicals and
Chemical Categories. The EPA scientists use a technical approach analogous to the Agency's
method for deriving RfD and RfC values, cancer risk estimates, and WOE determinations. It
must be emphasized, however, that these derived values are not the equivalent of the more
rigorous and resource-intensive IRIS assessment process and are only useful for screening-level
purposes.
Data from these sources are categorized in three-tiered, hierarchical fashion to give preference to
EPA and consensus data sources, where possible. Toxicity data are gathered separately for
individual endpoints; a chemical's RfD may be from IRIS, while its OSF may be from HEAST,
as an example.
The three-tiered hierarchy used for toxicity weighting assignments is as follows:
Tier 1. The most recent data from EPA's IRIS and OPP are used for each chronic toxicity health
endpoint. If the data are comparable, preference is given to IRIS, since IRIS reflects Agency-
wide expert scientific judgments. If EPA's AirToxScreen/NATA has made a policy decision to
use an alternative data source, that is adopted unless otherwise indicated by modeling
considerations.
Tier 2. In the absence of data from the above sources for an individual chronic toxicity health
endpoint, toxicity data from the most recent entry in ATSDR and CalEPA are used.
Tier 3. In the absence of data from the above sources for an individual chronic toxicity health
endpoint, the following data sources, in this order, are used: 1) PPRTVs; 2) HEAST; 3) Derived;
and 4) IRIS values previously used in toxicity weighting, that were withdrawn pending revision.
For chemicals with carcinogenicity risk values, WOE designations are obtained using the same
data source hierarchy. Therefore, preference is given to WOEs from EPA's IRIS or OPP. As a
general rule, chemicals with cancer potency factors from IRIS or OPP will also have WOEs.
CalEPA, however, references either EPA or the International Agency for Research on Cancer
(IARC) for WOE designations. Therefore, in the absence of an EPA consensus WOE, WOEs are
obtained from IARC. However, due to the differences in WOE definition, it is not always
possible to translate IARC WOE into EPA WOE without examining the toxicity data. WOEs are
matched in the following way:
• IARC Group 1 = EPA Group A (Carcinogenic to Humans)
• IARC Group 2A = EPA Group B (Probably Carcinogenic to Humans)
• IARC Group 2B = EPA Group B or EPA Group C (Possibly Carcinogenic to Humans)
• IARC Group 3 = EPA Group D (Not Classifiable as to Human Carcinogenicity)
• IARC Group 4 = EPA Group E (Evidence of Non-Carcinogenicity for Humans)
The IARC Group 2B designation is not easily translated to the EPA designation, because its
definition spans EPA Groups B and C. This is a particularly important distinction because the
use of a B2 or C WOE designation will affect the calculation of the toxicity weight. Therefore,
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for the chemicals with IARC Group 2B designations, summaries of the toxicity data used to
generate the OSF or IUR are evaluated to derive the WOE designation. To date, this approach
has been used for chemicals with data from CalEPA; therefore, the CalEPA "Technical Support
Document for Describing Available Cancer Potency Factors" was used for the background
information.
Currently, using all of the available data sources described above, toxicity weights are available
for over 400 of the more than 800 chemicals and chemical categories on the 2021 TRI chemical
list. Chemicals and chemical categories with toxicity weights account for 99% of the reported
quantities for all releases and transfers to modeled media in 2021. The RSEI results are
recomputed for all years in the TRI database on an annual basis in order to incorporate revisions
to the reported data.
Toxicity weights for individual chemicals and chemical categories are presented in Technical
Appendix A- Toxicity Weights for TRI Chemicals and Chemical Categories.
4.5 How RSEI Toxicity Weightings Differ from EPCRA Section 313
Criteria
As previously described, the RSEI model uses TRI chemical reporting data as one of the primary
data sources. All TRI chemicals and chemical categories included in RSEI modeling are listed on
the TRI chemical list because they have met one or more statutory criteria regarding acute or
chronic human health toxicity, or environmental toxicity. One of the goals of the RSEI method
and model is to use data reported to the Agency to investigate the relative risk-based impacts of
certain waste management quantities (e.g., releases to the environment) of toxic chemicals. The
RSEI model differentiates the relative toxicities of TRI-listed chemicals and weights them in a
consistent and transparent manner. The weighting of each chemical reflects its toxicity only
relative to other chemicals that are included in the RSEI model. Toxicity is not compared to
some "absolute" or benchmark criteria, as is required when adding or removing a chemical from
the TRI list of toxic chemicals established under section 313 of the Emergency Planning and
Community Right-to-Know Act (EPCRA). Furthermore, the RSEI model addresses only the
single, most sensitive chronic human health toxicity endpoint.
The EPCRA statutory criteria used for listing and delisting TRI chemicals, on the other hand,
consider acute and chronic human toxicity, as well as environmental toxicity and also
considerations for multiple effects and the severity of those effects. It is important that users not
confuse the use of the RSEI model as a screening-level tool with the very different and separate
regulatory activity of listing/delisting chemicals on the TRI chemical list using statutory criteria.
A description of the listing/delisting criteria and process is described below.
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). The statutory criteria used for listing and delisting chemicals addresses
the "absolute" chronic toxicity of chemicals on the TRI (e.g., multiple effects or the severity of
effects). 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:
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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 judgment 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).
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, 1991b), 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/deli sting decisions under EPCRA section 313 and the methodology used to assign toxicity
weights to chemicals for the RSEI model. Therefore, these toxicity weights cannot be used as a
scoring system for evaluating listing/delisting decisions under EPCRA section 313. The RSEI
model does not attempt to reflect the statutory criteria for these TRI-listed chemicals and
chemical categories.
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Chapter 5: Exposure and Population Modeling
5. Exposure and Population Modeling
To estimate the magnitude of exposure potential from chemical waste management activities
(e.g., from releases to the environment), separate exposure evaluations can be conducted for each
environmental exposure pathway. The following pathways may be evaluated and eventually
modeled in RSEI:
• Air releases: stack (point) and fugitive (non-point) air emissions pathways;
• Water releases: drinking water and fish ingestion pathways; and
• Land releases: groundwater pathway (not currently modeled).
The ideal derivation of an exposure dose would involve a site-specific exposure assessment for
each waste management activity quantity and its environmental exposure pathway. Such an
effort, however, is well beyond the scope of the RSEI project; further, reporting of extensive site-
specific information relevant for exposure modeling is not subject to TRI reporting requirements.
For example, the EPA Form R (Toxic Chemical Release Inventory Reporting Form) does not
require reporting of data on groundwater flow, soil conditions, and other factors that affect
groundwater contamination from land releases. Although some site-specific data are used in the
RSEI model, it is not the intent of the RSEI project to gather extensive site-specific data or
measurements that would be needed to perform site-specific calculations. The need to accurately
reflect exposure scenarios and detailed characteristics in the RSEI model must be balanced by
the need for simple, quick, and understandable results that are easily communicated to users that
are based on current readily-available data.
Therefore, in the RSEI method, the exposure evaluations combine data on physicochemical
properties, environmental fate and transport data, media-specific environmental release
quantities, and where available, site (e.g., facility) characteristics, with models to predict an
estimate of the ambient concentration of the chemical for each relevant exposure pathway. The
ambient environmental media concentrations are then combined with human exposure
assumptions to estimate a "surrogate dose". The term surrogate dose is used because limited site-
specific data and the use of models that rely on default values and assumptions for some input
parameters preclude the calculation of an actual dose estimate. Instead, the purpose of this
methodology is to generate as accurate a surrogate dose as possible without conducting an in-
depth and resource-intensive risk assessment. The estimates of surrogate doses resulting from
certain waste management activities of TRI chemicals are relative to the surrogate doses
resulting from other waste management activities included in the RSEI model.
Estimates of the surrogate dose for each potentially exposed person are combined with estimates
of the number of people potentially exposed. Potential exposure is determined by the geographic
location of the population, as identified by the decennial U.S. Censuses for 1990, 2000, and
2010. The size of the potentially exposed population is calculated separately for each exposure
pathway. The RSEI model assumes continuous exposure, and does not account for the activity
patterns of the people who may be potentially exposed. However, population estimates do
consider changing demographic patterns (total population, as well as subpopulations by age and
sex).
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The methods used to model each type of waste management activity are specific to that type of
activity and depend on the data available to evaluate that exposure pathway. In some cases,
models are combined with some site-specific data to estimate exposure; in other cases,
reasonable generic worst-case models and/or assumptions may be used in the absence of any
site-specific data. The physicochemical property data used for the exposure evaluations are
found in Technical Appendix B - Physicochemical Properties for TRI Chemicals and Chemical
Categories. It should be noted, however, that products of decay or biotransformation are not
modeled by RSEI. Exclusion of these decay or biotransformation products from the RSEI model
may underestimate or overestimate the risk-related impacts of certain waste management
activities, since the decay or biotransformation product(s) may be more or less toxic than the
parent chemical.
Specific pathway calculations are discussed in the sections below. First, Section 5.1 discusses the
geographic basis of the RSEI model, and describes the grid cell system underlying the model and
how facilities and people are located on it. This discussion describes how annual grid cell-level
general population datasets are created. From these general population datasets, the model
generates estimates of populations potentially exposed through particular exposure pathways.
The next sections then describe the modeling for each exposure pathway, including the
estimation of surrogate doses and potentially exposed population for that pathway.
5.1 Geographic Basis of the RSEI Model
Underlying the RSEI method is the ability to locate facilities, environmental releases, and people
geographically and attribute characteristics of the physical environment such as meteorology,
hydrography, and topography on surrounding areas once they are located to estimate potential
exposure and relative impacts. The RSEI model describes the U.S. and its territories40 using a
grid-based system and a surface water network. The grid-based system is composed of 810 meter
by 810 meter grid cells. For each cell in the grid system, a location "address" in terms of (x,^)
coordinates is assigned based on latitude and longitude (lat/long) to be able to incorporate facility
and population information. The surface water network is composed of linear sections of
streams, lakes, reservoirs, and estuaries that are linked to form a skeletal structure representing
the branching patterns of surface water drainage systems. Facility- and chemical-specific data
retrieved from Agency-reported informational data sources (such as site addresses and lat/long
coordinates) are then geographically indexed to their corresponding grid cell or stream
segment/flowline in the surface water network for modeling purposes.
5.1.1 The RSEI Model Grid Cell System
RSEI uses a standard Albers equal-area projection (NAD 83)41 to create each of the grids that are
used in the model. The grid cell system is split into six individual grids which cover the
continental U.S., Alaska, Hawaii, and the territories. Each unique cell address is composed of (1)
40 The model also includes Puerto Rico, the U.S. Virgin Islands, Guam, American Samoa, and the Northern Mariana
Islands. 1990 U.S. Census data were provided by GeoLytics, Inc., East Brunswick, NJ.
41 RSEI versions 2.2.0 and earlier used a non-standard grid developed specifically for RSEI. The use of a standard
projection makes it easier for users to import RSEI data into geographic information systems, software, and
applications.
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the grid number, and (2) the (x,y) address of the cell in that grid. Exhibit 5.1 below provides the
grid number (used in the model to identify each grid), the grid characteristics that can be used to
recreate the grid in a geographic information system (GlS)-based system, and the bounding
coordinates for each.
Exhibit 5.1
RSEI Grid Characteristics
Grid Reference Characteristics
Grid
Code
Grid
Latitude
of Origin
Central
Meridian
Standard
Parallel 1
Standard
Parallel 2
Lower Left
x Coord.
(m)
Lower Left
v Coord.
(m)
Columns
Rows
14
Conterminous
U.S.
23 °N
96°W
29.5°N
45.5°N
-2,365,605
251,505
5,724
3,618
24
Alaska
50°N
154°W
55°N
65°N
-1,046,115
564,975
3,291
2,505
34
Hawaii
20.5625°N
157.5625°W
19.4375°N
21.2375°N
-287,955
-185,895
739
480
44
Puerto Rico/
Virgin Islands
18°N
66.25°W
17.875°N
18.5°N
-185,895
-40,095
462
129
54
Guam/
Marianas
0°
155°E
12°N
15°N
-1,133,595
1,468,935
203
295
64
American
Samoa
0°
170°W
12°S
15°S
-91,125
-1,578,285
203
36
Bounding Coordinates for Lower-Left (LL), Upper-Right (UR),
Lower-Right (LR), and Upper-Left (UL) Corners
Grid
Code
Grid
LL Long
LL Lat
UR Long
UR Lat
LR Long
LR Lat
UL Long
ULLat
14
Conterminous
U.S.
118.78°W
22.69°N
65.14°W
48.29°N
74.09°W
22.89°N
128.05°W
48.01°N
24
Alaska
170.07°W
53.95°N
111.99°W
68.54°N
129.76°W
52.41°N
176.63°W
71.23°N
34
Hawaii
160.29°W
18.86°N
154.54°W
22.37°N
154.6°W
18.86°N
160.36°W
22.38°N
44
Puerto Rico/
Virgin Islands
68°W
17.63°N
64.46°W
18.58°N
64.47°W
17.63°N
68.01°W
18.58°N
54
Guam/
Marianas
144.54°E
13.18°N
145.98°E
15.4°N
146.06°E
13.24°N
144.44°E
15.34°N
64
American
Samoa
170.85°W
14.38°S
169.32°W
14.12°S
169.32°W
14.38°S
170.84°W
14.12°S
The (x,y) coordinates used in each grid are defined as:
x = number of cells from the center cell in the East-West direction.
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y = number of cells from the center cell in the North-South direction.
RSEI grid shapefiles containing the outlines of each grid cell for each grid, can be found on the
RSEI file transfer protocol (ftp) site at ftp://newftp.epa.gov/RSEI/Shapefiles/ or
https://gaftp.epa.gov/rsei/Shapefiles/.
5.1.2 Locating Facilities on the Grid
Once the grid system for the U.S. is created, each facility must be located on the grid and
assigned to a grid cell. Facilities are projected onto each grid using GIS software and the (x,y)
coordinates of the cell where the facility is mapped are assigned to the facility. Once a grid cell's
(x,y) coordinates are assigned, the facility is assumed to be at the cell's center, for ease of
modeling. For a complete description of the method used to select lat/long coordinates for both
TRI reporting facilities and off-site facilities, see Technical Appendix D - Locational Data for
TRI Reporting Facilities and Off-site Facilities.
TRI Reporting Facilities. Because the location of a facility is key to the subsequent exposure
modeling (e.g., facility location will determine which population is assumed to be potentially
exposed to the facility's air releases), it is important that the lat/long coordinates are as accurate
as possible. RSEI uses the best pick coordinates from EPA's Facility Registry Service (FRS),
which collects coordinates and related documentation on location and other facility information
from various programs offices across EPA. The facility lat/long coordinates are projected onto
the relevant grid, and the (x,y) coordinates of the grid cell to which the facility maps are
assigned. The facility is then modeled as being located at the center of its assigned grid cell.
Off-site Facilities. RSEI also models some potential exposures that may result from waste
management activities (e.g., releases to the environment) of TRI chemicals from "off-site"
facilities, that is, facilities that receive chemical waste transfers from TRI-reporting facilities.
Note that these off-site facilities do not report chemical waste transfers received from other
facilities; instead their names, addresses, and the type and quantity of each waste management
activity are reported by the facilities that transfer the TRI chemical(s) in waste streams to them.42
Each report of a receiving off-site facility becomes a separate record in the TRI database, even
though each off-site facility often receives transfers from more than one TRI-reporting facility.
This produces multiple records of the same off-site facility; however, because the names and
addresses are often reported slightly differently by reporting facilities, the records cannot easily
be matched to each other. EPA has developed an approximate text string matching program to
identify imperfect matches in order to refine the set of off-site facilities to what are considered to
be unique off-site facilities. The program matches values without requiring their exact equality.
This approach accommodates misspelled words and inconsistencies in how a facility might
report its identifying information over time. For example, "DuPont," "Du Pont," and "E.I.
DuPont" might all refer to the same facility. A possible match is identified based on similarity
42 Some facilities may be considered both on-site and off-site facilities, if they both receive chemical waste transfers
from other facilities (as an off-site facility) and also meet TRI reporting criteria and report their waste management
activity quantities on site. RSEI only adjusts for "double counting" of chemical waste management quantities from
facilities that both receive off-site transfers for the purpose of incineration and that also report on-site waste
management quantities to TRI with a primary NAICS code of 562211 (Hazardous Waste Treatment and Disposal).
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rather than exact equality in the name field, and then the address fields are examined to
determine whether the records match.
For RSEI Version 2.1.3 (reporting year 2003), all off-site records went through the approximate
text matching program, and were also geocoded (lat/long coordinates were assigned based on
street address). For each set of facilities that were determined to be matches, the record whose
geocoded lat/long was of the highest confidence level was selected. The name, address, and
lat/long coordinates for this facility record are selected for the master off-site facility database,
and used in the RSEI model to represent all of the records in that matched group. For Version
2.1.3, this resulted in a master off-site database of approximately 47,000 off-site facilities.
Beginning with Version 2.1.5 (reporting year 2005), off-site facilities are no longer geocoded.
Instead, the entire set of all reporting years of off-site records (1988-current) is matched back to
the previous reporting year's master off-site database using an approximate text matching
program. Again, this is necessary because there are no universal identifiers reported along with
the off-site records in TRI that would allow for direct matching from year to year. Any records
that are not matched back to the previous year's database (especially any new off-site facilities)
are added to the master off-site database, resulting in a new master off-site database. Additional
data from EPA's FRS are also used where possible to identify lat/longs for off-site facilities.
Grid cell locations for off-site facilities are determined in the same manner as for TRI reporting
facilities; the facility lat/long coordinates are projected onto the relevant grid, and the (x,y)
coordinates of the grid cell to which the facility maps are assigned. The off-site facility is
assumed to be in the center of its assigned grid cell.
5.1.3 Locating People on the Grid
In order to estimate potential exposure, the U.S. population must also be geographically located
on the RSEI model grid. To match annual TRI chemical waste management activity quantities
and capture the effect of the changing distribution of the population, RSEI uses detailed annual
population datasets at the grid cell level. The data are based on decennial U.S. Census data, and
include information on population, age, and sex.
The following sections describe how the U.S. Census data are used to generate annual population
estimates, and how the unit of analysis for the U.S. Census (the block) is translated into the unit
of analysis for the RSEI model (the grid cell).
U.S. Census Data. The RSEI model uses decennial U.S. Census data for 1990, 2000, and 2010
at the block level.43 Census blocks are the smallest geographic area for which decennial Census
data are collected. Blocks are of varying size, formed by streets, roads, railroads, streams and
other bodies of water, other visible physical and cultural features, and the legal boundaries
shown on U.S. Census Bureau maps. In 1990, there were approximately 7 million Census blocks.
Due to boundary changes and increased resolution for highly populated areas, there were
approximately 9 million blocks in the 2000 Census, and more than 11 million in 2010. Block-
43 Some U.S. Census data and block shapefiles were provided by GeoLytics, Inc. The decennial U.S. Census data for
2020 is now available and will be incorporated into the RSEI model environment for a future model release.
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level data from the three decennial Censuses44 are used to create detailed age-sex population
groups for each of the Census blocks in the U.S. for 1990, 2000 and 2010. Because the U.S.
Census Bureau presents data in slightly different format, some data processing was necessary to
create the following age-sex population groups used in the model:
• Males Aged 0 through 9 years
• Males Aged 10 through 17 years
• Males Aged 18 through 44 years
• Males Aged 45 through 64 years
• Males Aged 65 Years and Older
• Females Aged 0 through 9 years
• Females Aged 10 through 17 years
• Females Aged 18 through 44 years
• Females Aged 45 through 64 years
• Females Aged 65 Years and Older
For Puerto Rico, the U.S. Virgin Islands, American Samoa, Guam, and the Northern Mariana
Islands, block-level shapefiles and block-level population data were only available for 2000.45
For 1990, the grid cell-level populations from 2000 were scaled by age-sex specific Census
population estimates for 1990 to create 1990 population estimates. For 2010, block-level
population was only available for Puerto Rico; for the other areas, similar age-sex specific
Census data from 2010 were used to scale the 2000 data to create 2010 population estimates.
Grid cells for Puerto Rico and island areas are mapped in the same way as described below.
Mapping blocks to grid cells. Because the grid cell is the unit of analysis for the RSEI model,
Census data must be transposed from blocks to the model grid cells. The U.S. Census Bureau
provides the geometry for each block in the Topologically Integrated Geographic Encoding and
Referencing (TIGER) geographic database, which was used to create shapefiles for the 1990,
2000, and 2010 Census years. A corresponding set of shapefiles for grid cells was created, with
each grid cell defined by its four corner points, calculated from its (x,y) coordinates. The
shapefiles were then compared, in essence overlaid, and each block was mapped to the cells in
the grid that it overlaid, and the percentage of the block's total area falling within each cell was
calculated.46
The process described above was performed separately for 1990, 2000, and 2010, as the block
boundaries change between the Censuses. This process resulted in three tables, each with four
44 For 1990, not all of the variables were available at the block level. For those variables that were only available at
the block group level, block group ratios were calculated and applied to the data available at the block level. For
2000, all of the required variables were available at the block level.
45 For 2010, block-level shapefiles were available, but block-level population data were not released in time for
incorporation.
46 Due to irregular, invalid block shapes, some of the block percentages did not sum to 100 percent. For these blocks,
the boundary overlay process was not used; instead, the whole block was assigned to whatever grid cell contained
the centroid of the block (an approximate center point defined in the Census).
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fields: the Xcoordinate and the Y coordinate which identify the grid cell, the block identifier
assigned by the Census, and the percent of that block assigned to the grid cell.
Calculating Populations. For each block assigned to a grid cell, the block populations were
multiplied by the percentage of that block assigned to that grid cell. Those values were then
summed over each grid cell. This process was performed separately for 1990, 2000, and 2010,
resulting in three grid cell-level datasets, each containing the ten age-sex population groups listed
above.47 For 1990, there were 11,083,291 populated grid cells; for 2000, there were 9,399,819;
and for 2010 there were 9,258,679 populated grid cells.
To create annual datasets for 1991 through 1999, a straight-line interpolation at the grid cell level
is performed within the RSEI model between the 1990 and 2000 datasets; annual datasets for
2001 through 2009 are created using a straight-line interpolation between the 2000 and 2010
datasets. The 1990-2000 line is extrapolated backward to create annual datasets for 1988 and
1989 and the 2000-2010 line is extrapolated forward to 2021.
5.1.4 Surface Water Network
RSEI has adopted the National Hydrography Dataset (NHD) system for indexing water stream
segments or flowlines.48 The NHD is a feature-based database that interconnects and uniquely
identifies the stream segments/flowlines that comprise the nation's surface water drainage
system. The NHD provides a national framework for assigning flowline addresses to water-
related entities such as facility dischargers, drinking water supplies, fish habitat areas, and wild
and scenic rivers. Flowline addresses establish the locations of these entities relative to one
another within the NHD surface water drainage network in a manner similar to street addresses.
Once linked to the NHD by their flowline addresses, the upstream/downstream relationships of
these water-related entities and any associated information about them can be analyzed using
software tools ranging from spreadsheets to GIS software applications. As an example, EPA's
Watershed Assessment, Tracking & Environmental Results System (WATERS) uses the
flowline codes in NHD to link multiple databases containing water quality and programmatic
information.
EPA, in partnership with the U.S. Geological Survey, has created a version of the NHD called
NHDPlus49, which provides the stream network of individual flowlines, upstream/downstream
directionality and connectivity, and flow and velocity estimates by flowline that are used to
calculate chemical concentrations in the RSEI model. The NHDPlus version used by RSEI is of
medium resolution (l:100,000-scale or 30 meter ground spacing) and contains the geographies
47 The data processing results in fractional people; populations were rounded to four decimal places for use in
calculations, but are rounded to the nearest integer for display.
48 The Reach File 1 (RF1) system was used in prior versions of the RSEI model (Version 2.2.0 and before).
49 https://www.epa.gov/waterdata/nhdplus-national-hvdrographv-dataset-plus. The NHDPlus Version 2 data are
hosted by Horizon Systems Corporation, which hosts and maintains the NHDPlus data. Documentation and data are
available at http://www.horizon-svstems.com/nhdplus/index.php.
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for the continental U.S. and the following islands: Northern Mariana Islands, Guam, Hawaii,
American Samoa, Puerto Rico, and the U.S. Virgin Islands.50
5.2 Pathway-specific Methods to Evaluate Human Exposure Potential
The following sections describe the algorithms used for evaluating potential exposure for each of
the following exposure pathways: (1) stack and fugitive air emissions, (2) discharges to receiving
streams or waterbodies, (3) discharges to publicly owned treatment works (POTW) (4) other off-
site transfers for further waste management, and (5) releases to land. An overview of the
exposure pathways and methods used to model each pathway is presented in Exhibit 2.1.
The following discussions of exposure modeling frequently mention concentration and surrogate
dose. This is not meant to imply that an actual dose can be accurately calculated within this RSEI
model as discussed previously. The exposure algorithms used are intended to be simple ways to
gauge risk-related impacts from certain waste management activities of TRI chemicals to
different environmental media in a consistent, defensible way, by modeling and estimating
potential resulting exposure. In some cases, the modeling is purposely simplified, given the lack
of site-specific data and/or more detailed information.
When possible, exposures are estimated for relevant populations defined by age, sex, or other
factors. Exposure for individual populations is modeled using exposure factors (i.e., inhalation
rates, drinking water rates, fish ingestion rates, and average body weight) and population data
specific to these such populations. For example, ingestion rates specific to recreational and
subsistence fishers are used to estimate exposures for these fishers and their families. Also, age-
and sex-specific inhalation and drinking water ingestion rates are used. Assumptions for relevant
exposure potential for populations are also described in the following sections.
5.3 Modeling Air Releases
Air releases can either be through stacks air emissions or as fugitive air emissions. Stack (or
point) air emissions include releases to air through stacks, confined vents, ducts, pipes, or other
confined air streams, and represent the majority of reported air releases. Fugitive (or non-point)
air emissions include all other releases that are not stack air emissions, such as equipment leaks
from valves, pump seals, flanges, compressors, sampling connections, open-ended lines,
evaporative losses from surface impoundments and spills, and releases for building ventilation
systems. Stack and fugitive air emissions are modeled as two separate exposure pathways in the
RSEI model, although the potentially exposed population and human exposure assumptions are
the same for both. The following sections describe the method and data sources for each
pathway.
50 A high resolution version of NHD (1:24,000 scale or 10 meter ground spacing) is now available and may be
incorporated into the RSEI model environment for a future model release. See https://www.usgs.gov/core-science-
svstems/ngp/national-hvdrographv/nhdplus-high-resolution.
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5.3.1 Stack Air Emissions: Method
Stack air emissions are modeled using the American Meteorological Society/EPA Regulatory
Model (AERMOD). AERMOD replaced the Industrial Source Complex (ISC) model as EPA's
preferred regulatory model in 2005. AERMOD is a steady-state Gaussian plume model used to
estimate pollutant concentrations downwind of a stack or area source. The pollutant
concentration is a function of facility-specific parameters, meteorology, and chemical-specific,
first-order air decay rates. The following sections describe the parameters of the AERMOD
model used.51
5.3.1.1 AERMOD
The AERMOD model is specifically designed to support the EPA's regulatory modeling
programs, as specified in the Guideline on Air Quality Models (Revised).52 AERMOD is a
steady-state plume model. In the stable boundary layer (SBL), it assumes the concentration
distribution to be Gaussian in both the vertical and horizontal. In the convective boundary layer
(CBL), the horizontal distribution is also assumed to be Gaussian, but the vertical distribution is
described with a bi-Gaussian probability density function (pdf). Additionally, in the CBL,
AERMOD treats "plume lofting," whereby a portion of plume mass, released from a buoyant
source, rises to and remains near the top of the boundary layer before becoming mixed into the
CBL. AERMOD also tracks any plume mass that penetrates into the elevated stable layer, and
then allows it to re-enter the boundary layer when and if appropriate. For sources in both the
CBL and the SBL, AERMOD treats the enhancement of lateral dispersion resulting from plume
meander. Unlike existing regulatory models, AERMOD accounts for the vertical inhomogeneity
of the planetary boundary layer (PBL) in its dispersion calculations. This is accomplished by
averaging the parameters of the actual PBL into effective parameters of an equivalent
homogeneous PBL.
5.3.1.2 Model Dispersion Options
AERMOD is used with its regulatory default options53, except for the following: chemical-
specific decay is considered (the TOXICS with SCIM option is used), and flat terrain is assumed.
The non-default option of modeling urban areas with increased surface heating is not used.
Weather data from the National Weather Service (NWS) observation stations are used as the
meteorological input (see Section 5.3.1.4 below).
5.3.1.3 Source Parameters
In the RSEI model, the U.S.54 is represented by a grid system composed of 810 meter (m) by
810m square grid cells. Facilities are assigned to a particular grid cell in this grid according to
51 The following description is based on equations and text provided in the AERMOD manuals and documentation.
The most recent AERMOD manuals are available from EPA's Support Center for Regulatory Atmospheric
Modeling (SCRAM) website at https://www.epa.gov/scram/air-qualitv-dispersion-modeling-preferred-and-
recommended-models.
52 The Guideline on Air Quality Models can be found in 40 CFR Part 51, Appendix W or accessed online at:
http ://www. epa. gov/ttn/scram/guidance/guide/appw 05 .pdf
53 See https://www.epa.gov/scram/air-qualitv-dispersion-modeling-preferred-and-recommended-models.
54 Including Puerto Rico, the U.S. Virgin Islands, American Samoa, Guam, and the Northern Mariana Islands.
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their latitude and longitude coordinates (see Technical Appendix D - Locational Data for TRI
Reporting Facilities and Off-site Facilities, for details on the coordinates used). To increase
modeling efficiency, a facility is then assumed to be located at the center of the grid cell,
regardless of where its latitude and longitude coordinates place it within the cell.
As a result of this assumption, the actual location of a facility may differ from its modeled
location by up to 573 meters, which is the maximum distance between the center and the corner
of the grid cell. To simplify the analysis, a facility's stack air (point source) emissions are
modeled as a single stack located at the facility's geographic center.
RSEI uses facility-specific stack parameters derived from EPA's National Emissions Inventory (
NEI)55 when available. These include stack height, exit-gas velocity, and stack diameter. Stack
exit-gas temperature is assumed constant for all stacks (432 Kelvin (K)). For facilities with
multiple stacks, the median value for the stack heights and diameters for that facility is used for
modeling. For facilities without stack-specific values, industry-specific North American Industry
Classification System (NAICS) code-based median stack parameters are assigned. If no valid
NAICS code is available for the facility, or no stack data are available for that industry-specific
NAICS code, then overall median values are used for modeling. Stack parameters are further
discussed in Section 5.3.6.1 and in Technical Appendix E - Derivation of Stack Parameter Data.
Annual chemical stack air emissions as reported to the TRI Program are converted to an
equivalent constant emission rate (in grams per second) according to the following equation:56
Q = 453-6 q (Eq. 5.3)
31,536,000
where:
Q = chemical emission rate (g/sec)
q = TRI annual stack (point) air emissions (lbs/yr)
453.6 = constant to convert pounds (lbs) to grams (g)
31,536,000 = constant to convert years (yr) to seconds (sec) assuming 365 days
per year
5.3.1.4 Meteorological Input Data
For a given chemical emission source, meteorology around the source affects the dispersion
characteristics. Meteorological factors such as wind speed and direction, air temperature,
stability, turbulence, and the height of the mixing layer all have a direct effect on the dispersion
55 NEI data are available here: https://www.epa.gov/air-emissions-inventories/national-emissions-inventorv-nei
56 Although RSEI can model any chemical air emission that is accompanied by the appropriate chemical, locational,
and toxicity weight information, the model currently uses TRI reporting as the source of chemical release
information.
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and dilution of air pollution and the resulting magnitude and location of ground level
concentrations of emitted chemicals.
AERMOD is designed to run with a minimum of observed meteorological parameters, and
requires only a single surface measurement of wind, wind direction, and ambient temperature.
Like ISC, AERMOD also needs observed cloud cover. However, if cloud cover is not available
(e.g., from an on-site monitoring program), two vertical measurements of temperature (typically
at 2 and 10 meters) and a measurement of solar radiation can be substituted. A full morning
upper air sounding is required in order to calculate the convective mixing height throughout the
day. Surface characteristics (surface roughness, Bowen ratio, and albedo) are also needed in
order to construct similarity profiles of the relevant PBL parameters.
5.3.1.5 Calculating Chemical Concentrations
The RSEI model uses AERMOD to calculate chemical air concentrations at hypothetical
"receptors" located within a square 100 kilometers (km) per side surrounding each facility.
Concentrations are calculated at ground level, starting at 200 meters (m) from the facility
location, and every 200m until 1600m from the facility location. After that point, concentrations
are calculated every 2km, until 50km from the facility location is reached. These calculated
concentrations are then applied to the RSEI grid, and a concentration is then determined at the
center of each RSEI grid cell, using a spatial weighting technique similar to inverse distance-
weighted averaging. Exhibit 5.2 illustrates the combination of receptors (shown as small blue
dots) and 810m by 810m RSEI grid cells (shown as gray squares), for the area close to the
facility. The facility is shown as an orange dot at the center of the center grid cell.
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Exhibit 5.2 RSEI Grid Cells and AERMOD Receptor Points for Area Closest to Facility
100m 810m
0 200m 1km
to 49km
to 49km
to 49km
The RSEI modeled concentrations are then determined for each grid cell within a circle having a
radius of 49km that is centered on the facility. To determine the optimal distance for RSEI
modeling, EPA modeled air concentrations for the 20 most toxic carcinogens and the 20 most
toxic non-carcinogens included in the RSEI model at various stack heights. These analyses
indicated that extending modeled distances out to 50km5" was necessary to capture potential
concentrations of concern under certain atmospheric conditions. This extended distance is
expected to capture the majority of the potential environmental impacts from the TRI reporting
facilities, including electric utilities, which usually have taller stack heights than other facilities.
57 In the final RSEI modeling, 49km was used instead of 50km due to modeling constraints.
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Details of these analyses can be found in Part B of Analyses Performedfor the Risk-Screening
Environmental Indicators,58
5.3.2 Fugitive Air Emissions: Method
As for stack air emissions, long-term chemical concentrations downwind of the facility due to
TRI-reported fugitive (non-point) air emissions are also modeled using algorithms from
AERMOD.
5.3.2.1 Model Dispersion Options
Model dispersion options used in modeling fugitive air emissions are the same as those used for
stack air releases, as described in Section 5.3.1.2.
5.3.2.2 Source Options
Fugitive emissions are modeled as an area source which is 10 meters by 10 meters in size,
located at the center of the grid cell containing the facility. The model assumes a release height at
ground level.
Fugitive emissions are converted from pounds per year to grams per square meter per second
(g/m2s) according to the following equation:
453.6a
Qa = — 7 (Eq. 5.4)
31,536,000* l(f V H 7
where:
Qa = chemical area emission rate (g/m2s)
qa = TRI annual fugitive air emissions (lbs/yr)
453.6 = constant to convert pounds (lbs) to grams (g)
31,536,000 = constant to convert years (yr) to seconds (sec)
102 = conversion factor necessary to convert annual emissions (g/s) to
area emission rate (g/m2s), assuming an area 10m x 10m.
5.3.2.3 Calculating Chemical Concentration
Chemical concentrations for fugitive air emissions are calculated using AERMOD, as described
previously for stack air emissions.
5.3.3 Calculating Surrogate Dose for Air Releases
The calculated air concentrations described earlier are combined with assumptions regarding
inhalation rate and human body weight to arrive at a surrogate dose for a given grid cell:
58 These analyses were performed using an earlier version of RSEI that incorporated EPA's Industrial Source
Complex (ISC) model. RSEI now uses AERMOD, which has replaced ISC as the Agency's recommended air
modeling program.
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(Eq. 5.5)
where:
DOSEarr
surrogate dose of chemical contaminant from air (mg/kg-day)
air concentration in grid cell ([j,g/m3)
inhalation rate (m3/day)
human body weight (kg)
constant to convert micrograms (|ig) to milligrams (mg)
5.3.4 Estimating Population Size for Air Releases
The population potentially exposed to air releases is assumed to be equal to the population
assigned to the grid cells in the 810m by 810m modeled area, as described previously in Section
5.1.3. Exposed population is only considered for grid cells with non-zero chemical
concentrations.
5.3.5 Calculating the RSEI Score for Air Releases
Exhibit 5.3 provides a graphical overview of the steps for determining the air modeling
component of the RSEI model. First, the chemical concentration in each grid cell is calculated
using TRI emissions data and the AERMOD algorithms. Then, population-specific exposure
factors are used to calculate a surrogate dose for each grid cell. Finally, the surrogate dose is
multiplied by the number of people potentially exposed in each population in the grid cell and by
the chemical toxicity weight to obtain the risk-related score for the grid cell. Then the scores for
all impacted grid cells are summed. The result is the RSEI Score for a given air release. To
calculate the RSEI Score for all air releases, the same steps are followed for each air release, and
all the results are summed.
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Exhibit 5.3
Calculating the RSEI Score for Air Releases
Air Release (lbs/year)
EPA/AMS Regulatory
Model (AERMOD)
1
Chemical concentration
in grid cell (x,y)
Population-specific
exposure factors
1
Surrogate dose (mg/kg-
day)
I
Population data and
chemical toxicity weights
±
Score for grid cell (x,y)
Sum over all 11,289 grid
cells around facility
Score for Air Release
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5.3.6 Stack and Fugitive Air Emissions: Data
The air exposure pathway uses facility-specific parameter values (stack height, stack diameter,
and exit-gas velocity), meteorology, chemical-specific first-order air decay rates, and exposure
assumptions (inhalation rate and body weight). The values used for this pathway are summarized
below in Exhibit 5.4.
Exhibit 5.4
Air Modeling Parameters
Parameter
Value
Source/Comment
Chemical emission
rate
Site-specific (lbs/yr)
TRI (2021-1988)
Stack height
In order of preference:
• Median value across stacks at facility as
reported to NEI or EPRI (for electric utilities)
• Median value across stacks in the facility's 4-
digit NAICS code or in EPRI dataset (for
electric utilities)
• Median value across all stacks
NEI (2017, 2014, 2011,
2008, and 2005), EPRI
(for Electric Utilities)
Stack diameters
In order of preference:
• Median value across stacks at facility as
reported to NEI or EPRI (for electric utilities)
• Median value across stacks in the facility's 4-
digit NAICS code or in EPRI dataset (for
electric utilities)
• Median value across all stacks
NEI (2017, 2014, 2011,
2008, and 2005), EPRI
(for Electric Utilities)
Exit-gas velocity
In order of preference:
• Median value across stacks at facility as
reported to NEI or EPRI (for electric utilities)
• Median value across stacks in the facility's 4-
digit NAICS code or in EPRI dataset (for
electric utilities)
• Median value across all stacks
NEI (2017, 2014, 2011,
2008, and 2005), EPRI
(for Electric Utilities)
Exit-gas
temperature
432 K
Based on EPA (2004b)
Meteorological
data
Site-specific
Processed using
AERMET as contained
in the HEM-3 data
library (EPA, 2007)
Decay rate
Chemical-specific values account for removal by
physical and chemical processes (s1)
SRC (1994-1999)
Area source size
10 m2
Based on EPA (1992b)
Area source height
Ground level
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5.3.6.1 Stack Height, Stack Diameter, and Exit-Gas Velocity
Stack parameter data (height, diameter, and exit-gas velocity) were obtained from the five most
recent triennial NEI databases (data years 2017, 2014, 2011, 2008, and 2005)59. For each TRI
reporting facility, the closest NEI year that is greater than or equal to the last year of stack
releases reported to TRI is used for the stack parameter data. For instance, if a facility last
reported to the TRI in reporting year 2016, data from the 2017 NEI is used; if a facility last
reported to the TRI in reporting year 2013, then data from the 2014 NEI is used. For any facility
with stack parameter data in NEI, the median parameter value of all stacks that emit TRI
chemicals at the facility is used. For any TRI facility that has no stack parameter data in NEI, the
median parameter value for all of the facilities in that facility's NAICS code is used instead. The
NAICS code-based stack parameters are estimated from data in NEI for facilities in the
appropriate 4-digit NAICS code. If no 4-digit NAICS code is available, the median parameter
value of all stack parameter values with TRI-reportable NAICS codes is used.
The Electric Power Research Institute (EPRI) provided EPA with site-specific data for electric
utilities (electric utilities were required to report to TRI beginning with reporting year 1998),
transmitted in two databases. These data included stack height, stack diameter, and exit-gas
velocity. Of the 960 TRI facilities reporting in any year and classified in NAICS code 2211-
Electric Power Generation in reporting year 2021, 42 percent match a corresponding facility
listed in one of the EPRI databases; approximately 58 percent of TRI electric utility facilities do
not. For the 58 percent that did not match specific facilities, facility-specific data from NEI were
used. If no facility-specific data were found in NEI, then the median parameters taken across all
of the coal or oil combusting stacks in the EPRI databases were used (the overall EPRI median
was used for 9 percent of facilities in NAICS 2211).
Analyses have been conducted that show air concentrations predicted by the RSEI model using a
combination of generic and site-specific data closely match concentrations estimated by using
more complete site-specific data.60 See Technical Appendix E - Derivation of Stack Parameter
Data, for details on the derivation of stack data.
5.3.6.2 Meteorology61
The meteorological data used in the RSEI model are taken from EPA's Human Exposure Model,
Version 3 (HEM-3), a model for use in site-specific air toxics risk assessment. RSEI uses
weather data included in EPA's HEM-3 data library, which has been prepared using AERMOD's
meteorological processor, AERMET. AERMET requires hourly surface weather observations
and the full twice-daily upper air soundings (i.e., meteorological variables reported at all levels).
59 Currently, the RSEI model can only assign one set of stack parameters to each facility. If a facility has reported
stack releases throughout the entire period of NEI data (2005-2017), the most recent stack parameters are used.
60 These analyses were performed using an earlier version of RSEI that incorporated EPA's Industrial Source
Complex (ISC) model. RSEI now uses AERMOD, which has replaced ISC as the Agency's recommended air
model.
61 This description is taken from the HEM-3 User's Manual (EPA, 2007), available at
https://www.epa.gov/fera/human-exposure-model-hem-3-users-guides.
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The surface and upper air stations are paired to produce the data files require for input into
AERMOD: one file consists of surface scalar parameters, and the other file consists of vertical
profiles of meteorological data.
To simplify processing and to minimize the amount of quality assurance needed, HEM-3's
processing was restricted to meteorological data collected prior to the installation of the
Automated Surface Observation System (ASOS). The ASOS has previously been found to omit
the ceiling height for a large percentage of the observations at a number of meteorological
stations. Installation and operation of ASOS equipment began in 1992; therefore, data for 1991
were used. Data were retrieved from products available from the National Climatic Data Center
(NCDC). The surface data for 1991 were retrieved from the Hourly United States Weather
Observation (HUSWO) CD. Upper air soundings were obtained from the Radiosonde Data of
North America CDs produced by NCDC and the Forecast Systems Laboratory (FSL).
Certain surface characteristics must be specified when processing meteorological data using
AERMET, including the surface roughness length, the Bowen ratio (an indicator of surface
moisture), and the albedo (an indicator of surface reflectivity). These surface characteristics are
used by AERMET to calculate the level of shear-induced mechanical turbulence generated by
flow over the surface and for the energy balance calculations used in the determination of the
Monin-Obukhov stability parameter and the convective velocity scale. For the HEM-3
meteorological data, the following surface characteristics were used:
• Surface roughness length = 0.25 m. At the airport meteorological site, the surface
roughness includes runways, terminal buildings and other airport structures. In addition,
off-airport structures often are within 3 kilometers of the measurement site. This
combination of land covers suggests a value of 0.2 - 0.3 meters is appropriate.
• Bowen ratio =1.0. Representing an equal partition of the heat fluxes.
• Albedo = 0.15. Representing conditions for all seasons, including winter without
continuous snow cover.
• The file STNS.TXT located on the HUSWO CD was used for the anemometer heights
required by AERMET. These heights are to the nearest meter and were deemed
appropriate for use in this application.
5.3.6.3 First-Order Chemical Air Decay Rates
Chemicals may be removed from the atmosphere by either physical processes or chemical
transformation. The RSEI model uses chemical-specific air decay rates from SRC, Inc.'s
Atmospheric Oxidation Program for Windows (AOPWIN), an atmospheric oxidation computer
program (SRC, 1994-1998). AOPWIN estimates the second-order rate constant for the
atmospheric, gas-phase reaction between photochemically produced hydroxyl radicals and
organic chemicals.62 The daughter products of photodegradation are not modeled further, i.e., it is
assumed that all chemicals are photodegraded into non-toxic compounds. AOPWIN data also
contains certain empirically-derived air decay rates. For the RSEI model, a concentration of
hydroxyl radicals of 1.5 x 106 molecules/cm3 is used to convert the second-order rate constant
62 For a few chemicals, other sources were used. See Technical Appendix B - Physicochemical Properties for TRI
Chemicals and Chemical Categories, for the source used for each chemical.
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provided in AOPWIN to a first-order rate constant. Furthermore, the rate is divided by a factor of
two to reflect an assumed average day length of 12 hours:
5.3.6.4 Human Exposure Data and Assumptions
For the air exposure pathway, sex- and age-specific inhalation rates and body weights are used in
the RSEI model. The primary source for all exposure factors used in the model is EPA's
Exposure Factors Handbook (EPA, 2011, hereafter denoted as EFH)63, which provides a
summary of the available statistical data on various factors used in assessing human exposure.
These factors include: drinking water consumption, soil ingestion, inhalation rates, dermal
factors including skin area and soil adherence factors, consumption of fruits and vegetables, fish,
meats, dairy products, homegrown foods, breast milk intake, human activity factors, consumer
product use, and residential characteristics. In the EFH, EPA recommends mean values for the
general population and also for various segments of the population who may have characteristics
different from the general population. RSEI uses inhalation rates and body weights derived from
the recommended factors, except where noted.
EFH (EPA, 1997b, Table 5-23, p. 5-24) was used to estimate inhalation rates for eight age-sex
groups (ages 0-17, 18-44, 45-64, 65+).64 The inhalation rates recommended by the EFH were not
categorized into the same age groups used in RSEI. For children, the RSEI age groups were
broader than the EFH age groups. Therefore, the exposure factor was calculated using a weighted
average of the inhalation rates for all EFH age groups that overlap the RSEI age group as
follows:
63 The Exposure Factors Handbook can be found at https://www.epa.gov/expobox/about-exposure-factors-handbook
64 The RSEI model provides the ability to view risk-related scores for the 0-9 year old age group, however, there is
not a separate exposure factor for this age group. Instead, the exposure factor for the 0-17 year old age group is used.
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* 7.5 x JO6* 3600
(Eq. 5.6)
where:
air decay rate (hr"1)
second-order rate constant from AOPWIN
hydroxyl radical concentration (molecules/cm3)
constant to convert molecules/seconds to molecules/hour
constant to reflect assumed day length of 12 hours
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EF = (Eq. 5.7)
N
where:
£F = RSEI exposure factor,
IRi = intake rate for EFH age group z,
zz, = number of years that EFH age group z overlaps with the RSEI age
group, and
N = number of years in RSEI age group.
For adults, the EFH provides only one range of recommended inhalation rate for males and
females. The RSEI adult inhalation factors are based on weighted averages calculated from this
data, using Equation 5.7. The RSEI inhalation factors are then divided by age- and sex-specific
body weights, averaged to match the RSEI age groups using data provided in the EFH (EPA,
2011, Table 6-1). Exhibit 5.5 provides the range of data used, and Exhibit 5.6 presents the final
exposure factors used in the RSEI model. More detail on the derivation of the exposure factors
can be found in Technical Appendix C - Derivation of Model Exposure Parameters.
Exhibit 5.5
Range of Data Used to Estimate Exposure Factors
Parameter
Value
Source/Comment
Inhalation rate
3.6 -16.3 m3/day
(Varies by age)
EPA (2011)
Body weight
4.6 - 90.5 kg
(Varies by age and sex)
EPA (2011)
Exhibit 5.6
Inhalation Exposure Factors (m3/kg-day)
Model Age
Group
Male
Female
0-17
0.315
0.332
18-44
0.185
0.217
45-64
0.173
0.201
>65
0.159
0.187
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5.4 Modeling Water Releases
People may be exposed to chemicals released into water through a variety of ways. The RSEI
model focuses on potential chemical exposure in two ways: from drinking contaminated tap
water from a public water system whose drinking water intake was located in the path of a
chemical release; or from eating contaminated fish caught in a waterbody in the path of a
chemical release. The following sections first describe the methods used to calculate the initial
chemical concentrations in water for both potential exposure pathways, and then the different
methods used to calculate surrogate doses and potentially exposed populations for the drinking
water and fish ingestion pathway. The data section presents the data used for both exposure
pathways and the human exposure defaults and assumptions used.
5.4.1 Water Releases: Methods
5.4.1.1 Locating the Facility Discharge Flowline
The first step in assessing surface water releases is to locate the discharging facility on the RSEI
model grid using their lat/long coordinates, and the flowline (a linear, unbranched section of a
waterbody) into which the chemicals are discharged. To find the discharge flowline, RSEI uses
EPA records of Clean Water Act (CWA) discharge permits for facilities, which in some cases
specify the discharge flowline by the locational coordinates of the discharging outfall(s).
National Pollutant Discharge Elimination System (NPDES) permit records, including permit
conditions, permit limits, monitoring data (e.g., Discharge Monitoring Reports (DMRs)),
locational, and descriptive information are maintained in EPA's Integrated Compliance
Information System (ICIS-NPDES), which is incorporated in EPA's Enforcement and
Compliance History Online (ECHO) data system.
Facilities without outfall location coordinates are assumed to discharge to the nearest flowline, as
long as that flowline is within four kilometers of the facility and meets minimum criteria for flow
and flowline type, as described below in Section 5.4.3.1. If no outfall coordinates are available,
and no acceptable flowline is found within four kilometers, the discharge is not modeled.
Flowline data are not currently available for Alaska, Guam, American Samoa, and the Northern
Mariana Islands; therefore, no surface water releases are modeled for these areas.
5.4.1.2 Calculating Chemical Concentrations
Chemical concentrations in the receiving flowline at a distance x from the discharging facility at
time t are estimated by using a simple first-order decay equation. The facility is assumed to
release its annual discharge quantity at a constant rate throughout the year. Annual average
chemical concentrations are then estimated until one of three conditions occurs: (1) the release
has traveled 300 kilometers downstream; (2) the release has been traveling downstream for a
week; or (3) the chemical concentration reaches 1 x 10"9 milligrams/liter (mg/L). Within the
initial flowline, the mass quantity of the chemical discharge is assumed to be instantaneously
mixed with the flow at the upstream end of that flowline. The calculated chemical concentration
at the downstream end of the flowline is then converted back to a mass quantity (after any decay)
and the process is repeated in the next adjoining flowline. Flowlines are defined by intersections
with other hydrological features and these "nodes" initiate the next flowline. The chemical-
specific decay coefficient is predominantly based on abiotic hydrolysis or microbial
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biodegradation, but may also include photooxidation. The general form of the first-order decay
equation is as follows:
where:
Cx= Coe
~k \\
(Eq. 5.8)
Cx
Co
kwater
t
concentration at distance x meters from the facility release point
(mg/L)
initial concentration (mg/L), which equals chemical release
(mg/day) divided by mean flow
decay coefficient (sec"1)
time at which Cx occurs (sec), which equals x/u, where u is the
water velocity (m/sec)
For surface water releases, the RSEI model estimates chronic human health exposures for two
exposure pathways: drinking contaminated water and eating non-commercial contaminated fish.
The methods used to estimate each of these exposure pathways are described below.
5.4.1.3 Modeling the Drinking Water Pathway
Surrogate doses from drinking water are calculated using the chemical concentrations in
flowlines where drinking water intakes are located. Drinking water intake locations were
obtained from the Public Supply Database (PSDB), a database of drinking water system
information developed and maintained by the U.S. Geological Survey (USGS), based on
information in the EPA's Safe Drinking Water Information System (SDWIS). Each drinking
water intake is assumed to be drawing water from the flowline nearest to its plotted location. For
this exposure pathway, the chemical concentration in drinking water is assumed to be equal to its
flowline concentration (calculated at the upstream end of the flowline; conservatively using the
highest concentration), up to the level of the maximum contaminant level (MCL),65 where
applicable. Seventy-nine TRI chemicals had existing MCLs in effect during one or more
reporting years for which TRI data are available;66 this number includes metal compound
chemical categories, which are treated similar to their elemental metal forms. If the flowline
concentration exceeds the MCL, the drinking water is assumed to be treated to the level of the
MCL for the year of that release. For each flowline with a drinking water intake, the chemical
concentration is combined with standard exposure parameters (see Section 5.4.3.6) to yield a
surrogate dose:
65 Copper and lead have action levels instead of MCLs; however, RSEI models them in the same manner as MCLs.
This also applies to copper compounds and lead compounds, as metal compounds are modeled like their elemental
forms.
66 As MCLs are sometimes revised and new ones are added in the years of TRI reporting, RSEI applies MCL limits
for only the years that the MCLs were in effect. For several chemicals for which MCLs were first instituted in 1976
and then revised in 1991, the original MCL values were not readily available, so the revised values were also used
for the years before the revision. These chemicals are barium, cadmium, chromium, lead, lindane, mercury,
methoxychlor, nitrate, selenium, and toxaphene.
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where:
DOSE
C
water, flowline J- water
BW
(Eq. 5.9)
DOSEdw
C water, flowline
Iwater
BW
surrogate dose of chemical in drinking water (mg/kg-day)
average annual chemical concentration in the flowline of interest,
calculated at the upstream end of the flowline (mg/L)
drinking water ingestion rate (L/day)
human body weight (kg)
5.4.1.4 Estimating Population Size for the Drinking Water Exposure Pathway
To estimate the size of the potential population exposed to surface water releases of TRI
chemicals through drinking water, the RSEI model uses estimates of the population served by
each drinking water intake from USGS's PSDB, which incorporates population estimates from
the EPA's SDWIS67. However, this data set only lists the intake location and the number of
people served by the water system. In many cases, there are multiple water intakes per water
system. In the absence of other data, it is assumed that the total population of the public water
system may be exposed to the full concentration of the released chemical estimated at the
flowline where a public water intake is located (calculated at the upstream end of the flowline).
The drinking water intake information from SDWIS contains only the number of people served
by each drinking water system; it does not provide demographic or locational information for
those served (the time frame in which this information was collected also varies widely). To
derive demographic information (that is, age and sex breakdowns) for the population served,
RSEI uses the percentages of people in each of the ten age-sex categories for the total population
located in grid cells within an 80km radius of each flowline containing a drinking water intake
(this information is calculated for the fish ingestion pathway - see Section 5.4.1.6). Then, these
percentages are applied to the SDWIS intake population (population served), creating the
population groups that are used for calculating RSEI model results.
5.4.1.5 Modeling the Fish Ingestion Exposure Pathway
A second potential exposure pathway is through consumption of fish contaminated by chemicals
discharged into the water from facilities. These fish may be consumed by recreational and
subsistence fishers and their families.68 As in the drinking water exposure pathway, chemical
concentrations are calculated until one of the three conditions occurs: (1) the release has traveled
300 kilometers downstream; (2) the release has been traveling downstream for a week; or (3) the
chemical concentration reaches 1 x 10"9 mg/L. The chemical concentration in fish is estimated
using the following equation:
67 RSEI uses SDWIS data that is contained in the USGS Public Supply Database (PSDB), see Section 5.4.3.2. More
information about SDWIS can be found at https://www.epa.gov/enviro/sdwis-search.
68 Although store-bought fish may also contain chemicals originating from facilities, modeling this exposure
pathway is not currently possible.
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Cfish,flowline Cwater,flowline * BCF
(Eq. 5.10)
where:
Cfish, flowline
C water, flowline
BCF
chemical concentration in fish in the specified flowline (mg/kg)
average annual chemical concentration in the flowline of interest
(mg/L)
bioconcentration factor for chemical (L/kg)
The chemical concentration in fish in a flowline is combined with exposure assumptions to
determine the surrogate dose from this exposure pathway:
where:
DOSEf c =
c fish,flowline*1 fish,pop
BW
(Eq. 5.11)
DOSE fc
Cfish, flowlin
I fish, pop
BW
surrogate dose of chemical c from facility /(mg/kg-day)
average annual chemical concentration in fish tissue (mg/kg)
fish ingestion rate for recreational or subsistence fishers (kg/day)
human body weight (kg)
5.4.1.6 Estimating Population for the Fish Ingestion Exposure Pathway
The RSEI model uses several steps to estimate the population within each grid cell that
consumes non-commercial fish. First, a county-level dataset containing the number of fishing or
hunting/fishing combination licenses was created from state fish and wildlife licensing data for
1996 (if 1996 data were not available, 1997 data were used). The number of fishing licenses in a
county is then divided by the 1990 total population in the county.69 The resulting ratio is
multiplied by the population in each grid cell in each year to obtain the number of individuals
with fishing licenses within that grid cell. To account for family members who also eat fish
caught by a fisher, the RSEI model multiplies the number of fishers by 2.62, the size of the
average U.S. household in 1995 (U.S. Census Bureau, 1996). The total population in a grid cell
consuming non-commercial fish is described by the following equation:
FishPopceiiy = TotalPopceuy * Uc^es * FamSize (Eq. 5.12)
where:
FishPopceii, y = total fish-eating population in a grid cell in year y
TotalPopceii,y = total resident population in a cell in year j' (see Section 5.1.3)
69 If no licensing information for a county was available, all of the grid cells in that county are assigned the ratio of
total state licenses to total state population. If no information was available for the state in which the grid cell is
located, the ratio for the state closest to that grid cell is assigned.
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Licenses = number of fishing licenses in the county or state in 1996 or 1997
Pop = total population in the county or state in 1990
FamSize = average family size in 1995
Next, the population that consumes fish is then apportioned based on whether fish are eaten
recreationally or for subsistence. Recreational fishers may fish during only certain times of the
year for recreational purposes or to supplement their diet. In contrast, subsistence fishers may
fish throughout the year and a major part of their diets may consist of the fish they catch. Data
are lacking on the numbers of recreational compared to subsistence fishers; RSEI follows
guidance from EPA's Office of Water (Harrigan, 2000). The RSEI model assumes that of the
population that eats non-commercial fish, 95 percent eat fish on a recreational basis, and the
remaining 5 percent subsist on fish. This apportionment is described by the following
relationships:
RecPopcell = FishPopcell * 0.95 (Eq. 5.13)
SubsistP opcell = FishPopcell * 0.05 (Eq. 5.14)
where:
RecPopcell = recreational fishers (and families) in a grid cell
SubsistP op ceii = subsistence fishers (and families) in a grid cell
The fishing population in each grid cell is then assigned to specific flowlines where they are
presumed to catch fish. This is done in two steps. First, overlapping circles of 80km radii
associated with each of the two to seven points that describe individual flowlines are used to
define those grid cells that will be modeled for fishing population in the 48 contiguous states
(i.e., all fishing areas within 80km of all stream flowlines). The distance of 80 kilometers (50
miles) from the flowline is chosen based on a finding reported in the 1991 National Survey of
Fishing, Hunting, and Wildlife-Associated Recreation that 65 percent of anglers travel less than
50 miles to fish (U.S. Department of the Interior, 1993). This distance approximates the size of
many counties and corresponds with the use of county-level fishing license data.
Second, all flowlines within an 80km radius of the center of each grid cell from the first selection
are identified. The fish-eating population in the grid cell is apportioned to each surrounding
flowline based on the ratio of the length of that flowline to the total flowline kilometers within
80 km of the grid cell. For example, flowlines A and B may be located within 80 km of a given
grid cell. If flowline A is 15km in length and flowline B is 5km in length (and the entire length
of each flowline is completely within 80km of the grid cell), then a total of 20km of flowlines are
located within the specified distance. Because flowline A represents three-fourths (15/20) and
flowline B represents one-fourth (5/20) of total kilometers, the RSEI model therefore assumes
that three-fourths of the fishing population in the grid cell catches fish from flowline A and one-
fourth catches fish from flowline B. Note that the RSEI model uses only the portion of the
flowline's length that is within 80km of the grid cell.
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Because of the size of the database created, the fishing population data attributed to individual
flowlines is summed and stored at the flowline level. The percentage of people in each of the ten
age-sex categories for the aggregated total fishing population (reflecting the ratio of the various
age and gender populations in the neighboring grid cells) is also maintained for each flowline.
The RSEI model then matches the chemical concentration in fish in the appropriate flowline to
the correctly-apportioned population. This is done for all flowlines that have modeled chemical
concentrations.
5.4.2 Calculating the RSEI Score for Water Releases
RSEI risk-related scores for drinking water and fish ingestion are calculated by generating a
surrogate dose for each unique combination of chemical release, flowline, and exposure
pathway, then multiplying this surrogate dose by the chemical toxicity weight and the potentially
exposed population. The RSEI Score for a surface water release from a facility is calculated by
adding the drinking water score and the fish consumption score (recreational and subsistence
fishing) for each flowline and then summing the scores over all flowlines affected by the
chemical release (up to 300 kilometers downstream from the facility). Exhibit 5.7 shows the
approach for calculating the RSEI Score for surface water releases.
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Exhibit 5.7
Calculating the RSEI Score for Water Releases
Discharge to receiving
stream or waterbody
(Ibs/yr)
Water volume and velocity
estimates; decay equation
Population data and Population data and
chemical toxicity weights chemical toxicity weights
flowlines and both
exposure pathways
±
RSEI Score for Water
Releases
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5.4.3 Water Releases: Data
A variety of data are required to estimate exposure to chemical discharges to surface waters. The
parameters required for surface water modeling and the data sources used are listed in Exhibit
5.8 and described further below.
Exhibit 5.8
Water Modeling Parameters
Parameter
Value (Units)
Source/Comment
Chemical discharge rate
Site-specific (lbs/yr)
TRI (2021-1988)
Flowline location
Lat/long in decimal degrees
NHDPlus Version 2 (U.S.
EPA/USGS, 2012)
Drinking water intake location
and population served
Lat/long in decimal degrees and
number of persons
Public Supply Database
(2012), based on SDWIS
Water flow
mean flow (million L/day)
NHDPlus Version 2 (U.S.
EPA/USGS, 2012)
Decay rate of chemical in water
chemical-specific (sec1)
SRC (1994-99)
Pollutant chemical concentration
in flowline
(mg/L)
calculated
Bioconcentration factor
chemical-specific (L/kg)
SRC (1994-99);
Lyman et al. (1990);
EPA (1999b)
Fish tissue concentration
(mg/kg)
calculated
Family size
2.62 (people/household)
U.S. Census Bureau (1996)
5.4.3.1 Flowline Assignments
Each facility is matched to an EPA-assigned discharge flowline, or if no assigned discharge
flowline is available, the facility is assumed to discharge into the nearest flowline within four
kilometers of the facility. Certain minimum criteria regarding flow and flowline type are applied
to the set of potential discharge flowlines, as explained below. If no acceptable flowline is found
within four kilometers, then the water discharge is not modeled. The flowlines used in the RSEI
model are linear sections of streams, lakes, reservoirs, and estuaries that are linked to form a
skeletal structure representing the branching patterns of surface water drainage systems. Non-
transport flowlines (i.e., those that do not have an upstream or downstream connection) are
excluded from the RSEI model.
Certain criteria were applied to the NHDPlus dataset to select the flowlines to be used in the
RSEI model. Specifically, because RSEI calculates the movement of a chemical release
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downstream using flow and velocity data, qualifying flowlines must have at least one
downstream or upstream connecting flowline70, and have a non-negative flow and velocity. The
RSEI model will not calculate chemical concentrations for certain types of flowlines, such as
coastlines, treatment reservoirs, and bays; the downstream path of any chemical is assumed to
stop if one of these types of flowlines is encountered. Additionally, some types of flowlines are
excluded from the set of fishable flowlines, such as pipelines, aqueducts, and certain types of
reservoirs. NHDPlus does not separate canals (presumably fishable) and ditches (presumably not
fishable), so the RSEI model excludes flowlines in the canal/ditch category if the annual mean
flow is less than 5 cubic feet per second (ft3/s). This is an arbitrary minimum, and is intended
primarily to exclude ditches at the point of the facility discharge. For flowlines designated as not
fishable in NHDPlus, the chemical is still assumed to travel downstream to the next flowline,
which may or may not be fishable.
Because NHDPlus contains a large number of flowlines with very small annual mean flows, the
RSEI model also excludes the very smallest flowlines from assignment as discharge flowlines.
To determine an appropriate minimum, a national set of EPA-assigned discharge flowlines from
the ICIS-NPDES database was matched to the NHDPlus annual mean flow data. For each
NHDPlus region, the non-zero annual mean flows were ranked, and the fifth percentile flow for
each region was selected as the minimum annual mean flow. Assigned regional minimum values
ranged from 0.0036 ft3/s to 1.9 ft3/s. For instance, if a facility in a region whose minimum value
was selected as 0.0036 ft3/s had a nearest flowline with annual mean flow of 0.0025 ft3/s, this
would not be selected as the discharge flowline. Instead the next closest flowline with a flow
equal or greater than 0.0036 ft3/s would be selected as the discharge flowline.
5.4.3.2 Drinking Water Intakes and Populations
Drinking water intake locations were obtained from the Public Supply Database (PSDB), a
database of drinking water system information developed and maintained by the U.S. Geological
Survey (USGS), based on information in EPA's Safe Drinking Water Information System
(SDWIS). SDWIS is a publicly accessible database that contains the information EPA uses to
monitor public water systems. The database contains information on over 156,000 water
systems, which serve over 96 percent of the U.S. population.71 SDWIS is operated and
maintained by EPA's Office of Water (OW). USGS's PSDB was designed to support USGS
analyses of the water resources used by public drinking water systems. The PSDB includes
SDWIS data, and supplements it with additional information about the waterbodies from which
systems draw their water. In addition, multiple quality assurance checks have been performed on
the data, including the lat/long coordinates.
The version of the PSDB used contains SDWIS population data from 2007, which was updated
during 2011. Approximately 11,400 drinking water intakes were included in the database.
Several types of intakes were excluded from the set used for RSEI modeling: 1) if the drinking
water system for the intake closed prior to 2002; 2) if the source water for the intake was
70 In the NHDPlus dataset, topologically connected flowlines with known flow are indicated by a "FlowDir" value
of "With Digitized." Only flowlines with this value for this field were included in RSEI modeling, which includes
2.6 million out of 2.9 million flowlines in NHD.
71 https://www.epa.gov/waterdata/drinking-water-tools.
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something that could not reasonably be expected to be connected a network of streams (such as
an aqueduct or an infiltration gallery); or 3) if the intake was emergency, interim (peak) or other
(rather than permanent or seasonal). Excluding these cases left 6,215 drinking water intakes that
are modeled in RSEI.
5.4.3.3 Water Flow and Velocity
The RSEI model uses NHDPlus Version 2 estimates of water flow and velocity based on the unit
runoff method,72 which was developed for the National Water Pollution Control Assessment
Model (NWPCAM). The unit runoff method calculates average runoff per square kilometer in a
watershed (8-digit hydrologic unit code (HUC)) based on gages in the HydroClimatic Data
Network (HCDN). These gages are usually not affected by human activities, such as major
reservoirs, intakes, and irrigation withdrawals; thus, the mean annual flow estimates are most
representative of "natural" flow conditions. Based on elevation and drainage patterns, each
square kilometer in a watershed is assigned to a catchment area, from which the runoff flows to a
specific flowline. The runoff from each catchment area is summed and attributed to its assigned
flowline. That flow is assigned to the next downstream flowline, to which the downstream
flowline's catchment runoff is added, and so on down the stream path. Unit runoff estimates are
calibrated for areas west of the Mississippi to account for water withdrawals and transfers.
NHDPlus velocities are estimated for mean annual flow conditions (using the unit runoff
method) based on the work of Jobson (1996). This method uses regression analyses on hydraulic
variables for over 980 time-of-travel studies, which represent about 90 different rivers in the U.S.
representing a range of sizes, slopes, and channel geometries. Four principal flowline variables
are used in the Jobson methods: drainage area, flowline slope, mean annual discharge, and
discharge at the time of the measurement.73
5.4.3.4 Water Decay Rates
Water decay rates are required to model downstream chemical concentrations. The primary
sources for water decay values were SRC, Inc.'s CHEMFATE database, a component of SRC's
Environmental Fate Data Base (SRC, 2002a), which contains experimental data, and SRC's
aqueous hydrolysis rate program, HYDROWIN (part of the Estimation Programs Interface (EPI)
Suite of estimation programs (SRC, 1994-1999)), both of which were developed for the EPA.
The CHEMFATE database contains environmental fate and physical/chemical property
information for commercially-important chemical compounds, including TRI-listed chemicals.
HYDROWIN estimates hydrolysis rate constants for esters, carbamates, epoxides, halomethanes,
and selected alkyl halides. Values of water decay rates can be found in Technical Appendix B -
Physicochemical Properties for TRI Chemicals and Chemical Categories.
5.4.3.5 Bioconcentration Factors
Bioconcentration factor (BCF) is the term used to describe the equilibrium concentration of
chemicals in aquatic organisms living in contaminated water. The BCF is defined as the ratio of
72 NHDPlus also contains estimates developed using the Vogel method, but this method is considered to have a
narrow band of applicability.
73 For more information, see the NHDPlus User's Guide (US EPA/USGS 2012) at
https://www.epa.gov/waterdata/learn-more
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the chemical concentration in the organism (mg/kg) to that in the surrounding water (mg/L). The
term "bioconcentration" refers to the uptake and retention of a chemical by an aquatic organism
from the surrounding water only ^ Experimental BCF values were obtained from SRC's
CHEMFATE database. Other BCFs were estimated from either log(Kow) values using regression
equations from Lyman et al. (1990), or from the SRC estimation program BCFWIN. See
Technical Appendix B - Physicochemical Properties for TRI Chemicals and Chemical
Categories, for values and references for the BCFs of chemicals used in the RSEI model.
5.4.3.6 Human Exposure Assumptions
Drinking Water. For the drinking water exposure pathway, the RSEI model uses estimates for
the amount of tap water ingested to estimate exposure. As in the stack and fugitive air release
pathways, data are acquired from the February 2019 update to Chapter 3 of EPA's Exposure
Factors Handbook (EFH) (EPA, 2019). The EFH recommends mean tap water ingestion values
for males and females combined from EPA's analysis of National Health and Nutrition
Examination Survey (NHANES) data from 2005-2010.
Drinking water ingestion rates per body weight were calculated for each of the RSEI modeled
groups (male and female: ages 0-17, 18-44, 45-64, 65+)75 using the weighted average approach
presented in Equation 5.7. The final drinking water exposure factors are presented in Exhibit 5.9.
More detail on the derivation of exposure factors can be found in Technical Appendix C -
Derivation of Model Exposure Parameters.
Exhibit 5.9
Drinking Water Exposure Factors
Model Age Group
Exposure Factors
(Male)
Exposure Factors
(Female)
(L/kg-day)
0-17
0.0101
0.0101
18-44
0.0099
0.0099
45-64
0.0117
0.0117
>65
0.0108
0.0108
74 The BCF can underestimate the accumulation of chemicals that are highly persistent and hydrophobic as
compared to the bioaccumulation factor (BAF), which measures the uptake and retention of a chemical by an
aquatic organism from all surrounding media (e.g., water, food, sediment). The bioaccumulation factor (BAF) is
defined as the ratio of the chemical concentration in the organism (mg/kg) to that in the surrounding water (mg/L),
in situations where both the organism and its food are exposed. Due to data limitations at the present time, only
BCFs are used in the RSEI model.
75 The RSEI model provides the ability to view risk-related scores for the 0-9 year old age group, however, there is
not a separate exposure factor for this age group. Instead, the exposure factor for the 0-17 year old age group is used.
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Fish Ingestion. The RSEI model uses annual estimates of the amount of fish ingested by
recreational and subsistence fishers and their families. However, there are no national data on
fish ingestion rates specific to recreational and subsistence fishers. In the absence of such data,
the RSEI model uses fish ingestion rates from the 1994-1996 U.S. Department of Agriculture
(USDA) Continuing Survey of Food Intake by Individuals (CSFII). This survey was conducted
by the USDA in 50 states and the District of Columbia over a three-year period. A total of
15,303 individuals provided two non-consecutive days of data on dietary intake. Appropriate
statistical techniques were used to extrapolate to the national population. In a 2002 publication,
EPA assigned specific fish species to habitats (freshwater, estuarine, and marine) based on the
majority of time the species spend in those habitats (EPA, 2000). Based on these assignments,
EPA estimated a distribution of uncooked finfish and shellfish ingestion rates specific to
freshwater and estuarine fish.76 As recommended by EPA's Office of Water (Tudor et al., 2000),
for environmental assessments, the 90th percentile is used to represent ingestion rates for
recreational fishers, and the 99th percentile is used for subsistence fishers. The ingestion rates are
reported by age group (<15 years, 15-44 years, 45+ years) and sex (EPA, 2002). These values
are roughly similar to ingestion rates obtained from regional studies of recreational fishers and
subsistence fishers, respectively. Fish ingestion values were estimated for the RSEI model age
groups using Equation 5.7. These values are then divided by age- and sex-specific body weights,
averaged to match the RSEI model age groups using data provided in the EFH (EPA, 2011,
Tables 8-4 and 8-5). Exhibit 5.10 presents the fish ingestion rates used in the RSEI model. More
detail on the derivation of exposure factors can be found in Technical Appendix C - Derivation
of Model Exposure Parameters.
Exhibit 5.10
Fish Ingestion Exposure Factors
Recreational (g/kg-day)1
Subsistence (g/kg-day)1
Model Age Group
Male
Female
Male
Female
0-17
0.0678
0.0288
2.37
1.85
18-44
0.182
0.0862
1.76
1.50
45-64
0.362
0.229
1.85
1.41
>65
0.398
0.255
2.04
1.57
1 Fish ingestion exposure factors are converted to kg/kg-day for the surrogate dose calculation in the RSEI model.
5.5 Modeling Transfers to POTWs
TRI reporting has included chemical data and information on off-site transfers to publicly owned
treatment works (POTW) facilities since the first year of TRI reporting (reporting year 1987). As
part of the TRI reporting requirements, subject facilities are required to report total annual
quantities of TRI-listed chemicals in wastes that they send off site to each POTW for further
76 Consumption of marine fish is not included in the ingestion rates, because marine areas are not modeled in RSEI.
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waste management.77 The most common transfers of this type are conveyances of the toxic
chemical in facility wastewater through underground sewage pipes; however, materials may also
be trucked or transferred via some other direct methods to a POTW.
The Pollution Prevention Act (PPA) of 1990 introduced additional TRI reporting requirements
for subject facilities on source reduction and waste management activities, effective for TRI
beginning with reporting year 1991. With these new reporting requirements, subject facilities
were not only now required to report the quantities of TRI-listed chemicals transferred off site to
POTWs during a given reporting year, but were also required to use their best readily-available
information to provide estimates on the ultimate disposition of the chemicals following their
transfer to POTWs. If information (data) on a recipient POTW's removal efficiencies and waste
management activities involving TRI chemicals are readily available, reporting facilities should
use such data. In cases where reporting facilities do not have information on the removal
efficiencies and environmental fates of TRI chemicals once at POTWs, EPA provides chemical-
specific default POTW distribution percentages for TRI reporting purposes.78
TRI default POTW distribution percentages for specific TRI-listed chemicals and chemical
categories are located in Table III of the most recent version of EPA's TRI Reporting Forms and
Instructions (RFI) annual guidance document, on EPA's TRI Guidance-Made Easy (GuideME)
webpages, and are also programmed into EPA's internet-based software application for
electronic filing of TRI reporting forms, Toxics Release Inventory-Made Easy (TRI-MEweb).
The chemical-specific default TRI POTW distribution percentages and assumptions EPA
provides in the above-mentioned sources are based on and derived from experimental and/or
estimated POTW removal (treatment), within-POTW partitioning rate data, and fundamental
principles of chemistry. Underlying data sources used to populate Table III of the TRI RFI
include POTW operational performance field studies, experimentally-measured laboratory
results, and prediction model estimates.79 Table III does not contain POTW distribution
percentages for all TRI-listed chemicals and chemical categories. For chemicals and chemical
categories not included in this table, the default assumption is that 100% of the chemical or
chemical category transferred to a POTW is treated for destruction, with the exception of metals,
metal compound categories, and for per- and polyfluoroalkyl substances (PFAS),80 for which the
default assumption is that none of the quantities of these chemicals transferred to POTWs are
treated for destruction at the POTWs, and that 100% of the transferred quantity is released to the
environment.
EPA's understanding is that these default distribution percentages and assumptions are realistic
expectations for typical POTWs handling TRI chemicals and that the Agency will incorporate
77 POTWs are not subject to TRI reporting requirements, but are regulated under other EPA regulations and
programs such as those under the Clean Water Act.
78 See the "POTW Percentages" tab under "Reporting Forms and Instructions" at
https://ordspub.epa.gov/ords/guideme ext/f?p=guideme:rfi-home for more information.
79 See Technical Appendix B - Physicochemical Properties for TRI Chemicals and Chemical Categories, for more
details.
80 This default PFAS assumption for POTW distribution percentages will remain in effect until more accurate
information becomes available and that better describe the disposition of PFAS at POTWs.
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improved default POTW distribution percentages when it learns of more accurate data. In pursuit
of this goal and to more closely align with how transfer quantities to other off-site facilities (i.e.,
non-POTW facilities) are reported, the TRI Program has incorporated new POTW waste
management activity transfer codes, effective for reporting year 2018. EPA is currently
evaluating screening-level exposure methodologies which might be used and incorporated into
the RSEI model to better assess risk-related impacts pertaining to these new reportable POTW
waste management activity transfer codes.
Overall, to predict the environmental fate of TRI-listed chemicals transferred to POTWs, EPA
uses data on chemical removal efficiencies at POTWs and of the ultimate fate of the chemical
amount removed. The amount of the chemical removed by POTWs is divided into the
percentages removed by (1) sorbing to sludge, (2) volatilizing into the air, or (3) degradation.
The remaining amount (i.e., the portion not removed by POTWs) is the percentage of the influent
TRI chemical that remains in POTW effluent untreated and ultimately discharged into surface
waters, which could potentially result in human exposure through drinking water or fish
ingestion.
The following sections describe the method and data used to model transfers to POTWs.
5.5.1 Transfers to POTWs: Method
Each TRI-reported chemical waste transfer to a POTW is modeled in RSEI as entering the
POTW as liquid influent. Dependent upon on the chemical's physicochemical properties, the
RSEI model uses estimates of POTW removal efficiencies and within-POTW partitioning
percentages to describe the environmental fate of TRI chemicals that are sent off site to POTWs.
Modeling exposures from TRI-reported chemical transfers to POTWs requires: (1) location of
the POTWs to which the TRI-listed chemicals are transferred, (2) location of the flowlines to
which the POTWs discharges, (3) consideration of overall removal efficiencies of POTWs and
resulting effluent discharges from POTWs (e.g., chemical-specific removal rates), and (4) waste
management handling and activities at POTWs (environmental partitioning within the POTW
and ultimate disposition of the chemical(s)).
5.5.1.1 Locating the POTW
In order to model discharges from POTWs, these facilities must first be located on the RSEI
model grid. Like other off-site facilities, POTW names and addresses are reported to the TRI by
the facility transferring its chemical waste. Latitude and longitude coordinates of the receiving
POTWs are not reported to the TRI Program. In order to derive lat/long coordinates, the reported
street addresses were geocoded for RSEI Version 2.1.3 (lat/long coordinates were assigned based
on street address).81 POTWs (as well as incinerators) were matched to EPA's Facility Registry
Service (FRS), based on name, address, and Resource Conservation and Recovery Act (RCRA)
identification number, where possible. Duplicate entries for the same POTW (in the common
instance where two or more TRI-reporting facilities have transferred to the same POTW) were
collapsed to a single entry using an approximate string-matching program (see Technical
Appendix D - Locational Data for TRI Reporting Facilities and Off-site Facilities, for more
81 Geocoding services were provided by Thomas Computing Services, a commercial firm.
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details). Once latitude and longitude coordinates are assigned (from geocoding, the FRS data, or
based on zip code centroids), the data are used to map the POTW to the RSEI grid cell with the
same coordinates. Substantial data processing was necessary to prepare the set of off-site
facilities (including POTWs) for use in the RSEI model; see Technical Appendix D - Locational
Data for TRI Reporting Facilities and Off-site Facilities, for more details on the steps that were
taken.
5.5.1.2 Locating the POTW Discharge Flowline
As with TRI-reporting facilities, the POTW's discharge flowline must be identified. The main
data used to accomplish this are EPA records of Clean Water Act (CWA) discharge permits for
POTWs, which in some cases specify the discharge flowline by the locational coordinates of the
discharging outfall(s). National Pollutant Discharge Elimination System (NPDES) permit
records, including permit conditions, permit limits, monitoring data (e.g., Discharge Monitoring
Reports (DMRs)), locational, and descriptive information are maintained in EPA's Integrated
Compliance Information System (ICIS-NPDES), which is incorporated in EPA's Enforcement
and Compliance History Online (ECHO) data system.
POTWs were matched to the FRS system based on name and address to obtain the FRS IDs for
each POTW. The FRS IDs were then used to access ICIS-NPDES and the assigned discharge
flowlines for each POTW. Approximately 3,000 records were matched to a discharge flowline
using this method.
POTWs not matched to an ICIS-NPDES discharge flowline were assumed to discharge to the
nearest flowline within four kilometers that meets the minimum flow requirements described
previously in Section 5.4.3.1.
5.5.1.3 Overall POTW Removal Rate
POTWs cannot completely remove all of the chemicals that are transferred to them from TRI-
reporting facilities, and as a result, some chemicals in POTW influent streams will be discharged
untreated as effluent to surface waters. To calculate the fraction of transferred chemical removed
by the POTW, typical chemical-specific POTW removal rates are applied to the quantities
transferred to the POTW from the TRI-reporting facility. See Technical Appendix B -
Physicochemical Properties for TRI Chemicals and Chemical Categories, for a listing of POTW
removal rates and references for each chemical. The remaining fraction is assumed to exit the
POTW untreated in water effluent. The water effluent quantities discharged from the POTW are
modeled in RSEI for the drinking water and fish ingestion exposure pathways using the same
methods for water releases described previously.
5.5.1.4 Partitioning within the POTW
The quantities of chemicals removed by POTWs are divided into percentages removed by (1)
sorbing to sludge, (2) volatilizing into the air or (3) degradation. The quantities of chemicals
removed by each of these three processes is modeled in RSEI using typical chemical-specific
within-POTW partitioning rates (see Technical Appendix B - Physicochemical Properties for
TRI Chemicals and Chemical Categories, for the listing of within-POTW partitioning rates and
references for each chemical).
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Once the environmental fate of chemicals entering POTWs is established, exposures associated
with the quantities of chemicals partitioned to each environmental compartment are estimated.
Chemical quantities discharged to surface waters in the POTW effluent are modeled in RSEI
using the water release evaluation methods described previously in Section 5.4. Chemical
quantities that degrade at the POTW are assumed to degrade into innocuous chemicals that do
not pose any further potential risk. Chemical quantities that volatilize off to air at the POTW are
treated like area source (non-point) air releases, as described earlier in Section 5.3.2 in the
fugitive air emissions evaluation method.
For exposures to chemical quantities that are removed via partitioning to sludge, the exposure
pathway estimates are dependent upon the sludge waste management activity employed and
utilized by the POTW. The specific method of sludge waste management utilized by POTWs
cannot be directly determined from the information reported by subject facilities to the TRI
program.82 Therefore, the RSEI model algorithm currently assumes all POTW chemical sludge is
landfilled at the POTW, a common method of sludge disposal. POTWs may in reality, however,
use other sludge waste management activities, such as sludge incineration, land
treatment/application farming, disposal to surface impoundments, and other land disposal
methods. These various waste management activities may result in different exposure levels and
may effect different exposed populations.
A summary of the RSEI approach to modeling chemical transfers to POTWs is found in Exhibit
5.11.
82 Newly implemented POTW waste management activity transfer codes (effective for TRI reporting year 2018),
however, may help to elucidate these quantities in the future.
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Exhibit 5.11
RSEI Modeling Approach for Chemical Transfers to POTWs
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5.5.1.5 Estimating Exposed Population Size from Transfers to POTW Model
The population exposed to fugitive air releases by within-POTW volatilization of the transferred
chemical is assumed to be the population within 49km around the POTW (see Section 5.3.2 for
more detail). The population exposed to POTW water effluent discharges surrounding the
POTW is further described in the section on exposed populations from surface water releases
(see Sections 5.4.1.2 and 5.4.1.4.). Populations exposed by releases to land from within-POTW
sorption to sludge (e.g., landfills) are not currently estimated and modeled in RSEI.
5.5.2 Transfers to POTWs: Data
Exhibit 5.12 presents the data sources used in the RSEI modeling of chemical transfers to
POTWs in estimating environmental releases and exposures from POTWs. In addition to the
parameter data presented here, data from the air release exposure pathway (see Exhibit 5.3), and
water release exposure pathway (see Exhibit 5.7) are also used. Environmental fate and exposure
factors specific to these pathways are described in their previous relevant sections.
Exhibit 5.12
Data Used to Estimate Environmental Releases from POTWs
Parameter
Value
Source/Comment
Chemical transfer to POTW
Site-specific (lbs/yr)
TRI (2021-1988)
POTW removal efficiencies
chemical-specific
RREL or STPWIN
(SRC, 1994-99)
Within-POTW partitioning
chemical-specific
RREL or STPWIN
(SRC, 1994-99)
5.5.2.1 POTW Removal Efficiencies and Within-POTW Partitioning
Data specific to this type of off-site transfer include chemical-specific POTW removal
efficiencies and within-POTW partitioning values. These parameters help to describe the
environmental fate of chemicals once transferred to POTWs. As further described in Technical
Appendix B - Physicochemical Properties for TRI Chemicals and Chemical Categories, the total
POTW removal efficiency is the total percentage of the chemical removed by the POTW (i.e.,
influent concentration minus effluent concentration divided by influent concentration). The
within-POTW partitioning values describe the fate of that portion of the chemical removed by
the POTW, that is, whether the chemical may sorb to sludge, volatilize into the air, or be
degraded. The within-POTW partitioning values are expressed as percentages of the total POTW
removal efficiency; that is, they sum to 100 percent.
POTW removal efficiencies were obtained primarily from the Treatability Database maintained
by EPA's Office of Research and Development (ORD), National Risk Management Research
Laboratory (NRMRL), Risk Reduction Engineering Laboratory (RREL). For any given
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chemical, the RREL Treatability Database provided a list of POTW 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.
Within-POTW partitioning values were obtained for most organic chemicals from EPA's
Exposure Assessment Branch (EAB), now presently grouped in the Existing Chemicals Risk
Assessment Division (ECRAD) within the Office of Pollution Prevention and Toxics (OPPT).
Inorganic chemicals, except for ammonia, were assumed to partition 100% to sludge. For
chemicals without data from these sources, SRC, Inc.'s Sewage Treatment Plant Fugacity Model
(STPWIN) was used to estimate total POTW removal efficiencies and within-POTW partitioning
values.
5.6 Modeling Other Off-site Transfers
Facilities subject to TRI reporting must also report the total annual quantities of TRI-listed
chemicals in wastes sent to all other off-site facilities (non-POTW facilities) for further waste
management activities. These types of off-site waste management activities include disposal,
treatment, energy recovery, and recycling operations. As part of the TRI reporting requirements,
TRI reporting facilities are required to report the names and addresses of the receiving facilities,
the quantities transferred, and the type of waste management activity used by the receiving off-
site facility.
Currently, only transfers of TRI-listed chemicals in wastes to off-site facilities for the purpose of
incineration are modeled by RSEI, and are further described below.
5.6.1 Transfers Off Site to Incineration: Method
To assess the exposure potential associated with off-site transfers to incineration, it is important
to have information about the off-site facility location and some of its operational characteristics.
Locations of other off-site facilities (i.e., non-POTW facilities) are determined in the same way
as the locations of POTWs. The reported street addresses were geocoded for RSEI Version 2.1.3
(lat/long coordinates were assigned based on street address).83 Incinerators (as well as POTWs)
were also matched to EPA's FRS, based on name, address, and RCRA identification number,
where possible. Duplicate entries for the same off-site facility (in the common instance where
two or more reporting facilities have transferred to the same off-site facility) were collapsed to a
single entry using an approximate string-matching program (see Technical Appendix D -
Locational Data for TRI Reporting Facilities and Off-site Facilities, for more details). Once
latitude and longitude coordinates for a facility are assigned (from geocoding, the FRS data, or
based on zip code centroids), the data are used to map the facility to the RSEI grid cell with the
same coordinates. See Technical Appendix D - Locational Data for TRI Reporting Facilities and
Off-site Facilities, for detailed information on locating off-site facilities.
TRI reporting requirements require the reporting facility to indicate the waste management
activity used at the off-site facility. If this information is not reported (despite the requirement),
83 Geocoding services were provided by Thomas Computing Services, a commercial firm.
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the off-site transfer is not evaluated in the RSEI algorithm, but is flagged as a missing value and
assigned a zero quantity.
Beginning with reporting year 1998, facilities in the commercial hazardous waste treatment
sector were subject to reporting requirements to the TRI Program. This introduces the potential
for "double counting" the quantities of some off-site transfers and on-site releases, as many of
the facilities in this industry sector also receive waste transfers from other TRI-reporting
facilities. Beginning with RSEI Version 2.3.5, adjustments were made in the RSEI model to
reported chemical waste transfer quantities to off-site facilities for incineration to help account
for this potential double counting. TRI-reporting facilities in NAICS code 562211 (Hazardous
Waste Treatment and Disposal), which is the most likely NAICS code in the commercial
hazardous waste treatment sector to include commercial hazardous waste incinerators, are
matched against the list of off-site facilities (reported by the transferring facilities). For any
matched facilities that receive a transfer for off-site incineration, it is assumed that the receiving
facility is reporting any on-site environmental releases (e.g., air releases) from this incineration
operation to the TRI Program. To correct for this potential double counting scenario, the reported
off-site transfer for incineration by the originating facility and the corresponding pounds and
modeled-based results related to this off-site transfer are dropped from the RSEI model. Since
the expansion of TRI-covered industry sectors to include the commercial hazardous waste
treatment sector was first in effective for reporting year 1998, only transfers quantities from 1998
and onward are adjusted.
For off-site chemical waste transfer quantities to incineration that are not dropped by the double
counting adjustments, incinerator destruction and removal efficiencies (DREs) are applied to the
off-site transfer quantity amount. Once the DREs have been applied, the resulting air releases are
modeled using the same method previously described for stack air emissions in Section 3.1,
using overall median values for stack parameters.
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5.6.2 Transfers Off Site to Incineration: Data
5.6.2.1 Incinerator Destruction and Removal Efficiencies
For organics, the destruction and removal efficiency (DRE) is assumed to be 99 percent (see
Technical Appendix B - Physicochemical Properties for TRI Chemicals and Chemical
Categories). The exceptions to the 99 percent removal assumption are for polychlorinated
biphenyls (PCBs) and for dioxin and dioxin-like compounds, which are assumed to have a DRE
of 99.9999 percent, as required by the Toxic Substances Control Act (TSCA) regulation. For
inorganics, DRE values are taken from multiple hearth sludge incinerator studies (EPA, 1992a).
5.7 Modeling Land Releases
Chemical releases to land include disposal84 to landfills, surface impoundments, land treatment
(application farming), underground injection wells, and other land disposal methods. For these
types of land releases, two major exposure pathways are of interest; volatilization of chemicals to
air and leaching of chemicals into groundwater. Any volatilization of chemicals from on-site
land disposal is reported to the TRI Program on reporting forms by subject facilities under
fugitive (non-point) air emissions quantities, and is modeled by RSEI as part of the facility's
fugitive air releases (see Section 5.3). Volatilization from off-site transfers to land disposal are
not currently modeled in RSEI. The potential for groundwater contamination from chemical
releases to land depends on the regulatory status of the land disposal unit in which the chemical
is disposed to. For example, chemical waste could be deposited in an on-site Resource
Conservation and Recovery Act (RCRA) Subtitle C-regulated hazardous waste unit, or in an on-
site RCRA Subtitle D-regulated non-hazardous solid waste management unit. RCRA Subtitle C
regulatory standards for hazardous waste units are designed to include technical controls to
prevent release of contaminants into groundwater. If chemicals are placed in such regulated
units, EPA assumes that releases to groundwater are negligible, so the RSEI model assigns a zero
value to the risk-related scores for such releases. If chemicals are placed in non-hazardous land
disposal units such as those regulated by RCRA Subtitle D (e.g., non-RCRA Subtitle C landfills,
non-RCRA Subtitle C surface impoundments, etc.), there may be a potential for chemical
groundwater exposure.
The current version of the RSEI model, however, does not provide risk-related modeling results
for these types of reported land releases. EPA is currently evaluating screening-level exposure
methodologies which might be used and incorporated into the RSEI model to assess risk-related
impacts pertaining to groundwater exposure from on- and off-site land releases and volatilization
from off-site land releases. For the time being, however, the RSEI model does provide the
capability for users to examine the quantities of releases (pounds) to land that are reported to the
TRIPprogram, as well as viewing these releases from a hazard-based perspective.
84 Disposal means any underground injection, placement in landfills, surface impoundments, land treatment, or other
intentional land disposal as defined under EPCRA (40 CFR 372.3).
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6. Calculating RSEI Results
This section summarizes the computation of the principal types of RSEI results. Because of the
multifunctional nature of the RSEI model, a wide variety of results can be created. The three
main kinds of results are described below.
Exhibit 6.1
Description of RSEI Results
Risk-related results (scores)
Estimated Dose x Toxicity Weight x Potentially Exposed
Population
Hazard-based results
Pounds x Toxicity Weight
Pounds-based results
TRI Pounds Released/Transferred
Risk-related results. The exposure route-specific chemical toxicity weight, estimated dose,
and potentially exposed population components are multiplied to obtain a risk-related score.
The estimated (surrogate) dose is determined through pathway-specific modeling of the fate
and transport of the chemical through the environment, combined with population-specific
exposure factors and assumptions. The final score generated is a unitless value that is not
independently meaningful, but is a risk-related measure that can be compared to other risk-
related values calculated using the same methodology. If toxicity data or other data required
for risk-related modeling are absent or zero, or if the waste management activity or exposure
pathway is not currently modeled in RSEI, then the risk-related score generated is zero. RSEI
risk-related scores are only calculated for certain types of chemical releases and transfers
(RSEI modeled media). The current RSEI modeled media are for stack and fugitive air
emissions, discharges to receiving streams or waterbodies, transfers off site to publicly
owned treatment works (POTW) facilities, and transfers off site to incineration.
• RSEI Score- Product of estimated dose, potentially exposed population, and the higher
toxicity weight for each exposure route (see Exhibit ES.2 for details).
• Cancer Score- Product of estimated dose, potentially exposed population, and the IUR or
OSF toxicity weight (see Exhibit ES.2 for details).
• Noncancer Score- Product of surrogate dose, population, and the RfC or RfD toxicity
weight (see Exhibit ES.2 for details).
Higher toxicity weights are typically associated with higher relative risk-related values (and
lower toxicity weights are typically associated with lower relative risk-related values). For
chemicals with cancer effects, multiplying the toxicity weights associated with cancer toxicity
and exposure to the chemical seems intuitive, since this is somewhat similar to the calculation of
cancer risk with a slope factor or unit risk value and the dose or exposure level. For chemicals
with noncancer effects, the multiplicative nature of the toxicity weights and exposure level may
not seem intuitive, because in risk assessments, risk is usually characterized as the estimated
exposure divided by the RfD/RfC. However, because of the manner in which the RSEI model
toxicity weights have been constructed, the product of toxicity weight and surrogate dose varies
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in the same direction and degree as the ratio of exposure to RfD/RfC. This is because the toxicity
weight is inversely related to the magnitude of the RfD/RfC. Thus, for a given dose or exposure
level, a chemical with a more stringent (i.e., lower) RfD/RfC will receive a higher toxicity value
than a chemical with a less stringent (i.e., higher) RfD/RfC, as shown in the following example:
Exposure
Toxicity
(i.e., surrogate
Weight *
R I'D (mg/kg-
Toxicity
Surrogate dose
dose) /RfD
Surrogate
day)
Weight
(mg/kg-day)
Ratio
Dose
Scenario 1
0.1
10
1
1/0.1 = 10
10*1=10
Scenario 2
0.01
100
1
1/0.01 = 100
100*1= 100
Since no adverse effects are expected to occur below the RfD/RfC, one could argue that releases
that result in surrogate doses below the RfD/RfC should be excluded. However, this approach
was not pursued for the following reasons: first, the estimation of surrogate dose is only a
screening-level approximation for the purposes of comparing one release quantity to another in a
relative way, and should never be considered an actual calculation of exposure. To exclude
release quantities resulting in surrogate doses below the RfD/RfC would incorrectly imply that
the method could predict precisely when doses would occur below the RfD/RfC. 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 potential risk, even if
each release quantity individually did not exceed the RfD/RfC. Finally, if the surrogate dose is
low, this will be reflected by a correspondingly low score relative to other release quantities for
that chemical.
Hazard-based results. Hazard-based results are calculated by multiplying the TRI chemical
waste management activity quantities (in pounds) by the appropriate chemical-specific toxicity
weight (the toxicity weight also depends on the exposure-specific pathway). The inhalation
toxicity weight is used for air releases of fugitive and stack emissions, and for transfers to off-
site incineration. The oral toxicity weight is used for water releases, land releases, and for
transfers to POTWs. For other types of chemical waste management activities (such as
recycling), the higher of the inhalation toxicity weight or the oral toxicity weight for the
chemical is used. For these results, no exposure modeling or population estimates are involved.
If there is no toxicity weight available for the chemical, then the hazard-based results are zero.
Hazard-based results can be calculated for modeled media (RSEI Modeled Hazard) or for any
TRI chemical waste management activity quantity. RSEI model hazard-based results provide an
alternative perspective to pounds-based results or full risk-related results, and are especially
valuable when necessary data for risk-related modeling are not available.
• RSEI Hazard- Product of TRI Pounds and the higher toxicity weight for each exposure
route (see Exhibit 4.4 for details).
• RSEI Modeled Hazard- Product of TRI Pounds and the higher toxicity weight for each
exposure route (see Exhibit 4.4 for details). Same as RSEI Hazard, but calculated for
RSEI modeled media only.
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• Cancer Hazard- Product of TRI Pounds and the IUR toxicity weight or the OSF toxicity
weight (see Exhibit 4.4 for details).
• Noncancer Hazard- Product of TRI Pounds and the RfC toxicity weight or the RfD
toxicity weight (see Exhibit 4.4 for details).
Pounds-based results. These results only reflect the waste management activity quantities as
reported to TRI and do not consider adjustments for toxicity or for exposure potential and
population size.
• TRI Pounds- Waste management activity quantity (e.g., chemical quantity released to
the environment or transferred off site for further waste management) in pounds per year.
This result includes quantities reported to all environmental media, whether or not they
are modeled by RSEI.
• RSEI Modeled Pounds- Waste management activity quantity (e.g., chemical quantity
released to the environment or transferred off site for further waste management) in
pounds per year, calculated only for RSEI modeled media, or the kinds of releases and
transfers that RSEI models.85
6.1 Combining RSEI Scores
Once all of the RSEI results are calculated, they can be combined and analyzed in many different
ways. The majority of RSEI results are designed to be additive, so a result for a specific set of
given parameters is calculated by summing the results for all of the relevant chemical waste
management activity quantities.86 This method is very flexible, allowing for countless variations
in the resulting outputs for data user needs. For example, RSEI results can be generated for
various subsets of parameters (e.g., chemicals, industry sectors, geographic areas) and compared
to each other to assess the relative contribution of each subset to the total proportional impact.
Or, RSEI results for the same subset of parameters for different years can be produced, to assess
the general trends in pounds-based, hazard-based, or risk-related results and potential impacts
over time.
It must be reiterated that while relative differences in RSEI results compared between years
would imply that there have been changes in potential hazard-based or risk-related impacts, the
actual magnitude of any specific change or the reason for the differences may not be necessarily
obvious. Although the RSEI results themselves may be useful in identifying chemicals or
geographic areas with the highest relative potential for hazard or risk, the values themselves do
not represent a quantitative estimate or provide an exact indication of the magnitude of
associated individual hazard or risk.
85 For transfers off-site to incineration, RSEI Modeled Pounds also reflects an adjustment made for double counting,
whereby quantities are dropped if the receiving facility is determined to also report to TRI.
86 Separate results can also be calculated for each exposure pathway component of an environmental release, such as
the drinking water or fish ingestion components of a given water release; however, in most user-facing applications
the RSEI model results are presented at the overall environmental release level.
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6.2 Adjusting RSEI Results for Changes in TRI Reporting
A change in the number of chemicals and/or facilities subject to TRI reporting can occur through
several mechanisms. The addition to or deletion of chemicals from the TRI list of toxic
chemicals will occur as EPA responds to petitions or initiates its own regulatory actions such as
through the chemical listing or delisting process. The largest revision to the TRI chemical list
occurred in November 1994, when the Agency added 245 chemicals and chemical categories to
the existing list, effective for the 1995 TRI reporting year. Other revisions to the TRI list have
occurred since, with one of the latest revisions being the additions of certain per- and
polyfluoroalkyl substances (PFAS) to the TRI list by the National Defense Authorization Act.87
Compliance with TRI reporting has changed over time, which has led to more facilities
reporting. Increases in the number of reporting facilities may also occur as a result of changes in
TRI reporting requirements. For instance, chemical activity threshold requirements for subject
facilities were decreased over the first few years of TRI reporting, in addition to lowered
thresholds for persistent bioaccumulative toxic (PBT) chemicals. The TRI Program has also
expanded the set of industrial facilities required to report such as including electric utilities,
mining facilities, commercial hazardous waste facilities, solvent recovery facilities, and
wholesale chemical and petroleum terminal facilities. All of these modifications can act to alter
the total chemical waste management activity quantities reported to the TRI Program and in turn
result in alterations to the RSEI model's computation of the associated relative risk-based
impacts and result values.
Such TRI reporting changes would not necessarily represent a large change in actual
environmental impacts, but rather would reflect a broader understanding of the impacts that may
have always existed prior to the reporting requirement changes. To maintain comparability in the
calculated RSEI results over time for purposes of meaningful time-series analyses, the RSEI
model must be adjusted in some manner when such changes to TRI reporting occur. Otherwise,
differences in reporting requirements over the years may skew or bias RSEI generated results
(e.g., increases in the number of reportable chemicals may erroneously imply increases in
potential risk-related impacts). To allow data users this ability to pursue meaningful trend
analyses, the RSEI model maintains and provides lists of data elements and flags that denote
changes to TRI reporting requirement over the years (such as "core chemicals" lists and a "new
industry" flag) that can be used to create consistent time-series analytical results. In addition, the
RSEI model also produces specific datasets that can be then be viewed and filtered to research
RSEI results for which the TRI reporting requirements have not changed during a certain time
period.
When deletions from the TRI chemical list occur, RSEI's chemical database is modified to
remove all RSEI results from previous TRI reporting years of the deleted chemical(s). Also, the
data in the TRI database are subject to ongoing data quality review and corrective actions by
both EPA and by TRI-reporting facilities. As a result, yearly comparisons could be flawed if
such corrective actions to reported data (e.g., withdrawn, revised, or newly submitted reporting
87 Section 7321 of the National Defense Authorization Act for Fiscal Year 2020 immediately added certain PFAS to
the list of chemicals covered by TRI and provided a framework for additional PFAS to be added to TRI on an annual
basis.
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forms) were not included in each previous RSEI model year's results. Therefore, RSEI model
results are recomputed every year, for all TRI reporting years on an annual basis in order to
incorporate chemical deletions, modifications, and reporting requirement changes to the reported
data that are contained in the TRI database.
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7. Dissemination of RSEI Data and RSEI Model
Results
RSEI model results are currently distributed in several different formats, for different users and
stakeholders. Additional data products may be created in the future. Users are advised to check
the RSEI website at https://www.epa.gov/rsei for updates and new products and features.
7.1 EasyRSEI Dashboard
Facility-level RSEI model results are currently distributed in the EasyRSEI dashboard, accessible
through an internet browser88 or through the RSEI website. The EasyRSEI dashboard allows
users to view and query RSEI model results for TRI reporting years 2012-current. A separate
dashboard is available for users who are interested in the full TRI reporting time series (1988-
current), and a RSEI Queries database for users comfortable in Microsoft Access is also
available for download.89
Users of the EasyRSEI dashboard can quickly and easily view trends and rankings and also filter
by dimensions such as state, chemical, industry, year, etc., with no downloading required.
Preformatted reports are also available for printing. Results can be used for screening-level
prioritization for strategic planning purposes, risk-related targeting, pollution prevention
opportunities, and for comparative trends analyses. Considerable resources can be saved by
conducting preliminary analyses with RSEI to identify risk-related situations of potential
concern, which may warrant further investigation and evaluation.
As noted above, users can evaluate RSEI information using a number of variables, such as
chemical, environmental medium, geographic area, or industry. For instance, the following types
of questions can be investigated:
• How do industry sectors compare to one another from a risk-related perspective?
• What is the relative contribution of chemicals within a given industry sector?
• What exposure pathways for a particular chemical pose the greatest potential risk-related
impacts?
Users can view pounds-based, hazard-based, and other results, to investigate the relative
influence of toxicity and population components on the risk-related results, which also
incorporate exposure modeling.
Information regarding the RSEI project is available on the RSEI website. Complete
documentation and contact information are all posted on the site. Periodic updates and
troubleshooting information are also available for users.
88 EasyRSEI is available at https://edap.epa.gov/public/extensions/EasvRSEI/EasvRSEI.html. The All Years version
is available at https://edap.epa.gov/public/extensions/EasvRSEI AllYears/EasvRSEI AllYears.html.
89 RSEI Queries and other data products are available at https://www.epa.gov/rsei/wavs-get-rsei-results.
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7.2 RSEI Geographic Microdata
RSEI Geographic Microdata90 datasets are also produced at various levels of aggregation, spatial
geographies, and time periods for data users. These detailed air and water modeling results allow
for a flexible ability to analyze RSEI model outputs and results from a receptor-based
perspective of potentially impacted geographic areas. In contrast to the suite of RSEI results that
are distributed in tools such as EPA's EasyRSEI dashboard and in EPA's Envirofacts data
warehouse,91 RSEI Microdata are not aggregated and assigned to the facility level, but rather
include values resulting from where the chemical releases and potential impacts may occur. With
the Microdata, geographic-based analyses are more intuitive; a state ranking is based on the
potential impacts that may occur within the geographic confines of each state, regardless of
where the chemical releases or generated wastes originate. The Microdata are provided for
looking at small-scale geographic areas, and users can examine the potential impacts that
environmental releases of toxic chemicals from multiple facilities may have on a particular area
from a relative risk-related perspective. RSEI Microdata are made available in a variety of data
and file formats to meet analytical needs. More information about downloading the RSEI
Microdata can be found on the RSEI website.
7.3 Other RSEI Data Products
RSEI model results can also be accessed in EPA data products like Envirofacts and the TRI
National Analysis. There is also a map with current-year results on the RSEI website. Additional
outlets for RSEI data are listed on the Ways to Get RSEI Results page on EPA's RSEI website.
90 The use of the word "Microdata" throughout this document should be interpreted to be synonymous and
interchangeable with the words "RSEI-GM" and "Geographic Microdata".
91 In order to make the RSEI data small enough to work with in a desktop database application, EasyRSEI adds up
potential impacts from certain waste management activities involving TRI chemicals and attributes them to the
facilities of origin. These facility-level results are also presented in Envirofacts.
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Chapter 8: References
8. References
General References
Bodek, I., W.J. Lyman, W.F. Reehl, and D.H. Rosenblatt. 1988. Environmental Inorganic
Chemistry. Pergamon Press. New York.
Boubel, R.W., et al. 1994. Fundamentals of Air Pollution. Academic Press. New York.
Canadian Ministry of National Health and Welfare. 1981. Tapwater Consumption in Canada.
Doc # 82-EHD-80. Public Affairs Directorate, Department of National Health and
Welfare, Ottawa, Canada.
Chow, V.T., Open-channel Hydraulics, McGraw-Hill, New York, 1959.
Dourson, M. 1993. Environmental Criteria and Assessment Office, U.S. Environmental
Protection Agency. Personal communication, October 19.
Ershow, A.G. and K.P. Cantor. 1989. Total Water and Tapwater Intake in the United States:
Population-Based Estimates of Quantities and Sources. Life Sciences Research Office,
Federation of American Societies for Experimental Biology.
Harrigan, P. 2000. Office of Water, U.S. Environmental Protection Agency (EPA). Personal
communication. March.
Horn, Marilee. 2008. U.S. Geological Survey (USGS). Written communication and provision of
data via email. April.
Jobson, H. E., Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams, U.S.
Geological Survey Water Resources Investigations Report 96-4013 (1996), U.S.
Geological Survey.
Lyman, W. J., W. F. Reehl, and D. H. Rosenblatt. 1990. Handbook of Chemical Property
Estimation Methods. American Chemical Society. Washington, D.C.
Price, Curtis. 2012. U.S. Geological Survey (USGS). Written communication and provision of
data via email. June.
Syracuse Research Corporation (SRC). 1994-1999. EPIWin v 3.01-EPA. Syracuse, NY.
Syracuse Research Corporation (SRC). 2002a. Chemfate/Environmental Fate Data Base.
Accessed online at http://esc.syrres.com/efdb.htm, see http://www.srcinc.com/what-we-
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RSEI supporting documentation released by EPA
These documents can be found on the RSEI website at https://www.epa.gov/rsei/rsei-
documentation-and-help.
RSEI Technical Appendices:
Technical Appendix A - Toxicity Weights for TRI Chemicals and Chemical Categories
Technical Appendix B - Physicochemical Properties for TRI Chemicals and Chemical
Categories
Technical Appendix C - Derivation of Model Exposure Parameters
Technical Appendix D - Locational Data for TRI Reporting Facilities and Off-site
Facilities
Technical Appendix E - Derivation of Stack Parameter Data
Technical Appendix F - Summary of Differences between RSEI Data and the TRI
National Analysis
TRI Relative Risk-based Environmental Indicators: Summary of Comments Received on the
Draft 1992 Methodology and Responses to Comments. Prepared for the Office of
Pollution Prevention and Toxics, Economics, Exposure and Technology Division,
Regulatory Impacts Branch. May 1997. Prepared by Abt Associates under Contract # 68-
D2-0175.
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Chapter 8: References
TRI Relative Risk-based Environmental Indicators: Methodology. Prepared for the Office of
Pollution Prevention and Toxics, Economics, Exposure and Technology Division,
Regulatory Impacts Branch. June 1997. Prepared by Abt Associates under Contract # 68-
D2-0175.
TRI Relative Risk-based Environmental Indicators: Interim Toxicity Weighting Summary
Document. Prepared for the Office of Pollution Prevention and Toxics, Economics,
Exposure and Technology Division, Regulatory Impacts Branch. 1997. Prepared by Abt
Associates under Contract # 68-D2-0175.
Ground-Truthing of the Air Pathway Component of OPPT's Risk-Screening Environmental
Indicators Model. December 1998.
Estimates of Stack Heights and Exit Gas Velocities for TRI Facilities in OPPT's Risk-Screening
Environmental Indicators Model. June 1999.
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