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Deliberative Draft Document for EPA Internal Review

Draft 

Residual Risk Assessment for the Primary Aluminum Production 

Source Category

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

NovemberOctober 2011
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Table of Contents

1 Introduction................................................................................................................ 444

2 Methods..................................................................................................................... 444

2.1 Emissions and source data ................................................................................... 444

2.2 Dispersion modeling for inhalation exposure assessment ..................................... 555

2.3 Estimating chronic human inhalation exposure .................................................... 878

2.4 Screening for potential acute impacts of concern.................................................. 988

2.5 Multipathway human health and environmental risk screening......................... 10910

2.6 Dose-response assessment ............................................................................. 111111

2.6.1 Sources of chronic dose-response information ........................................ 111111

2.6.2 Sources of acute dose-response information............................................ 151515

2.7 Risk characterization...................................................................................... 171717

2.7.1 General................................................................................................... 171717

2.7.2 Mixtures................................................................................................. 191919

2.7.3 Facility-wide risks .................................................................................. 202020

3 Risk results for the primary aluminum production source category................... 202020

3.1 Source category description and results.......................................................... 202020

3.2 Baseline risk characterization......................................................................... 212121

3.3 Post-control risk characterization ................................................................... 252525

4 General discussion of uncertainties and how they have been addressed ................ 262626

4.1 Exposure modeling uncertainties.................................................................... 262626

4.2 Uncertainties in the dose-response relationships............................................. 272727

5 References ........................................................................................................... 353535

Index of Tables

Table 2.2-1 AERMOD version 09292 model options for RTR modeling........................... 666

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

.................................................................................................................................... 141314

Table 2.6-1 (b) Dose-Response Values for Chronic Oral Exposure to Carcinogens .... 141414

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

.................................................................................................................................... 151515

Table 2.6-2 Dose-Response Values for Acute Exposure.............................................. 171717

Table 3.1-1 Summary of Emissions from the Primary Aluminum Production Source Category 

and Availability of Dose-Response Values................................................................... 212121

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

Production ................................................................................................................... 232323

Table 3.2-2 Summary of Refined Acute Results for Secondary Aluminum Production 

Facilities...................................................................................................................... 242424

Appendices

Appendix 1 Technical Support Document for HEM-AERMOD Modeling

Appendix 2 Meteorological Data for HEM-AERMOD Modeling

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

rates

Appendix 4 Technical Support Document for TRIM-Based Multipathway Screening 

Scenario for RTR: Summary of Approach and Evaluation

Appendix 5 Draft Detailed Risk Modeling Results

Appendix 6 Acute Impacts Refined Analysis Figures

Appendix 7 Development of the Chronic Screening Level for Carbonyl Sulfide

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model

AEGL Acute exposure guideline level

ASTDR US Agency for Toxic Substances and Disease Registry

CalEPA California Environmental Agency

CTE Central Tendency Estimate

ERPG Emergency Response Planning Guideline

HAP Hazardous Air Pollutant

HEM Human Exposure Model

HI Hazard index

HQ Hazard quotient

IRIS Integrated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of action

NAC National Advisory Committee

NAAQS National Ambient Air Quality Standards

NATA National Air Toxics Assessment

NEI National Emissions Inventory

NPRM Notice of Proposed Rulemaking

PB-HAP Persistent and Bioaccumulative - HAP

POM Polycyclic organic matter

REL Reference exposure level

RfC Reference concentration

RfD Reference dose

RME Reasonable Maximum Exposure

RTR Risk and Technology

TOSHI Target-organ-specific hazard index

URE Unit risk estimate
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1 Introduction

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

addressing emissions of hazardous air pollutants (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 

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

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

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

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

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

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

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

Key Recommendations of the SAB Review of RTR Risk Assessment Methodologies” [4].

This document contains the methods and the results of baseline risk assessments performed 

for the Primary Aluminum Production source category. The methods discussion includes 

descriptions of the methods used to screen for acute health risks, chronic non-inhalation 

health risks, and adverse environmental effects, as well as descriptions of the methods used to 

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

and noncancer endpoints.

2 Methods

2.1 Emissions and source data

The preliminary dataset was based on information in the 2005 National Air Toxics 

Assessment (NATA) Inventory. This information was then supplemented with test data and 

other information through an Information Collection Request (ICR), received in April 2011, 

from 11 of the 15 facilities in the source category. These ICR data were then used along with 

the 2005 NATA inventory data to develop the emissions dataset for this source category. We 
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then performed an engineering review of the information using EPA engineers to identify

readily apparent limitations and issues with the emissions data. Notably, one facility in this 

source category, Columbia Falls, has not been fully operational since 1999 and has been 

completely closedbeen idle for 2approximately 4 years and therefore we did not receive recent 

emissions data to calculate risks based on actual emissions. However, we did estimate risks 

based on estimates of MACT allowable emissions for this one facility to provide an indication 

of what risks it might pose if it were to re-open. Details on the development of the emissions 

and source data for this source category, including the estimation of allowable emissions from 

the Columbia Falls facility, are discussed in: Draft Summary Primary Aluminum RTR 

Modeling File Development, available in the docket for this rulemaking. Section 3 below 

provides a summary of the emissions. 

2.2 Dispersion modeling for inhalation exposure assessment

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

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

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

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

system is outlined below, and further details are provided in Appendix 1. 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.

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.
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Table 2.2-1 AERMOD version 09292 model options for RTR 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, to 

minimize data processing time and resources for this assessment, 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 2

(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 system 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 impacts of multiple facilities when estimating 

concentration impacts at each block centroid. Typically we combined only the impacts of 

facilities within the same source category, and assessed chronic exposure and risk only for 

census blocks with at least one resident (i.e., locations where people may reasonably be 

assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient 

concentrations were calculated as the annual average of all estimated short-term (one-hour) 

concentrations at each block centroid. Possible future residential use of currently uninhabited 

areas was not considered. Census blocks, the finest resolution available in the census data, 

are typically comprised of approximately 40 people or about ten households. 
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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 typically applied the general 

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 (see Appendix 3)1.

However, for this source category, an engineering analysis demonstrated that peak 1-hour 

emissions are approximately 5 times average hourly emissions, and thus a factor of 5, rather 

than the default factor of 10 was used in the acute risk assessment.

2 3

. However, for this 

source category, an engineering analysis demonstrated that peak 1-hour emissions are 

approximately 5 times average hourly emissions, and thus a factor of 5, rather than the default 

factor of 10 was used in the acute risk assessment.

4

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 all the major HAP-emitting sources 

located in an area of Texas near Houston (originally reported on by Allen et al. 2004)[7]. In 

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

annual emissions data for volatile organic compounds for all facilities in a heavilyindustrialized 4-county area (Harris, Galveston, Chambers, and Brazoria Counties, TX) over 

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

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

over short periods of time (see Appendix 3, “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 screening; it is intended to cover routinelyvariable emissions. While there have been some documented emission excursions above this 

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

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

emissions from typical industrial sources. We have no data relating specifically to peak short1

In situations where we have information on hourly emissions, we will take this into account when evaluating 

acute risks.

2

Justification for applying an acute factor of 5 rather than the default value of 10 can be found in the memo 

“Acute Risk Modeling of Primary Aluminum Potroom Emissions” which is located in the docket supporting the 

proposed rulemaking.

3

In situations where we have information on hourly emissions, we will take this into account when evaluating 

acute risks.

4

Justification for applying an acute factor of 5 rather than the default value of 10 can be found in the memo 

“Acute Risk Modeling of Primary Aluminum Potroom Emissions” which is located in the docket supporting the 

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

this same default approach for particulate emissions as well.

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 

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 1. 

2.3 Estimating chronic 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 (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 (note 

that the MIR can be estimated for each source as well as for the entire source category); 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 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. 
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When screening for potentially significant acute exposures, we used an estimate of the highest 

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

potential acute exposure concentration for any individual.

2.4 Screening for potential acute impacts of concern

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

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

developing chronic health risk assessments for other rules under the residual risk program. 

That is, we developed a tiered, iterative approach. This approach to risk assessment was

endorsed by the National Academy of Sciences in its 1993 publication “Science and Judgment 

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

Congress” in 1999. 

With respect to screening for potential acute health risks, 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 began with a screening 

assessment, which relies on readily available data and uses conservative assumptions that in 

combination approximate a worst-case exposure. The result of this screening process is that 

either the facility being assessed poses no potential acute health risks (i.e., it “screens out”), or 

that it requires further, more refined assessment with respect to potential acute exposures from

emitted HAP. A more refined acute assessment could use industry- or site-specific data on 

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

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

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

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

not necessary.

Acute health risk screening was performed for each facility as the first step. We used 

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

the following worst-case assumptions in our screening approach:

• Peak 1-hour emissions were assumed to equal 5 times the average 1-hour emission 

rates except in the case of fugitive dust (see section 2.2)

• 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 at the nearest NWS site) was assumed to 

occur at the same time the peak emission rates occur. The recommended EPA localscale dispersion model, AERMOD, was used for simulating atmospheric dispersion

during this worst-case hour.
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• A person was assumed to be located downwind at the point of maximum modeled 

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

meters. As a result, the maximum modeled 1-hour off-site concentration equals the

worst-case acute exposure concentration.

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

HAP being assessed to determine whether 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 to the extent possible. In some 

cases, this may include the use of a facility-specific emissions multiplier to estimate the peak 

hourly emission rates from the average rates (rather than the default factor of 10, as is the case 

for this source category, see section 3.2). In other cases, this may entail determining the 

actual physical layout and boundaries of a facility to more accurately gauge where people 

might reasonably be exposed for an hour.

2.5 Multipathway human health and environmental risk screening

The potential for significant human health risks and adverse environmental impacts due to 

exposures via routes other than inhalation (i.e., multipathway exposures) was screened by first 

determining whether any sources emitted any hazardous air pollutants known to be persistent 

and bioaccumulative in the environment (PB-HAP). The PB-HAP compounds or compound 

classes are identified for the screening from the EPA’s Air Toxics Risk Assessment Library

[8], and they 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. 

With respect to PB-HAP other than lead, emissions were evaluated for potential noninhalation risks and adverse environmental impacts using our recently-developed screening 

scenario which was developed for use with the TRIM.FaTE5 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.6In

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 4 for a complete discussion of the development and testing 

of the screening scenario, as well as for the values of facility-level screeningde minimis

emission rates developed for screening potentially significant multi-pathway impacts. In 

general, for the purpose of developing emission rates for our multi-pathway screening, we 

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

6

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

http://www.epa.gov/epaoswer/hazwaste/combust/riskvol.htm#volume1
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derived emission levels for each PB HAP at which the maximum human health risk would be 

1 in a million for lifetime cancer risk or a hazard quotient of 1.0 for noncancer impacts. 

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

developing a screening emission rate, we generally compare maximum estimated chronic (3-

month average) atmospheric concentrations with the current primary National Ambient Air 

Quality Standard (NAAQS) for lead. Values below the NAAQS are considered to have a low 

potential for multi-pathway risks. Notably, for this source category, POM was the only PBHAP identified in the emissions inventory.

We also evaluated the potential for significant direct environmental exposures to HAP by

evaluating the potential for exceedances of chronic human health inhalation reference values 

in the ambient air near these facilities. Human health dose-response reference 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 reference values 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 HAP 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 (i.e., is below the human health reference value which is itself a lower 

reference value than would be expected for an ecologic effect), 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 HAP, we note that as an uncertainty and, where possible, 

refine our analysis by comparing our modeled impacts to available reference values from the 

scientific literature.

2.6 Dose-response assessment

2.6.1 Sources of chronic dose-response information 

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

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

Aluminum Production sources were based on the EPA Office of Air Quality Planning and 

Standards’ (OAQPS) existing recommendations for HAP [9], also used for NATA 1999, 

2002, and 2005 [10]. This information has been obtained from various sources and prioritized 

according to (1) conceptual consistency with EPA risk assessment guidelines and (2) level of 

peer review received. The prioritization process was aimed at incorporating into our 

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

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

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

assessments for chronic exposure for many of the pollutants in this study. These 
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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/m3in 

air.” The SF is “an upper bound, approximating a 95% confidence limit, on the increased

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

units of proportion (of a population) affected per mg/kg-day...” EPA disseminates doseresponse assessment information in several forms, based on the level of review. The 

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

health assessment information, including dose-response information. All IRIS assessments 

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

process includes review by EPA scientists, interagency reviewers from other federal 

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

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

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

and scheduling of current individual IRIS assessments and updates 

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

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

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

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

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

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

inhalation exposure that are based on a nonlinear MOA.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Environmental Health Hazard Assessment has developed dose-response assessments for 

many substances, based both on carcinogenicity and health effects other than cancer. The 
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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 assessments7: “The 

guidelines for developing chronic inhalation exposure levels incorporate many

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

includes available inhalation health risk guidance values expressed as chronic inhalation 

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

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

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

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

In developing chronic risk estimates, we adjusted dose-response values for some HAPs based 

on professional judgment, as follows: 

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

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

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

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

out from further assessment. 

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

(see Tables 2.6-1 (a) to 2.6-1 (c), we apply category-specific chemical speciation profiles 

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

category. 

3) Emissions from Primary Aluminum Production facilities include POM. A substantial 

proportion of POM reported to EPA’s national emission inventory (NEI) are 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 [17]. The NATA 

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

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

potency, for which we can apply the same URE. 

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

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

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

to develop the COS chronic screening level is provided in Appendix 7.8. The screening 

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

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

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

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

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

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

February 2000 (http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf)
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See section 5 of this document for a detailed discussion of exposure modeling 

uncertainties. 

The chronic screening level for COS is used only as a screening level assessment to 

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

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

The emissions inventory for the Primary Aluminum Production source category includes 

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

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

through (c).

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

Carcinogens

URE (unit risk estimate for cancer)8= cancer risk per •g/m3of 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. EPA ORD = EPA Office of Research and 

Development

Pollutant CAS Number9 URE5

(1/•g/m3)

Source

Naphthalene 91203 0.000034 CAL

Polycyclic Organic Matter10 (POM)

(as Benzo [a] pyrene toxic 

equivalent) 50328 0.0016 CAL

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

POM (as Benzo [a] pyrene toxic 

equivalent) 50328 10 CAL

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

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

a plausible upper limit to the true value. 

9 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.

10 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
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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 = US Agency for Toxic Substances Disease Registry. 

Pollutant CAS Number6 RfC 

(mg/m3)

Source11

Carbonyl sulfide 463581 0.163 ORD Screening Value

Hydrofluoric acid 7664393 0.014 CAL

Naphthalene 91203 0.003 IRIS - M

2.6.2 Sources of acute dose-response information 

Hazard identification and dose-response assessment information for preliminary acute 

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

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

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

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

Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelines 

(ERPGs), with the recognition that the ultimate interpretation of any potential risks associated 

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

level and any limitations expressed therein. Comparisons among different available 

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

found in an EPA document.

12

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

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

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

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

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

specified exposure duration. [19]. 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 

11 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.

12 See: 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.)
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Reference Concentrations (RfCs) for chronic exposures (and, in fact, California also has 

developed chronic RELs).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

possibly the international community in conjunction with chemical emergency response, 

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

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

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

releases at fixed facilities and from transport carriers.” The NAC/AEGL defines AEGL-1 and 

AEGL-2 as:

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

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

experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. 

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

exposure.”

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

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

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

ability to escape.”

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

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

irritation or certain asymptomatic, nonsensory effects. With increasing airborne 

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

Association (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [20] 

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 Primary Aluminum Production source category includes 

emissions of two 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.

Table 2.6-2 Dose-Response Values for Acute Exposure

Pollutant CAS Number

AEGL-1

(1-hr)

(mg/m3)

AEGL-2

(1-hr)

(mg/m3)

ERPG-1

(mg/m3)

ERPG-2

(mg/m3) REL 

Carbonyl sulfide 463581 140

Hydrofluoric acid 7664393 0.82 20 1.6 20 0.24

2.7 Risk characterization

2.7.1 General

The final product of the risk assessment is the risk characterization, in which the information 
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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 [21] 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 [22], in 2002 by the Agency’s information quality guidelines [23], and in the 

OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis13, and 

are incorporated in these assessments.

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

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

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

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

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

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

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

limitations.

For each carcinogenic HAP included in 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 [24], we applied 

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

Carcinogens [25]. 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 [26] 

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

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

13Memorandum 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)
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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.

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

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

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

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

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

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

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

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

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

this on possible health interpretations. 

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

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

RfCs incorporate generally conservative uncertainty factors in the face of uncertain 

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

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

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

Screening for potentially significant acute inhalation exposures also followed the HQ 

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

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

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

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

information is used to determine whether 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’ 

[27,28] default assumption of additivity of effects, and combine risks by summing them using 

the independence formula in the mixtures guidelines.

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

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

to aggregate HQs. In consideration of these mode-of-action differences, the mixtures 
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guidelines support aggregating effects of different substances in specific and limited ways. 

Consistent with these guidelines, we aggregated non-cancer HQs of HAPs that act by similar 

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

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

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

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

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

Although HQs associated with some pollutants have been aggregated into more than one 

TOSHI, this has been done only in cases where the critical dose affects more than one target 

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

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

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

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

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

interpreted carefully by health scientists and risk managers.

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

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

basis, not using the TOSHI approach.

2.7.3 Facility-wide risks

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

using facility-wide and source category data files developed by EPA through emission data 

updates from industry and refined EPA profiles for the source category. For this source 

category we did not receive facility-wide emissions, and therefore, a facility-wide assessment 

was not performed. However, most all primary aluminum production facilities are co-located 

with secondary aluminum production facilities and a facility-wide analysis will be part of the 

risk assessment that is currently being done for the secondary aluminum source category14. 

3 Risk results for the primary aluminum production source category

3.1 Source category description and results

The Primary Aluminum Production source category consists of facilities that produce 

aluminum from refined ore (alumina) using a reduction process whereby the alumina is 

dissolved in an electrolytic bath in reduction cells which are connected electrically in series to 

form “potlines” in the presence of fluoride. The main raw materials in this process are 

alumina (Al2O3), coke, pitch, and fluoride. The process of aluminum reduction includes 

passing a high electrical direct current from a carbon anode to a carbon cathode which results 

in purified molten aluminum sinking to the bottom of the reduction cell, beneath the 

electrolytic bath. 

14 The results of this analysis will be available in the docket for the secondary aluminum source category.
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There are currently 14 secondary aluminum smelters operating in the U.S. The NPRM data 

set for the Primary Aluminum Production category contains 14 facilities identified with a 

Primary Aluminum Reduction MACT code in the 2005 National-Scale Air Toxics 

Assessment (NATA) National Emissions Inventory (NEI), September 2010 version. All 14 of 

these facilities are identified as major sources in the NEI. 

The emissions in the Primary Aluminum Production source category NPRM data set (of 15

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

are approximately 6,000 tons per year. Air emissions from Primary Aluminum Production

facilities include 4 MACT regulated toxic air pollutants: polycyclic organic matter (POM), 

carbonyl sulfide, hydrofluoric acid, and naphthalene.

Table 3.1-1 Summary of Emissions from the Primary Aluminum Production Source Category and 

Availability of Dose-Response Values

HAPa

Emission

Estimates

(tpy)

Number of 

Facilities 

where HAP 

Reported or 

Estimated 

(14 facilities 

in NPRM

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate for 

Cancer?

Reference 

Concentration 

for Chronic 

Noncancer?

Health 

Benchmark 

Values for Acute 

Noncancer?

Carbonyl sulfide 4,564 13 Υ

c Υ

Hydrofluoric acid 1,351 13 Υ Υ

POM 91 14 Υ Υ

Naphthalene 0.72 14 Υ Υ

a Notes for how HAP were speciated for risk assessment:

• There were 15 total facilities, but actual emission estimates were not provided for the Columbia Falls facility. 

• 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). For this source 

category, all POMs are PAHs.

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.

C The chronic, noncancer health effects benchmark value for carbonyl sulfide is an ORD screening value.

3.2 Baseline risk characterization

This section presents the results of the risk assessment for the Primary Aluminum Production

source category based on the modeling methods described in the previous sections. All 

baseline risk results are developed using the best estimates of actual and MACT-allowable 

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

individual lifetime cancer risk, the maximum target organ specific chronic hazard index, and 

the cancer incidence. We also present results from our acute inhalation impact screening 

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 
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hazard at the highest exposure location. A detailed summary of the facility-specific risk 

assessment results is available in Appendix 5.

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

this source category. The results of the chronic inhalation cancer risk assessment indicate that 

the maximum lifetime individual cancer risk, considering actual emissions, could be up toas 

high as 30 in a million, driven by POM emissions primarily from pot line roof vents and 

anode bake furnaces. The maximum cancer risks for this source category exceeded a cancer 

risk of 1 in a million at 12 of 14 facilities. The total estimated cancer incidence from this 

source category based on actual emission levels is 0.005 excess cancer cases per year, or one 

excess case in every 200 years. Approximately 900 people were estimated to have cancer 

risks above 10 in a million and approximately 41,000 people were estimated to have cancer 

risks above 1 in a million considering all facilities in this source category. Based on 

engineering judgment, MACT-allowable emissions for this source category could be up toas 

high as 1.5 times actual emissions; thus considering MACT allowable emissions, the MIR 

could be up toas high as 50-in a million for the facilities presented in Table 3.2-1. 

In addition to the facilities presented in Table 3.2-1, we also estimated cancer risks for the 

Columbia Falls facility which has not been fully operational since 1999 and has been 

completely closed for 24 years, and thus, did not report actual emissions for the year 2010. 

For this facility, we calculated an estimate of allowable emissions to approximate the cancer 

risk should this facility resume its primary aluminum production operations.15 The results of 

this assessment indicated that should this plant resume its operations, cancer risk could be as 

high as 100-in a million, resulting predominantly from pot line roof vent emissions of POM.

With respect to chronic inhalation noncancer risk, we estimate a maximum TOSHI value of 

0.4 for the Primary Aluminum source category, with pot line vent emissions of HF

dominating those impacts. Considering MACT-allowable emissions, this maximum TOSHI 

value is estimated to be 0.6. With respect to Columbia Falls, should this facility resume its 

primary aluminum production operations, we estimate a maximum TOSHI value of 0.2

primarily from emissions of HF from pot line roof vents.

15 See the emissions chapter of the TSD document for a discussion of how emissions were calculated for the 

Columbia Falls facility (available in the docket for the proposed rulemaking).
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Table 3.2-1 Summary of Source Category Level Inhalation Risks for Primary 

Aluminum Production

Result HAP “Drivers”

Facilities in Source Category

Number of Facilities Estimated to be in Source 

Category 15 n/a

Number of Facilities Identified in NEI and 

Modeled in Preliminary Risk Assessment 1416 n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 

1 million) 30 POM

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 POM 

Greater than or equal to 1 in 1 million 12 POM 

Chronic Noncancer Risks

Maximum Developmental Hazard Index 0.4 hydrofluoric acid

Number of Facilities with Maximum Developmental Hazard Index:

Greater than 1 0 n/a

Refined Acute Noncancer Results

Maximum Acute Hazard Quotient

10

4

2

hydrofluoric acid (REL)

hydrofluoric acid (AEGL-1)

hydrofluoric acid (ERPG-1)

Number of Facilities With Potential for Acute 

Effects 8 hydrofluoric acid

Population Exposure

Number of People Living Within 50 

Kilometers of Facilities Modeled 3,300,000 n/a

Number of People Exposed to Cancer Risk:

Greater than or equal to 100 in 1 

million 0 n/a

Greater than or equal to 10 in 1 

million 900 n/a

Greater than or equal to 1 in 1 million 41,200 n/a

Number of People Exposed to Noncancer Developmental Hazard Index:

Greater than 1 0 n/a

Estimated Cancer Incidence (excess cancer 

cases per year) 0.005 n/a

Contribution of HAP to Cancer Incidence

POM 99%90% n/a

16 The Columbia Falls facility has not been fully operational since 1999 and has been completely closed for

2operated in approximately 4 years and therefore, EPA did not generate risk estimates based on actual emissions 

for this facility. However, as seen below, EPA did estimate risk based on MACT allowable emissions for this 

facility. 
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Table 3.2-2 Summary of Refined Acute Results for Secondary Aluminum Production 

Facilities

Refined Results

MAXIMUM ACUTE HAZARD 

QUOTIENTS

ACUTE DOSE-RESPONSE 

VALUES

Based on 

REL

Based on 

AEGL-1

Based on

ERPG-1

REL

(mg/m3)

AEGL-1 

(1-hr) 

(mg/m3)

ERPG-1 

(mg/m3)

HAP Max. 1-hr. Air 

Conc. (mg/m3)

hydrofluoric acid 3.0 10 4 2 0.24 0.82 1.6

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.

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.

For this source category, there were two pollutants that had relevant acute health effect 

screening values: carbonyl sulfide and hydrofluoric acid. With respect to carbonyl sulfide, we 

did not find any potential for acute health concerns for the 14 operational facilities based on 

their actual emissions. However, hydrofluoric acid emissions did not screen out. Our 

screening analysis showed that worst-case screening-level acute HQ values for hydrofluoric 

acid could exceed a value of 1 (based on the REL, AEGL-1, or ERPG-1) at 9 of the 14 

facilities. We refined our acute screening values somewhat by taking into account whether 

acute screening value locations identified in the initial screen were within a facility’s 

boundary (they must be off-site to represent a potential exposure to the general public, see 

Appendix 5 and Appendix 6). Considering this refinement, the highest HQ for hydrofluoric 

acid based on a REL is 10, based on an AEGL-1 is 4, and based on an ERPG-1 is 2 (see Table 

3.2-2). Moreover, after refinement, 8 of the 14 operational facilities show the potential for 

worst-case acute HQ values greater than 1 based on the REL, 4 of 14 facilities show the 

potential for worst-case acute HQ values greater than 1 based on the AEGL-1 and 45 of 14 

facilities show the potential for worst-case acute HQ values greater than or equal to 1 based 
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on the ERPG-1.17AEGL-1 and 4 of 14 facilities shows the potential for worst-case acute HQ 

values greater than or equal to 1 based on the ERPG-1

18

. Notably in humans, concentrations 

above the AEGL-1 or at or above the AEGL-1 and/or ERPG-1 for hydrofluoric acid are 

associated with reversible minor irritation of the skin and eyes, as well an increase in 

pulmonary inflammation. That being said, we note again that this is still a conservative, 

worst-case screen with built-in assumptions that bias the results high. As a result, there is 

considerable uncertainty as to whether concentrations of hydrofluoric acid above at the 

AEGL-1 or at or above the ERPG-1 benchmark value could actually occur near some of these 

facilities. Thus, these results only indicate that there may be some potential for acute health 

effects from emissions of hydrofluoric acid from facilities in this source category; they do not 

indicate that effects are actually occurring.

In addition to the analyses presented above, to screen for potential multipathway effects from 

emissions of PAHs, we compared actual PAH emission rates from 14 facilities in this source 

category to the screening value for PAHs described in section 2.5 (also see Appendix 43 for a 

more detailed discussion of screening emission rates). Results of this worst- case screen 

estimate that actual PAH emissions from all facilities exceed the PAH screening emission rate 

by as much as approximately 7,000 times. With respect to these exceedences of the worstcase multipathway screening level for PAHs, we note that this only indicates the potential for

multipathway-related cancer risks of concern from PAHs. That is, while in general, emission 

rates below the worst-case multipathway screening level indicate no significant potential for 

multipathway related health effects, emission levels above this worst-case screening level 

only indicate the potential for multipathway-related health risks of concern based on a worstcase scenario. Due to data limitations, we were not able to refine our multi-pathway analysis 

beyond the worst-case screening assessment. Thus, we note that these results are biased high 

for purposes of screening and are therefore subject to significant uncertainties. As a result, we 

cannot say whether multi-pathway risks may be a concern.concern; we can only say that we 

cannot rule them out.

With respect to the potential for significant and widespread environmental effects from non 

PB-HAP, and in particular hydrofluoric acid which can potentially have adverse effects on 

vegetation, we note that all chronic non-cancer HQ values for all pollutants considering actual 

emissions are well below 1 using human health reference values. Thus, we believe that it is 

unlikely that adverse environmental effects would occur at the actual HAP concentrations 

estimated in our human health risk assessment. 

3.3 Post-control risk characterization

The proposed changes to the current NESHAP (see discussion in the proposed rule) will have 

negligible effect on all the estimated risks associated with all the currently operating facilities 

17 Individual facility acute HQ values for all facilities can be found in Appendix 5, Table 4, of this document. 

Acute HQ values exceeding a value of 1 based on the REL were as follows: 10, 10, 9, 9, 5, 3, 2 and 2. Acute HQ 

values greater than a value of 1 based on the AEGL-1 were as follows: 4, 4, 3 and 3. Acute HQ values greater 

than or equal to a value of 1 based on the ERPG-1 were as follows: 2, 2, 1 and 1.

18
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in the Primary Aluminum category. For the one facility which is currently not operational 

(the Columbia Falls facility), however, the cancer MIR under MACT-allowable emissions 

would be reduced from 100 in a million to approximately 70 in a million, effectively capping 

the potential cancer risks from this facility should it resume operations19. 

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 sitespecific parameters and reasonably representative meteorology. If anything, the population 

exposure estimates are biased high by not accounting for short- or long-term population 

mobility, and by neglecting processes like deposition, plume depletion, and atmospheric 

degradation. Additionally, estimates of the maximum individual risk (MIR) contain 

uncertainty, because they are derived at census block centroid locations rather than actual 

residences. This uncertainty is known to create potential underestimates and overestimates of 

the actual MIR values for individual facilities, but, overall, it is not thought to have a 

significant impact on the estimated MIR for a source category. Finally, we did not factor in 

the possibility of a source closure occurring during the 70-year chronic exposure period, 

leading to a potential upward bias in both the MIR and population risk estimates; nor did we 

factor in the possibility of population growth during the 70-year chronic exposure period, 

leading to a potential downward bias in both the MIR and population risk estimates.

A sensitivity analysis performed for the 1999 NATA found that the selection of the 

meteorology dataset location could result in a range of chronic ambient concentrations which 

varied from as much as 17% below the predicted value to as much as 84% higher than the 

predicted value. This variability translates directly to the predicted exposures and risks in our 

assessment, indicating that the actual risks could vary from 17% lower to 84% higher than the 

predicted values.

We have purposely biased the acute screening results high, considering that they depend upon 

the joint occurrence of independent factors, such as hourly emissions rates, meteorology and 

human activity patterns. However, we note that there is an unquantified level of uncertainty

regarding the emission estimates and the nature of the worst-case conditions for estimating the 

worst-case impacts of acute emissions of fugitive dusts. The current set of assumptions used 

in deriving the estimate assumes the average hourly emission level (annual emissions divided 

by 8760 hours per year) to occur at the default worst-case meteorological conditions (low 

19 EPA is also proposing to lower the POM limit for existing pitch storage tanks, but we do not anticipate that 

this will have an appreciable effect on the risk estimates presented above since pitch storage tanks are not a 

significant driver of risk. 
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winds with a stable atmosphere). The actual risks may be higher or lower than the estimates 

based upon the current set of assumptions. In cases where multiple acute threshold values are 

considered scientifically acceptable we have chosen the most conservative of these threshold 

values, erring on the side of overestimating potential health risks from acute exposures. In the 

cases where these results indicated the potential for exceeding short-term health thresholds

post-controls, we refined our assessment by developing a better understanding of the 

geography of the facility relative to potential exposure locations. 

4.2 Uncertainties in the dose-response relationships

In the sections that follow, separate discussions are provided on uncertainty associated with 

cancer potency factors and for noncancer reference values. Cancer potency values are derived 

for chronic (lifetime) exposures. Noncancer reference values are generally derived for 

chronic exposures (up to a lifetime), but may also be derived for acute (•<24 hours), short-term 

(>24 hours up to 30 days), and subchronic (>30 days up to 10% of lifetime) exposure 

durations, all of which are derived based on an assumption of continuous exposure throughout 

the duration specified. For the purposes of assessing all potential health risks associated with 

the emissions included in an assessment, we rely on both chronic (cancer and noncancer) and 

acute (noncancer) benchmarks, which are described in more detail below.

Although every effort is made to identify peer-reviewed dose-response values for all HAPs

emitted by the source category included in an assessment, some HAP have no peer-reviewed 

cancer potency values or reference values for chronic non-cancer or acute effects (inhalation 

or ingestion). Since exposures to these pollutants cannot be included in a quantitative risk 

estimate, an understatement of risk for these pollutants at environmental exposure levels is 

possible.

Additionally, chronic dose-response values for certain compounds included in the assessment 

may be under EPA IRIS review and revised assessments may determine that these pollutants 

are more or less potent than currently thought. We will re-evaluate risks if, as a result of these 

reviews, a dose-response metric changes enough to indicate that the risk assessment may

significantly mischaracterize human health risk

Cancer assessment

The discussion of dose-response uncertainties in the estimation of cancer risk below focuses 

on the uncertainties associated with the specific approach currently used by the EPA to 

develop cancer potency factors. In general, these same uncertainties attend the development 

of cancer potency factors by CalEPA, the source of peer-reviewed cancer potency factors 

used where EPA-developed values are not yet available. To place this discussion in context, 

we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [29] (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 
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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).20 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.21

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

underestimate risk, EPA generally relies on conservative default approaches.22 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 

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

21 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.

22 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are 

generic approaches, based on general scientific knowledge and policy judgment, that are applied to various 

elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 

NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the 

option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to 

the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the 

agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be 

appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions 

are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly 

overestimate risk). See EPA 2004 An Examination of EPA Risk Assessment Principles and Practices, 

EPA/100/B-04/001 available at: http://www.epa.gov/osa/pdfs/ratf-final.pdf.
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choices, data, models and assumptions [30]. 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 are 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.23 However, unless scientific support is available to show 

otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target 

organ concordance. For a specific pollutant, qualitative differences in species responses can 

lead to either under-estimation or over-estimation of human cancer risks. 

(2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead 

to differences in risk predictions. For example, the measure of dose is commonly expressed 

in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, data may

support development of a pharmacokinetic model for the absorption, distribution, metabolism 

and excretion of an agent, which may result in improved dose metrics (e.g., average blood 

concentration of the pollutant or the quantity of agent metabolized in the body). Quantitative 

uncertainties result when the appropriate choice of a dose metric is uncertain or when dose 

metric estimates are themselves uncertain (e.g., as can occur when alternative 

pharmacokinetic models are available for a compound). Uncertainty in dose estimates may

lead to either over or underestimation of risk.

(3) For the quantitative extrapolation of cancer risk estimates from experimental animals to 

humans, EPA uses scaling methodologies (relating expected response to differences in 

physical size of the species), which introduce another source of uncertainty. These 

methodologies are based on both biological data on differences in rates of process according 

to species size and empirical comparisons of toxicity between experimental animals and 

humans. For a particular pollutant, the quantitative difference in cancer potency between 

experimental animals and humans may be either greater than or less than that estimated by

baseline scientific scaling predictions due to uncertainties associated with limitations in the 

test data and the correctness of scaled estimates. 

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, 

are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which 

there is a specified excess risk of cancer, which is used as the point of departure (or POD) for 

the remainder of the calculation. Statistical uncertainty in developing a POD using a 

benchmark dose (BMD) approach is generally addressed though use of the 95% lower 

confidence limit on the dose at which the specified excess risk occurs (the BMDL), 

decreasing the likelihood of understating risk. EPA has generally utilized the multistage 

model for estimation of the BMDL using cancer bioassay data (see further discussion below).

23 Per the EPA Cancer Guidelines: “The default option is that positive effects in animal cancer studies indicate 

that the agent under study can have carcinogenic potential in humans.” and “Target organ concordance is not a 

prerequisite for evaluating the implications of animal study results for humans.”
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(5) Extrapolation from high to low doses is an important, and potentially large, source of 

uncertainty in cancer risk assessment. EPA uses different approaches to low dose risk 

assessment (i.e., developing estimates of risk for exposures to environmental doses of an 

agent from observations in experimental or epidemiological studies at higher dose) depending 

on the available data and understanding of a pollutant’s mode of action (i.e., the manner in 

which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use 

of reliable, compound-specific, biologically-based risk models when feasible; however, such 

models are rarely available. The mode of action for a pollutant (i.e., the manner in which a 

pollutant causes cancer) is a key consideration in determining how risks should be estimated 

for low-dose exposure. A reference value is calculated when the available mode of action 

data show the response to be nonlinear (e.g., as in a threshold response). A linear low-dose 

(straight line from POD) approach is used when available mode of action data support a linear 

(e.g., nonthreshold response) or as the most common default approach when a compound’s 

mode of action is unknown. Linear extrapolation can be supported by both pollutant-specific 

data and broader scientific considerations. For example, EPA’s Cancer Guidelines generally

consider a linear dose-response to be appropriate for pollutants that interact with DNA and 

induce mutations. Pollutants whose effects are additive to background biological processes in 

cancer development can also be predicted to have low-dose linear responses, although the 

slope of this relationship may not be the same as the slope estimated by the straight line 

approach. 

EPA most frequently utilizes a linear low-dose extrapolation approach as a baseline sciencepolicy choice (a “default”) when available data do not allow a compound-specific 

determination. This approach is designed to not underestimate risk in the face of uncertainty

and variability. EPA believes that linear dose-response models, when appropriately applied 

as part of EPA’s cancer risk assessment process, provide an upper bound estimate of risk and 

generally provide a health protective approach. Note that another source of uncertainty is the 

characterization of low-dose nonlinear, non-threshold relationships. The National Academy

of Sciences has encouraged the exploration of sigmoidal type functions (e.g., log-probit 

models) in representing dose response relationships due to the variability in response within 

human populations. Another National Research Council (NRC) report [31] 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 
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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) [32]. It is important to note that 

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

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

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

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

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

model.

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

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

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

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

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

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

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

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

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

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

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

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

of uncertainty and variability.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure levels that are intended to be 

health-protective. That is, EPA and other organizations which develop noncancer reference 

values (e.g., the Agency for Toxic Substances and Disease Registry – ATSDR) utilize an 

approach that is intended not to underestimate risk in the face of uncertainty and variability. 

When there are gaps in the available information, uncertainty factors (UFs) are applied to 

derive reference values that are intended to be protective against appreciable risk of 

deleterious effects. Uncertainty factors are commonly default values24 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 

24 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are 

generic approaches, based on general scientific knowledge and policy judgment, that are applied to various 

elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 

NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the 

option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to 

the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the 

agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be 

appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions 

are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly 

overestimate risk). See EPA 2004 An examination of EPA Risk Assessment Principles and Practices,

EPA/100/B-04/001 available at: http://www.epa.gov/osa/pdfs/ratf-final.pdf. 
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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 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.25 To derive values that are intended to be “without 

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

EPA, 1993, 1994) which includes consideration of both uncertainty and variability.

EPA begins by evaluating all of the available peer-reviewed literature to determine noncancer endpoints of concern, evaluating the quality, strengths and limitations of the available 

studies. EPA typically chooses the relevant endpoint that occurs at the lowest dose, often 

using statistical modeling of the available data, and then determines the appropriate point of 

departure (POD) for derivation of the reference value. A POD is determined by (in order of 

preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of 

the dose or concentration at which the toxic response was not significantly elevated (no 

observed adverse effect level— NOAEL); or (3) use of the lowest observed adverse effect 

level (LOAEL).

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

the reference value (U.S. EPA 1994, 2002). 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., interindividual variability); (2) uncertainty in extrapolating from experimental animal data to 

humans (i.e., interspecies differences); (3) uncertainty in extrapolating from data obtained in a 

study with less-than-lifetime exposure (i.e., extrapolating from subchronic to chronic 

exposure); (4) uncertainty in extrapolating from a LOAEL in the absence of a NOAEL; and 

(5) uncertainty when the database is incomplete or there are problems with applicability of 

available studies. When scientifically sound, peer-reviewed assessment-specific data are not 

available, default adjustment values are selected for the individual UFs. For each type of 

uncertainty (when relevant to the assessment), EPA typically applies an UF value of 10 or 3 

with the cumulative UF value leading to a downward adjustment of 10-3000 fold from the 

selected POD. An UF of 3 is used when the data do not support the use of a 10-fold factor. If 

an extrapolation step or adjustment is not relevant to an assessment (e.g., if applying human 

toxicity data and an interspecies extrapolation is not required) the associated UF is not used. 

The major adjustment steps are described more fully below.

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

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

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

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

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

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

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

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

among humans.

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

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

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

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

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

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

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

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

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

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

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

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

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

Pharmacokinetic models are useful to examine species differences in pharmacokinetic 

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

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

toxicodynamic differences between animals and humans, and in many cases a 10-fold UF 

(with separate factors of 3 for toxicokinetic and toxicodynamic components) is used to 

account for expected species differences and associated uncertainty in extrapolating from 

laboratory animals to humans in the derivation of a reference value. If information on one or 

the other of these components is available and accounted for in the cross-species 

extrapolation, a UF of 3 may be used for the remaining component.

3) In the case of reference values for chronic exposures where only data from shorter 

durations are available (e.g., 90-day subchronic studies in rodents) or when such data are 

judged more appropriate for development of an RfC, an additional UF of 3 or 10-fold is 

typically applied unless the available scientific information supports use of a different value.

4) Toxicity data are typically limited as to the dose or exposure levels that have been 

tested in individual studies; in an animal study, for example, treatment groups may differ in 

exposure by up to an order of magnitude. The preferred approach to arrive at a POD is to use 

BMD analysis; however, this approach requires adequate quantitative results for a meaningful 

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. 
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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 

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

characterization as potential uncertainties. 
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5 References

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/EP

A-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. 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

8. 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. 

9. 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

10. US EPA, 2005. 1999 National Air Toxics Risk Assessment. 

http://www.epa.gov/ttn/atw/nata1999

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

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

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

13. 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.

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

Washington, DC: National Academy Press.
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15. 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. 

16. 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.

17. 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.

18. 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

19. 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

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

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

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

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

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

23. 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

24. 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

25. 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.

26. 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

27. 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
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28. 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.

29. 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

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

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

Trichloroethylene. National Academies Press, Washington DC.

32. 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.
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