Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

1

Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

May 2015
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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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................................ 11

2.6 Dose-response assessment......................................................................................... 16

2.6.1 Sources of chronic dose-response information .................................................. 16

2.6.2 Sources of acute dose-response information...................................................... 24

2.7 Risk characterization ................................................................................................. 28

2.7.1 General ............................................................................................................... 28

2.7.2 Mixtures ............................................................................................................. 30

2.7.3 MACT-Allowable Risks.................................................................................... 30

3 Risk results for the Ferroalloys source category................................................................. 31

3.1 Source category description and results.................................................................... 31

3.2 Baseline risk characterization.................................................................................... 34

3.3 Post-control risk characterization.............................................................................. 42

4 General discussion of uncertainties and how they have been addressed ......................... 43

4.1 Exposure modeling uncertainties .............................................................................. 43

4.2 Uncertainties in the dose-response relationships....................................................... 44

5 References........................................................................................................................ 54

Index of Tables

Table 2.2-1 AERMOD version 13350 model options for RTR modeling................................ 6

Table 2.6-1 (A) Dose-Response Values for Chronic Inhalation Exposure to Carcinogens.... 20

Table 2.6-1 (B) Dose-Response Values for Chronic Oral Exposure to Carcinogens............. 22

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

.................................................................................................................................................. 23

Table 2.6-1 (B) Dose-Response Values for Chronic Oral Exposure to Noncarcinogens....... 24

Table 2.6-3 Dose-Response Values for Acute Exposure........................................................ 28

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

Residual Risk Assessment and Availability of Dose-Response Values .................................. 32

Table 3.2-1 Summary of Source Category Level Inhalation Risks for Ferroalloys................ 35

Table 3.2-2 Summary of Source Category Level Multipathway Screening Assessment Risk 

Results for Ferroalloys............................................................................................................. 38

Table 3.2-3 Summary of Source Category Level Site-Specific Multipathway Risk Results for 

Ferroalloys Baseline Scenario.................................................................................................. 40

Table 3.2-4 Summary of Source Category Environmental Risk Screening Results for 

Ferroalloys ............................................................................................................................... 42
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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Appendices

Appendix 1 Emissions Inventory Support Memorandum

Appendix 2 Technical Support Document for HEM3 Modeling

Appendix 3 Meteorological Data for HEM3 Modeling

Appendix 4 Technical Support Document for TRIM-Based Multipathway Screening 

Scenario for RTR: Summary of Approach and Evaluation 

Appendix 5 Analysis of short-term emission rates relative to long-term emission rates

Appendix 6 Detailed Risk Modeling Results

Appendix 7 Acute Impacts Refined Analysis

Appendix 8 Dispersion Model Receptor Revisions and Additions for Ferroalloys

Appendix 9 Protocol for Developing a TRIM.FaTE Model Scenario

Appendix 10 Technical Support Document: Human Health Multipathway Residual Risk 

Assessment for the Ferroalloys Production Source Category

Appendix 11 Environmental Risk Screen

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model

AEGL Acute exposure guideline level

ASTDR US Agency for Toxic Substances and Disease Registry

CalEPA California Environmental Agency

ERPG Emergency Response Planning Guideline

HAP Hazardous Air Pollutant

HEM Human Exposure Model

HI Hazard index

HQ Hazard quotient

IRIS Integrated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of action

NAC National Advisory Committee

NAAQS National Ambient Air Quality Standards

NATA National Air Toxics Assessment

NEI National Emissions Inventory

NPRM Notice of Proposed Rulemaking

PAH Polynuclear Aromatic Hydrocarbon

PB-HAP Persistent and Bioaccumulative - HAP

POM Polycyclic organic matter

REL Reference exposure level

RfC Reference concentration

RfD Reference dose

RTR Risk and Technology

TOSHI Target-organ-specific hazard index

URE Unit risk estimate
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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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 

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

Review 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 several CAA section 114 information collection requests (ICR) were used for this 

assessment. In 2010 and 2012 we sent ICRs to the two companies which own the two 

facilities in the U.S. which we are aware are covered by the Ferroalloys Production MACT 
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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standard. The ICRs requested available information regarding process equipment, control 

devices, point and 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 (HCl), hydrogen fluoride (HF),

1

formaldehyde, mercury compounds, polynuclear aromatic hydrocarbons (PAH), 

polychlorinated biphenyls (PCB), and chlorodibenzodioxins and chlorodibenzofurans

(CDD/CDF). Also, additional test data were received during the comment period for the 

September 2014 supplemental proposal, and those data were incorporated into the emissions 

dataset. The results of these tests and data collection efforts are described in more detail in 

the memo Revised Development of the Risk and Technology Review (RTR) Emissions Dataset 

for the Ferroalloys Production Source Category for the 2015 Final Rule, available in the 

docket (EPA-HQ-OAR-2010-0895) and as Appendix 1 to this document. 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 (HEM) 

in combination with the American Meteorological Society/EPA Regulatory Model 

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

modeling system is outlined below, and further details are provided in Appendix 2 of this 

document (Technical Support Document for HEM3 Modeling). The HEM3 performs three 

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

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

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

other subsections of Sections 2 and 3.

The dispersion model in the HEM3 system, AERMOD version 13350, 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.

 

1 As explained in the memo Revised Development of the Risk and Technology Review (RTR) Emissions Dataset 

for the Ferroalloys Production Source Category for the 2015 Final Rule, test data were received from 4 furnaces 

for HF. All test results were below the detection limit of the test method. While we initially calculated 

numerical estimates based on the assumption that non-detects were equal to one-half of the detection limit and 

included these estimates in the inputs to the risk assessment, we have no evidence that HF is emitted from these 

sources.
Residual Risk Assessment for the Ferroalloys Source Category

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

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

summarized in Table 2.2-1 and are discussed further below.

Table 2.2-1 AERMOD version 13350 model options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point and area

Receptor orientation Polar (13 rings and 16 radials)

Discrete (census block centroids) and user-supplied receptors

Terrain characterization Actual from USGS 1-degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option Included if source in urbanized area

Meteorology 1 year representative NWS from nearest site (over 800

stations)

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

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

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

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

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

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

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

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

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

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

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

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

applicable meteorological station was approximately 30 miles (50 km). Appendix 3 of this 

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

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

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

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

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

Assessment Methodologies” [2].

Beginning with version 12345, AERMET allows for a minimum wind speed of 0.5 m/s to be 

utilized when processing monitoring stations that are equipped with sonic anemometers and 

for an adjustment to the surface velocity (u*). The public version of AERMET available at 

the time we conducted the modeling for this source category did not include the surface 
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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friction velocity adjustment. Also at that time, an updated version of AERMET (and 

AERMOD) was under development that incorporated further surface friction velocity 

adjustments to AERMET version 12345. In anticipation of the update, EPA processed 

meteorological data using a pre-public release version of AERMET and incorporated the 

updated surface friction velocity adjustment in the output. It was EPA’s judgment that the 

pre-public release version of AERMET would generate AERMOD-ready meteorological data 

very close to that generated with the final public release version. 

EPA has posted the AERMET meteorological data used in the ferroalloys analysis on the 

EPA’s FERA (Fate, Exposure, and Risk Analysis) website2under the HEM model page. 

AERMET and AERMOD (version 13350) were released to the public in late December 2013 

on the EPA’s Support Center for Regulatory Atmospheric Modeling (SCRAM) website.3

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

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

user. See Appendix 8 to this document (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 uninhabited areas was not considered. Census blocks, the finest 

resolution available in the census data, are typically comprised of approximately 50 people or 

about 20 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. More description of our short-term 

assessment can be found in Section 2.4 of this document - Acute Risk Screening and Refined 

Assessments.

 

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

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

 

2 The FERA webpage is http://www2.epa.gov/fera and the HEM3 webpage is http://www2.epa.gov/fera/riskassessment-and-modeling-human-exposure-model-hem

3 The SCRAM webpage is http://www.epa.gov/ttn/scram/. 
Residual Risk Assessment for the Ferroalloys Source Category

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

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

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

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

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

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

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

were estimated and used in the AERMOD modeling, see Appendix 2 of this document, 

Technical Support Document for HEM3 Modeling. 

2.3 Estimating chronic human inhalation exposure

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

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

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

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

influence on their exposure.

 

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

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

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

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

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

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

centroids may underestimate or overestimate actual exposure concentrations at some 

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

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

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

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

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

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

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

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

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

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

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

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

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

number of people at specific risk levels. 

2.4 Acute Risk Screening and Refined Assessments

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

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

developing chronic health risk assessments under the residual risk program. That is, we 
Residual Risk Assessment for the Ferroalloys Source Category

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

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

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

in 1999. 

The assessment methodology is designed to eliminate from further consideration those 

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

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

means that we 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 more refined acute assessment could use industry- or site-specific data on the temporal 

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

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

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

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

necessary. 

Acute health risk screening was performed for each facility as the first step. When we 

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

screening estimates to the extent possible. In some cases, this may include the use of a 

facility-specific emissions multiplier to estimate the peak hourly emission rates from the 

average rates (rather than the default factor of 10). In other cases, this may entail determining 

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

might reasonably be exposed for an hour.

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

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

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

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

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

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

source. (The average hourly 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 acute 

screening was originally based on engineering judgment. 

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

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

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

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

Consortium Project compared hourly and annual emissions data for volatile organic 

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

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

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

quantities of HAP over short periods of time (see Appendix 5 of this document, Analysis of 
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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

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

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

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

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

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

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

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

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

use this same default approach for particulate emissions as well.

For the ferroalloys source category, however, maximum hourly emissions estimates were 

available, so we did not use the default emissions multiplier of 10. See Appendix 1 to this 

document, Revised Development of the Risk and Technology Review (RTR) Emissions Dataset 

for the Ferroalloys Production Source Category for the 2015 Final Rule, which is also 

available separately in the docket, for the detailed description of how the maximum hourly 

emissions were developed for the ferroalloys source category. In general, some processes 

operate continuously so there are no peak emissions and these processes received a factor of 1 

(i.e., maximum hourly emissions equal annual average hourly emissions). Other processes, 

for example tapping and casting, have specific cycles, with peak emissions occurring for a 

part of that cycle (e.g., 30 minutes during a 2-hour period). For these processes, we used a 

factor of 4 in the acute assessment. 

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

benchmarks, we pursue refining our acute screening estimates to the extent possible. For the 

ferroalloys production source category, we conducted a review of the layout of the polar 

receptors around the facilities compared to the facility boundaries to determine the maximum 

off-site acute impact for the facilities that did not screen out during the initial run. 

Appendix 6 to this document (Detailed Risk Modeling Results) contains the initial acute 

results for the source category, while Appendix 7 to this document (Acute Impacts Refined 

Analysis), contains the refined acute results. 

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

location, and refined data where available. We used the following assumptions in our acute 

assessment approach:

 Peak 1-hour emissions were obtained from the emissions memo and based on the 

operating characteristics of ferroalloys production emission sources as described in 

Appendix 1.

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

occur at all emission points at the same time.

 We assumed that the peak emissions 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 
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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.

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)4. 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 (PCB), polycyclic organic matter

(POM), toxaphene, and trifluralin. Emissions of cadmium compounds, chlorinated 

dibenzodioxins and furans, lead compounds, mercury compounds, PCBs, and POM (of which 

PAH are a subset) were identified in the emissions inventory for the ferroalloys source 

category. 

With respect to PB-HAP emissions other than lead, emissions were evaluated for potential 

non-inhalation risks using a tiered screening approach which was developed for use with the 

EPA’s peer-reviewed Total Risk Integrated Methodology – Fate, Transport, and Ecological 

Exposure (TRIM.FaTE5) model. With this approach, we first determine whether the facilityspecific emission rates of each of the emitted PB-HAP are large enough to create the potential 

for significant non-inhalation human health risks under reasonable worst-case conditions. To 

facilitate this step, we developed emission rate screening levels for each PB-HAP using a 

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

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

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

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

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

scenario. The PB-HAP emissions from each facility in the source category were compared to 

 

4 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). 

5 EPA’s Total Risk Integrated Methodology (General Information) http://www2.epa.gov/fera/total-riskintegrated-methodology-trim-general
Residual Risk Assessment for the Ferroalloys Source Category

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the emission rate screening levels for each of the PB-HAP identified to assess the potential for 

significant human health risks via non-inhalation pathways. For the purpose of developing 

emission rates for the multipathway screen, we derived emission levels for each 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. We call this application of the 

TRIM.FaTE model the Tier I Screen. See Appendix 4 of this document (Technical Support 

Document for TRIM-Based Multipathway Screening Scenario for RTR: Summary of 

Approach and Evaluation) for a complete discussion of the development and testing of the 

screening scenario, as well as for the values of facility-level emission rates developed for 

screening potentially significant multipathway impacts. 

If the PB-HAP emissions for a facility exceed the Tier I screening emission rate, we conduct a 

Tier II multipathway screen. In the Tier II screen, the location of each facility that exceeded 

the Tier I emission rate is used to refine some of the assumptions associated with the 

environmental scenario while maintaining the exposure scenario assumptions. We then adjust 

the risk-based Tier I screening level for each PB-HAP for each facility based on an 

understanding of how exposure concentrations estimated for the screening scenario change 

with meteorology and environmental assumptions. The screening scenarios developed 

include 2 separate receptors; 1) subsistence fisher and 2) subsistence farmer. This step creates 

a facility-specific emission rate for each PB-HAP (i.e., the threshold for cadmium could be 

different for every facility), for each scenario unlike the Tier 1 emission rate threshold which 

was constant for the same PB-HAP at different facilities (i.e., the threshold for cadmium was 

the same for every facility). 

The subsistence fisher scenario assumes a high-end fish consumption rate of 373 grams/day.6 

Also, the assessment uses the assumption that the biological productivity limitation of each 

lake is 1 gram of fish per acre of water Thus, in order to fulfill the adult ingestion rate, we 

may need to model more than one lake. Refer to Appendix 4 of this document (Technical 

Support Document for TRIM-Based Multipathway Screening Scenario for RTR: Summary of 

Approach and Evaluation) for a complete discussion of the bioassay studies used to support 

this assumption. 

If we need to include more than one lake to achieve the 373 g/day ingestion rate, we begin 

with the lake with highest chemical concentration of a given PB-HAP group, and “fish” up to 

the lake’s biological productivity. We then systematically proceed to other lakes based on 

concentration, until the 373 g/day limit is met. A maximum travel radius of 50 km relative to 

the facility is used to maintain a realistic scenario. The final Tier 2 screening result for the 

fisher can be expressed as the sum of the risk from each lake that is fished (which is based on 

the amount of fish ingested for each lake multiplied by the fish concentration). If the highestconcentration lake is at least 373 acres, the ingestion rate is not altered (i.e., remains 373 g/d 

for adults). If the cumulative size of multiple visited lakes exceeds 373 acres, the model 

includes from the final lake only the amount of fish necessary to satisfy the ingestion rate (i.e., 

to reach the 373 g/d). If there are not 373 acres of lake, the risk reflects a reduced ingestion 

rate based on the lake acreage. The farmer scenario (same approach for all Tiers) involves an 

 

6 Burger, J. 2002. Daily consumption of wild fish and game: Exposures of high end recreationalists. 

Environmental Health Research. 12(4):343–354
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individual living for a 70-year lifetime on a farm homestead in the vicinity of the source and 

consuming produce grown on, and meat and animal products raised on, the farm. The 

ingestion rate used for these food groups are set at the 90th percentile of EPA’s “Exposure 

Factors Handbook: 2011 Edition”, and is considered an upper-bound level.7

Facility emissions of PB-HAP that do not exceed these new Tier II screening levels are 

considered to pose no significant risks. When facilities exceed the Tier II screening levels, it 

does not mean that multipathway impacts are significant, only that we cannot rule out that 

possibility based on the results of the screen. See Appendix 4 of this document (Technical 

Support Document for TRIM-Based Multipathway Screening Scenario for RTR: Summary of 

Approach and Evaluation) for a complete discussion of the Tier II screen. 

If the PB-HAP emissions for a facility exceed the Tier II screening emissions rate, and data 

are available, we may decide to conduct a more refined multipathway assessment. A refined 

assessment replaces some of the assumptions made in the Tier II screen, with site specific 

data. The refined assessment also uses the TRIM.FaTE model and facility-specific emission 

rate levels that are created for each PB-HAP. There are many variables to consider in a 

refined multipathway assessment and we have developed a protocol to maintain consistency 

across source categories. This protocol can be found in Appendix 9 of this document 

(Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site-Specific Risk 

Assessment in the RTR Program). For the ferroalloys production source category, we did 

conduct a refined multipathway assessment for one facility in the category. A detailed 

discussion of the approach for this assessment can be found in Appendix 10 of this document 

(Technical Support Document: Human Health Multipathway Residual Risk Assessment for 

the Ferroalloys Production Source Category). 

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 

 

7 US EPA, September 2011. Exposure Factors Handbook: 2011 Edition; 

 http://www.epa.gov/ncea/efh/pdfs/efh-complete.pdf
Residual Risk Assessment for the Ferroalloys Source Category

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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.

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

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

screen focuses on the following seven environmental HAP:

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

mercury (both inorganic mercury and methyl mercury), and lead,

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

HAP that persist and bioaccumulate are of particular environmental concern because they 

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

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

Appendix 11 of this document, Environmental Risk Screen, for the PB-HAP and acid gas 

benchmarks included in the environmental risk screen.

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

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

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

proceed to the second step of the evaluation.

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

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

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

each of the emitted environmental HAP exceeded ecological benchmarks represented as 

emissions screening levels. If off-site emissions from a facility do not exceed the Tier I

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

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

levels, we evaluate the facility further in Tier II.
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In Tier II of the environmental screening analysis, the screening emission levels are adjusted 

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

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

II screening levels, the facility passes the screen, and is typically not evaluated further. If offsite emissions from a facility exceed the Tier II screening levels, the facility does not pass the 

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

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

of the area of exceedance.

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

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

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

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

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

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

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

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

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

there is an adverse environmental effect.

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

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

part of the human health exposure and risk analysis using the HEM3-AERMOD air dispersion 

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

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

emissions to the level of the secondary National Ambient Air Quality Standard (NAAQS) for 

lead. The secondary lead NAAQS is a reasonable means of evaluating environmental risk 

because it is set to provide substantial protection against adverse welfare effects which can 

include “effects on soils, water, crops, vegetation, man-made materials, animals, wildlife, 

weather, visibility and climate, damage to and deterioration of property, and hazards to 

transportation, as well as effects on economic values and on personal comfort and wellbeing.” 8

 

 

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

maintenance of which, in the judgment of the Administrator, based on criteria, is requisite to protect the public 

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

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

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

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

on personal comfort and well-being.”
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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

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

(OAQPS) existing recommendations for HAP [9], which were 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 percent confidence limit, on the increased 

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

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

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

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

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

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

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

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

become available. Refer to the “IRIS Track” website9for detailed information on status 

and scheduling of current individual IRIS assessments and updates. EPA’s science policy

approach, under the current carcinogen guidelines, is to use linear low-dose extrapolation 

as a default option for carcinogens for which the mode of action (MOA) has not been 

identified. We expect future EPA dose-response assessments to identify nonlinear MOAs 

where appropriate, and we will use those analyses (once they are peer reviewed) in our 

 

9http://cfpub.epa.gov/ncea/iristrac/ 
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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 assessments10: “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) Consistent with Agency policy (as mentioned above), which was supported by the SAB,11

the EPA has chosen in this instance to rely on the ATSDR MRL for manganese in the 

current ferroalloys supplemental proposal. There is an existing IRIS RfC for manganese 

 

10 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 )

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

http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/EPA-SAB-10-007-

unsigned.pdf
Residual Risk Assessment for the Ferroalloys Source Category

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(Mn) published in 199312. This value was in the RTR risk assessment supporting the 2011 

Ferroalloys Notice of Proposed Rulemaking. However, since the 2011 proposal ATSDR 

has published an assessment of manganese toxicity (2012) which includes a chronic 

inhalation reference value (i.e., an ATSDR Minimal Risk Level or MRL)

13

. Both the 

1993 IRIS RfC and the 2012 ATSDR MRL were based on the same study (Roels et al., 

1993). In developing their assessment, ATSDR used updated dose-response modeling 

methodology (benchmark dose approach) and considered recent pharmacokinetic findings 

to support their MRL derivation. Consistent with Agency policy, which was supported by 

SAB, the EPA has chosen to rely on the ATSDR MRL for manganese in the current 

ferroalloys final rule. 

2) In the case of nickel compounds, to provide a conservative estimate of potential cancer 

risks, we used the IRIS URE value for nickel subsulfide (which is considered the most 

potent carcinogen among all nickel compounds) in the assessment for the 2011 proposed 

rule for ferroalloys production. In the 2011 proposal rule, the determination of the percent 

of nickel subsulfide was considered a major factor for estimating the risks of cancer due to 

nickel-containing emissions. Nickel speciation information for some of the largest nickelemitting 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 cancer 

risk for the mixture of inhaled nickel compounds (based on nickel subsulfide, and 

representative of pure insoluble crystalline nickel) was 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)

14, International Agency for Research 

on Cancer (IARC)

15, and other international agencies)16 that 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 carcinogenic effects in humans is not always clear, studies 

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

 

12 USEPA Integrated Risk Information System Review of Manganese (1993) available at 

http://www.epa.gov/iris/subst/0373.htm

13 Agency for Toxic Substances & Disease Registry Toxicological Profile for Manganese (2012) available at 

http://www.atsdr.cdc.gov/toxprofiles/tp.asp?id=102&tid=23

14

 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

15

 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.

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

Environmental Risks (SCHER, 2006).
Residual Risk Assessment for the Ferroalloys Source Category

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

review by Grimsrud et al., 201017). 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 the inhalation risk assessment for the 2011 proposal, to take a conservative approach, 

we considered all nickel compounds to have the same carcinogenic potential as nickel 

subsulfide and used the IRIS URE for nickel subsulfide to estimate risks due to all nickel

emissions from the source category. However, given that there are two additional URE 

values18 derived for exposure to mixtures of nickel compounds, as a group, that are 2-3 

fold lower than the IRIS URE for nickel subsulfide, the EPA also considers it reasonable 

to use a value that is 50 percent of the IRIS URE for nickel subsulfide for providing an 

estimate of the lower end of the plausible range of cancer potency values for different

mixtures of nickel compounds. In the public comments provided in response to the 

proposal and available in the docket, one facility provided additional data in the form of a 

laboratory test report that indicated it would be unlikely that 100 percent of the nickel 

from the furnace would be in the form of nickel subsulfide. Therefore, given our current 

knowledge of the carcinogenic potential of all nickel compounds, and the potential 

differences in carcinogenic potential across nickel compounds, we considered it 

reasonable to use a value that is 50 percent of the IRIS URE for nickel subsulfide for 

providing an estimate of the cancer potency for different mixtures of nickel compounds in 

the revised dataset for the 2014 supplemental proposal. We also consider it reasonable for 

the 2015 final rule.

3) 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. 

4) Where POM emissions were not speciated into individual compounds, we applied the 

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

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

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

potency, for which we can apply the same URE.

5) 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 

 

17

 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.occup-med.com/content/5/1/7

18

 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 ).
Residual Risk Assessment for the Ferroalloys Source Category

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appropriate and, in 2010 EPA returned to using the 1991 IRIS value. The 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.

19

 

The EPA will follow the NAS Report recommendations and will present results obtained 

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

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

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

recommended by the NAS committee, appropriate sensitivity and uncertainty analyses 

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

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

the final assessment will be posted on the IRIS database. In the interim, we will present 

findings using the 1991 IRIS value as a primary estimate; 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, 38 are classified as 

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

available. These 38 HAP, their quantitative inhalation chronic cancer dose-response values, 

and the source of each value are listed in Table 2.6-1(A). The dioxin and 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). Thirty HAP have quantitative 

inhalation chronic noncancer threshold values available; two of these thirty HAP (cadmium 

and mercury), for which a multipathway assessment was performed, also have quantitative 

oral chronic noncancer threshold values available. These 30 HAP, their threshold values, and 

the source of the value are listed in Table 2.6-2(A) and Table 2.6-2(B). 

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

Carcinogens

URE (unit risk estimate for cancer)20 = cancer risk per μg/m3 of average lifetime exposure. 

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

Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the 

EPA Office of Air Quality Planning and Standards

Pollutant CAS 

Number21

URE5

(1/μg/m3)

Source

Arsenic compounds 7440382 4.3E-3 IRIS

Cadmium compounds 7440439 0.0018 IRIS

Chlorinated Dioxin/Furans

 1,2,3,4,6,7,8,9-Octachlorodibenzo-p-dioxin 3268879 0.0099 EPA ORD

 1,2,3,4,6,7,8,9-Octochlorodibenzofuran 39001020 0.0099 EPA ORD

 1,2,3,4,6,7,8-Heptachlorodibenzo-p-dioxin 35822469 0.33 EPA ORD

 

19

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

20 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. 

21 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.
Residual Risk Assessment for the Ferroalloys Source Category

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

Carcinogens

URE (unit risk estimate for cancer)20 = cancer risk per μg/m3 of average lifetime exposure. 

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

Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the 

EPA Office of Air Quality Planning and Standards

Pollutant CAS 

Number21

URE5

(1/μg/m3)

Source

 1,2,3,4,6,7,8-Heptachlorodibenzofuran 67562394 0.33 EPA ORD

 1,2,3,4,7,8,9-Heptachlorodibenzofuran 55673897 0.33 EPA ORD

 1,2,3,4,7,8-Hexachlorodibenzo-p-dioxin 39227286 3.3 EPA ORD

 1,2,3,4,7,8-Hexachlorodibenzofuran 70648269 3.3 EPA ORD

 1,2,3,6,7,8-Hexachlorodibenzo-p-dioxin 57653857 3.3 EPA ORD

 1,2,3,6,7,8-Hexachlorodibenzofuran 57117449 3.3 EPA ORD

 1,2,3,7,8,9-Hexachlorodibenzo-p-dioxin 19408743 3.3 EPA ORD

 1,2,3,7,8,9-Hexachlorodibenzofuran 72918219 3.3 EPA ORD

 1,2,3,7,8-Pentachlorodibenzo-p-dioxin 40321764 33 EPA ORD

 1,2,3,7,8-Pentachlorodibenzofuran 57117416 0.99 EPA ORD

 2,3,4,6,7,8-Hexachlorodibenzofuran 60851345 3.3 EPA ORD

 2,3,4,7,8-Pentachlorodibenzofuran 57117314 9.9 EPA ORD

 2,3,7,8-Tetrachlorodibenzo-p-dioxin 1746016 33 EPA ORD

 2,3,7,8-Tetrachlorodibenzofuran 51207319 3.3 EPA ORD

Chromium (VI) 18540299 1.2E-2 IRIS

Formaldehyde22 50000 1.3E-5 IRIS

Naphthalene 91203 3.4E-5 CAL

Nickel compounds 7440020 2.4E-4

23 IRIS

Polycyclic Organic Matter 246 24

2-Methylnaphthalene 91576 8.8E-5 CAL

Acenaphthene 83329 8.8E-5 CAL

Acenaphthylene 206968 8.8E-5 CAL

Benz[a]anthracene 56553 1.76E-4 CAL

Benzo[a]pyrene 50328 1.76E-3 CAL

Benzo[b]fluoranthene 205992 1.76E-4 CAL

Benzo[e]pyrene 192972 8.8E-5 CAL

Benzo[g,h,i]perylene 191242 8.8E-5 CAL

Benzo[k]fluoranthene 207089 1.76E-4 CAL

Chrysene 218019 1.76E-5 CAL

 

22 The EPA has used the CIIT value (5.5x10-9 per mg/m3

) to characterize formaldehyde cancer risks in some 

instances. 

23 We typically use the value of 4.8E-4 (1/μg/m3

) for nickel compounds, as explained earlier in this report. For 

this source category, we had information to indicate that a value of 2.4E-4 (1/μg/m3) was appropriate.

24 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 (A) Dose-Response Values for Chronic Inhalation Exposure to 

Carcinogens

URE (unit risk estimate for cancer)20 = cancer risk per μg/m3 of average lifetime exposure. 

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

Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the 

EPA Office of Air Quality Planning and Standards

Pollutant CAS 

Number21

URE5

(1/μg/m3)

Source

Dibenzo[a,h]anthracene 53703 1.92E-3 CAL

Fluoranthene 206440 8.8E-5 CAL

Fluorene 86737 8.8E-5 CAL

Indeno[1,2,3-cd]pyrene 193395 1.76E-4 CAL

Perylene 198550 8.8E-5 CAL

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

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

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

Health Hazard Assessment

Pollutant CAS Number9

SF

(1/mg/kg/d) Source

Dioxin/Furans

 Hexachlorodibenzo-p-dioxin 19408743 6200 IRIS

 2,3,7,8-Tetrachlorodibenzo-p-dioxin 1746016 150000 EPA ORD

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-cd]pyrene 193395 1.2 CAL
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

23

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)

Source25

Arsenic compounds 7440382 0.000015 CAL

Cadmium compounds 7440439 0.00001 ATSDR

Chlorinated dioxins and furans

1,2,3,4,6,7,8,9-Octochlorodibenzofuran 39001020 0.00013 CAL

1,2,3,4,6,7,8,9-Octochlorodibenzo-p-dioxin 3268879 0.00013 CAL

1,2,3,4,6,7,8-Heptachlorodibenzofuran 67562394 0.000004 CAL

1,2,3,4,6,7,8-Heptachlorodibenzo-p-dioxin 35822469 0.000004 CAL

1,2,3,4,7,8,9-Heptachlorodibenzofuran 55673897 0.000004 CAL

1,2,3,4,7,8-Hexachlorodibenzofuran 70648269 0.0000004 CAL

1,2,3,4,7,8-Hexachlorodibenzo-p-dioxin 39227286 0.0000004 CAL

1,2,3,6,7,8-Hexachlorodibenzofuran 57117449 0.0000004 CAL

1,2,3,6,7,8-Hexachlorodibenzo-p-dioxin 57653857 0.0000004 CAL

1,2,3,7,8,9-Hexachlorodibenzofuran 72918219 0.0000004 CAL

1,2,3,7,8,9-Hexachlorodibenzo-p-dioxin 19408743 0.0000004 CAL

1,2,3,7,8-Pentachlorodibenzo-p-dioxin 40321764 0.00000004 CAL

1,2,3,7,8-Pentachlorodibenzofuran 57117416 0.0000013 CAL

2,3,4,6,7,8-Hexachlorodibenzofuran 60851345 0.0000004 CAL

2,3,4,7,8-Pentachlorodibenzofuran 57117314 0.00000013 CAL

2,3,7,8-Tetrachlorodibenzo-p-dioxin 1746016 0.00000004 CAL

2,3,7,8-Tetrachlorodibenzofuran 51207319 0.0000004 CAL

Chromium (VI) compounds 18540299 0.0001 IRIS - M

Formaldehyde 50000 0.0098 ATSDR

Hydrochloric acid 7647010 0.02 IRIS - L

Hydrofluoric acid 7664393 0.014 CAL

Lead compounds 7439921 0.00015

EPA 

OAQPS

Manganese compounds 7439965 0.0003 ATSDR

Mercury (elemental) 7439976 0.0003 IRIS - M

Gaseous divalent mercury 201 0.0003 IRIS - M

Particulate divalent mercury 184 0.0003 IRIS - M

Naphthalene 91203 0.003 IRIS - M

 

25 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.
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

24

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)

Source25

Nickel compounds 7440020 0.00009 ATSDR

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 26

Cadmium compounds 7440439 0.0005 IRIS - H

Mercuric chloride27 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 an EPA document of graphical arrays [19].

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

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

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

 

26 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.

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

separate oral exposure estimates for divalent mercury and methylmercury.
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

25

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

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

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

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

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

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

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

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

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

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

developed chronic RELs).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

releases at fixed facilities and from transport carriers.” 

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

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

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

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.”
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

26

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

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

irritation or certain asymptomatic, nonsensory effects. With increasing airborne 

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

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

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

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

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

responses, could experience the effects described at concentrations below the 

corresponding AEGL.”

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

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

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

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

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

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

ERPG values (https://www.aiha.org/getinvolved/aihaguidelinefoundation/emergencyresponseplanningguidelines/Pages/default.aspx) 

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

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

adequacy of accident prevention and emergency response plans, including transportation 

emergency planning, community emergency response plans, and incident prevention and 

mitigation.” 

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

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

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

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

odor.”

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

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

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

ability to take protective action.”

In the RTR program, EPA assesses acute risk using toxicity values derived from one hour 

exposures. Based on an in-depth examination of the available acute value for nickel 

[California EPA’s acute (1-hour) REL], we have concluded that this value is not appropriate 

to use to support EPA’s risk and technology reviews rules. This conclusion takes into 

account: the effect on which the acute REL is based; aspects of the methodology used in its 

derivation; and how this assessment stands in comparison to the ATSDR toxicological 

assessment, which considered the broader nickel health effects database.
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

27

The broad nickel noncancer health effects database strongly suggests that the respiratory tract 

is the primary target of nickel toxicity following inhalation exposure. The available database 

on acute noncancer respiratory effects is limited and was considered unsuitable for 

quantitative analysis of nickel toxicity by both California EPA28 and ATSDR29. The 

California EPA’s acute (1-hour) REL is based on an alternative endpoint, immunotoxicity in 

mice, specifically depressed antibody response measured in an antibody plaque assay.

In addition, the current California acute (1-hour) REL for nickel includes the application of 

methods that are different from those described in EPA guidelines. Specifically, the (1-hour) 

REL applies uncertainty factors that depart from the defaults in EPA guidelines and does not 

apply an inhalation dosimetric adjustment factor. 

Further, the ATSDR’s intermediate MRL (relevant to nickel exposures for a time frame 

between 14 and 364 days), was established at the same concentration as the California EPA 

(1- hour) REL, indicating that exposure to this concentration “is likely to be without 

appreciable risk of adverse noncancer effects” (MRL definition)30 for up to 364 days.

We have high confidence in the nickel ATSDR intermediate MRL. Our analysis of the broad 

toxicity database for nickel indicates that this value is based on the most biologically-relevant 

endpoint. That is, the intermediate MRL is based on a scientifically sound study of acute 

respiratory toxicity. Furthermore, this value is supported by a robust subchronic nickel 

toxicity database and was derived following guidelines that are consistent with EPA 

guidelines.31 Finally, there are no AEGL-1/ERPG-1 or AEGL-2/ERPG-2 values available for 

nickel. Thus, for all the above mentioned reasons, we will not include nickel in our acute 

analysis for this source category or in future assessments unless and until an appropriate value 

becomes available.

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.

 

28 http://oehha.ca.gov/air/allrels.html

29 http://www.atsdr.cdc.gov/substances/toxsubstance.asp?toxid=44

30 Agency for Toxic Substances and Disease Registry (ATSDR), Toxic Substances Portal. Minimal Risk Levels 

(MRLs) http://www.atsdr.cdc.gov/mrls/index.asp

31 US EPA 2002. Review of the reference dose and reference concentration processes (EPA/630/P-02/002F 

December 2002, http://www.epa.gov/raf/publications/pdfs/rfd-final.pdf
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

28

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

(mg/m3)

Arsenic compounds 7440382 0.0002

Formaldehyde 50000 1.1 17 1.2 12 0.055

Hydrochloric acid 7647010 2.7 33 4.5 30 2.1

Hydrofluoric acid 7664393 0.82 20 1.6 16 0.24

Mercury (elemental) 7439976 1.7 2 0.0006

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 Analysis32, 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.

 

32Memorandum for the Heads of Executive Departments and Agencies - Updated Principles for Risk Analysis

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

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

Office of Science and Technology Policy 

http://www.whitehouse.gov/sites/default/files/omb/memoranda/fy2007/m07-24.pdf
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

29

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 

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.
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

30

Screening for potentially significant acute inhalation exposures also followed the HQ 

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

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

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

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

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

2.7.2 Mixtures

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

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

exposures from a particular source category combined.

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

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

the independence formula in the mixtures guidelines.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

interpreted carefully by health scientists and risk managers.

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

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

basis, not using the TOSHI approach.

2.7.3 MACT-Allowable Risks

The emissions data in the dataset for the ferroalloys source category are estimates of actual 

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

on these actual emissions. For the ferroalloys production source category, estimates of 

MACT-allowable emissions were also estimated, and the risk results based on those emissions 
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

31

are presented below as well. For more detail, please refer to the emissions memo in the 

docket, which is also Appendix 1 to this document, Revised Development of the Risk and 

Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category

for the 2015 Final Rule. 

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 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 polycyclic organic 

matter (POM), such as PAH, are also expected. Additionally, chlorine is present in coal, 

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

expected. 

There are 2 ferroalloys production facilities operating in the U.S. Both facilities are identified 

as major sources of HAP. The emissions for the ferroalloys source category dataset are 

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

approximately 200 tons per year. Based on these data, the HAP emitted in the largest 

quantities are manganese compounds, hydrofluoric acid, hydrochloric acid, phenanthrene, 

fluoranthene, formaldehyde, pyrene, and naphthalene.

33

 Emissions of these eight HAP make 

up more than 95 percent of the total emissions by mass. Persistent and bioaccumulative HAP 

(PB-HAP) 34 reported as emissions from these facilities include lead compounds, mercury 

compounds, PCBs, dioxins/furans, cadmium compounds, and polycyclic organic matter. The 

following environmental HAP are emitted from the ferroalloys production source category 

 

33 As described in the emissions memo Revised Development of the Risk and Technology Review (RTR) 

Emissions Dataset for the Ferroalloys Production Source Category, numerical estimates for HF were provided 

for input to the risk assessment. Upon closer investigation, we found that all test results were below the 

detection limit of the test method and therefore we believe HF is not emitted from these sources.

34 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://www2.epa.gov/sites/production/files/2013-

08/documents/volume_1_reflibrary.pdf
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

32

and are included in the environmental risk screen: cadmium, dioxins/furans, hydrogen 

chloride, hydrofluoric acid, lead, mercury, and PAHs.

 

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

Assessment and Availability of Dose-Response Values

HAPa

Emission

Estimates

(tpy)

Number of 

Facilities 

where HAP 

Reported or 

Estimated 

(2 facilities 

in dataset)

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 109 2 

Hydrofluoric acid 39 2  

Hydrochloric acid 24 2  

Formaldehyde 5 2   

Polycyclic Organic Matter

2-Methylnaphthalene 1 2  

Acenaphthene 0.3 2  

Acenaphthylene 1 2  

Anthracene 0.6 2 

Benz[a]anthracene 0.5 2  

Benzo[a]pyrene 0.07 2  

Benzo[b]fluoranthene 0.4 2  

Benzo[g,h,i]perylene 0.03 2  

Benzo[e]pyrene 0.2 2  

Benzo[k]fluoranthene 0.12 2  

Chrysene 1 2  

Dibenzo[a,h]anthracene 0.005 2  

Fluorene 0.5 2  

Fluoranthene 5 2  

Indeno[1,2,3-cd]pyrene 0.03 2  

Perylene 0.01 2  

Phenanthrene 5 2 

Pyrene 4 2 

Naphthalene 3 2  

Lead compounds 1 2 c 

Nickel compounds 0.4 2  

Mercury compounds

Mercury (elemental) 0.2 2   

Gaseous divalent mercury 0.025 2  

Particulate divalent mercury 0.025 2  

Chromium compounds

 Chromium III 0.2 2

 Chromium (VI) 0.02 2  

Cadmium compounds 0.1 2   Y

Arsenic compounds 0.04 2   
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

33

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

Assessment and Availability of Dose-Response Values

HAPa

Emission

Estimates

(tpy)

Number of 

Facilities 

where HAP 

Reported or 

Estimated 

(2 facilities 

in dataset)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate for 

Cancer?

Reference 

Concentration 

for Noncancer?

Health 

Benchmark 

Values for Acute 

Noncancer?

Polychlorinated Biphenyls 0.0003 2  Y

Chlorinated Dibenzodioxins 

and furans

1,2,3,4,6,7,8,9-

Octochlorodibenzofuran 2.14E-07 2

  Y

1,2,3,4,6,7,8,9-

Octochlorodibenzo-p-dioxin 5.63E-07 2

  Y

1,2,3,4,6,7,8-

Heptachlorodibenzofuran 1.64E-07 2

  Y

1,2,3,4,6,7,8-

Heptachlorodibenzo-pdioxin 1.22E-07 2

  Y

1,2,3,4,7,8,9-

Heptachlorodibenzofuran 4.32E-08 2

  Y

1,2,3,4,7,8-

Hexachlorodibenzofuran 2.30E-07 2

  Y

1,2,3,4,7,8-

Hexachlorodibenzo-p-dioxin 4.66E-08 2

  Y

1,2,3,6,7,8-

Hexachlorodibenzofuran 1.14E-07 2

  Y

1,2,3,6,7,8-

Hexachlorodibenzo-p-dioxin 4.78E-08 2

  Y

1,2,3,7,8,9-

Hexachlorodibenzofuran 4.46E-08 2

  Y

1,2,3,7,8,9-

Hexachlorodibenzo-p-dioxin 5.64E-08 2

  Y

1,2,3,7,8-

Pentachlorodibenzofuran 3.05E-07 2

  Y

1,2,3,7,8-

Pentachlorodibenzo-pdioxin 7.50E-07 2

  Y

2,3,4,6,7,8-

Hexachlorodibenzofuran 8.39E-07 2

  Y

2,3,4,7,8-

Pentachlorodibenzofuran 2.91E-07 2

  Y

2,3,7,8-

Tetrachlorodibenzofuran 1.55E-06 2

  Y

2,3,7,8-Tetrachlorodibenzop-dioxin 9.24E-08 2

  Y

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.
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

34

 Chromium emissions were speciated based on test data. See Appendix 1 of this document (Revised Development of the 

Risk and Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category for the 2015 

Final Rule) for more information. 

 For emissions reported generically as “mercury” or “mercury & compounds,” emissions are speciated for this category 

as 80 percent “mercury (elemental),” 10 percent “gaseous divalent mercury,” and 10 percent “particulate divalent 

mercury.” 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

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

toxics at http://www2.epa.gov/fera/dose-response-assessment-assessing-health-risks-associated-exposure-hazardous-airpollutants 

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 adopted in October 2008 (http://www.epa.gov/air/lead/actions.html). The primary (health-based) standard is a 

maximum or not-to-be-exceeded, rolling three-month average, measured as total suspended particles (TSP). The secondary 

(welfare-based) standard is identical to the primary standard.

3.2 Baseline risk characterization

This section presents the results of the baseline risk assessment for the ferroalloys production 

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

baseline risk results are developed using the best estimates of actual HAP emissions 

summarized in the previous section. The basic chronic inhalation risk estimates presented 

here are the maximum individual lifetime cancer risk, the maximum chronic hazard index, 

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

assessments in the form of maximum hazard quotients, as well as the results of our 

preliminary screen for potential non-inhalation risks from PB-HAP. Also presented are the 

HAP “drivers,” which are the HAP that collectively contribute 90 percent of the maximum 

cancer risk or maximum hazard 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 facility-specific risk assessment results is available in Appendix 6 of 

this document, Detailed Risk Modeling Results.

Baseline Inhalation Risk Assessment Results Based on Actual Emissions

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

category. The results of the chronic inhalation cancer risk assessment estimate that the 

maximum lifetime individual cancer risk posed by these two facilities could be as high as 

20 in a million, with PAHs, chromium compounds, and nickel compounds from process 

fugitives as the major contributors to the risk. The total estimated cancer incidence from this 

source category is 0.003 excess cancer cases per year, or one excess case in every 333 years. 

Approximately 90 people are estimated to have cancer risks above 10 in a million and 

approximately 41,000 people are 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 4 from emissions of manganese from 

process fugitives as the major contributors to the HI. An estimated 1,300 people are exposed 

to TOSHI levels above 1 due to manganese emissions. 

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

acute benchmark, as shown in Table 3.1-1. For cases where the screening HQ was greater 
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

35

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

outside facility boundaries. Based on actual, baseline emissions, the highest acute screening 

HQ value is 1 (based on the acute RELs for arsenic compounds and hydrofluoric acid) and is 

shown in Table 3.2-1. This value includes a refinement of determining the highest HQ value 

that is outside facility boundaries. 

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) 20 chromium compounds, PAH, nickel 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

chromium compounds, PAH, 

nickel compounds, arsenic 

compounds, formaldehyde, 

dioxins, cadmium compounds

Greater than or equal to 1 in 1 million 2

chromium compounds, PAH, 

nickel compounds, arsenic 

compounds, formaldehyde, 

dioxins, cadmium compounds

Chronic Noncancer Risks

Maximum Neurological Hazard Index 4 manganese compounds

Number of Facilities with Maximum Neurological Hazard Index:

Greater than 1 2 manganese compounds

Acute Noncancer Refined Screening Results

Maximum Acute Hazard Quotient35

1

1

<1

<1

<1

arsenic compounds (REL)

hydrofluoric acid (REL)

formaldehyde (REL)

hydrochloric acid (REL)

mercury (REL)

Number of Facilities With Potential for 

Acute Effects 0 n/a

Population Exposure

 

35

 There are no reference values available (including a lack of short-term occupational values) to assess any 

potential risks from acute exposure to manganese. In addition, as described earlier, we do not believe that HF is 

emitted from these sources.
Residual Risk Assessment for the Ferroalloys Source Category

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36

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

Result HAP “Drivers”

Number of People Living Within 50 

Kilometers of Facilities Modeled 380,000 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 90 n/a

Greater than or equal to 1 in 1 million 41,000 n/a

Number of People Exposed to Noncancer Neurological Hazard Index:

Greater than 1 1,300 n/a

Estimated Cancer Incidence (excess 

cancer cases per year) 0.003 n/a

Contribution of HAP to Cancer Incidence

PAH 49% n/a

Chromium compounds 15% n/a

Cadmium compounds 12% n/a

Baseline Inhalation Assessment Results Based on Allowable Emissions

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

allowable under the MACT standards (i.e., MACT-allowable emissions) were also calculated 

for stack emissions for the two facilities.36 Risk estimates based on the actual emissions were 

then scaled up using these factors. (See Revised Development of the Risk and Technology 

Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category for the 

2015 Final Rule in Appendix 1 of this document, or separately in the docket, for a discussion 

of the development of the allowable factors.) In addition, an idled furnace at Eramet was 

included in the calculation of allowable risks. 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 with arsenic and cadmium emissions driving 

the risks, and that the maximum chronic noncancer TOSHI value could be as high as 40 at the 

MACT-allowable emissions level with manganese emissions driving the TOSHI value. Risks 

are likely higher than these presented here because process fugitive emissions increase with 

increased stack emissions (for which there are current MACT standards), and emissions of 

pollutants for which there are currently no MACT standards would also increase with 

increased stack emissions. 

 

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

MACT standard only has emission limits for stack emissions. In addition, MACT-allowable emissions were not 

calculated for those HAP (e.g., PAH) that do not currently have a MACT standard. Finally, for Eramet, the 

allowable estimates include emissions for an idle furnace that was not included in the calculation of actual 

emissions because it is not currently operating. MACT-allowable emissions, and associated risks, are likely 

underestimated.
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

37

Baseline Multipathway Assessment Results Based on Actual Emissions

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

performed a screening analysis (Tier I) that compared emissions of PB-HAP emitted from the 

ferroalloys source category (based on actual emissions) to screening emission rates (see 

section 2.5). The PB-HAP emitted by facilities in this category include cadmium compounds, 

chlorinated dibenzodioxins and furans (as 2,3,7,8-TCDD toxicity equivalents, or TEQ), 

mercury compounds, polychlorinated biphenyls (PCBs), and POM (as benzo(a)pyrene TEQ). 

PCBs are PB-HAP but do not currently have multipathway screening values and so were not 

evaluated for potential non-inhalation risks. As shown in Table 3.1-1, this PB-HAP is not 

emitted in appreciable quantities. 

The two facilities in the source category both reported emissions of these PB-HAP, and with 

the exception of cadmium emissions from one facility, both facilities had emission rates 

greater than the Tier I screening emission levels for all four PB-HAP indicating that the initial 

multipathway screening model does not rule out the potential for multipathway impacts of 

concern. One facility’s emission rates of cadmium compounds exceeded the screening level

by about 10 times, while the other was below the level. One facility’s emission rates of 

mercury exceeded the screening level by 100 times, while the other facility’s mercury 

emission rates exceeded the level by 10 times. For dioxins, one facility’s emission rates 

exceeded the level by 100 times, while the other facility’s emission rates exceeded the level

by 40 times. For POM, one facility’s emission rates exceeded the screening level by 500

times, while the other facility’s emission rates exceeded the level by 20 times. Due to the 

theoretical construct of the screening model, these factors are not directly translatable into 

estimates of risk or hazard quotients for these facilities. Table 3.2-2 summarizes the results of 

this Tier I screen. 

For the PB-HAP and facilities that did not screen out during our initial Tier I multipathway 

screening analysis, we improved our analysis with some additional site-specific information 

to develop a Tier II screen. (See Appendix 4 of this document, Technical Support Document 

for TRIM-Based Multipathway Screening Scenario for RTR: Summary of Approach and 

Evaluation, for more information about the Tier II 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 levels for each of the four PB-HAP. Based on this Tier II screening 

analysis, the cadmium emission rates for both facilities were below site-specific levels for that 

PB-HAP. For mercury, one facility’s emissions was below the screening level, while the 

other facility had emissions of mercury that exceeded its site-specific level by eight times. 

The PAH and dioxin emissions at both facilities exceeded their respective site-specific levels

by a range of 2 to 50. Table 3.2-2 presents these results.

Similar to the results from the Tier I screen, an exceedance of a screening level in Tier II

cannot be equated with a risk value or a hazard quotient (or hazard index). Rather, it 

represents a high-end estimate of what the risk or hazard may be. For example, an 

exceedance of 2 for a non-carcinogen can be interpreted to mean that we have high 

confidence that the hazard would be lower than 2. Similarly, an exceedance of 30 for a 
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

38

carcinogen means that we have high confidence that the risk is lower than 30 in a million. 

Our confidence comes from the conservative, or health-protective, assumptions that are in the 

screens: we choose inputs from the upper end of the range of possible values for the 

influential parameters used in the screens; and we assume that the exposed individual exhibits 

ingestion behavior that would lead to a high total exposure.

 

Table 3.2-2 Summary of Source Category Level Multipathway Screening Assessment Risk Results 

for Ferroalloys

Tier I

Tier II

PBHAP

Facilities 

Emitting 

PBHAP

(2 in 

source 

category)

Max 

Emissions 

of this 

PBHAP 

(TPY)a

Max 

Emissions 

Divided by 

Screening 

Level

Facilities 

Exceeding 

Screening 

Level

Max 

Emissions 

Divided by 

Screening 

Level (fish 

only)

Max 

Emissions 

Divided by 

Screening 

Level (farm 

only)

Facilities 

Exceeding 

Either 

Screening 

Level

Carcinogens

Chlorinated Dibenzodioxins 

and Furans as 2,3,7,8-

Tetrachlorodibenzo-pdioxin TEQ

2 3.53E-7 100 2 7 7 2

Polycyclic Organic Matter 

as Benzo(a)Pyrene TEQ 2

1.25E-00 500 2 10 30 2

Non-carcinogens

Cadmium Compounds 2 1.17E-1 10 1 0.7 0.07 0

Divalent Mercury 2 4.19E-2 100 2 8 0.009 1

Notes:

a – PAH and dioxin emissions in this column were normalized to BaP and 2,3,7,8-TCDD, respectively, for oral toxicity and Tier I modeled 

environmental fate and transport. Emissions were further normalized in Tier II for environmental fate and transport. 

We conducted a more refined multipathway assessment for one of the facilities in the 

ferroalloys production source category. This facility, the Eramet facility in Marietta, Ohio 

was selected (1) because of its Tier II screening results and (2) based on the feasibility, with 

respect to the modeling framework, of obtaining parameter values for the region surrounding 

the facility. We expect that the exposure scenarios we assessed are among the highest that 

might be encountered for this source category, although not the absolute highest. The 

approach, data, assumptions, and results of the site-specific assessment are presented in 

Appendix 10 of this document (Technical Support Document: Human Health Multipathway 

Residual Risk Assessment for the Ferroalloys Production Source Category). 

The site-specific assessment, as in the screening assessments, includes some hypothetical 

elements, namely the hypothetical farmer and angler scenarios. We also included children in 

different age ranges and adults. It is important to note that even though the multipathway 

assessment has been conducted, no data exist to verify the existence of either the farmer or 

angler scenario outlined below. The farmer scenario involves an individual living for a 70-

year lifetime on a farm homestead in the vicinity of the source and consuming produce grown 

on, and meat and animal products raised on, the farm. The individual also incidentally ingests 
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

39

surface soil at the location of the farm homestead. The angler scenario involves an individual 

who regularly consumes fish caught in freshwater lakes in the vicinity of the source of interest 

over the course of a 70-year lifetime. In addition, exposure estimates and risks for infants 

consuming contaminated breast milk were evaluated in the case of dioxins, with the 

assumption that the nursing mother was exposed to chemicals via one of the two scenarios 

described above. We evaluated variations of these two scenarios using different assumptions 

regarding food source (i.e., location of the farm homestead or the water body from which fish 

are obtained), the age of the individual exposed (for noncancer hazards), the assumed 

ingestion rate of each food type, and other factors. In particular, a range of fish ingestion 

rates was evaluated to determine the possible health risks associated with that pathway.

Results of the Site-Specific Multipathway Assessment:

 Cancer risk estimates from the site-specific assessment are presented in Table 3.2-3

(Maximum Site-Specific Results column).

o Incremental lifetime cancer risk from exposure to PAHs is 10-in-1 million

from the farm pathway and 7-in-1 million from the fish pathway.

o Incremental lifetime cancer risk from exposure to dioxins is 1-in-1 million

from the farm pathway and 0.5 from the fish pathway.

o For both the PAHs and dioxins, farm ingestion at the 90th percentile ingestion 

rate drives the risk. 

 Noncancer hazards from the site-specific assessment are also presented in Table 3.2-3

(Maximum Site-Specific Results column).

o Noncancer hazard quotients did not exceed one for any scenario (farm or fish) 

for exposure to cadmium, and was driven by fish ingestion by the adult female 

angler at the 99th percentile ingestion rate. 

o The noncancer hazard quotient for mercury was estimated to be 1 from the fish 

pathway, with methyl mercury exposure to the adult female angler at the 99th

percentile ingestion rate for the subsistence fisherman or at a rate of 373 

grams/day driving the risk. These risk estimates are the maximum results from 

the refined assessment. 

Because this more refined assessment uses location-specific information where appropriate 

and available (e.g., location of actual lakes rather than a generic lake as in Tier I1), the water 

body producing the maximum risk results can change between the Tier I screen and the 

refined assessments. Since the Tier II screen employs the “subsistence ” method, multiple 

lakes are included in that screening scenario, while only one is the “maximum” lake in the 

site-specific assessment. We can also show the comparison of results from the Tier I screen, 

the Tier II screen, and the site-specific assessment in order to observe the trend in screening 

level exceedances, however given the differences just described, it is not a comparison of 

equivalent scenarios. The trend also shows how obtaining more site-specific data can 

decrease the emission rate screening level. For example, for mercury, we can see that the 

Tier I exceedance is 100 times the Tier I emission rate level for mercury, the Tier II 

exceedance for the fish pathway is 8 times the facility-specific Tier II emission rate level for 

mercury, and the site-specific assessment produces an HQ of 1. (As stated above, Tier I and 

Tier II results are not risk estimates.) 
Residual Risk Assessment for the Ferroalloys Source Category

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40

Table 3.2-3 Summary of Source Category Level Site-Specific Multipathway Risk 

Results for Ferroalloys Baseline Scenario

PB-HAP

Emissions Divided by Screening 

Level Site-Specific Assessment Cancer 

Risk or Hazard Quotient

Tier I

(farm 

and 

fish)b

Tier II

(farm 

only)

Tier II (fish 

only)

Maximum 

Site-Specific 

Results (fish 

only)c

Maximum SiteSpecific Results

(farm only)d

Dioxins 

(cancer) 40 2 2 0.5 1

PAH 

(cancer) 500 10 30 7 10

Cadmium 

(noncancer) 10 0.7 0.07 0.09 0.05

Mercurya

(noncancer) 100 8 0.009 1 0.01

Notes:

a Exposure to methyl mercury was evaluated for the fish pathway, while exposure to divalent mercury was 

evaluated for the farm pathway.

b Tier I assessments do not separately assess risks or hazards from fish and farm; they are aggregated. To be 

congruent with the setup of the screening assessments, the site-specific values use the Chile 1-2 age group 

for HQs (the ingestion amount per body weight is largest for the Child 1-2 category), a lifetime defined as 

age 1 through age 70) including infant breast milk for dioxin exposure) for cancer risk, the “subsistence 

angler” scenario for fish exposure, and the 90th percentile ingestion rate for subsistence farmer exposure.

c Site-specific assessments assess risks or hazards from individual lakes, while Tier II assessments assess 

risks or hazards from potentially multiple lakes in combination. For mercury, Wolf Run Lake is the 

maximum lake, while for the other PB-HAP, Veto Lake was the maximum lake.

d The maximum farm for dioxins was the SE farm, while for the other PB-HAP, the NNW farm was the 

maximum farm. 

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 would not be exceeded at either of 

the two facilities. This analysis estimates that the annual lead concentrations could be up to 

about 20 percent of the value of the NAAQS for lead (maximum concentration is 

0.027 μg/m3). The maximum post-control concentration of lead at either facility is 0.01

μg/m3, or about seven percent of the NAAQS value. 

Baseline Environmental Risk Screening Based on Actual Emissions

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

associated with emissions of the following environmental HAP from the ferroalloys 
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

41

production source category: cadmium, dioxins/furans, hydrogen chloride, hydrofluoric acid,37

lead, mercury, and PAHs. The results of the environmental screening analysis are 

summarized in Table 3.2-4. 

In the Tier I screening analysis for PB-HAP (other than lead, which was evaluated 

differently), the individual modeled Tier I concentrations for one facility in the source 

category exceeded some sediment, fish – avian piscivorus, and surface soil benchmarks for 

PAHs, methyl mercury, and mercuric chloride. Therefore, we conducted a Tier II screen for 

PAHs, methyl mercury, and mercuric chloride. 

In the Tier II screen for PAHs and methyl mercury, none of the individual modeled 

concentrations for any facility in the source category exceeded any of the ecological 

benchmarks (either the LOAEL or NOAEL). For mercuric chloride, soil benchmarks were 

exceeded for one facility for some individual modeled points that collectively accounted for 

11 percent of the modeled area (6 percent of the area modeled in the category). However, the 

weighted average modeled concentration for all soil parcels was well below the soil 

benchmarks. For lead, we did not estimate any exceedances of the secondary lead NAAQS.

For HCl, each individual concentration (i.e., each off-site data point in the modeling domain) 

was below the ecological benchmarks for all facilities. The average modeled HCl 

concentration around each facility (i.e., the average concentration of all off-site data points in 

the modeling domain) did not exceed any ecological benchmark. 

For HF, some individual modeled points exceeded the ecological benchmarks for one facility 

but accounted for less than 0.02 percent of the modeled area for that facility (0.01 percent of 

the modeled area for the category). The average modeled HF concentration around each 

facility (i.e., the average concentration of all off-site data points in the modeling domain) did 

not exceed any ecological benchmark.38 

 

37 As described earlier, we do not believe that HF is emitted from these sources.

38 As described earlier, we do not believe that HF is emitted from these sources.
Residual Risk Assessment for the Ferroalloys Source Category

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42

Table 3.2-4 Summary of Source Category Environmental Risk Screening Results for 

Ferroalloys

Environmental 

HAP

Number of Facilities In Category 

Exceeding

Percent of 

Modeled Area in 

Category 

Exceeding2

Tier I Screen Tier II Screen1

NOAEL LOAEL NOAEL LOAEL NOAEL LOAEL

PBHAP

Pb None None None None 0% 0%

HgCl2 NA 1 NA None NA 6%

Methyl Hg 1 None None None 0% 0% 

PAH 1 None None None 0% 0%

Dioxins None None None None 0% 0%

Acid 

Gases

HF3 NA None - - NA 0.01%

HCl

4 NA None - - NA 0%

NA – Not Applicable. 

1- Tier II screen is performed for PB-HAP when there are exceedances of the Tier I screen. The acid gas screen 

is a one tier screen.

2 - A value of 0% indicates that none of the modeled data points exceeded the benchmark. For PB-HAP the 

percent area is based on the Tier II results, if a Tier II analysis is performed. Otherwise, the percent area is based 

on the Tier I results. 

3 – For HF, we evaluated two benchmarks, one from Canada and the other from the State of Washington. 

Although, they are both considered to be LOELs - the level between a NOAEL and a LOAEL, we have listed the 

results under the LOAEL column.

4 – For HCl, we evaluated one benchmark at the LOAEL level.

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 by 95 percent (e.g., enhanced local capture).39 Based on this scenario, we estimated 

that the maximum chronic noncancer inhalation TOSHI value would be reduced to 1, from the

baseline estimate of 4, with manganese emissions from the MOR process baghouse outlet

driving the risk. There would be no people estimated to have a TOSHI greater than 1. With 

respect to cancer risk, given the control scenario described above, the cancer MIR would be 

reduced from 20 in a million (i.e., pre-controls) to approximately 10 in a million (i.e., postcontrols), with PAH, cadmium compounds, arsenic compounds, and naphthalene driving the 

risk. There is an estimated reduction in cancer incidence to 0.002 excess cancer cases per 

year, from 0.003 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 41,000 to 

26,000. We also note that post-control, the maximum worst-case acute refined HQ value 

 

39 This post control scenario also includes the assumption that one facility will install controls for mercury.
Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

43

would be reduced from a potential value of 1 to less than 1 (using the REL values and the 

refinements described for the baseline acute assessment). 

For the baseline emissions scenario, we conducted both multipathway screening assessments 

and a more refined assessment (results shown above). For the post-control scenario, however, 

we only conducted a screening assessment, with the following results:

 Both facilities’ cadmium emissions are below the Tier II facility-specific emission rate 

levels for that PB-HAP for both the farm and fish scenarios. 

 For mercury, the facility with the largest exceedance of the screening value had an 

exceedance of eight times higher than its Tier II screening emission rate level for the 

fish scenario. However, as shown above, for the baseline emissions scenario, which 

had higher mercury emissions, the refined multipathway assessment produced an HQ 

of 1 for mercury for this facility. 

 For dioxins, the facility with the largest exceedance of the screening value had an 

exceedance of 5 times its facility-specific emission rate level for that PB-HAP for the 

fish scenario and 5 times its facility-specific emission rate level for that PB-HAP for 

the farm scenario. 

 For PAH, the facility with the largest exceedance of the screening value had an 

exceedance of 30 times its facility-specific emission rate level for that PB-HAP for the 

farm scenario and 10 times its facility-specific emission rate level for that PB-HAP for 

the fish scenario. 

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

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

description of the tiered multipathway screening approach, while Appendix 10 of this 

document (Technical Support Document: Human Health Multipathway Residual Risk

Assessment for the Ferroalloys Production Source Category) contains the results of the tiered 

screening assessment. 

As mentioned above, the highest lead concentration after controls, 0.01 μg/m3, is below the 

NAAQS for lead, 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. 
Residual Risk Assessment for the Ferroalloys Source Category

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Additionally, estimates of the maximum individual risk (MIR) contain uncertainty, because 

they are derived at census block centroid locations rather than actual residences. This 

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

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

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

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

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

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

downward bias in both the MIR and population risk estimates.

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

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

varied from as much as 17 percent below the predicted value to as much as 84 percent 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 percent lower to 84

percent 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. 

4.2 Uncertainties in the dose-response relationships

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

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

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

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

(>24 hours up to 30 days), and subchronic (>30 days up to 10 percent 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.
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Additionally, chronic dose-response values for certain compounds included in the assessment 

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

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

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

significantly mischaracterize human health risk

Cancer assessment

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

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

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

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

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

we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [30] (herein 

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

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

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

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

described in the Cancer Guidelines.

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

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

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

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

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

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).40 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.41 

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.42 EPA also 

 

40 IRIS glossary 

http://ofmpub.epa.gov/sor_internet/registry/termreg/searchandretrieve/glossariesandkeywordlists/search.do?detai

ls=&glossaryName=IRIS%20Glossary

41 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.

42 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 
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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.43 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.

 

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

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

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

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

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

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

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

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

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

test data and the correctness of scaled estimates. 

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

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

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

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

benchmark dose (BMD) approach is generally addressed though use of the 95 percent 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 
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characterization of low-dose nonlinear, non-threshold relationships. The National Academy 

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

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

human populations. Another National Research Council (NRC) report [32] suggests that 

models based on distributions of individual thresholds are likely to lead to sigmoidal-shaped 

dose-response functions for a population. This report notes sources of variability in the 

human population: “One might expect these individual tolerances to vary extensively in 

humans depending on genetics, coincident exposures, nutritional status, and various other 

susceptibility factors...” Thus, if a distribution of thresholds approach is considered for a 

carcinogen risk assessment, application would depend on ability of modeling to reflect the 

degree of variability in response in human populations (as opposed to responses in bioassays 

with genetically more uniform rodents). Note also that low dose linearity in risk can arise for 

reasons separate from population variability: due to the nature of a mode of action and 

additivity of a chemical’s effect on top of background chemical exposures and biological 

processes.

As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight 

line approach from the BMDL. This is equivalent to using an upper confidence limit on the 

slope of the straight line extrapolation. The impact of the choice of the BMDL on bottom line 

risk estimates can be quantified by comparing risk estimates using the BMDL value to central 

estimate BMD values, although these differences are generally not a large contributor to 

uncertainty in risk assessment (Subramaniam et. al., 2006) [33]. It is important to note that 

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

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

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

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

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.
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Chronic noncancer assessment

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

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

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

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

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

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

deleterious effects. Uncertainty factors are commonly default values44 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.45 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).

 

44

 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

45 See IRIS glossary
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A series of downward adjustments using default UFs is then applied to the POD to estimate 

the reference value [36]. While collectively termed “UFs”, these factors account for a number 

of different quantitative considerations when utilizing observed animal (usually rodent) or 

human toxicity data in a risk assessment. The UFs are intended to account for: (1) variation 

in susceptibility among the members of the human population (i.e., inter-individual 

variability); (2) uncertainty in extrapolating from experimental animal data to humans (i.e., 

interspecies differences); (3) uncertainty in extrapolating from data obtained in a study with 

less-than-lifetime exposure (i.e., extrapolating from subchronic to chronic exposure); 

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

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

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

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

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

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

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

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

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

The major adjustment steps are described more fully below.

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

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

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

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

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

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

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

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

among humans.

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

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

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

account for expected species differences and associated uncertainty in extrapolating from 

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

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

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

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

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

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

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

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

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

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

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

analysis, which is not always possible. Use of a NOAEL is the next preferred approach after 

BMD analysis in determining a POD for deriving a health effect reference value. However, 

many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a 

NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3-fold is 

often applied. 

5) The database UF is intended to account for the potential for deriving an 

underprotective RfD/RfC due to a data gap preventing complete characterization of the 

chemical’s toxicity. In the absence of studies for a known or suspected endpoint of concern, a 

UF of 10 or 3-fold is typically applied.

There is no RfD or other comparable chronic health benchmark value for lead compounds. 

Thus, to address multipathway human health and environmental risks associated with 

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 
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0.15 μg/m3, in combination with the specified choice of indicator, averaging time, and form, 

is requisite to protect public health, including the health of sensitive groups, with an adequate 

margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and 

exposure analyses, and their associated uncertainties can be found in EPA’s final rule revising 

the lead NAAQS (73 FR 66970-66981, November 12, 2008). 

We also note the uncertainties associated with the health-based (i.e., primary) NAAQS are 

likely less than the uncertainties associated with dose-response values developed for many of 

the other HAP, particularly those HAP for which no human health data exist. In 1988, EPA’s 

IRIS program reviewed the health effects data regarding lead and its inorganic compounds 

and determined that it would be inappropriate to develop an RfD for these compounds, 

saying, “A great deal of information on the health effects of lead has been obtained through 

decades of medical observation and scientific research. This information has been assessed in 

the development of air and water quality criteria by the Agency's Office of Health and 

Environmental Assessment (OHEA) in support of regulatory decision-making by the Office 

of Air Quality Planning and Standards (OAQPS) and by the Office of Drinking Water 

(ODW). By comparison to most other environmental toxicants, the degree of uncertainty 

about the health effects of lead is quite low. It appears that some of these effects, particularly 

changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral 

development, may occur at blood lead levels so low as to be essentially without a threshold. 

The Agency's RfD Work Group discussed inorganic lead (and lead compounds) at two 

meetings (07/08/1985 and 07/22/1985) and considered it inappropriate to develop an RfD for 

inorganic lead.” EPA’s IRIS assessment for Lead and compounds (inorganic) (CASRN 7439-

92-1), http://www.epa.gov/iris/subst/0277.htm. 

We note further that because of the multi-pathway, multi-media impacts of lead, the risk 

assessment supporting the NAAQS considered direct inhalation exposures and indirect airrelated multi-pathway exposures from industrial sources like primary and secondary lead 

smelting operations. It also considered background lead exposures from other sources (like 

contaminated drinking water and exposure to lead-based paints). In revising the NAAQS for 

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 
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extrapolating from animals to humans; 3) uncertainty in LOAEL to NOAEL adjustments; and 

4) uncertainty in accounting for an incomplete database on toxic effects of potential concern. 

Additional adjustments are often applied to account for uncertainty in extrapolation from 

observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an 

acute reference value at another exposure duration (e.g., 1 hour). 

Not all acute reference values are developed for the same purpose and care must be taken 

when interpreting the results of an acute assessment of human health effects relative to the 

reference value or values being exceeded. Where relevant to the estimated exposures, the 

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

characterization as potential uncertainties. 
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5 References

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

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

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

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

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

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

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

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

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