Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

1 

## Draft
Residual Risk Assessment for the Ferroalloys Source Category

by EPA’s Office of Air Quality Planning and Standards

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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

2 

### Table of Contents

1 Introduction

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

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

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

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

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

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

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

- response assessment

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

- response information

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

- response information

................................ ...................... 18
2.7 Risk characterization

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

................................ ................................ ................................ ............... 21
2.7.2 Mixtures

................................ ................................ ................................ ............. 2 2
3 Risk results f

or the Ferroalloys source category

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

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

................................ ................................ .................... 26
3.3 Post

- control risk characterization

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

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

................................ ................................ .............. 33
4.2 Uncertainties in the dose

- response relationships

................................ ....................... 34
5 References

................................ ................................ ................................ ........................ 44

Index of Tables

Table 2.2

- 1 AERMOD version 09292 model options for RTR modeling

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

- 1 (A) Dose

- Response Values for Chronic Inhalation Exposure to Carci nogens

.... 16
Table 2.6

- 1 (B) Dose

- Response Values for Chronic Oral Exposure to Carcinogens

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

- 2 (A) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

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

- 1 (B) Dose

- Response Values for Chronic Oral Exposure to Noncarcinogens

....... 18
Table 2.6

- 3 Dose

- Response Values for Acute Exposure

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

- 1 Summary of 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

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

- 2 Summary of Refined Acute Results for Ferroalloys

................................ ............ 29
Table 3.2

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

................................ . 32

Appendices

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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

3 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

4 

### 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

5 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

6 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

7 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

8 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

9 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

10 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 spelled out (i.e., the two

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

2 EPA’s Total Risk Integrated Methodology (General Information) http://e pa.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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

11 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

12 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

13 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) In the case of nickel compounds, to provide a health

- protective estimate of potential cancer risks, we used t he IRIS URE value for nickel subsulfide in this assessment. Based on past scientific and technical considerations, the determination of the percent of nickel

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

- Technical Support Document
for the Determination of Non

- cancer Chronic Reference Exposure Levels. Air Toxicology and Epidemiology Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. February 2000 ( http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf )Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

14 subsulfide was considered a major factor for estimating the extent and magnitude of the
risks of cancer due to nickel

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

- emitting sources (including oil combustion, coal combustion, and others) suggested that at least 35 percent of total nickel emissions may be soluble compounds and that the URE for the mixture of inhaled nickel compounds (based on
nickel subsulfide, and representative of pure insoluble crystalline nickel) could be derived to reflect the assumption that 65 percent of the total mass of nickel may be carcinogenic. Based on consistent views of major scientific bodies (i.e., National Toxicolog y Program ( NTP ) in their 12 th Report of the Carcinogens ( ROC ) 5 , I nternational Agency for Research on Cancer (I ARC ) 6 , and other international agencies) 7 that consider all nickel compounds to be carcinogenic, we currently consider all nickel compounds to hav e the potential of being carcinogenic to humans

. The 12th Report of the Carcinogens states that the ―combined results of epidemiological studies, mechanistic studies, and carcinogenic studies in rodents support the concept that nickel compounds generate n ickel ions in target cells at sites critical for carcinogenesis, thus allowing consideration and evaluation of these compounds as a single group.‖ Although the precise nickel compound (or compounds) responsible for the carcinogenic effects in humans is no t always clear, studies
indicate that nickel sulfate and the combinations of nickel sulfides and oxides encountered in the nickel refining industries cause cancer in humans (these studies are summarized in a review by Grimsrud et al., 2010 8 ). The major sc ientific bodies mentioned above have also recognized that there are differences in toxicity and/or carcinogenic potential across the different nickel compounds. In this inhalation risk assessment, to take a conservative approach, we have considered all ni ckel compounds to be as carcinogenic as nickel
subsulfide and have applied the IRIS URE for nickel subsulfide without a factor to reflect the assumption that 100 percent of the total mass of nickel may be as carcinogenic as pure nickel subsulfide

. In addition, given that there are two additional URE values 9 derived for exposure to mixtures of nickel compounds , as a group, that are 2

- 3 fold lower than the IRIS URE for nickel subsulfide, the EPA also considers it reasonable to use a value that is
50 percent of the IRIS URE for nickel subsulfide for providing an estimate of the lower end of the plausible range of cancer potency values for different mixtures of nickel compounds.

5 National Toxicology Program (NTP), 2011. Report on carcinogens. 12 th ed. Research Triangle Park, NC: US Department of Health and Human Services (DHHS), Public Health Service. Available onl ine at http://ntp.niehs.nih.gov/ntp/roc/twelfth/roc12.pdf

6 International Agency for Research on Cancer (IARC), 1990. IARC monographs on the evaluation of carcinogenic risks to humans. Chromium, nickel, and welding. Vol. 49. Lyons, France: Internatio nal Agency for Research on Cancer, World Health Organization Vol. 49:256.

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

. 8 Grimsrud TK and Andersen A. Evidence of car cinogenicity in humans of water

- soluble nickel salts. J Occup Med Toxicol 2010, 5:1

- 7. Available online at http://www.ossup

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

9 Two UREs (other than the current IRIS values) have been der ived for nickel compounds as a group : one developed by the California Department of Health Services ( http://www.arb.ca.gov/toxics/id/summary/nickel_tech_b.pdf ) and the other by the Texas Commission on Environmental Quality ( http://www.epa.gov/ttn/atw/nata1 999/99pdfs/healtheffectsinfo.pdf ).Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

15 2) Where possible for emissions of unspecified mixtures of HAP categorie s 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 Emissio n 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 ―groups‖ that are modeled as separate pollutants. Each POM group comprises POM species of similar carcinogenic potency, for which we can apply the same URE.

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

cancer dose

- respons e value for formaldehyde (5.5 x 10 - 9 per μg/m 3 ) was based on better
science than the IRIS cancer 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. S ubsequent research published by EPA suggested that the CIIT model was not appropriate and in 2010 EPA returned to using 1991 IRIS value. EPA has been working on revising the formaldehyde IRIS assessment and the National Academy of Sciences (NAS) completed its review of the EPA’s draft assessment in April of 2011

. 10 EPA will follow the NAS Report recommendations and will present results obtained by implementing the biologically

- based dose

- response ( BBDR ) model for formaldehyde. EPA will compare these estim ates with those currently presented in the External Review draft of the assessment and will discuss their strengths and weaknesses. As recommended by the NAS committee, appropriate sensitivity and uncertainty analyses will be an integral component of impl ementing the BBDR model. In the interim, we will present findings using the 1991 IRIS value as a primary estimate, and EPA may also consider other
information as the science evolves.

The emissions inventory for the 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 T able 2.6

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

- response values available (for which multipathway screening assessments were performed) are listed in Table 2.6

- 1.B. Eleven HAP have quantitative inhalation chronic
noncancer threshold values available; one of these eleven H AP (mercury), for which a multipathway assessment w as performed, also ha s quantitative oral chronic noncancer
threshold values available. These 11 HAP, their threshold values, and the source of the value
are listed in Table 2.6

- 2.A and Table 2.6

- 2.B.

10 http://www.nap.edu/catalog.php?record_id=13142Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

16 Table 2.6

- 1 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 11 = cancer risk per μg/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 Air Quality Planning and Standards

Pollutant CAS Number 12 URE 5 (1/μg/m 3 ) Source

Arsenic Compounds 7440382 4.3E

- 3 IRIS

Chrom i um ( VI) 18540299 1.2E

- 2 IRIS Formaldehyde 13 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 14 EPA OAQPS

2

- Methylnaphthalene 91576 8.8E

- 5 EPA OAQPS Acenaphthene 83329 8.8E

- 5 EPA OAQPS Acenaphthylene 206968 8.8E

- 5 EPA OAQPS

Anthracene 120127 8.8E

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

- 4 CAL Benzo[a]Pyrene 50328 1.6E

- 3 CAL Benzo[b]Fluoranthene 205992 1.6E

- 4 CAL Benzo[e]Pyrene 192972 8.8E

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

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

- 4 CAL Chrysene 218019 1.6E

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

- 3 CAL

Fluoranthene 206440 8.8E

- 5 EPA OAQPS

Fluorene 86737 8.8E

- 5 EPA OAQPS Indeno[1,2,3

- c,d]Pyrene 193395 1.6E

- 4 CAL Perylene 198550 8.8E

- 5 EPA OAQPS

Phenanthrene 85018 8.8E

- 5 EPA OAQPS Pyrene 129000 8.8E

- 5 EPA OAQPS

11 The URE is the upper

- bound excess cancer risk estimated to result from continuous lifetime exposure to an agent at a concentration of 1 μg/m 3 in air. URE’s are considered upper bound estimates meaning they represent a plausible upper limit to the true value.

12 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have used a surrogate 3

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

13 The EPA has used the CIIT value (5.5x10 - 9 per mg/m 3 ) to characterize formaldehyde cancer risks in some
instances.

14 Assigned the URE associated with a mixture of POM compounds having a similar potency. Details of this method, also used in the National Air Toxics Assessments, are available at http://www.epa.gov/ttn/atw/nata2005/methods.html#pomDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

17 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 CAL

Table 2.6

- 2 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of de leterious 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 recommend ed by the EPA Office of Air Quality Planning and Standards
Pollutant CAS Number 6 RfC (mg/m 3 ) Source 15

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

- L Formaldehyde 50000 0.0098 ATSDR Hydrochloric Acid 7647010 0.02 IRIS

- L Hydrofluoric Acid 7664393 0.014 CAL

Lead Compounds 182 0.00015 EPA OAQPS Manganese 183 0.00005 IRIS

- M Mercury Compounds

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

- M Naphthalene 91203 0.003 IRIS

– L/M

Nickel Compounds 7440020 0.00009 ATSDR

15 The descriptors L (low), M (medium), and H (high) have been added for IRIS RfC values to i ndicate the overall level of confidence in the RfC value, as reported in the IRIS file.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

18 Table 2.6

- 1 ( B ) Dose

- Response Values for Chronic Oral Exposure to Noncarcinogens

RfD (reference dose) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System

Pollutant CAS Number RfD (mg/kg/d) Source 16

Mercuric chloride 17 7439976 0.0003 IRIS

- H

2.6.2 Sources of acute dose

- response information

Hazard identification and dose

- response assessment information for preliminary acute inhalation exposure assessments are based on the existing recommendations of OAQPS for HAP [ 18 ]

. Depending on availability, the results from screening acute assessments ar e compared to both ―no effects‖ reference levels for the general public, such as the California Reference Exposure Levels (RELs), as well as emergency response levels, such as Acute Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelin es (ERPGs), with the recognition that the ultimate interpretation of any potential risks associated with an estimated exceedance of a particular reference level depends on the definition of that level and any limitations expressed therein. Comparisons amo ng different available inhalation health effect reference values (both acute and chronic) for selected HAP can be
found in a n ewly released EPA document [ 19 ].

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

- response reference values for many
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 . [ 20 ]

. RELs are based on the most sensitive, relevant,
adverse heal th 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

uncerta inties, 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 Concen trations (RfCs) for chronic exposures (and, in fact, California also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory
Committee (NAC) on Acute Exposure Guideline Levels (NAC/AEGL) f or Hazardous

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

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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

19 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 assessments to aid in the development of

emergency p reparedness and prevention plans, as well as real time emergency response actions, for accidental chemical releases at fixed facilities and from transport carriers.‖ The
document states that ―the primary purpose of the AEGL program and the NAC/AEGL
Commit tee is to develop guideline levels for once

- in

- a

- lifetime , short

- term exposures to airborne concentrations of acutely toxic, high

- priority chemicals.‖ In detailing the intended application of AEGL values, the document states that

, ― It is anticipated that the AEGL values will be used for regulatory and nonregulatory purposes by U.S. Federal and State agencies, and possibly the international community in conjunction with chemical emergency response, planning, and prevention programs. More specifically, the AEGL values will be used for conducting various risk assessments to aid in the development of emergency preparedness and prevention plans, as well as real

- time emergency response actions, for accidental chemical releases at fixed facilities and from transp ort carriers.‖

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 nota ble discomfort, irritation, or certain asymptomatic nonsensory effects. However, the effects are not disabling and are transient and reversible upon cessation of

exposure. ‖

― AEGL

- 2 is the airborne concentration (expressed as ppm or mg/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 to escape. ‖

― Airborne concentrations below AEGL

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

Emergency Re sponse Planning Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [ 21 ] for acute exposures at three different levels of severity. These guidelines represent
concentrations f

or exposure of the general population (but not particularly sensitive persons)Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

20 for up to 1 hour associated with effects expected to be mild or transient (ERPG

- 1), irreversible or serious (ERPG

- 2), and potentially life

- threatening (ERPG

- 3).

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

- erpglevels.pdf ) are described in their supporting documentation as follows: ― Emergency Response Planning Guidelines (ERPGs) were develop ed for emergency planning and are intended as health based guideline concentrations for single exposures to chemicals. These guidelines (i.e., the ERPG
Documents and ERPG values) are intended for use as planning tools for assessing the adequacy of acciden t 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 me asure airborne concentrations and then to take action. ‖

ERPG

- 1 and ERPG

- 2 values are defined by AIHA as follows:

― ERPG

- 1 is the maximum airborne concentration below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing other than mild
transient adverse health effects or without perceiving a clearly defined, objectionable
odor. ‖

― ERPG

- 2 is the maximum airborne concentration below which it is believed that nearly all individuals could be expose d 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 0.006Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

21 

### 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 [ 22 ] specifies that a risk characterization ―be prepared in a manner that is clear, transparent, reasonable, and consistent with other risk
characterizations of similar scope prepared across programs in the Agency.‖ These principles of transparency and consistency have been reinforced by the Agency’s Risk Characterization
Handbook [ 23 ], in 2002 by the Agency’s information quality guidelines [ 24 ], and in the
OMB/OST P September 2007 Memorandum on Updated Principles for Risk Analysis 18 , and are incorporated in these assessments.

Estimates of health risk are presented in the context of uncertainties and limitations in the data and methodology. Through our tiered, 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 [ 25 ], we applied
EPA’s Supplemental Guidance for Assessing Susceptibility from Early

- Life Exposure to Carcinogens [ 26 ]

. This guidance has the effect of adjusting the URE by factors of 10 (for children aged 0

- 1), 3 (for children aged 2

- 15), or 1.6 (for 70 years of exposure beginning at birth), as needed in risk assessments . In this case, this has the effect of increasing the estimated life time risks for these pollutants by a factor of 1.6. In addition, although only a

18 Memorandum f

or t he Heads o f Executive Departments a nd Agencies

- Up dated 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

22 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 [ 27 ] 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 the compound(s) of concern (i.e., high, medium, or low confidence) and discusses the impact of this on possible health interpretations.

The risk characterization for chronic effects other than cancer is expressed in terms of the HQ
for 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.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

23 To combine risks across multiple carcinogens, our assess ments use the mixtures guidelines’ [ 28

, 29 ] default assumption of additivity of effects, and combine risks by summing them using the independence formula in the mixtures guidelines.

In assessing noncancer hazard from chronic exposures, in cases where 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.

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 ofDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

24 polycyclic organic matter (POM), such as polycyclic aromatic hydrocarbon (PAH), are also expected but in r elatively small quantities. Additionally, chlorine is present in coal, which is used as a raw material in the furnace, and thus hydrochloric acid emissions can be expected.

We currently estimate that there are 2 ferroalloys production facilities oper ating 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 160 tons per year. Based on these data, the HAP emitt ed in the largest quantities are manganese compounds, hydrochloric acid, and lead compounds . Emissions of these three HAP make up 93 percent of
the total emissions by mass. Persistent and bioaccumulative HAP (PB

- HAP ) 19 reported as
emissions from these fa cilities include lead compounds, mercury compounds, and polycyclic organic matter.

Table 3.1

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

Response 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 d 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

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

EPa

- 453K

- 04

- 001A, as referenced in the ANPRM and provide d on the EPA’s Technology Transfer Network website for Fate, Exposure, and Risk Assessment at http://www.epa.gov/ttn/fera/risk_atra_vol1.html

.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

25 Table 3.1

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

Response 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?

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.

Chr omium 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 Appendix 1 ( Draft Modeling Emission Estimation Methodologies for Ferroalloy Facilities ) for more inform ation )

. 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 Tec hnology Transfer Network website for emissions inventories at http://www.epa.gov/ttn/chief/net/2005inventory.html#inventorydata

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

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

b Specific dose

- response values for each chemical are identified on EPA’s Technology Transfer Network website for air
toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html

.

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

average exposur e estimates to the National Ambient Air Quality Standards (NAAQS) for lead (0.15 μg/m 3 ). These NAAQS for lead were recently reviewed with revisions adopted in October 2008 ( http://www.epa.gov/air/lead /actions.html ). The primary (health

- based) standard is a maximum or not

- to

- be

- exceeded, rolling three

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

- based) standard is identical to the primary standard.

d The hydrogen fluoride emissions presented here were included in the risk assessment, however they are based on using one

half of the test detection limit. All emission tests for hydrogen fluoride were below the detection limit, so half of the
detection l imit was used. Therefore this estimate of emissions is likely an overestimate. The actual emissions are probably
much lower and could be as low as zero. More information about the test and emissions estimates can be found in the
memorandum Modeling Emis sion Estimation Methodologies for Ferroalloy Facilities , which is Appendix 1 to this risk
document.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

26 

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

. The basic chronic inhalatio n risk estimates presented here are the maximum individual lifetime cancer risk, the maximum chronic hazard index, and the cancer incidence. We also present results from our acute inhalation impact screening assessments in the form of maximum hazard quoti ents, as well as the results of our preliminary screen for potential non

inhalation risks from PB

- HAP. Also presented are the HAP ―drivers,‖ which are the HAP that collectively contribute 90 percent of the maximum cancer risk or maximum hazard at the high est 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 up to 80 in a million , with arsenic, chromium, and nick el 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 sourc e 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 and an estimated 30 people exposed to a TOSHI greater than 10 due to mang an ese emiss ions

. Given that the results show a high TOSHI value, we provide some additional discussion of the manganese RfC associated with the inhalation of manganese and our confidence in the principal studies supporting the development of that RfC for context. I n the case of manganese, the effect of concern was a
decrease in visual reaction time in adult males who were occupationally exposed to manganese. The effects were seen at a dose

- adjusted value of 0.05 mg/m 3 and then to derive the RfC, EPA divided this va lue by 1000 to account for uncertainties related to sensitive individuals (10x), use of the lowest exposure level at which effects were observed in lieu of a level without effects (10x), and due to database limitations (10x). We note that the
concentratio n reflected in the maximum TOSHI of 90 (0.0045 mg/m 3 ) is approximately a factor of 10 lower than the 0.05 mg/m 3 dose

- adjusted effect level in a n adult male work force
and used in the derivation of the RfC. The population from which the effect level was de rived was an adult male worker population, and that this population does not necessarily represent the general population

. The EPA has ―medium confidence‖ (as used and described in the IRIS database) in the RfC value of 0.00005 mg/m 3 . The confidence level reflects the overall level of uncertainty in the principal studies, which were based on human occupational studies, and the database. Please see the full IRIS summary for manganese for further discussion of
the RfC. 20

20 IRIS Manganese (1995) http://www.epa.gov/iris/subst/0373.htmDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

27 Overall confidence in the principal studies (Roels et al., 1987, 1992) is ―medium‖. Neither of the principal studies identified a no observed adverse effect level (NOAEL) for neurobehavioral effects, nor did either study directly measure particle size or provide information on the particle size distribution. The 1992 study by Roels et al. did provide respirable and total dust measurements, but the 1987 study measured only total dust. 21 These limitations of the studies are mitigated by the fact that the principa l studies found similar indications of neurobehavioral dysfunction, which was consistent with the results of other
human studies. In addition, the 1992 Roels et al. study provides sufficient information to establish individual integrated exposures; the 19 87 Roels et al. study did not.

Confidence in the database on manganese health effects is ―medium‖. The duration of exposure was relatively limited and the workers were relatively young in all of the principal and supporting studies. These temporal limit ations raise concerns that longer durations of exposure and/or interactions with aging might result in the detection of effects at lower concentrations, as suggested by results from other studies. In addition, the studies, with the exception of the 1992 R oels et al. study in which manganese exposure was limited to manganese oxide, did not specify the species of manganese to which workers were exposed. It is not clear whether certain compounds or oxidation states of manganese are more toxic
than others. A lthough the primary neurotoxicological effects of exposure to airborne manganese have been qualitatively well characterized by the general consistency of effects across studies, the exposure

- effect relationship remains to be well quantified, and a no

- effec t level for neurotoxicity has not been identified in any of these studies thus far. Finally, the effects of manganese on development and reproduction have not been studied adequately. See the full IRIS summary for manganese for more information

.

Analysis of potential differences between actual emissions levels and the maximum emissions
allowable under the MACT standards were also calculated for stack emissions for the two
facilities. 22 Risk estimates based on the actual emissions were then scaled up using these
factors. (See Appendix 1 for a discussion of the development of the allowable factors.) Risk
results from the inhalation risk assessment using the MACT

- allowable stack emissions
indicate that the maximum lifetime individual cancer risk could be as high as 100 in a million,
and that the maximum chronic noncancer TOSHI value 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 emis sions.

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 further 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 t hat had an acute HQ greater

21 Total and respirable dust concentrations were highly correlated, with the Mn content of the respirable fraction representing on average 25% of the manganese content in the total dust. The RfC is based on the respirable
fraction.

22 MACT

- allowable emissions were not calculated for process fugitive or fugitive emissions because the current MACT standard only has emission limits for stack emissions.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

28 than 1 for any benchmark. T he highest refined worst

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

Table 3.2

- 1 Summary of Source Category Level Inhalation Risks for Ferroalloys

Result HAP “Drivers” Facilities in Source Category
Number of Facilities Estimated to be in Source Category 2 n/a

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

Cancer Risks
Maximum Individual Lifetime Cancer Risk (in 1 million) 8 0 23 nickel compounds, chromium compounds, arsenic compounds Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a

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

Greater than or equal to 1 in 1 million 2 nickel compounds, chromium compounds, arsenic compounds, POM72002, POM75002, POM76002, naphthalene
Chronic Noncancer Risks
Maximum Neurological Hazard Index 90 manganese compounds

Maximum Developmental Hazard Index 2 lead compounds, arsenic compounds Number of Facilities with Maximum Neurological Hazard Index:

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

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

Maximum Acute Hazard Quotient 40
40 nickel compounds (REL)

arsenic compounds (REL)

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

23 The plausible range of URE values for nickel (2.4E

- 04 to 4.8E

- 04 per ug/m 3 ) gives rise to a range of estimates for the cancer MIR ( 50 to 80 in a million). The cancer incidence would also have a range of estimate s, but due to presenting the results to one significant figure, there is no change in cancer incidence when using the lower end of the nickel URE range. Estimated population values are not scalable with the nickel URE range, but would be lower using the l ower end of the range.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

29 Table 3.2

- 1 Summary of Source Category Level Inhalation Risks for Ferroalloys

Result HAP “Drivers”
Refined Acute Noncancer Results

Maximum Acute Hazard Quotient 24 10
9 nickel compounds (REL)

arsenic compounds (REL)

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

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

Greater than or equal to 1 in 1 million 26,000 n/a Number of People Exposed to Noncancer Neurological Hazard Index:
Greater than 10 30 n/a
Greater than 1 28,000 n/a Number of People Exposed to Noncancer Developmental Hazard Index:
Greater than 1 600 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.002 n/a

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

POM72002 10% n/a

Table 3.2

- 2 Summary of Refined Acute Results for Ferroalloys

Refined Results Maximum Acute Hazard Quotients Acute Dose

- Response Values

HAP Max. 1

- hr.

Air Conc. (mg/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

24 As shown in Tables 2.6

- 3 and 3.2

- 2 there are no AEGL or ERPG values for arsenic or nickel. Additionally,
there are no short

- term occupational values for these metals to compare to the REL values. It should also be
noted that the re are no reference values available (including a lack of short

- term occupational values) to assess any potential risks from acute exposure to manganese.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

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

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

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

- Response Values:

REL

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

- hour exposures.
AEGL

– Acute exposure guideline levels r epresent emergency exposure (1

- hour) limits for the general public.
AEGL

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

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

- lasting adverse health effec ts of an impaired ability to escape.
EPRG

– Emergency Removal Program guidelines represent emergency exposure (1

- hour) limits for the general public.
ERPG

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

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

To identify potential multipathway health risks from PB

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

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

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

PB

- HAP, and both of them had emission rates greater than the screening emission threshold
values for the pollutants indicating that there may be potential multipathway impacts of
concern due to emissions of these pollutants from these two 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 rates exceeded the threshold by 50 times. For mercury, exceeding the screening emission rate
relates to a potential for creating a chronic noncancer hazard q uotient in excess of 1. For POM, exceeding the screening emission rate relates to a potential for creating a cancer risk in

excess of 1 in a million.

For the two PB

- HAP that did not screen out during our initial multipathway screening analysis, we refi ned 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 around
the facilities

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

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

. One facility’s emission rates
exceeded the site

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

- specific screening thresh old for POM by 60 times, while the other facility’s emission rates exceeded the threshold by 5 times. We were unable to obtain the data necessary to conduct a fully refined assessment of multipathway risks from these two
facilities.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

31 I n evaluating the po tential 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 greate r 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 NAA QS, 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 manganese concentrations with those measured during a three to four month period in lat e 2009 at three monitors in close proximity (within 0.5 to 2.5 kilometers) to the Eramet ferroalloys facility. More specifically, we compared the mean manganese concentrations from the EPA’s Schools Monitoring Initiative to the predicted manganese concentrations at model receptor locations in close prox imity to these monitoring sites. The facility and monitors are shown in Figure 1. Results of this

an alysis are presented in Table 3.2

- 3 and indicate that at these three locations, annual average model predictions are generally within a factor of two (when looking at actual emissions) when compared to mean monitored concentrations for the sample period at these sites. These results indicate that AERMOD estimates of ambient air manganese concentrations provide a reasonable representation of the measured manganese concentrations present in the ambient air near this facility.

These results also show that the mean monitored manganese concentrations over the sampling period were observed to be above the RfC for manganese for all three sites. I t is important to note that the variability in the daily monitored values such that some samples were above the
RfC an d some were below. The daily values are highly variable and influenced by wind direction and speed. However, the RfC is protective of long

- term exposures and should be evaluated over a longer time period. More information about the EPA’s School Air Toxi cs Initiative and the monitoring conducted around the Eramet facility can be found at http://www.epa.gov/schoolair/pdfs/MariettaTechReport.pdf.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

32 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 ) 25 Mean Monitored

Manganese
Concentration (μg /m 3 ) 26 95% Confidence Interval

on the Mean (Monitored Manganese Concentrations) 25 Model to

Monitor
Ratio

N eale Elementary School (Vienna, WV) 0.07 0.07 .0 15

– 0. 13 1.00

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

- 0.19 0.11 0. 1 1

– 0. 2 1 1.00

- 1.73

Warren Elementary School (Marietta, OH) 0.07

- 0.29 0.146 0

– 0. 34 0.48

- 1.98

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

26 Mean monitor concentrations from the 3

- month sampling period and the 95 percent confidence intervals on the
mean can be found at: http://www.epa.gov/schoolair/pdfs/MariettaTechReport.pdf (Table 1). The recorded sample values from the monitors can be found in Table 2.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

33 

### 3.3 Post

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

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

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

.

We also note that post

- control, the maximum worst

- case acute refined HQ value would be reduced from a potential value of 10 to 0.3 (using the REL value for nickel compounds and
the ref inements 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 ra tes. Based on our intermediate screening approach for multipathway risks, emissions of mercury ―screen out‖, or are reduced below the screening thresholds for both facilities, indicating no potential for multipathway impacts of concern due to mercury.

Ho wever, e missions of POM ( as benzo(a)pyrene TEQ ) remain above the intermediate screening threshold s for both facilities (one by a factor of 20 and one by a factor of 2)

, indicating that we cannot rule out the potential for multipathway impacts of concern du e to emissions of POM from these facilities using our intermediate screening approach . 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 d ue 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 identify all the relevant facilities and emission points, as well as to develop accurate estimates of the annual emission rates for all relevant HAP, the uncertainties in our emission inventory likely dominate the unc ertainties in the exposure analysis . The chronic ambient modeling uncertainties are considered relatively small in comparison, since we are using EPA’s refined local dispersion model with site

- specific parameters and reasonably representative meteorology. If anything, the population exposure estimates are biased high by not accounting for short

- or long

- term population mobility, and by neglecting processes like deposition, plume depletion, and atmospheric degradation. Additionally, estimates of the maxim um individual risk (MIR) contain uncertainty , because they are deriv ed at census block centroid locations rather than actual residences. ThisDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

34 uncertainty is known to create potential underestimates and overestimates of the actual MIR
values for individual facilities, but, overall, it is not thought to have a significant impact on the estimated MIR for a source category. Finally, we did not factor in the possibility of a source closure occurring during the 70

- year chronic exposure period, leading to a pote ntial upward bias in both the MIR and population risk estimates; nor did we factor in the possibility of population growth during the 70

- year chronic exposure period, leading to a potential downward bias in both the MIR and population risk estimates.

A se nsitivity analysis performed for the 1999 NATA found that the selection of the meteorology dataset location could result in a range of chronic ambient concentrations which varied from as much as 17% below the predicted value to as much as 84% higher than t he predicted value. This variability translates directly to the predicted exposures and risks in our assessment, indicating that the actual risks could vary from 17% lower to 84% higher than the predicted values.

We have purposely biased the acute screen ing 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 scientific ally 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 thre sholds, we refined our assessment by developing a better understanding of the geography of the facility relative to potential exposure locations. In this case, refining the assessment for the

two 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 chro nic (lifetime) exposures. Noncancer 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) expo sure durations, all of which are derived based on an assumption of continuous exposure throughout the duration specified. For the purposes of assessing all potential health risks associated wit h
the emissions included in an assessment, we rely on both chr onic (cancer and noncancer) and acute (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 understatem ent of risk for these pollutants at environmental exposure levels is possible.

Additionally, chronic dose

- response values for certain compounds included in the assessment may be under EPA IRIS review and revised assessments may determine that these pollut antsDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

35 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 assessm ent

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 atten d 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 Carcinog en Risk Assessment [ 30 ] (herein
referred to as Cancer Guidelines ). ―The primary goal of EPA actions is protection of human health; accordingly, as an Agency policy, risk assessment procedures, including default options that are used in the absence of scien tific data to the contrary, should be health protective.‖ The approach adopted in this document is consistent with this approach as
described in the Cancer Guidelines

.

For cancer endpoints EPA usually derives an oral slope factor for ingestion and a unit risk value for inhalation exposures. These values allow estimation of a lifetime probability of developing cancer given long

- term exposures to the pollutant. Depending on the pollutant being evaluated, EPA relies on both animal bioassay and epidemiologi cal 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.

Extrapolatio n of study data to estimate potential risks to human populations is based upon EPA’s assessment of the scientific database for a pollutant using EPA’s guidance documents and other peer

- reviewed methodologies. The EPA Cancer Guidelines describes the Agency ’s recommendations for methodologies for cancer risk assessment. EPA believes that cancer risk estimates developed following the procedures described in the Cancer Guidelines and outlined below generally provide an upper bound estimate of risk. That is, EPA’s upper bound estimates represent a ―plausible upper limit to the true value of a quantity‖ (although this is usually not a true statistical confidence limit). 27 In some circumstances, the true risk could be as low as zero; however, in other circumsta nces the risk could also be greater. 28 When developing an upper bound estimate of risk and to provide risk values that do not underestimate risk, EPA generally relies on conservative default approaches. 29 EPA also

27 IRIS glossary (www.epa.gov/NCEA/iris/help_gloss.ht m).

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

29 According to the NRC report Science and Judgm ent 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 unc ertain.‖ 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‖ (NR C, 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 beDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

36 uses the upper bound (rather than lower bound or central) estimates in its assessments, although it is noted that this approach can have limitations for some uses (e.g. priority setting, expected benefits analysis).

Such health risk assessments have associated uncertainties, some which may be c onsidered quantitatively, and others which generally are expressed qualitatively. Uncertainties may vary substantially among cancer risk assessments associated with exposures to different pollutants, since the assessments employ different databases with d ifferent strengths and limitations and the procedures employed may differ in how well they represent actual biological processes for
the assessed substance. EPA’s Risk Characterization Handbook also recommends that risk characterizations present estimates demonstrating the impact on the assessment of alternative choices, data, models and assumptions [ 31 ]. Some of the major sources of uncertainty and variability in deriving cancer risk values are described more fully below.

(1) The qualitative similariti es or differences between tumor responses observed in experimental animal bioassays and those which would occur in humans is a source of uncertainty in cancer risk assessment. In general, EPA does not assume that tumor sites observed in an experimental an imal bioassay are necessarily predictive of the sites at which
tumors would occur in humans. 30 However, unless scientific support is available to show otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target organ concord ance. For a specific pollutant, qualitative differences in species responses can
lead to either under

- estimation or over

- estimation of human cancer risks.

(2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead
to d ifferences in risk predictions. For example, the measure of dose is commonly expressed in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, data may support development of a pharmacokinetic model for the absorption, distri bution, metabolism and excretion of an agent, which may result in improved dose metrics (e.g., average blood concentration of the pollutant or the quantity of agent metabolized in the body). Quantitative uncertainties result when the appropriate choice of a dose metric is uncertain or when dose metric estimates are themselves uncertain (e.g., as can occur when alternative pharmacokinetic models are available for a compound). Uncertainty in dose estimates may
lead to either over or underestimation of risk.

(3) For the quantitative extrapolation of cancer risk estimates from experimental animals to humans, EPA uses scaling methodologies (relating expected response to differences in physical size of the species), which introduce another source of uncertainty . These methodologies are based on both biological data on differences in rates of process according to species size and empirical comparisons of toxicity between experimental animals and humans. For a particular pollutant, the quantitative difference in cancer potency between

appropriate. In keeping with EPA’s goal of protecti ng 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 P ractices,
EPA/100/B

- 04/001 available at: http://www.epa.gov/osa/pdfs/ratf

- final.pdf.

30 Per the EPA Cancer Guidelines: ―The default option is that positive effects in animal cancer studies indicate that the agent under study can have carcinogenic potential in humans.‖ and ―Target organ concordance is not a prerequisite for evaluating the implications of animal study results for humans.‖Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

37 experimental animals and humans may be either greater than or less than that estimated by baseline scientific scaling predictions due to uncertainties associated with limitations in the
test data and the correctness of scaled estima tes.

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which there is a specified excess risk of cancer, which is used as the point of departure (or POD) for the remainder of the calculation. Statistical uncertainty in developing a POD using a benchmark dose (BMD) approach is generally addressed though use of the 95% lower confidence limit on the dose at which the specified exc ess risk occurs (the BMDL), decreasing the likelihood of understating risk. EPA has generally utilized the multistage model for estimation of the BMDL using cancer bioassay data (see further discussion below).

(5) Extrapolation from high to low doses is an important, and potentially large, source of uncertainty in cancer risk assessment. EPA uses different approaches to low dose risk assessment (i.e., developing estimates of risk for exposures to environmental doses of an agent from observations in exper imental or epidemiological studies at higher dose) depending on the available data and understanding of a pollutant’s mode of action (i.e., the manner in which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use
of reliabl e, compound

- specific, biologically

- based risk models when feasible; however, such models are rarely available. The mode of action for a pollutant (i.e., the manner in which a pollutant causes cancer) is a key consideration in determining how risks should be estimated
for low

- dose exposure. A reference value is calculated when the available mode of action data show the response to be nonlinear (e.g., as in a threshold response). A linear low

- dose (straight line from POD) approach is used when available mo de 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 consideration s. 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 baseli ne 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 nonlinear, non

- threshold relationships. The National Academy of Sciences has encouraged the exploration of sigmoidal type functions (e.g., log

- probit models) in representing dose response relationships due to the variability in response within human populations. Anothe r National Research Council (NRC) report [ 32 ] suggests that models based on distributions of individual thresholds are likely to lead to sigmoidal

- shaped
dose

- response functions for a population. This report notes sources of variability in theDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

38 human popula tion: ―One might expect these individual tolerances to vary extensively in humans depending on genetics, coincident exposures, nutritional status, and various other susceptibility factors...‖ Thus, if a distribution of thresholds approach is considered for a carcinogen risk assessment, application would depend on ability of modeling to reflect the degree of variability in response in human populations (as opposed to responses in bioassays with genetically more uniform rodents). Note also that low dose l inearity in risk can arise for reasons separate from population variability: due to the nature of a mode of action and additivity of a chemical’s effect on top of background chemical exposures and biological

processes.

As noted above, EPA’s current approa ch 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 estima tes can be quantified by comparing risk estimates using the BMDL value to central estimate BMD values, although these differences are generally not a large contributor to uncertainty in risk assessment (Subramaniam et. al., 2006) [ 33 ]. It is important to n ote that earlier EPA assessments, including the majority of those for which risk values exist today, were generally developed using the multistage model to extrapolate down to environmental
dose levels and did not involve the use of a POD. Subramaniam et. al. (2006) also provide comparisons indicating that slopes based on straight line extrapolation from a POD do not show large differences from those based on the upper confidence limit of the multistage
model.

(6) Cancer risk estimates do not generally ma ke specific adjustments to reflect the variability in response within the human population

— resulting in another source of uncertainty in assessments. In the diverse human population, some individuals are likely to be more
sensitive to the action of a ca rcinogen than the typical individual, although compound

- specific data to evaluate this variability are generally not available. There may also be important life stage differences in the quantitative potency of carcinogens and, with the exception of the

re commendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic mode of action, risk assessments do not generally quantitatively address life stage differences. However, one approach used commonly in EPA assessments that may help addr ess variability in response is to extrapolate human response from results observed in the most sensitive species and sex tested, resulting typically in the highest URE which can be supported by reliable data, thus supporting estimates that are designed not to underestimate risk in the face of uncertainty and variability.

Chronic noncancer assessment

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

- protective. That is, EPA and other organizations which dev elop noncancer reference values (e.g., the Agency for Toxic Substances and Disease Registry

– ATSDR) utilize an approach that is intended not to underestimate risk in the face of uncertainty and variability. When there are gaps in the available informatio n, uncertainty factors (UFs) are applied to derive reference values that are intended to be protective against appreciable risk ofDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

39 deleterious effects . Uncertainty factors are commonly default values 31 e.g., factors of 10 or 3, used in the absence of compound

- specific data; where data are available, uncertainty factors may also be developed using compound

- specific information. When data are limited, more assumptions are needed and more default factors are used. Thus there may be a greater tendency to overestimate risk

— in the sense that further study might support development of reference values that are higher (i.e., less potent) because fewer default assumptions are needed. However, for some pollutan ts it is possible that risks may be underestimated.

For non

- cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) for exposures via ingestion, and a Reference Concentration (RfC) for inhalation exposures.
These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or of a continuous inhalation exposure (RfC) to the human population (including sensitive subgroups) that is likely to be without an appreciable ris k of deleterious effects during a lifetime. 32 To derive values that are intended to be ―without appreciable risk,‖ EPA’s methodology relies upon an uncertainty factor (UF) approach [ 34 ], [ 35 ] which includes consideration of both uncertainty and variability.

EPA begins by evaluating all of the available peer

- reviewed literature to determine 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 usi ng the benchmark dose (BMD) approach; (2) use of the dose or concentration at which the toxic response was not significantly elevated (no
observed adverse effect level

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

A series of do wnward adjustments using default UFs is then applied to the POD to estimate
the reference value [ 36 ] . While collectively termed ―UFs‖, these factors account for a number of different quantitative considerations when utilizing observed animal (usually roden t) or human toxicity data in a risk assessment. The UFs are intended to account for: (1) variation in susceptibility among the members of the human population (i.e., inter

- individual variability); (2) uncertainty in extrapolating from experimental animal data to humans (i.e., interspecies differences); (3) uncertainty in extrapolating from data obtained in a study with

31 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) ―[Default] options are generic approach es, 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: M anaging 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 envir onment, 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 ava ilable at: http://www.epa.gov/osa/pdfs/ratf

- final.pdf.

32 See IRIS glossaryDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

40 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 sele cted for the individual UFs. For each type of uncertainty (when relevant to the assessment) , EPA typically applies an UF value of 10 or 3 with the cumulative UF value leading to a downward adjustment of 10

- 3000 fold from the
selected POD. An UF of 3 is us ed when the data do not support the use of a 10

- fold factor. If an extrapolation step or adjustment is not relevant to an assessment (e.g., if applying human toxicity data and an interspecies extrapolation is not required) the associated UF is not used. The major adjustment steps are described more fully below.

1) Heterogeneity among humans is a key source of variability as well as uncertainty. Uncertainty related to human variation is considered in extrapolating doses from a subset or
smaller

- sized po pulation, 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 uncerta inty associated with human variation. Human variation may be larger or smaller; however, data to examine the potential magnitude of human variability are often unavailable. In some situations, a smaller UF of 3 may be applied to reflect a known lack of s ignificant variability among humans.

2) Extrapolation from results of studies in experimental animals to humans is a necessary step for the majority of chemical risk assessments . When interpreting animal data, the concentration at the POD (e.g. NOAEL, B MDL) in an animal model (e.g. rodents) is extrapolated to estimate the human response. While there is long

- standing scientific support
for the use of animal studies as indicators of potential toxicity to humans , there are uncertainties in such extrapolati ons. 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 relat ive sensitivity in humans versus rodents are lacking, thus leading to uncertainty in this extrapolation. Size

- related differences (allometric relationships) indicate that typically humans are more sensitive than rodents when compared on a mg/kg/day basis. The default choice of 10 for the interspecies UF is consistent with these differences. For a 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 uncertainties; however, such dosimetric adjustments are not always possible. Information may not be available to quantitatively assess toxicokine tic 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 extrap olating from laboratory animals to humans in the derivation of a reference value. If information on one or the other of these components is available and accounted for in the cross

- species extrapolation, a UF of 3 may be used for the remaining component.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

41 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 1 0

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

4) Toxicity data are typically limited as to the dose or exposure levels that have been tested in individual studies; in an animal study, for exampl e, 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 possi ble. Use of a NOAEL is the next preferred approach after BMD analysis in determining a POD for deriving a health effect reference value. However, many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a
NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3

- fold is often applied.

5) The database UF is intended to account for the potential for deriving an underprotective RfD/RfC due to a data gap preventing complete characterization of the
che mical’s toxicity. In the absence of studies for a known or suspected endpoint of concern, a
UF of 10 or 3

- fold is typically applied.

There is no RfD or other comparable chronic health benchmark value for lead compounds. Thus, to address multipathway hum an health and environmental risks associated with emissions of lead from this facility, ambient lead concentrations were compared to the NAAQS for lead. In developing the NAAQS for lead, EPA considered human health evidence reporting adverse health effect s associated with lead exposure, as well as an EPA conducted multipathway risk assessment that applied models to estimate human exposures to
air

- related lead and the associated risk (73FR at 66979). EPA also explicitly considered the
uncertainties associat ed 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
uncertai nties between blood lead levels and loss of IQ points in children (73FR at 66981). In considering the evidence and risk analyses and their associated uncertainties, the EPA
Administrator noted his view that there is no evidence

- or risk

- based bright line that indicates a single appropriate level. Instead, he noted, there is a collection of scientific evidence and judgments and other information, including information about the uncertainties inherent in many relevant factors, which needs to be considered to gether in making this public health policy judgment and in selecting a standard level from a range of reasonable values (73FR at 66998). In so doing, the Administrator decided that, a level for the primary lead standard of 0.15 μg/m 3 , in combination with the specified choice of indicator, averaging time, and form, is requisite to protect public health, including the health of sensitive groups, with an adequate margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and

exposur e analyses, and their associated uncertainties can be found in EPA’s final rule revising the lead NAAQS (73 FR 66970

- 66981, November 12, 2008).

We also note the uncertainties associated with the health

- based (i.e., primary) NAAQS are likely less than th e uncertainties associated with dose

- response values developed for many ofDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

42 the other HAP, particularly those HAP for which no human health data exist. In 1988, EPA’s IRIS program reviewed the health effects data regarding lead and its inorganic compounds and determined that it would be inappropriate to develop an RfD for these compounds, saying, ―A great deal of information on the health effects of lead has been obtained through
decades of medical observation and scientific research. This information has been assessed in the development of air and water quality criteria by the Agency's Office of Health and Environmental Assessment (OHEA) in support of regulatory decision

- making by the Office of Air Quality Planning and Standards (OAQPS) and by the Office o f Drinking Water (ODW). By comparison to most other environmental toxicants, the degree of uncertainty about the health effects of lead is quite low. It appears that some of these effects, particularly changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral development, may occur at blood lead levels so low as to be essentially without a threshold. The Agency's RfD Work Group discussed inorganic lead (and lead compounds) at two meetings (07/08/1985 and 07/22/1985) and con sidered it inappropriate to develop an RfD for inorganic lead.‖ EPA’s IRIS assessment for Lead and compounds (inorganic) (CASRN 7439

- 92

- 1), http://www.epa.gov/iris/subst/0277.htm

.

We note further that because of the multi

- pathway, multi

- media impacts of lead, the risk assessment supporting the NAAQS considered direct inhalation exposures and indirect air

related multi

- pathway exposures from industrial sources like primary and secondary lead smelting op erations. It also considered background lead exposures from other sources (like contaminated drinking water and exposure to lead

- based paints). In revising the NAAQS for lead, we note that the Administrator placed more weight on the evidence

- based framew ork 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 revis ing 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).

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 theDraft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

43 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

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

44 

### 5 References

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

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

.

2 . US EPA, 2009. Risk and Technology Review (RTR) Risk Assessment Methodologies: For Review by the EPA’s Science Advisory Board with Case Studies

– MACT I Petroleum Refining Sources and Portland Cement Manufacturing

. EPA

- 452/R

- 09

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

3 . US EPA, 2010. SAB’s Response to EPA’s RTR Risk Assessment Methodologies. http://yosemite.epa.gov

/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/E

PA

- SAB

- 10

- 007

- unsigned.pdf

4 . US EPA, 2010. Memorandum from Dave Guinnup to RTR Wood Furniture Docket, entitled, ―EPA’s Actions in Response to Key Recommendations of the SAB Review of RTR Risk Assessment Methodologies.

5 . US EPA, 2005. Revision to the Guideline on Air Quality Models: Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final
Rule. 40 CFR Part 51. http://www.epa.gov/EPA

- AIR/2005/November/Day

- 09/a21627.htm

6 . US EPA, 2004. Users’ guide for the AMS/EPA regulatory model

– AERMOD. EPA

- 454/B

03

- 001

. http://www.epa.gov/scram001/7thconf/aermod/aermodugb.pdf

.

7

. Allen , D. , C

. Murphy, Y

. Kimura, W

. Vizuete, T

. Edgar

, H

. Jeffries, B

. - U

. Kim, M

. Webster

, and M

. Symons , 2004. Variable i ndustrial VOC emissions and their impact on ozone formation in the Houston Galveston Area. Final Report: Texas Environmental Research Consortium Project H

- 13.
ht tp://files.harc.edu/Projects/AirQuality/Projects/H013.2003/H13FinalReport.pdf

8 . US EPA, 2004. Air Toxics Risk Assessment Reference Library, Volume 1. EPA

- 453

- K

- 04

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

9

. US EPA, 2005. Table 1. Pr ioritized Chronic Dose

- Response Values (2/28/05). Office of Air Quality Planning and Standards. http://www.epa.gov/ttn/atw/toxsource/table1.pdf

10 . US EPA, 2005. 1999 National Air Toxics Ris k Assessment. http://www.epa.gov/ttn/atw/nata1999

11

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

.

12

. US Agency for Toxic Substances and Disease Registry. 2006. Minimum Risk Levels (MRLs)
for Hazardous Substances. http://www.atsdr.cdc.gov/mrls/index.html

.

13

. US EPA, 1994

. US Environmental Protection Agency. M ethods for Derivation of Inhalation Reference Concentrations and Application of Inhalation Dosimetry.
EPA/600/8

- 90/066F. Office of Research and Development. Washington, DC: U.S.EPA.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

45 14

. NRC, 1994. National Research Council. Science and Judgment in Risk Ass essment. Washington, DC: National Academy Press.

15

. CA Office of Environmental Health Hazard Assessment, 2005. Chronic Reference Exposure Levels Adopted by OEHHA as of December 2008. http://www.oehha.ca.gov/air/chronic_rels/AllChrels.html

.

16

. CA Office of Environmental Health Hazard Assessment, 2005. Technical Support Document for Describing Available Cancer Pot ency Factors, May 2005

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

.

17 . US EPA, 2006. Approach for modeling POM. Technical support information for the 1999
National Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata1999/99pdfs/pomapproachjan.pdf

.

18 . US EPA, 2005. Table 2. Acute Dose

- Response Values for Screening Risk Assessments (6/02/2005). Off

ice of Air Quality Planning and Standards. http://www.epa.gov/ttn/atw/toxsource/table2.pdf

19

. U.S. EPA , 2009 . Graphical Arrays of Chemical

- Specific Health Effect Reference Values for
Inhalati on Exposures [Final Report]. EPA/600/R

- 09/061, 2009. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm? deid=211003.

20 . CA Office of Environmental Health Hazard Assessment, 2000. All Acute Reference Exposure Levels developed by OEHHA as of May 2000. http://www.oehha.ca.gov/air/acute_rels/allAcRELs.html

21 . American Industrial Hygiene Association , 2009. Current AIHA ERPG Values. http://www.aiha.org/insideaiha/volunteergroups/Documents/ERP

- erpglevels.pdf

.

22 . US EPA, 1995. Guidance for Risk Characterization. Science Policy Council. http://www.epa.gov/OSA/spc/pdfs/rcguide.pdf

.

23 . US EPA, 2000. Risk Characterization Handbook. EPA 100

- B

- 00

- 002.

24 . US EPA, 2002. EPA’s Guidelines for Ensuring and Maximizing the Quality, Objectivity, Utility , and Integrity of Information Disseminated by the Environmental Protection Agency.
EPA Office of Environmental Information. EPA/260R

- 02

- 008

. http://w ww.epa.gov/quality/informationguidelines/documents/EPA_InfoQualityGuidelines.pdf

25

. US EPA, 2006. Performing risk assessments that include carcinogens described in the Supplemental Guidance as having a mutagenic mode of action. Science Policy Council Can cer Guidelines Implementation Workgroup Communication II: Memo from W.H. Farland dated
14 June 2006. http://www.epa.gov/osa/spc/pdfs/CGIWGCommunication_II.pdf

26

. US EPA, 2005. Supplemental guidance for assessing early

- life exposure to carcinogens.
EPA/630/R

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

.Draft Risk Assessment for the Ferroalloys Source Category

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

46 27

. US EPA, 2005. Science Policy Council Cancer Guidelines Implementation Workgroup Communication I: Memo from W.H. Farland dated 4 October 2005 to Science Policy
Council. http://www.epa.gov/osa/spc/pdfs/cangu id1.pdf

28

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

- 630

- R

- 98

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

29

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

- 630/R

- 00

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

.

30

. U S EPA, 2005. Guidelines for Carcinogen Risk Assessment (2005). U.S. Environmental Protection Agency, Washington, DC, EPA/630/P

- 03/001F, 2005. http://cfpub.epa.gov/ncea/raf/recordisp lay.cfm?deid=116283

31

. US EPA

. 2000

. Risk Characterization Handbook. EPA 100

- B

- 00

- 002.

32

. NRC (National Research Council) 2006. Assessing the Human Health Risks of Trichloroethylene. National Academies Press, Washington DC

.

33

. R.P. Subramaniam, P. White and V.J. Cogliano. 2006. Comparison of cancer slope factors using different statistical approaches, Risk Anal. Vol 26, p. 825

– 830.

34 . US EPA. 1993. Reference Dose (RfC): Description and Use in Health Risk Assessments. http://www.epa.gov/iris/rfd.htm

.

35 . US EPA. 1994. Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation Dosimetry. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=71993

.

36 . US EPA. 2002. A Review of the Reference Dose and Reference Concentration Processes. http://www.epa.gov/ncea/iris/RFC_FINAL1.pdf