Draft Risk Assessment for the Ferroalloys Source Category

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## Deliberative Draft Document for EPA Internal Review

Draft
Residual Risk Assessment for the Ferroalloys Source Category

by EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation August 2011Draft Risk Assessment for the Ferroalloys Source Category

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### Table of Contents

1 Introduction

................................ ................................ ................................ ........................ 4

2 Methods

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

................................ ................................ ........................... 4
2.2 Dispersion modeling for inhalation exposure assessment

................................ ........... 5
2.3 Estimating chronic human inhalation exposure

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

................................ ........................ 8
2.5 Multipathway human health and environmental risk screening

................................ 10
2.6 Dose

- response as sessment

................................ ................................ ......................... 12
2.6.1 Sources of chronic dose

- response information

................................ .................. 12
2.6.2 Sources of acute dose

- response information

................................ ...................... 17
2.7 Risk characterization

................................ ................................ ................................ . 20

2.7.1 General

................................ ................................ ................................ ............... 20
2.7.2 Mixtures

................................ ................................ ................................ ............. 22
3 Risk results f

or the Ferroalloys source category

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

................................ ................................ .... 23
3.2 Baseline risk characterization

................................ ................................ .................... 25
3.3 Post

- control risk characterization

................................ ................................ .............. 31

4 General discussion of uncertainties and how they have been addressed

......................... 31
4.1 Exposure modeling uncertainties

................................ ................................ .............. 31
4.2 Uncertainties in the dose

- response relationships

................................ ....................... 32
5 References

................................ ................................ ................................ ........................ 42

Index of Tables

Table 2.2

- 1 AERMOD version 09292 model options for RTR modeling

................................ 6
Table 2.6

- 1 (A) Dose

- Response Values for Chronic Inhalation Exposure to Carci nogens

.... 15
Table 2.6

- 1 (B) Dose

- Response Values for Chronic Oral Exposure to Carcinogens

............. 16
Table 2.6

- 2 (A) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

................................ ................................ ................................ ................................ .................. 17
Table 2.6

- 2 (B) Dose

- Response Values for Chronic Oral Exposure to Noncarcinogens

....... 17
Table 2.6

- 2 Dose

- Response Values for Acute Exposure

................................ ........................ 20
Table 3.1

- 1 Summary of Em issions from the Ferroalloys Source Category and Availability of

Dose

- Response Values

................................ ................................ ................................ ............. 24
Table 3.2

- 1 Summary of Source Category Le vel Inhalation Risks for Ferroalloys

................ 26
Table 3.2

- 2 Summary of Refined Acute Results for Ferroalloys

................................ ............ 28
Table 3.2

- 3 Comparison of AERMOD Modeled to Ambient Manganese Concentrations Reported by Three Monitors in Close Proximity to the Eramet Facility

................................ . 30

Appendices

Appendix 1 Emissions Inventory Support Memoranda Appendix 2 Technical Support Document for HEM 3 Modeling Appendix 3 Meteorological Data for HEM 3 ModelingDraft Risk Assessment for the Ferroalloys Source Category

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Appendix 4 Analysis of data on short

- term emission rates relative to long

- term emission

rates Appendix 5 Technical Support Document for TRIM

- Based Multipathway Screening

Scenario for RTR: Summary of Approach and Evaluation Appendix 6 Draft Detailed Risk Mo deling Results Appendix 7 Acute Impacts Refined Analysis Appendix 8 Dispersion Model Receptor Revisions and Additions for Ferroalloys

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model

AEGL Acute exposure guideline level

ASTDR US Agency for Toxic Substances and Disease Registry
CalEPA California Environmental Agency

CTE Central Tendency Estimate

ERPG Emergency Response Planning Guideline

HAP Hazardous Air Pollutant

HEM Human Exposure Model

HI Hazard index HQ Hazard q uotient

IRIS Integrated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of action

NAC National Advisory Committee NAAQS National Ambient Air Quality Standards

NATA National Air Toxics Assessment

NEI National Emissions Inventory

NPRM Notice of Proposed Rulemaking

PB

- HAP Persistent and Bioaccumulative

- HAP
POM Polycyclic organic matter

REL Reference exposure level
RfC Reference concentration

RfD Reference dose

RME Reasonable Maximum Exposur e RTR Risk and Technology

TOSHI Target

- organ

- specific hazard index

URE Unit risk estimateDraft Risk Assessment for the Ferroalloys Source Category

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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 p rovision. 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,

processe s 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 resid ual 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 Pla n , ‖ 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 Methodo logies‖ [ 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 assessment s 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 availa ble. Our responses to the key
recommendations of the SAB are outlined in a memo entitled, ―EPA’s Actions in Response to Key Recommendations from t he SAB Review of RTR risk Assessment Methodologies‖ [ 4 ].

This document contains the methods and the results of baseline risk assessments (i.e., after the implementation of the MACT standard) and the results of the post

- control scenario risk

assessment per formed for the f erroalloys source category. The methods discussion includes descriptions of the methods used to develop refined estimates of chronic inhalation exposures and human health risks for cancer and noncancer endpoints, as well as descriptions of the
methods used to screen for acute health risks, chronic non

- inhalation health risks, and adverse
environmental effects

.



### 2 Methods

2.1 Emissions and source data
Data from a CAA section 114 information collection request (ICR) were used for this

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

U.S

. which we are aware are covered by the Ferroalloys Production MACT standard . The ICR requested available information regarding process equipment, control devices, point an dDraft Risk Assessment for the Ferroalloys Source Category

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fugitive emissions, practices used to control fugitive emissions, and other aspects of facility operations, including stack parameters and locations. Additionally, we requested that the two facilities conduct emissions tests for certain HAP from specifi c processes that were considered representative of the industry. Pollutants tested included metal HAP (e.g., manganese, nickel compounds) hydrochloric acid

, formaldehyde, mercury, polyaromatic hydrocarbons, and dioxins and furans. The results of these te sts were submitted to EPA in the fall of 2010 and are available in the docket. Details on the development of the emissions and source data for this source category are discussed in the Appendix 1 memorandum , entitled Draft Modeling Emission Estimation Met hodologies for Ferroalloy Facilities . Section 3 below provides a summary of the emissions.



### 2.2 Dispersion modeling for inhalation exposure assessment
Both long

- and short

- term inhalation exposure concentrations and associated health risk s from each facility in the source category were estimated using the Human Exposure Model in combination with the American Meteorological Society/EPA Regulatory Model dispersion modeling system (HEM

- AERMOD, or HEM 3 ). The approach used in applying this mode ling system is outlined below, and further details are provided in Appendix 2

. The HEM 3 performs three main operations: atmospheric dispersion modeling, estimation of individual human exposures and health risks, and estimation of population risks. This s ection focuses on the dispersion modeling component. The exposure and risk characterization components are
discussed in other subsections of Sections 2 and 3.

The dispersion model in the HEM 3 system, AERMOD version 09292, is a state

- of

- the

science Gaussi an 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 r ate from the inventory into the 8,760 hours of the year.

The first step in the application of the HEM 3 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.Draft Risk Assessment for the Ferroalloys Source Category

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Table 2.2

- 1 AERMOD version 09292 mo del options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Poin t, area represented as pseudo point source

Receptor orientation Polar (13 rings and 16 radials) Discrete (census block centroids) and u ser

- supplied receptors

Terrain characterization Actual from USGS 1

- degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option No

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

In HEM 3 , meteorological data are ordinarily selected from a list of 189 National Weather Service (NWS) surface observation stations across the continental United States, Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is selected as representative of the conditions at the subject facility. Ideally, when c onsidering 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 forma tted model input files derived from available meteorological data, we modeled only a single year, typically 1991. While the selection of a single year may
result in under

- prediction of long

- term ambient levels at some locations, likewise it may result

in over

- prediction at others. For each facility identified by its characteristic latitude and longitude coordinates, the closest meteorological station was used in the dispersion modeling

. The average distance between a modeled facility and the applicable m eteorological station

was 90 miles ( 1 45 km). Appendix 3 ( Meteorological Data Processing Using AERMET for

HEM 3 ) provides a complete listing of stations and assumptions along with further details used in processing the data through AERMET. The sensitivity of model results to the selection of the nearest weather station and the use of one year of meteorological data is discussed in

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

The HEM 3 system estimates ambient concen trations at the geographic centroids of census blocks (using the 2000 Census) and at other receptor locations that can be specified by the

user. See Appendix 8 ( Dispersion Model Receptor Revisions and Addition s for the Ferroalloys Source Category ) for a d iscussion 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 facilit y). 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 currentlyDraft Risk Assessment for the Ferroalloys Source Category

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uninhabited areas was not considered. Census blocks, the finest resolution available in the census data, are typically comprised of approximately 40 people or about ten households.

In contrast to the development of ambient concentrations for evaluating long

- term exposures, which was performed only for occupi ed 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 m eters 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 contain s only annual emission totals, we generally apply the assumption to all source categories that the maximum one

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

The ave rage hourly emissions rate is defined as the total emissions for a year divided by the total number of operating hours in the year. This choice of a factor of ten for screening was originally based on engineering judgment

. To develop a more robust peak

- t o

- 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 data set from a
number of source s located in Texas (originally reported on by All en et al

. 2004)[ 7 ]. In that report, the Texas Environmental Research Consortium Project compared hourly and annual
emissions data for volatile organic compound s for all facilities in a heavily

- industrialized 4

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

- month time period in 2001 . We obtained the dataset and performed our own analysis, focusing that analysis on sources whic h reported emitting high quantities of HAP over short periods of time (see Appendix 4 Analysis of data on short

- term emission rates relative to long

- term emission

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

w as a factor of 74 times the annual average , and the 99 th percentile ratio of peak hourly emission rate to the annual hourly emission rate was 9 . Based on these results, we chose the factor of ten for all initial screening . These factors are intended to c over all possible hourly peaks associated with routinely

- variable emissions. While there have been some documented emission excursions above this level, our analysis of the data from the Texas Environmental Research Consortium suggests that this factor sh ould cover more than 99% of the short

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

. We have no data relating specifically to peak short

- term emissions of particulate HAP. In the absence of
source category

- specific data, we use this same default approach for particulate emissions as
well.

Census block elevations for HEM 3 modeling were determined nationally from the US Geological Service 1

- degree digital elevation model (DEM) data files, which have a spatial
resolution of a bout 90 meters. Elevations of polar grid points used in estimating short

- and long

- term ambient concentrations were assumed to be equal to the highest elevation of any census block falling within the polar grid sector corresponding to the grid point. If a sector does not contain any blocks, the model defaults the elevation to that of the nearest block. If an elevation is not provided for the emission source, the model uses the average elevation of all sectors within the innermost model ring.Draft Risk Assessment for the Ferroalloys Source Category

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In addition to using receptor elevation to determine plume height, AERMOD adjusts the plume’s flow if nearby elevated hills are expected to influence the wind patterns. For details on how hill heights were estimated and used in the AERMOD modeling see Appendix 2

.



### 2.3 Estimating chronic human inhalation exposure
We used the annual average ambient air concentration of each HAP at each census block centroid as a surrogate for the lifetime inhalation exposure concentration of all the people who
reside in the census blo ck. 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 e xperience 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 e stimates about 25% for particulate HAP; it will also reduce risk estimates for gaseous HAP, but typically by much less. Second, basing exposure estimates on average ambient concentrations at census block centroids may underestimate or overestimate actual exposure concentrations at some residences. Further reducing exposure estimates for the most highly exposed residents by modeling their short

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

We did not address long

- term migration nor popul ation 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 t hree 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 a cross the affected population, shifting it toward higher estimated individual risks at the upper end and reducing the number of people estimated to be at lower risks, thereby increasing the estimated number of people at specific risk levels.

When scre ening for potentially significant acute exposures, we used an estimate of the highest hourly ambient concentration at any off

- site location as the surrogate for the maximum potential acute exposure concentration for any individual.



### 2.4 Acute Risk Screening an d Refined Assessments
In establishing a scientifically defensible approach for the assessment of potential health risks due to acute exposures to HAP, we f ollowed the same general approach that has been used for developing chronic health risk assessments u nder the residual risk program. That is, we developed a tiered, iterative approach. This approach to risk assessment was endorsed by theDraft Risk Assessment for the Ferroalloys Source Category

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National Academy of Sciences in its 1993 publication ―Science and Judgment in Risk Assessment‖ and subsequently was adopted in the EPA’s ―Residual Risk Report to Congress‖
in 1999.

The assessment methodology is designed to eliminate from further consideration those
facilities for which we have confidence that no acute adverse health effects of concern will

occur. To do so, we use what is called a tiered, iterative approach to the asse ssment. This means that we bega n with a screening assessment, which relies on readily available data and uses conservative assumptions that in combination approximate a worst

- case expos ure . The result of this screening process is that either the facility being assessed poses no potential acute health risks (i.e., it ―screens out‖), or that it requires further , more refined assessment.
A refined acute assessment could u s e industry

- or s ite

- 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 other s, lesser amount s of site

- specific data can be used to determine that acute exposures are not a concern, and significant additional data collection is not necessary.

Acute health risk screening was performed as the first step. We used conservative assumptions for emission rates, meteorology, and exposure location. We used the following

worst

- case assumptions in our screening approach:

Peak 1

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

- hour emission

rates For facilities with multipl e emission points, peak 1

- hour emissions were assumed to occur at all emission points at the same time. For facilities with multiple emission points, 1

- hour concentrations at each receptor
were assumed to be the sum of the maximum concentrations due to eac h emission point, regardless of whether those maximum concentrations occurred during the same
hour.

Worst

- case meteorology (from one year of local meteorology ) was assumed to occur at the same time the peak emission rates occur. The recommended EPA local

- scale dispersion model, AERMOD, is used for simulating atmospheric dispersion. A person was assumed to be located downwind at the point of maximum modeled impact during this same worst

- case 1

- hour period, but no nearer to the source than 100

meters.
The m aximum impact was compared to multiple short

- term health benchmarks for the

HAP being assessed to determine if a possible acute health risk might exist. These benchmarks are described in section 2.6 of this report.

As mentioned above, when we identify ac ute impacts which exceed their relevant benchmarks, we pursue refining our acute screening estimates to the extent possible . In some cases, this include s the use of a refined emissions multiplier to estimate the peak hourly emission rates from the average rates (rather than the default factor of 10)

. In other cases, this
entail s determining the actual physical layout and boundaries of a facility to more accurately gauge where people might reasonably be exposed for an hour.Draft Risk Assessment for the Ferroalloys Source Category

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For the ferroalloys source ca tegory, maximum hourly emissions estimates were available, so we did not use the default emissions multiplier of 10. See the Appendix 1 memorandum

M ethodology for Estimation of Maximum Hourly Emissions for Ferroalloys Sources for the detailed description of how the maximum hourly emissions were developed for the ferroalloys source category. We also conducted a review of the layout of the emission points at the facilities with the facility boundaries to determine the maximum o ff

- site acute impact for the facilities that did not screen out during the initial run. Refer to Appendices 6 and 7 for the
detailed results for these sites.



### 2.5 Multipathway human health and environmental risk screening
The potential for significant human health risks d ue to exposures via routes other than inhalation (i.e., multipathway exposures) was screened by first determining whether any sources emitted any hazardous air pollutants known to be persistent and bioaccumulative in the environment (PB

- HAP) 1 . The PB

- HAP compounds or compound classes are identified for the screening from the EPA’s Air Toxics Risk Assessment Library [ 8 ] . Examples of

PB

- HAP are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, heptachlor, hexachloroben zene, hexachlorocyclohexane, lead compounds, mercury compounds, methoxychlor, polychlorinated biphenyls, polycyclic organic matter (POM)

, toxaphene, and triflurali n. Emissions of lead, mercury, and POM were identified in the emissions inventory for the fe rroalloys source category.

These PB

- HAP e missions were evaluated for potential non

- inhalation risks and adverse environmental impacts using our recently

- developed screening scenario which was developed
for use with the TRIM.FaTE 2 model. This screening scenario uses environmental media outputs from the peer

- reviewed TRIM.FaTE to estimate the maximum potential ingestion risks for any specified emission scenario by using a generic farming/fishing exposure scenario
that simulates a subsistence environment. The screening scenario retains many of the ingestion and scenario inputs developed for EPA’s Human Health Risk Assessment Protocols (HHRAP) for hazardous waste combustion facilities. 3 In the development of the screening scenario a sensitivity analysis wa s conducted to ensure that its key design parameters were established such that environmental media concentrations were not underestimated, and to also minimize the occurrence of false positives for human health endpoints. Se e Appendix 5 for a complete discussion of the development and testing of the screening scenario, as well as for the values of facility

- level emission rates developed for screening potentially significant multipathway impacts. For the purpose of developing emission ra tes for our multipathway screening, we derived emission levels for each PB

- HAP (other than lead) at which the
maximum human health risk would be 1 in a million for lifetime cancer risk or a hazard quotient of 1.0 for noncancer imp acts.

1 Although the two

- letter chemical symbol for lead is Pb, in this assessment PB

- HAP refers to the many air pollutants known to be persistent and bioaccumulative in the environment. In instances where the report is specifically referring to lead, it is s pelled out (i.e., the two

- letter chemical symbol for lead is not used in this document).

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

3 EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous Waste Combustion Facilities; http://www.epa.gov/epaoswer/hazwaste/combust/riskvol.htm#volume1Draft Risk Assessment for the Ferroalloys Source Category

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In evaluating the potential multipathway risks from emissions of lead compounds, rather than developing a screening emission rate for them , we compared maximum estimated chronic atmospheric concentrations with the current National Ambient Air Quality Standard (NAAQS) for l ead. 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 set ting 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 protec t 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 ri sk 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 fo r lead, combined with: 2) the site

- specific dispersion modeling used in this assessment to estimated ambient lead concentrations due to ferroalloys emissions. It should be noted, however, that this comparison does not account for possible population expos ures 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 Adminis trator, 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 beca use 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 i ndicate the potential for adverse
environmental effects.

Additionally, w e evaluated the potential for significant ecological exposures to non PB

- HAP
from exceedances of chronic human health inhalation thresholds in the ambient air near these
facilities. Human health dose

- response threshold values are generally derived from studies conducted on laboratory animals (such as rodents) and developed with the inclusions of uncertainty factors that could be as high as 3000. As a result, these human threshold val ues are often significantly lower than the level expected to cause an adverse effect in an exposed rodent. It should be noted that there is a scarcity of data on the direct atmospheric impact of these HAP on other receptors, such as plants, birds, and wil dlife. Thus, if the maximumDraft Risk Assessment for the Ferroalloys Source Category

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

, we have generally concluded that mammalian receptors should be at no risk of adverse effects due to inhalation exposures from non PB

- HAP, and have assu rance that other ecological receptors are also not at any significant risk from direct atmospheric impact. In some isolated cases where we have data indicating potential adverse impacts on plants, birds, or other wildlife due to the direct atmospheric imp acts of specific HAP, we note that as an uncertainty and, where possible, refine our analysis by comparing our modeled impacts to available threshold values
from the scientific literature.



### 2.6 Dose

- r esponse a ssessment

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 f erroalloys

source s were based on the EPA Office of Air Quality Planning and Standards’ (OAQPS) existing recommendations for HAP [ 9 ], also used for NATA [ 10 ]. This information has been obtained from various sources and prioritized according to (1) conceptual consistency with EPA risk assessment guidelines and (2) level of peer review received. The prioritization process was aimed at incorporating into our assessments the best available science with respect to dose

- response information. The recommendations are based on the f ollowing 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 reg arding 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, fo r 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/m 3 in air. ‖ The

SF is ―a n upper bound, approximating a 95% confidence limit, on the increased cancer risk from a lifetime exposure to an agent. This estimate, [is] usually expressed in units of proportion (of a population) affected per mg/kg

- day ...‖ EPA disseminates dose

- res ponse 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 assessm ents since 1996 have also undergone independent external peer review. The current IRIS process includes review by EPA scientists, interagency reviewers from other federal agencies, and the public, and peer review by independent scientists external to EPA. EPA’s scienceDraft Risk Assessment for the Ferroalloys Source Category

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policy approach , under the current carcinogen guidelines, is to use linear low

- dose extrapolation as a default option for carcinogens for which the mode of action (MOA) has not been identified. We expect future EPA dose

- response assessment s to identify nonlinear MOAs where appropriate, and we will use those analyses (once they are peer reviewed) in our risk assessments. At this time, however, there are no available carcinogen dose

- response assessments for inhalation exposure that are based on a nonlinear MOA

.

2) US Agency for Toxic Substances and Disease Registry (ATSDR). ATSDR, which is part of the US Department of Health and Human Services, develops and publishes Minimum Risk Levels (MRLs) [ 12 ] for inhalation and oral exposure to many toxic substances. As
stated on the ATSDR web site: ― Following discussions with scientists within the Department of Health and Human Services (HHS) and the EPA, ATSDR chose to adopt a practice similar to that of the EPA's Reference Dose (RfD) and Reference Conc entration (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

- respo nse 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 pe er review. As cited in the CalEPA Technical Support Document for developing their chronic assessments 4 : ―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 gener al 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 value s for some HAP based on professional judgment, as follows:

1) The IRIS URE for nickel inhalation was derived from evidence of the carcinogenic effects of nickel subsulfide. Based on past scientific and technical considerations, the determination of the per cent of nickel subsulfide was considered a major factor for

4 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III

- Technical Support Docume nt
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/ch ronic_rels/pdf/relsP32k.pdf )Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 14

estimating the extent and magnitude of the risks of cancer due to nickel

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

- emitting sources (including oil combust ion, coal combustion, and others) suggested that at least 35 percent of total nickel emissions may be soluble compounds and that the URE for the mixture of inhaled nickel compounds (based on nickel subsulfide, and representative of pure insoluble crystalli ne nickel) could be derived to reflect the assumption that 65 percent of the total mass of nickel may be carcinogenic. Based on more recent, consistent views of major scientific bodies (i.e., NTP in their 12 th ROC, IARC, and other international agencies) 5 that now consider all nickel compounds to be carcinogenic, we currently consider all nickel compounds to have the potential of being as carcinogenic as nickel subsulfide. To implement this approach in our inhalation risk assessments, we apply the

IRIS UR E for nickel subsulfide without a factor to reflect the assumption that 100 percent of the total mass of nickel may be as carcinogenic as pure nickel subsulfide

. Based on the fact that there may be differences in toxicity and/or carcinogenic potential acr oss the different nickel compounds, and given that there have been two URE values derived for exposure to mixtures of nickel compounds 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.

2) Where possible for emissions of unspecified mixtures of HAP cat egories such as metal compounds and POM, we apply category

- specific chemical speciation profiles appropriate to the source category to develop a composite dose

- response value for the category.

3) A substantial proportion of POM reported to EPA’s National E mission Inventory (NEI)

are not s pe ciated in t o individual compounds. A s a result, it is necessary to apply the same

s im plifying a ssumptions to assessments that are used in NATA [ 17 ]. The NATA approach partitions POM into eight different non

- overlapping ―g roups‖ that are modeled as separate pollutants. Each POM group comprises POM species of similar carcinogenic potency, for which we can apply the same URE.

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

cancer dose

- response value for formaldehyde (5.5 x 10 - 9 per μg/m 3 ) was based on better
science than the IRIS dose

- response value (1.3 x 10 - 5 per μg/m 3 ), and we switched from using the IRIS value to the CIIT value in risk assessments supporting regulatory actions. However, subsequent research published by EPA suggests that the CIIT model was not appropriate and in 2010 EPA returned to using 1991 IRIS value, which is more health protective [ 18 ]. 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 in May of 2011. EPA is reviewing the public comments and the NAS independent scientific peer review, and the draft IRIS assessment will be revised and the final assessment will be posted on the IRIS database. In the interim, we will present findings using the 1991 IRIS value as a primary estimate, and may also consider other information as the science
evolves.

5 World Health Organization (WHO, 1991) and the Europea n Union’s Scientific Committee o n Health and Environmental Risks (SCHER, 2006)

.Draft Risk Assessment for the Ferroalloys Source Category

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The emissions inventory for the f erroalloys source category includes emissions of HAP with
availa b le ch r onic quantitative inhalation dose

- response values. Of these, 23 are classified as known, probably, or possible carcinogens, with quantitative cancer dose

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

- response values,
and the source of each value are listed in Table 2.6

- 1.A. The POM compounds with chronic
oral cancer dose

- response values available (for which multipathway screening assessments

were per formed) are listed in Table 2.6

- 1.B. Eleven HAP have quantitative inhalation chronic noncancer threshold values available; one of these eleven H AP (mercury), for which a multipathway assessment w as performed, also ha s quantitative oral chronic noncancer

t hreshold values available. These 11 HAP, their threshold values, and the source of the value
are listed in Table 2.6

- 2.A and Table 2.6

- 2.B.

Table 2.6

- 1 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 6 = cancer risk per μg/m 3 of a verage lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of
Environmental Health Hazard Assessm e nt, EPA/OAQPS = interim value recommended by the
EPA Office of Ai r Quality Planning and Standards

Pollutant CAS Number 7 URE 5 (1/μg/m 3 ) Source

Arsenic Compounds 7440382 4.3E

- 3 IRIS

Chrom i um ( VI) 18540299 1.2E

- 2 IRIS Formaldehyde 50000 1.3E

- 5 IRIS Naphthalene 91203 3.4E

- 5 CAL Nickel Compounds 7440020 4.8E

- 4 EPA OAQPS Polycyclic Organic M a tt e r 246 8 EPA OAQPS

2

- Methylnaphthalene 91576 8.8E

- 5 EPA OAQPS Acenaphthene 83329 8.8E

- 5 EPA OAQPS Acenaphthylene 206968 8.8E

- 5 EPA OAQPS

Anthracene 120127 8.8E

- 5 EPA OAQPS Benz[a]Anthracene 56553 1.6E

- 4 CAL Benzo[a]Pyrene 50328 1.6E

- 3 CAL Benzo[b]Fluoranthene 205992 1.6E

- 4 CAL Benzo[e]Pyrene 192972 8.8E

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

- 5 EPA OAQPS Benzo[k]Fluoranthene 207089 1.6E

- 4 CAL

6 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/m 3 in air. URE’s are considered upper bound estimates meaning they represent a plausible upper limit to the true value.

7 Chemical Abstract Services identification number. For groups of compounds that lac k a CAS number we have used a surrogate 3

- digit identifier corresponding to the group’s position on the CAA list of HAP.

8 Assigned the URE associated with a mixture of POM compounds having a similar potency. Details of this method, also used in the Natio nal Air Toxics Assessments, are available at http://www.epa.gov/ttn/atw/nata2005/methods.html#pomDraft 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) 6 = cancer risk per μg/m 3 of a verage lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of
Environmental Health Hazard Assessm e nt, EPA/OAQPS = interim value recommended by the
EPA Office of Ai r Quality Planning and Standards

Pollutant CAS Number 7 URE 5 (1/μg/m 3 ) Source

Chrysene 218019 1.6E

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

- 3 CAL

Fluoranthene 206440 8.8E

- 5 EPA OAQPS

Fluorene 86737 8.8E

- 5 EPA OAQPS Indeno[1,2,3

- c,d]Pyrene 193395 1.6E

- 4 CAL Perylene 198550 8.8E

- 5 EPA OAQPS

Phenanthrene 85018 8.8E

- 5 EPA OAQPS Pyrene 129000 8.8E

- 5 EPA OAQPS

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 Number 9 SF (1/mg/kg/d) Source Polycyclic Organic M a tt e r 246 Benz[a]Anthracene 56553 1.2 CAL Benzo[a]Pyrene 50328 7.3 IRIS Benzo[b]Fluoranthene 205992 1.2 CAL Benzo[k]Fluoranthene 207089 1.2 CAL Chrysene 218019 0.12 CAL Dibenzo[a,h]Anthracene 53703 4.1 CAL Indeno[1,2,3

- c,d]Pyrene 193395 1.2 CALDraft Risk Assessment for the Ferroalloys Source Category

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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 recomm ended by the EPA Office of Air Quality Planning and
Standards

Pollutant CAS Number 6 RfC (mg/m 3 ) Source 9

Arsenic Compounds 174 0.000015 CAL Chromium (VI) 18540299 0.0001 IRIS

- L Formaldehyde 50000 0.0098 ATSDR Hydrochloric Acid 7647010 0.02 IRIS

- L Hydrofluoric Acid 7664393 0.014 CAL

Lead Compounds 182 0.00015 EPA OAQPS Manganese 183 0.00005 IRIS

- M Mercury Compounds

Mercuric Chloride 7487947 0.00003 CAL Mercury (elemental) 7439976 0.0003 IRIS

- M Naphthalene 91203 0.003 IRIS

– L/M

Nickel Compounds 7440020 0.00009 ATSDR

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 durin g a lifetime.
Sources: IRIS = EPA Integrated Risk Information System

Pollutant CAS Number RfD (mg/kg/d) Source 10

Mercuric chloride 11 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 [ 19 ]

. Depending on availability, the results from screening acute assessments are

9 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 repor ted in the IRIS file.

10 The descriptors L (low), M (medium), and H (high) have been added for IRIS RfC values to indicate the overall level of confidence in the RfC value, as reported in the IRIS file.

11 The multipathway exposure assessment for mercury inc luded fate and transport analysis, that included separate oral exposure estimates for divalent mercury and methylmercury.Draft Risk Assessment for the Ferroalloys Source Category

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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 Acut e 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 defi nition of that level and any limitations expressed therein. Comparisons among different available inhalation health effect reference values (both acute and chronic) for selected HAP can be
found in a n ewly released EPA document [ 20 ].

California Acute Refe rence Exposure Levels (RELs ). The California Environmental Protection Agency (CalEPA) has developed acute dose

- response reference values for many
substan ces, expressing the results as a cute inhalation Reference Exposure Levels (RELs).

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

― t he concentration level at or below which no adverse health effects are anticipated for a specified exposure duration . [ 21 ]

. REL s 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 (NA C) on Acute Exposure Guideline Levels (NAC/AEGL) f or Hazardous
Substances , and then reviewed and published by the National Research Council

. A s 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 as sessments 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 p urpose 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 che mical releases at fixed facilities and from transport carriers.‖Draft Risk Assessment for the Ferroalloys Source Category

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The NAC/AEGL defines AEGL

- 1 and AEGL

- 2 as:

― AEGL

- 1 is the airborne concentration (expressed as ppm or mg/m 3 ) 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 c oncentration (expressed as ppm or mg/m 3 ) 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 t o escape. ‖

― Airborne concentrations below AEGL

- 1 represent exposure levels that can produce mild and progressively increasing but transient and nondisabling odor, taste, and sensory irritation or certain asymptomatic, nonsensory effects. With increasing airborne concentrations above each AEGL, there is a progressive increase in the likelihood of occurrence and the severity of effects described for each corresponding AEGL. Although the AEGL values represent threshold levels for the general public, includ ing 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 concentr ation s below the corresponding AEGL.‖

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [ 22 ] for acute exposures at three different levels of sev erity. 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 pote ntially life

- threatening (ERPG

- 3).

ERPG values ( http://www.aiha.org/1documents/Committees/ERP

- erpglevels.pdf ) are described in their supporting documentation as follows: ― Emergenc y Response Planning Guidelines (ERPGs) were developed for emergency planning and are intended as health based guideline concentrations for single exposures to chemicals. These guidelines (i.e., the ERPG
Documents and ERPG values) are intended for use as p lanning tools for assessing the adequacy of accident prevention and emergency response plans, including transportation

emergency planning and for developing comm unity emergency response plans. The emphasis
is on ERPGs as planning values: When an actual chemical emergency occurs there is seldom
time to measure airborne concentrations and then to take action. ‖

ERPG

- 1 and ERPG

- 2 values are defined by AIHA as follows:

― ERPG

- 1 is the maximum airborne concentration below which it is believed that nearly al l individuals could be exposed for up to 1 hour without experiencing other than mildDraft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 20

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

― ERPG

- 2 is the maximum airborne concentration below which it is believed t hat nearly all individuals could be exposed for up to 1 hour without experiencing or developing irreversible or other serious health effects or symptoms which could impair an individual's ability to take protective action. ‖

The emissions inventory for the f erroalloys source category includes emissions of six HAP with relevant and available quantitative acute dose

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

- 3

.

Table 2.6

- 3 Dose

- Response Values for Acute Exposure

Pollutant CAS Number AEGL

- 1 (1

- hr) (mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

- 1

(mg/m 3 ) ERPG

- 2

(mg/m 3 ) REL
Arsenic Compounds 7440382 0.0002 Formaldehyde 50000 1.1 17 1.1 17 0.055 Hydrochloric Acid 7647010 2.7 33 2.7 33 2.1 Hydrofluoric Acid 7664393 0.82 20 0.82 20 0.24

M ercury (elemental) 7439976 1.7 2 0 .0006

Nickel Compounds 7440020 0.006



### 2.7 Risk c haracterization

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 gen eral, 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 identifi ed and discussed. Further, the EPA Administrator’s March

1995 Policy for Risk Characterization [ 23 ] 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 [ 24 ], in 2002 by the Agency’s information quality guidelines [ 25 ], and in the

OMB/OST P September 2007 Memorandum on Updated Principles for Risk Analysis 12 , and are incorporated in these assessments.

12 Memorandum f

or t he Heads o f Executive Departments a nd Agencies

- Updated Principles for Risk Analysis ( September 19, 2007 ), From Susan E. Dudley, Administrator, Office of Information and Regulatory Affairs, Office of Management and Budget; and Sharon L. Hays, Associate Director and Deputy Director for Science, Office of Science and Technology Policy ( http://www.whitehouse.gov/omb/ memoranda/fy2007/m07

- 24.pdf )Draft Risk Assessment for the Ferroalloys Source Category

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Estimates of health risk are presented in the context of uncertainties and limitations in the data and methodology. Through our tiered, itera tive 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 individua l cancer risks and noncancer hazards, as well as cancer incidence estimates) along with a discussion of the major uncertainties associated with their derivation to provide decision makers with the fullest picture of the assessment and its
limitations.

For each carcinogenic HAP included in an assessment that has a potency estimate available,
individu al and population cancer risks we re calculated by multiplying the corresponding lifetime average exposure estimate by the appropriate URE. This calculated canc er risk is defined as the upper

- bound probability of developing cancer over a 70

- y r 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 p redicted, and could be

zero.

For EPA’s list of carcinogenic HAP that act by a mutagenic mode

- of

- action [ 26 ], we applied
EPA’s Supplemental Guidance for Assessing Susceptibility from Early

- Life Exposure to Carcinogens [ 27

]

. 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 implem entation policy [ 28 ] recommends applyi ng the Supplemental Guidance to all carcinogenic PAH s 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 wa s estimated by multip lying 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 wa s divided by 70 years to obtain an
estimat e 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

effec ts. 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 R fC values for theDraft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 22

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 inha lation, calculated for each HAP at each census block centroid. As discussed above, RfCs incorporate generally conservative uncertainty factors in the face of uncertain extrapolations, such that an HQ greater than one does not necessarily suggest the onset of adverse effects. The HQ cannot be translated to a probability that adverse effects will occur, and is unlikely to be proportional to adverse health effect outcomes in a population

.

Screening for potentially significant acute inhalation exposures also followed the HQ approach. We divided the maximum estimated acute exposure by each available short

- term threshold value to develop an array of HQ values relative to the various acute endpoints and thresholds. In general, when none of these HQ values are greater than one, there is no potential for acute risk. In those cases where HQ values above one are seen, additional
information is used to determine if there is a potential for significant acute risks.

2.7.2 Mixtures
Since most or all receptors in these asse ssments 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 assess ments use the mixtures guidelines’ [ 29

, 30 ] 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 differe nt 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 substance s 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. A ll TOSHI calculations presented here were based exclusively on effects occurring
at the ― critical d ose‖ (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

. Be cause 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 a s 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.Draft Risk Assessment for the Ferroalloys Source Category

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Becaus e of the conservative nature of the acute inhalation screening and the variable nature of emissions and potential exposures, acute impacts were screened on an individual pollutant basis, not using the TOSHI approach.



### 3 Risk r esults for the Ferroalloys s ource c ategory

3.1 Source c ategory d escription and r esults
The ferroalloys production source category consists of major source facilities that produce ferroalloys containing manganese, such as ferromanganese and silicomanganese . A f erroalloy
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 t o produce steel and cast iron products with enhanced or special properties. Ferroalloy s production normally occurs when an electric arc furnace (EAF) is charged with raw materials to begin smelting the ores. The molten product is ―tapped‖ or poured from the furnace. Raw material and product handling (e.g., crushing and screening operations) also occur as part of the ferroalloy production process. The HAP emission sources at ferroalloys production facilities
include open EAFs, semi

- closed EAFs, tapping o perations, 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 pr esent 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 polycyclic aromatic hydrocarbon (PAH), are also expected but in r elatively small quantities. Additionally, compounds such as chlorine and fluorides are present in coal, which is used as a raw material in the furnace, and thus hydrochloric acid and hydrogen fluoride emissions can be expected.

We currently estimate that there are 2 ferroalloys production facilities operating in the U.S.
The emissions for the ferroalloys source categor y data set are summarized in Table 3.1

- 1. The total HAP emissions for the source category are approximately 170 tons per year. Based on these data, the HAP emitt ed in the largest quantities are manganese compounds, hydrochloric acid, lead compounds, and hydro gen fluoride . Emissions of these four HAP make up 95 percent of the total emissions by mass. Persistent a nd bioaccumulative HAP (PB

HAP ) 13 reported as emissions from these facilities include lead compounds, mercury compounds, and polycyclic organic matter.

13 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, Ex posure, and Risk Assessment at http://www.epa.gov/ttn/fera/risk_atra_vol1.html

.Draft Risk Assessment for the Ferroalloys Source Category

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Table 3.1

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

Re sponse Values

HAP a Emission

Estimates (tpy) Number of

Facilities
where HAP Repor ted or
Estimated ( 2 facilities
in data set) Prioritized Inhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk
Estimate for
Cancer? Reference

Concentration
for Noncancer? Health

Benchmark
Values for Acute
Noncancer?

Manganese Compounds 126 2 Hydrochloric Acid 17 2 Lead Compounds 8 2 c Hydro gen fluoride 8 2 Nickel Compounds 4 2 Formaldehyde 2 2 Naphthalene 0.7 2 Polycyclic Organic Matter Acenaphthylene 0.7 2

Fluorene 0.6 2

Fluoranthene 0.5 2

2

- Methylnaphthalene 0.4 2

Phenanthrene 0.4 2

Anthracene 0.2 2
Benzo[b]Fluoranthene 0.2 2 Acenaphthene 0.1 2 Chrysene 0.1 2
Benzo[e]Pyrene 0.09 2
Pyrene 0.09 2
Benz[a]Anthracene 0.06 2
Benzo[k]Fluoranthene 0.05 2 Benzo[g,h,i]Perylene 0.04 2
Indeno[1,2,3

- c,d]Pyrene 0.04 2
Benzo[a]Pyrene 0.02 2
Dibenzo[a,h]Anthracene 0.01 2 Perylene 0.002 2 Mercury Compounds Mercury (elemental) 0.3 2

Mercuric chloride 0.07 2

Arsenic Compounds 0.2 2 Chromium Compounds

Chromium III 0.2 2
Chromium (VI) 0.06 2

a Notes for how HAP were speciated for risk assessment: For most metals, emissions reported as the elemental metal are combined with metal compound emissions (e.g., ―cadmium‖ emissions modeled as ―cadmium & compounds‖). In the absence of speciation information, we assume the reported mass is 100 percent metal.

Chromium emissions wer e speciated based on test data; hexavalent chromium data were collected from the EAF fabric
filter outl ets using EPA Method 316. See Append ix 1 ( Draft Modeling Emission Estimation Methodologies for Ferroalloy Facilities ) for more information )

.Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 25

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

as 80 percent ―mer cury (elemental)‖ and 2 0 percent ―mercuric chloride

. ‖ Mer cury speciation profiles can be found on the EPA’s Technology Transfer Network website for emissions inventories at

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

. For emissions of any chemicals or chemical groups classified as polycyclic organic matter (POM), emissions were grouped into POM subgroups as found on EPA’s Technology Transfer Network websi te for the 2002 National

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

b Specific dose

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

toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html

.

c There is no reference concentration for lead. In considering noncancer hazards for lead in this assessment, we compared the average exposure estimates to the National Ambient Air Quality Standards (NAAQS) for lead (0.15 μg/m 3 ). These NAAQS for lead were recently re viewed with revisions adopted in October 2008 ( http://www.epa.gov/air/lead/actions.html ). The primary (health

- based) standard is a maximum or not

- to

- be

- exceeded, rolling three

- month average, measured as total suspended particles (TSP). The secondary (welfare

- based) standard is identical to the primary standard.



### 3.2 Baseline r isk c haracterization
This section presents the results of the risk assessment for the f erroalloys source category

. The basic chr onic 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
maximu m 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 haza rd 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

.

Table s 3 .2

- 1 and 3.2

- 2 summarize the chronic and acute inhalation risk results for this source
category

. T he results indicate that the current maximum lifetime individual cancer risk posed by these two facilities could be as high as 80 in a million , with arsenic, chromium, and nickel compounds from process fugitives as the major contributors to the risk. The total estimated cancer incidence from this source category is 0. 00 2 ex cess cancer cases per year, or one excess case in every 500 years. A pproximate ly 1, 0 00 pe ople were estimated to have cancer risks above 10 in a million and approximatel y 26 ,000 peop le were estimated to have cancer
risks above 1 in a million considering the two facilities in this source category . The
maximum chronic noncancer TOSHI value for the source category could be up to 90 from
emissions of man ganese from process fugitives , with an estimated 28,000 people exposed to TOSHI levels above 1 due to manganese emissions . At exposure levels above its RfC, manganese can cause central nervous system effects. Visual reaction time, hand steadiness, and eye

- hand coordination effects have been reported in chronically

- exposed workers.

Analysis of potential differences between actual emissions levels and the maximum emissions
allowable under the M ACT standards were also calculated for stack emissions for the two
facilities. 14 Risk estimates based on the actual emissions were then scaled up using these
factors. (See Appendix 1 for a discussion of the development of the allowable factors.) Risk

14 MACT

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

MAC T standard only has emission limits for stack emissions.Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 26

res ults from the inhalation risk assessment using the MACT

- allowable stack emissions
indicate that the maximum lifetime individual cancer risk could be as high as 100 in a million,
and that the maximum chronic noncancer TOSHI value co uld be as high as 200 at the MACT

allowable emissions level. Risks could be higher than these presented here if process fugitive
emissions increase with increased stack emissions.

Taken together

, these results suggest that there is an unacceptable level of risk from this

sou rce category, primarily associated with chronic noncancer inhalation health risks due to the
actual and MACT

- allowable HAP emissions , and cancer risk due to MACT

- allowable HAP
emissions.

Worst

- case a cute hazard quotients (HQs) were calculated for every HAP shown in
Table 3.1

- 1 that has an acute benchmark, and the high est screening acute HQ value of 40 (based on the acute REL for arsenic and nickel compounds) is shown in Table 3 .2

- 1

. For cases where the screening acute HQ was greater than 1, we fur ther refined the estimates by determining the highest HQ value that is outside facility boundaries . Ta ble 3

. 2

- 2 provides
more information on the refined acute risk estimates for HAP that had an acute HQ greater than 1 for any benchmark. T he highest refin ed worst

- case acute HQ value is 10 (based on the acute REL for nickel compounds).

Table 3.2

- 1 Summary of Source Category Level Inhalation Risks for Ferroalloys

Result HAP “Drivers” Facilities in Source Category

Number of Facilities Estimated to be in Source Category 2 n/a

Number of Facilities Identified in NEI and
Modeled in Risk Assessment 2 n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 1 million) 8 0 nickel compounds, chromium compounds, arsenic compounds Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a

Greater than or equal to 10 in 1 million 2 nickel compounds, chromium compounds, arsenic compounds, POM72002, POM75002, POM76002, naphthalene

Greater than or equal to 1 in 1 million 2 nickel compounds, chromium compounds, arsenic compounds, POM72002, POM75002, POM76002, naphthalene

Chronic Noncancer Risks

Maximum Neurological Hazard Index 90 manganese compounds

Maximum Developmental Hazard Index 2 lead compounds, arsenic compoundsDraft Risk Assessment for the Ferroalloys Source Category

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Table 3.2

- 1 Summary of Source Category Level Inhalation Risks for Ferroalloys

Result HAP “Drivers” Number of Facilities with Maximum Neurological Hazard Index:

Greater than 1 2 manganese compounds , lead compounds Number of Facilities with Maximum Developmental Hazard Index:

Greater than 1 1 lead compounds, arsenic compounds Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 40
40 nickel compounds (REL)

arsenic compounds (REL)

Number of Facilities With Potential for
Acute Effects 2 arsenic compounds, nickel compounds

Refined Acute Noncancer Results

Maximum Acute Hazard Quotient 10

9 nickel compounds (REL)

arsenic compounds (REL)

Number of Facilities With Potential for
Acute Effects 2 arsenic compounds, nickel compounds Population Exposure Number of People Living Within 50
Kilometers of Facilities Modeled 37,000 n/a

Number of People Exposed to Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 1,000 n/a Greater than or equal to 1 in 1 million 26,000 n/a Number of People Exposed to Noncancer Neurological Hazard Index:

Greater than 10 30 n/a

Greater than 1 28,000 n/a Number of People Exposed to Noncancer Developmental Hazard Index:

Greater than 1 600 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.002 n/a

Contribution of HAP to Cancer Incidence nickel compounds 36% n/a chromium compounds 24% n/a arsenic compounds 24% n/a

POM72002 10% n/aDraft Risk Assessment for the Ferroalloys Source Category

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Table 3.2

- 2 Summary of Refined Acute Results for Ferroalloys

Refined Results Maximum Acute Hazard Quotients Acute Dose

- Response Values

HAP Max. 1

- hr.

Air Conc. (mg/m 3 ) Based on

REL Based on

AEGL

- 1/
ERPG

- 1 Based on

AEGL

- 2/
ERPG

- 2 REL

(mg/m 3 ) AEGL

- 1

(1

- hr) (mg/m 3 ) ERPG

- 1

(mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

- 2

(mg/m 3 )

Arsenic compounds 0.007 9 n/a n/a 0.0002

Nickel compounds 0.3 10 n/a n/a 0.006

Notes on Refined Process: 1) The initial screening was performed for all emitted HAP with available acute dose

- response values. Only those pollutants whose screening HQs were greater than 1 for at least one acute threshold value are shown in the table. 2) HAP with available acute dose

- response values which are not in the table do not carry any potential for posing acute health risks, based on an analysis of currently available emissions data.
Notes on Acute Dose

- Respo nse Values:

REL

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

- hour exposures.

AEGL

– Acute exposure guideline levels represent emergency exposure (1

- hour) limits for the general public.
AEGL

- 1 is th e exposure level above which it is predicted that the general population, including susceptible individuals, could experience effects t hat are notable discomfort, but which are transient and reversible upon cessation of exposure.

AEGL

- 2 is the exposure lev el above which it is predicted that the general population, including susceptible individuals, could experience irreversible or other serious, long

- lasting adverse health effects of an impaired ability to escape.

EPRG

– Emergency Removal Program guideline s represent emergency exposure (1

- hour) limits for the general public.

ERPG

- 1 is the maximum level below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing other than mild, transient adverse health effec ts.
ERPG

- 2 is the maximum exposure below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing or developing irreversible or other serious health effects or symptoms which could impair an individual’s abili ty to take protective action.

To identify potential multipathway health risks from PB

- HAP other than lead, we first performed a screening analysis that compared emissions of PB

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

- HAP emitted by facilities in this category include mercury and POM ( as benzo(a)pyrene toxicity equivalen ts, or TEQ). The two facilities in the source category reported emissions of these

PB

- HAP, and both of them had emission rat es greater than the screening emission threshold
values for the pollutants indicating that there may be potential multipathway impacts of
concern due to emissions of these pollutants from these two facilitie s. One facility’s emission rates of mercury exceeded the screening threshold by 30 times, while the other facility ’s mercury emission rates exceeded the threshold by 7 times. For POM, one facility ’s emission

rates exceeded the screening threshold by 600 times, while the other facility ’s emission ra tes exceeded the threshold by 50 times. For mercury, exceeding the screening emission rate
relates to a potential for creating a chronic noncancer hazard quotient in excess of 1. For POM, exceeding the screening emission rate relates to a potential for c reating a cancer risk in

excess of 1 in a million.

For the two PB

- HAP that did not screen out during our initial multipathway screening analysis, we refined our analysis somewhat with some additional site

- specific information to develop an ―intermediate screen. ‖ (See Appendix 5 for more information about this intermediate screen.) T he additional site

- specific information included the land use aroundDraft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 29

the facilities

, the location of fishable lakes , and local wind direction and speed. The result of
this analysis was the development of site

- specific emission screening thresholds for POM and mercury. Based on this intermediate screening analysis, neither facility screened out, meaning that we cannot rule out the potential for multipathway risks of concern impacts due to emissions of these pollutants from these two facilities

. One facility’s emission rates

exceeded the site

- specific screening threshold for mercury by 4 times, while the other facility’s emission rates equaled the threshold value. For POM, o ne facility’s emissions rates

exceeded the site

- specific screening threshold for POM by 60 times, while the other facility’s emission rates exceeded the threshold by 5 times. We were unable to obtain the data necessary to conduct a fully refined assessmen t of multipathway risks from these two
facilities.

I n evaluating the potential for mul ti pathway effects from emissions of lead, modeled
maximum annual lead concentrations were compared to the NAAQS for lead (0.15 μg/m 3 )

. Results of this analysis estimate that the NAAQS for lead could be exceeded at one of the two facilities, largely due to process fugitive emissions. T his analysis estimates that the annual lead concentrations could be as high as two times the NAAQS for lead

, and if the maximum

3

- month rolling average concentrations were used, the result could be even greater concentrations above the NAAQS. However, this additional analysis was not conducted because, as s hown below in the results for the post

- control scenario risk assessment, the
maximum annual lead concentration after controls is significantly below the NAAQS, with a
value of 0.02 μg/m 3

.

In addition to the model results presented above, for calendar year 2009, we also compared annual average AERMOD estimates of ambient manganes e concentrations with those measured during a three to four month period in late 2009 at three monitors in close proximity to the Eramet ferroalloys facility. More specifically, we compared maximum manganese
concentrations from the EPA’s Schools Monitorin g Initiative to the predicted manganese concentrations at model receptor locations in close prox imity to these monitoring sites. The facility and monitors are shown in Figure 1. Results of this analysis are presented in
Table 3.2

- 3 and indicate that at t hese three locations, model predictions are generally within a factor of two when compared to monitored concentrations at these sites. These results indicate that AERMOD estimates of ambient air manganese concentrations provide a reasonable representation of the measured maximum manganese concentrations present in the ambient air near this facility.Draft Risk Assessment for the Ferroalloys Source Category

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Table 3.2

- 3 Comparison of AERMOD Modeled to Ambient Manganese Concentrations Reported by Three Monitors in Close Proximity to the Eramet Facility

Location Annual Average AERMOD

Modeled Manganese Concentration (μg /m 3 ) 15 Average Monitored Manganese Concentration (μg /m 3 ) 16 Model to

Monitor Ratio

N eale Elementary School (Vienna, WV) 0.07 0.07 1.00

The Ohio Valley
Educational
Service Center (Marietta, OH) 0.11

- 0.19 0.11 1.00

- 1.73

Warren Elementary School (Marietta, OH) 0.07

- 0.29 0.146 0.48

- 1.98

15 Model estimate based on closest polar receptor to monitor location. In cases where the monitor falls between several polar receptors the range of modeled concentrations is provided.

16 Average moni tor concentrations across can be found at: http://www.epa.gov/schoolair/index.htmlDraft Risk Assessment for the Ferroalloys Source Category

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### 3.3 Post

- control risk characterization

As noted above, the results of the baseline risk assessment suggest that there is an unacceptable level of risk from this source category. Process fugitive emissions of metal HAP are primarily driving these risks. Given this, using the same risk assessment methods
descr ibed above, we estimated what the risks would be if the two manganese facilities adopted control measures to limit process fugitive emissions (e.g., full building enclosure). Based on this scenario, we estimated (based on use of the same modeling assumpti ons and methodologies used for the baseline risk assessment) that the maximum chronic noncancer
inhalation TOSHI value would be reduced to 2, from the baseline estimate of 90. The number of people estimated to have a TOSHI greater than 1 would be reduced from 28,000 to less
than 10. With respect to cancer risk, given the control scenario described above, the cancer
MIR would be reduced from 8 0 in a million (i.e., pre

- controls) to approximately 5 in a million (i.e., post

- controls), with an estimated reduct ion in cancer incidence to 0.0004 excess cancer cases per year. In addition, the number of people estimated to have a cancer risk greater than or equal to 1 in a million would be reduced from 26,000 to 1,300

.

We also note that post

- control, the maximum worst

- case acute refined HQ value would be reduced from a potential high of 10 to 0.3 (using the REL value for nickel compounds and the refinements described for the baseline acute assessment).

Considering post

- control emissions of multipathway HAP, mercury emissions are reduced approximately 88 percent, while POM emissions are reduced approximately 66 percent from
the baseline emission rates. Based on our intermediate screening approach for multipathway risks, emissions of mercury ―screen out‖, or a re reduced below the screening thresholds for both facilities, indicating no potential for multipathway impacts of concern due to mercury. However, e missions of POM ( as benzo(a)pyrene TEQ ) remain above the intermediate screening threshold s for both facili ties (one by a factor of 20 and one by a factor of 2)

, indicating that we cannot rule out the potential for multipathway impacts of concern due to
emissions of POM from these facilities. As mentioned above, the highest lead concentration after controls, 0 .02 μg /m 3 , is well below the NAAQS, indicating a low potential for multipathway impacts of concern due to lead.



### 4 General d iscussion of u ncertainties and h ow t hey h ave b een

a ddressed

4.1 E xposure m odeling u ncertainties
Although every effort has been made to ide ntify 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 expos ure estimates are biased high by not accounting for short

- or long

- term population mobility, andDraft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 32

by neglecting processes like deposition, plume depletion, and atmospheric degradation. Additionally, estimates of the maximum individual risk (MIR) contain un certainty , because they are deriv ed 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 no t 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 a nd 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 th e 1999 NATA found that the selection of the meteorology dataset location could result in a range of chronic ambient concentrations which varied from as much as 17% below the predicted value to as much as 84% higher than the predicted value. This variabili ty translates directly to the predicted exposures and risks in our assessment, indicating that the actual risks could vary from 17% lower to 84% higher than the predicted values.

We have purposely biased the acute screening results high, considering that they depend upon the joint occurrence of independent factors, such as hourly emissions rates, meteorology and human activity patterns. Furthermore, i n 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 b y developing a better understanding of the geography of the facility relative to potential exposure locations. In this case, refining the assessment for the

two facilit ies that did not screen out resulted in lower acute risks.



### 4.2 Uncertainties in the d ose
- r esponse r elationships
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. Noncance r reference values are generally derived for chronic exposures (up to a lifetime), bu t may also be derived for acute (

- term (>24 hours up to 30 days), and subchronic (>30 days up to 10% of lifetime) exposure durations, all of which are de rived based on an assumption of continuous exposure throughout the duration specified. For the purposes of assessing all potential health risks associated wit h
the emissions included in an assessment, we rely on both chronic (cancer and noncancer) and

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

Although every effort is made to identify peer

- review ed 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 e xposure levels is possible.Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 33

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 [ 31 ] (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

p rotective.‖ 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 v alues 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 describe s 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). 17 In some circumstances, the true risk could be as low as zero; however, in oth er circumstances the risk could also be greater. 18
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. 19 EPA also

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

18 The exception to this is the URE for benzene, which is consid ered to cover a range of values, each end of which is considered to be equally plausible, and which is based on maximum likelihood estimates.

19 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) ―[Default] options are generic a pproaches, 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 Govern ment: Managing the Process defined default option as ―theDraft Risk Assessment for the Ferroalloys Source Category

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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 wh ich 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 data bases 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 prese nt estimates demonstrating the impact on the assessment of alternative choices, data, models and assumptions [ 32 ]. Some of the major sources of uncertainty and variability in deriving cancer risk values are described more fully below.

(1) The qualitativ e 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 exp erimental animal bioassay are necessarily predictive of the sites at which
tumors would occur in humans. 20 However, unless scientific support is available to show otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target

o rgan 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 al so 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 absorp tion, 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 appropria te 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 underestimat ion of risk.

(3) For the quantitative extrapolation of cancer risk estimates from experimental animals to humans, EPA uses scaling methodologies (relating expected response to differences in physical size of the species), which introduce another source of uncertainty. These

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 bi nd 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/pdf s/ratf

- final.pdf.

20 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 fo r evaluating the implications of animal study results for humans.‖Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 35

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 d ifference 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 s caled estimates.

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which there is a specified excess risk of cancer, which is used as the point of departure (or POD) for the remainder of the calculation. Statistical uncertainty in developing a POD using a benchmark dose (BMD) approach is generally addressed though use of the 95% lower
confidence limit on the dose at which the s pecified 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 l ow 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 observati ons 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 us e 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 r isks 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 c onsiderations. 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 science

policy choice (a ―default‖) when available data do not allow a compound

- specific determination. This approach is designed to not underestimate risk in the face of uncertainty and variability. EPA believes that linear dose

- response models, when appropriately applied as part of EPA’s cancer risk assessment process, provide an upper bound estimate of risk and generally provide a health protective approach. Note that another source of uncertainty is the
characterization of low

- dose non linear, 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 withinDraft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 36

human populati ons. Another National Research Council (NRC) report [ 33 ] 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 tha t 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 cu rrent 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) [ 34 ]. It is im portant 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. Sub ramaniam 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 ac tion 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 excepti on 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 m ay help address variability in response is to extrapolate human response from results observed in the most sensitive species and sex tested, resulting typically in the highest URE which can be supported by reliable data, thus supporting estimates that are designed not to underestimate risk in the face of uncertainty and variability.

Chronic noncancer assessment

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

- protective. That is, EPA and other organizatio ns 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.Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 37

When there are gaps in the availabl e 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 values 21 e.g., factors of 10 or 3,
used in the abse nce 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
tend ency 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 underes timated.

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 perh aps 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. 22 To der ive values that are intended to be ―without appreciable risk,‖ EPA’s methodology relies upon an uncertainty factor (UF) approach [ 35 ], [ 36 ] which includes consideration of both uncertainty and variability.

EPA begins by evaluating all of the available peer

- reviewed literature to determine non

cancer 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

t he dose or concentration at which the toxic response was not significantly elevated (no
observed adverse effect level

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

A series of downward adjustments using default UFs is then appli ed to the POD to estimate
the reference value [ 37

] . 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. T he UFs are intended to account for: (1) variation in susceptibility among the members of the human population (i.e., inter

- individual

21 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 underestim ated (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.

22 See IRIS glossaryDraft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 38

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

unce rtainty (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

- fo ld 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 full y 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 varia tion 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) Extrapol ation 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 extrapol ated 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 lacki ng, 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 s pecific 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 uncerta inties; however, such dosimetric adjustments are not always possible. Information may not be available to quantitatively assess toxicokinetic or toxicodynamic differences between animals and humans, and in many cases a 10

- fold UF (with separate factors of 3 for toxicokinetic and toxicodynamic components) is used to account for expected species differences and associated uncertainty in extrapolating from laboratory animals to humans in the derivation of a reference value. If information on one orDraft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 39

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) Toxici ty 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 eff ect 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 inte nded 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 ty pically 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 w ere 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 esti mate 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 judg ments 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 va lues (73FR at 66998). In so doing, the Administrator decided that, a level for the primary lead standard of 0.15 μg/m 3 , in combination with the specified choice of indicator, averaging time, and form, is requisite to protect public health, including the h ealth 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 6697 0

- 66981, November 12, 2008).Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 40

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 fo r 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 info rmation 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
Environment al 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 he alth 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 witho ut 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 (inor ganic) (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 dir ect inhalation exposures and indirect air

related 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 ex posure 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 ba sed on chemical

specific 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 par agraph). The UFs applied in acute reference value derivation include: 1) heterogeneity among humans; 2) uncertainty in extrapolating from animals to humans; 3) uncertainty in LOAEL to NOAEL adjustments; and 4) uncertainty in accounting for an incomplete database on toxic effects of potential concern. Additional adjustments are often applied to account for uncertainty in extrapolation from observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an
acute reference value a t another exposure duration (e.g., 1 hour).Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 41

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 b eing exceeded. W here 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.Draft Risk Assessment for the Ferroalloys Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 42



### 5 References

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