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Draft

Residual Risk Assessment for the Off-Site Waste and Recovery 

Operations Source Category

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

May 2014
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Table of Contents

1 Introduction........................................................................................................................ 4

2 Methods.............................................................................................................................. 4

2.1 Emissions and source data........................................................................................... 4

2.2 Dispersion modeling for inhalation exposure assessment........................................... 5

2.3 Estimating chronic human inhalation exposure .......................................................... 7

2.4 Acute Risk Screening and Refined Assessments ........................................................ 8

2.5 Multipathway and environmental risk screening ...................................................... 10

2.6 Dose-Response Assessment ...................................................................................... 13

2.6.1 Sources of chronic dose-response information .................................................. 13

2.6.2 Sources of acute dose-response information...................................................... 21

2.7 Risk Characterization ................................................................................................ 26

2.7.1 General ............................................................................................................... 26

2.7.2 Mixtures ............................................................................................................. 28

2.7.3 Facility-wide Risks ............................................................................................ 28

2.7.4 MACT-Allowable Risk...................................................................................... 29

3 Risk Results for the OSWRO Source Category............................................................... 29

3.1 Source Category Description and Results................................................................. 29

3.2 Risk Characterization ................................................................................................ 34

4 General Discussion of Uncertainties and How They Have Been Addressed................... 38

4.1 Exposure Modeling Uncertainties............................................................................. 38

4.2 Uncertainties in the Dose-Response Relationships................................................... 39

5 References........................................................................................................................ 48

Index of Tables

Table 2.2-1 AERMOD version 12345 model options for RTR modeling................................ 6

Table 2.6-1 Dose-Response Values for Chronic Inhalation Exposure to Carcinogens .......... 16

Table 2.6-2 Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens .... 18

Table 2.6-3 Dose-Response Values for Acute Exposure........................................................ 24

Table 3.1-1 Summary of Emissions from the OSWRO Source Category Used in the Residual 

Risk Assessment and Availability of Dose-Response Values ................................................. 30

Table 3.2-1 Summary of Source Category Level Inhalation Risks for OSWRO ................... 36

Table 3.2-2 Summary of Environmental Risks Screen Results for OSWRO.......................... 37

Table 3.2-3 Source Category Contribution to Facility-Wide Cancer Risks............................ 38

Appendices

Appendix 1 Technical Support Document for HEM3 Modeling

Appendix 2 Meteorological Data for HEM3 Modeling

Appendix 3 Analysis of data on short-term emission rates relative to long-term emission 

rates

Appendix 4 Technical Support Document for TRIM-Based Multipathway Screening 

Scenario for RTR: Summary of Approach and Evaluation
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Appendix 5 Detailed Risk Modeling Results

Appendix 6 Acute Impacts Refined Analysis

Appendix 7 Dispersion Model Receptor Revisions and Additions for OSWRO

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model

AEGL Acute exposure guideline level

ASTDR US Agency for Toxic Substances and Disease Registry

CalEPA California Environmental Agency

CTE Central Tendency Estimate

ERPG Emergency Response Planning Guideline

HAP Hazardous Air Pollutant

HEM Human Exposure Model

HI Hazard index

HQ Hazard quotient

IRIS Integrated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of action

NAC National Advisory Committee

NAAQS National Ambient Air Quality Standard

NATA National Air Toxics Assessment

NEI National Emissions Inventory

NPRM Notice of Proposed Rulemaking

PB-HAP Persistent and Bioaccumulative - HAP

POM Polycyclic organic matter

REL Reference exposure level

RfC Reference concentration

RfD Reference dose

RME Reasonable Maximum Exposure

RTR Risk and Technology

TOSHI Target-organ-specific hazard index

URE Unit risk estimate
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1 Introduction

Section 112 of the Clean Air Act (CAA) establishes a two-stage regulatory process for 

addressing emissions of hazardous air pollutants (HAP) from stationary sources. In the first 

stage, section 112(d) requires the Environmental Protection Agency (EPA, or the Agency) to 

develop technology-based standards for categories of sources (e.g., petroleum refineries, pulp 

and paper mills, etc.) [1]. EPA has largely completed the initial Maximum Achievable 

Control Technology (MACT) standards as required under this provision. Under section 

112(d)(6), EPA must review each of these technology-based standards at least every eight 

years and revise a standard, as necessary, “taking into account developments in practices, 

processes and control technologies.” In the second stage, EPA is required under section 

112(f)(2) to assess the health and environmental risks that remain after implementation of the 

MACT standards. If additional risk reductions are necessary to protect public health with an 

ample margin of safety or to prevent an adverse environmental effect, EPA must develop 

standards to address these remaining risks. This second stage of the regulatory process is 

known as the residual risk stage. For each source category for which EPA issued MACT 

standards, the residual risk stage must be completed within eight years of promulgation of the 

initial technology-based standard.

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board 

(SAB) on the “Risk and Technology Review (RTR) Assessment Plan” and in June of 2007, 

we received a letter with the results of that consultation. Subsequent to the consultation, in 

July of 2009 a meeting was held with an SAB panel for a formal peer review of the “Risk and 

Technology Review (RTR) Assessment Methodologies” [2]. We received the final SAB 

report on this review in May of 2010 [3]. Where appropriate, we have responded to the key 

messages from this review in developing our current risk assessments and we will be 

continuing our efforts to improve our assessments by incorporating updates based on the SAB 

recommendations as they are developed and become available. Our responses to the key 

recommendations of the SAB are outlined in a memo entitled, “EPA’s Actions in Response to 

the Key Recommendations of the Science Advisory Board Review of Risk and Technology 

Review (RTR) Risk Assessment Methodologies” [4].

This document contains the methods and the results of baseline risk assessments (i.e., after the 

implementation of the MACT standard) performed for the off-site waste and recovery 

operations (OSWRO) source category. The methods discussion includes descriptions of the 

methods used to develop refined estimates of chronic inhalation exposures and human health 

risks for cancer and noncancer endpoints, as well as descriptions of the methods used to 

screen for acute health risks, chronic non-inhalation health risks, and adverse environmental 

effects. 

2 Methods

2.1 Emissions and source data

The starting point for this assessment involved generating a list of facilities potentially subject 

to the OSWRO MACT. The initial list, which included over 400 facilities across the United 
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States, was developed from databases maintained for the Resource Conservation and 

Recovery Act (RCRA) and the EPA’s Office of Enforcement and Compliance Assurance 

(OECA), as well as from databases used in development of the original OSWRO MACT

standards. The facilities were checked against compliance databases, including the Air 

Facility System (AFS), and title V operating permit information to ensure that the facilities 

were still operating, were subject to the OSWRO MACT and were major sources of HAP 

emissions. The resulting facility list, which consisted of 53 facilities, was used to create a 

subset of the 2005 NEI that included facility, process and emissions data. Data from nine 

corporate entities were also gathered through a CAA section 114 questionnaire. Where data 

for a facility was available from the questionnaire, the questionnaire data was used; NEI data 

were used for the remaining facilities, where OSWRO emissions could be identified. These 

data underwent a QA/QC procedure, and revisions were made to the dataset as necessary. In 

addition, facility and industry representatives were contacted to clarify details and resolve 

issues with the data for several sources. In the end, data for 38 facilities were included in the 

modeling dataset. Details on the development of the emissions and source data for this source

category are discussed in a memorandum entitled, “Development of the RTR Emissions 

Dataset for the Off-Site Waste and Recovery Operations Source Category” available in the 

docket for this rule making. Section 3 below provides a summary of the emissions.

2.2 Dispersion modeling for inhalation exposure assessment

Both long- and short-term inhalation exposure concentrations and associated health risk from 

each facility in the source category of interest were estimated using the Human Exposure 

Model in combination with the American Meteorological Society/EPA Regulatory Model

(AERMOD) dispersion modeling system (HEM3). The approach used in applying this 

modeling system is outlined below, and further details are provided in Appendix 1 of this 

document, Technical Support document for HEM3 Modeling. The HEM3 performs three 

main operations: atmospheric dispersion modeling, estimation of individual human exposures 

and health risks, and estimation of population risks. This section focuses on the dispersion 

modeling component. The exposure and risk characterization components are discussed in 

other subsections of Sections 2 and 3.

The dispersion model in the HEM3 system, AERMOD version 12345, is a state-of-thescience Gaussian plume dispersion model that is preferred by EPA for modeling point, area, 

and volume sources of continuous air emissions from facility applications [5]. Further details 

on AERMOD can be found in the AERMOD Users Guide [6]. The model is used to develop 

annual average ambient concentrations through the simulation of hour-by-hour dispersion 

from the emission sources into the surrounding atmosphere. Hourly emission rates used for 

this simulation are generated by evenly dividing the total annual emission rate from the 

inventory into the 8,760 hours of the year.

The first step in the application of the HEM3 modeling system is to predict ambient 

concentrations at locations of interest. The AERMOD model options employed are 

summarized in Table 2.2-1 and are discussed further below.
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Table 2.2-1 AERMOD version 12345 model options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point and Area

Receptor orientation Polar (13 rings and 16 radials)

Discrete (census block centroids) and user-supplied receptors

Terrain characterization Actual from USGS 1-degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option Included if source in urbanized area

Meteorology 1 year representative NWS from nearest site (over 800

stations)

In HEM3, meteorological data are ordinarily selected from a list of over 800 National 

Weather Service (NWS) surface observation stations across the continental United States, 

Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is selected as 

representative of the conditions at the subject facility. Ideally, when considering off-site 

meteorological data most site-specific dispersion modeling efforts will employ up to five 

years of data to capture variability in weather patterns from year to year. However, because 

we had an insufficient number of appropriately formatted model input files derived from 

available meteorological data, we modeled only a single year, typically 2011. While the 

selection of a single year may result in under-prediction of long-term ambient levels at some 

locations, likewise it may result in over-prediction at others. For each facility identified by its 

characteristic latitude and longitude coordinates, the closest meteorological station was used 

in the dispersion modeling. The average distance between a modeled facility and the 

applicable meteorological station was 23 miles (37 km). Appendix 2 of this document

(Meteorological Data Processing Using AERMET for HEM3) provides a complete listing of 

stations and assumptions along with further details used in processing the data through 

AERMET (the AERMOD meteorological data pre-processing program). The sensitivity of 

model results to the selection of the nearest weather station and the use of one year of 

meteorological data is discussed in “Risk and Technology Review (RTR) Risk Assessment 

Methodologies” [2].

The HEM3 system estimates ambient concentrations at the geographic centroids of census 

blocks (using the 2010 Census), and at other receptor locations that can be specified by the 

user. See Appendix 7 to this document (Dispersion Model Receptor Revisions and Additions 

for the Off-Site Waste and Recovery Operations Source Category) for a discussion of user 

receptors and centroid location changes specific to this source category. The model accounts 

for the effects of multiple facilities when estimating concentration impacts at each block 

centroid. Typically we combined only the impacts of facilities within the same source 

category, and assessed chronic exposure and risk only for census blocks with at least one 
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resident (i.e., locations where people may reasonably be assumed to reside rather than 

receptor points at the fenceline of a facility). Chronic ambient concentrations were calculated 

as the annual average of all estimated short-term (one-hour) concentrations at each block 

centroid. Possible future residential use of currently uninhabited areas was not considered. 

Census blocks, the finest resolution available in the census data, are typically comprised of 

approximately 40 people or about ten households. 

In contrast to the development of ambient concentrations for evaluating long-term exposures, 

which was performed only for occupied census blocks, worst-case short-term (one-hour) 

concentrations were estimated both at the census block centroids and at points nearer the 

facility that represent locations where people may be present for short periods, but generally 

no nearer than 100 meters from the center of the facility (note that for large facilities, this 

100-meter ring could still contain locations inside the facility property). Since short-term 

emission rates were needed to screen for the potential for hazard via acute exposures, and 

since the emissions data contain only annual emission totals, we generally apply the 

assumption to all source categories that the maximum one-hour emission rate from any source 

is ten times the average annual hourly emission rate for that source. More description of our 

short-term assessment can be found in Section 2.4 of this document – Acute Risk Screening 

and Refined Assessments. 

Census block elevations for HEM3 modeling were determined nationally from the US 

Geological Service 1/3 Arc Second National Elevation Dataset, which have a spatial 

resolution of about 10 meters. Elevations of polar grid points used in estimating short- and 

long-term ambient concentrations were assumed to be equal to the highest elevation of any 

census block falling within the polar grid sector corresponding to the grid point. If a sector 

does not contain any blocks, the model defaults the elevation to that of the nearest block. If 

an elevation is not provided for the emission source, the model uses the average elevation of 

all sectors within the innermost model ring. AERMOD adjusts the plume’s flow if nearby 

elevated hills are expected to influence the wind patterns. For details on how hill heights 

were estimated and used in the AERMOD modeling, see Appendix 1 of this document, 

Technical Support Document for HEM3 Modeling.

 

2.3 Estimating chronic human inhalation exposure

We used the estimated annual average ambient air concentration of each HAP at each census 

block centroid as a surrogate for the lifetime inhalation exposure concentration of all the 

people who reside in the census block. That is, the risk analysis did not consider either the 

short-term or long-term behavior (mobility) of the exposed populations and its potential 

influence on their exposure.

 

We did not address short-term human activity for two reasons. First, our experience with the 

NATA assessments (which modeled daily activity using EPA’s HAPEM model) suggests 

that, given our current understanding of microenvironment concentrations and daily activities, 

modeling short-term activity would, on average, reduce risk estimates about 25 percent for 

particulate HAP; it will also reduce risk estimates for gaseous HAP, but typically by much 

less. Second, basing exposure estimates on average ambient concentrations at census block 
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centroids may underestimate or overestimate actual exposure concentrations at some 

residences. Further reducing exposure estimates for the most highly exposed residents by 

modeling their short-term behavior could add a systematic low bias to these results.

We did not address long-term migration nor population growth or decrease over 70 years, 

instead basing the assessment on the assumption that each person’s predicted exposure is 

constant over the course of their lifetime which is assumed to be 70 years. In assessing cancer 

risk, we generally estimated three metrics; the maximum individual risk (MIR), which is 

defined as the risk associated with a lifetime of exposure at the highest concentration; the 

population risk distribution; and the cancer incidence. The assumption of not considering 

short or long-term population mobility does not bias the estimate of the theoretical MIR nor 

does it affect the estimate of cancer incidence since the total population number remains the 

same. It does, however, affect the shape of the distribution of individual risks across the 

affected population, shifting it toward higher estimated individual risks at the upper end and 

reducing the number of people estimated to be at lower risks, thereby increasing the estimated 

number of people at specific risk levels. 

2.4 Acute Risk Screening and Refined Assessments

In establishing a scientifically defensible approach for the assessment of potential health risks 

due to acute exposures to HAP, we followed the same general approach that has been used for 

developing chronic health risk assessments under the residual risk program. That is, we 

developed a tiered, iterative approach. This approach to risk assessment was endorsed by the 

National Academy of Sciences in its 1993 publication “Science and Judgment in Risk 

Assessment” and subsequently was adopted in the EPA’s “Residual Risk Report to Congress” 

in 1999. 

The assessment methodology is designed to eliminate from further consideration those 

facilities for which we have confidence that no acute adverse health effects of concern will 

occur. To do so, we use what is called a tiered, iterative approach to the assessment. This 

means that we begin with a screening assessment, which relies on readily available data and 

uses conservative assumptions that in combination approximate a worst-case exposure. The 

result of this screening process is that either the facility being assessed poses no potential 

acute health risks (i.e., it “screens out”), or that it requires further, more refined assessment. 

A more refined acute assessment could use industry- or site-specific data on the temporal 

pattern of emissions, the layout of emission points at the facility, the boundaries of the 

facility, and/or the local meteorology. In some cases, all of these site-specific data are used to 

refine the assessment; in others, lesser amounts of site-specific data can be used to determine 

that acute exposures are not a concern, and significant additional data collection is not

necessary. 

Acute health risk screening was performed as the first step. When we identify acute impacts 

which exceed their relevant benchmarks, we pursue refining our acute screening estimates to 

the extent possible. In some cases, this may include the use of a facility-specific emissions 

multiplier to estimate the peak hourly emission rates from the average rates (rather than the 

default factor of 10). In other cases, this may entail determining the actual physical layout 
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and boundaries of a facility to more accurately gauge where people might reasonably be 

exposed for an hour.

When screening for potentially significant acute exposures, we used an estimate of the highest 

hourly ambient concentration at any off-site location as the surrogate for the maximum 

potential acute exposure concentration for any individual. These hourly concentrations are 

based on hourly emissions, as described above. Since information is not usually available on 

short-term emission rates, we generally apply the assumption that the maximum one-hour 

emission rate from any source is ten times the average annual hourly emission rate for that 

source. (The average hourly emission rate is defined as the total emissions for a year divided

by the total number of operating hours per year.) This choice of a factor of ten for acute 

screening was originally based on engineering judgement.

To develop a more robust peak-to-mean emissions factor, and in response to one of the key 

messages from the SAB consultation on our RTR Assessment Plan, we performed an analysis 

using a short-term emissions dataset from a number of sources located in Texas (originally 

reported on by Allen et al. 2004) [7]. In that report, the Texas Environmental Research 

Consortium Project compared hourly and annual emissions data for volatile organic 

compounds for all facilities in a heavily-industrialized 4-county area (Harris, Galveston, 

Chambers, and Brazoria Counties) over an eleven-month time period in 2001. We obtained 

the dataset and performed our own analysis, focusing on sources which reported emitting high 

quantities of HAP over short periods of time (see Appendix 4 of this document, Analysis of 

data on short-term emission rates relative to long-term emission rates). Most peak emission 

events were less than twice the annual average, and the highest was a factor of 74 times the 

annual average, and the 99th percentile ratio of peak hourly emission rate to the annual hourly 

emission rate was 9. Based on these results, we generally chose the factor of ten for all initial 

screening. This factor is intended to cover all possible hourly peaks associated with routinelyvariable emissions. While there have been some documented emission excursions above this 

level, our analysis of the data from the Texas Environmental Research Consortium suggests 

that this factor should cover more than 99 percent of the short-term peak gaseous or volatile 

HAP emissions from typical industrial sources. We have no data relating specifically to peak 

short-term emissions of particulate HAP. In the absence of source category-specific data, we 

use this same default approach for particulate emissions as well.

When we identify acute impacts which exceed their relevant benchmarks, we pursue refining 

our acute screening estimates to the extent possible. For the off-site waste and recovery 

operations source category, we conducted a review of the layout of the polar receptors around 

the facilities to determine the maximum off-site acute impact for the facilities that did not 

screen out during the initial run. Appendix 5 to this document (Draft Detailed Modeling 

Results) contains the initial acute results for the source category, while Appendix 6 to this 

document (Acute Impacts Refined Analysis) contains the refined acute results. 

In summary, we used conservative assumptions for emission rates, meteorology, and exposure 

location, and refined data where available. We used the following worst-case assumptions in 

our screening approach:
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 Peak 1-hour emissions were assumed to equal 10 times the average 1-hour emission 

rates.

 For facilities with multiple emission points, peak 1-hour emissions were assumed to 

occur at all emission points at the same time.

 For facilities with multiple emission points, 1-hour concentrations at each receptor 

were assumed to be the sum of the maximum concentrations due to each emission 

point, regardless of whether those maximum concentrations occurred during the same 

hour. 

 Worst-case meteorology (from one year of local meteorology) was assumed to occur 

at the same time the peak emission rates occur. The recommended EPA local-scale 

dispersion model, AERMOD, is used for simulating atmospheric dispersion.

 A person was assumed to be located downwind at the point of maximum impact 

during this same worst-case 1-hour period, but no nearer to the source than 100 

meters.

 The maximum impact was compared to multiple short-term health benchmarks for the 

HAP being assessed to determine if a possible acute health risk might exist. These 

benchmarks are described in section 2.6 of this report.

2.5 Multipathway and environmental risk screening

The potential for significant human health risks due to exposures via routes other than 

inhalation (i.e., multipathway exposures) was screened by first determining whether any 

sources emitted any hazardous air pollutants known to be persistent and bioaccumulative in 

the environment (PB-HAP)1. The PB-HAP compounds or compound classes are identified 

for the screening from the EPA’s Air Toxics Risk Assessment Library [8]. Examples of PBHAP are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, 

heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury 

compounds, methoxychlor, polychlorinated biphenyls, polycyclic organic matter (POM), 

toxaphene, and trifluralin. 

Currently, the multipathway screen can be used to quantitatively estimate exposures and risks 

for the following five PB-HAP compounds: lead, cadmium compounds, chlorinated 

dibenzodioxins and furans, mercury compounds, and polycyclic organic matter (POM). 

These compounds are the focus of the screen because, based on current emissions and toxicity 

considerations, they are expected to pose the vast majority of the non-inhalation risks to 

humans from air emissions at sources subject to residual risk provisions of the CAA. 

Potential impacts on human health from non-inhalation exposures to cadmium compounds, 

chlorinated dibenzodioxins and furans, mercury compounds, and polycyclic organic matter 

are evaluated using our screening scenario developed for use with the EPA’s peer-reviewed 

Total Risk Integrated Methodology – Fate, Transport, and Ecological Exposure 

 

1 Although the two-letter chemical symbol for lead is Pb, in this assessment PB-HAP refers to the many air 

pollutants known to be persistent and bioaccumulative in the environment. In instances where the report is 

specifically referring to lead, it is spelled out (i.e., the two-letter chemical symbol for lead is not used in this 

document).
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(TRIM.FaTE2) model. With this approach, we first determine whether the facility-specific 

emission rates of each of the four PB-HAP listed above are large enough to create the 

potential for significant non-inhalation human health risks under reasonable worst-case 

conditions. To facilitate this step, we developed emission rate thresholds for each PB-HAP 

using a hypothetical upper-end screening exposure scenario developed for use in conjunction 

with TRIM.FaTE. The exposure scenario includes a generic farming/fishing exposure 

scenario that simulates a subsistence environment. We conducted a sensitivity analysis on the 

screening scenario to ensure that its key design parameters would represent the upper end of 

the range of possible values, such that it would represent a conservative but not impossible 

scenario. The PB-HAP emissions (of the four listed PB-HAP above) from each facility in the 

source category were compared to the emission rate threshold values for each of the four PBHAP identified to assess the potential for significant human health risks via non-inhalation 

pathways. For the purpose of developing emission rates for the multipathway screen, we 

derived emission levels for each of the four PB-HAP listed above at which the maximum 

human health risk would be 1-in-1 million for lifetime cancer risk or a hazard quotient of 1.0 

for noncancer impacts. We call this application of the TRIM.FaTE model the Tier I screen. 

See Appendix 4 of this document (Technical Support Document for TRIM-Based 

Multipathway Screening Scenario for RTR: Summary of Approach and Evaluation) for a 

complete discussion of the development and testing of the screening scenario, as well as for 

the values of facility-level emission rates developed for screening potentially significant 

multi-pathway impacts. 

In evaluating the potential multi-pathway risks from emissions of lead compounds, rather than 

developing a screening emission rate for them, we compared maximum estimated chronic

atmospheric concentrations with the current National Ambient Air Quality Standard 

(NAAQS) for lead. Values below the NAAQS were considered to have a low potential for 

multi-pathway risks.

Emissions of polycyclic organic matter (analyzed as benzo(a)pyrene), polychlorinated 

biphenyls, lindane (gamma-hch), chlordane, hexachlorobenzene, methoxychlor, toxaphene, 

heptachlor, and trifluralin were identified in the emissions inventories for the OSWRO source 

category. 

 

The EPA has developed a screening approach to examine the potential for adverse 

environmental effects as required under section 112(f)(2)(A) of the CAA. The environmental 

screen focuses on the following seven environmental HAP: 

 Five persistent bioaccumulative HAP (PB-HAP) – cadmium, dioxins/furans, 

polycyclic organic matter (POM), mercury (both inorganic mercury and methyl 

mercury) and lead.

 Two acid gases - hydrogen chloride (HCl), and hydrogen fluoride (HF). 

 

2 EPA’s Total Risk Integrated Methodology (General Information) http://epa.gov/ttn/fera/trim_gen.html
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HAP that persist and bioaccumulate are of particular environmental concern because they 

accumulate in the soil, sediment and water. The acid gases, HCl and HF, were included due to 

their well-documented potential to cause direct damage to terrestrial plants.

For the environmental risk screening analysis, EPA first determined whether any facilities in 

the source category emitted any of the seven environmental HAP. If one or more of the seven 

environmental HAP evaluated are emitted by at least one facility in the source category we 

proceed to the second step of the evaluation.

For cadmium, mercury, POM and dioxins/furans, the environmental screening analysis 

consists of two tiers. In the first tier, TRIM.FaTE modeling was conducted under worst-cast 

environmental conditionals to determine whether the facility-specific off-site emission rates 

of each of the emitted environmental HAP exceeded ecological benchmarks represented as 

emissions threshold values. If off-site emissions from a facility do not exceed the Tier I

thresholds the facility “passes” the screen, and therefore, is not evaluated further under the 

screening approach. If off-site emissions from a facility exceed the Tier I thresholds, we 

evaluate the facility further in Tier II.

In Tier II of the environmental screening analysis, the screening emission thresholds are 

adjusted to account for local meteorology and the actual location of lakes in the vicinity of 

facilities that did not pass the Tier I screen. If off-site emissions from a facility do not exceed 

the Tier II thresholds, the facility passes the screen, and is typically not evaluated further. If 

off-site emissions from a facility exceed the Tier II thresholds, the facility does not pass the 

screen and, therefore, may have the potential to cause adverse environmental effects. Such 

facilities are evaluated further to investigate factors such as the magnitude and characteristics 

of the area of exceedance. 

For acid gases, the environmental screening analysis evaluates the potential phytotoxicity and 

reduced productivity of plants due to chronic exposure to acid gases. The environmental risk 

screening methodology for acid gases is a single-tier screen that compares the average off-site 

ambient air concentration over the modeling domain to ecological benchmarks for each of the 

acid gases. For purposes of ecological risk screening, EPA identifies a potential for adverse 

environmental effects to plant communities from exposure to acid gases when the average 

concentration of the HAP around a facility exceeds the LOAEL ecological benchmark. In 

such cases, we further investigate factors such as the magnitude and characteristics of the area 

of exceedance (e.g., land use of exceedance area, size of exceedance area) to determine if 

there is an adverse environmental effect. 

For lead compounds, we currently do not have the ability to calculate media concentrations 

using the TRIM.FaTE model. However, air concentrations of lead are already calculated as 

part of the human health exposure and risk analysis using the HEM-3 AERMOD air 

dispersion model. To evaluate the potential for adverse environmental effects from lead, we 

compare the average modeled air emission concentrations of lead from each facility in the 

source category emissions to the level of the secondary National Ambient Air Quality 

Standard (NAAQS) for lead. The secondary lead NAAQS is a reasonable means of evaluating 

environmental risk because it is set to provide substantial protection against adverse welfare 
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effects which can include “effects on soils, water, crops, vegetation, man-made materials, 

animals, wildlife, weather, visibility and climate, damage to and deterioration of property, and 

hazards to transportation, as well as effects on economic values and on personal comfort and 

well-being.”3

2.6 Dose-Response Assessment

2.6.1 Sources of chronic dose-response information 

Dose-response assessment (carcinogenic and non-carcinogenic) for chronic exposure (either 

by inhalation or ingestion) for the HAP reported in the emissions inventory for the OSWRO

source category were based on the EPA Office of Air Quality Planning and Standards’ 

existing recommendations for HAP [9], also used for NATA [10]. This information has been 

obtained from various sources and prioritized according to (1) conceptual consistency with 

EPA risk assessment guidelines and (2) level of peer review received. The prioritization 

process was aimed at incorporating into our assessments the best available science with 

respect to dose-response information. The recommendations are based on the following 

sources, in order of priority: 

1) US Environmental Protection Agency (EPA). EPA has developed dose-response 

assessments for chronic exposure for many of the pollutants in this study. These 

assessments typically provide a qualitative statement regarding the strength of scientific 

data and specify a reference concentration (RfC, for inhalation) or reference dose (RfD, 

for ingestion) to protect against effects other than cancer and/or a unit risk estimate (URE, 

for inhalation) or slope factor (SF, for ingestion) to estimate the probability of developing 

cancer. The RfC is defined as an “estimate (with uncertainty spanning perhaps an order of 

magnitude) of a continuous inhalation exposure to the human population (including 

sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects 

during a lifetime.” The RfD is “an estimate (with uncertainty spanning perhaps an order 

of magnitude) of a daily oral exposure to the human population (including sensitive 

subgroups) that is likely to be without an appreciable risk of deleterious effects during a 

lifetime.” The URE is defined as “the upper-bound excess cancer risk estimated to result 

from continuous lifetime exposure to an agent at a concentration of 1 μg/m3in air.” The 

SF is “an upper bound, approximating a 95% confidence limit, on the increased cancer 

risk from a lifetime exposure to an agent. This estimate, [is] usually expressed in units of 

proportion (of a population) affected per mg/kg-day...” EPA disseminates dose-response 

assessment information in several forms, based on the level of review. The Integrated 

Risk Information System (IRIS) [11] is an EPA database that contains scientific health 

 

3 A secondary standard, as defined in Section 109(b)(2), must “specify a level of air quality the attainment and 

maintenance of which, in the judgment of the Administrator, based on [air quality] criteria, is requisite to protect 

the public welfare from any known or anticipated adverse effects associated with the presence of [the] pollutant 

in the ambient air.” Welfare effects as defined in section 302(h) (42 U.S.C. 7602(h)) include, but are not limited 

to, “effects on soils, water, crops, vegetation, man-made materials, animals, wildlife, weather, visibility, and 

climate, damage to and deterioration of property, and hazards to transportation, as well as effects on economic 

values and on personal comfort and well-being.”
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assessment information, including dose-response information. All IRIS assessments since 

1996 have also undergone independent external peer review. The current IRIS process 

includes review by EPA scientists, interagency reviewers from other federal agencies, and 

the public, and peer review by independent scientists external to EPA. New IRIS values 

are developed and old IRIS values are updated as new health effects data become 

available. Refer to the “IRIS Track” website for detailed information on status and 

scheduling of current individual IRIS assessments and updates 

(http://cfpub.epa.gov/ncea/iristrac/index.cfm). EPA’s science policy approach, under the 

current carcinogen guidelines, is to use linear low-dose extrapolation as a default option 

for carcinogens for which the mode of action (MOA) has not been identified. We expect 

future EPA dose-response assessments to identify nonlinear MOAs where appropriate, 

and we will use those analyses (once they are peer reviewed) in our risk assessments. At 

this time, however, there are no available carcinogen dose-response assessments for 

inhalation exposure that are based on a nonlinear MOA.

2) US Agency for Toxic Substances and Disease Registry (ATSDR). ATSDR, which is part 

of the US Department of Health and Human Services, develops and publishes Minimum 

Risk Levels (MRLs) [12] for inhalation and oral exposure to many toxic substances. As 

stated on the ATSDR web site: “Following discussions with scientists within the 

Department of Health and Human Services (HHS) and the EPA, ATSDR chose to adopt a 

practice similar to that of the EPA's Reference Dose (RfD) and Reference Concentration 

(RfC) for deriving substance specific health guidance levels for non neoplastic endpoints.” 

The MRL is defined as “an estimate of daily human exposure to a substance that is likely 

to be without an appreciable risk of adverse effects (other than cancer) over a specified 

duration of exposure.” ATSDR describes MRLs as substance-specific estimates to be 

used by health assessors to select environmental contaminants for further evaluation. 

Exposures above an MRL do not necessarily represent a threat, and MRLs are therefore 

not intended for use as predictors of adverse health effects or for setting cleanup levels.

3) California Environmental Protection Agency (CalEPA). The CalEPA Office of 

Environmental Health Hazard Assessment has developed dose-response assessments for 

many substances, based both on carcinogenicity and health effects other than cancer. The 

process for developing these assessments is similar to that used by EPA to develop IRIS 

values and incorporates significant external scientific peer review. As cited in the 

CalEPA Technical Support Document for developing their chronic assessments4: “The 

guidelines for developing chronic inhalation exposure levels incorporate many 

recommendations of the U.S. EPA [13] and NAS [14].” The non-cancer information 

includes available inhalation health risk guidance values expressed as chronic inhalation 

reference exposure levels (RELs) [15]. CalEPA defines the REL as “the concentration 

level at or below which no health effects are anticipated in the general human population.” 

CalEPA's quantitative dose-response information on carcinogenicity by inhalation 

exposure is expressed in terms of the URE [16], defined similarly to EPA's URE. 

 

4 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III - Technical Support Document

for the Determination of Non-cancer Chronic Reference Exposure Levels. Air Toxicology and Epidemiology 

Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. 

February 2000 (http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf)
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In developing chronic risk estimates, we adjusted dose-response values for some HAP based 

on professional judgment, as follows: 

1) In the case of HAP categories such as glycol ethers and cyanide compounds, the most 

conservative dose-response value of the chemical category is used as a surrogate for other 

compounds in the group for which dose-response values are not available. This is done in 

order to examine, under conservative assumptions, whether these HAP that lack doseresponse values may pose an unacceptable risk and require further examination, or screen 

out from further assessment. 

2) Where possible for emissions of unspecified mixtures of HAP categories such as metal 

compounds and POM, we apply category-specific chemical speciation profiles appropriate 

to the source category to develop a composite dose-response value for the category. 

3) In 2004, the EPA determined that the Chemical Industry Institute of Toxicology (CIIT)

cancer dose-response value for formaldehyde (5.5 x 10-9per μg/m3) was based on better 

science than the IRIS cancer dose-response value (1.3 x 10-5per μg/m3), and we switched 

from using the IRIS value to the CIIT value in risk assessments supporting regulatory 

actions. Subsequent research published by EPA suggested that the CIIT model was not 

appropriate and in 2010 EPA returned to using 1991 IRIS value. EPA has been working 

on revising the formaldehyde IRIS assessment and the National Academy of Sciences 

(NAS) completed its review of the EPA’s draft assessment in April of 2011.

5 EPA will 

follow the NAS Report recommendations and will present results obtained by 

implementing the biologically-based dose-response (BBDR) model for formaldehyde. 

EPA will compare these estimates with those currently presented in the External Review 

draft of the assessment and will discuss their strengths and weaknesses. As recommended 

by the NAS committee, appropriated sensitivity and uncertainty analyses will be an 

integral component of implementing the BBDR model. The draft IRIS assessment will be 

revised in response to the NAS peer review and public comments and the final assessment 

will be posted on the IRIS database. In the interim, we will present findings using the 

1991 IRIS value as a primary estimate and EPA may also consider other information as 

the science evolves. 

4) A substantial proportion of POM reported to EPA’s National Emission Inventory (NEI) is

not speciated into individual compounds. As a result, it is necessary to apply the same 

simplifying assumptions to assessments that are used in NATA [17]. The NATA 

approach partitions POM into eight different non-overlapping “groups” that are modeled 

as separate pollutants. Each POM group comprises POM species of similar carcinogenic 

potency, for which we can apply the same URE. 

The emissions inventory for the OSWRO source category includes emissions of HAP with 

available chronic quantitative inhalation dose-response values. Of these, 56 are classified as 

known, probable, or possible carcinogens, with quantitative cancer dose-response values 

 

5 http://www.nap.edu/catalog.php?record_id=13142
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available. These 56 HAP, their quantitative inhalation chronic cancer dose-response values, 

and the source of each value are listed in Table 2.6-1. Eighty-two HAP have quantitative 

inhalation chronic noncancer threshold values available. These HAP, their threshold values, 

and the source of the value are listed in Table 2.6-2.

Table 2.6-1 Dose-Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer)6 = cancer risk per μg/m3of average lifetime exposure. 

Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of 

Research & Development, EPA OAQPS = EPA Office of Air Quality Planning & 

Standards, CAL = California EPA Office of Environmental Health Hazard Assessment.

HEAST = EPA Health Effects Assessment Tables, Conv. Oral = Oral unit risk converted to 

inhalation.

Pollutant CAS 

Number7

URE11

(1/μg/m3)

Source

1,1,2,2-Tetrachloroethane 79345 0.000058 IRIS

1,1,2-Trichloroethane 79005 0.000016 IRIS

1,2-Dibromo-3-chloropropane 96128 0.002 CAL

1,2-Diphenylhydrazine 122667 0.00022 IRIS

1,3-Butadiene 106990 0.00003 IRIS

1,3-Dichloropropene 542756 0.000004 IRIS

1,3-Propane sultone 1120714 0.00069 CAL

1,4-Dioxane 123911 0.000005 IRIS8

2,4,6-Trichlorophenol 88062 0.0000031 IRIS

2,4-Dinitrotoluene 121142 0.000089 CAL

2,4-Toluene diamine 95807 0.0011 CAL

2,4-Toluene diisocyanate 584849 0.000011 CAL

2-Nitropropane 79469 0.0000056 EPA OAQPS

3,3'-Dichlorobenzidine 91941 0.00034 CAL

4,4'-methylene Bis(2-chloroaniline) 101144 0.00043 CAL

4,4'-Methylenedianiline 101779 0.00046 CAL

4-Dimethylaminoazobenzene (pDimethylaminoazobenzene 60117 0.0013 CAL

Lindane (gamma-HCH) 58899 0.00031 CAL

Acetaldehyde 75070 0.0000022 IRIS

Acetamide 60355 0.00002 CAL

Acrylamide 79061 0.00016 IRIS

Acrylonitrile 107131 0.000068 IRIS

Allyl chloride 107051 0.000006 CAL

Aniline 62533 0.0000016 CAL

 

6 The URE is the upper-bound excess cancer risk estimated to result from continuous lifetime exposure to an 

agent at a concentration of 1 μg/m3in air. URE’s are considered upper bound estimates meaning they represent 

a plausible upper limit to the true value. 

7 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have 

used a surrogate 3-digit identifier corresponding to the group’s position on the CAA list of HAP.

8

IRIS external review draft value, September 2011. 
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Table 2.6-1 Dose-Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer)6 = cancer risk per μg/m3of average lifetime exposure. 

Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of 

Research & Development, EPA OAQPS = EPA Office of Air Quality Planning & 

Standards, CAL = California EPA Office of Environmental Health Hazard Assessment.

HEAST = EPA Health Effects Assessment Tables, Conv. Oral = Oral unit risk converted to 

inhalation.

Pollutant CAS 

Number7

URE11

(1/μg/m3)

Source

Benzene9 71432 0.0000078 IRIS

Benzidine 92875 0.1072 IRIS

Benzyl chloride 100447 0.000049 CAL

Bis(2-ethylhexyl)phthalate 117817 0.0000024 CAL

Bromoform 75252 0.0000011 IRIS

Carbon tetrachloride 56235 0.000006 IRIS

Chlordane 57749 0.0001 IRIS

Chlorobenzilate 510156 0.000078 HEAST

Dichloroethyl ether 111444 0.00033 IRIS

Epichlorohydrin (1-Chloro-2,3-epoxypropane) 106898 0.0000012 IRIS

Ethyl benzene 100414 0.0000025 CAL

Ethyl carbamate 51796 0.000464 CAL

Ethylene dibromide 106934 0.0006 IRIS

Ethylene dichloride 107062 0.000026 IRIS

Ethylene oxide 75218 0.000088 CAL

Ethylene thiourea 96457 0.000013 CAL

Ethylidene dichloride (1,1-Dichloroethane) 75343 0.0000016 CAL

Formaldehyde10 50000 0.000013 IRIS

Heptachlor 76448 0.0013 IRIS

Hexachlorobenzene 118741 0.00046 IRIS

Hexachlorobutadiene 87683 0.000022 IRIS

Hydrazine 302012 0.0049 IRIS

Methyl tert-butyl ether 1634044 0.00000026 CAL

Methylene chloride 75092 0.00000013 IRIS

Naphthalene 91203 0.000034 CAL

Nitrobenzene 98953 0.00004 IRIS

Nitrosodimethylamine 62759 0.022 IRIS

N-nitrosomorpholine 59892 0.0019 CAL

o-Toluidine 95534 0.000051 CAL

P-dichlorobenzene (1,4- dichlorobenzene) 106467 0.000011 CAL

Pentachlorophenol 87865 0.0000051 CAL

Polychlorinated biphenyls (PCB) 1336363 0.0001 IRIS

 

9 The EPA IRIS assessment for benzene provides a range of plausible UREs. This assessment used the highest 

value in that range, 7.8E-06 per ug/m3. The low end of the range is 2.2E-06 per ug/m3.

10 The EPA has used the CIIT URE value, 5.5X10-9 per mg/m3

, to characterize formaldehyde cancer risk in 

some instances.
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Table 2.6-1 Dose-Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer)6 = cancer risk per μg/m3of average lifetime exposure. 

Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of 

Research & Development, EPA OAQPS = EPA Office of Air Quality Planning & 

Standards, CAL = California EPA Office of Environmental Health Hazard Assessment.

HEAST = EPA Health Effects Assessment Tables, Conv. Oral = Oral unit risk converted to 

inhalation.

Pollutant CAS 

Number7

URE11

(1/μg/m3)

Source

Polycyclic Organic Matter11 (POM)

 2-Acetylaminofluorene 53963 0.00208 CAL

Propylene oxide 75569 0.0000037 IRIS

Tetrachloroethene 127184 0.00000026 IRIS

Toxaphene 8001352 0.00032 IRIS

Trichloroethylene 79016 0.0000048 IRIS

Vinyl chloride 75014 0.0000088 IRIS

Table 2.6-2 Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order 

of magnitude) of a continuous inhalation exposure to the human population (including sensitive 

subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. 

Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of 

Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease 

Registry, HEAST = EPA Health Effects Assessment Tables, EPA OAQPS = EPA Office of Air 

Quality Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number12 RfC 

(mg/m3)

Source12

1,1,1-Trichloroethane (methyl chloroform) 71556 5 IRIS - M

1,1,2-Trichloroethane 79005 0.4 CAL

1,2,4-Trichlorobenzene 120821 0.2 HEAST

1,2-Dibromo-3-chloropropane 96128 0.0002 IRIS - M

1,2-Epoxybutane 106887 0.02 IRIS - M

1,3-Butadiene 106990 0.002 IRIS - M

1,3-Dichloropropene 542756 0.02 IRIS - H

 

11 POM without a chemical-specific URE are assigned a URE associated with a mixture of POM compounds 

having similar characteristics. Details of this method, also used in the 2002 National Air Toxics Assessment, are 

available at http://www.epa.gov/ttn/atw/nata2002/02pdfs/pom_approach.pdf.

12 The descriptors L (low), M (medium), and H (high) have been added for IRIS RfC values to indicate the 

overall level of confidence in the RfC value, as reported in IRIS.
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Table 2.6-2 Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order 

of magnitude) of a continuous inhalation exposure to the human population (including sensitive 

subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. 

Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of 

Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease 

Registry, HEAST = EPA Health Effects Assessment Tables, EPA OAQPS = EPA Office of Air 

Quality Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number12 RfC 

(mg/m3)

Source12

1,4-Dichlorobenzene (P-dichlorobenzene) 106467 0.8 IRIS - M

1,4-Dioxane 123911 0.03 IRIS - D13

2,4-Dinitrotoluene 121142 0.007 CAL

2,4-Toluene diisocyanate 584849 0.00007 IRIS - M

2-Nitropropane 79469 0.02 IRIS - L

4,4'-Methylenedianiline 101779 0.02 CAL

4,4'-Methylenediphenyl diisocyanate 101688 0.0006 IRIS - M

Acetaldehyde 75070 0.009 IRIS - L

Acetonitrile 75058 0.06 IRIS - M

Acrolein 107028 0.00002 IRIS - M

Acrylamide 79061 0.006 IRIS - M

Acrylic acid 79107 0.001 IRIS - M

Acrylonitrile 107131 0.002 IRIS - M

Allyl chloride 107051 0.001 IRIS - L

Aniline 62533 0.001 IRIS - L

Benzene 71432 0.03 IRIS - M

Benzidine 92875 0.01 CAL

Bis(2-ethylhexyl)phthalate 117817 0.01 CAL

Carbon disulfide 75150 0.7 IRIS - M

Carbon tetrachloride 56235 0.1 IRIS - M

Chlordane 57749 0.0007 IRIS - L

Chlorine 7782505 0.00015 ATSDR

Chlorobenzene 108907 1 CAL

Chloroform 67663 0.098 ATSDR

Cresols (mixed) 1319773 0.6 CAL

 m-Cresol 108394 0.6 CAL

 o-Cresol 95487 0.6 CAL

 p-Cresol 106445 0.6 CAL

Cumene 98828 0.4 IRIS - M

Dichlorvos 62737 0.0005 IRIS - M

Diethanolamine 111422 0.003 CAL

Dimethyl formamide 68122 0.03 IRIS - M

 

13 IRIS external review draft value, September 2011. 
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Table 2.6-2 Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order 

of magnitude) of a continuous inhalation exposure to the human population (including sensitive 

subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. 

Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of 

Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease 

Registry, HEAST = EPA Health Effects Assessment Tables, EPA OAQPS = EPA Office of Air 

Quality Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number12 RfC 

(mg/m3)

Source12

Epichlorohydrin (1-Chloro-2,3 

epoxypropane) 106898 0.001 IRIS - M

Ethyl benzene 100414 1 IRIS - L

Ethyl chloride 75003 10 IRIS - M

Ethylene dibromide 106934 0.009 IRIS - M

Ethylene dichloride 107062 2.4 ATSDR

Ethylene glycol 107211 0.4 CAL

Ethylene oxide 75218 0.03 CAL

Ethylene thiourea 96457 0.003 CAL

Ethylidene dichloride (1,1-Dichloroethane) 75343 0.5 HEAST

Formaldehyde 50000 0.0098 ATSDR

Glycol Ethers14

 Ethylene glycol ethyl ether 110805 0.2 IRIS - M

 Ethylene glycol methyl ether 109864 0.02 IRIS - M

 Glycol ethers 181 0.02 IRIS - M

Hexachlorobenzene 118741 0.003 CAL

Hexachlorobutadiene 87683 0.09 CAL

Hexachlorocyclopentadiene 77474 0.0002 IRIS – M/H

Hexachloroethane 67721 0.03 IRIS - L

Hexane 110543 0.7 IRIS - M

Hydrazine 302012 0.0002 CAL

Hydrochloric acid (hydrogen chloride) 7647010 0.02 IRIS - L

Hydrofluoric acid (hydrogen fluoride) 7664393 0.014 CAL

Isophorone 78591 2 CAL

Lindane (gamma-HCH) 58899 0.0003 CAL

Maleic anhydride 108316 0.0007 CAL

Methanol 67561 4 CAL

Methyl bromide 74839 0.005 IRIS - H

Methyl chloride 74873 0.09 IRIS - M

Methyl isobutyl ketone 108101 3 IRIS - L/M

Methyl methacrylate 80626 0.7 IRIS - M/H

Methyl tert-butyl ether 1634044 3 IRIS - M

Methylene chloride 75092 0.6 IRIS – M/H

 

14 The RfC value for ethylene glycol methyl ether was used as a surrogate for all glycol ethers without an RfC.
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Table 2.6-2 Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order 

of magnitude) of a continuous inhalation exposure to the human population (including sensitive 

subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. 

Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of 

Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease 

Registry, HEAST = EPA Health Effects Assessment Tables, EPA OAQPS = EPA Office of Air 

Quality Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number12 RfC 

(mg/m3)

Source12

Naphthalene 91203 0.003 IRIS - M

Nitrobenzene 98953 0.009 IRIS - M

Pentachlorophenol 87865 0.1 CAL

Phenol 108952 0.2 CAL

Phosphine 7803512 0.0003 IRIS - L

Phthalic anhydride 85449 0.02 CAL

Propionaldehyde 123386 0.008 IRIS – L/M

Propylene dichloride 78875 0.004 IRIS - M

Propylene oxide 75569 0.03 IRIS - M

Styrene 100425 1 IRIS - M

Styrene oxide 96093 0.006 CAL

Tetrachloroethene 127184 0.04 IRIS -M

Titanium tetrachloride 7550450 0.0001 ATSDR

Toluene 108883 5 IRIS - H

Trichloroethylene 79016 0.002 IRIS - H

Triethylamine 121448 0.007 IRIS - L

Vinyl acetate 108054 0.2 IRIS - H

Vinyl chloride 75014 0.1 IRIS - M

Vinylidene chloride 75354 0.2 IRIS – H/M

Xylenes (mixed) 1330207 0.1 IRIS - M

 m-Xylene16 108383 0.1 IRIS - M

 o-Xylene15 95476 0.1 IRIS - M

 p-Xylene16 106423 0.1 IRIS - M

2.6.2 Sources of acute dose-response information 

Hazard identification and dose-response assessment information for preliminary acute 

inhalation exposure assessments are based on the existing recommendations of OAQPS for 

HAP [18]. Depending on availability, the results from screening acute assessments are 

compared to both “no effects” reference levels for the general public, such as the California 

Reference Exposure Levels (RELs), as well as emergency response levels, such as Acute 

Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelines 

 

15 The RfC for mixed xylene was used as a surrogate.
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(ERPGs), with the recognition that the ultimate interpretation of any potential risks associated 

with an estimated exceedance of a particular reference level depends on the definition of that 

level and any limitations expressed therein. Comparisons among different available 

inhalation health effect reference values (both acute and chronic) for selected HAP can be 

found in an EPA document of graphical arrays [19]. 

California Acute Reference Exposure Levels (RELs). The California Environmental 

Protection Agency (CalEPA) has developed acute dose-response reference values for many 

substances, expressing the results as acute inhalation Reference Exposure Levels (RELs). 

The acute REL (http://www.oehha.ca.gov/air/pdf/acuterel.pdf) is defined by CalEPA as 

“the concentration level at or below which no adverse health effects are anticipated for a

specified exposure duration. [20]. RELs are based on the most sensitive, relevant, 

adverse health effect reported in the medical and toxicological literature. RELs are 

designed to protect the most sensitive individuals in the population by the inclusion of

margins of safety. Since margins of safety are incorporated to address data gaps and

uncertainties, exceeding the REL does not automatically indicate an adverse health 

impact.” Acute RELs are developed for 1-hour (and 8-hour) exposures. The values 

incorporate uncertainty factors similar to those used in deriving EPA’s Inhalation 

Reference Concentrations (RfCs) for chronic exposures (and, in fact, California also has 

developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs). AEGLs are developed by the National Advisory 

Committee (NAC) on Acute Exposure Guideline Levels (NAC/AEGL) for Hazardous 

Substances, and then reviewed and published by the National Research Council As described 

in the Committee’s “Standing Operating Procedures (SOP)”

(http://www.epa.gov/opptintr/aegl/pubs/sop.pdf), AEGLs “represent threshold exposure limits 

for the general public and are applicable to emergency exposures ranging from 10 min to 8 h.” 

Their intended application is “for conducting risk assessments to aid in the development of 

emergency preparedness and prevention plans, as well as real time emergency response 

actions, for accidental chemical releases at fixed facilities and from transport carriers.” The 

document states that “the primary purpose of the AEGL program and the NAC/AEGL 

Committee is to develop guideline levels for once-in-a-lifetime, short-term exposures to 

airborne concentrations of acutely toxic, high-priority chemicals.” In detailing the intended 

application of AEGL values, the document states that, “It is anticipated that the AEGL values 

will be used for regulatory and nonregulatory purposes by U.S. Federal and State agencies, 

and possibly the international community in conjunction with chemical emergency response, 

planning, and prevention programs. More specifically, the AEGL values will be used for 

conducting various risk assessments to aid in the development of emergency preparedness and 

prevention plans, as well as real-time emergency response actions, for accidental chemical 

releases at fixed facilities and from transport carriers.” 

The NAC/AEGL defines AEGL-1 and AEGL-2 as:

“AEGL-1 is the airborne concentration (expressed as ppm or mg/m3) of a substance above 

which it is predicted that the general population, including susceptible individuals, could 
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experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. 

However, the effects are not disabling and are transient and reversible upon cessation of 

exposure.”

“AEGL-2 is the airborne concentration (expressed as ppm or mg/m3) of a substance above 

which it is predicted that the general population, including susceptible individuals, could 

experience irreversible or other serious, long-lasting adverse health effects or an impaired 

ability to escape.”

“Airborne concentrations below AEGL-1 represent exposure levels that can produce mild 

and progressively increasing but transient and nondisabling odor, taste, and sensory 

irritation or certain asymptomatic, nonsensory effects. With increasing airborne 

concentrations above each AEGL, there is a progressive increase in the likelihood of 

occurrence and the severity of effects described for each corresponding AEGL. Although 

the AEGL values represent threshold levels for the general public, including susceptible 

subpopulations, such as infants, children, the elderly, persons with asthma, and those with 

other illnesses, it is recognized that individuals, subject to unique or idiosyncratic 

responses, could experience the effects described at concentrations below the 

corresponding AEGL.”

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene 

Association (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [21] 

for acute exposures at three different levels of severity. These guidelines represent 

concentrations for exposure of the general population (but not particularly sensitive persons) 

for up to 1 hour associated with effects expected to be mild or transient (ERPG-1), 

irreversible or serious (ERPG-2), and potentially life-threatening (ERPG-3). 

ERPG values (- http://www.aiha.org/getinvolved/AIHAGuidelineFoundation/EmergencyResponsePlanningGuidelines/Pages/default.a

spx ) are described in their supporting documentation as follows: “ERPGs are air 

concentration guidelines for single exposures to agents and are intended for use as tools to 

assess the adequacy of accident prevention and emergency response plans, including 

transportation emergency planning, community emergency response plans and incident 

prevention and mitigation.”

ERPG-1 and ERPG-2 values are defined by AIHA as follows:

“ERPG-1 is the maximum airborne concentration below which it is believed that nearly all 

individuals could be exposed for up to 1 hour without experiencing other than mild 

transient adverse health effects or without perceiving a clearly defined, objectionable 

odor.”

“ERPG-2 is the maximum airborne concentration below which it is believed that nearly all 

individuals could be exposed for up to 1 hour without experiencing or developing 

irreversible or other serious health effects or symptoms which could impair an individual's 

ability to take protective action.”
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The emissions inventory for the OSWRO source category includes emissions of 57 HAP with 

relevant and available quantitative acute dose-response threshold values. These HAP, their 

acute threshold values, and the source of the value are listed below in Table 2.6-3.

Table 2.6-3 Dose-Response Values for Acute Exposure

Pollutant

CAS 

Number

AEGL-1

(1-hr)

(mg/m3)

AEGL-2

(1-hr)

(mg/m3)

ERPG1

(mg/m3

)

ERPG-2

(mg/m3) REL 

1,1-Dimethylhydrazine 57147 7.4

1,2-Epoxybutane 106887 210 410

1,3-Butadiene 106990 1500 12000 22 440

1,4-Dioxane 123911 61 1200 3

2,4-Toluene diisocyanate 584849 0.14 0.59 0.071 1.1

Acetaldehyde 75070 81 490 18 360 0.47

Acetonitrile 75058 22 540

Acrolein 107028 0.069 0.23 0.11 0.34 0.0025

Acrylic acid 79107 4.4 140 3 150 6

Acrylonitrile 107131 10 130 22 77

Allyl chloride 107051 8.8 170 9.4 130

Aniline 62533 30 46

Benzene 71432 170 2600 160 480 1.3

Benzyl chloride 100447 5.2 52 0.24

Biphenyl 92524 61

Carbon disulfide 75150 40 500 3.1 160 6.2

Carbon tetrachloride 56235 280 1200 130 630 1.9

Chlorine 7782505 1.5 5.8 2.9 8.7 0.21

Chlorobenzene 108907 46 690

Chloroform 67663 310 240 0.15

Chloromethyl methyl ether 107302 1.6 3.3

Cumene 98828 250 1500

Dichlorvos 62737 0.99 5.1

Dimethyl formamide 68122 270 6 300

Dimethyl sulfate 77781 0.12 0.62

Epichlorohydrin (1-Chloro-2,3-

epoxypropane) 106898 22 91 19 76 1.3

Ethyl acrylate 140885 34 150 0.041 120

Ethyl benzene 100414 140 4800

Ethylene dibromide 106934 130 180

Ethylene dichloride 107062 200 810

Ethylene oxide 75218 81 90

Formaldehyde 50000 1.1 17 1.2 12 0.055
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Table 2.6-3 Dose-Response Values for Acute Exposure

Pollutant

CAS 

Number

AEGL-1

(1-hr)

(mg/m3)

AEGL-2

(1-hr)

(mg/m3)

ERPG1

(mg/m3

)

ERPG-2

(mg/m3) REL 

Glycol Ethers16

 Ethylene glycol ethyl ether 110805 0.37

 Ethylene glycol methyl ether 109864 0.093

 Glycol ethers 181 0.093

Hexachlorobutadiene 87683 11 32

Hexane 110543 12000

Hydrazine 302012 0.13 17 0.65 6.5

Maleic anhydride 108316 0.8 8

Methanol 67561 690 2700 260 1300 28

Methyl bromide 74839 820 190 3.9

Methyl chloride 74873 1900 830

Methyl hydrazine 60344 3.2

Methyl iodide 74884 150 290

Methyl methacrylate 80626 70 490

Methyl tert-butyl ether 1634044 180 2100

Methylene chloride 75092 690 1900 1000 2600 14

Phenol 108952 58 89 38 190 5.8

Phosphine 7803512 2.8 0.7

Propionaldehyde 123386 110 620

Propylene oxide 75569 170 690 120 590 3.1

Styrene 100425 85 550 210 1100 21

Tetrachloroethene 127184 240 1600 680 1400 20

Titanium tetrachloride 7550450 0.54 7.8 5 20

Toluene 108883 750 4500 190 1100 37

Trichloroethylene 79016 700 2400 540 2700

Triethylamine 121448 2.8

Vinyl acetate 108054 24 630 18 260

Vinyl chloride 75014 640 3100 1300 13000 180

Xylenes (mixed) 1330207 560 4000 22

 m-Xylene17 108383 22

 o-Xylene18 95476 22

 p-Xylene18 106423 22

 

16 The acute REL for ethylene glycol methyl ether was used as a surrogate for glycol ether compounds without 

an acute REL.

17 The REL for mixed xylenes was used as a surrogate.
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2.7 Risk Characterization

2.7.1 General

The final product of the risk assessment is the risk characterization, in which the information 

from the previous steps is integrated and an overall conclusion about risk is synthesized that is 

complete, informative, and useful for decision makers. In general, the nature of this risk 

characterization depends on the information available, the application of the risk information 

and the resources available. In all cases, major issues associated with determining the nature 

and extent of the risk are identified and discussed. Further, the EPA Administrator’s March 

1995 Policy for Risk Characterization [22] specifies that a risk characterization “be prepared 

in a manner that is clear, transparent, reasonable, and consistent with other risk 

characterizations of similar scope prepared across programs in the Agency.” These principles 

of transparency and consistency have been reinforced by the Agency’s Risk Characterization 

Handbook [23], in 2002 by the Agency’s information quality guidelines [24], and in the 

OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis18, and 

are incorporated in these assessments.

Estimates of health risk are presented in the context of uncertainties and limitations in the data 

and methodology. Through our tiered, iterative analytical approach, we have attempted to 

reduce both uncertainty and bias to the greatest degree possible in these assessments, within 

the limitations of available time and resources. We provide summaries of risk metrics 

(including maximum individual cancer risks and noncancer hazards, as well as cancer 

incidence estimates) along with a discussion of the major uncertainties associated with their 

derivation to provide decision makers with the fullest picture of the assessment and its 

limitations.

For each carcinogenic HAP included in the assessment that has a potency estimate available, 

individual and population cancer risks were calculated by multiplying the corresponding 

lifetime average exposure estimate by the appropriate URE. This calculated cancer risk is 

defined as the upper-bound probability of developing cancer over a 70-yr period (i.e., the 

assumed human lifespan) at that exposure. Because UREs for most HAP are upper-bound 

estimates, actual risks at a given exposure level may be lower than predicted, and could be 

zero.

For EPA’s list of carcinogenic HAP that act by a mutagenic mode-of-action [25], we applied 

EPA’s Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to 

Carcinogens [26]. This guidance has the effect of adjusting the URE by factors of 10 (for 

children aged 0-1), 3 (for children aged 2-15), or 1.6 (for 70 years of exposure beginning at 

birth), as needed in risk assessments. In this case, this has the effect of increasing the 

estimated life time risks for these pollutants by a factor of 1.6. In addition, although only a 

 

18Memorandum for the Heads of Executive Departments and Agencies - Updated Principles for Risk Analysis

(September 19, 2007), From Susan E. Dudley, Administrator, Office of Information and Regulatory Affairs, 

Office of Management and Budget; and Sharon L. Hays, Associate Director and Deputy Director for Science, 

Office of Science and Technology Policy 

(http://www.whitehouse.gov/sites/default/files/omb/assets/omb/memoranda/fy2007/m07-24.pdf)
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small fraction of the total POM emissions may be reported as individual compounds, EPA 

expresses carcinogenic potency for compounds in this group in terms of benzo[a]pyrene 

equivalence, based on evidence that carcinogenic POM have the same mutagenic mechanism 

of action as does benzo[a]pyrene. For this reason, EPA implementation policy [27] 

recommends applying the Supplemental Guidance to all carcinogenic PAHs for which risk 

estimates are based on relative potency. Accordingly, we applied the Supplemental Guidance 

to all unspeciated POM mixtures.

Increased cancer incidence for the entire receptor population within the area of analysis was 

estimated by multiplying the estimated lifetime cancer risk for each census block by the 

number of people residing in that block, then summing the results for the entire modeled 

domain. This lifetime population incidence estimate was divided by 70 years to obtain an 

estimate of the number of cancer cases per year.

In the case of benzene, the high end of the reported cancer URE range was used in our 

assessments to provide a conservative estimate of potential cancer risks. Use of the high end 

of the range provides risk estimates that are approximately 3.5 times higher than use of the 

equally plausible low end value. If the estimated benzene–associated risks exceed 1 in a 

million, we also evaluated the impact of using the low end of the URE range on our risk 

results.

Unlike linear dose-response assessments for cancer, noncancer health hazards generally are 

not expressed as a probability of an adverse occurrence. Instead, “risk” for noncancer effects 

is expressed by comparing an exposure to a reference level as a ratio. The “hazard quotient” 

(HQ) is the estimated exposure divided by a reference level (e.g., the RfC). For a given HAP, 

exposures at or below the reference level (HQ≤1) are not likely to cause adverse health 

effects. As exposures increase above the reference level (HQs increasingly greater than 1), 

the potential for adverse effects increases. For exposures predicted to be above the RfC, the 

risk characterization includes the degree of confidence ascribed to the RfC values for the 

compound(s) of concern (i.e., high, medium, or low confidence) and discusses the impact of 

this on possible health interpretations. 

The risk characterization for chronic effects other than cancer is expressed in terms of the HQ 

for inhalation, calculated for each HAP at each census block centroid. As discussed above, 

RfCs incorporate generally conservative uncertainty factors in the face of uncertain 

extrapolations, such that an HQ greater than one does not necessarily suggest the onset of 

adverse effects. The HQ cannot be translated to a probability that adverse effects will occur, 

and is unlikely to be proportional to adverse health effect outcomes in a population.

Screening for potentially significant acute inhalation exposures also followed the HQ 

approach. We divided the maximum estimated acute exposure by each available short-term 

threshold value to develop an array of HQ values relative to the various acute endpoints and 

thresholds. In general, when none of these HQ values are greater than one, there is no 

potential for acute risk. In those cases where HQ values above one are seen, additional 

information is used to determine if there is a potential for significant acute risks.
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2.7.2 Mixtures

Since most or all receptors in these assessments receive exposures to multiple pollutants 

rather than a single pollutant, we estimated the aggregate health risks associated with all the 

exposures from a particular source category combined.

To combine risks across multiple carcinogens, our assessments use the mixtures guidelines’ 

[28,29] default assumption of additivity of effects, and combine risks by summing them using 

the independence formula in the mixtures guidelines.

In assessing noncancer hazard from chronic exposures, in cases where different pollutants 

cause adverse health effects via completely different modes of action, it may be inappropriate 

to aggregate HQs. In consideration of these mode-of-action differences, the mixtures 

guidelines support aggregating effects of different substances in specific and limited ways. 

To conform to these guidelines, we aggregated non-cancer HQs of HAP that act by similar 

toxic modes of action, or (where this information is absent) that affect the same target organ. 

This process creates, for each target organ, a target-organ-specific hazard index (TOSHI), 

defined as the sum of hazard quotients for individual HAP that affect the same organ or organ 

system. All TOSHI calculations presented here were based exclusively on effects occurring 

at the “critical dose” (i.e., the lowest dose that produces adverse health effects). Although 

HQs associated with some pollutants have been aggregated into more than one TOSHI, this 

has been done only in cases where the critical dose affects more than one target organ. 

Because impacts on organs or systems that occur above the critical dose have not been 

included in the TOSHI calculations, some TOSHIs may have been underestimated. As with 

the HQ, the TOSHI should not be interpreted as a probability of adverse effects, or as strict 

delineation of “safe” and “unsafe” levels. Rather, the TOSHI is another measure of the 

potential for adverse health outcomes associated with pollutant exposure, and needs to be 

interpreted carefully by health scientists and risk managers.

Because of the conservative nature of the acute inhalation screening and the variable nature of 

emissions and potential exposures, acute impacts were screened on an individual pollutant 

basis, not using the TOSHI approach.

2.7.3 Facility-wide Risks

To help place the source category risks in context, we examined “facility-wide” risks using 

NEI data and modeling as described in Section 2.2. For the facilities in the OSWRO source

category, we estimated the maximum inhalation cancer and chronic noncancer risks 

associated with all HAP emissions sources at the facility, including emissions sources that are 

not part of this source category but are located within a contiguous area and are under 

common control. We analyzed risks due to the inhalation of HAP for the populations residing 

within 50 kilometers of each facility. The results of the facility-wide assessment are 

summarized below in the risk characterization section of this document. The complete results 

of the facility-wide assessment are provided in Appendix 5 of this document, Detailed Risk 

Modeling Results.
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2.7.4 MACT-Allowable Risk

The emissions data in the data set for the OSWRO source category are estimates of actual 

emissions on an annual basis. The risk results presented in the following sections are based 

on these actual emissions. For the OSWRO source category, estimates of MACT-allowable 

emissions were also estimated, and the risk results based on those emissions are presented 

below as well. For more detail, please refer to the MACT-Allowable memo in docket for this 

action (MACT-Allowable Emissions for the Off-Site Waste and Recovery Operations Source 

Category, located in Docket EPA-HQ-OAR-2012-0360.)

3 Risk Results for the OSWRO Source Category

3.1 Source Category Description and Results

The OSWRO source category includes facilities that store, treat, recycle, or dispose of certain 

wastes, used oil, or used solvents from off-site locations. Specifically, facilities in the 

OSWRO source category handle off-site material, which is defined as any material generated 

from commercial, industrial, agricultural, and mining operations or community activities that 

is recycled, reused, reprocessed, discarded, or is being accumulated, stored, or treated 

(physically, chemically, biologically, or thermally) before being discarded, discharged, or 

recycled. The activities that take place at OSWRO sources vary widely depending on the 

specific treatment, storage, or other handling processes that are being conducted (e.g., 

treatment of wastewater, physical separation of waste mixtures, storage of wastes, 

reprocessing of wastes for recovery or recycling purposes, and other processes). Potential 

HAP emission sources at OSWRO operations include tanks, surface impoundments, 

containers, oil-water separators, process vents, equipment leaks, and individual drain systems 

and other material conveyance systems. 

The data set for the OSWRO source category contains 38 facilities identified with an 

OSWRO MACT code 806 in the 2005 National-scale Air Toxics Assessment (NATA) 

National Emissions Inventory (NEI), as explained in Section 2.1 of this document. The 2005 

NATA NEI was updated for this category with data from industry and enhanced quality 

assurance of facility and emission locations. In the NEI, thirty seven (37) of these facilities are 

identified as major sources one facility is identified as an area source, however we believe 

that all 38 facilities are major sources.

The emissions for the OSWRO source category data set (of 38 facilities) are summarized in 

Table 3.1-1. The total HAP emissions for the source category are approximately 80 tons per 

year. Based on these data, the HAP emitted in the largest quantities across these 38 facilities 

are toluene, methylene chloride, methanol, tetrachloroethene, xylenes (mixed), hydrochloric 

acid, methyl tert-butyl ether, acetonitrile, methyl isobutyl ketone, chlorine, 1,1,1-

trichloroethane, ethyl benzene, acetaldehyde, glycol ethers, hexane, trichloroethylene, 

formaldehyde, styrene, propionaldehyde, benzene, 2,4-toluene diamine, carbon tetrachloride, 

chloroform, ethylene dichloride, ethylene glycol, 1,2-epoxybutane, naphthalene, carbon 

disulfide, 1,1,2-trichloroethane, vinyl acetate, phenol, hydrofluoric acid, chlorobenzene,
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ethylene oxide, methylene diphenyl diisocyanate, cresols (mixed), nitrobenzene, acrylonitrile, 

vinylidene chloride, aniline, methyl methacrylate, propylene dichloride, phthalic anhydride, 

lindane (gamma-hch), 2,4-toluene diisocyanate, titanium tetrachloride, 2-nitropropane, mcresol (3-methylphenol), p-cresol (4-methy phenol), dimethyl formamide, acetamide, and 2,4-

d, salts and esters. These 52 chemicals account for 99 percent of the total emissions by mass. 

Persistent and bioaccumulative HAP (PB HAP)19 reported as emissions from these facilities 

include polycyclic organic matter (analyzed as benzo(a)pyrene), polychlorinated biphenyls, 

lindane (gamma-hch), chlordane, hexachlorobenzene, methoxychlor, toxaphene, heptachlor, 

and trifluralin. The following environmental HAP are emitted from the Off-Site Waste and 

Recovery Operations source category and are included in the environmental risk screen: 

POM, hydrogen chloride and hydrogen fluoride.

Table 3.1-1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk 

Assessment and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (38

facilities in 

data set)

Prioritized Inhalation Dose-Response 

Value Identified by OAQPSb

PBHAP?

Unit 

Risk 

Estimate 

for 

Cancer?

Reference 

Concentration 

for 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

Toluene 15 25  

Methylene Chloride 11 21   

Methanol 8 26  

Tetrachloroethene 8 22   

Xylenes (mixed) 7 24  

Hydrochloric Acid 6 7  

Methyl Tert-butyl Ether 5 11   

Acetonitrile 3 13  

Methyl Isobutyl Ketone 3 24 

Chlorine 2 3  

1,1,1-trichloroethane 2 9  

Ethyl Benzene 1 21   

Acetaldehyde 1 3   

Glycol Ethers  

 Glycol Ethers 1 8  

 Ethylene Glycol Ethyl Ether 0.002 2  

 Ethylene Glycol Methyl Ether 0.002 1  

Hexane 0.8 14  

Trichloroethylene 0.6 16   

Formaldehyde 0.4 12   

Styrene 0.4 17  

Propionaldehyde 0.3 2  

 

19 Persistent and bioaccumulative HAP are defined in the EPA’s Air Toxics Risk Assessment Library, Volume 1, 

EPA-453K-04-001A, as referenced in the NPRM and provided on the EPA’s Technology Transfer Network 

website for Fate, Exposure, and Risk Assessment at http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 
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Table 3.1-1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk 

Assessment and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (38

facilities in 

data set)

Prioritized Inhalation Dose-Response 

Value Identified by OAQPSb

PBHAP?

Unit 

Risk 

Estimate 

for 

Cancer?

Reference 

Concentration 

for 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

Benzene 0.3 15   

2,4-toluene Diamine 0.3 2 

Carbon Tetrachloride 0.3 8   

Chloroform 0.3 11  

Ethylene Dichloride 0.3 8   

Ethylene Glycol 0.3 9 

1,2-epoxybutane 0.2 2  

Naphthalene 0.2 16  

Carbon Disulfide 0.2 6  

1,1,2-trichloroethane 0.2 6  

Vinyl Acetate 0.2 7  

Phenol 0.2 10  

Hydrofluoric Acid 0.1 4  

Chlorobenzene 0.1 7  

Ethylene Oxide 0.1 1   

Methylene Diphenyl Diisocyanate 0.1 1  

Cresols (mixed) 0.1 6 

Nitrobenzene 0.1 6  

Acrylonitrile 0.1 6   

Vinylidene Chloride 0.1 2 

Aniline 0.07 5   

Methyl Methacrylate 0.06 6  

Propylene Dichloride 0.05 4 

Phthalic Anhydride 0.05 4 

Lindane (gamma-hch) 0.05 3   

2,4-toluene Diisocyanate 0.05 3   

Titanium Tetrachloride 0.04 4  

2-nitropropane 0.04 3  

M-cresol (3-methylphenol) 0.04 2 

P-cresol (4-methy Phenol) 0.04 2 

Dimethyl Formamide 0.04 9  

Acetamide 0.04 2 

2,4-d, Salts And Esters 0.04 3

P-dichlorobenzene 0.03 4  

1,3-butadiene 0.03 2   

O-cresol 0.03 1 

Dichloroethyl Ether 0.03 2 
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Table 3.1-1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk 

Assessment and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (38

facilities in 

data set)

Prioritized Inhalation Dose-Response 

Value Identified by OAQPSb

PBHAP?

Unit 

Risk 

Estimate 

for 

Cancer?

Reference 

Concentration 

for 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

Chlordane 0.03 5   

Hexachlorobenzene 0.03 6   

Hexachlorobutadiene 0.03 4   

Hexachloroethane 0.02 5 

1,4-dioxane 0.02 3   

Epichlorohydrin 0.02 4   

Acetophenone 0.02 4

Methoxychlor 0.02 4 

Maleic Anhydride 0.02 4  

2,4-dinitrotoluene 0.02 2  

Dibutylphthalate 0.02 3

Ethyl Acrylate 0.02 6 

Cumene 0.02 8  

Isophorone 0.02 1 

Polychlorinated biphenyls 0.02 3  

1,1,2,2-tetrachloroethane 0.01 4 

Vinyl Chloride 0.01 4   

M-xylene 0.01 4  

Acrylamide 0.01 4  

Toxaphene 0.01 3  

Hexachlorocyclopentadiene 0.01 3 

Bis(2-ethylhexyl)phthalate 0.01 3  

1,2,4-trichlorobenzene 0.01 3 

P-xylene 0.01 2  

Dibenzofuran 0.009 1

Carbaryl 0.008 3

Dimethyl Phthalate 0.008 3

Ethyl Carbamate 0.008 3 

Acrylic Acid 0.008 4  

Methyl Chloride 0.008 3  

Triethylamine 0.008 4  

Pentachlorophenol 0.007 2  

Biphenyl 0.007 3 

4-nitrobiphenyl 0.007 1

N-nitrosomorpholine 0.007 1 

Nitrosodimethylamine 0.007 1 

Heptachlor 0.007 5  
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Table 3.1-1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk 

Assessment and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (38

facilities in 

data set)

Prioritized Inhalation Dose-Response 

Value Identified by OAQPSb

PBHAP?

Unit 

Risk 

Estimate 

for 

Cancer?

Reference 

Concentration 

for 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

Methyl Bromide 0.006 2  

Pentachloronitrobenzene 0.006 1

O-toluidine 0.006 3 

4-nitrophenol 0.005 1

O-xylene 0.005 2  

3,3'-dimethylbenzidine 0.005 1

4,4'-methylene Bis(2-chloroaniline) 0.005 1 

Dimethylcarbamoyl Chloride 0.005 1

Benzidine 0.005 2  

2,4-dinitrophenol 0.005 1

Ethyl Chloride 0.005 1 

Ethylene Dibromide 0.004 2   

3,3'-dimethoxybenzidine 0.004 1

2,4,6-trichlorophenol 0.004 1 

Hydrazine 0.004 3   

1,3-propane Sultone 0.004 1 

Captan 0.004 3

2,4,5-trichlorophenol 0.003 1

Chlorobenzilate 0.003 1 

Diethanolamine 0.003 2 

Dimethyl Sulfate 0.002 3 

Propylene Oxide 0.002 2   

4,4'-methylenedianiline 0.002 1  

Ethylene Thiourea 0.002 1  

Quinone 0.002 1

Allyl Chloride 0.002 1   

Methyl Iodide 0.002 1 

Benzyl Chloride 0.002 3  

1,3-dichloropropene 0.002 1  

P-dimethylaminoazobenzene 0.002 1 

Ethylidene Dichloride 0.002 2  

N,n-dimethylaniline 0.001 2

1,2-dibromo-3-chloropropane 0.001 1  

1,1-dimethylhydrazine 0.001 1 

1,2-diphenylhydrazine 0.001 1 

Benzotrichloride 0.001 1

Phosphorus, White 0.001 1
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Table 3.1-1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk 

Assessment and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (38

facilities in 

data set)

Prioritized Inhalation Dose-Response 

Value Identified by OAQPSb

PBHAP?

Unit 

Risk 

Estimate 

for 

Cancer?

Reference 

Concentration 

for 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

Hydroquinone 0.001 2

Polycyclic Organic Matter  

 2-acetylaminofluorene 0.001 1  

Dichlorvos 0.0008 1  

3,3'-dichlorobenzidine 0.0007 1 

Chloromethyl Methyl Ether 0.0006 1 

Bromoform 0.0004 1 

Styrene Oxide 0.0004 1 

Acrolein 0.0002 2  

Trifluralin 0.0001 2 

Methyl Hydrazine 0.00003 1 

Phosphine 0 1  

a Notes for how HAP were speciated for risk assessment:

 For emissions reported generically as “Glycol Ethers” or specific glycol ethers not found on EPA’s Technology 

Transfer Network for air toxics (see footnote b), emissions were treated as ethylene glycol methyl ether.

b Specific dose-response values for each chemical are identified on EPA’s Technology Transfer Network website for air 

toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html. 

3.2 Risk Characterization

This section presents the results of the risk assessment for the OSWRO source category based 

on the modeling methods described in the previous sections. All baseline risk results are 

developed using the best estimates of actual HAP emissions summarized in the previous 

section. The basic chronic inhalation risk estimates presented here are the maximum 

individual lifetime cancer risk, the maximum chronic hazard index, and the cancer incidence.

We also present results from our acute inhalation impact screening in the form of maximum 

hazard quotients, as well as the results of our preliminary screen for potential non-inhalation 

risks from PB-HAP. Also presented are the HAP “drivers,” which are the HAP that 

collectively contribute 90 percent of the maximum cancer risk or maximum hazard index at 

the highest exposure location, as well as a summary of the results of our facility-wide 

assessments and our analysis of risks associated with the maximum allowed emissions under 

the current MACT standards. A detailed summary of the facility-specific risk assessment 

results is available in Appendix 5 of this document, Draft Detailed Risk Modeling Results.
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Table 3.2-1 summarizes the chronic and acute inhalation risk results for this source category. 

The results of the chronic inhalation cancer risk assessment for the OSWRO source category

estimate that the maximum lifetime individual cancer risks posed by these facilities could be 

as high as 9-in-1 million. The major contributors to this risk are benzidine, and 2,4-toluene 

diamine . Approximately 210,000 people were estimated to have cancer risks at or above 1-in1 in a million as a result of the emissions from this source category. The maximum chronic 

non-cancer target organ specific hazard index (TOSHI) value for the source category could be 

up to 0.6 associated with emissions of chlorine, indicating no significant potential for chronic 

non-cancer impacts. 

Analysis of potential differences between chronic inhalation risks based on actual emission 

levels and the maximum emissions allowed under the MACT standards (i.e., MACTallowable emissions) was conducted. See the memo, MACT-Allowable Emissions for the OffSite Waste and Recovery Operations Source Category, for more details on the calculation of 

these allowable risks. The maximum individual lifetime cancer risk based on allowable 

emissions is estimated to be 20-in-1 million, while the maximum chronic noncancer TOSHI 

value is estimated to be 1.

Worst-case acute hazard quotients (HQs) were calculated for every emitted HAP that has an 

acute benchmark, based on actual emissions. For cases where the screening acute HQ was 

greater than 1, we further refined the estimates by determining the highest HQ value that 

might occur outside facility boundaries. Analysis of potential off-site impacts for the 

OSWRO source category identified no facility with an acute value greater than 1. 

As presented above, the PB-HAP emitted by facilities in this category include polycyclic 

organic matter (POM) (2-acetylaminofluorene analyzed as benzo(a)pyrene TEQ) (1 facility), 

polychlorinated biphenyls (3 facilities), hexachlorobenzene (6 facilities), chlordane (5 

facilities), lindane (gamma hch) (3 facilities), methoxyclor (4 facilities), toxaphene (3 

facilities), heptachlor (5 facilities), and trifluralin (2 facilities). To identify potential 

multipathway health risks from PB-HAP other than lead, we first performed a screening 

analysis (Tier I) that compared emissions of PB-HAP emitted from the OSWRO source 

category (based on actual emissions) to screening emission rates (see section 2.5), where 

those screening emission rates are available. Of the PB-HAP emitted by this category, the 

POM compound 2-acetylaminofluorene has a screening emission rate. The emissions of the 

POM 2-acetylaminofluorene were below the screening value for POM. The remaining PBHAP do not currently have multipathway screening values and so are not evaluated for 

potential non-inhalation risks. As shown in Table 3.1-1, these HAP are not emitted in 

appreciable quantities from off-site waste and recovery operations. 

We conducted a screening-level evaluation of the potential adverse environmental risks 

associated with emissions of the following environmental HAP from the Off-Site Waste and 

Recovery Operations source category: POM, hydrogen chloride, and hydrogen fluoride. The 

results of the environmental screening analysis are summarized in Table 3.2-2. In our Tier I

analysis, emissions of POM did not exceed the threshold emission rates for any of the 

ecological benchmarks (either the LOAEL or NOAEL) for any facility in the source category. 

Therefore, we did not conduct a Tier II environmental screening analysis. For hydrogen 
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fluoride and hydrogen chloride, the average modeled concentration around each facility (i.e., 

the average concentration of all off-site data points in the modeling domain) did not exceed 

the ecological benchmarks. In addition, each individual modeled concentration of hydrogen 

chloride and hydrogen fluoride (i.e., each off-site data point in the modeling domain) was 

below the ecological benchmarks for all facilities. 

Table 3.2-1 Summary of Source Category Level Inhalation Risks for OSWRO

Result HAP “Drivers”

Facilities in Source Category

Number of Facilities Estimated to be in Source 

Category20 38 n/a

Number of Facilities Identified in the NEI and 

Modeled in Risk Assessment 38 n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 1 

million) 9 benzidine, 2,4-toluene diamine

Number of Facilities with Maximum Individual Lifetime Cancer Risk:

Greater than or equal to 100 in 1 million 0 n/a

Greater than or equal to 10 in 1 million 0 n/a

Greater than or equal to 1 in 1 million 8

benzidine, 2,4-toluene diamine, 

nitrosodimethylamine, nnitrosomorpholine, ethylene oxide, 

lindane (gamma-HCH), 

hexachlorobenzene, heptachlor, 

formaldehyde, nitrobenzene, carbon 

tetrachloride, benzene, hydrazine, 

ethylene dichloride, ethyl carbamate, 

acetamide, naphthalene, acrylonitrile, 

2,4-toluene diisocyanate, chlordane, 

toxaphene, ethyl benzene

Chronic Noncancer Risks

Maximum Respiratory Hazard Index 0.6 chlorine

Number of Facilities with Maximum Respiratory Hazard Index:

Greater than 1 0 n/a

Acute NoncancerResults

Maximum Acute Hazard Quotient 1 glycol ethers (REL)

Number of Facilities With Potential for Acute 

Effects 0 n/a

Population Exposure

Number of People Living Within 50 Kilometers 

of Facilities Modeled 35,000,000 n/a

Number of People Exposed to Cancer Risk:

Greater than or equal to 100 in 1 million 0 n/a

 

20 As explained in Section 2.1 of this document, the list of facilities began with 53 facilities and there are 38

facilities included in the modeling file used for this risk assessment.
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Table 3.2-1 Summary of Source Category Level Inhalation Risks for OSWRO

Result HAP “Drivers”

Greater than or equal to 10 in 1 million 0 n/a

Greater than or equal to 1 in 1 million 210,000 n/a

Number of People Exposed to Noncancer Respiratory Hazard Index:

Greater than 1 0 n/a

Estimated Cancer Incidence (excess cancer cases 

per year) 0.02 n/a

Contribution of HAP to Cancer Incidence:

Benzidine 73% n/a

2,4-Toluene diamine 19% n/a

Table 3.2-2 Summary of Environmental Risks Screen Results for OSWRO

Environmental 

HAP

Number of Facilities In Category 

Exceeding

Percent of Modeled 

Area in Category 

Exceeding2

Tier I Screen Tier II Screen1

NOAEL LOAEL NOAEL LOAEL NOAEL LOAEL

PBHAP POM None None - - 0% 0% 

Acid 

Gases3

HF NA None - - NA 0%

HCL4 NA None - - NA 0%

NA – Not Applicable. 

1- Tier II screen is performed for PB-HAP when there are exceedances of the Tier I screen. The acid gas screen 

is a one tier screen.

2 - A value of 0% indicates that none of the modeled data points exceeded the benchmark. For PB-HAP the 

percent area is based on the Tier II results, if a Tier II analysis is performed. Otherwise, the percent area is based 

on the Tier I results. 

3 – For HF, we evaluated two benchmarks, one from Canada and the other from the State of Washington. 

Although, they are both considered to be LOELs - the level between a NOAEL and a LOAEL, we have listed the 

results under the LOAEL column.

4 – For HCL, we evaluated one benchmark at the LOAEL level.

The facility-wide MIR and TOSHI, available in Appendix 5 of this document (Draft Detailed 

Risk Results), are based on emissions, as collected in the NEI, from all emissions sources at 

the identified facilities. The results of the facility-wide assessment are summarized in Table 

3.2-3. The results indicate that 17 facilities with OSWRO processes have facility-wide cancer

MIR greater than or equal to 1-in-1million. The maximum facility-wide MIR is 200 in a 

million due to emissions of beryllium compounds from cement manufacturing, with the 

OSWRO source category contributing less than 1 percent of the risk. The maximum facilitywide TOSHI is 4, and occurs at 2 facilities. At one, the HI is driven mainly by emissions of 

chlorine from industrial inorganic chemical manufacturing processes and synthetic organic 

chemical manufacturing processes, while the other is driven mainly by emissions of beryllium 
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compounds from cement manufacturing. In each instance, the source category contributes 

less than 1 percent to the facility-wide TOSHI.

Table 3.2-3 Source Category Contribution to Facility-Wide Cancer Risks 

OSWRO Number of Facilities Binned by Facility-Wide 

MIR (in 1 million)

Source Category MIR 

Contribution to Facility-Wide 

MIR

<1 1≤ MIR<10 10≤ MIR<100 > 100 Total

> 90% 7* 4 0 0 11

50-90% 4 3 0 0 7

10-50% 1 0 0 0 1

< 10% 9 5 4 1 19

Total 21 * 12 4 1 38 *

* Includes one facility for which both source category and facility-wide modeled risk is 0.

4 General Discussion of Uncertainties and How They Have Been 

Addressed

4.1 Exposure Modeling Uncertainties

Although every effort has been made to identify all the relevant facilities and emission points, 

as well as to develop accurate estimates of the annual emission rates for all relevant HAP, the 

uncertainties in our emission inventory likely dominate the uncertainties in our exposure

modeling estimates. The chronic ambient modeling uncertainties are considered relatively 

small in comparison, since we are using EPA’s refined local dispersion model with sitespecific parameters and reasonably representative meteorology. If anything, the population 

exposure estimates are biased high by not accounting for short- or long-term population 

mobility, and by neglecting processes like deposition, plume depletion, and atmospheric 

degradation. Additionally, estimates of the maximum individual risk (MIR) contain 

uncertainty, because they are derived at census block centroid locations rather than actual 

residences. This uncertainty is known to create potential underestimates and overestimates of 

the actual MIR values for individual facilities, but, overall, it is not thought to have a 

significant impact on the estimated MIR for a source category. Finally, we did not factor in 

the possibility of a source closure occurring during the 70-year chronic exposure period, 

leading to a potential upward bias in both the MIR and population risk estimates; nor did we 

factor in the possibility of population growth during the 70-year chronic exposure period, 

leading to a potential downward bias in both the MIR and population risk estimates.

A sensitivity analysis performed for the 1999 NATA found that the selection of the 

meteorology dataset location could result in a range of chronic ambient concentrations which 

varied from as much as 17% below the predicted value to as much as 84% higher than the 
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predicted value. This variability translates directly to the predicted exposures and risks in our 

assessment, indicating that the actual risks could vary from 17% lower to 84% higher than the 

predicted values.

We have purposely biased the acute screening results high, considering that they depend upon 

the joint occurrence of independent factors, such as hourly emissions rates, meteorology and 

human activity patterns. Furthermore, in cases where multiple acute threshold values are 

considered scientifically acceptable we have chosen the most conservative of these threshold 

values, erring on the side of overestimating potential health risks from acute exposures. In the 

cases where these results indicated the potential for exceeding short-term health thresholds, 

we have refined our assessment by developing a better understanding of the geography of the 

facility relative to potential exposure locations. 

4.2 Uncertainties in the Dose-Response Relationships

In the sections that follow, separate discussions are provided on uncertainty associated with 

cancer potency factors and for noncancer reference values. Cancer potency values are derived 

for chronic (lifetime) exposures. Noncancer reference values are generally derived for 

chronic exposures (up to a lifetime), but may also be derived for acute ( -

term (>24 hours up to 30 days), and subchronic (>30 days up to 10% of lifetime) exposure 

durations, all of which are derived based on an assumption of continuous exposure throughout 

the duration specified. For the purposes of assessing all potential health risks associated with 

the emissions included in an assessment, we rely on both chronic (cancer and noncancer) and 

acute (noncancer) benchmarks, which are described in more detail below.

Although every effort is made to identify peer-reviewed dose-response values for all HAP

emitted by the source category included in an assessment, some HAP have no peer-reviewed 

cancer potency values or reference values for chronic non-cancer or acute effects (inhalation 

or ingestion). Since exposures to these pollutants cannot be included in a quantitative risk 

estimate, an understatement of risk for these pollutants at environmental exposure levels is 

possible.

Additionally, chronic dose-response values for certain compounds included in the assessment 

may be under EPA IRIS review and revised assessments may determine that these pollutants 

are more or less potent than currently thought. We will re-evaluate risks if, as a result of these 

reviews, a dose-response metric changes enough to indicate that the risk assessment may 

significantly mischaracterize human health risk

Cancer assessment

The discussion of dose-response uncertainties in the estimation of cancer risk below focuses 

on the uncertainties associated with the specific approach currently used by the EPA to 

develop cancer potency factors. In general, these same uncertainties attend the development 

of cancer potency factors by CalEPA, the source of peer-reviewed cancer potency factors 

used where EPA-developed values are not yet available. To place this discussion in context, 
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we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [30] (herein 

referred to as Cancer Guidelines). “The primary goal of EPA actions is protection of human 

health; accordingly, as an Agency policy, risk assessment procedures, including default 

options that are used in the absence of scientific data to the contrary, should be health 

protective.” The approach adopted in this document is consistent with this approach as 

described in the Cancer Guidelines.

For cancer endpoints EPA usually derives an oral slope factor for ingestion and a unit risk 

value for inhalation exposures. These values allow estimation of a lifetime probability of 

developing cancer given long-term exposures to the pollutant. Depending on the pollutant 

being evaluated, EPA relies on both animal bioassay and epidemiological studies to 

characterize cancer risk. As a science policy approach, consistent with the Cancer 

Guidelines, EPA uses animal cancer bioassays as indicators of potential human health risk 

when other human cancer risk data are unavailable. 

Extrapolation of study data to estimate potential risks to human populations is based upon 

EPA’s assessment of the scientific database for a pollutant using EPA’s guidance documents 

and other peer-reviewed methodologies. The EPA Cancer Guidelines describes the Agency’s 

recommendations for methodologies for cancer risk assessment. EPA believes that cancer 

risk estimates developed following the procedures described in the Cancer Guidelines and 

outlined below generally provide an upper bound estimate of risk. That is, EPA’s upper 

bound estimates represent a “plausible upper limit to the true value of a quantity” (although 

this is usually not a true statistical confidence limit).21 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.22 

When developing an upper bound estimate of risk and to provide risk values that do not 

underestimate risk, EPA generally relies on conservative default approaches.23 EPA also uses 

the upper bound (rather than lower bound or central) estimates in its assessments, although it 

is noted that this approach can have limitations for some uses (e.g. priority setting, expected 

benefits analysis).

Such health risk assessments have associated uncertainties, some which may be considered 

quantitatively, and others which generally are expressed qualitatively. Uncertainties may vary 

substantially among cancer risk assessments associated with exposures to different pollutants, 

 

21 IRIS glossary (www.epa.gov/NCEA/iris/help_gloss.htm).

22 The exception to this is the URE for benzene, which is considered to cover a range of values, each end of 

which is considered to be equally plausible, and which is based on maximum likelihood estimates.

23 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are 

generic approaches, based on general scientific knowledge and policy judgment, that are applied to various 

elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 

NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the 

option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to 

the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the 

agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be 

appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions 

are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly 

overestimate risk). See EPA 2004 An Examination of EPA Risk Assessment Principles and Practices, 

EPA/100/B-04/001 available at: http://www.epa.gov/osa/pdfs/ratf-final.pdf.
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since the assessments employ different databases with different strengths and limitations and 

the procedures employed may differ in how well they represent actual biological processes for 

the assessed substance. EPA’s Risk Characterization Handbook also recommends that risk 

characterizations present estimates demonstrating the impact on the assessment of alternative 

choices, data, models and assumptions [31]. Some of the major sources of uncertainty and 

variability in deriving cancer risk values are described more fully below. 

(1) The qualitative similarities or differences between tumor responses observed in 

experimental animal bioassays and those which would occur in humans is a source of 

uncertainty in cancer risk assessment. In general, EPA does not assume that tumor sites 

observed in an experimental animal bioassay are necessarily predictive of the sites at which 

tumors would occur in humans.24 However, unless scientific support is available to show 

otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target 

organ concordance. For a specific pollutant, qualitative differences in species responses can 

lead to either under-estimation or over-estimation of human cancer risks. 

(2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead 

to differences in risk predictions. For example, the measure of dose is commonly expressed 

in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, data may 

support development of a pharmacokinetic model for the absorption, distribution, metabolism 

and excretion of an agent, which may result in improved dose metrics (e.g., average blood 

concentration of the pollutant or the quantity of agent metabolized in the body). Quantitative 

uncertainties result when the appropriate choice of a dose metric is uncertain or when dose 

metric estimates are themselves uncertain (e.g., as can occur when alternative 

pharmacokinetic models are available for a compound). Uncertainty in dose estimates may 

lead to either over or underestimation of risk.

(3) For the quantitative extrapolation of cancer risk estimates from experimental animals to 

humans, EPA uses scaling methodologies (relating expected response to differences in 

physical size of the species), which introduce another source of uncertainty. These 

methodologies are based on both biological data on differences in rates of process according 

to species size and empirical comparisons of toxicity between experimental animals and 

humans. For a particular pollutant, the quantitative difference in cancer potency between 

experimental animals and humans may be either greater than or less than that estimated by 

baseline scientific scaling predictions due to uncertainties associated with limitations in the 

test data and the correctness of scaled estimates. 

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, 

are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which 

there is a specified excess risk of cancer, which is used as the point of departure (or POD) for 

the remainder of the calculation. Statistical uncertainty in developing a POD using a 

benchmark dose (BMD) approach is generally addressed though use of the 95% lower 

confidence limit on the dose at which the specified excess risk occurs (the BMDL), 

 

24 Per the EPA Cancer Guidelines: “The default option is that positive effects in animal cancer studies indicate 

that the agent under study can have carcinogenic potential in humans.” and “Target organ concordance is not a 

prerequisite for evaluating the implications of animal study results for humans.”
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decreasing the likelihood of understating risk. EPA has generally utilized the multistage 

model for estimation of the BMDL using cancer bioassay data (see further discussion below).

(5) Extrapolation from high to low doses is an important, and potentially large, source of 

uncertainty in cancer risk assessment. EPA uses different approaches to low dose risk 

assessment (i.e., developing estimates of risk for exposures to environmental doses of an 

agent from observations in experimental or epidemiological studies at higher dose) depending 

on the available data and understanding of a pollutant’s mode of action (i.e., the manner in 

which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use 

of reliable, compound-specific, biologically-based risk models when feasible; however, such 

models are rarely available. The mode of action for a pollutant (i.e., the manner in which a 

pollutant causes cancer) is a key consideration in determining how risks should be estimated 

for low-dose exposure. A reference value is calculated when the available mode of action 

data show the response to be nonlinear (e.g., as in a threshold response). A linear low-dose 

(straight line from POD) approach is used when available mode of action data support a linear 

(e.g., nonthreshold response) or as the most common default approach when a compound’s 

mode of action is unknown. Linear extrapolation can be supported by both pollutant-specific 

data and broader scientific considerations. For example, EPA’s Cancer Guidelines generally 

consider a linear dose-response to be appropriate for pollutants that interact with DNA and 

induce mutations. Pollutants whose effects are additive to background biological processes in 

cancer development can also be predicted to have low-dose linear responses, although the 

slope of this relationship may not be the same as the slope estimated by the straight line 

approach. 

EPA most frequently utilizes a linear low-dose extrapolation approach as a baseline sciencepolicy choice (a “default”) when available data do not allow a compound-specific 

determination. This approach is designed to not underestimate risk in the face of uncertainty 

and variability. EPA believes that linear dose-response models, when appropriately applied 

as part of EPA’s cancer risk assessment process, provide an upper bound estimate of risk and 

generally provide a health protective approach. Note that another source of uncertainty is the 

characterization of low-dose nonlinear, non-threshold relationships. The National Academy 

of Sciences has encouraged the exploration of sigmoidal type functions (e.g., log-probit 

models) in representing dose response relationships due to the variability in response within 

human populations. Another National Research Council (NRC) report [32] suggests that 

models based on distributions of individual thresholds are likely to lead to sigmoidal-shaped 

dose-response functions for a population. This report notes sources of variability in the 

human population: “One might expect these individual tolerances to vary extensively in 

humans depending on genetics, coincident exposures, nutritional status, and various other 

susceptibility factors...” Thus, if a distribution of thresholds approach is considered for a 

carcinogen risk assessment, application would depend on ability of modeling to reflect the 

degree of variability in response in human populations (as opposed to responses in bioassays 

with genetically more uniform rodents). Note also that low dose linearity in risk can arise for 

reasons separate from population variability: due to the nature of a mode of action and 

additivity of a chemical’s effect on top of background chemical exposures and biological 

processes.
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As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight 

line approach from the BMDL. This is equivalent to using an upper confidence limit on the 

slope of the straight line extrapolation. The impact of the choice of the BMDL on bottom line 

risk estimates can be quantified by comparing risk estimates using the BMDL value to central 

estimate BMD values, although these differences are generally not a large contributor to 

uncertainty in risk assessment (Subramaniam et. al., 2006) [33]. It is important to note that 

earlier EPA assessments, including the majority of those for which risk values exist today, 

were generally developed using the multistage model to extrapolate down to environmental 

dose levels and did not involve the use of a POD. Subramaniam et. al. (2006) also provide 

comparisons indicating that slopes based on straight line extrapolation from a POD do not 

show large differences from those based on the upper confidence limit of the multistage 

model.

(6) Cancer risk estimates do not generally make specific adjustments to reflect the variability 

in response within the human population — resulting in another source of uncertainty in 

assessments. In the diverse human population, some individuals are likely to be more 

sensitive to the action of a carcinogen than the typical individual, although compound-specific 

data to evaluate this variability are generally not available. There may also be important life 

stage differences in the quantitative potency of carcinogens and, with the exception of the 

recommendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic 

mode of action, risk assessments do not generally quantitatively address life stage differences. 

However, one approach used commonly in EPA assessments that may help address variability 

in response is to extrapolate human response from results observed in the most sensitive 

species and sex tested, resulting typically in the highest URE which can be supported by 

reliable data, thus supporting estimates that are designed not to underestimate risk in the face 

of uncertainty and variability.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure levels that are intended to be 

health-protective. That is, EPA and other organizations which develop noncancer reference 

values (e.g., the Agency for Toxic Substances and Disease Registry – ATSDR) utilize an 

approach that is intended not to underestimate risk in the face of uncertainty and variability. 

When there are gaps in the available information, uncertainty factors (UFs) are applied to 

derive reference values that are intended to be protective against appreciable risk of 

deleterious effects. Uncertainty factors are commonly default values25 e.g., factors of 10 or 3, 

 

25

 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are 

generic approaches, based on general scientific knowledge and policy judgment, that are applied to various 

elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 

NRC report, Risk Assessment in the Federal Government: Managing the Process defined default option as “the 

option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to 

the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the 

agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be 

appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions 

are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly 

overestimate risk). See EPA 2004 An examination of EPA Risk Assessment Principles and Practices,

EPA/100/B-04/001 available at: http://www.epa.gov/osa/pdfs/ratf-final.pdf.
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used in the absence of compound-specific data; where data are available, uncertainty factors 

may also be developed using compound-specific information. When data are limited, more 

assumptions are needed and more default factors are used. Thus there may be a greater 

tendency to overestimate risk—in the sense that further study might support development of 

reference values that are higher (i.e., less potent) because fewer default assumptions are 

needed. However, for some pollutants it is possible that risks may be underestimated.

For non-cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) 

for exposures via ingestion, and a Reference Concentration (RfC) for inhalation exposures. 

These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) 

of daily oral exposure (RfD) or of a continuous inhalation exposure (RfC) to the human 

population (including sensitive subgroups) that is likely to be without an appreciable risk of 

deleterious effects during a lifetime.26 To derive values that are intended to be “without 

appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach 

[34],[35] which includes consideration of both uncertainty and variability.

 

EPA begins by evaluating all of the available peer-reviewed literature to determine noncancer endpoints of concern, evaluating the quality, strengths and limitations of the available 

studies. EPA typically chooses the relevant endpoint that occurs at the lowest dose, often 

using statistical modeling of the available data, and then determines the appropriate point of 

departure (POD) for derivation of the reference value. A POD is determined by (in order of 

preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of 

the dose or concentration at which the toxic response was not significantly elevated (no 

observed adverse effect level— NOAEL); or (3) use of the lowest observed adverse effect 

level (LOAEL).

A series of downward adjustments using default UFs is then applied to the POD to estimate 

the reference value [36]. While collectively termed “UFs”, these factors account for a number 

of different quantitative considerations when utilizing observed animal (usually rodent) or 

human toxicity data in a risk assessment. The UFs are intended to account for: (1) variation 

in susceptibility among the members of the human population (i.e., inter-individual 

variability); (2) uncertainty in extrapolating from experimental animal data to humans (i.e., 

interspecies differences); (3) uncertainty in extrapolating from data obtained in a study with 

less-than-lifetime exposure (i.e., extrapolating from subchronic to chronic exposure); (4) 

uncertainty in extrapolating from a LOAEL in the absence of a NOAEL; and (5) uncertainty 

when the database is incomplete or there are problems with applicability of available studies.

When scientifically sound, peer-reviewed assessment-specific data are not available, default 

adjustment values are selected for the individual UFs. For each type of uncertainty (when 

relevant to the assessment), EPA typically applies an UF value of 10 or 3 with the cumulative 

UF value leading to a downward adjustment of 10-3000 fold from the selected POD. An UF 

of 3 is used when the data do not support the use of a 10-fold factor. If an extrapolation step 

or adjustment is not relevant to an assessment (e.g., if applying human toxicity data and an 

 

26 See IRIS glossary
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interspecies extrapolation is not required) the associated UF is not used. The major 

adjustment steps are described more fully below.

1) Heterogeneity among humans is a key source of variability as well as uncertainty. 

Uncertainty related to human variation is considered in extrapolating doses from a subset or 

smaller-sized population, often of one sex or of a narrow range of life stages (typical of 

occupational epidemiologic studies), to a larger, more diverse population. In the absence of 

pollutant-specific data on human variation, a 10-fold UF is used to account for uncertainty 

associated with human variation. Human variation may be larger or smaller; however, data to 

examine the potential magnitude of human variability are often unavailable. In some 

situations, a smaller UF of 3 may be applied to reflect a known lack of significant variability 

among humans.

2) Extrapolation from results of studies in experimental animals to humans is a 

necessary step for the majority of chemical risk assessments. When interpreting animal data, 

the concentration at the POD (e.g. NOAEL, BMDL) in an animal model (e.g. rodents) is 

extrapolated to estimate the human response. While there is long-standing scientific support 

for the use of animal studies as indicators of potential toxicity to humans, there are 

uncertainties in such extrapolations. In the absence of data to the contrary, the typical 

approach is to use the most relevant endpoint from the most sensitive species and the most 

sensitive sex in assessing risks to the average human. Typically, compound specific data to 

evaluate relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty 

in this extrapolation. Size-related differences (allometric relationships) indicate that typically 

humans are more sensitive than rodents when compared on a mg/kg/day basis. The default 

choice of 10 for the interspecies UF is consistent with these differences. For a specific 

chemical, differences in species responses may be greater or less than this value.

Pharmacokinetic models are useful to examine species differences in pharmacokinetic 

processing and associated uncertainties; however, such dosimetric adjustments are not always 

possible. Information may not be available to quantitatively assess toxicokinetic or 

toxicodynamic differences between animals and humans, and in many cases a 10-fold UF 

(with separate factors of 3 for toxicokinetic and toxicodynamic components) is used to 

account for expected species differences and associated uncertainty in extrapolating from 

laboratory animals to humans in the derivation of a reference value. If information on one or 

the other of these components is available and accounted for in the cross-species 

extrapolation, a UF of 3 may be used for the remaining component.

3) In the case of reference values for chronic exposures where only data from shorter 

durations are available (e.g., 90-day subchronic studies in rodents) or when such data are 

judged more appropriate for development of an RfC, an additional UF of 3 or 10-fold is 

typically applied unless the available scientific information supports use of a different value.

4) Toxicity data are typically limited as to the dose or exposure levels that have been 

tested in individual studies; in an animal study, for example, treatment groups may differ in 

exposure by up to an order of magnitude. The preferred approach to arrive at a POD is to use 

BMD analysis; however, this approach requires adequate quantitative results for a meaningful 
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analysis, which is not always possible. Use of a NOAEL is the next preferred approach after 

BMD analysis in determining a POD for deriving a health effect reference value. However, 

many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a 

NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3-fold is 

often applied. 

5) The database UF is intended to account for the potential for deriving an 

underprotective RfD/RfC due to a data gap preventing complete characterization of the 

chemical’s toxicity. In the absence of studies for a known or suspected endpoint of concern, a 

UF of 10 or 3-fold is typically applied.

There is no RfD or other comparable chronic health benchmark value for lead compounds. 

Thus, to address multipathway human health and environmental risks associated with 

emissions of lead from these facilities, ambient lead concentrations were compared to the 

NAAQS for lead. In developing the NAAQS for lead, EPA considered human health 

evidence reporting adverse health effects associated with lead exposure, as well as an EPA 

conducted multipathway risk assessment that applied models to estimate human exposures to 

air-related lead and the associated risk (73FR at 66979). EPA also explicitly considered the 

uncertainties associated with both the human health evidence and the exposure and risk 

analyses when developing the NAAQS for lead. For example, EPA considered uncertainties 

in the relationship between ambient air lead and blood lead levels (73FR at 66974), as well as 

uncertainties between blood lead levels and loss of IQ points in children (73FR at 66981). In 

considering the evidence and risk analyses and their associated uncertainties, the EPA 

Administrator noted his view that there is no evidence- or risk-based bright line that indicates 

a single appropriate level. Instead, he noted, there is a collection of scientific evidence and 

judgments and other information, including information about the uncertainties inherent in 

many relevant factors, which needs to be considered together in making this public health 

policy judgment and in selecting a standard level from a range of reasonable values (73FR at 

66998). In so doing, the Administrator decided that, a level for the primary lead standard of 

0.15 μg/m3, in combination with the specified choice of indicator, averaging time, and form, 

is requisite to protect public health, including the health of sensitive groups, with an adequate 

margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and 

exposure analyses, and their associated uncertainties can be found in EPA’s final rule revising 

the lead NAAQS (73 FR 66970-66981, November 12, 2008). 

We also note the uncertainties associated with the health-based (i.e., primary) NAAQS are 

likely less than the uncertainties associated with dose-response values developed for many of 

the other HAP, particularly those HAP for which no human health data exist. In 1988, EPA’s 

IRIS program reviewed the health effects data regarding lead and its inorganic compounds 

and determined that it would be inappropriate to develop an RfD for these compounds, 

saying, “A great deal of information on the health effects of lead has been obtained through 

decades of medical observation and scientific research. This information has been assessed in 

the development of air and water quality criteria by the Agency's Office of Health and 

Environmental Assessment (OHEA) in support of regulatory decision-making by the Office 

of Air Quality Planning and Standards (OAQPS) and by the Office of Drinking Water 

(ODW). By comparison to most other environmental toxicants, the degree of uncertainty 
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about the health effects of lead is quite low. It appears that some of these effects, particularly 

changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral 

development, may occur at blood lead levels so low as to be essentially without a threshold. 

The Agency's RfD Work Group discussed inorganic lead (and lead compounds) at two 

meetings (07/08/1985 and 07/22/1985) and considered it inappropriate to develop an RfD for 

inorganic lead.” EPA’s IRIS assessment for Lead and compounds (inorganic) (CASRN 7439-

92-1), http://www.epa.gov/iris/subst/0277.htm. 

We note further that because of the multi-pathway, multi-media impacts of lead, the risk 

assessment supporting the NAAQS considered direct inhalation exposures and indirect airrelated multi-pathway exposures from industrial sources like primary and secondary lead 

smelting operations. It also considered background lead exposures from other sources (like 

contaminated drinking water and exposure to lead-based paints). In revising the NAAQS for 

lead, we note that the Administrator placed more weight on the evidence-based framework 

and less weight on the results from the risk assessment, although he did find the risk estimates 

to be roughly consistent with and generally supportive of the evidence-based framework 

applied in the NAAQS determination (73FR at 67004). Thus, when revising the NAAQS for 

lead to protect public health with an adequate margin of safety, EPA considered both the 

evidence-based framework and the risk assessment, albeit to different extents.

Acute noncancer assessment

Many of the UFs used to account for variability and uncertainty in the development of acute 

reference values are quite similar to those developed for chronic durations, but more often 

using individual UF values that may be less than 10. UFs are applied based on chemicalspecific or health effect-specific information (e.g., simple irritation effects do not vary 

appreciably between human individuals, hence a value of 3 is typically used), or based on the 

purpose for the reference value (see the following paragraph). The UFs applied in acute 

reference value derivation include: 1) heterogeneity among humans; 2) uncertainty in 

extrapolating from animals to humans; 3) uncertainty in LOAEL to NOAEL adjustments; and 

4) uncertainty in accounting for an incomplete database on toxic effects of potential concern. 

Additional adjustments are often applied to account for uncertainty in extrapolation from 

observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an 

acute reference value at another exposure duration (e.g., 1 hour). 

Not all acute reference values are developed for the same purpose and care must be taken 

when interpreting the results of an acute assessment of human health effects relative to the 

reference value or values being exceeded. Where relevant to the estimated exposures, the 

lack of threshold values at different levels of severity should be factored into the risk 

characterization as potential uncertainties. 
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5 References

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Review by the EPA’s Science Advisory Board with Case Studies – MACT I Petroleum Refining 

Sources and Portland Cement Manufacturing. EPA-452/R-09-006. 

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3. US EPA, 2010. SAB’s Response to EPA’s RTR Risk Assessment Methodologies. 

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A-SAB-10-007-unsigned.pdf

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20. CA Office of Environmental Health Hazard Assessment, 2000. All Acute Reference Exposure 

Levels developed by OEHHA as of May 2000. 

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27. US EPA, 2005. Science Policy Council Cancer Guidelines Implementation Workgroup 

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34. US EPA. 1993. Reference Dose (RfD): Description and Use in Health Risk Assessments. 

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35. US EPA. 1994. Methods for Derivation of Inhalation Reference Concentrations and 

Application of Inhalation Dosimetry. 

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36. US EPA. 2002. A Review of the Reference Dose and Reference Concentration Processes. 

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