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Draft Residual Risk Assessment for the Flexible Polyurethane 

Foam Production Source Category

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

August 2013
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Table of Contents

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

2 Methods.............................................................................................................................. 5

2.1 Emissions and source data........................................................................................... 5

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

2.3 Estimating human inhalation exposure ....................................................................... 8

2.4 Acute Risk Screening and Refined Assessments ........................................................ 9

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

2.6 Dose-Response Assessment ...................................................................................... 11

2.6.1 Sources of chronic dose-response information .................................................. 12

2.6.2 Sources of acute dose-response information...................................................... 17

2.7 Risk Characterization ................................................................................................ 20

2.7.1 General ............................................................................................................... 20

2.7.2 Mixtures............................................................................................................. 22

3 Risk Results.................................................................................................................. 23

3.1 Source Category Description and Results................................................................. 23

3.2 Risk Characterization ................................................................................................ 24

4 General Discussion of Uncertainties and How They Have Been Addressed................... 28

4.1 Exposure Modeling Uncertainties............................................................................. 28

4.2 Uncertainties in the Dose-Response Relationships................................................... 29

5 References........................................................................................................................ 38

Index of Tables

Table 2.2-1 AERMOD version 11103 model options for RTR modeling................................ 6

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

Table 2.6-1 (b) Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens

.................................................................................................................................................. 17

Table 2.6-2 Dose-Response Values for Acute Exposure........................................................ 20

Table 3.1-1 Summary of Emissions from the Flexible Polyurethane Foam Production 

Category and Availability of Dose-Response Values.............................................................. 24

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

Foam Production ...................................................................................................................... 26

Appendices

Appendix 1 Development of the RTR Emissions Dataset for the Flexible Polyurethane 

Foam Production Source Category

Appendix 2 Technical Support Document for HEM3 Modeling

Appendix 3 Meteorological Data for HEM3 Modeling

Appendix 4 Analysis of data on short-term emission rates relative to long-term emission 

rates
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Appendix 5 Technical Support Document for TRIM-Based Multipathway Screening 

Scenario for RTR: Summary of Approach and Evaluation

Appendix 6 Detailed Risk Modeling Results

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

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

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 (HAPs) 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 the memo entitled, “EPA’s Actions in Response 

to Key Recommendations from the SAB Review of RTR risk Assessment Methodologies” 

[4].

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

implementation of the respective MACT standards) performed for the Flexible Polyurethane 

Foam Production 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. 
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2 Methods

2.1 Emissions and source data

The Flexible Polyurethane Foam Production source category includes facilities manufacturing 

flexible polyurethane foam. Specifically, the rule targets three distinct segments of this 

industry: slabstock, molded, and rebond polyurethane foam production. Potential hazardous 

air pollutant (HAP) emission sources at foam production facilities depend on the type of foam 

being produced. Generally, air toxics are released from reactants, auxiliary blowing agents, 

solvents, adhesives, equipment cleaners, and other chemicals used in the manufacturing of 

these materials. A complete description of the flexible polyurethane foam production source 

category can be found in the text of the NPRM.

We currently estimate that there are approximately 13 Flexible Polyurethane Foam production 

facilities subject to the MACT standards: 7 Slabstock, 6 molded, and 2 rebond. Both rebond 

facilities are co-located with either a slabstock or molded foam facility. The NPRM data set 

contains these 13 facilities identified with a MACT code 1314 in the 2005 National-scale Air 

Toxics Assessment (NATA) National Emissions Inventory (NEI). The 2005 NATA NEI was 

updated for this category with data from industry and enhanced quality assurance of facility 

and emission locations. 

The emissions for the Flexible Polyurethane Foam Production source category NPRM data set 

(of 13 facilities) are summarized in Table 2-1. The total HAP emissions for the source 

category are approximately 1 ton per year. Based on these data, the HAP emitted in the largest 

quantities across these 13 facilities are 2,4-toluene diisocyanate, propylene oxide, and toluene. 

These 3 chemicals account for 93 percent of the total emissions by mass. No persistent and 

bioaccumulative HAP (PB HAP)1 are reported as emissions from the 13 facilities in the 

Flexible Polyurethane Foam Production source category. The emissions data and risk 

assessment inputs for the FPUF production source category are described further in Appendix 

1, “Development of the RTR Emissions Dataset for the Flexible Polyurethane Foam 

Production Source Category.”

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 2. 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.

 1 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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The dispersion model in the HEM3 system, AERMOD version 11103, 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.

Table 2.2-1 AERMOD version 11103 model options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point

Receptor orientation Polar (13 rings and 16 radials)

Discrete (census block centroids)

Terrain characterization Actual from USGS 1/3 Arc Second NED data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option No

Meteorology 1 year representative NWS from nearest site (over 800 

stations)

In HEM3, meteorological data are ordinarily selected from a list of over 824 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 52 miles (84 km). Appendix 3 (Meteorological Data 

Processing Using AERMET for HEM3) provides a complete listing of stations and 
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assumptions along with further details used in processing the data through AERMET. 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. 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 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 contains 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.

The average hourly emissions rate is defined as the total emissions for a year divided by the 

total number of operating hours in the year. The choice of a factor of ten for acute screening 

was originally based on engineering judgment. 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 heavilyindustrialized 4-county area (Harris, Galveston, Chambers, and Brazoria Counties, TX) over 

an eleven-month time period in 2001. We obtained the dataset and performed our own 

analysis, focusing that analysis on sources which reported emitting high quantities of HAP 

over short periods of time (see Appendix 4, 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, 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 typically chose a factor of ten for the initial screening. These factors are

intended to cover all possible hourly peaks associated with routinely-variable emissions. 

While there have been some documented emission excursions above this level, our analysis of 
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the data from the Texas Environmental Research Consortium suggests that this factor should 

cover more than 99% of the short-term peak gaseous or volatile HAP emissions from typical 

industrial sources. 

 

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.

In addition to using receptor elevation to determine plume height, 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 2. 

2.3 Estimating 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% 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 

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. 
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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.

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. We used conservative 

assumptions for emission rates, meteorology, and exposure location. We used the following 

worst-case assumptions in our screening approach:

• 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.
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• 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.

As mentioned above, when we identify acute impacts which exceed their relevant 

benchmarks, we pursue refining our acute screening estimates. For the Flexible Polyurethane 

Foam Production source category data were not available to develop a refined emissions 

multiplier, therefore, the default emissions multiplier of 10 was used.

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). The PB-HAP compounds or compound classes are identified for 

the screening from the EPA’s Air Toxics Risk Assessment Library [8]. Examples of PB-HAP 

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. There are no PB-HAP emissions in the Flexible Polyurethane 

Foam Production source category. 

PB-HAP emissions, if emitted, are evaluated for potential non-inhalation risks and adverse 

environmental impacts using our screening scenario which was developed for use with the 

TRIM.FaTE2 model. This screening scenario uses environmental media outputs from the 

peer-reviewed TRIM.FaTE to estimate the maximum potential ingestion risks for any 

specified emission scenario by using a generic farming/fishing exposure scenario that 

simulates a subsistence environment. The screening scenario retains many of the ingestion 

and scenario inputs developed for EPA’s Human Health Risk Assessment Protocols 

(HHRAP) for hazardous waste combustion facilities.3

 In the development of the screening 

scenario a sensitivity analysis was conducted to ensure that its key design parameters were 

established such that environmental media concentrations were not underestimated, and to 

also minimize the occurrence of false positives for human health endpoints. See Appendix 5 

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. For the purpose of developing emission rates for our multi-pathway 

screening, we derived emission levels for each PB HAP at which the maximum human health 

risk would be 1 in a million for lifetime cancer risk or a hazard quotient of 1.0 for noncancer 

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 

 2 EPA’s Total Risk Integrated Methodology (General Information) http://epa.gov/ttn/fera/trim_gen.html

3 EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous Waste Combustion Facilities;

http://www.epa.gov/epaoswer/hazwaste/combust/riskvol.htm#volume1
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(NAAQS) for lead. Values below the NAAQS were considered to have a low potential for 

multi-pathway risks.

Since none of the facilities in the Flexible Polyurethane Foam Production source category

reported emissions of PB HAP an assessment of multi-pathway exposures. 

In section 3 we present our inhalation exposure results separate from the multipathway 

screening assessment results, if conducted. We have been questioned as to why we do not 

add these two risk results together. We do not believe it is appropriate to add a multipathway 

screening result to a refined quantitative inhalation risk result. The purpose of the 

multipathway screen is not to provide a quantitative value. This multipathway screening 

approach is designed to point out facilities and pollutants that we are confident do not have a 

multipathway effect and for those that do not screen out, more effort can be focused on them. 

The multipathway screening scenario is a hypothetical scenario that does not have a realworld counterpart. The real world result would be less than the screening result value, but we 

cannot say how much less it would be. In addition, the inhalation assessment is quite refined 

and the multipathway screen is a less rigorous assessment. It might be mathematically logical 

to add these values together, but it is not scientifically appropriate. It is also highly unlikely 

that the receptor exposed to the maximum inhalation risk is also the receptor exposed to the 

maximum multipathway risk. Therefore, we do not believe that it is appropriate to sum the 

inhalation risk assessment results and the multipathway screening result. However, in certain 

cases where we perform a refined multipathway assessment on facilities that have failed the 

Tier 1 and Tier 2 multipathway screen it may be appropriate to combine this refined 

multipathway result with the inhalation result. Compatibility is a major factor in deciding the 

appropriateness of combining the two risk results. For instance if the refined multipathway 

risk results and the inhalation results are associated with the same target organ (e.g. liver 

cancer) then it may be appropriate to add the results together. It should be noted that any 

decision to add these results will bring additional new uncertainties into the assessment. 

Since none of the facilities in the Flexible Polyurethane Foam Production source category 

reported emissions of any environmental HAP included in our environmental risk screen (i.e., 

lead, dioxins, cadmium, mercury, PAHs, HCL, and HF) an environmental risk screen was not 

performed. 
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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 HAPs reported in the emissions inventories for Flexible 

Polyurethane Foam Production sources were based on the EPA Office of Air Quality Planning 

and Standards’ existing recommendations for HAPs [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/m3 in 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 

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 
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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. 

 

In developing chronic risk estimates, we adjusted dose-response values for some HAPs 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 HAPs that lack doseresponse values may pose an unacceptable risk and require further examination, or screen 

out from further assessment. 

 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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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 10-9 per μg/m3) was based on better 

science than the IRIS cancer dose-response value (1.3 x 10-5 per 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, appropriate 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) In the case of nickel compounds, to provide a health-protective estimate of potential 

cancer risks, we used the IRIS URE value for nickel subsulfide in this assessment. Based 

on past scientific and technical considerations, the determination of the percent of nickel 

subsulfide was considered a major factor for estimating the extent and magnitude of the 

risks of cancer due to nickel-containing emissions. Nickel speciation information for 

some of the largest nickel-emitting sources (including oil combustion, coal combustion, 

and others) suggested that at least 35 percent of total nickel emissions may be soluble 

compounds and that the URE for the mixture of inhaled nickel compounds (based on 

nickel subsulfide, and representative of pure insoluble crystalline nickel) could be derived 

to reflect the assumption that 65 percent of the total mass of nickel may be carcinogenic. 

Based on consistent views of major scientific bodies (i.e., National Toxicology Program 

(NTP) in their 12th Report of the Carcinogens (ROC)6

, International Agency for Research 

on Cancer (IARC)7, and other international agencies)8 that consider all nickel compounds 

to be carcinogenic, we currently consider all nickel compounds to have the potential of 

being as carcinogenic to humans. The 12th Report of the Carcinogens states that the 

 5 http://www.nap.edu/catalog.php?record_id=13142

6 National Toxicology Program (NTP), 2011. Report on carcinogens. 12th ed. Research Triangle Park, NC: US 

Department of Health and Human Services (DHHS), Public Health Service. Available online at 

http://ntp.niehs.nih.gov/ntp/roc/twelfth/roc12.pdf

7 International Agency for Research on Cancer (IARC), 1990. IARC monographs on the evaluation of 

carcinogenic risks to humans. Chromium, nickel, and welding. Vol. 49. Lyons, France: International Agency 

for Research on Cancer, World Health Organization Vol. 49:256.

8 World Health Organization (WHO, 1991) and the European Union’s Scientific Committee on Health and 

Environmental Risks (SCHER, 2006).
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“combined results of epidemiological studies, mechanistic studies, and carcinogenic 

studies in rodents support the concept that nickel compounds generate nickel ions in target 

cells at sites critical for carcinogenesis, thus allowing consideration and evaluation of 

these compounds as a single group.” Although the precise nickel compound (or 

compounds) responsible for the carcinogenic effects in humans is not always clear, studies 

indicate that nickel sulfate and the combinations of nickel sulfides and oxides encountered 

in the nickel refining industries cause cancer in humans (these studies are summarized in a 

review by Grimsrud et al., 20109). The major scientific bodies mentioned above have also 

recognized that there are differences in toxicity and/or carcinogenic potential across the 

different nickel compounds. In this inhalation risk assessment, to take a conservative 

approach, we have considered all nickel compounds to be as carcinogenic as nickel 

subsulfide and have applied the IRIS URE for nickel subsulfide without a factor to reflect 

the assumption that 100 percent of the total mass of nickel may be as carcinogenic as pure 

nickel subsulfide. In addition, given that there are two additional URE10 values derived 

for exposure to mixtures of nickel compounds, as a group, that are 2-3 fold lower than the 

IRIS URE for nickel subsulfide, the EPA also considers it reasonable to use a value that is 

50 percent of the IRIS URE for nickel subsulfide for providing an estimate of the lower 

end of the plausible range of cancer potency values for different mixtures of nickel 

compounds. 

5) 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. 

5) A chronic screening level of 163 ug/m3was developed for carbonyl sulfide (COS) from a 

No Observed Adverse Effects Level (NOAEL) of 200 ppm based on brain lesions and 

neurophysiological alterations in rodents. A more detailed discussion of the studies used 

to develop the COS chronic screening level is provided in Appendix 8. The screening 

level includes a total uncertainty factor (UF) of 3,000: 10x for extrapolation for 

interspecies differences, 10x for consideration of intraspecies variability, 10x for 

extrapolation from subchronic to chronic duration, and 3x for database insufficiencies. 

See section 5 of this document for a detailed discussion of exposure modeling 

uncertainties. 

 9

Grimsrud TK and Andersen A. Evidence of carcinogenicity in humans of water-soluble nickel salts. J Occup 

Med Toxicol 2010, 5:1-7. Available online at 

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2868037/?tool=pubmed

10 Two UREs (other than the current IRIS values) have been derived for nickel compounds as a group: one 

developed by the California Department of Health Services 

(http://www.arb.ca.gov/toxics/id/summary/nickel_tech_b.pdf) and the other by the Texas Commission on 

Environmental Quality (http://www.epa.gov/ttn/atw/nata1999/99pdfs/healtheffectsinfo.pdf).
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The chronic screening level for COS is used only as a screening level assessment to 

identify areas with significant inhalation risk potential. A high COS chronic risk based on 

the screening level does not necessarily indicate that further action is required. 

The emissions inventory for the Flexible Polyurethane Foam Production source category

includes emissions of 9 HAP with available chronic quantitative inhalation dose-response 

values. These HAP, their dose-response values, and the source of the values are listed in 

Tables 2.6-1 (a) and (b).

Table 2.6-1 (a) Dose-Response Values for Chronic Inhalation Exposure to 

Carcinogens

URE (unit risk estimate for cancer)11 = cancer risk per μg/m3 of average lifetime 

exposure. Sources: IRIS = EPA Integrated Risk Information System, CAL = California 

EPA Office of Environmental Health Hazard Assessment.

Pollutant CAS Number12 URE5

(1/μg/m3)

Source

Propylene oxide 75569 0.0000037 IRIS

2,4-Toluene diisocyanate 584849 0.000011 CAL

Trichloroethylene 79016 0.0000048 IRIS

 11 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/m3 in air. URE’s are considered upper bound estimates meaning they represent 

a plausible upper limit to the true value. 

12 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 HAPs.
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Table 2.6-1 (b) 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, EPA OAQPS = EPA Office of Air Quality Planning 

and Standards.

Pollutant CAS Number6 RfC 

(mg/m3)

Source13

Diethanolamine 111422 0.003 CAL

Dimethyl formamide 68122 0.03 IRIS - M

Methyl isobutyl ketone 108101 3 IRIS - L/M

4,4'-Methylene diphenyl diisocyanate 101688 0.0006 IRIS - M

Propylene oxide 75569 0.03 IRIS - M

2,4-Toluene diisocyanate 584849 0.00007 IRIS - M

Toluene 108883 5 IRIS - H

Trichloroethylene 79016 0.002 IRIS - H

Xylenes (mixed) 1330207 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 

HAPs [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 

(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 HAPs can be 

found in an EPA document [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 

 13 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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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 

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 
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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/insideaiha/GuidelineDevelopment/ERPG/Pages/default.aspx) 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.”

The emissions inventory for the Wool Fiberglass Manufacturing and for the Mineral Wool 

Production source categories includes emissions of 9 HAP with relevant and available 

quantitative acute dose-response threshold values. These HAPs, their acute threshold values, 

and the source of the value are listed below in Table 2.6-2.
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Table 2.6-2 Dose-Response Values for Acute Exposure

Pollutant

CAS 

Number

AEGL-1

(1-hr)

(mg/m3)

AEGL-2

(1-hr)

(mg/m3)

ERPG-1

(mg/m3)

ERPG-2

(mg/m3) REL 

Dimethyl formamide 68122 270 6 300

4,4-Methylene diphenyl diisocyanate 101688 5

Propylene oxide 75569 170 690 120 590 3.1

Toluene 108883 750 4500 190 1100 37

2,4-Toluene diisocyanate 584849 0.14 0.59 0.071 1.1

Trichloroethylene 79016 700 2400 540 2700

Xylenes (mixed) 1330207 560 4000 22

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 Analysis14, 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.

 14Memorandum 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/omb/assets/omb/memoranda/fy2007/m07-24.pdf)
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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 HAPs 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 HAPs 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 

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. 
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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.

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 HAPs 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 HAPs 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 
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basis, not using the TOSHI approach.

3 Risk Results 

3.1 Source Category Description and Results

The FPUF Production MACT standards apply to each new and existing flexible polyurethane 

foam or rebond foam process that produces flexible polyurethane foam or rebond foam, emits 

HAP, and is located at a contiguous, major source plant site. There are three types of FPUF 

producers in the source category: slabstock, molded and rebond. Slabstock foam is produced 

in large continuous buns that are then cut into the desired size and shape. Slabstock foam 

products are primarily used in furniture seat cushions and bedding materials. Molded foam is 

produced by "shooting" the foam mixture into a mold of the desired shape and size. Molded 

foam is typically used in automotive seats, packaging and a range of specialty products. 

Rebond foam is made from scrap foam that is converted into a material primarily used for 

carpet underlay. Rebond foam production is often co-located with slabstock foam production 

facilities.

There are 13 FPUF production facilities subject to the MACT standards: 7 slabstock, 6 

molded and 2 rebond. One rebond facility is co-located with a slabstock facility, and the other 

rebond facility is co-located with a molded foam facility.

Table 3.1-1 summarizes the emissions for the Flexible Polyurethane Foam Production source 

category. Based on these data, the HAP emitted in largest quantities in total from these 

facilities are 2,4-toluene diisocyante, propylene oxide, and toluene; emissions of these 3

pollutants account for 93 percent of the total HAP emissions by mass from the data set. 

No PB HAP emissions are reported in the data set for the source category. 

The HAP emission points at FPUF production facilities depend on the type of foam being 

produced. HAP emissions points for slabstock foam facilities include the foam production 

line, storage vessels, and equipment leaks. At molded and rebond foam facilities, the primary 

HAP emission points are storage vessels and equipment leaks.
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Table 3.1-1 Summary of Emissions from the Flexible Polyurethane Foam Production Category and 

Availability of Dose-Response Values

HAP Emissions 

(tpy)

Number 

of 

Facilities 

Reporting 

HAP (7 

facilities 

in data 

set) 

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSa

PBUnit Risk HAP?

Estimate for 

Cancer?

Reference 

Concentration 

for Noncancer?

Health 

Benchmark 

Values for Acute 

Noncancer?

2,4-toluene Diisocyanate 0.6 9    

Propylene Oxide 0.2 1    

Toluene 0.08 1   

Methyl Isobutyl Ketone 0.03 1  

Methylene Diphenyl 

Diisocyanate 0.02 7   

Xylenes (mixed) 0.01 1   

Trichloroethylene 0.01 1    

Diethanolamine 0.0004 1  

Dimethyl Formamide 0.0001 1   

a Tables 2.6-1 (a) and (b) of this report contain the URE and RfC values for the HAP emitted from Flexible Polyurethane 

Foam Production facilities. Table 2.6-2 of this report contains the acute noncancer values for the HAP emitted from Flexible 

Polyurethane Foam Production facilities. 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 Flexible Polyurethane Foam

Production source category. 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 noninhalation risks from PB HAP, as applicable. 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.

Tables 3.2-1 and 3.2-2 summarize the chronic and acute inhalation risk results for this source 

category. The results for the Flexible Polyurethane Foam Production source category indicate 

that maximum lifetime individual cancer risks could be up to 0.7 in a million, based on actual 

emissions. The major contributor to this risk is 2,4-Toluene diisocyanate. There were no 

cancer risks above 1 in a million based on actual emissions. The maximum chronic noncancer TOSHI value for the source category could be up to 0.9 with emissions of 2,4-toluene 

diisocyanate dominating those impacts, indicating no significant potential for chronic 

noncancer impacts. 
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Worst-case screening acute hazard quotients (HQs) were calculated for every HAP shown in 

Table 3.1-1 that has an acute benchmark, and the highest acute HQ (ERPG-1 of 0.9 for 2,4-

toluen diisocyanate) is shown in Table 3.2-1. The default emissions multiplier of 10 was used 

to estimate the peak hourly emission rates from the average rates. There were no facilities 

with an acute HQ above 1. 

Chronic noncancer target organ specific hazard indices (HIs) were calculated for every HAP 

shown in Table 3.1-1 that has a chronic benchmark, and the highest target organ specific HI 

(0.9 for 2,4-toluene diisocyanate) is shown in Table 3.2-1. There were no HIs greater than 1 

for this source category. 

We conducted a screening-level evaluation of the potential human health risks associated with 

emissions of PB HAP. There were no reported emissions of PB HAP from facilities in the 

source category. 15 

In order to estimate the risk from each type of emission point (e.g., slabstock tanks), each 

emission point was assigned to an emission point type. Table 3.2-3 presents the maximum 

individual lifetime cancer risk, population exposure, and incidence from each modeled 

emission point type.

We determined that MACT-allowable HAP ABA emissions levels at slabstock production 

facilities are greater than actual HAP ABA emissions, while allowable emissions from all 

other processes are equal to actual emissions. The inhalation risk modeling using MACTallowable HAP ABA emissions and the actual emissions for the other processes at slabstock 

production facilities, indicate that the maximum lifetime individual cancer risk could be up to

5-in-1 million, the maximum chronic non-cancer TOSHI value could be up to 0.9, and the 

maximum off-facility site acute HQ value could be up to 4, based on the REL value for 

methylene chloride. The total estimated national cancer incidence from these facilities based 

on the MACT-allowable emission levels is 0.0004 excess cancer cases per year or one case in 

every 2,500 years.

The facility-wide MIR and TOSHI are based on actual emissions from all emissions sources 

at the identified facilities. The results indicate that 3 facilities have a facility-wide cancer MIR 

greater than or equal to 1-in-1 million. The maximum facility-wide MIR is 20-in-1 million, 

with the FPUF production source category contributing less than 10 percent of the risk. The 

maximum facility-wide TOSHI is 0.9, with the FPUF production source category contributing 

100 percent to the facility-wide TOSHI.

 15 ICF International. TRIM-Based Multipathway Screening Scenario. Prepared for U.S. Environmental 

Protection Agency, Research Triangle Park, NC. October 2008.
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Table 3.2-1 Summary of Source Category Level Inhalation Risks for Flexible 

Polyurethane Foam Production

Result HAP 

“Drivers”

Facilities in Source Category

Number of Facilities Estimated to be in Source Category 13 n/a

Number of Facilities Identified in the NEI and Modeled in Preliminary 

Risk Assessment 13 n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 1 million) 0.7 2,4-toluene 

diisocyanate

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 0 n/a

Chronic Noncancer Risks

Maximum Hazard Index 0.9 2,4-toluene 

diisocyanate

Number of Facilities with Maximum Respiratory Hazard Index:

Greater than 1 0 n/a

Refined Acute Noncancer Screening Results

Maximum Acute Hazard Quotient [using scaling factor of 10] 0.9 2,4-toluene diisocyanate

(ERPG-1)

Number of Facilities With Potential for Acute Effects 0 n/a

Population Exposure

Number of People Living Within 50 Kilometers of Facilities Modeled 10,400,000 n/a

Number of People Exposed to 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 0 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) 0.00004 n/a

Contribution of HAP to Cancer Incidence:

 2,4-toluene diisocyanate

 Propylene oxide

 Trichloroethylene

94%

4%

2%

n/a
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Table 3.2-2 Summary of Refined Acute Results for Flexible Polyurethane Foam

Production Facilities 

Refined Results

MAXIMUM ACUTE HAZARD 

QUOTIENTS

ACUTE DOSE-RESPONSE VALUES

Based 

on 

REL

Based on 

AEGL-1/

ERPG-1

Based on 

AEGL-2/

ERPG-2

REL

(mg/m3

)

AEGL-1 (1-hr) 

(mg/m3)

ERPG-1 

(mg/m3)

AEGL-2

(1-hr)(mg/m3)

ERPG-2 

(mg/m3 HAP Max. 1 ) -hr. 

Air Conc. 

(mg/m3

)

2,4-toluene 

diisocyanate 0.06 - 0.4/0.9 0.1/0.06 - 0.14 0.071 0.59 1.1

Notes on Refined Process:

1) The screening was performed for all emitted HAP with available acute dose-response values. Only those pollutants whose 

screening HQs were greater than 1 for at least one acute threshold value are shown in the table.

2) HAP with available acute dose-response values which are not in the table do not carry any potential for posing acute health risks, 

based on an analysis of currently available emissions data.

Notes on Acute Dose-Response Values:

REL – California EPA reference exposure level for no adverse effects. Most, but not all, RELs are for 1-hour exposures.

AEGL – Acute exposure guideline levels represent emergency exposure (1-hour) limits for the general public.

AEGL-1 is the exposure level above which it is predicted that the general population, including susceptible individuals, could 

experience effects that are notable discomfort, but which are transient and reversible upon cessation of exposure.

AEGL-2 is the exposure level above which it is predicted that the general population, including susceptible individuals, could 

experience irreversible or other serious, long-lasting adverse health effects of an impaired ability to escape.

ERPG – Emergency Removal Program guidelines represent emergency exposure (1-hour) limits for the general public.

ERPG-1 is the maximum level 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.

ERPG-2 is the maximum exposure 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.

Table 3.2-3. Cancer Risk Estimates by Emission Point Type for the Flexible Polyurethane 

Foam Production Source Category

Maximum Overall Slabstock Process Emissions Slabstock Tanks Molded Foam 

Emissions

Cancer Risk due to Emission Point Type:

Maximum (in 1 

million) 0.7 0.7 0.05 0.004

Population Exposure due to Emission Point Type:

>= 100 in 1 million 0 0 0 0

>= 10 in 1 million 0 0 0 0

>= 1 in 1 million 0 0 0 0

Incidence due to 

Emission Point Type:

0.00004 0.00003 0.000001 0.0000008

Sm Slabstock 

Process Emissions Sm Slabstock Tanks

Cancer Risk due to Emission Point Type:

Maximum (in 1 

million) 0.0005 0.0001

Population Exposure due to Emission Point Type:

>= 100 in 1 million 0 0

>= 10 in 1 million 0 0

>= 1 in 1 million 0 0

Incidence due to 

Emission Point Type:

0.0000002 0.000000006
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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 

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. 
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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 (<24 hours), short-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 HAPs

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, 

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 
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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).16 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.17 

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.18 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, 

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 

 16 IRIS glossary (www.epa.gov/NCEA/iris/help_gloss.htm). 17 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. 18 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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tumors would occur in humans.19 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), 

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 

 19 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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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.

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 
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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 values20 e.g., factors of 10 or 3, 

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. 

 20 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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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.21 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 

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.

 21 See IRIS glossary
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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 

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 
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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 

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 
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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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27. US EPA, 2005. Science Policy Council Cancer Guidelines Implementation Workgroup 

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Trichloroethylene. National Academies Press, Washington DC.

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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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