1

 Residual Risk Assessment for the Wood Furniture 

Manufacturing Source Category 

by 

EPA’s Office of Air Quality Planning and Standards 

Office of Air and Radiation 

August 2011 
2

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 ....................................................... 8 

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

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

2.6.1 Sources of chronic dose-response information ................................................ 11 

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

2.7 Risk Characterization ............................................................................................... 21 

2.7.1 General ............................................................................................................. 21 

2.7.2 Mixtures ........................................................................................................... 23 

2.7.3 Facility-wide Risks .......................................................................................... 24 

3 Risk Results for the Wood Furniture Manufacturing Source Category ....................... 24 

3.1 Source Category Descriptions and Results .............................................................. 24 

3.2 Risk Characterization ............................................................................................... 28 

4 General Discussion of Uncertainties and How They Have Been Addressed................... 35 

4.1 Exposure Modeling Uncertainties ............................................................................ 35 

4.2 Uncertainties in the Dose-Response Relationships .................................................. 36 

5 References ........................................................................................................................ 44 

Index of Tables 

Table 2.2-1 AERMOD version 09292 model options for RTR II modeling ............................ 6 

Table 2.6-1 (a) Dose-Response Values for Chronic Inhalation Exposure to Carcinogens ..... 14 

Table 2.6-1 (b) Dose-Response Values for Chronic Oral Exposure to Carcinogens .............. 15 

Table 2.6-1 (c) Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens 15 

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

Table 3.1-1 Summary of Emissions from the Wood Furniture Manufacturing Source 

Category and Availability of Dose-Response Values .............................................................. 25 

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

Manufacturing Facilities .......................................................................................................... 29 

Table 3.2-2: Summary of NPRM Acute Refined Results for Wood Furniture Manufacturing 

Facilities ................................................................................................................................... 30 

Table 3.2-3 Wood Furniture Source Category Contribution to Facility-Wide Cancer Risks . 35 
3

Appendices 

Appendix 1 Emissions Inventory Support Memorandum 

Appendix 2 Technical Support Document for HEM-AERMOD Modeling 

Appendix 3 Meteorological Data for HEM-AERMOD Modeling 

Appendix 4 Analysis of Data on Short-Term Emission Rates Relative to Long-Term 

Emission Rates 

Appendix 5 TRIM-Based Multipathway Screening Scenario 

Appendix 6 Detailed Risk Modeling Results (Source Category and Facility-wide) 

Appendix 7 Refined Acute Assessments 

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 

HEAST Health Health Effects Assessment Summary Table 

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 

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
4

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) Risk Assessment Methodologies” [2]. We received the final SAB 

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

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

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

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

recommendations of the SAB are outlined in a memo to this rulemaking docket [4]. 

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

implementation of the respective MACT standards) performed for the Wood Furniture 

Manufacturing source category. The methods discussion includes descriptions of the methods 

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

cancer and non-cancer endpoints, as well as descriptions of the methods used to screen for 

acute health risks, chronic non-inhalation health risks, and adverse environmental effects. 

Since none of the screening assessments indicated any significant potential for chronic noninhalation health effects or environmental impacts, including effects to threatened and 

endangered species, no further refinement of these assessments was performed. 
5

2 Methods 

2.1 Emissions and source data 

The 2005 National-Scale Air Toxics Assessment (NATA) National Emissions Inventory 

(NEI) served as the starting point for this assessment. The 2005 NEI contains information on 

actual emissions during the entire 2005 base year. Using the process MACT codes1

, we 

developed a subset of this inventory that contains emissions and facility data for the source 

category. Next, we performed an engineering review of the information using EPA engineers 

who were directly involved in the development of the MACT standards for the source 

category, and/or who have extensive knowledge of the characteristics of this industry. NEI 

data were updated with available industry supplied data. The goal of the engineering review 

was to identify limitations and issues with the emissions data (particularly those that would 

have the potential to influence risk estimates) and to make changes to the data where possible 

to address these issues and decrease the uncertainties associated with the assessment. 

 

Details on the development of the emissions and source data for this source category are 

discussed in Section 3. The emissions data and modifications made to the NEI data are 

discussed in Appendix 1, entitled “Emissions Inventory Support Memorandum.” 

2.2 Dispersion modeling for inhalation exposure assessment 

Both long- and short-term inhalation exposure concentrations and associated health risks 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 

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

system is outlined below, and further details are provided in Appendix 2. HEM-AERMOD 

performs three main operations: atmospheric dispersion modeling, estimation of individual 

human exposures and health risks, and estimation of population risks. This section focuses on 

the dispersion modeling component. The exposure and risk characterization components are 

discussed in other subsections of Sections 2 and 3. 

The dispersion model in the HEM-AERMOD system, AERMOD version 09292, is a state-ofthe-science 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. 

 

1

 The tagging of data with MACT codes allows EPA to determine reductions attributable to the MACT program. 

The NEI associates MACT codes corresponding to MACT source categories with stationary major and area 

source data. MACT codes may be assigned either at the process level or at the site level in the point source data 

(e.g., the MACT code for municipal waste combustors (MWCs) is assigned at the site level whereas the MACT 

code for petroleum refinery catalytic cracking is assigned at the process level). 
6

The first step in the application of the HEM-AERMOD 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 09292 model options for RTR II modeling 

Modeling Option Selected Parameter for chronic exposure 

Type of calculations Hourly ambient concentration 

Source type Point, area represented as pseudo point source 

Receptor orientation Polar (13 rings and 16 radials) 

Discrete (census block centroids) 

Terrain characterization Actual from USGS 1-degree DEM data 

Building downwash Not Included 

Plume deposition/depletion Not Included 

Urban source option No 

Meteorology 1 year representative NWS from nearest site (158 stations) 

In HEM-AERMOD, meteorological data are ordinarily selected from a list of 158 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 1991. 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 40 miles (72 km). Appendix 3 (Meteorological Data 

Processing Using AERMET for HEM-AERMOD) provides a complete listing of stations and 

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 HEM-AERMOD model estimates ambient concentrations at the geographic centroids of 

census blocks (using the 2000 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 
7

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 NEI contains only annual emission totals, we generally apply the assumption to all 

source categories that the maximum one-hour emission rate from any source was ten times the 

average annual hourly emission rate for that source. For the wood furniture source category, 

we applied an hourly emission factor of 4(x) the annual average emission rate based upon an 

engineering review of all the emission production processes for each pollutant. Rationale for 

this acute emissions factor is documented in a memo to the rulemaking docket [7]. 

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. This choice of a factor of ten for 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)[8]. In that 

report, the Texas Environmental Research Consortium Project compared hourly and annual 

emissions data for volatile organic compounds for all facilities in a heavily-industrialized 4-

county area (Harris, Galveston, Chambers, and Brazoria Counties, 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, and the 

highest was a factor of 11 times the annual average. Based on these results, we chose the 

factor of ten for all initial acute screening; it is intended to cover routinely-variable emissions 

as well as startup, shutdown, and malfunction (SSM) emissions. While there have been some 

documented emission excursions above this level, our analysis of the data from the Texas 

Environmental Research Consortium suggests that this factor should cover more than 99% of 

the short-term peak gaseous or volatile HAP emissions from typical industrial sources. 

Census block elevations for HEM-AERMOD modeling were determined nationally from the 

US Geological Service 1-degree digital elevation model (DEM) data files, which have a 

spatial resolution of about 90 meters. Elevations of polar grid points used in estimating shortand 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 
8

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 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 

1996, 1999, 2002 and 2005 NATA assessments [9] (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 HAPs; it will also reduce risk estimates for gaseous 

HAPs, 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 biasing the risk 

estimates high. 

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 is used for 

developing chronic health risk assessments under the residual risk program. That is, we 
9

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 acute health 

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

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 would be needed to refine the 

assessment; in others, lesser amounts of site-specific data could be used to determine that 

acute exposures are not a concern, and significant additional data collection would not be 

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 exposure 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, was used for simulating atmospheric dispersion. 

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

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

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

chemical 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. In some cases, this includes 

use of a refined emissions multiplier to estimate the peak hourly emission rates from the 

average rates. In this case as mentioned earlier in section 2.2, our industry experts have 

advised us that a refined emissions multiplier of 4 should be used to cover routine variations 

in process emissions. We also conducted a review of the layout of emission points at the 
10

facility with the facility boundaries to determine the maximum off-site acute impact for the 

facilities that did not screen out during the initial model run. Refer to Appendix 7 for the 

detailed results for these sites. 

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 [10]. Examples of PBHAP are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, 

heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury 

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

toxaphene, and trifluralin. Emissions of 3 different PB HAP were identified in the emissions 

inventory for the Wood Furniture Manufacturing source category; they are POM, lead, and 

cadmium. These emissions were evaluated for potential non-inhalation risks and adverse 

environmental impacts using our recently-developed 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 thresholds developed for screening potentially 

significant multi-pathway impacts. For the purpose of developing emissions thresholds 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 an emissions screening threshold, we 

compared maximum estimated chronic (3-month average) atmospheric concentrations with 

the current National Ambient Air Quality Standard (NAAQS) for lead. Values below the 

NAAQS were considered to have a low potential for multi-pathway risks of any significance. 

Additionally, we evaluated the potential for significant ecological exposures to non PB-HAP 

from exceedances of chronic human health inhalation thresholds in the ambient air near these 

facilities. Human health dose-response threshold values are generally derived from studies 

conducted on laboratory animals (such as rodents) and developed with the inclusions of 

uncertainty factors that could be as high as 3000. As a result, these human threshold values 

 

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 
11

are often significantly lower than the level expected to cause an adverse effect in an exposed 

rodent. It should be noted that there is a scarcity of data on the direct atmospheric impact of 

these HAPs on other receptors, such as plants, birds, and wildlife. Thus, if the maximum 

inhalation hazard in an ecosystem is below the level of concern for humans, we have 

generally concluded that mammalian receptors should be at no risk of adverse effects due to 

inhalation exposures from non PB-HAP, and have assurance that other ecological receptors 

are also not at any significant risk from direct atmospheric impact. In some isolated cases 

where we have data indicating potential adverse impacts on plants, birds, or other wildlife due 

to the direct atmospheric impacts of specific HAPs, we note that as an uncertainty and, where 

possible, refine our analysis by comparing our modeled impacts to available threshold values 

from the scientific literature. 

2.6 Dose-Response Assessment 

2.6.1 Sources of chronic dose-response information 

Dose-response assessment information (carcinogenic and non-carcinogenic) for chronic 

exposure (either by inhalation or ingestion) for the HAPs reported in the emissions inventory 

for Wood Furniture Manufacturing sources is based on the EPA Office of Air Quality 

Planning and Standards’ existing recommendations for HAPs, also used for NATA 1999, 

2002, and 2005 [11]. 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 incorporatin

our assessments the best available science with respect to dose-response information. T

recommendations are based on the following sources, in order of priority: 

g into 

he 

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

Integrated Risk Information System (IRIS) [12] 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 o

federal agencies, and the public, and peer review by independent scientists external to

EPA. EPA’s science policy approach, under the current carcinogen guidelines, is to use 

ther 
12

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 assessme

to identify nonlinear MOAs where appropriate, and we will use those analyses (once they 

are peer reviewed) in our risk assessments. At this time, however, there are no availab

carcinogen dose-response assessments for inhalation exposure that are based on a 

nonlinear MOA.

nts 

le 

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) [13] 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 [14] and NAS [15].” The non-cancer information 

includes available inhalation health risk guidance values expressed as chronic inhalation 

reference exposure levels (RELs) [16]. 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 [17], 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 

 

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) 
13

 dose- response values may pose an unacceptable risk and require further examination, or 

 screen out from further assessment. 

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

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

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

 category. 

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

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

 science than the IRIS 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. 

 Based on subsequent, published research, however EPA changed its determination 

 regarding the CIIT model, and in 2010 EPA returned to using 1991 IRIS value. The 

 National Academy of Sciences (NAS) completed its review of the EPA’s draft 

 assessment in April of 2011 (http://www.nap.edu/catalog.php?record_id=13142), and 

 EPA has been working on revising the formaldehyde assessment. The EPA will follow 

 the NAS Report recommendations and will present results obtained by implementing the 

 biologically based dose response (BBDR) model for formaldehyde. The 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. In the interim, we will present findings 

 using the 1991 IRIS value as a primary estimate, and may also consider other information 

 as the science evolves. 

 4) The IRIS URE for nickel inhalation was derived from evidence of the carcinogenic effects 

 of insoluble nickel compounds in crystalline form. Soluble nickel species, and insoluble 

 species in amorphous form, do not appear to produce genotoxic effects by the same toxic 

 mode of action as insoluble crystalline nickel. Nickel speciation information for some of 

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

 others) suggests that at least 35% of total nickel emissions may be soluble compounds. 

 The remaining insoluble nickel emissions are not well-characterized. Consistent with this 

 limited information, this assessment will conservatively assume that 65% of emitted 

 nickel is insoluble and that all insoluble nickel is crystalline. The nickel URE (based on 

 nickel subsulfide, and representative of pure insoluble crystalline nickel) was adjusted to 

 reflect an assumption that 65% of the total mass of nickel may be carcinogenic. The 

 noncancer dose-response values were not adjusted because noncancer effects of nickel 

 are not thought to be limited to the crystalline, insoluble form. 

 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 were used for the 1999 NATA study [18]. 

 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. 
14

The emissions inventory for the wood furniture manufacturing source category includes 

emissions of 49 HAP with available quantitative chronic inhalation dose-response values. 

These HAP, their dose-response values, and the source of the values are listed in Tables 2.6-1 

(a) through (c). 

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

URE (unit risk estimate for cancer)5 = 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, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality 

Planning and Standards.

Pollutant CAS 

Number6

URE5

 (1/μg/m3) 

Source 

Acetaldehyde 75070 2.2E-06 IRIS 

Acrylonitrile 107131 6.8E-05 IRIS 

Arsenic compounds 174 4.3E-03 IRIS 

Benzene7 71432 7.8E-06 IRIS 

Beryllium compounds 175 2.4E-03 IRIS 

Benzyl chloride 100447 4.9E-05 CAL 

Bis(2-Ethylhexyl)phthalate 117817 2.4E-06 CAL 

Cadmium compounds 7440439 1.8E-03 IRIS 

p-Dichlorobenzene 106467 1.1E-05 CAL 

1,4-Dioxane 123911 7.7E-06 CAL 

Ethyl benzene 100414 2.5E-6 CAL 

Formaldehyde8 50000 1.3E-05 IRIS 

Methylene chloride 75092 4.7E-07 IRIS 

Naphthalene 91203 3.4E-05 CAL 

Nickel compounds 186 4.8E-04 IRIS 

Polycyclic Organic Matter 246 9

 - Benzo(a)anthracene 56553 1.1E-04 CAL 

 - Benzo(a)pyrene 50328 1.1E-03 CAL 

 - Benzo(b)fluoranthene 205992 1.1E-04 CAL 

 - Benzo(k)fluoranthene 207089 1.1E-04 CAL 

 

5

 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. 

6

 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. 7

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

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

. 8

 The EPA has used the CITT URE value, 5.5x10-9 per mg/m3 to characterize formaldehyde cancer risk in some 

 Instances. 

9

 Assigned the URE associated with a mixture of POM compounds having a similar potency. Details of this 

method, also used in the 1999 National Air Toxics Assessment, are available at 

http://www.epa.gov/ttn/atw/nata1999/99pdfs/pomapproachjan.pdf

 
15

 - Chrysene 218019 1.1E-05 CAL 

 - Dibenzo(a,h)anthracene 53703 1.2E-03 CAL 

 - Indeno(1,2,3-cd)pyrene 193395 1.1E-04 CAL 

Propylene Oxide 75569 3.7E-6 IRIS 

2,4-Toluene Diisocyanate 26471625 1.1E-05 CAL 

Trichloroethylene 79016 2.0E-06 CAL 

Vinyl Chloride 75014 8.8E-06 IRIS 

Table 2.6-1 (b) Dose-Response Values for Chronic Oral Exposure to Carcinogens 

SF (oral slope factor for cancer) = cancer risk per mg/kg/d of average lifetime exposure. Sources: IRIS = EPA 

Integrated Risk Information System, CAL = California EPA Office of Environmental Health Hazard Assessment, 

EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards. 

Pollutant CAS Number10

SF 

(1/mg/kg/d) Source 

Polycyclic organic matter (POM) 246 0.5 

 - Benzo(a)anthracene 56553 1 CAL 

 - Benzo(a)pyrene 50328 7 CAL 

 - Benzo(b)fluoranthene 205992 1 CAL 

 - Benzo(k)fluoranthene 207089 1 CAL 

 - Chrysene 218019 0.1 CAL 

 - Dibenz(a,h)anthracene 53703 4 CAL 

 - Indeno(1,2,3-cd)pyrene 193395 1 CAL 

Table 2.6-1 (c) 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 = Agency for Toxic Substances Disease Registry. 

Pollutant CAS Number

6 RfC 

(mg/m3)

Source10

Acetaldehyde 75070 0.009 IRIS -- L

Acrylonitrile 107131 0.002 IRIS - M

Acrylic acid 79107 0.001 IRIS - M

Arsenic compounds 174 0.000015 CAL

Benzene 71432 0.03 IRIS – M

Cadmium compounds 176 0.00001 ATSDR

Chlorobenzene 108907 1 CAL

Cresols (mixed)11 95487 0.6 CAL

Cyanide compounds12 180 0.003 IRIS - H

 

10 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 the IRIS file. 

11 Cresols (mixed) includes all isomers (ortho, meta, and para) 12 The value for hydrogen cyanide was used as a surrogate for all cyanide compounds 
16

Table 2.6-1 (c) 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 = Agency for Toxic Substances Disease Registry. 

Pollutant CAS Number6 RfC 

(mg/m3) 

Source10

p-Dichlorobenzene 106467 0.8 IRIS – M

Diethanolamine 111422 0.003 CAL

1,4-Dioxane 123911 3.6 ATSDR

Ethyl benzene 100414 1 IRIS – L

Ethylene glycol 107211 0.4 CAL

Formaldehyde 13 50000 0.0098 ATSDR

Glycol ethers 14 181 0.02 IRIS – M

 - Diethylene glycol monobutyl ether (DGBE) * 112345 0.02 

 - Diethylene glycol monomethyl ether (DGME) * 111773 0.02 

 - Ethyl glycol ethyl ether 110805 0.2 IRIS - M

 - Ethylene glycol methyl ether (EGME) 109864 0.02 IRIS - M

 - 2-Butoxyethyl acetate * 112072 0.02 

 - Ethylene glycol ethyl ether acetate 111159 0.3 CAL

 - Butyl carbitol acetate * 124174 0.02 

 - Triethylene glycol * 112276 0.02 

 - Diethylene Glycol Monoethyl Ether * 111-90-0 0.02 

 - Phenyl Cellosolve * 122996 0.02 

 - Propyl Cellosolve * 2807309 0.02 

Hexamethylene-1,6-diisocyanate 822060 0.00001 IRIS - L

n-Hexane 110543 0.7 IRIS – M

Hydrochloric acid 7647010 0.02 IRIS – L

Hydrogen cyanide 74908 0.003 IRIS - L

Lead and compounds 182 0.00015 EPA OAQPS

Maleic anhydride 108316 0.0007 CAL

Manganese compounds 183 0.00005 IRIS - H

Methanol 67561 4 CAL

4,4’-Methylenediphenyl diisocyanate 101686 0.0006 IRIS - M

Methyl isobutyl ketone 108101 3 IRIS – L/M

Methylene chloride 75092 1 ATSDR

Methyl methacrylate 80626 0.7 IRIS - L

Naphthalene 91203 0.003 IRIS – M

Nickel compounds 186 0.00009 ATSDR

Phenol 108952 0.2 CAL

Propylene oxide 75569 0.03 IRIS - M

 

14 The RfC value for ethylene glycol methyl ether was used as a surrogate for all glycol ethers without an RfC; 

 (denoted with an * ). 
17

Table 2.6-1 (c) 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 = Agency for Toxic Substances Disease Registry. 

Pollutant CAS Number6 RfC 

(mg/m3) 

Source10

Selenium compounds 7782492 0.02 CAL

Styrene 100425 1 IRIS – M

Toluene 108883 5 IRIS – H

2,4-Toluene diisocyanate 26471625 0.00007 IRIS - M

1,1,1-Trichloroethane 71556 5 IRIS - M

Trichloroethylene 79016 0.6 CAL

Triethylamine 121448 0.007 IRIS - L

Vinyl acetate 108054 0.2 IRIS – H

Vinyl chloride 75014 0.1 IRIS - H

Xylenes (mixed) 1330207 0.1 IRIS – M

m-Xylene15 108383 0.1 IRIS – M

o-Xylene13 95476 0.1 IRIS – M

p-Xylene13 106423 0.1 IRIS – M

2.6.2 Sources of acute dose-response information 

Hazard identification and dose-response assessment information for the preliminary acute 

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

HAPs [19]. 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 a newly released EPA document (Reference: U.S. EPA. Graphical Arrays of 

Chemical-Specific Health Effect Reference Values for Inhalation Exposures [Final Report]. 

U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R-09/061, 2009. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003.) 

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). 

 

15 The RfC for mixed xylene was used as a surrogate. 
18

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

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

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

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

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

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

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

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

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

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

developed chronic RELs). 

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

Committee 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 
19

irritation or certain asymptomatic, nonsensory effects. With increasing airborne 

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

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

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

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

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

responses, could experience the effects described at concentrations below the 

corresponding AEGL.” 

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

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

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

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

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

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

ERPG values (http://www.aiha.org/1documents/Committees/ERP-erpglevels.pdf) are 

described in their supporting documentation as follows: “Emergency Response Planning 

Guidelines (ERPGs) were developed for emergency planning and are intended as health based 

guideline concentrations for single exposures to chemicals. These guidelines (i.e., the ERPG 

Documents and ERPG values) are intended for use as planning tools for assessing the 

adequacy of accident prevention and emergency response plans, including transportation 

emergency planning and for developing community emergency response plans. The emphasis 

is on ERPGs as planning values: When an actual chemical emergency occurs there is seldom 

time to measure airborne concentrations and then to take action.” 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 wood furniture manufacturing source category includes 

emissions of 53 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. 
20

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) 

ERPG1 

(mg/m3) 

ERPG2 

(mg/m3) REL 

1,1,1-Trichloroethane 71556 1300 3300 1900 3800 68 

1,2-Epoxybutane 106887 210 410 

1,4-Dioxane 123911 61 1200 3 

2,4-Toluene diisocyanate 584849 0.14 0.59 0.071 1.1 

4,4’-Methylenediphenyl 

diisocyanate 101688 5 

Acetaldehyde 75070 81 490 18 360 0.47 

Acrylic acid 79107 4.4 140 3 150 6 

Acrylonitrile 107131 10 130 22 77 

Arsenic compounds 7440382 0.0002 

Benzyl chloride 100447 5.2 52 0.24 

Benzene 71432 170 2600 160 480 1.3 

Beryllium compounds 7440417 0.025 

Chlorobenzene 108907 46 690 

Cumene 98828 250 1500 

Cyanide compounds 57125 2.2 7.8 11 

Ethyl acrylate 140885 34 150 0.041 120 

Ethyl Benzene 100414 140 4800 

Formaldehyde 50000 1.1 17 1.2 12 0.055 

Glycol ethers16 

 Ethylene glycol methyl 

 ether 109864 0.093 

 - 2- butoxyethyl acetate * 112072 0.093 

 - Butyl carbitol acetate * 124174 0.093 

 - Diethylene glycol monobutyl 

 ether * 112345 0.093 

 - Diethylene glycol monoethyl 

 ether * 111900 0.093 

 - Diethylene glycol 

 monomethyl ether * 111773 0.093 

 - Ethyl Glycol 2- 

 ethoxyethanol 110805 0.37 

 - Ethylene glycol ethyl ether 

 acetate 111159 0.14 

 - Triethylene glycol * 112276 0.093 

 - Phenyl cellosolve * 122996 0.093 

 - Propyl cellosolve * 2807309 0.093 

Hexane 110543 12000 

Hydrochloric acid 7647010 2.7 33 4.5 30 2.1 

Hydrogen cyanide 74908 2.2 7.8 11 0.34 

 

16 The acute REL for ethylene glycol methyl ether (EGME) was used as a surrogate for all glycol ethers without 

 an acute REL; (denoted with an * ). 
21

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) 

ERPG1 

(mg/m3) 

ERPG2 

(mg/m3) REL 

Maleic anhydride 108316 0.8 8 

Methanol 67561 690 2700 260 1300 28 

Methyl methacrylate 80626 70 490 

Methylene chloride 75092 690 1900 1000 2600 14 

Nickel compounds 7440020 0.006 

Phenol 108952 58 89 38 190 5.8 

Propylene oxide 75569 170 690 120 590 3.1 

Styrene 100425 85 550 210 1100 21 

Toluene 108883 750 4500 190 1100 37 

Trichloroethylene 79016 700 2400 540 2700 

Triethylamine 121448 2.8 

Vinyl acetate 108054 24 630 18 260 

Vinyl chloride 75014 640 3100 1300 13000 180 

Xylenes (mixed) 1330207 560 4000 22 

 - m-Xylene 108383 22 

 - p-Xylene 106423 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 Analysis17, and 

are incorporated in these assessments. 

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

 

17Memorandum 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/omb/memoranda/fy2007/m07-24.pdf) 
22

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 non-cancer hazards, as well as cancer 

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

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

limitations. 

For each carcinogenic HAP included in an 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” 
23

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

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

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

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

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

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

this on possible health interpretations. 

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

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

RfCs incorporate generally conservative uncertainty factors in the face of uncertain 

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

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

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

Screening for potentially significant acute inhalation exposures also follows 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 is 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 non-cancer 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 is 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 be underestimated. As with the HQ, 

the TOSHI should not be interpreted as a probability of adverse effects, or as strict delineation 
24

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

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

carefully by health scientists and risk managers. 

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

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

basis, not using the TOSHI approach. 

2.7.3 Facility-wide Risks 

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

the results of the 2005 NATA. For the facilities in these source categories, we extracted from 

the NATA results, based on facility ID, estimates of the maximum inhalation cancer and 

chronic non-cancer risks associated with all HAP emissions sources at the facility, including 

emissions sources that are not part of the source categories but that are located within a 

contiguous area and are under common control. We analyzed risks due to the inhalation of 

HAP for the populations residing within 50 kilometers of each facility. The results of these 

facility-wide assessments are summarized below in the Risk Characterization section of this 

document. The complete results of the facility-wide assessments are provided in Table 2 of 

Appendix 5. 

3 Risk Results for the Wood Furniture Manufacturing Source Category 

3.1 Source Category Descriptions and Results 

The wood furniture manufacturing source category includes facilities engaged in the 

manufacture of wood furniture or wood furniture components. The industry encompasses the 

application of any protective, decorative, or functional coating to wood furniture or wood 

furniture components. This source category includes wood kitchen cabinets, wood residential 

furniture, upholstered residential and office furniture, wood office furniture and fixtures, 

partitions, shelving, lockers, and other wood furniture not included in one of the above 

categories. Finishing, gluing, cleaning, and washoff operations are the four processes that 

take place during wood furniture manufacturing that result in HAP emissions and are covered 

in the MACT rule for this category. A complete description of the wood furniture 

manufacturing source category can be found in the text of the NPRM. 

We currently estimate that there are 405 wood furniture facilities operating in the U.S. The 

NPRM data set at proposal contained 385 facilities identified with a wood furniture 

manufacturing MACT code based upon the 2005 National-Scale Air Toxics Assessment 

(NATA) NEI. This was later changed to 384 facilities after we received comments from the 

proposal that one facility was not within the wood furniture MACT source category. This one 

facility listed also had the highest cancer risk for the source category. All references to this 

facility will be amended as well as any documents, attachments, and summaries concerning 

emissions and/or risk for this facility will be removed. While the NEI identifies 3 of these 384 

facilities as area sources of HAP (and 381 as major sources), the uncertainty associated with 

these major and area source classifications is considered significant. Without verification of 

the area source status of individual facilities, EPA will consider all facilities in the NEI to be 

major sources in this and any future RTR risk assessments. Two of these three facilities were 
25

major sources at the MACT compliance date and the third is a synthetic minor facility. All 

three facilities are treated as major sources in this assessment. 

The emissions for the wood furniture manufacturing source category NPRM data set (of 384 

facilities) are summarized in Table 3.1-1. The total HAP emissions for the source category 

are approximately 5,600 tons per year. Based on these data, the HAP emitted in largest 

quantities by the source category are: toluene, xylenes (mixed), 1,1,1-trichloroethane, 

methanol, ethyl benzene, methyl isobutyl ketone, hexane, methylene chloride, styrene, propyl 

cellosolve, diethylene glycol monobutyl ether, formaldehyde, and o-xylene. Emissions of 

these 13 HAP make up 99 percent of the total emissions by mass. Toluene was emitted in the 

largest quantity and is reported from 314 of the 384 facilities in the data set (82 percent). 

To estimate chronic and acute HQ values for 66 facilities reporting un-speciated emissions of 

glycol ethers, a speciation profile was developed based upon average speciation profiles from 

the 26 facilities that provided speciated emissions data. Rationale for this speciation profile is 

documented in a memo to the docket [30]. 

Persistent and bioaccumulative HAP (PB HAP)18 emissions reported in the data set for the 

wood furniture source category include lead, cadmium, and polycyclic organic matter. 

Table 3.1-1 Summary of Emissions from the Wood Furniture Manufacturing Source Category and 

Availability of Dose-Response Values 

HAPa Emissions 

(tpy) 

Number of 

Facilities 

Reporting HAP 

(384 facilities in 

NPRM data set) 

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate 

for Cancer? 

Reference 

Concentration 

for 

Noncancer? 

Health 

Benchmark 

Values for Acute 

Noncancer? 

Toluene 1,840 314 Υ Υ 

Xylenes (Mixture) 1,623 283 Υ Υ 

1,1,1-Trichloroethane 692 44 Υ Υ 

Methanol 544 211 Υ Υ 

Ethyl Benzene 236 184 Υ Υ

Methyl Isobutyl Ketone 222 158 Υ

Hexane 119 41 Υ Υ 

Methylene Chloride 72 20 Υ Υ Υ 

Styrene 51 23 Υ Υ 

Glycol Ethers 

Propyl Cellosolve 46 73 (S) (S) 

Diethylene Glycol 

Monobutyl Ether 20 73 (S) (S) 

Diethylene Glycol 

Monomethyl Ether 4 68 (S) (S) 

Butyl Carbitol Acetate 2 64 (S) (S) 

 

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

EPA-453K-04-001A, which is accessible from the EPA’s Technology Transfer Network website for Fate, 

Exposure, and Risk Assessment at http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 
26

Table 3.1-1 Summary of Emissions from the Wood Furniture Manufacturing Source Category and 

Availability of Dose-Response Values 

HAPa Emissions 

(tpy) 

Number of 

Facilities 

Reporting HAP 

(384 facilities in 

NPRM data set) 

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate 

for Cancer? 

Reference 

Concentration 

for 

Noncancer? 

Health 

Benchmark 

Values for Acute 

Noncancer? 

Cellosolve Solvent 2 70 Y Y 

Ethylene Glycol 

Monoethyl Ether 

Acetate 

1 68 Y Y 

2-Butoxyethyl Acetate 0.6 67 (S) (S) 

Diethylene Glycol 

Monoethyl Ether 0.4 67 (S) (S) 

Phenyl Cellosolve 0.2 66 (S) (S) 

Triethylene glycol 0.1 65 (S) (S) 

Formaldehyde 20 140 Υ Υ Υ 

o-Xylene 14 9 Υ Υ 

Methyl Methacrylate 12 7 Υ Υ 

Ethylene Glycol 10 35 Υ

Bis(2-Ethylhexyl)Phthalate 10 28 Υ Υ

Cumene 9 84 Υ Υ 

Dibutyl Phthalate 4 43 

Ethyl Acrylate 4 1 Υ 

Vinyl Acetate 3 42 Υ Υ 

Naphthalene 2 55 Υ Υ

m-Xylene 2 8 Υ Υ 

Chlorobenzene 1 1 Υ Υ 

Phenol 0.9 15 Υ Υ 

4,4'-Methylenediphenyl 

Diisocyanate 0.8 10 Υ Υ 

Acrylic Acid 0.8 1 Υ Υ 

Dimethyl Phthalate 0.7 8 

Hydroquinone 0.6 5 

Cyanide & Compounds 0.6 2 Υ

p-Xylene 0.5 6 Υ Υ 

p-Dioxane 0.4 5 Υ Υ Υ 

Manganese Compounds 

Manganese & 

Compounds 0.4 50 Υ

Manganese Trioxide 0.03 8 Υ

Lead Compounds 0.4 3 c Υ

Chromium Compounds 

Chromium III 0.2 36 

Chromium VI 0 29 Υ Υ

Trichloroethylene 0.1 2 Υ Υ Υ 

Propylene Oxide 0.1 1 Υ Υ Υ

Acetaldehyde 0.08 9 Υ Υ Υ 
27

Table 3.1-1 Summary of Emissions from the Wood Furniture Manufacturing Source Category and 

Availability of Dose-Response Values 

HAPa Emissions 

(tpy) 

Number of 

Facilities 

Reporting HAP 

(384 facilities in 

NPRM data set) 

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate 

for Cancer? 

Reference 

Concentration 

for 

Noncancer? 

Health 

Benchmark 

Values for Acute 

Noncancer? 

1,2-Epoxybutane 0.06 1 Υ

Benzene 0.05 7 Υ Υ Υ

Cobalt Compounds 0.04 42 Υ

2,4-Toluene Diisocyanate 0.04 1 Υ Υ Υ 

Triethylamine 0.04 6 Υ Υ 

Hexamethylene 

Diisocyanate 0.02 6 Υ

Acrylonitrile 0.02 1 Υ Υ Υ 

Nickel Compounds 0.01 3 Υ Υ Υ

Hydrochloric Acid 0.01 1 Υ Υ 

Diethanolamine 0.006 4 Υ

Hydrogen Cyanide 0.003 1 Υ Υ 

Quinone 0.001 1 

o-Cresol 0.0009 1 Υ

Maleic Anhydride 0.00009 1 Υ Υ 

Vinyl Chloride 0.000008 1 Υ Υ Υ 

Benzyl Chloride 0.000004 5 Υ Υ 

p-Dichlorobenzene 0.000003 1 Υ Υ

Cadmium compounds 0.000003 1 Υ Υ Υ

Selenium & Compounds 0.0000003 3 Υ

Arsenic & Compounds 

(Inorganic Including 

Arsine) 

0.0000006 1 Υ Υ Υ 

POM 0.000000295 3 Υ Y 

Beryllium compounds 0.00000003 1 Υ Υ Υ

a

 Notes for how HAP were speciated for risk assessment: 

• (S) – denotes a surrogate health benchmark value was used for estimating cancer or non-cancer risks 

• For most metals, emissions reported as the elemental metal are combined with metal compound emissions (e.g., 

“cadmium” emissions modeled as “cadmium & compounds”). In the absence of speciation information, we assume the 

reported mass is 100 percent metal. 

• For metal and cyanide compounds consisting of more than just the metal or cyanide ion (on which the dose-response 

values are based), emissions were adjusted according to the mass fraction of the metal or cyanide. For example, for lead 

nitrate, emissions were multiplied by 0.6218 to account for the mass of the one Pb atom (mass of 207.2) in a single 

molecule of Pb(HNO3)2 (total mass of 333.22). For metal compounds containing two metal species of interest, the NEI 

chemical was multiplied by adjustment factors two times (to account for each metal of interest), resulting in two 

chemicals for modeling (i.e., toxicity to both metal compounds was assessed). For example, emissions of lead arsenate 

(PbAsH3O4) were multiplied by 0.5935 to account for the mass of lead in the emitted compound, and were multiplied by 

0.2146 to account for the mass of arsenic in the emitted compound. 

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

Network for air toxics (see footnote b), emissions were treated as ethylene glycol methyl ether for the chronic noncancer 

risk assessment and ethylene glycol methyl ether for the acute noncancer risk assessment. 

• For emissions of any chemicals or chemical groups classified as polycyclic organic matter (POM), emissions were 

grouped into POM subgroups as found on EPA’s Technology Transfer Network website for the 2002 National-Scale Air 

Toxics Assessment at http://www.epa.gov/nata2002/methods.html#pom. (Approach to Modeling POM). 
28

b

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

toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html and are also available in Appendix 5 of the Development of 

Preliminary Risk Estimates for Source Categories Previously Subjected to Technology-based Standards document. 

c

 There is no reference concentration for lead. In considering noncancer hazards for lead in this preliminary assessment, we 

compared maximum 3-month ambient exposure estimates to the National Ambient Air Quality Standards (NAAQS) for lead 

(0.15 μg/m3

). These NAAQS for lead were recently reviewed with revisions adopted in October 2008 

(http://www.epa.gov/air/lead/actions.html). The primary (health-based) standard is a maximum or not-to-be-exceeded, 

rolling three-month average, measured as total suspended particles (TSP). The secondary (welfare-based) standard is 

identical to the primary standard. 

3.2 Risk Characterization 

This section presents the results of the preliminary risk assessment for the wood furniture 

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 assessments in the form of maximum 

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

PB HAP. Also presented are the HAP “drivers,” which are the HAP that collectively 

contribute 90 percent of the maximum cancer risk or maximum hazard at the highest exposure 

location, as well as a summary of the results of our facility-wide assessments and our analysis 

of risks associated with the maximum allowed emissions under the current MACT standards. 

A detailed summary of the facility-specific risk assessment results is available in Appendix 6. 

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

this source category. The results for the wood furniture manufacturing source category 

indicate that maximum lifetime individual cancer risks (the MIR) could be as high as 20 in a 

million19. The major contributors to the risks are formaldehyde, bis(2-ethylhexyl)phthalate, 

and ethyl benzene. Approximately 20 people were estimated to have cancer risks above 10 in 

a million as a result of the emissions from 3 facilities, and approximately 20,000 people were 

estimated to have cancer risks above 1 in a million as a result of the emissions from 64 

facilities. The total cancer incidence associated with the source category was estimated to be 

0.00520. 

 

19 We note that this MIR value would be reduced by 50 percent if the CIIT URE for formaldehyde were used 

instead of the IRIS URE. 

20 We note that the cancer incidence would be reduced by 30 percent if the CIIT URE for formaldehyde were 

used instead of the IRIS URE. 
29

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

Manufacturing Facilities 

Result HAP “Drivers” 

Facilities in Source Category 

Number of Facilities Estimated to be in Source 

Category 406 n/a 

Number of Facilities Identified in NEI and 

Modeled in Preliminary Risk Assessment 384 n/a 

Cancer Risks 

Maximum Individual Lifetime Cancer Risk (in 1 

million) 1021 ethyl benzene, formaldehyde 

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 2 ethyl benzene, formaldehyde 

 Greater than or equal to 1 in 1 million 63 

ethyl benzene, formaldehyde, methylene 

chloride, acrylonitrile, bis(2-

ethylhexyl)phthalate, 1,4-dioxane, 

naphthalene 

Chronic Noncancer Risks 

Maximum Hazard Index (Neurological) 0.4 n-hexane 

Number of Facilities with Hazard Index:

 Greater than 1 0 n/a 

Acute Noncancer Screening Results 

Maximum Acute Hazard Quotient 20 formaldehyde (REL) 

Number of Facilities With Potential for Acute 

Effects 25 formaldehyde, propyl cellosolve, toluene 

 Acute Noncancer Refined Results

Maximum Acute Hazard Quotient 

10 

7 / 0.35 

2 / 0.35 

propyl cellosolve (REL) 

 formaldehyde (REL / AEGL1) 

 toluene (REL / AEGL1) 

Number of Facilities with Potential for Acute 

Effects 19 propyl cellosolve, formaldehyde, toluene 

Population Exposure 

Number of People Living Within 50 Kilometers 

of Facilities Modeled 103,000,000 n/a 

 

21 We note that the MIR for this source category would not change if the CIIT URE for formaldehyde had been 

used in the assessment, although the total cancer incidence would decrease by 30%. There is an ongoing IRIS 

reassessment for formaldehyde, and future RTR risk assessments will use the cancer potency for formaldehyde 

that results from that reassessment. As a result, the current results may not match those of future assessments. 
30

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

Manufacturing Facilities 

Result HAP “Drivers” 

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 7 n/a 

 Greater than or equal to 1 in 1 million 20,000 n/a 

Number of People Exposed to Noncancer Hazard Index: 

 Greater than 1 0 n/a 

Estimated Cancer Incidence (excess cancer 

cases per year) 0.00519 n/a 

Contribution of HAP to Cancer Incidence

 ethyl benzene 28% n/a 

 bis(2-ethylhexyl)phthalate 28% n/a 

 formaldehyde 28% n/a 

methylene chloride 6% n/a 

naphthalene 5% n/a 

1,4-dioxane 3% n/a 

acrylonitrile 3% n/a 

Table 3.2-2: Summary of NPRM Acute Refined Results for Wood Furniture 

Manufacturing Facilities 

Screening Results MAXIMUM ACUTE HAZARD 

QUOTIENTS ACUTE DOSE-RESPONSE VALUES 

HAP 

Max. 1-hr. 

Air Conc. 

(mg/m3

) 

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

) 

Formaldehyde 0.39 7 0.35 0.02 0.055 1.1 1.1 17 17 

Propyl 

Cellosolve 0.93 10 n/a n/a 0.093 

Toluene 67 2 0.09/0.35 0.01/0.06 37 750 190 4500 1130 

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. 

 EPRG – 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. 
31

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.

The maximum chronic non-cancer TOSHI values for the source category could be as high as 

0.4, with emissions of n-hexane dominating those impacts, indicating no significant potential 

for chronic noncancer impacts. The estimation of chronic non-cancer TOSHI values was 

performed consistent with the approach taken in previous risk and technology review for other 

source categories, i.e., we used our existing hierarchy of reference values (EPA 1999 – 

Residual Risk Report to Congress), which favors the use of an IRIS value when available, and 

favors using values which have been developed and peer-reviewed using processes similar to 

the IRIS process under the sponsorship of a state or federal government agency, the 

documentation of which can be easily accessed by the public (such as those from ATSDR or 

the California EPA) when IRIS values are not available. The use of a surrogate reference 

value for chemicals in a chemical group (e.g., glycol ethers) is part of this approach when 

specific chemicals in the group do not have available reference values, and/or emissions are 

reported generically for the chemical group and not specific chemicals. In this case, the IRIS 

RfC for ethylene glycol monomethyl ether (EGME) is the lowest (i.e., most health protective) 

of the available reference values for glycol ethers from our hierarchy of reference values. 

Using the surrogate approach described above, the maximum chronic non-cancer Target 

Organ-Specific Hazard Index (HI) for the source category could be as high as 0.4 (based on 

actual emissions) and 0.8 (based on allowable emissions), with emissions of n-hexane 

dominating. 

In reviewing data sources for this residual risk assessment, we identified a Provisional Peer 

Reviewed Toxicity Value (PPRTV) for assessing chronic noncancer health risks from 

inhalation of diethylene glycol monobutyl ether (DGBE), which is emitted by some facilities 

in this source category. PPRTVs are reference values, developed by EPA for use specifically

in EPA’s Superfund Program when an acceptable reference value, such as those found in 

EPA’s IRIS database, is not otherwise available. 

The DGBE PPRTV was prepared for EPA’s Superfund Program in 2009. Inhalation toxicity 

information for DGBE is essentially limited to the results of a single 5-week study in rats 

(Gushow et al., 1984), which resulted in slight vacuolization of the liver cells consistent with 

fatty change. An uncertainty factor of 3000 was applied in deriving the PPRTV, and 

confidence in the provisional RfC (p-RfC) value is low. 

PPRTVs differ from IRIS values in that PPRTVs do not receive the multiprogram review 

provided for IRIS values. As stated in the DGBE PPRTV document, this is because “...IRIS 

values are generally intended to be used in all U.S. EPA programs, while PPRTVs are 

developed specifically for the Superfund Program.” 

The EPA’s Superfund Program uses PPRTVs in conjunction with assessments to support sitespecific clean-up decisions. PPRTVs are applied to high quality exposure data developed for 

each Superfund site using measurements of the specific chemical for which the PPRTV was 

developed. Each final cleanup decision, as memorialized in a Record of Decision, is subject 

to public notice and comment, and it is at this stage of the process that a public review of how 
32

a PPRTV was used in that site-specific context may occur, which may include consideration 

of comments on the development of the PPRTV itself (i.e., the PPRTV development 

document is not explicitly the subject of a separate public review or comment period). The 

current process for development of the reference values used to support today’s proposed 

decisions includes a public comment period prior to a final external peer review of the 

assessment. This more rigorous review process prior to the release of the values enables 

immediate use of the derived values across multiple EPA Program Offices, including 

providing support for national regulatory decisions (e.g., RTR). 

Contrasting the site-specific Superfund application of PPRTVs and related Records of 

Decision, the Wood Furniture RTR proposal is of national scope and will not be subject to 

ongoing review related to each application to a facility. Based on the foregoing discussion, 

EPA has determined that reliance on the DGBE PPRTV value in this RTR rule is beyond the 

specific purpose for which it was developed, and would exacerbate the cumulative uncertainty 

in the risk assessment stemming from limitations in the underlying exposure and toxicity data. 

Accordingly, EPA has not used the DGBE PPRTV value in the baseline Wood Furniture risk 

assessment supporting this proposed action, noting that a suitable alternative value (in this 

case, it is the RfC for EGME from IRIS) is available to represent the toxicity of glycol ethers 

without hierarchically based noncancer reference values in the assessment. 

The acute screening risk assessment for this source category identified 25 facilities with a 

potential HQ greater than 1, with a maximum HQ up to 20. We performed refined acute 

assessments for these facilities with improved mapping and emission source modeling, 

resulting in a maximum estimated off-site HQ of 10, with 20 facilities having an HQ 

estimated to be greater than 1. The primary acute risk drivers were glycol ethers, 

formaldehyde, and toluene, and all the HQ estimates greater than 1 were based on REL 

values. Table 3.2-2 shows that the maximum acute HQ values for formaldehyde and toluene 

based on ERPG-1 values were 0.35 and 0.35, respectively, and that the maximum acute HQ 

values based on AEGL-1 values were 0.35 and 0.09, respectively. There are no other 

appropriate acute values for glycol ethers on which to base a comparison or interpretation of 

potential risk. Refer to Appendix 7 for detailed results of the refined acute assessments. 

Based on the REL value for formaldehyde, an off-site acute HQ value from a wood furniture 

manufacturing facility could be up to 7. We also estimate that emissions of formaldehyde 

from 11 facilities (or about 3 percent of the total facilities) may result in maximum acute 

HQREL values greater than 1. The REL is considered protective; exposures above the REL do 

not necessarily indicate that adverse effects will occur. The AEGL-1 and ERPG-1 values are 

those that when exceeded can produce mild and progressively increasing but transient and 

nondisabling sensory irritation or certain asymptomatic, nonsensory effects. . The maximum 

acute HQ for formaldehyde based on an AEGL-1 or ERPG-1 value is 0.35, indicating that 

these effects (which are generally eye and nose irritation) might not be expected to occur. 

To better characterize the potential health risks associated with estimated worst-case 

acute exposures to HAP, and in response to a key recommendation from the Science Advisory 
33

Board’s peer review of EPA’s RTR risk assessment methodologies22, we examine a wider 

range of available acute health metrics than we do for our chronic risk assessments. This is in 

response to the acknowledgement that there are generally more data gaps and inconsistencies 

in acute reference values than there are in chronic reference values. By definition, the acute 

CA-REL represents a health-protective level of exposure, with no risk anticipated below those 

levels, even for repeated exposures; however, the health risk from higher-level exposures is 

unknown. Therefore, when a CA-REL is exceeded and an AEGL-1 or ERPG-1 level is 

available (i.e., levels at which mild effects are anticipated in the general public for a single 

exposure), we have used them as a second comparative measure. Historically, comparisons of 

the estimated maximum off-site one-hour exposure levels have not been typically made to 

occupational levels for the purpose of characterizing public health risks in RTR assessments. 

This is because occupational ceiling values are not generally considered protective for the 

general public since they are designed to protect the worker population (presumed healthy 

adults) for short duration (<15 minute) increases in exposure21. As a result, for most 

chemicals, the 15-minute occupational ceiling values are set at levels higher than a one-hour 

AEGL-1, making comparisons to them irrelevant unless the AEGL-1 or ERPG-1 levels are 

exceeded21. Such is not the case when comparing the available acute inhalation health effect 

reference values for formaldehyde23. 

The worst-case maximum estimated 1-hour exposure to formaldehyde outside the 

facility fence line for this source category is 0.47 mg/m3. This estimated worst-case exposure 

exceeds the 1-hour REL by a factor of 8 (HQREL = 8) and is below the 1-hour AEGL-1 

(HQAEGL-1 = 0.4). Although this exposure estimate does not exceed the AEGL-1, it exceeds 

the workplace ceiling level guideline for the value developed by the NIOSH24 “for any 15 

minute period in a work day” (NIOSH REL-ceiling value of 0.12 mg/m3; HQNIOSH = 4). 

Additionally, the estimated maximum acute exposure exceeds the Air Quality Guideline value 

that was developed by the World Health Organization25 for 30-minute exposures (0.1 mg/m3; 

HQWHO = 5). The estimated HQ equals 1 when the ACGIH TLV-Ceiling value (0.37 mg/m3

), 

 

22 The SAB peer review of RTR Risk Assessment Methodologies is available at: 

http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/EPA-SAB-10-

007-unsigned.pdf 

23 U.S. EPA. (2009) Chapter 2.9 Chemical Specific Reference Values for Formaldehyde in Graphical Arrays of 

Chemical-Specific Health Effect Reference Values for Inhalation Exposures (Final Report). U.S. 

Environmental Protection Agency, Washington, DC, EPA/600/R-09/061, and available on-line at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003 

24 National Institutes for Occupational Safety and Health (NIOSH). Occupational Safety and Health Guideline 

for Formaldehyde; http://www.cdc.gov/niosh/docs/81-123/pdfs/0293.pdf 

25 WHO (2000). Chapter 5.8 Formaldehyde, in Air Quality Guidelines for Europe, second edition. World Health 

Organization Regional Publications, European Series, No. 91. Copenhagen, Denmark. Available on-line at 

http://www.euro.who.int/__data/assets/pdf_file/0005/74732/E71922.pdf. 
34

a value defined as “not to be exceeded at any time,”26 is compared to the worst-case acute 

exposure screening level27. 

As noted in Table 3.2-2, using the REL to assess concentrations from one of the glycol ethers, 

propyl cellosolve, an off-site acute non-cancer HQ value up to 10 could occur based upon the 

use of the acute dose-response value of EGME. Exposures above the REL do not necessarily 

indicate that adverse effects will occur, only that they cannot be ruled out. We estimate that 

emissions of propyl cellosolve from 8 facilities (or about 2 percent of the total facilities) may 

result in maximum acute HQ values greater than 1. 

In characterizing the potential acute noncancer risks from propyl cellosolve, a glycol ether 

HAP, it is important to consider the uncertainties related to the emissions inventory. First, 

there is uncertainty in the speciation profile developed for glycol ethers for this source 

category based upon extrapolating speciated glycol ether emissions from 26 facilities to the 

remaining 66 facilities that reported only total glycol ether emissions rather than emissions of 

individual glycol ether species. This profile may not be representative of the source category 

since it is based on data from a limited subset of facilities. Second, these uncertainties are 

compounded in our attempt to assess risks for those glycol ether compounds for which we do 

not have dose-response values. 

When interpreting the chronic cancer risk results and potential acute risks from formaldehyde 

emissions from this source category, it is important to note that the reported levels of 

formaldehyde in the NEI are likely derived from coatings content and therefore may not fully 

account for gluing operations or curing processes that may also create formaldehyde. 

Recognizing that there is no approved method for estimating formaldehyde emissions from 

curing, this is an uncertainty that is likely to bias our risk assessment low. The extent of such 

underestimation, if any, however, is unknown. 

In performing the screening for potential multi-pathway exposures and risks of concern, we 

determined that emissions of cadmium and POM were not significant enough to pose multipathway impacts of concern for human health or the environment. We also determined that 

emissions of lead were not significant enough to cause an exceedance of the lead NAAQS, 

indicating that potential multipathway impacts for lead from this source category are not 

significant. 

The results of the facility-wide assessments are summarized in Table 3.2-3. The results 

indicate that one facility has the highest cancer MIR of 100 in a million, 2 facilities have a 

cancer MIR between 10 and 100 in a million. All other facility MIR values were equal to or 

less than 10 in a million. The source category MIR at the one facility with the highest MIR is 

1 in a million, contributing only 1% to the facility-wide cancer risk. Additionally, this facility 

with the highest MIR also has the highest facility-wide HI of 3 with a source category HI 

 

26 ACGIH (2001) Formaldehyde. In Documentation of the TLVs and BEIs with other Worldwide Occupational 

Exposure Values. ACGIH, 1300 Kemper Meadow Drive, Cincinnati, OH 45240(ISBN: 978-1-882417-74-2) 

and available on-line at http://www.acgih.org. 

27 EPA considers this HQ of 1, not to represent an exceedance for purposes of the RTR program. 
35

contribution of 13%. In general, facility-wide cancer risks are low (MIR less than or equal to 

1) for the source category, and the contribution of the source category to overall facility risks 

is close to 100% for most of the facilities with facility-wide MIR values greater than 1 in this 

source category. 

Table 3.2-3 Wood Furniture Source Category Contribution to Facility-Wide Cancer 

Risks 

Number of Facilities Binned by Facility-Wide 

MIR (in 1 million) 

Source Category MIR Contribution 

to Facility-Wide MIR 

< 1 ≥ 1 <10 ≥ 10 < 100 > 100 Total 

100% 95 48 2 0 145 

90-99% 45 7 0 0 52 

50-89% 21 6 0 0 27 

10-49% 9 6 0 0 15 

1-9% 0 1 0 1 2 

0% 141 2 0 0 143 

Total 311 70 2 1 384 

Analysis of potential differences between actual emission levels and the maximum emissions 

allowable under the MACT standards for wood furniture manufacturers indicated that MACT 

allowable emission levels may be up to 2 times greater than actual emission levels. 

Considering this difference, the risk results from the inhalation risk assessment indicate that 

the maximum lifetime individual cancer risk could be up to 40 in a million and that the 

maximum chronic noncancer TOSHI could be up to 0.8 for this source category with all 

facilities operating at MACT-allowable emission levels. For more detail about this estimate 

of the ratio of actual to MACT-allowable emissions, for the wood furniture manufacturing 

source category, see the memo to the rulemaking docket [31]. 

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 exposure modeling uncertainties are considered relatively 

small in comparison, since we are using EPA’s refined local dispersion model with 

reasonably representative meteorology. It is possible that population exposure estimates are 

also biased slightly higher by not accounting for short- or long-term population mobility, and 

by neglecting processes like deposition, plume depletion, and atmospheric degradation. 
36

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 

assessments, 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 and the true variability of 

short-term emission rates. For this source category, refining the assessments for the facilities 

that did not screen out resulted in estimates of acute risks which were the same or lower than 

those from the screening assessment. 

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 non-cancer reference values. Cancer potency values are 

derived for chronic (lifetime) exposures. Non-cancer reference values are generally derived 

for chronic exposures (up to a lifetime), but may also be derived for acute (<24 hours), shortterm (>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 non-cancer) and 

acute (non-cancer) 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 sources 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 
37

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 [32] (herein 

referred to as Cancer Guidelines). “The primary goal of EPA actions is protection of human 

health; accordingly, as an Agency policy, risk assessment procedures, including default 

options that are used in the absence of scientific data to the contrary, should be health 

protective.” The approach adopted in this document is consistent with this approach as 

described in the Cancer Guidelines. 

For cancer endpoints EPA usually derives an oral slope factor for ingestion and a unit risk 

value for inhalation exposures. These values allow estimation of a lifetime probability of 

developing cancer given long-term exposures to the pollutant. Depending on the pollutant 

being evaluated, EPA relies on both animal bioassay and epidemiological studies to 

characterize cancer risk. As a science policy approach, consistent with the Cancer 

Guidelines, EPA uses animal cancer bioassays as indicators of potential human health risk 

when other human cancer risk data are unavailable. 

Extrapolation of study data to estimate potential risks to human populations is based upon 

EPA’s assessment of the scientific database for a pollutant using EPA’s guidance documents 

and other peer-reviewed methodologies. The EPA Cancer Guidelines describes the Agency’s 

recommendations for methodologies for cancer risk assessment. EPA believes that cancer 

risk estimates developed following the procedures described in the Cancer Guidelines and 

outlined below generally provide an upper bound estimate of risk. That is, EPA’s upper 

bound estimates represent a “plausible upper limit to the true value of a quantity” (although 

this is usually not a true statistical confidence limit).28 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.29 

When developing an upper bound estimate of risk and to provide risk values that do not 

 

28 IRIS glossary (www.epa.gov/NCEA/iris/help_gloss.htm). 

29 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. 
38

underestimate risk, EPA generally relies on conservative default approaches.30 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 [33]. Some of the major sources of uncertainty and 

variability in deriving cancer risk values are described more fully below. 

(1) The qualitative similarities or differences between tumor responses observed in 

experimental animal bioassays and those which would occur in humans is a source of 

uncertainty in cancer risk assessment. In general, EPA does not assume that tumor sites 

observed in an experimental animal bioassay are necessarily predictive of the sites at which 

tumors would occur in humans.31 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. 

 

30 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. 31 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.” 
39

(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 

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 
40

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 [34] 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) [35]. It is important to note that 

earlier EPA assessments, including the majority of those for which risk values exist today, 

were generally developed using the multistage model to extrapolate down to environmental 

dose levels and did not involve the use of a POD. Subramaniam et. al. (2006) also provide 

comparisons indicating that slopes based on straight line extrapolation from a POD do not 

show large differences from those based on the upper confidence limit of the multistage 

model. 

(6) Cancer risk estimates do not generally make specific adjustments to reflect the variability 

in response within the human population — resulting in another source of uncertainty in 

assessments. In the diverse human population, some individuals are likely to be more 

sensitive to the action of a carcinogen than the typical individual, although compound-specific 

data to evaluate this variability are generally not available. There may also be important life 

stage differences in the quantitative potency of carcinogens and, with the exception of the 

recommendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic 

mode of action, risk assessments do not generally quantitatively address life stage differences. 

However, one approach used commonly in EPA assessments that may help address variability 

in response is to extrapolate human response from results observed in the most sensitive 

species and sex tested, resulting typically in the highest URE which can be supported by 

reliable data, thus supporting estimates that are designed not to underestimate risk in the face 

of uncertainty and variability. 

Chronic non-cancer assessment
41

Chronic non-cancer reference values represent chronic exposure levels that are intended to be 

health-protective. That is, EPA and other organizations which develop non-cancer 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 values32 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. 

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.33 To derive values that are intended to be “without 

appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach 

[36],[37]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). 

 

32 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. 

33 See IRIS glossary 
42

A series of downward adjustments using default UFs is then applied to the POD to estimate 

the reference value,[38]. 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-in

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. 

dividual 

 1) Heterogeneity among humans is a key source of variability as well as uncertainty. 

Uncertainty related to human variation is considered in extrapolating doses from a subset or 

smaller-sized population, often of one sex or of a narrow range of life stages (typical of 

occupational epidemiologic studies), to a larger, more diverse population. In the absence of 

pollutant-specific data on human variation, a 10-fold UF is used to account for uncertainty 

associated with human variation. Human variation may be larger or smaller; however, data to 

examine the potential magnitude of human variability are often unavailable. In some 

situations, a smaller UF of 3 may be applied to reflect a known lack of significant variability 

among humans. 

 2) Extrapolation from results of studies in experimental animals to humans is a 

necessary step for the majority of chemical risk assessments. When interpreting animal data, 

the concentration at the POD (e.g. NOAEL, BMDL) in an animal model (e.g. rodents) is 

extrapolated to estimate the human response. While there is long-standing scientific support 

for the use of animal studies as indicators of potential toxicity to humans, there are 

uncertainties in such extrapolations. In the absence of data to the contrary, the typical 

approach is to use the most relevant endpoint from the most sensitive species and the most 

sensitive sex in assessing risks to the average human. Typically, compound specific data to 

evaluate relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty 

in this extrapolation. Size-related differences (allometric relationships) indicate that typically 

humans are more sensitive than rodents when compared on a mg/kg/day basis. The default 

choice of 10 for the interspecies UF is consistent with these differences. For a specific 

chemical, differences in species responses may be greater or less than this value. 

Pharmacokinetic models are useful to examine species differences in pharmacokinetic 

processing and associated uncertainties; however, such dosimetric adjustments are not always 

possible. Information may not be available to quantitatively assess toxicokinetic or 
43

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. 

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 
44

 

lack of threshold values at different levels of severity should be factored into the risk 

characterization as potential uncertainties. 

5 References 

1. US EPA. National Emission Standards for Hazardous Air Pollutants. 

http://www.epa.gov/ttn/atw/mactfnlalph.html. 

2. US EPA, 2009. Risk and Technology Review (RTR) Risk Assessment Methodologies: For 

Review by the EPA’s Science Advisory Board with Case Studies – MACT I Petroleum 

Refining Sources and Portland Cement Manufacturing. EPA-452/R-09-006. 

http://www.epa.gov/ttn/atw/rrisk/rtrpg.html. 

3. US EPA, 2010. SAB’s Response to EPA’s RTR Risk Assessment Methodologies. 

http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/E

PA-SAB-10-007-unsigned.pdf. 

4. US EPA, 2010. Memorandum from Dave Guinnup to RTR Wood Furniture Docket, entitled, 

“EPA’s Actions in Response to Key Recommendations of the SAB Review of RTR Risk 

Assessment Methodologies. 

5. US EPA, 2005. Revision to the Guideline on Air Quality Models: Adoption of a Preferred 

General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final 

Rule. 40 CFR Part 51. http://www.epa.gov/EPA-AIR/2005/November/Day-09/a21627.htm

6. US EPA, 2004. Users’ guide for the AMS/EPA regulatory model – AERMOD. EPA-454/B03-001. http://www.epa.gov/scram001/7thconf/aermod/aermodugb.pdf. 

7 . US EPA, October 22, 2010. Memorandum from Kaye Whitfield to RTR Wood Furniture 

Docket, entitled, “Acute Effects Factor Based on Facilities with Formaldehyde Emissions 

for Wood Furniture Manufacturing Operations”

8. Allen, D., C. Murphy, Y. Kimura, W. Vizuete, T. Edgar, H. Jeffries, B.-U. Kim, M. Webster, 

and M. Symons, 2004. Variable industrial VOC emissions and their impact on ozone 

formation in the Houston Galveston Area. Final Report: Texas Environmental Research 

Consortium Project H-13. 

http://files.harc.edu/Projects/AirQuality/Projects/H013.2003/H13FinalReport.pdf

9. US EPA, 1996, 1999, 2002, 2005. National-Scale Air Toxics Assessments (NATA), 

Technology Transfer Network Air Toxics web site: http://www.epa.gov/airtoxics/natamain/. 

10. US EPA, 2004. Air Toxics Risk Assessment Reference Library, Volume 1. EPA-453-K-04-

001A. http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 

11. US EPA, 2005. Table 1. Prioritized Chronic Dose-Response Values (2/28/05). Office of 

Air Quality Planning and Standards. http://www.epa.gov/ttn/atw/toxsource/table1.pdf

12. US EPA, 2006. Integrated Risk Information System. http://www.epa.gov/iris/index.html. 
45

 

13. US Agency for Toxic Substances and Disease Registry. 2006. Minimum Risk Levels (MRLs) 

for Hazardous Substances. http://www.atsdr.cdc.gov/mrls/index.html. 

14. US EPA, 1994. US Environmental Protection Agency. Methods for Derivation of 

Inhalation Reference Concentrations and Application of Inhalation Dosimetry. 

EPA/600/8-90/066F. Office of Research and Development. Washington, DC: U.S.EPA.

15. NRC, 1994. National Research Council. Science and Judgment in Risk Assessment. 

Washington, DC: National Academy Press. 

16. CA Office of Environmental Health Hazard Assessment, 2005. Chronic Reference 

Exposure Levels Adopted by OEHHA as of December 2008. 

http://www.oehha.ca.gov/air/chronic_rels/AllChrels.html. 

17. CA Office of Environmental Health Hazard Assessment, 2005. Technical Support Document 

for Describing Available Cancer Potency Factors, May 2005. 

http://www.oehha.ca.gov/air/hot_spots/may2005tsd.html. 

18. US EPA, 2006. Approach for modeling POM. Technical support information for the 1999 

National Air Toxics Assessment. 

http://www.epa.gov/ttn/atw/nata1999/99pdfs/pomapproachjan.pdf. 

19. US EPA, 2005. Table 2. Acute Dose-Response Values for Screening Risk Assessments 

(6/02/2005). Office of Air Quality Planning and Standards. 

http://www.epa.gov/ttn/atw/toxsource/table2.pdf

20. CA Office of Environmental Health Hazard assessment, 2000. All Acute Reference Exposure 

Levels developed by OEHHA as of May 2000. 

http://www.oehha.ca.gov/air/acute_rels/allAcRELs.html

21. American Industrial Hygiene Association , 2009. Current AIHA ERPG Values. 

http://www.aiha.org/insideaiha/volunteergroups/Documents/ERP-erpglevels.pdf. 

22. US EPA, 1995. Guidance for Risk Characterization. Science Policy Council. 

http://www.epa.gov/OSA/spc/pdfs/rcguide.pdf. 

23. US EPA, 2000. Risk Characterization Handbook. EPA 100-B-00-002. 

24. US EPA, 2002. EPA’s Guidelines for Ensuring and Maximizing the Quality, Objectivity, 

Utility, and Integrity of Information Disseminated by the Environmental Protection Agency. 

EPA Office of Environmental Information. EPA/260R-02-008. 

http://www.epa.gov/quality/informationguidelines/documents/EPA_InfoQualityGuidelines.pdf

25. US EPA, 2006. Performing risk assessments that include carcinogens described in the 

Supplemental Guidance as having a mutagenic mode of action. Science Policy Council Cancer 

Guidelines Implementation Workgroup Communication II: Memo from W.H. Farland dated 

14 June 2006. http://www.epa.gov/osa/spc/pdfs/CGIWGCommunication_II.pdf
46

 

26. US EPA, 2005. Supplemental guidance for assessing early-life exposure to carcinogens. 

EPA/630/R-03003F. http://www.epa.gov/ttn/atw/childrens_supplement_final.pdf. 

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

Communication I: Memo from W.H. Farland dated 4 October 2005 to Science Policy 

Council. http://www.epa.gov/osa/spc/pdfs/canguid1.pdf 

28. US EPA, 1986. Guidelines for the Health Risk Assessment of Chemical Mixtures. EPA-630-

R-98-002. http://www.epa.gov/NCEA/raf/pdfs/chem_mix/chemmix_1986.pdf

29. US EPA, 2000. Supplementary Guidance for Conducting Health Risk Assessment of 

Chemical Mixtures. EPA-630/R-00-002. 

http://www.epa.gov/ncea/raf/pdfs/chem_mix/chem_mix_08_2001.pdf. 

30. US EPA, October 22, 2010. Memorandum from Kaye Whitfield to RTR Wood Furniture 

Docket, entitled, “Review of Glycol Ether Emissions Associated with the Wood Furniture 

Manufacturing Source Category”.

31. US EPA, September 9, 2010. Memorandum Maximum Achievable Control Technology 

(MACT) Allowable Emissions Estimate”; Kaye Whitefield Project Lead 

32. US EPA, 2005. Guidelines for Carcinogen Risk Assessment (2005). U.S. Environmental 

Protection Agency, Washington, DC, EPA/630/P-03/001F, 2005. 

http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=116283

33. US EPA, 2000. Risk Characterization Handbook. EPA 100-B-00-002. 

34. NRC (National Research Council) 2006. Assessing the Human Health Risks of 

Trichloroethylene. National Academies Press, Washington DC. 

35. R.P. Subramaniam, P. White and V.J. Cogliano. 2006. Comparison of cancer slope factors 

using different statistical approaches, Risk Anal. Vol 26, p. 825–830. 

36. US EPA. 1993. Reference Dose (RfD): Description and Use in Health Risk Assessments. 

http://www.epa.gov/iris/rfd.htm. 

37. US EPA. 1994. Methods for Derivation of Inhalation Reference Concentrations and 

Application of Inhalation Dosimetry. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=71993. 

38. US EPA. 2002. A Review of the Reference Dose and Reference Concentration Processes. 

http://www.epa.gov/ncea/iris/RFD_FINAL1.pdf.