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Draft

Residual Risk Assessment for the Ferroalloys Source Category

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

October 2011
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Table of Contents

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

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

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

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

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

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

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

2.6 Dose-response assessment......................................................................................... 12

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

2.6.2 Sources of acute dose-response information...................................................... 18

2.7 Risk characterization ................................................................................................. 21

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

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

3 Risk results for the Ferroalloys source category................................................................. 23

3.1 Source category description and results.................................................................... 23

3.2 Baseline risk characterization.................................................................................... 26

3.3 Post-control risk characterization.............................................................................. 33

4 General discussion of uncertainties and how they have been addressed ......................... 33

4.1 Exposure modeling uncertainties .............................................................................. 33

4.2 Uncertainties in the dose-response relationships....................................................... 34

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

Index of Tables

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

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

Table 2.6-1 (B) Dose-Response Values for Chronic Oral Exposure to Carcinogens............. 17

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

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

Table 2.6-1 (B) Dose-Response Values for Chronic Oral Exposure to Noncarcinogens....... 18

Table 2.6-3 Dose-Response Values for Acute Exposure ........................................................ 20

Table 3.1-1 Summary of Emissions from the Ferroalloys Source Category and Availability of 

Dose-Response Values............................................................................................................. 24

Table 3.2-1 Summary of Source Category Level Inhalation Risks for Ferroalloys................ 28

Table 3.2-2 Summary of Refined Acute Results for Ferroalloys............................................ 29

Table 3.2-3 Comparison of AERMOD Modeled to Ambient Manganese Concentrations 

Reported by Three Monitors in Close Proximity to the Eramet Facility ................................. 32

Appendices

Appendix 1 Emissions Inventory Support Memoranda

Appendix 2 Technical Support Document for HEM3 Modeling

Appendix 3 Meteorological Data for HEM3 Modeling
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Appendix 4 Analysis of data on short-term emission rates relative to long-term emission 

rates

Appendix 5 Technical Support Document for TRIM-Based Multipathway Screening 

Scenario for RTR: Summary of Approach and Evaluation

Appendix 6 Draft Detailed Risk Modeling Results

Appendix 7 Acute Impacts Refined Analysis

Appendix 8 Dispersion Model Receptor Revisions and Additions for Ferroalloys

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 (HAP) from stationary sources. In the first 

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

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

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

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

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

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

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

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

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

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

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

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

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

initial technology-based standard.

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

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

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

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 from the SAB Review of RTR risk Assessment Methodologies‖ [4].

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

implementation of the MACT standard) and the results of the post-control scenario risk 

assessment performed for the ferroalloys source category. The methods discussion includes 

descriptions of the methods used to develop refined estimates of chronic inhalation exposures 

and human health risks for cancer and noncancer endpoints, as well as descriptions of the 

methods used to screen for acute health risks, chronic non-inhalation health risks, and adverse 

environmental effects.

2 Methods

2.1 Emissions and source data

Data from a CAA section 114 information collection request (ICR) were used for this 

assessment. In 2010 we sent an ICR to the two companies which own the two facilities in the 

U.S. which we are aware are covered by the Ferroalloys Production MACT standard. The 

ICR requested available information regarding process equipment, control devices, point and 
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fugitive emissions, practices used to control fugitive emissions, and other aspects of facility 

operations, including stack parameters and locations. Additionally, we requested that the two 

facilities conduct emissions tests for certain HAP from specific processes that were 

considered representative of the industry. Pollutants tested included metal HAP (e.g., 

manganese, nickel compounds) hydrochloric acid, formaldehyde, mercury, polyaromatic 

hydrocarbons, and dioxins and furans. The results of these tests were submitted to EPA in the 

fall of 2010 and are available in the docket. Details on the development of the emissions and 

source data for this source category are discussed in the Appendix 1 memorandum, entitled 

Draft Modeling Emission Estimation Methodologies for Ferroalloy Facilities. 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 risks from 

each facility in the source category were estimated using the Human Exposure Model in 

combination with the American Meteorological Society/EPA Regulatory Model dispersion 

modeling system (HEM-AERMOD, or HEM3). The approach used in applying this modeling 

system is outlined below, and further details are provided in Appendix 2. The HEM3

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

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

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

discussed in other subsections of Sections 2 and 3.

The dispersion model in the HEM3 system, AERMOD version 09292, is a state-of-thescience Gaussian plume dispersion model that is preferred by EPA for modeling point, area, 

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

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

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

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

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

inventory into the 8,760 hours of the year.

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

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

summarized in Table 2.2-1 and are discussed further below.
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Table 2.2-1 AERMOD version 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) and user-supplied receptors

Terrain characterization Actual from USGS 1-degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option No

Meteorology 1 year representative NWS from nearest site (189 stations)

In HEM3, meteorological data are ordinarily selected from a list of 189 National Weather 

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

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

conditions at the subject facility. Ideally, when considering off-site meteorological data most 

site specific dispersion modeling efforts will employ up to five years of data to capture 

variability in weather patterns from year to year. However, because we had an insufficient 

number of appropriately formatted model input files derived from available meteorological 

data, we modeled only a single year, typically 1991. While the selection of a single year may 

result in under-prediction of long-term ambient levels at some locations, likewise it may result 

in over-prediction at others. For each facility identified by its characteristic latitude and 

longitude coordinates, the closest meteorological station was used in the dispersion modeling. 

The average distance between a modeled facility and the applicable meteorological station 

was 90 miles (145 km). Appendix 3 (Meteorological Data Processing Using AERMET for 

HEM3) provides a complete listing of stations and assumptions along with further details used 

in processing the data through AERMET. The sensitivity of model results to the selection of 

the nearest weather station and the use of one year of meteorological data is discussed in 

―Risk and Technology Review (RTR) Risk Assessment Methodologies‖ [2].

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

blocks (using the 2000 Census) and at other receptor locations that can be specified by the 

user. See Appendix 8 (Dispersion Model Receptor Revisions and Additions for the 

Ferroalloys Source Category) for a discussion of user receptors and centroid location changes 

specific to this source category. The model accounts for the effects of multiple facilities when 

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

impacts of facilities within the same source category, and assessed chronic exposure and risk 

only for census blocks with at least one 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 
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uninhabited areas was not considered. Census blocks, the finest resolution available in the 

census data, are typically comprised of approximately 40 people or about ten households. 

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

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

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

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

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

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

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

since the ICR data contains only annual emission totals, we generally apply the assumption to 

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

the average annual hourly emission rate for that source.

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

total number of operating hours in the year. This choice of a factor of ten for screening was 

originally based on engineering judgment. To develop a more robust peak-to-mean emissions 

factor, and in response to one of the key messages from the SAB consultation on our RTR 

Assessment Plan, we performed an analysis using a short-term emissions dataset from a

number of sources located in Texas (originally reported on by Allen et al. 2004)[7]. In that 

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

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

county area (Harris, Galveston, Chambers, and Brazoria Counties, TX) over an eleven-month 

time period in 2001. We obtained the dataset and performed our own analysis, focusing that 

analysis on sources which reported emitting high quantities of HAP over short periods of time 

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

rates). Most peak emission events were less than twice the annual average, and the highest 

was a factor of 74 times the annual average, and the 99th percentile ratio of peak hourly 

emission rate to the annual hourly emission rate was 9. Based on these results, we chose the 

factor of ten for all initial screening. These factors are intended to cover all possible hourly 

peaks associated with routinely-variable emissions. While there have been some documented 

emission excursions above this level, our analysis of 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 short-term emissions of particulate HAP. In the absence of 

source category-specific data, we use this same default approach for particulate emissions as 

well.

 

Census block elevations for HEM3 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 short- and 

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

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

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

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

all sectors within the innermost model ring.
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In addition to using receptor elevation to determine plume height, AERMOD adjusts the 

plume’s flow if nearby elevated hills are expected to influence the wind patterns. For details 

on how hill heights were estimated and used in the AERMOD modeling see Appendix 2. 

2.3 Estimating 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 

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

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

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

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

less. Second, basing exposure estimates on average ambient concentrations at census block 

centroids may underestimate or overestimate actual exposure concentrations at some 

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

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

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

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

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

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

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

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

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

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

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

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

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

number of people at specific risk levels. 

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

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

potential acute exposure concentration for any individual.

2.4 Acute Risk Screening and Refined Assessments

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

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

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

developed a tiered, iterative approach. This approach to risk assessment was endorsed by the 
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National Academy of Sciences in its 1993 publication ―Science and Judgment in Risk 

Assessment‖ and subsequently was adopted in the EPA’s ―Residual Risk Report to Congress‖ 

in 1999. 

The assessment methodology is designed to eliminate from further consideration those 

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

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

means that we 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. 

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

emissions, the layout of emission points at the facility, the boundaries of the facility, and/or

the local meteorology. In some cases, all of these site-specific data are used to refine the 

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

exposures are not a concern, and significant additional data collection is not necessary. 

Acute health risk screening was performed as the first step. We used conservative 

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

worst-case assumptions in our screening approach:

Peak 1-hour emissions were assumed to equal 10 times the average 1-hour emission 

rates

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

occur at all emission points at the same time.

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

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

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

hour. 

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

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

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

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

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

meters.

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

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

benchmarks are described in section 2.6 of this report.

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 includes the use of a refined emissions multiplier to estimate the peak hourly 

emission rates from the average rates (rather than the default factor of 10). In other cases, this 

entails determining the actual physical layout and boundaries of a facility to more accurately 

gauge where people might reasonably be exposed for an hour. 
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For the ferroalloys source category, maximum hourly emissions estimates were available, so 

we did not use the default emissions multiplier of 10. See the Appendix 1 memorandum 

Methodology for Estimation of Maximum Hourly Emissions for Ferroalloys Sources for the 

detailed description of how the maximum hourly emissions were developed for the ferroalloys 

source category. We also conducted a review of the layout of the emission points at the 

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

facilities that did not screen out during the initial run. Refer to Appendices 6 and 7 for the 

detailed results for these sites. 

2.5 Multipathway human health and environmental risk screening

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

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

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

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

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

PB-HAP are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, 

heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury 

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

toxaphene, and trifluralin. Emissions of lead, mercury, and POM were identified in the 

emissions inventory for the ferroalloys source category. 

These PB-HAP emissions were evaluated for potential non-inhalation risks and adverse 

environmental impacts using our recently-developed screening scenario which was developed 

for use with the TRIM.FaTE2 model. This screening scenario uses environmental media 

outputs from the peer-reviewed TRIM.FaTE to estimate the maximum potential ingestion 

risks for any specified emission scenario by using a generic farming/fishing exposure scenario 

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

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

(HHRAP) for hazardous waste combustion facilities.3 In the development of the screening 

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

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

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

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

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

multipathway impacts. For the purpose of developing emission rates for our multipathway 

screening, we derived emission levels for each PB-HAP (other than lead) 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. 

 

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

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

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

document). 

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

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

http://www.epa.gov/epaoswer/hazwaste/combust/riskvol.htm#volume1
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In evaluating the potential multipathway risks from emissions of lead compounds, rather than 

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

atmospheric concentrations with the current National Ambient Air Quality Standard 

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

multipathway risks.

The NAAQS value, a public health policy judgment, incorporated the Agency’s most recent 

health evaluation of air effects of lead exposure for the purposes of setting a national ambient 

air quality standard. In setting this value, the Administrator promulgated a standard that was 

requisite to protect public health with an adequate margin of safety. We consider values 

below the level of the primary NAAQS to protect against multipathway risks because as 

mentioned above, the primary NAAQS is set as to protect public health with an adequate 

margin of safety. However, ambient air lead concentrations above the NAAQS are 

considered to pose the potential for increased risk to public health. We consider this NAAQS 

assessment to be a refined analysis given: 1) the numerous health studies, detailed risk and 

exposure analyses, and level of external peer and public review that went into the 

development of the primary NAAQS for lead, combined with: 2) the site-specific dispersion 

modeling used in this assessment to estimated ambient lead concentrations due to ferroalloys 

emissions. It should be noted, however, that this comparison does not account for possible 

population exposures to lead from sources other than the one being modeled; for example, via 

consumption of water from untreated local sources or ingestion of locally grown food. 

Nevertheless, the Administrator judged that such a standard would protect, with an adequate 

margin of safety, the health of children and other at-risk populations against an array of 

adverse health effects, most notably including neurological effects, particularly 

neurobehavioral and neurocognitive effects, in children (73 FR 67007). The Administrator, in 

setting the standard, also recognized that no evidence-or risk based bright line indicated a 

single appropriate level. Instead a collection of scientific evidence and other information was 

used to select the standard from a range of reasonable values (73 FR 67006).

We further note that comparing ambient lead concentrations to the NAAQS for lead, 

considering the level, averaging time, form and indicator, also informs whether there is the 

potential for adverse environmental effects. This is because the secondary lead NAAQS, set 

to protect against adverse welfare effects (including adverse environmental effects), has the 

same averaging time, form, and level as the primary standard. Thus, ambient lead 

concentrations above the NAAQS for lead also indicate the potential for adverse 

environmental effects.

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

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

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

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

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

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

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

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

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

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

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

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

from the scientific literature.

2.6 Dose-response assessment

2.6.1 Sources of chronic dose-response information 

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

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

sources were based on the EPA Office of Air Quality Planning and Standards’ (OAQPS) 

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

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

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

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

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

sources, in order of priority: 

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

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

assessments typically provide a qualitative statement regarding the strength of scientific 

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

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

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

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

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

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

during a lifetime.‖ The RfD is ―an estimate (with uncertainty spanning perhaps an order 

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

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

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

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

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

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

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

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

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

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

extrapolation as a default option for carcinogens for which the mode of action (MOA) has 

not been identified. We expect future EPA dose-response assessments to identify 

nonlinear MOAs where appropriate, and we will use those analyses (once they are peer 

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

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

nonlinear MOA.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Environmental Health Hazard Assessment has developed dose-response assessments for 

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

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

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

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

guidelines for developing chronic inhalation exposure levels incorporate many 

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

includes available inhalation health risk guidance values expressed as chronic inhalation 

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

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

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

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

 

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

on professional judgment, as follows: 

1) In the case of nickel compounds, to provide a health-protective estimate of potential 

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

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

 

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

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

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

February 2000 (http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf)
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subsulfide was considered a major factor for estimating the extent and magnitude of the 

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

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

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

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

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

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

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

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

5

, International Agency for Research 

on Cancer (IARC)

6

, and other international agencies)7that consider all nickel compounds 

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

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

―combined results of epidemiological studies, mechanistic studies, and carcinogenic 

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

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

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

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

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

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

review by Grimsrud et al., 20108). The major scientific bodies mentioned above have also 

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

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

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

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

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

nickel subsulfide. In addition, given that there are two additional URE values9derived for 

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

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

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

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

compounds. 

 

5

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

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

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

6

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

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

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

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

Environmental Risks (SCHER, 2006).

8

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

Med Toxicol 2010, 5:1-7. Available online at http://www.ossup-med.com/content/5/1/7.

9

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

developed by the California Department of Health Services 

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

Environmental Quality (http://www.epa.gov/ttn/atw/nata1999/99pdfs/healtheffectsinfo.pdf).
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2) Where possible for emissions of unspecified mixtures of HAP categories such as metal 

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

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

3) 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 are used in NATA [17]. The NATA 

approach partitions POM into eight different non-overlapping ―groups‖ that are modeled 

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

potency, for which we can apply the same URE.

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

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

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

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

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

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

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

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

10

 EPA will 

follow the NAS Report recommendations and will present results obtained by 

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

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

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

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

component of implementing the BBDR model. In the interim, we will present findings 

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

information as the science evolves. 

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

available chronic quantitative inhalation dose-response values. Of these, 23 are classified as 

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

available. These 23 HAP, their quantitative inhalation chronic cancer dose-response values, 

and the source of each value are listed in Table 2.6-1.A. The POM compounds with chronic 

oral cancer dose-response values available (for which multipathway screening assessments 

were performed) are listed in Table 2.6-1.B. Eleven HAP have quantitative inhalation chronic 

noncancer threshold values available; one of these eleven HAP (mercury), for which a 

multipathway assessment was performed, also has quantitative oral chronic noncancer 

threshold values available. These 11 HAP, their threshold values, and the source of the value 

are listed in Table 2.6-2.A and Table 2.6-2.B. 

 

10

 http://www.nap.edu/catalog.php?record_id=13142
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Table 2.6-1 (A) Dose-Response Values for Chronic Inhalation Exposure to 

Carcinogens

URE (unit risk estimate for cancer)11 = cancer risk per μg/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

Pollutant CAS Number12 URE5

(1/μg/m3)

Source

Arsenic Compounds 7440382 4.3E-3 IRIS

Chromium (VI) 18540299 1.2E-2 IRIS

Formaldehyde13 50000 1.3E-5 IRIS

Naphthalene 91203 3.4E-5 CAL

Nickel Compounds 7440020 4.8E-4 EPA OAQPS

Polycyclic Organic Matter 246 14 EPA OAQPS

2-Methylnaphthalene 91576 8.8E-5 EPA OAQPS

Acenaphthene 83329 8.8E-5 EPA OAQPS

Acenaphthylene 206968 8.8E-5 EPA OAQPS

Anthracene 120127 8.8E-5 EPA OAQPS

Benz[a]Anthracene 56553 1.6E-4 CAL

Benzo[a]Pyrene 50328 1.6E-3 CAL

Benzo[b]Fluoranthene 205992 1.6E-4 CAL

Benzo[e]Pyrene 192972 8.8E-5 EPA OAQPS

Benzo[g,h,i]Perylene 191242 8.8E-5 EPA OAQPS

Benzo[k]Fluoranthene 207089 1.6E-4 CAL

Chrysene 218019 1.6E-5 CAL

Dibenzo[a,h]Anthracene 53703 1.6E-3 CAL

Fluoranthene 206440 8.8E-5 EPA OAQPS

Fluorene 86737 8.8E-5 EPA OAQPS

Indeno[1,2,3-c,d]Pyrene 193395 1.6E-4 CAL

Perylene 198550 8.8E-5 EPA OAQPS

Phenanthrene 85018 8.8E-5 EPA OAQPS

Pyrene 129000 8.8E-5 EPA OAQPS

 

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

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

a plausible upper limit to the true value. 

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

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

13 The EPA has used the CIIT value (5.5x10-9

per mg/m3) to characterize formaldehyde cancer risks in some 

instances. 

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

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

http://www.epa.gov/ttn/atw/nata2005/methods.html#pom
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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

Pollutant CAS Number9

SF

(1/mg/kg/d) Source

Polycyclic Organic Matter 246

Benz[a]Anthracene 56553 1.2 CAL

Benzo[a]Pyrene 50328 7.3 IRIS

Benzo[b]Fluoranthene 205992 1.2 CAL

Benzo[k]Fluoranthene 207089 1.2 CAL

Chrysene 218019 0.12 CAL

Dibenzo[a,h]Anthracene 53703 4.1 CAL

Indeno[1,2,3-c,d]Pyrene 193395 1.2 CAL

Table 2.6-2 (A) Dose-Response Values for Chronic Inhalation Exposure to 

Noncarcinogens

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

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

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

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

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

Registry, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and 

Standards

Pollutant CAS Number6 RfC 

(mg/m3)

Source15

Arsenic Compounds 174 0.000015 CAL

Chromium (VI) 18540299 0.0001 IRIS - L

Formaldehyde 50000 0.0098 ATSDR

Hydrochloric Acid 7647010 0.02 IRIS - L

Hydrofluoric Acid 7664393 0.014 CAL

Lead Compounds 182 0.00015 EPA OAQPS

Manganese 183 0.00005 IRIS - M

Mercury Compounds

Mercuric Chloride 7487947 0.00003 CAL

Mercury (elemental) 7439976 0.0003 IRIS - M

Naphthalene 91203 0.003 IRIS – L/M

Nickel Compounds 7440020 0.00009 ATSDR

 

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

RfD (reference dose) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a 

continuous oral 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

Pollutant CAS Number

RfD

(mg/kg/d) Source 16

Mercuric chloride17 7439976 0.0003 IRIS - H

2.6.2 Sources of acute dose-response information 

Hazard identification and dose-response assessment information for preliminary acute 

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

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

compared to both ―no effects‖ reference levels for the general public, such as the California 

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

Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelines 

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

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

level and any limitations expressed therein. Comparisons among different available 

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

found in a newly released EPA document [19].

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

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

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

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

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

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

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

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

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

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

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

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

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

developed chronic RELs).

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

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

 

16 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.

17 The multipathway exposure assessment for mercury included fate and transport analysis, that included 

separate oral exposure estimates for divalent mercury and methylmercury.
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Substances, and then reviewed and published by the National Research Council. As described 

in the Committee’s ―Standing Operating Procedures (SOP)‖

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

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

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

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

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

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

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

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

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

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

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

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

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

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

releases at fixed facilities and from transport carriers.‖ 

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

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

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

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

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

exposure.‖

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

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

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

ability to escape.‖

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

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

irritation or certain asymptomatic, nonsensory effects. With increasing airborne 

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

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

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

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

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

responses, could experience the effects described at concentrations below the 

corresponding AEGL.‖

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

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

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

concentrations for exposure of the general population (but not particularly sensitive persons) 
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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 ferroalloys source category includes emissions of six HAP

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

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

Table 2.6-3 Dose-Response Values for Acute Exposure

Pollutant CAS Number

AEGL-1

(1-hr)

(mg/m3)

AEGL-2

(1-hr)

(mg/m3)

ERPG-1

(mg/m3)

ERPG-2

(mg/m3) REL 

Arsenic Compounds 7440382 0.0002

Formaldehyde 50000 1.1 17 1.1 17 0.055

Hydrochloric Acid 7647010 2.7 33 2.7 33 2.1

Hydrofluoric Acid 7664393 0.82 20 0.82 20 0.24

Mercury (elemental) 7439976 1.7 2 0.0006

Nickel Compounds 7440020 0.006
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2.7 Risk characterization

2.7.1 General

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

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

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

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

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

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

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

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

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

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

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

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

are incorporated in these assessments.

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

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

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

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

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

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

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

limitations.

For each carcinogenic HAP included in 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 HAP are upper-bound 

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

zero.

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

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

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

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

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

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

 

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

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

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

Office of Science and Technology Policy (http://www.whitehouse.gov/omb/memoranda/fy2007/m07-24.pdf)
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small fraction of the total POM emissions may be reported as individual compounds, EPA 

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

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

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

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

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

to all unspeciated POM mixtures.

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

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

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

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

estimate of the number of cancer cases per year.

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

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

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

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

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

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

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

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

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

this on possible health interpretations. 

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

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

RfCs incorporate generally conservative uncertainty factors in the face of uncertain 

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

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

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

Screening for potentially significant acute inhalation exposures also followed the HQ 

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

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

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

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

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

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

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

the independence formula in the mixtures guidelines.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

delineation of ―safe‖ and ―unsafe‖ levels. Rather, the TOSHI is another measure of the 

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

interpreted carefully by health scientists and risk managers.

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

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

basis, not using the TOSHI approach.

3 Risk results for the Ferroalloys source category

3.1 Source category description and results

The ferroalloys production source category consists of major source facilities that produce 

ferroalloys containing manganese, such as ferromanganese and silicomanganese. A ferroalloy 

is an alloy of iron and one or more other elements, such as nickel, chromium, manganese, 

and/or silicon. Silicon metal is also typically considered a ferroalloy product. Ferroalloy 

products are consumed primarily in iron and steel making, where they are used to produce 

steel and cast iron products with enhanced or special properties. Ferroalloys production 

normally occurs when an electric arc furnace (EAF) is charged with raw materials to begin 

smelting the ores. The molten product is ―tapped‖ or poured from the furnace. Raw material 

and product handling (e.g., crushing and screening operations) also occur as part of the 

ferroalloy production process. The HAP emission sources at ferroalloys production facilities 

include open EAFs, semi-closed EAFs, tapping operations, metal oxygen refining (MOR)

processes, crushing and screening operations, ladle treatment, casting, and fugitive dust 

sources. The specific HAP that are emitted, and the quantity of these emissions, are related to 

the amount of HAP compounds present in the raw materials used. Metallic HAP expected to 

be emitted by the furnaces include arsenic, chromium, manganese, and nickel. Emissions of 
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polycyclic organic matter (POM), such as polycyclic aromatic hydrocarbon (PAH), are also 

expected but in relatively small quantities. Additionally, chlorine is present in coal, which is 

used as a raw material in the furnace, and thus hydrochloric acid emissions can be expected. 

We currently estimate that there are 2 ferroalloys production facilities operating in the U.S. 

The emissions for the ferroalloys source category data set are summarized in Table 3.1-1. 

The total HAP emissions for the source category are approximately 160 tons per year. Based 

on these data, the HAP emitted in the largest quantities are manganese compounds, 

hydrochloric acid, and lead compounds. Emissions of these three HAP make up 93 percent of 

the total emissions by mass. Persistent and bioaccumulative HAP (PB-HAP)

19 reported as 

emissions from these facilities include lead compounds, mercury compounds, and polycyclic 

organic matter. 

 

Table 3.1-1 Summary of Emissions from the Ferroalloys Source Category and Availability of DoseResponse Values

HAPa

Emission

Estimates

(tpy)

Number of 

Facilities 

where HAP 

Reported or 

Estimated 

(2 facilities 

in data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate for 

Cancer?

Reference 

Concentration 

for Noncancer?

Health 

Benchmark 

Values for Acute 

Noncancer?

Manganese Compounds 126 2

Hydrochloric Acid 17 2

Lead Compounds 8 2 c

Hydrogen fluorided8 2

Nickel Compounds 4 2

Formaldehyde 2 2

Naphthalene 0.7 2

Polycyclic Organic Matter

Acenaphthylene 0.7 2

Fluorene 0.6 2

Fluoranthene 0.5 2

2-Methylnaphthalene 0.4 2

Phenanthrene 0.4 2

Anthracene 0.2 2

Benzo[b]Fluoranthene 0.2 2

Acenaphthene 0.1 2

Chrysene 0.1 2

Benzo[e]Pyrene 0.09 2

Pyrene 0.09 2

Benz[a]Anthracene 0.06 2

Benzo[k]Fluoranthene 0.05 2

 

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

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

website for Fate, Exposure, and Risk Assessment at http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 
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Table 3.1-1 Summary of Emissions from the Ferroalloys Source Category and Availability of DoseResponse Values

HAPa

Emission

Estimates

(tpy)

Number of 

Facilities 

where HAP 

Reported or 

Estimated 

(2 facilities 

in data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate for 

Cancer?

Reference 

Concentration 

for Noncancer?

Health 

Benchmark 

Values for Acute 

Noncancer?

Benzo[g,h,i]Perylene 0.04 2

Indeno[1,2,3-c,d]Pyrene 0.04 2

Benzo[a]Pyrene 0.02 2

Dibenzo[a,h]Anthracene 0.01 2

Perylene 0.002 2

Mercury Compounds

Mercury (elemental) 0.3 2

Mercuric chloride 0.07 2

Arsenic Compounds 0.2 2

Chromium Compounds

 Chromium III 0.2 2

 Chromium (VI) 0.06 2

a Notes for how HAP were speciated for risk assessment:

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

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

reported mass is 100 percent metal.

Chromium emissions were speciated based on test data; hexavalent chromium data were collected from the EAF fabric 

filter outlets using EPA Method 316. See Appendix 1 (Draft Modeling Emission Estimation Methodologies for 

Ferroalloy Facilities) for more information). 

For emissions reported generically as ―mercury‖ or ―mercury & compounds,‖ emissions are speciated for this category 

as 80 percent ―mercury (elemental)‖ and 20 percent ―mercuric chloride.‖ Mercury speciation profiles can be found on 

the EPA’s Technology Transfer Network website for emissions inventories at 

http://www.epa.gov/ttn/chief/net/2005inventory.html#inventorydata. 

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).

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

average exposure estimates to the National Ambient Air Quality Standards (NAAQS) for lead (0.15 μg/m3). These NAAQS 

for lead were recently reviewed with revisions adopted in October 2008 (http://www.epa.gov/air/lead/actions.html). The 

primary (health-based) standard is a maximum or not-to-be-exceeded, rolling three-month average, measured as total 

suspended particles (TSP). The secondary (welfare-based) standard is identical to the primary standard.

d The hydrogen fluoride emissions presented here were included in the risk assessment, however they are based on using onehalf of the test detection limit. All emission tests for hydrogen fluoride were below the detection limit, so half of the 

detection limit was used. Therefore this estimate of emissions is likely an overestimate. The actual emissions are probably 

much lower and could be as low as zero. More information about the test and emissions estimates can be found in the 

memorandum Modeling Emission Estimation Methodologies for Ferroalloy Facilities, which is Appendix 1 to this risk 

document. 
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3.2 Baseline risk characterization

This section presents the results of the risk assessment for the ferroalloys source category. 

The basic chronic inhalation risk estimates presented here are the maximum individual 

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

present results from our acute inhalation impact screening assessments in the form of 

maximum hazard quotients, as well as the results of our preliminary screen for potential noninhalation risks from PB-HAP. Also presented are the HAP ―drivers,‖ which are the HAP 

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

highest exposure location, as well as our analysis of risks associated with the maximum 

allowed emissions under the current MACT standards. A detailed summary of the facilityspecific risk assessment results is available in Appendix 6.

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

category. The results indicate that the current maximum lifetime individual cancer risk posed 

by these two facilities could be up to 80 in a million, with arsenic, chromium, and nickel 

compounds from process fugitives as the major contributors to the risk. The total estimated 

cancer incidence from this source category is 0.002 excess cancer cases per year, or one 

excess case in every 500 years. Approximately 1,000 people were estimated to have cancer 

risks above 10 in a million and approximately 26,000 people were estimated to have cancer 

risks above 1 in a million considering the two facilities in this source category. 

The maximum chronic noncancer TOSHI value for the source category could be up to 90 

from emissions of manganese from process fugitives, with an estimated 28,000 people 

exposed to TOSHI levels above 1 due to manganese emissions and an estimated 30 people 

exposed to a TOSHI greater than 10 due to manganese emissions. Given that the results show 

a high TOSHI value, we provide some additional discussion of the manganese RfC associated 

with the inhalation of manganese and our confidence in the principal studies supporting the 

development of that RfC for context. In the case of manganese, the effect of concern was a 

decrease in visual reaction time in adult males who were occupationally exposed to 

manganese. The effects were seen at a dose-adjusted value of 0.05 mg/m3and then to derive 

the RfC, EPA divided this value by 1000 to account for uncertainties related to sensitive 

individuals (10x), use of the lowest exposure level at which effects were observed in lieu of a 

level without effects (10x), and due to database limitations (10x). We note that the 

concentration reflected in the maximum TOSHI of 90 (0.0045 mg/m3) is approximately a 

factor of 10 lower than the 0.05 mg/m3dose-adjusted effect level in an adult male work force 

and used in the derivation of the RfC. The population from which the effect level was derived 

was an adult male worker population, and that this population does not necessarily represent 

the general population. The EPA has ―medium confidence‖ (as used and described in the 

IRIS database) in the RfC value of 0.00005 mg/m3. The confidence level reflects the overall 

level of uncertainty in the principal studies, which were based on human occupational studies, 

and the database. Please see the full IRIS summary for manganese for further discussion of 

the RfC. 20 

 

20

 IRIS Manganese (1995) http://www.epa.gov/iris/subst/0373.htm
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Overall confidence in the principal studies (Roels et al., 1987, 1992) is ―medium‖. Neither of 

the principal studies identified a no observed adverse effect level (NOAEL) for 

neurobehavioral effects, nor did either study directly measure particle size or provide 

information on the particle size distribution. The 1992 study by Roels et al. did provide 

respirable and total dust measurements, but the 1987 study measured only total dust. 21 These 

limitations of the studies are mitigated by the fact that the principal studies found similar 

indications of neurobehavioral dysfunction, which was consistent with the results of other 

human studies. In addition, the 1992 Roels et al. study provides sufficient information to 

establish individual integrated exposures; the 1987 Roels et al. study did not.

Confidence in the database on manganese health effects is ―medium‖. The duration of 

exposure was relatively limited and the workers were relatively young in all of the principal 

and supporting studies. These temporal limitations raise concerns that longer durations of 

exposure and/or interactions with aging might result in the detection of effects at lower 

concentrations, as suggested by results from other studies. In addition, the studies, with the 

exception of the 1992 Roels et al. study in which manganese exposure was limited to 

manganese oxide, did not specify the species of manganese to which workers were exposed. 

It is not clear whether certain compounds or oxidation states of manganese are more toxic 

than others. Although the primary neurotoxicological effects of exposure to airborne 

manganese have been qualitatively well characterized by the general consistency of effects 

across studies, the exposure-effect relationship remains to be well quantified, and a no-effect 

level for neurotoxicity has not been identified in any of these studies thus far. Finally, the 

effects of manganese on development and reproduction have not been studied adequately. See 

the full IRIS summary for manganese for more information.

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

allowable under the MACT standards were also calculated for stack emissions for the two 

facilities.22 Risk estimates based on the actual emissions were then scaled up using these 

factors. (See Appendix 1 for a discussion of the development of the allowable factors.) Risk 

results from the inhalation risk assessment using the MACT-allowable stack emissions 

indicate that the maximum lifetime individual cancer risk could be as high as 100 in a million, 

and that the maximum chronic noncancer TOSHI value could be as high as 200 at the MACTallowable emissions level. Risks could be higher than these presented here if process fugitive 

emissions increase with increased stack emissions. 

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

Table 3.1-1 that has an acute benchmark, and the highest screening acute HQ value of 40 

(based on the acute REL for arsenic and nickel compounds) is shown in Table 3.2-1. For 

cases where the screening acute HQ was greater than 1, we further refined the estimates by 

determining the highest HQ value that is outside facility boundaries. Table 3.2-2 provides 

more information on the refined acute risk estimates for HAP that had an acute HQ greater 

 

21 Total and respirable dust concentrations were highly correlated, with the Mn content of the respirable fraction 

representing on average 25% of the manganese content in the total dust. The RfC is based on the respirable 

fraction.

22 MACT-allowable emissions were not calculated for process fugitive or fugitive emissions because the current 

MACT standard only has emission limits for stack emissions.
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than 1 for any benchmark. The highest refined worst-case acute HQ value is 10 (based on the 

acute REL for nickel compounds). 

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

Result HAP “Drivers”

Facilities in Source Category

Number of Facilities Estimated to be in 

Source Category 2 n/a

Number of Facilities Identified in NEI and 

Modeled in Risk Assessment 2 n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk 

(in 1 million) 80

23 nickel compounds, chromium 

compounds, arsenic compounds

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

nickel compounds, chromium 

compounds, arsenic compounds, 

POM72002, POM75002, 

POM76002, naphthalene

Greater than or equal to 1 in 1 million 2

nickel compounds, chromium 

compounds, arsenic compounds, 

POM72002, POM75002, 

POM76002, naphthalene

Chronic Noncancer Risks

Maximum Neurological Hazard Index 90 manganese compounds

Maximum Developmental Hazard Index 2

lead compounds, arsenic 

compounds

Number of Facilities with Maximum Neurological Hazard Index:

Greater than 1 2

manganese compounds, lead 

compounds

Number of Facilities with Maximum Developmental Hazard Index:

Greater than 1 1

lead compounds, arsenic 

compounds

Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 40

40

nickel compounds (REL)

arsenic compounds (REL)

Number of Facilities With Potential for 

Acute Effects 2

arsenic compounds, nickel 

compounds

 

23 The plausible range of URE values for nickel (2.4E-04 to 4.8E-04 per ug/m3

) gives rise to a range of estimates 

for the cancer MIR (50 to 80 in a million). The cancer incidence would also have a range of estimates, but due 

to presenting the results to one significant figure, there is no change in cancer incidence when using the lower 

end of the nickel URE range. Estimated population values are not scalable with the nickel URE range, but 

would be lower using the lower end of the range.
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Table 3.2-1 Summary of Source Category Level Inhalation Risks for Ferroalloys

Result HAP “Drivers”

Refined Acute Noncancer Results

Maximum Acute Hazard Quotient24 10

9

nickel compounds (REL)

arsenic compounds (REL)

Number of Facilities With Potential for 

Acute Effects 2

arsenic compounds, nickel 

compounds

Population Exposure

Number of People Living Within 50 

Kilometers of Facilities Modeled 37,000 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 1,000 n/a

Greater than or equal to 1 in 1 million 26,000 n/a

Number of People Exposed to Noncancer Neurological Hazard Index:

Greater than 10 30 n/a

Greater than 1 28,000 n/a

Number of People Exposed to Noncancer Developmental Hazard Index:

Greater than 1 600 n/a

Estimated Cancer Incidence (excess cancer 

cases per year) 0.002 n/a

Contribution of HAP to Cancer Incidence

nickel compounds 36% n/a

chromium compounds 24% n/a

arsenic compounds 24% n/a

POM72002 10% n/a

 

Table 3.2-2 Summary of Refined Acute Results for Ferroalloys

Refined Results Maximum Acute Hazard Quotients Acute Dose-Response Values

HAP

Max. 1-hr. 

Air Conc. 

(mg/m3)

Based on 

REL

Based on 

AEGL-1/

ERPG-1

Based on 

AEGL-2/

ERPG-2

REL

(mg/m3)

AEGL-1 

(1-hr) 

(mg/m3)

ERPG-1 

(mg/m3)

AEGL-2

(1-hr)

(mg/m3)

ERPG-2 

(mg/m3)

Arsenic 

compounds 0.007 9 n/a n/a 0.0002

Nickel 

compounds 0.3 10 n/a n/a 0.006

 

24

 As shown in Tables 2.6-3 and 3.2-2 there are no AEGL or ERPG values for arsenic or nickel. Additionally, 

there are no short-term occupational values for these metals to compare to the REL values. It should also be 

noted that there are no reference values available (including a lack of short-term occupational values) to assess 

any potential risks from acute exposure to manganese. 
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Notes on Refined Process:

1) The initial 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.

To identify potential multipathway health risks from PB-HAP other than lead, we first 

performed a screening analysis that compared emissions of PB-HAP emitted from the 

ferroalloys source category to screening emission rates (see section 2.5). The PB-HAP 

emitted by facilities in this category include mercury and POM (as benzo(a)pyrene toxicity 

equivalents, or TEQ). The two facilities in the source category reported emissions of these

PB-HAP, and both of them had emission rates greater than the screening emission threshold 

values for the pollutants indicating that there may be potential multipathway impacts of 

concern due to emissions of these pollutants from these two facilities. One facility’s emission 

rates of mercury exceeded the screening threshold by 30 times, while the other facility’s 

mercury emission rates exceeded the threshold by 7 times. For POM, one facility’s emission 

rates exceeded the screening threshold by 600 times, while the other facility’s emission rates

exceeded the threshold by 50 times. For mercury, exceeding the screening emission rate 

relates to a potential for creating a chronic noncancer hazard quotient in excess of 1. For 

POM, exceeding the screening emission rate relates to a potential for creating a cancer risk in 

excess of 1 in a million. 

For the two PB-HAP that did not screen out during our initial multipathway screening 

analysis, we refined our analysis somewhat with some additional site-specific information to 

develop an ―intermediate screen.‖ (See Appendix 5 for more information about this 

intermediate screen.) The additional site-specific information included the land use around 

the facilities, the location of fishable lakes, and local wind direction and speed. The result of 

this analysis was the development of site-specific emission screening thresholds for POM and 

mercury. Based on this intermediate screening analysis, neither facility screened out, 

meaning that we cannot rule out the potential for multipathway risks of concern impacts due 

to emissions of these pollutants from these two facilities. One facility’s emission rates 

exceeded the site-specific screening threshold for mercury by 4 times, while the other 

facility’s emission rates equaled the threshold value. For POM, one facility’s emissions rates 

exceeded the site-specific screening threshold for POM by 60 times, while the other facility’s 

emission rates exceeded the threshold by 5 times. We were unable to obtain the data 

necessary to conduct a fully refined assessment of multipathway risks from these two 

facilities.
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In evaluating the potential for multipathway effects from emissions of lead, modeled 

maximum annual lead concentrations were compared to the NAAQS for lead (0.15 μg/m3). 

Results of this analysis estimate that the NAAQS for lead could be exceeded at one of the two

facilities, largely due to process fugitive emissions. This analysis estimates that the annual 

lead concentrations could be as high as two times the NAAQS for lead, and if the maximum 

3-month rolling average concentrations were used, the result could be even greater 

concentrations above the NAAQS. However, this additional analysis was not conducted 

because, as shown below in the results for the post-control scenario risk assessment, the 

maximum annual lead concentration after controls is significantly below the NAAQS, with a 

value of 0.02 μg/m3. 

In addition to the model results presented above, for calendar year 2009, we also compared 

annual average AERMOD estimates of ambient manganese concentrations with those 

measured during a three to four month period in late 2009 at three monitors in close proximity

(within 0.5 to 2.5 kilometers) to the Eramet ferroalloys facility. More specifically, we 

compared the mean manganese concentrations from the EPA’s Schools Monitoring Initiative 

to the predicted manganese concentrations at model receptor locations in close proximity to 

these monitoring sites. The facility and monitors are shown in Figure 1. Results of this 

analysis are presented in Table 3.2-3 and indicate that at these three locations, annual average 

model predictions are generally within a factor of two (when looking at actual emissions)

when compared to mean monitored concentrations for the sample period at these sites. These 

results indicate that AERMOD estimates of ambient air manganese concentrations provide a 

reasonable representation of the measured manganese concentrations present in the ambient 

air near this facility.

These results also show that the mean monitored manganese concentrations over the sampling 

period were observed to be above the RfC for manganese for all three sites. It is important to 

note that the variability in the daily monitored values such that some samples were above the 

RfC and some were below. The daily values are highly variable and influenced by wind 

direction and speed. However, the RfC is protective of long-term exposures and should be 

evaluated over a longer time period. More information about the EPA’s School Air Toxics 

Initiative and the monitoring conducted around the Eramet facility can be found at 

http://www.epa.gov/schoolair/pdfs/MariettaTechReport.pdf.
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Table 3.2-3 Comparison of AERMOD Modeled to Ambient Manganese Concentrations 

Reported by Three Monitors in Close Proximity to the Eramet Facility

Location Annual Average

AERMOD Modeled

Manganese 

Concentration 

(μg/m3)

25

Mean Monitored

Manganese

Concentration 

(μg/m3)

26

95% Confidence Interval 

on the Mean (Monitored 

Manganese 

Concentrations)25

Model to 

Monitor 

Ratio

Neale Elementary 

School (Vienna, WV) 0.07 0.07 .015– 0.13 1.00

The Ohio Valley 

Educational Service 

Center (Marietta, OH)

0.11-0.19 0.11 0.11 – 0.21

1.00 -

1.73

Warren Elementary 

School (Marietta, OH) 0.07-0.29 0.146 0 – 0.34 0.48-1.98

 

25 Model estimate based on closest polar receptor to monitor location. In cases where the monitor location falls 

between several polar receptors the range of modeled concentrations across those receptors is provided.

26 Mean monitor concentrations from the 3-month sampling period and the 95 percent confidence intervals on the 

mean can be found at: http://www.epa.gov/schoolair/pdfs/MariettaTechReport.pdf (Table 1). The recorded 

sample values from the monitors can be found in Table 2.
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3.3 Post-control risk characterization

Process fugitive emissions of metal HAP are primarily driving the baseline risks. Given this, 

using the same risk assessment methods described above, we estimated what the risks would 

be if the two manganese facilities adopted control measures to limit process fugitive 

emissions (e.g., full building enclosure). Based on this scenario, we estimated (based on use 

of the same modeling assumptions and methodologies used for the baseline risk assessment) 

that the maximum chronic noncancer inhalation TOSHI value would be reduced to 2, from the

baseline estimate of 90. The number of people estimated to have a TOSHI greater than 1 

would be reduced from 28,000 to less than 10. With respect to cancer risk, given the control 

scenario described above, the cancer MIR would be reduced from 80 in a million (i.e., precontrols) to approximately 5 in a million (i.e., post-controls), with an estimated reduction in 

cancer incidence to 0.0004 excess cancer cases per year. In addition, the number of people 

estimated to have a cancer risk greater than or equal to 1 in a million would be reduced from 

26,000 to 1,300. 

We also note that post-control, the maximum worst-case acute refined HQ value would be 

reduced from a potential value of 10 to 0.3 (using the REL value for nickel compounds and 

the refinements described for the baseline acute assessment). 

Considering post-control emissions of multipathway HAP, mercury emissions are reduced 

approximately 88 percent, while POM emissions are reduced approximately 66 percent from 

the baseline emission rates. Based on our intermediate screening approach for multipathway 

risks, emissions of mercury ―screen out‖, or are reduced below the screening thresholds for 

both facilities, indicating no potential for multipathway impacts of concern due to mercury. 

However, emissions of POM (as benzo(a)pyrene TEQ) remain above the intermediate 

screening thresholds for both facilities (one by a factor of 20 and one by a factor of 2), 

indicating that we cannot rule out the potential for multipathway impacts of concern due to 

emissions of POM from these facilities using our intermediate screening approach. As 

mentioned above, the highest lead concentration after controls, 0.02 μg/m3, is well below the 

NAAQS, indicating a low potential for multipathway impacts of concern due to lead.

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 the exposure

analysis. The chronic ambient modeling uncertainties are considered relatively small in 

comparison, since we are using EPA’s refined local dispersion model with site-specific 

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 
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uncertainty is known to create potential underestimates and overestimates of the actual MIR 

values for individual facilities, but, overall, it is not thought to have a significant impact on 

the estimated MIR for a source category. Finally, we did not factor in the possibility of a 

source closure occurring during the 70-year chronic exposure period, leading to a potential 

upward bias in both the MIR and population risk estimates; nor did we factor in the possibility 

of population growth during the 70-year chronic exposure period, leading to a potential 

downward bias in both the MIR and population risk estimates.

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

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

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

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

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

predicted values.

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

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

human activity patterns. Furthermore, in cases where multiple acute threshold values are 

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

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

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

we refined our assessment by developing a better understanding of the geography of the 

facility relative to potential exposure locations. In this case, refining the assessment for the 

two facilities that did not screen out resulted in lower acute risks. 

4.2 Uncertainties in the dose-response relationships

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

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

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

chronic exposures (up to a lifetime), but may also be derived for acute ( -term 

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

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

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

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

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

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

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

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

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

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

possible.

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

may be under EPA IRIS review and revised assessments may determine that these pollutants 
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are more or less potent than currently thought. We will re-evaluate risks if, as a result of these 

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

significantly mischaracterize human health risk

Cancer assessment

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

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

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

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

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

we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [30] (herein 

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

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

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

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

described in the Cancer Guidelines.

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

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

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

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

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

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).27 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.28 

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.29 EPA also 

 

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

28 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.

29 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 
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uses the upper bound (rather than lower bound or central) estimates in its assessments, 

although it is noted that this approach can have limitations for some uses (e.g. priority setting, 

expected benefits analysis).

Such health risk assessments have associated uncertainties, some which may be considered 

quantitatively, and others which generally are expressed qualitatively. Uncertainties may vary 

substantially among cancer risk assessments associated with exposures to different pollutants, 

since the assessments employ different databases with different strengths and limitations and 

the procedures employed may differ in how well they represent actual biological processes for 

the assessed substance. EPA’s Risk Characterization Handbook also recommends that risk 

characterizations present estimates demonstrating the impact on the assessment of alternative 

choices, data, models and assumptions [31]. Some of the major sources of uncertainty and 

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

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

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

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

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

tumors would occur in humans.30 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 

 

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.

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

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

test data and the correctness of scaled estimates. 

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

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

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

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

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

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

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

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

(5) Extrapolation from high to low doses is an important, and potentially large, source of 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

approach. 

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

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

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

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

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

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

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

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

human populations. Another National Research Council (NRC) report [32] suggests that 

models based on distributions of individual thresholds are likely to lead to sigmoidal-shaped 

dose-response functions for a population. This report notes sources of variability in the 
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human population: ―One might expect these individual tolerances to vary extensively in 

humans depending on genetics, coincident exposures, nutritional status, and various other 

susceptibility factors...‖ Thus, if a distribution of thresholds approach is considered for a 

carcinogen risk assessment, application would depend on ability of modeling to reflect the 

degree of variability in response in human populations (as opposed to responses in bioassays 

with genetically more uniform rodents). Note also that low dose linearity in risk can arise for 

reasons separate from population variability: due to the nature of a mode of action and 

additivity of a chemical’s effect on top of background chemical exposures and biological 

processes.

As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight 

line approach from the BMDL. This is equivalent to using an upper confidence limit on the 

slope of the straight line extrapolation. The impact of the choice of the BMDL on bottom line 

risk estimates can be quantified by comparing risk estimates using the BMDL value to central 

estimate BMD values, although these differences are generally not a large contributor to 

uncertainty in risk assessment (Subramaniam et. al., 2006) [33]. It is important to note that 

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

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

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

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

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 
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deleterious effects. Uncertainty factors are commonly default values31 e.g., factors of 10 or 3, 

used in the absence of compound-specific data; where data are available, uncertainty factors 

may also be developed using compound-specific information. When data are limited, more 

assumptions are needed and more default factors are used. Thus there may be a greater 

tendency to overestimate risk—in the sense that further study might support development of 

reference values that are higher (i.e., less potent) because fewer default assumptions are 

needed. However, for some pollutants it is possible that risks may be underestimated.

For non-cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) 

for exposures via ingestion, and a Reference Concentration (RfC) for inhalation exposures. 

These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) 

of daily oral exposure (RfD) or of a continuous inhalation exposure (RfC) to the human 

population (including sensitive subgroups) that is likely to be without an appreciable risk of 

deleterious effects during a lifetime.32 To derive values that are intended to be ―without 

appreciable risk,‖ EPA’s methodology relies upon an uncertainty factor (UF) approach [34], 

[35] which includes consideration of both uncertainty and variability.

 

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

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

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

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

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

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

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

level (LOAEL).

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

the reference value [36]. While collectively termed ―UFs‖, these factors account for a number 

of different quantitative considerations when utilizing observed animal (usually rodent) or 

human toxicity data in a risk assessment. The UFs are intended to account for: (1) variation 

in susceptibility among the members of the human population (i.e., inter-individual 

variability); (2) uncertainty in extrapolating from experimental animal data to humans (i.e., 

interspecies differences); (3) uncertainty in extrapolating from data obtained in a study with 

 

31

 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. 

32 See IRIS glossary
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less-than-lifetime exposure (i.e., extrapolating from subchronic to chronic exposure); 

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

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

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

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

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

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

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

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

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

The major adjustment steps are described more fully below.

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

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

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

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

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

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

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

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

among humans.

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

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

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

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

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

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

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

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

analysis, which is not always possible. Use of a NOAEL is the next preferred approach after 

BMD analysis in determining a POD for deriving a health effect reference value. However, 

many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a 

NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3-fold is 

often applied. 

5) The database UF is intended to account for the potential for deriving an 

underprotective RfD/RfC due to a data gap preventing complete characterization of the 

chemical’s toxicity. In the absence of studies for a known or suspected endpoint of concern, a 

UF of 10 or 3-fold is typically applied.

There is no RfD or other comparable chronic health benchmark value for lead compounds. 

Thus, to address multipathway human health and environmental risks associated with 

emissions of lead from this facility, ambient lead concentrations were compared to the 

NAAQS for lead. In developing the NAAQS for lead, EPA considered human health 

evidence reporting adverse health effects associated with lead exposure, as well as an EPA 

conducted multipathway risk assessment that applied models to estimate human exposures to 

air-related lead and the associated risk (73FR at 66979). EPA also explicitly considered the 

uncertainties associated with both the human health evidence and the exposure and risk 

analyses when developing the NAAQS for lead. For example, EPA considered uncertainties 

in the relationship between ambient air lead and blood lead levels (73FR at 66974), as well as 

uncertainties between blood lead levels and loss of IQ points in children (73FR at 66981). In 

considering the evidence and risk analyses and their associated uncertainties, the EPA 

Administrator noted his view that there is no evidence- or risk-based bright line that indicates 

a single appropriate level. Instead, he noted, there is a collection of scientific evidence and 

judgments and other information, including information about the uncertainties inherent in 

many relevant factors, which needs to be considered together in making this public health 

policy judgment and in selecting a standard level from a range of reasonable values (73FR at 

66998). In so doing, the Administrator decided that, a level for the primary lead standard of 

0.15 μg/m3, in combination with the specified choice of indicator, averaging time, and form, 

is requisite to protect public health, including the health of sensitive groups, with an adequate 

margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and 

exposure analyses, and their associated uncertainties can be found in EPA’s final rule revising 

the lead NAAQS (73 FR 66970-66981, November 12, 2008). 

We also note the uncertainties associated with the health-based (i.e., primary) NAAQS are 

likely less than the uncertainties associated with dose-response values developed for many of 
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the other HAP, particularly those HAP for which no human health data exist. In 1988, EPA’s 

IRIS program reviewed the health effects data regarding lead and its inorganic compounds

and determined that it would be inappropriate to develop an RfD for these compounds, 

saying, ―A great deal of information on the health effects of lead has been obtained through 

decades of medical observation and scientific research. This information has been assessed in 

the development of air and water quality criteria by the Agency's Office of Health and 

Environmental Assessment (OHEA) in support of regulatory decision-making by the Office 

of Air Quality Planning and Standards (OAQPS) and by the Office of Drinking Water 

(ODW). By comparison to most other environmental toxicants, the degree of uncertainty 

about the health effects of lead is quite low. It appears that some of these effects, particularly 

changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral 

development, may occur at blood lead levels so low as to be essentially without a threshold. 

The Agency's RfD Work Group discussed inorganic lead (and lead compounds) at two 

meetings (07/08/1985 and 07/22/1985) and considered it inappropriate to develop an RfD for 

inorganic lead.‖ EPA’s IRIS assessment for Lead and compounds (inorganic) (CASRN 7439-

92-1), http://www.epa.gov/iris/subst/0277.htm. 

We note further that because of the multi-pathway, multi-media impacts of lead, the risk 

assessment supporting the NAAQS considered direct inhalation exposures and indirect airrelated multi-pathway exposures from industrial sources like primary and secondary lead 

smelting operations. It also considered background lead exposures from other sources (like 

contaminated drinking water and exposure to lead-based paints). In revising the NAAQS for 

lead, we note that the Administrator placed more weight on the evidence-based framework 

and less weight on the results from the risk assessment, although he did find the risk estimates 

to be roughly consistent with and generally supportive of the evidence-based framework 

applied in the NAAQS determination (73FR at 67004). Thus, when revising the NAAQS for 

lead to protect public health with an adequate margin of safety, EPA considered both the 

evidence-based framework and the risk assessment, albeit to different extents.

Acute noncancer assessment

Many of the UFs used to account for variability and uncertainty in the development of acute 

reference values are quite similar to those developed for chronic durations, but more often 

using individual UF values that may be less than 10. UFs are applied based on chemicalspecific or health effect-specific information (e.g., simple irritation effects do not vary 

appreciably between human individuals, hence a value of 3 is typically used), or based on the 

purpose for the reference value (see the following paragraph). The UFs applied in acute 

reference value derivation include: 1) heterogeneity among humans; 2) uncertainty in 

extrapolating from animals to humans; 3) uncertainty in LOAEL to NOAEL adjustments; and 

4) uncertainty in accounting for an incomplete database on toxic effects of potential concern. 

Additional adjustments are often applied to account for uncertainty in extrapolation from 

observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an 

acute reference value at another exposure duration (e.g., 1 hour). 

Not all acute reference values are developed for the same purpose and care must be taken 

when interpreting the results of an acute assessment of human health effects relative to the 
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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/E

PA-SAB-10-007-unsigned.pdf

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

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

Assessment Methodologies.

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

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

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

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

7. 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.
Draft Risk Assessment for the Ferroalloys Source Category –

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

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

Washington, DC: National Academy Press.

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. U.S. EPA, 2009. Graphical Arrays of Chemical-Specific Health Effect Reference Values for 

Inhalation Exposures [Final Report]. EPA/600/R-09/061, 2009. 

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

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

Exposure Levels developed by OEHHA as of May 2000. 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

EPA/630/R-03003F. http://www.epa.gov/ttn/atw/childrens_supplement_final.pdf.
Draft Risk Assessment for the Ferroalloys Source Category –

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

46

 

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

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

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

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

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

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

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

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

30. US EPA, 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

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

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

Trichloroethylene. National Academies Press, Washington DC.

33. 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.

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

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

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

Application of Inhalation Dosimetry. 

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

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

http://www.epa.gov/ncea/iris/RFC_FINAL1.pdf