EPA’s Risk-Screening Environmental Indicators (RSEI) Methodology RSEI Version 2.3.9


v>EPA

Office of Pollution Prevention
Environmental Protection	and Toxics

Agency	Washington, DC 20460	December 2020

EPA's Risk-Screening
Environmental Indicators
(RSEI) Methodology

RSEI Version 2.3.9

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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. Subsequent EPA staff who managed the RSEI project include Gary Cole, Lynne
Blake-Hedges, Wayne Davis, and Mitchell Sumner. Development support has been provided by
Abt Associates Inc., Rockville Maryland since 1991. The original Abt development team
included Susan Keane, Brad Firlie, and Elizabeth Levy.

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Table of Contents

Table of Contents

Executive Summary	1

ES-l. Introduction	1

ES-2. General Description of the RSEI Model	3

ES-2.1 Geographic Basis of the Model	3

ES-2.2 RSEI Results	9

ES-2.3 Adjusting RSEI Results for Changes in TRI Reporting	10

ES-2.4 RSEI Data Products	11

ES-2.5 How the RSEI Chronic Human Health Toxicity Weightings Differ from

EPCRA Section 313 (TRI) Statutory Criteria	12

ES-3. Important Caveats Regarding the RSEI Model	13

ES-4. New Features in Version 2.3.9	15

1.	Introduction	16

1.1	Background	17

1.2	RSEI Data Products	19

1.3	Organization of this Document	19

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	25

2.2.1	Strengths	25

2.2.2	Limitations	26

3.	TRI Data Used in the Model	27

4.	Methods for Calculating Toxicity Weights	29

4.1	Toxicity Weighting Scheme for Carcinogens and Non-carcinogens	30

4.1.1	Qualitative Data	30

4.1.2	Quantitative Data	32

4.1.3	Method for Calculating Toxicity Weights	33

4.2	Selecting the Final Toxicity Weights	34

4.3	Chemical Categories	37

4.4	Sources of Toxicity Data	39

4.5	How RSEI Toxicity Weightings Differ from EPCRA Section 313 Criteria	42

5.	Exposure and Population Modeling	44

5.1	Geographic Basis of the RSEI Model	45

5.1.1	The RSEI Model Grid Cell System	45

5.1.2	Locating Facilities on the Grid	47

5.1.3	Locating People on the Grid	48

5.2	Pathway-specific Methods to Evaluate Chronic Human Exposure Potential	50

5.3	Modeling Air Releases	50

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5.3.1	Stack Air Emissions: Method	51

5.3.2	Fugitive Air Emissions: Method	54

5.3.3	Calculating Surrogate Dose for Air Releases	55

5.3.4	Estimating Population Size for Air Releases	55

5.3.5	Calculating the RSEI Score for Air Releases	55

5.3.6	Stack and Fugitive Air Releases: Data	58

5.4	Modeling Surface Water Releases	63

5.4.1	Surface Water Releases: Methods	63

5.4.2	Calculating the RSEI Score for Surface Water Releases	68

5.4.3	Surface Water Releases: Data	70

5.5	Modeling Transfers to POTWs	75

5.5.1	Transfers to POTWs: Method	76

5.5.2	Transfers to POTWs: Data	80

5.6	Modeling Other Off-site Transfers	81

5.6.1	Off-site Transfers to Incineration: Method	81

5.6.2	Estimating Population for Off-Site Transfers to Incineration	82

5.6.3	Off-site Transfers to Incineration: Data	83

5.7	Modeling Land Releases	83

6.	Calculating RSEI Results	84

6.1	Combining RSEI Scores	86

6.2	Accounting for Changes in TRI Reporting	86

7.	Current Implementation of the RSEI Method	88

7.1	EasyRSEI D ashb oard	88

7.2	RSEI Geographic Microdata	89

7.3	Other RSEI Data Products	89

7.4	Conclusion	89

8.	References	90

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Executive Summary

Executive Summary

ES-1. Introduction

EPA's Risk-Screening Environmental Indicators (RSEI) is a screening-level, multi-media model
that incorporates EPA's Toxics Release Inventory (TRI) information together with other data
sources and risk factor concepts to assess the potential chronic human health impacts of TRI
chemicals. To help provide context on the relative hazard and potential for risks posed by certain
waste management activities of TRI chemicals (e.g., from releases to the environment), RSEI
produces hazard estimates and unitless risk scores, which represent harm and relative risks to
human health following chronic exposure to a TRI chemical. RSEI can be used to quickly and
easily screen large amounts of chemicals and chemical emissions data from the TRI database,
saving time and resources. RSEI is particularly useful for examining trends that compare
potential relative risks from year to year, or for ranking and prioritizing chemicals, industry
sectors, or geographic regions for strategic planning. 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 human health
impacts over time.

Using estimates of pounds of chemical releases to investigate potential health and environmental
impacts is limited by the assumptions that all chemicals are equally toxic and that all people are
equally exposed. Formal risk assessments are more accurate, but are complicated and time
consuming to prepare, requiring detailed data that are not always available, and the results are
often limited in scope and geographic area. The RSEI approach augments estimates of chemical
pounds released with toxicity and exposure considerations, but does not address all of the
potential factors that would have to be included in a full risk assessment. Thus, RSEI 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 considers the following information: the amount of chemical released, the toxicity of the
chemical, its fate and transport through the environment, the route and extent of human
exposure, and the number of people affected. This information is used to create numerical values
that can be added and compared in limitless ways to assess the relative risks of chemicals,
facilities, industries, regions, and many other factors. The values generated are for comparative
purposes and only meaningful when compared to other values produced by RSEI. It should be
emphasized that the results are not a detailed or quantitative risk assessment, however, RSEI
results do offer a screening-level, risk-related perspective for relative comparisons of certain
waste management activities of TRI chemicals.

The RSEI approach is very flexible and can be implemented in many ways. The use of the 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 quantities, and release
and transfer locations are known or can be estimated.

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As an indication of improvements in environmental quality over time, RSEI provides a valuable
tool to measure general trends based upon relative risk-related impacts of TRI chemicals.
Although RSEI results do not capture all environmental releases of concern, they generally relate
changes in releases to relative changes in chronic human health impacts from a large number of
toxic chemicals of concern to the Agency. Importantly, RSEI provides an ability to analyze the
relative contribution of chemicals, facilities, and industrial sectors to human health impacts, and
RSEI results serve as an analytical basis for setting priorities for further risk analyses, pollution
prevention, regulatory initiatives, enforcement targeting, and chemical testing requirements.

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ES-2. General Description of the RSEI Model

The RSEI model calculates values that reflect the risk-related impacts on chronic human health
of modeled TRI chemical releases and transfers. These values do not provide absolute measures
of risk and can only be interpreted as relative measures to be compared with other such values
(reflecting the direction and the general magnitude of changes at different points in time when
analyzing trends, or screening for situations of potential concern).

The model uses the reported quantities of TRI chemical releases and transfers to estimate the
risk-related impacts associated with certain types of waste management activities of TRI covered
facilities. The risk-related impacts potentially posed by a chemical are a function of chemical
toxicity, the fate and transport of the chemical in the environment after it is released, the pathway
of human exposure, and the number of people exposed.1

All 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.

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 model calculates risk-related results for the air and surface water
exposure pathways only (i.e., stack and fugitive air releases, direct surface water discharges, and
transfers off-site to wastewater treatment and incineration). Hazard-based results are available
for other kinds of waste management activities for chemicals and chemical categories with
toxicity data.2 In cases where toxicity data are not available, only pounds-based results can be
viewed.

ES-2.1 Geographic Basis of the Model

The RSEI model relies on the ability to locate facilities and people geographically, and to
attribute characteristics of the physical environment such as meteorology and areas surrounding
the facilities once they are located. To locate the facilities and the attribute data to those
facilities, the model describes the U.S. and its territories3 as an 810 meter (m) by 810 meter grid

1 The method is focused on the general population; individuals, particularly highly exposed or susceptible
individuals, are not the focus of the model.

2 Chemicals and chemical categories with toxicity data account for 99% of the total release and transfer quantities
reported to TRI in 2019.

3 The model also includes Puerto Rico, the U.S. Virgin Islands, Guam, American Samoa, and the Northern Mariana

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system. For each cell in the grid, a location "address" in terms of (x,y) coordinates is assigned
based on latitude and longitude (lat/long).

In order to estimate potential human exposure, TRI facilities and the U.S. population must be
geographically located on the model grid. TRI facilities are located using the facilities' lat/long
coordinates. To locate population, the model uses decennial U.S. census data for 1990, 2000, and
2010 at the block level. These data4 are used to create detailed age-sex-defined population groups
for each of the census blocks in the U.S. 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

Because the census block boundaries change between decennial census years, each set of census
block level data is first transposed onto the model grid, which is unchanging, using an area-
weighted method. Once populations for 1990, 2000, and 2010 are placed on the grid system, the
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 for 1988-89 and the
straight-line plot between 2000 and 2010 is extrapolated forward to estimate population for the
years after 2010.

Once facilities and people are located on the model's grid system, three main components are
used to compute risk-related impacts in the model. These components are:

• The quantity of chemicals released or transferred,

• Adjustments for chronic human health toxicity, and

• Adjustments for exposure potential and population size.

Islands. 1990 U.S. census data were provided by GeoLytics, Inc., East Brunswick, NJ.

4 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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These components and the method used to combine them are described in the following sections.

Chemical Releases and Transfers. The model uses information on facilities' chemical releases
and transfers from these facilities to off-site facilities (such as sewage treatment plants and
incinerators) to model risk-related impacts. Other kinds of waste management activities, such as
underground injection or transfers off-site to recycling, are not modeled, but users can view
hazard-based results (toxicity-weighted pounds) or pounds-based results for these activities.
These quantities are reported by facilities to EPA's TRI program, as mandated by the Emergency
Planning and Community Right-to-Know Act. As of the 2019 reporting year, there are over 600
TRI chemicals and chemical categories listed.

Adjustments for Chronic Human Health Toxicity. The model is based on current EPA
methodologies for assessing toxicity. The method EPA has chosen for assigning toxicity weights
to chemicals is clear and reproducible, based upon easily accessible and publicly available
information, and uses expert EPA-wide judgments to the greatest extent possible. RSEI reflects
the toxicities of chemicals relative to one another using a continuous system of numerical
weights. Toxicity weights for chemicals increase as their inherent ability to cause adverse health
effect(s) increase. 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.

Values developed by EPA experts are used to differentiate the degrees and types of toxicity of
chemicals. Oral Slope Factors (OSFs) and Inhalation Unit Risks (IURs)5 provide information
pertaining to toxicity for chemicals that may cause cancer. Reference Doses (RfDs) and
Reference Concentrations (RfCs) provide toxicity information related to non-cancer effects.6
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 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 Documents;

5 The Oral Slope Factor represents the upper-bound (approximating a 95% confidence limit) estimate of the slope of
the dose-response curve in the low-dose region for carcinogens. The units of the slope factor are usually expressed
as (mg/kg-day)_1. The Inhalation Unit Risk is the upper-bound excess lifetime cancer risk estimated to result from
continuous exposure to an agent at a concentration of 1 (ig/m3 in air.

6 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 is likely to be
without an appreciable risk of deleterious non-cancer effects during a lifetime.

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•	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 (STSC);

•	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

•	Reference Concentrations (RfCs) in mg/m3

Each value is transformed into a toxicity weight, so that as the toxicity weight increases, the
toxic effect(s) increase. The algorithms used to assign toxicity weights are shown below in
Exhibit ES.l.

Exhibit ES.l

Algorithms for Assigning Toxicity Weights



Route of Exposure

Inhalation

Oral

Type of Effect

Cancer*

IUR / 2.8e-7

OSF/ le-6

Non-cancer

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.

Each chemical is assigned up to four toxicity weights, according to the availability of its RfC,
RfD, IUR, and OSF. The RSEI results may use different toxicity weights, depending on the data.

RSEI Hazard and RSEI Score use the higher cancer or non-cancer 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 non-cancer hazard and non-cancer score results only
use the RfC- or RfD-based toxicity weights.

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In addition, the RSEI score, cancer score, and non-cancer score 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 appropriate) for the portion of the POTW transfer that is released from
the POTW as effluent.7 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. Exhibit
ES.2 below summarizes the selection of toxicity weights for each kind of RSEI result.

Exhibit ES.2

Selection of Toxicity Weights for Each RSEI Result

RSEI Result

Air Releases

Water
Releases

Transfers to POTWs

Fill in Toxicity Data Gaps?

Score

Higher of IUR
tox weight or
RfC tox weight.

Higher of OSF
tox weight or
RfD tox weight.

For portion of transfer that
volatilizes during
wastewater treatment use
higher of IUR tox weight
or RfC tox weight. For
portion of transfer that is
released from POTW as
effluent 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.

Cancer
Score

IUR tox weight.

OSF tox
weight.

For volatilized portion use
IUR tox weight. For
POTW effluent release
portion use OSF.

No. If no route-specific
cancer tox weight, then
cancer score is zero.

Non-

Cancer

Score

RfC tox weight.

RfD tox weight.

For volatilized portion use
RfC tox weight. For
POTW effluent release
portion use RfD tox
weight.

No. If no route-specific non-
cancer tox weight, then non-
cancer score is zero.

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.

Cancer
Hazard

IUR tox weight.

OSF tox
weight.

OSF tox weight.

No. If no route-specific
cancer tox weight, then
cancer hazard is zero.

Non-

Cancer

Hazard

RfC tox weight.

RfD tox weight.

No. If no route-specific non-
cancer tox weight, then non-
cancer hazard is zero.

7 Chemical-specific POTW removal and within-POTW partitioning rates are used to determine the portion of each
transfer to a POTW that biodegrades, adsorbs to sludge, or volatilizes. The remainder is assumed to be released from
the POTW as effluent.

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The distribution of toxicity values for TRI chemicals corresponds to a range of toxicity weights
of 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.

There are over 600 chemicals and chemical categories on the 2019 TRI Chemical List. Toxicity
weights are available for over 400 of these chemicals and chemical categories.8 Chemicals and
chemical categories with toxicity weights account for 99% of the reported quantities for all
releases and transfers to modeled media in 2019.

Adjustments for Exposure Potential 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 waste management activity. The exposure
evaluations use models that incorporate data on pathway-specific chemical releases and transfers,
physicochemical properties, and where available, site characteristics to estimate the ambient
chemical concentrations in the environmental medium into which the chemical is released or
transferred. The ambient concentrations are combined with human exposure assumptions and
estimates of exposed population size specific to age and sex.

The algorithms for calculating surrogate doses rely on the ability to locate facilities and people
geographically on the 810m by 810m grid cell system described earlier. While this method uses
the EPA exposure assessment paradigm to evaluate exposure potential, the results should not be
construed as an actual numerical dose resulting from TRI chemical waste management activities.
Limited facility-specific data and the use of modeling that relies on default values and
assumptions for many input parameters prevent the calculations of an actual numerical dose. The
purpose of this methodology, rather, 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 model.
Please note that not all chemical waste management activities and resulting exposures from these
activities are currently modeled.

8 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").

1988-2019 TRI data

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ES-2.2 RSEI Results

Because of the multi-functional nature of the model, a variety of results can be generated. The
three main kinds of results are described below.

Exhibit ES.3
Description of RSEI Results

Risk-related results (scores)

Surrogate Dose x Toxicity Weight x Population

Hazard-based results

Pounds x Toxicity Weight

Pounds-based results

Waste management activity quantities

Risk-related results (scores). The exposure route-specific chemical toxicity weight, surrogate
dose, and population components are multiplied to obtain a risk-related score. The 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. The final score
generated is a unitless measure that is not independently meaningful, but is a risk-related
estimate that can be compared to other risk-related estimates calculated using the same
methodology. If toxicity data or other data required for modeling are zero, or if the exposure
pathway is not currently modeled, then the risk-related score generated is zero. RSEI risk-related
scores are only calculated for certain types of TRI chemical releases and transfers (modeled
media).

• RSEI Score- Product of surrogate dose, population, and the higher toxicity weight for
each exposure route (see Exhibit ES.2 for details).

• Cancer Score- Product of surrogate dose, population, and the IUR or OSF toxicity
weight (see Exhibit ES.2 for details).

• Non-Cancer Score- Product of surrogate dose, population, and the RfC or RfD toxicity
weight (see Exhibit ES.2 for details).

Hazard-based results. Hazard-based results ("Hazard") are calculated by multiplying the TRI
chemical 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 releases of fugitive air and stack air, and transfers to off-site incineration. The oral toxicity
weight is used for surface water releases and transfers to POTWs. For these results, no exposure
modeling or population estimates are involved. If there is no toxicity weight available for the
chemical, then the hazard score is zero. Hazard can be calculated for modeled media (modeled
hazard) or for any TRI waste management quantity.

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• RSEI Hazard- Product of TRI Pounds and the higher toxicity weight for each exposure
route (see Table ES.2 for details).

• RSEI Modeled Hazard- Product of TRI Pounds and the higher toxicity weight for each
exposure route (see Table ES.2 for details). Same as RSEI hazard, but calculated for
modeled media only.

• Cancer Hazard- Product of TRI Pounds and the IUR toxicity weight or the OSF toxicity
weight (see Table ES.2 for details).

• Non-Cancer Hazard- Product of TRI Pounds and the RfC toxicity weight or the RfD
toxicity weight (see Table ES.2 for details).

Pounds-based results. These results ("TRI Pounds") reflect only the number of pounds reported
to TRI for each waste management activity, and are available for all TRI-reported quantities.

Once all of the results are calculated, they can be combined in many different ways. All of the
results are additive, so a result for a specific set of variables is calculated by summing the scores
for all of the relevant waste management activity quantities.9

This method is very flexible, allowing for countless variation in the resulting outputs. For
example, results can be generated for various subsets of variables (e.g., chemical, facility,
exposure pathway) and compared to each other to assess the relative contribution of each subset
to the total potential impact. Or, results for the same subset of variables for different years can be
produced, to assess the general trend in pounds-based, hazard-based, or risk-related impacts over
time.

It must be reiterated that while changes in results over the years would imply that there have
been changes in hazard- or risk-related environmental impacts, the actual magnitude of any
specific change or the reason may not be obvious. Although the value itself may be useful in
identifying chemicals, facilities, or geographic locations with the highest potential for hazard or
risk, the score itself does not represent a quantitative estimate or provide an exact indication of
the magnitude of associated individual hazard or risk.

ES-2.3 Adjusting RSEI Results for Changes in TRI Reporting

When a change occurs in the number of or reporting requirements for chemicals and/or facilities
regulated by the TRI program, the numerical value of RSEI results will be altered if no
adjustments are made to the method of calculation to account for the changes respective to trend
analyses. However, such changes would not necessarily represent a large change in actual
environmental impact, but rather would reflect a broader understanding of the impacts that may
have always existed. To maintain comparability in the weights over time, the results must be
adjusted in some manner when such changes in TRI reporting occur.

9 Separate results can also be calculated for each exposure pathway component of an environmental release, such as
the drinking water exposure or fish ingestion components of a surface water release; however, in most user-facing
applications the RSEI model results are presented at the overall environmental release level.

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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 chemical list will
occur as EPA responds to petitions or initiates its own regulatory action through the chemical
listing or delisting process. The largest revision to the list occurred in November 1994, when the
Agency added 245 chemicals and chemical categories to the existing TRI chemical list, effective
for the reporting year 1995. Other revisions have occurred since. To allow for meaningful trend
analyses, the RSEI model maintains a list of "core chemicals" which have been reported on since
1987, and for which their reporting requirements have not changed.

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
reporting requirements. For instance, chemical activity threshold requirements for facilities were
decreased over the first few years of TRI reporting, in addition to lowered thresholds for
Persistent Bioaccumulative Toxic chemicals (PBTs). The TRI program has also expanded the set
of industrial facilities required to report to include 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 quantities reported to the
TRI program and in turn result in alterations to the model's estimate of the associated relative
risk-based impacts.

When deletions from the TRI chemical list occur, RSEI's chemical database is modified to
remove all results from previous reporting years. Also, the yearly TRI data in the TRI database
are subject to ongoing quality control review and correction by both EPA and by TRI-reporting
facilities. As a result, yearly comparisons could be flawed if such revisions to reported data were
not included in each previous year's results. Therefore, RSEI results are recomputed for all years
on an annual basis in order to incorporate chemical deletions and modifications to the reported
data.

ES-2.4 RSEI Data Products

Users can access RSEI model results in a variety of ways. RSEI results are included in EPA data
tools such as Envirofacts10 and the TRI National Analysis. RSEI results are also currently
distributed in the EasyRSEI dashboard, accessible on the Qlik Sense platform through an internet
browser11 or through https://www.epa.gov/rsei. The EasyRSEI dashboard allows users to view
and query all RSEI model results for TRI reporting years 2007-2019 for modeled media. Pounds-
and hazard-based results for non-modeled media, including waste management activities
reported in Section 8 of the TRI Form R, are also available. A separate Qlik Sense dashboard is

10 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."

11 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.

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available for users who are interested in the full TRI time series (1988-2019), and a RSEI
Queries database for users comfortable in Microsoft Access is also available for download.12

Users of the EasyRSEI dashboard can quickly and easily view trends and rankings and 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
ranking and prioritization for strategic planning purposes, risk-related targeting, and trends
analyses. Considerable resources can be saved by conducting preliminary analyses with RSEI to
identify risk-related situations of high potential concern, which 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 web site at
https://www.epa. gov/rsei. 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 RSEI Chronic Human Health Toxicity Weightings Differ from
EPCRA Section 313 (TRI) Statutory Criteria

As described above, the RSEI model uses TRI chemical reporting data. However, it is important
that the public not confuse the use of the model as a screening-level tool for investigating relative
risk-based impacts related to the releases and transfers of TRI chemicals, with the very different
and separate regulatory activity of listing/deli sting chemicals on the TRI chemical list using
statutory criteria.

The goal of the RSEI 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 TRI
chemicals on the general, non-worker population. The model differentiates the relative toxicity
of listed chemicals and ranks them in a consistent and transparent manner. The ranking of each
chemical reflects its toxicity only relative to other chemicals that are included in the model.

12 RSEI Queries and other data products are available at https://www.epa.gov/rsei/waYS-get-rsei-results.

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Toxicity is not compared to some benchmark or absolute value as is required when adding or
removing a chemical from the TRI chemical list.

In contrast, the EPCRA statutory criteria used for listing and delisting chemicals consider both
acute and chronic human toxicity, as well as environmental toxicity, and consider multiple
effects and the severity of those effects. The criteria also address the "absolute" chronic toxicity
of chemicals on the TRI chemical list relative to a benchmark value.

Because of these differences, the toxicity weightings used in the model cannot be used as a
scoring system for evaluating listing/delisting decisions. The RSEI model does not attempt to
reflect the statutory criteria for these TRI chemicals and chemical categories.

ES-3. Important Caveats Regarding the RSEI Model

The RSEI model is a screening tool that provides a relative risk-related perspective in assessing
the environmental impacts of certain waste management activities of TRI chemicals. Risk-related
results are available for certain environmental exposure pathways (i.e., air and water), and
pounds- and hazard-based results are available for other waste management activities. RSEI
scores combine estimates of chemical toxicity, exposure level, and the exposed population to
provide relative risk-related comparisons, but do not provide a detailed or quantitative
assessment of risk. These resulting scores 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 are known to contain some
reporting issues and errors. The TRI program does not change any reported data in the
official database until the reporting facility submits an official correction to their
reporting form. In certain instances, reporting errors by facilities result in RSEI scores 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 and scores are set to zero.

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 ECPRA
Section 313 statutory criteria used for listing and delisting chemicals on the TRI chemical
list. RSEI risk-related model results account for estimated exposure and may not correlate
with listing/delisting decisions.

• The RSEI model only addresses chronic human toxicity (cancer and non-cancer effects,
such as developmental toxicity, reproductive toxicity, neurotoxicity, etc.) associated with

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long-term exposure and does not address concerns for either acute human toxicity or
environmental toxicity.

•	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 non-cancer effects incorporate uncertainty factors which
are reflected in the 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
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).13

•	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 chronic
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
2014 National Emissions Inventory (NEI) are used to estimate the fraction of each type.14
As trivalent chromium has a very low toxicity, only the hexavalent chromium fraction is
modeled, using a toxicity weight specifically for 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
non-cancer 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). Users need to consider
these assumptions, and whether the gathering of additional data is warranted, when
examining model results for metals and metal compounds.

13	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/national-air-toxics-assessment/2005-national-air-toxics-
assessment. RSEI assumes that PAC emissions reported to TRI are most like NATA's "7-PAH" category.

14	A default of 34% hexavalent, 66% trivalent is used where NAICS-based data are unavailable. The NEI is
available at https://www.epa.gov/air-emissions-inventories/2014-national-emissions-inventorv-nei-data.

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Exposure Component. The following caveats should be considered regarding the exposure
component of the model:

• Like other exposure models, RSEI estimates exposure levels. It does not yield actual
exposures. The RSEI model provides estimated air concentrations in each grid cell and
surface water concentrations.

• 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 are used when facility-specific data are unavailable. For large
facilities 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 exposures are
generated as modeled media.

• The model does not account for population activity scenarios or patterns.

• The model does not account for indirect exposure such as air deposition of pollutants to
other media, or absorption of pollutants 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 2019.

• 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 could increase or decrease even without changes in its 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 practices.

ES-4. New Features in Version 2.3.9

• Includes TRI data and information from reporting years 1988 to 2019.

• Toxicity weights have been updated with the most recent toxicity data.

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1. Introduction

EPA's Risk-Screening Environmental Indicators (RSEI) is a screening-level tool that assesses
the potential impact of certain waste management activities of TRI chemicals (e.g., from releases
to the environment) from pounds-based, hazard-based, and risk-related perspectives. RSEI can
be used to quickly and easily screen large amounts of chemicals and chemical emissions data
from the TRI database, saving time and resources. RSEI is particularly useful for examining
trends that compare potential relative risks from year to year, or for ranking and prioritizing
chemicals, industry sectors, or geographic regions for strategic planning. 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 human health impacts over time.

Using estimates of pounds of chemical releases to investigate potential health and environmental
impacts is limited by the assumptions that all chemicals are equally toxic and that all people are
equally exposed. Formal risk assessments are more accurate, but are complicated and time
consuming to prepare, requiring detailed data that are not always available, and the results are
often limited in scope and geographic area. The RSEI approach augments estimates of chemical
pounds released with toxicity and exposure considerations, but does not address all of the
potential factors that would have to be included in a full risk assessment.

RSEI considers the following information: the amount of chemical released, the toxicity of the
chemical, its fate and transport through the environment, the route and extent of human
exposure, and the number of people affected. This information is used to create numerical values
that can be added and compared in limitless ways to assess the relative risks of chemicals,
facilities, industries, regions, and many other factors. The values generated are for comparative
purposes and only meaningful when compared to other values produced by RSEI. It should be
emphasized that the results are not a detailed or quantitative risk assessment, however, RSEI
results do offer a screening-level, risk-related perspective for relative comparisons of certain
waste management activities of TRI chemicals.

RSEI can help users can investigate the following types of questions: 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 release pathway for a particular chemical poses
the greatest risk-related impacts? Users can view pounds-based, hazard-based, and other results,
to investigate the relative influence of toxicity and population on the risk-related results, which
also incorporate exposure modeling.

The RSEI approach is very flexible and can be implemented in many ways. The use of the 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 quantities, and release
and transfer locations are known or can be estimated.

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1.1 Background

In 1989, the EPA outlined goals for establishing strategic planning processes at the Agency
(EPA, 1990c). 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 contributions of particular
chemicals, industries, and geographic regions through the indicators would allow the Agency
(and other users and stakeholders) to establish priorities for improving human health and the
environment.

To efficiently track changes in human health and environmental impacts over time, the Agency
should take advantage of existing data sources that reflect multi-media trends in environmental
contaminant releases. The Toxic Chemical Release Inventory (i.e., Toxics Release Inventory
(TRI)) is one of the Agency's most relevant source of continuous data for developing indicators
of change in environmental impacts over time. Reporting to the TRI is required by Section 313
of the Emergency Planning and Community Right-to-Know Act (EPCRA, or Title III of the
Superfund Amendments and Reauthorization Act of 1986), Public Law 99 499. Reporting is
required to provide information to the public on releases and other waste management of EPCRA
Section 313 chemicals in their communities and to provide EPA with release and other waste
management information to assist the Agency in determining the need for future regulations.
Subject facilities must report the quantities of routine and accidental releases, and releases
resulting from catastrophic or other one-time events of EPCRA Section 313 chemicals, as well as
the maximum amount of the EPCRA Section 313 chemical on-site during the calendar year and
the amount contained in wastes managed on-site or transferred off-site.

In response to the need for environmental indicators, and to take advantage of the rich data
source offered by the TRI, the Office of Toxic Substances (OTS), known currently as the Office
of Pollution Prevention and Toxics (OPPT), convened a workgroup to explore the development
of an indicator or indicators based on the TRI that could track changes in human health and
environmental impacts. Specifically, the approach would integrate hazard, exposure, and
population considerations into the risk-related evaluation of environmental releases of toxic
chemicals. The RSEI model was subsequently developed in response to this initiative.

When evaluating impacts of chemicals, it is important to not only consider the quantities of a
chemical released to the environment, but also the toxicity of the chemical, its exposure
potential, and the size of the receptor population. RSEI integrates these factors and provides a
relative risk-based perspective of certain chemical releases and transfers. 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.

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The current version of the RSEI model tracks changes in chronic human health impacts.
Ultimately, the model may be expanded to track acute human health and acute and chronic
ecological impacts.

This document explains how the RSEI model is constructed, and describes the conceptual
method, data sources, and the computational approach. The aim is to explain the model to a
variety of agencies, stakeholders, and users that may wish to use or adopt the model or the RSEI
methodology in general, to suit their own needs. In addition, this document describes the
advantages of the RSEI approach in terms of flexibility, power, and usefulness as an analytical
basis for setting priorities for further risk analyses, pollution prevention, regulatory initiatives,
enforcement targeting, and chemical testing requirements.

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1.2 RSEI Data Products

Users can access RSEI model results in a variety of ways. RSEI results are included in EPA data
tools such as Envirofacts15 and the TRI National Analysis. RSEI results are also currently
distributed in the EasyRSEI dashboard, accessible on the Qlik Sense platform through an internet
browser16 or through https://www.epa.gov/rsei. The EasyRSEI dashboard allows users to view
and query all RSEI results for TRI reporting years 2007-2019 for modeled media. Pounds- and
hazard-based results for non-modeled media, including waste management activities reported in
Section 8 of the TRI Form R, are also available. A separate Qlik Sense dashboard is available for
users who are interested in the full TRI time series (1988-2019), and a RSEI Queries database for
users comfortable in Microsoft Access is also available for download.17

RSEI also produces geographically disaggregated data, called the Geographic Microdata. These
are very large datasets that present results for the air exposure pathway at the 810m x 810m grid
cell level. The RSEI Geographic Microdata results include score, chemical concentration, and
toxicity-weighted concentration for each air release for each grid cell. There is also an
aggregated version of the Microdata that sums the score, chemical concentration, and toxicity-
weighted concentration over all of the air releases for each cell.

Information regarding the RSEI project is available on the RSEI web site, at
https://www.epa. gov/rsei.

1.3 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 for calculating RSEI results, and Chapter 7 describes issues pertinent to
the current implementation of the RSEI method.

There are also six Technical Appendices that accompany this methodology document and
provide additional information on the data used in the model. The Appendices are as follows:

Technical Appendix A - Toxicity Weights for TRI Chemicals and Chemical Categories
Technical Appendix B - Physicochemical Properties for TRI Chemicals and Chemical

Category

Weight-of-Evidence

Sufficient evidence from epidemiological studies to support a causal relationship
between exposure to the agent and cancer.

Limited evidence from epidemiological studies and sufficient animal data.

Sufficient evidence from animal studies but inadequate or no evidence or no data from
epidemiological studies.

Limited evidence of carcinogenicity in animals and an absence of evidence or data in
humans.

Inadequate human and animal evidence for carcinogenicity or no data.

No evidence for carcinogenicity in at least two adequate animal tests in different
species or in both adequate epidemiological and animal studies, coupled with no
evidence or data in epidemiological studies.

Source: 51 FR 33996

24 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 non-cancer effects, WOE is considered qualitatively in the hazard identification step of
determining an RfD or an RfC. The WOE evaluation for non-cancer effects is different from the
WOE evaluation for carcinogenic effects. The WOE judgment for non-cancer 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 non-cancer 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 adverse 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 represents the upper-bound estimate of
the slope of the dose-response curve in the low-dose region for carcinogens, and is a measure of
cancer potency. The units of the slope factor are usually expressed as (mg/kg-day)"1. The IUR is
the upper-bound excess lifetime cancer risk estimated to result from continuous exposure to a
chemical at a concentration of 1 [j,g/m3 in air (RSEI model toxicity weights are based on this
value when expressed as risk per mg/m3). 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 risk25 (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.

„ OSF kg-day / mg

0TWC-W«kUay,mg (E^41)

25 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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For non-cancer 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
[non-cancer] 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-
Ob served-Adverse-Effect Level (NOAEL) or Lowest-Ob served-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 non-cancer risk varies as the ratio of the
estimated exposure dose or concentration to its respective RfD or RfC.

RSEFs oral non-cancer 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.

OTWnc = lmg/k^y (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,
milligram (mg) of chemical per cubic meter (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

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are used rather than oral toxicity values26 (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, non-cancer 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

Non-Cancer

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.

RSEI Hazard and RSEI Score use the higher cancer or non-cancer 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 non-cancer hazard and non-cancer score results only
use the RfC- or RfD-based toxicity weights.

26 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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weight (RfD or OSF as appropriate) for the portion of the POTW transfer that is released from
the POTW as effluent.27 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.

27 Chemical-specific POTW removal and within-POTW partitioning rates are used to determine the portion of each
transfer to a POTW that biodegrades, adsorbs to sludge, or volatilizes. The remainder is assumed to be released from
the POTW as effluent.

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Exhibit 4.4

Selection of Toxicity Weights for Each RSEI Result

RSEI Result

Air Releases

Water Releases

Transfers to POTWs

Fill in Toxicity Data Gaps?

Score

Higher of IUR
tox weight or RfC
tox weight.

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.

Cancer Score

IUR tox weight.

OSF tox weight.

For volatilized portion use
IUR tox weight. For
POTW effluent release
portion use OSF.

No. If no route-specific
cancer tox weight, then
cancer score is zero.

Non-Cancer
Score

RfC tox weight.

RfD tox weight.

For volatilized portion use
RfC tox weight. For POTW
effluent release portion use
RfD tox weight.

No. If no route-specific non-
cancer tox weight, then non-
cancer score is zero.

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.

Cancer Hazard

IUR tox weight.

OSF tox weight.

No. If no route-specific
cancer tox weight, then
cancer hazard is zero.

Non-Cancer
Hazard

RfC tox weight.

RfD tox weight.

No. If no route-specific non-
cancer tox weight, then non-
cancer hazard is zero.

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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
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 non-cancer toxicity weights
is assigned as the final toxicity weight for the chemical for the given route for the RSEI score
and RSEI hazard. For the other results, cancer and non-cancer 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 under-estimate
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 under-value 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.

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").

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, subject facilities do not need to disclose the specific
category member's identity in their TRI reporting forms.

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

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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 reported 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 2014 NEI are used to
estimate the speciation fraction of each type.28 As trivalent chromium has a very low toxicity,
only the hexavalent fraction is modeled in RSEI, using a toxicity weight specifically for 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.29

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

28	The NEI is available at https://www.epa.gov/air-emissions-inventories/2014-national-emissions-inventorv-nei-
data.

29	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/national-air-toxics-assessment/2005-national-air-toxics-
assessment.

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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 TCDD30. 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
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 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 non-cancer 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 non-cancer 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 work groups before inclusion in IRIS.

30 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-eauivalencv-factors-human-health-risk-assessments-
dioxin-and.

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NATA. EPA's National Air Toxics Assessment (NATA), 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).

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 Documents (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
non-cancer 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/mrls/index.asp 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 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
non-cancer 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 Base (HSDB), as well as various EPA and ATSDR summary
documents, provided succinct summaries of toxic effects and quantitative data, toxicological and
epidemiological studies, and, in some cases, regulatory status data. When the available data on

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chronic human toxicity were sufficient to derive values, a toxicity weighting summary was
developed summarizing the information used to develop each of these values. The summaries are
available in Technical Appendix A. 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.

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 dates are comparable, preference is given to IRIS, since IRIS reflects Agency-
wide expert scientific judgments. If EPA's 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,
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

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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 600 chemicals and chemical categories on the 2019 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 2019. The RSEI results are
recomputed for all years in the TRI database on an annual basis in order to incorporate revisions
to the reporting data.

Toxicity weights for individual chemicals and chemical categories are presented in Technical
Appendix A.

4.5 How RSEI Toxicity Weightings Differ from EPCRA Section 313
Criteria

As previously noted, the RSEI model uses data and information reported to the TRI program. All
TRI chemicals 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. The goal of the RSEI 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 TRI chemicals on the general, non-worker population. To achieve this
goal, the RSEI model differentiates the relative toxicity of listed chemicals and ranks them in a
consistent and transparent manner. The ranking of each chemical reflects its toxicity only relative
to other chemicals that are included in the model. Toxicity is not compared to some benchmark
or absolute value as is required when adding or removing a chemical from the TRI chemical list.
Furthermore, the RSEI model addresses only the single, most sensitive chronic human health
toxicity endpoint.

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:

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.

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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
li sting/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/deli sting decisions. RSEI also does not attempt to reflect the
statutory criteria for these chemicals.

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Chapter 5: Exposure and Population Modeling

5. Exposure and Population Modeling

To estimate the magnitude of exposure potential from certain TRI waste management activities
(e.g., releases to the environment), a separate exposure evaluation is conducted for each
environmental exposure pathway. The following pathways are evaluated:

•	Air: stack (point) and fugitive (non-point) air emission pathways;

•	Surface Water: drinking water intake and fish ingestion pathways;

•	Publicly Owned Treatment Works (POTWs): fugitive air, groundwater (not currently
modeled), drinking water intake and fish ingestion pathways;

•	Land: groundwater pathway (not currently modeled), volatilization to air included in
fugitive air emission pathway for on-site releases; and

•	Off-site transfers: groundwater (not currently modeled), volatilization (not currently
modeled) and stack air (from incineration) pathways.

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 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 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 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 exposed population is calculated separately for each exposure pathway. The RSEI

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model assumes continuous exposure, and does not account for the activity patterns of the people
potentially exposed. However, population estimates do consider changing demographic patterns
(total population, as well as subpopulations by age and sex).

The methods used to model each type of waste management activity are specific to that type of
activity and depend on 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. It should be noted, however, that products of decay are not modeled.
Exclusion of these decay products from the RSEI model may underestimate or overestimate the
risk-related impacts of certain waste management activities, since the decay 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 data sets are created. From these general population data sets, the model
generates estimates of populations exposed through particular exposure pathways. The next
sections describe the modeling for each exposure pathway, including the estimation of surrogate
doses and exposed population for that pathway.

5.1 Geographic Basis of the RSEI Model

Underlying the RSEI method is the ability to locate facilities and people geographically, and to
attribute characteristics of the physical environment, such as meteorology, to areas surrounding
the facilities once they are located. To locate the facilities and the attribute data to those
facilities, the model describes the U.S. and its territories31 as an 810 meter by 810 meter grid
system. For each cell in the grid system, a location "address" in terms of (x,y) coordinates is
assigned based on latitude and longitude (lat/long).

5.1.1 The RSEI Model Grid Cell System

RSEI uses a standard Albers Equal-Area projection32 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) 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 (GIS) based system, and the bounding coordinates for each.

31 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.

32 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 GIS applications.

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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

UL Lat

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
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 ftp site at ftp://newftp.epa.gov/RSEI/Shapefiles/.

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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
reporting facilities and off-site facilities, see Technical Appendix D.

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 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 System (FRS), which collects
coordinates and related documentation on location from 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 waste transfers from TRI-reporting facilities. Note that
these off-site facilities do not report transfers received from other facilities directly to TRI;
instead their names, addresses, and the type and quantity of each waste management activity are
reported by the facilities that transfer the TRI chemicals in waste streams to them.33 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 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 database, and used in the

33 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 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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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 (1988-2019) 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 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 is 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 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 includes
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 model (the grid cell).

U.S. Census Data. The model uses decennial U.S. census data for 1990, 2000, and 2010 at the
block level.34 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
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-level data from the
three decennial censuses35 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:

34 Some U.S. census data and block shape files were provided by GeoLytics, Inc.

35 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.

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• 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 2000.36
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 Census Bureau provides
the geometry for each block in the Topologically Integrated Geographic Encoding and
Referencing (TIGER) geographic database, which was used to create shape files for the 1990,
2000, and 2010 census years. A corresponding set of shape files for grid cells was created, with
each grid cell defined by its four corner points, calculated from its (x,y) coordinates. The shape
files 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.37

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
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

36 For 2010, block-level shapefiles were available, but block-level population data were not released in time for
incorporation.

37 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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above.38 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 2019.

5.2 Pathway-specific Methods to Evaluate Chronic Human Exposure
Potential

The following sections describe the algorithms used for modeling exposure for each of the
following exposure pathways: (1) stack and fugitive air releases, (2) direct surface water
discharges, (3) transfers to POTWs, (4) off-site transfers, and (5) on-site land releases. An
overview of the exposure pathways and methods used to evaluate 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
resulting exposure. In some cases, the modeling is purposely simplified, given the lack of site-
specific data and/or 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 intakes, 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, etc.,
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

38 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.

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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.

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.39

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).40 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 options41, 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).

39 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.

40 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

41 See https://www.epa.gov/scram/air-aualitv-dispersion-modeling-preferred-and-recommended-models.

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5.3.1.3 Source Parameters

In the RSEI model, the U.S.42 is represented by a grid system composed of 810m by 810m square
grid cells. Facilities are assigned to a particular grid cell in this grid according to their latitude
and longitude coordinates (see Technical Appendix D 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 NEI43 when available. These include
stack height, exit-gas velocity, and stack diameter. Stack exit gas temperature is assumed
constant for all stacks (432° K). For facilities with multiple stacks, the median value for the stack
heights and diameters for that facility is used. For facilities without stack-specific values,
industry-specific 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. Stack parameters are further discussed in Section
5.3.6.1 and in Technical Appendix E.

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:44

453.6q (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

42 Including Puerto Rico, the U.S. Virgin Islands, American Samoa, Guam, and the Northern Mariana Islands.

43 NEI data are available here: https://www.epa.gov/air-emissions-inventories/2014-national-emissions-inventorv-
nei-data.

44 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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5.3.1.4 Meteorological Input Data

For a given chemical 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
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 calculates chemical air concentrations at hypothetical "receptors" located
within a circle with a radius of 49 km surrounding each facility. Any grid cells with centers
within the 49 km circle are included. The model calculates ground-level concentrations for
receptors at 5 kilometer increments for distances from 5 to 49 km away from the modeled
facility. The concentration assigned to a grid cell containing a receptor is determined at the point
in that grid cell which is nearest to the facility (see Exhibit 5.2). For grid cells between the
receptor points where calculations are made, concentrations are interpolated using a spatial
weighting technique similar to inverse distance-weighted averaging.

Exhibit 5.2

Assigned concentration at point nearest to facility.

Moeelea Concentration Used
for Cell #2

Cell #i

if Stack Lccalion (Modeled)

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To estimate the concentration for the 810m by 810m center grid cell containing the facility, the
RSEI model calculates the interpolated concentration based on calculated concentrations at 441
receptor points within a kilometer of the grid cell center. Analyses performed during the
development of RSEI Version 2.0 (which used the ISC model45) indicated that using the
concentration in a surrounding grid cell as an estimate for the center grid cell may either
significantly over or under-represent chemical concentrations there (See Part B of Analyses
Performedfor the Risk-Screening Environmental Indicators).

The RSEI model estimates concentrations up to 49 km from the facility. To determine the
optimal distance, 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 to 50 km46 was necessary to capture potential
concentrations of concern under certain atmospheric conditions. This 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. Details of
these analyses can be found in Part B of Analyses Performedfor the Risk-Screening
Environmental Indicators.47

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.

45 Version 3 of the long-term ISC model (ISCLT3) was used to calculate chemical concentrations in air until Version
2.2.0, the first version in which AERMOD was used.

46 In the final RSEI modeling, 49 km was used instead of 50km due to modeling constraints.

47 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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Fugitive emissions are converted from pounds per year to grams per square meter per second
(g/m2s) according to the following equation:

453.6q

Qa =	——7	(Eq-

31,536,000* 102

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 10 m x 10 m.

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:

DOSEair=Ca,r*Ia'r *—	(Eq. 5.5)

BW 1000

where:

DOSEair	=	surrogate dose of chemical contaminant from air (mg/kg-day)

Cair	=	air concentration in grid cell (|ig/m3)

lair	=	inhalation rate (m3/day)

BW	=	human body weight (kg)

1000	=	constant to convert ([j,g) to (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

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multiplied by the number of people potentially exposed in each population in the grid cell and by
the chemical toxicity weight to obtain the score for the grid cell. Then the scores for all relevant
grid cells are summed. The result is the RSEI score for an air release. To calculate the RSEI
score for all air releases, the same steps are followed for each air release, and the results are
summed.

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Exhibit 5.3

Calculating the RSEI Score for Air Releases

Air Release (lbs/year)

I

EPA/AMS Regulatory
Model (AERMOD)

I

Chemical concentration
in grid cell (x,y)

Population-specific
exposure factors

1

Surrogate dose (mg/kg-
day)

I

Population data and
chemical toxicity weights

	I	

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 Releases: Data

The air exposure pathway use 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
in Exhibit 5.4.

Exhibit 5.4
Air Modeling Parameters

Parameter

Value

Source/Comment

Chemical emission
rate

Site-specific (lbs/yr)

TRI

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 (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 (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 (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 four most
recent NEI databases (data years 2014, 2011, 2008, and 2005)48. 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 2012, data from the 2014 NEI is used; if a facility last reported to the TRI in reporting year
2010, then data from the 2011 NEI is used. For any facility with stack parameter data in NEI, the
median parameter of all stacks that emit TRI chemicals at the facility is used. For the TRI
facilities that have no stack parameter data in NEI, the median parameter values 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 of all stack parameters 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 948 TRI facilities reporting in any year and classified in NAICS code 2211-
Electric Power Generation in reporting year 2019, 43 percent match a corresponding facility
listed in one of the EPRI databases; approximately 57 percent of TRI electric utility facilities do
not. For the 57 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.49 See Technical Appendix E for details on the derivation of
stack data.

5.3.6.2 Meteorology50

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

48 Currently, the RSEI model can only assign one set of stack parameters to each facility. If a facility has reported
stack releases throughout the period of NEI data (2005-2014), the most recent stack parameters (2014 NEI if
available) are used.

49 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.

50 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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and the full twice-daily upper air soundings (i.e., meteorological variables reported at all levels).
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 model uses chemical-specific air decay rates from SRC's Atmospheric
Oxidation Program (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.51 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

51 For a few chemicals, other sources were used. See Technical Appendix B for the source used for each chemical.

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molecules/cm3 is used to convert the second-order rate constant 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:

AOPWIN

Kair= * *L5><106*3600 (Eq. 5.6)

where:

Kair = air decay rate (hr"1)

AOPWIN = second-order rate constant from AOPWIN

1.5xl06 = hydroxyl radical concentration (molecules/cm3)

3600 = constant to convert molecules/seconds to molecules/hour

2 = constant to reflect assumed 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)52, 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 the eight RSEI
age-sex groups (ages 0-17, 18-44, 45-64, 65+).53 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:

52 The Exposure Factors Handbook can be found at http://cfbub.epa. gov/ncea/risk/recordisplav.cfm?deid=236252.

53 The RSEI model provides the ability to view risk 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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Y4iiR,*ni)

EF = -i		(Eq. 5.7)

N

where:

EF	= RSEI exposure factor,

IRi	= intake rate for EFH age group z,

rii	= number of years that EFH age group z overlaps with the RSEI age

group

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.

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 Surface Water Releases

People may be exposed to chemicals released into surface water in one of two ways: by drinking
tap water from a public water system whose water intake was located in the path of a chemical
release; or by eating contaminated fish caught in a water body in the path of a chemical release.
The following sections first describe the methods used to calculate the initial chemical
concentrations for both exposure pathways, and then the different methods used to calculate
surrogate dose and population for the drinking water pathway and the 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 Surface Water Releases: Methods

5.4.1.1	Locating the Facility Discharge Flowline

The first step in assessing surface water discharges is to locate the discharging facility on the
RSEI model grid using their lat/long, and the flowline(a linear, unbranched section of a water
body) 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. 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) 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 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 km downstream; (2) the release has been traveling downstream for a week; or
(3) the chemical concentration reaches 1 x 10"9 mg/L. Within the initial flowline, the mass
quantity of the 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 biodegradation, but may also include
photooxidation. The general form of the first-order decay equation is as follows:

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— ~~kwatert

x L,oe

(Eq. 5.8)

where:

¦•water

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),54 where
applicable. Seventy-nine TRI chemicals had existing MCLs in effect during one or more
reporting years for which TRI data are available;55 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:

54 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.

55 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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(Eq. 5.9)

where:

DOSEdw

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)

water, flowline

water

BW

5.4.1.4	Estimating Population Size for the Drinking Water Exposure Pathway

To estimate the size of the population exposed to surface water releases of TRI chemical 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 SDWIS56.
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 is 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 80-km 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 from facilities. These fish may be consumed by recreational and subsistence fishers
and their families.57 As in the drinking water exposure pathway, chemical concentrations are
calculated until one of three conditions occurs: (1) the release has traveled 300 km 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:

56	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.

57	Although store-bought fish may also contain chemicals originating from facilities, modeling this exposure
pathway is not currently possible.

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C fishfeach C water flowline BCF

(Eq. 5.10)

where:

Cfish, reach
Cwater, 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:

DOSEfc

C fishfeach I fish,pop

BW

(Eq. 5.11)

where:

DOSEfc	=	surrogate dose of chemical c from facility / (mg/kg-day)

Cfish, reach	=	average annual chemical concentration in fish tissue (mg/kg)

Ifsh, pop	=	fish ingestion rate for recreational or subsistence fishers (kg/day)

BW	=	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.58 The resulting ratio is
multiplied by the population in each grid cell in 2000 to obtain the number of individuals with
fishing licenses within that grid cell. To account for family members who also eat fish caught by
one member, 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:

58 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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FishPopcell = TotalPopcell * ^Acenses * FamSize (Eq. 5.12)

Pop

where:

FishPopcell
TotalPopcell
Licenses
Pop

FamSize

total fish-eating population in a grid cell in 2000
total resident population in a cell (see Section 5.1.3)
number of fishing licenses in the county or state
total population in the county or state in 1990
average family size

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:

RecP°Pceit = FishP°Pceit * °-95 (Eq- 5•13)

SubsistPopcell = FishPopcell * 0.05 (Eq. 5.14)

where:

RecPopceii = recreational fishers (and families) in a grid cell
SubsistPopcell = 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 80-km 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 80 km 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 80-km 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 15 km in length and Flowline B is 5 km in length

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(and the entire length of each flowline is completely within 80 km of the grid cell), then a total of
20 km 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 km, the RSEI model
therefore assumes that three-fourths of the fishing population in the cell catches fish from
Flowline A and one-fourth catches fish from Flowline B. Note that the model uses only the
portion of the flowline's length that is within 80 km of the grid cell.

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 Surface Water Releases

RSEI 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 estimated 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 over all flowlines affected by the release (up to 300 km 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 Surface Water Releases

Direct Surface Water
Release (Ibs/yr)

I

Water volume and velocity
estimates; decay equation

Bioconcentration
factor (BCF)

Chemical concentration
in fish in Flowline X
(mg/kg)

Standard exposure assumptions
(fish ingestion rate, body weight)

Surrogate dose from fish
consumption in Flowline
X (mg/kg-day)

Population data and
chemical toxicity weights

Standard exposure
assumptions (drinking water
ingestion rate, body weight)



Surrogate dose from

drinking water in
Flowline X (mg/kg-day)

Population data and
chemical toxicity weights

Sum over all Flowlines
and both exposure
pathways

-±_

RSEI Score for Direct
Water Releases

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5.4.3 Surface 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
Surface Water Modeling Parameters

Parameter

Value (Units)

Source/Comment

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 stream

(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 Flowlines

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.

RSEI has adopted the National Hydrography Dataset (NHD) system for indexing flowlines,
which is much more detailed than the Reach File 1 (RF1) system, which was used in RSEI
Version 2.2.0 and before. The NHD is a feature-based database that interconnects and uniquely
identifies the stream segments or flowlines that comprise the nation's surface water drainage

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system. The NHD provides a national framework for assigning flowline addresses to water-
related entities such as industrial 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 Geographic Information Systems (GIS). 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 NHDPlus59, which contains information on stream velocity and flow volume, which
are necessary for modeling chemical concentrations in streams in 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
downstream using flow and velocity data, qualifying flowlines must have at least one
downstream or upstream connecting flowline60, 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.

59 https://www.epa.gov/waterdata/nhdplus-national-hYdrographY-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-SYStems.com/nhdplus/index.php.

60 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.

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5.4.3.2 Drinking Water Intakes and Populations

Drinking water intake locations were obtained from the PSDB, a database of drinking water
system information developed and maintained by the USGS, based on information in EPA's
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.61 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 water bodies from which
systems draw their water. In addition, multiple quality-assurance checks have been performed on
the data, including the 1 at/longs.

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
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,62 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

61 https://www.epa.gov/waterdata/drinking-water-tools.

62 NHDPlus also contains estimates developed using the Vogel method, but this is method is considered to have a
narrow band of applicability.

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are used in the Jobson methods: drainage area, flowline slope, mean annual discharge, and
discharge at the time of the measurement.63

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 Syracuse Research Corporation's (SRC'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.

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
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.64 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 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 intake values for
males and females combined from EPA's analysis of National Health and Nutrition Examination
Survey (NHANES) data from 2005-2010.

Drinking water intake rates per body weight were calculated for each of the RSEI modeled
groups (male and female: ages 0-17, 18-44, 45-64, 65+)65 using the weighted average approach

63 For more information, see the NHDPlus User's Guide (US EPA/USGS 2012) at
https ://www. epa. gov/waterdata/learn-more

64 The BCF can underestimate the accumulation of chemicals that are highly persistent and hydrophobic as
compared to the bioaccumulation factor (B AF), 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.

65 The RSEI model provides the ability to view risk scores for the 0-9 year old age group, however, there is not a

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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.

Exhibit 5.9
Drinking Water Exposure Factors

Model Age Group

Exposure Factors
(Male)

Exposure Factors
(Female)

(L/kg-day)

0-17

0.0101

18-44

0.0099

45-64

0.0117

>65

0.0108

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.66 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.

separate exposure factor for this age group. Instead, the exposure factor for the 0-17 year old age group is used
66 Consumption of marine fish is not included in the ingestion rates, because marine areas are not modeled in RSEI.

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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 waste management.67 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.68 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.69

These chemical-specific default POTW distribution percentages provided by EPA are based on
experimental and estimated data collected by the Agency and used in the RSEI model (see
Technical Appendix B for more details). Table III does not contain POTW distribution
percentages for all TRI-listed chemicals and chemical categories. For chemicals and chemical

67	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.

68	See https://ofmpub.epa.gov/apex/guideme ext/f?p=guideme:aa: 16874845131167: :::aa: 19-633 for more details.

69	See Table III in https://ofmpub.epa.gov/apex/guideme ext/guideme ext/guideme/file/rv 2019 rfi.pdf#page=148

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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
and metal compounds, for which the default assumption is that 100% of the chemical or
chemical category is released to the environment (e.g., disposed of).

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
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 2019. 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, the quantity of a TRI-listed chemical removed by a POTW is divided into the
percentages removed by (1) sorbing to sludge, (2) volatilizing into the air or (3) being
biodegraded by microorganisms. The remaining portion (i.e., the portion not removed by the
POTW) is the percentage of the influent TRI chemical that passes through the POTW untreated
and is 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 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).

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).70 POTWs (as well as incinerators) were matched to EPA's Facility Registry

70 Geocoding services were provided by Thomas Computing Services, a commercial firm.

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System (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 for more 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 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. 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) 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 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 surface 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) being biodegraded by microorganisms. 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 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 surface water release evaluation methods described previously in Section 5.4. Chemical
quantities that biodegrade 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 emissions, as described earlier in Section 5.3.2 in the
fugitive air release 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.71 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.

71 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 49 km 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

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, 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 biodegraded by microorganisms. 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 Managment Research
Laboratory (NRMRL), Risk Reduction Engineering Laboratory (RREL). For any given
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

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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 Risk Assessment Division
(RAD) 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'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 Off-site Transfers 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 Version 2.1.3
(lat/long coordinates were assigned based on street address).72 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 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 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),
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

72 Geocoding services were provided by Thomas Computing Services, a commercial firm.

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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 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, 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 AERMOD-based air modeling algorithms described previously in Section 5.3.

5.6.2 Estimating Population for Off-Site Transfers to Incineration

Similar to on-site air releases, the population exposed to air releases from off-site transfers to
incineration is the population within 49 km around the off-site incinerator. See Section 5.3.4 for
more details.

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5.6.3 Off-site Transfers to Incineration: Data

5.6.3.1 Incinerator Destruction and Removal Efficiencies

For organics, the destruction and removal efficiency (DRE) is assumed to be 99 percent (see
Technical Appendix B). The exceptions to the 99 percent removal assumption are
Polychlorinated Biphenyls (PCBs) and dioxin and dioxin-like compounds, which are assumed to
have a DRE of 99.9999 percent, as required by 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 disposal73 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 the
fugitive 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
TRI program, as well as viewing these releases from a hazard-based perspective.

73 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
multi-functional 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)

Surrogate Dose x Toxicity Weight x 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, surrogate dose, and
population components are multiplied to obtain a risk-related score. The 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. The final score generated
is a unitless measure that is not independently meaningful, but is a risk-related estimate that can
be compared to other risk-related estimates calculated using the same methodology. If toxicity
data or other data required for modeling are zero, or if the exposure pathway is not currently
modeled, then the risk-related score generated is zero. RSEI risk-related scores are only
calculated for certain types of TRI chemical releases and transfers (modeled media).

• RSEI Score- Product of surrogate dose, population, and the higher toxicity weight for
each exposure route (see Exhibit ES.2 for details).

• Cancer Score- Product of surrogate dose, population, and the IUR or OSF toxicity
weight (see Exhibit ES.2 for details).

• Non-Cancer Score- Product of surrogate dose, population, and the RfC or RfD toxicity
weight (see Exhibit ES.2 for details).

Higher component toxicity weights are associated with higher relative risk-related values (and
lower toxicity weights are associated with lower relative risks-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 similar to the calculation of cancer risk with a slope
factor or unit risk value and dose or exposure level. For chemicals with non-cancer 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 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:

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Chapter 6: Calculating Results

Exposure

Toxicity

(i.e., surrogate

Weight *

RfD (mg/kg-

Toxicity

Surrogate dose

dose) /RfD

Surrogate

day)

Weight

(mg/kg-day)

Ratio

Dose

Scenario 1

0.1

1/0.1 = 10

5*1 = 5

Scenario 2

0.01

1/0.01 = 100

50*1 =50

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.

• 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
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).

• Non-Cancer 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 ("TRI Pounds") reflect only the number of pounds reported
to TRI for each waste management activity, and are available for all TRI-reported quantities.

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6.1	Combining RSEI Scores

Once all of the results are calculated, they can be combined in many different ways. All of the
results are additive, so a result for a specific set of variables is calculated by summing the scores
for all of the relevant waste management activity quantities.74

This method is very flexible, allowing for countless variation in the resulting outputs. For
example, results can be generated for various subsets of variables (e.g., chemical, facility,
exposure pathway) and compared to each other to assess the relative contribution of each subset
to the total potential impact. Or, results for the same subset of variables for different years can be
produced, to assess the general trend in pounds-based, hazard-based, or risk-related impacts over
time.

It must be reiterated that while changes in results over the years would imply that there have
been changes in hazard- or risk-related environmental impacts, the actual magnitude of any
specific change or the reason may not be obvious. Although the value itself may be useful in
identifying chemicals, facilities, or geographic locations with the highest potential for hazard or
risk, the score itself does not represent a quantitative estimate or provide an exact indication of
the magnitude of associated individual hazard or risk.

6.2	Accounting for Changes in TRI Reporting

When a change occurs in the number of or reporting requirements for chemicals and/or facilities
regulated by the TRI program, the numerical value of RSEI results will be altered if no
adjustments are made to the method of calculation to account for the changes respective to trend
analyses. However, such changes would not necessarily represent a large change in actual
environmental impact, but rather would reflect a broader understanding of the impacts that may
have always existed. To maintain comparability in the weights over time, the results must be
adjusted in some manner when such changes in TRI reporting occur.

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 chemical list will
occur as EPA responds to petitions or initiates its own regulatory action through the chemical
listing or delisting process. The largest revision to the list occurred in November 1994, when the
Agency added 245 chemicals and chemical categories to the existing TRI chemical list, effective
for the reporting year 1995. When deletions from the TRI chemical list occur, RSEI's chemical
database is modified to remove all results from previous reporting years. Also, the yearly TRI
data in the TRI database are subject to ongoing quality control review and correction by both
EPA and by TRI-reporting facilities. As a result, yearly comparisons could be flawed if such
revisions to reported data were not included in each previous year's results. Therefore, RSEI
results are recomputed for all years on an annual basis in order to incorporate chemical deletions
and modifications to the reported data.

74 Separate results can also be calculated for each exposure pathway component of an environmental release, such as
the drinking water exposure or fish ingestion components of a surface water release; however, in most user-facing
applications the RSEI model results are presented at the overall environmental release level.

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The deletion of chemicals for the TRI chemical list would presumably have a minor effect since
such chemicals would be deleted due to their low hazard. Delisted chemicals are removed from
the RSEI model. To account for changes in the representation of chemicals in the TRI database,
RSEI uses flag fields to denote chemicals that have been listed on the TRI since a given year
with no changes in reporting requirements. To allow for meaningful trend analyses, the RSEI
model maintains a list of "core chemicals" which have been reported on since 1987, and for
which their reporting requirements have not changed.

Facility-level changes can also affect year-to-year scores generated using the RSEI model.
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
reporting requirements. For instance, chemical activity threshold requirements for facilities were
decreased over the first few years of TRI reporting, in addition to lowered thresholds for
Persistent Bioaccumulative Toxic chemicals (PBTs). The TRI program has also expanded the set
of industrial facilities required to report to include 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 quantities reported to the
TRI program and in turn result in alterations to the model's estimate of the associated relative
risk-based impacts.

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Chapter 7: Current Implementation of the RSEI Method

7. Current Implementation of the RSEI Method

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

RSEI model results are currently distributed in the EasyRSEI dashboard, accessible on the Qlik
Sense platform through an internet browser75 or through the RSEI website. The EasyRSEI
dashboard allows users to view and query all RSEI model results for TRI reporting years 2007-
2019 for modeled media. Pounds- and hazard-based results for non-modeled media, including
waste management activities reported in Section 8 of the TRI Form R, are also available. A
separate Qlik Sense dashboard is available for users who are interested in the full TRI time series
(1988-2019), and a RSEI Queries database for users comfortable in Microsoft Access is also
available for download.76

• 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?

Information regarding the RSEI project is available on the RSEI web site at
https://www.epa. gov/rsei. Complete documentation and contact information are all posted on the
site. Periodic updates and troubleshooting information are also available for users.

75 EasyRSEI is available at https://edap.epa.gov/public/extensions/EasYRSEI/EasYRSEI.html. The All Years version
is available at https://edap.epa.gov/public/extensions/EasYRSEI AllYears/EasvRSEI AllYears.html.

76 RSEI Queries and other data products are available at https://www.epa.gov/rsei/waYS-get-rsei-results.

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7.2 RSEI Geographic Microdata

RSEI users should note that, as implemented in EasyRSEI, the RSEI model employs a facility-
based approach. All RSEI-modeled impacts are attributed to the facility originally releasing or
transferring the TRI-listed chemical. For instance, an air release resulting from an off-site
incinerator is modeled as exposing the population around that off-site facility, but the results
(pounds, hazard, score, etc.) are attributed to the reporting facility that transferred the chemical to
the off-site incinerator. Similarly, while impacts may extend beyond geographic boundaries such
as zip code, county, or state, the RSEI results are attributed to the geographic entity in which the
facility is located. EPA employs the RSEI methodology to create other databases which are
geographically based. These Geographic Microdata datasets are very large and have to be
manipulated outside of the user-friendly interface provided by the EasyRSEI dashboard.

Various Microdata datasets are available for download, as well as a brief documentation to help
users understand the data and use them correctly. More information is available on the Ways to
Get RSEI Results page on the EPA's 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.

7.4 Conclusion

As an indication of improvements in environmental quality over time, the RSEI model provides
EPA and the public with a valuable tool to measure general trends based upon the relative risk-
related impacts of TRI chemicals. Although RSEI model results do not capture all waste
management activity quantities (e.g., all environmental releases of toxic chemicals), the model
results generally relate changes in environmental releases to relative changes in chronic human
health impacts from a large number of toxic chemicals of concern to the Agency. Importantly,
RSEI provides an ability to analyze the relative contribution of chemicals, facilities, and industry
sectors to adverse human health impacts, and RSEI results serve as an analytical basis for setting
priorities for pollution prevention, regulatory initiatives, enforcement targeting, and chemical
testing requirements.

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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.

Job son, 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-
do/environmental/scientific-datab ases .html).

Syracuse Research Corporation (SRC). 2002b. PhysProp Data Base. Accessed online at

http://esc.syrres.com/interkow/physdemo.htm, see http://www.srcinc. com/what-we-
do/environmental/scientific-datab ases .html.

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Chapter 8: References

Tudor, L., H. Jacobs, and P. Harrigan. 2000. Memorandum to EAD, SASD, and HECD. Subject:
Fish Consumption Rates to Use in Environmental Assessments/Benefits Analyses. May
10.

U.S. Census Bureau. 1996. TABLE 1. Projections of Households by Type: 1995 to 2010, Series
1, 2, and 3. Available at: https://www.census.gOv/prod/l/pop/p25-1129.pdfMav.

U.S. Department of the Interior, Fish and Wildlife Service (DOI, FWS). 1993. 1991 National
Survey of Fishing, Hunting, and Wildlife Associated Recreation. U.S. Department of
Commerce, Bureau of the Census. U.S. Government Printing Office, Washington D.C.

U.S. Geological Survey (USGS). 2012. Public Supply Database (PSDB). Written communication
via email and provision of data by Curtis Price. June.

U.S. Environmental Protection Agency (EPA). 1985. Exposure to Airborne Contaminants

Released from Land Disposal Facilities — A Proposed Methodology. Prepared for the
Office of Solid Waste by Environmental Science and Engineering, Inc. ESE Document
Number 85-527-0100-2140. August.

U.S. Environmental Protection Agency (EPA). 1986a. Guidelines for Carcinogen Risk
Assessment. 51 Federal Register 33992 (September 24, 1986).

U.S. Environmental Protection Agency (EPA). 1986b. Guidelines for Mutagenicity Risk
Assessment. 51 Federal Register 34006 (September 24, 1986).

U.S. Environmental Protection Agency (EPA). 1987. Graphical Exposure Modeling System
(GEMS) User's Guide. Prepared for the Office of Pesticides and Toxic Substances,
Exposure Evaluation Division by General Sciences Corporation under Contract No.
68023970. February.

U.S. Environmental Protection Agency (EPA). 1988a. IRIS Background Document #1.

Reference Dose (RfD): Description and Use in Health Risk Assessments. Integrated Risk
Information System (IRIS). Online. Maintained by Environmental Criteria and
Assessment Office, Cincinnati, OH.

U.S. Environmental Protection Agency (EPA). 1988b. Report to Congress: Solid Waste Disposal
in the United States. Volume 2. April.

U.S. Environmental Protection Agency (EPA). 1988c. National Survey of Solid Waste

(Municipal) Landfill Facilities. Office of Solid Waste EPA/530-SW88-034. September.

U.S. Environmental Protection Agency (EPA). 1988d. Industrial Subtitle D Risk Screening
Analysis Results. Prepared for the Office of Solid Waste by ICF, Inc. December 30.

U.S. Environmental Protection Agency (EPA). 1990a. Exposure Factors Handbook. Office of
Health and Environmental Assessment. EPA/600/8-89/043. March.

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U.S. Environmental Protection Agency (EPA). 1990b. Hazard Ranking System: Final Rule. 55
Federal Register 241. pp. 51532-51667.

U.S. Environmental Protection Agency (EPA) 1990c. Science Advisory Board, Relative Risk
Reduction Project. Reducing Risk. EPA SAB-EC-90-021. September.

U.S. Environmental Protection Agency (EPA). 1991a. Toxics in the Community. National and
Local Perspectives. The Office of Pesticides and Toxic Substances. EPA 560/4-91-014.
September.

U.S. Environmental Protection Agency (EPA). 1991b. Guidelines for Developmental Toxicity
Risk Assessment. 56 Federal Register 63798 (December 5, 1991).

U.S. Environmental Protection Agency (EPA). 1992a. Human Health Risk Assessment for the
Use and Disposal of Sewage Sludge: Benefits of Regulation. Prepared for the Office of
Water. January.

U.S. Environmental Protection Agency (EPA). 1992b. User's Guide for the Industrial Source
Complex (ISC2) Dispersion Models. Volume 2. Description of Model Algorithms.
Prepared for the Office of Air Quality, Planning and Standards, Technical Support
Division. March.

U.S. Environmental Protection Agency (EPA). 1993b. User's Guide to the Building Profile Input
Program. Office of the Quality Planning and Standards. October.

U.S. Environmental Protection Agency (EPA). 1999a. "Residual Risk Report to Congress".
EPA-453/R-99-001. United States Environmental Protection Agency, Office of Air
Quality Planning and Standards. March.

U.S. Environmental Protection Agency (EPA). 1997a. Addition of Facilities in Certain Industry
Sectors. 62 Federal Register 84, pp.23833-23892.

U.S. Environmental Protection Agency (EPA). 2002. Estimated Per Capita Fish Consumption in
the United States: Based on Data Collected by the United States Department of
Agriculture's 1994-1996 Continuing Survey of Food Intake by Individuals. Office of
Water, Office of Science and Technology. August.

U.S. Environmental Protection Agency (EPA). 2004a. AERMOD: Description of Model

Formulation. Office of Air Quality, Planning and Standards. September. EPA-454/R-03-
004. Accessed online at

https://www3.epa.gov/scram001/7thconf/aermod/aermod mfd.pdf.

U.S. Environmental Protection Agency (EPA). 2004b. User's Guide for the AMS/EPA
Regulatory Model - AERMOD. Office of Air Quality, Planning and Standards.

September. EPA-454/B-03-001. Accessed online at
https://www3.epa.gov/scram001/7thconf/aermod/aermodugb.pdf.

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U.S. Environmental Protection Agency (EPA). 2005. Guidelines for Carcinogen Risk

Assessment. Risk Assessment Forum. March. EPA/630/P-03/001B. Accessed online at
https://www3.epa.gov/airtoxics/cancer guidelines final 3-25-05.pdf.

U.S. Environmental Protection Agency (EPA). 2007. The HEM-3 User's Guide. HEM-3 Human
Exposure Model Version 1.1.0 (AERMOD version). Draft. January. Available at:
https://www.epa.gov/fera/human-exposure-model-hem-3-users-guides.

U.S. Environmental Protection Agency (EPA) and U.S Geological Survey (USGS). 2016.
NHDPlus Version 2: User Guide. December 18. Available at http://www.horizon-
svstems.com/NHDPlus/NHDPlusV2 documentation.php

U.S. Environmental Protection Agency (EPA). 2011. Exposure Factors Handbook: 2011
Edition. Office of Health and Environmental Assessment. Volume 1. EPA/600/R-
090/052F. September. Available at

https://cfpub.epa. gov/ncea/risk/recordisplav.cfm?deid=236252.

U.S. Environmental Protection Agency. (EPA) 2019. Exposure Factors Handbook Chapter 3
(Update): Ingestion of Water and Other Select Liquids. Office of Research and
Development, Washington, DC, EPA/600/R-18/259F, 2019.
https://www.epa.gov/expobox/exposure-factors-handbook-chapter-3

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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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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