Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

1 

## Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

by EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation May 201 5Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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

................................ 11 2.6 Dose

- response assessment

................................ ................................ ......................... 16 2.6.1 Sources of chronic dose

- response information

................................ .................. 16 2.6.2 Sources of acute dose

- response information

................................ ...................... 24 2 .7 Risk characterization

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

................................ ................................ ................................ ............... 28 2.7.2 Mixtures

................................ ................................ ................................ ............. 30 2.7.3 MACT

- Allowable Risks

................................ ................................ .................... 30 3 Risk results for the Ferroalloys source category

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

................................ ................................ .... 31 3.2 Baseline risk characterization

................................ ................................ .................... 34 3.3 Post

- control risk characterization

................................ ................................ .............. 42 4 General discussion of uncertainties and how they have been addressed

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

................................ ................................ .............. 43 4.2 Uncertaintie s in the dose

- response relationships

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

................................ ................................ ................................ ........................ 54

Index of Tables

Table 2.2

- 1 AERMOD version 13350 model options for R TR modeling

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

- 1 (A) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

.... 20 Table 2.6

- 1 (B) Dose

- Response Values for Chronic Oral Exposure to Carcinogens

............. 22 Table 2.6

- 2 (A) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

................................ ................................ ................................ ................................ .................. 23 Table 2.6

- 1 (B) Dose

- Response Values for Chronic Oral Exposure to Noncarcinogens

....... 24 Table 2.6

- 3 Dose

- Response Values for Acute Exposure

................................ ........................ 28 Table 3.1

- 1 Summary of Emissions from the Ferroalloys Source Category Used in the Residual Risk Assessment and Availability of Dose

- Response Values

................................ .. 32 Table 3.2

- 1 Summary of Source Category Level Inh alation Risks for Ferroalloys

................ 35 Table 3.2

- 2 Summary of Source Category Level Multipathway Screening Assessment Risk Results for Ferroalloys

................................ ................................ ................................ ............. 38 Table 3.2

- 3 Summary of Source Category Level Site

- Specific Multipathway Risk Results for Ferroalloys Baseline Scen ario

................................ ................................ ................................ .. 40 Table 3.2

- 4 Summary of Source Category Environmental Risk Screening Results for Ferroalloys

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

in Support of the 2015 Final Rule

3 Appendices

Appendix 1 Emissions Invento ry Support Memorand um Appendix 2 Technical Support Document for HEM 3 Modeling Appendix 3 Meteorological Data for HEM 3 Modeling Appendix 4 Technical Support Document for TRIM

- Based Multipathway Screening

Scenario for RTR: Summary of Approach and Evaluation Appendix 5 Analysis of short

- term emission rates relative to long

- term emission rates Appendix 6 Detailed Risk Modeling Results Appendix 7 Acute Impacts Refined Analysis Appendix 8 Dispersion Model Receptor Revisions and Additions for Ferroalloys Ap pendix 9 Protocol for Developing a TRIM.FaTE Model Scenario Appendix 10 Technical Support Document: Human Health Multipathway Residual Risk

Assessment for the Ferroalloys Production Source Category Appendix 11 Environmental Risk Screen

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model AEGL Acute exposure guideline level ASTDR US Agency for Toxic Substances and Disease Registry CalEPA California Environmental Agency ERPG Emergency Response Planning Guideline HAP Hazardous Ai r Pollutant
HEM Human Exposure Model
HI Hazard index HQ Hazard quotient IRIS Integrated Risk Information System MACT Maximum Achievable Control Technology
MIR Maximum Individual Risk MOA Mode of action NAC National Advisory Committee NAAQS National Ambient Air Quality Standards NATA National Air Toxics Assessment NEI National Emissions Inventory NPRM Notice of Proposed Rulemaking PAH Polynuclear Aromatic Hydrocarbon
PB

- HAP Persistent and Bioaccumulative

- HAP POM Polycyclic organic matter
REL Reference exposure level RfC Reference concentration RfD Reference dose
RTR Risk and Technology TOSHI Target

- organ

- specific hazard index URE Unit risk estimateResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

4 

### 1 Introduction

Section 112 of the Clean Air Act (CAA) establishes a two

- stage regulatory pro cess for addressing emissions of hazardous air pollutants (HAP) from stationary sources. In the first stage, section 112(d) requires the Environmental Protection Agency (EPA, or the Agency) to develop technology

- based standards for categories of sources ( e.g., petroleum refineries, pulp and paper mills, etc.) [ 1 ]. EPA has largely completed the initial Maximum Achievable Control Technology ( MACT ) standards as required under this provision. Under section 112(d)(6), EPA must review each of these technology

- based standards at least every eight years and revise a standard, as necessary, “taking into account developments in practices,

processe s and control technologies.” In the second stage, EPA is required under section 112(f)(2) to assess the health and envi ronmental 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 addres s these remaining risks. This second stage of the regulatory process is known as the residual risk stage. For each source category for which EPA issued MACT standards, the residual risk stage must be completed within eight years of promulgation of the in itial technology

- based standard.

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board (SAB) on the “Risk and Technology Review (RTR) Assessment Plan

, ” and in June of 2007, we received a letter with the results of that consul tation. Subsequent to the consultation, in June of 2009

, a meeting was held with an SAB panel for a formal peer review of the “Risk and Technology Review (RTR) Assessment Methodologies” [ 2 ]. We received the final SAB report on this review in May of 2010 [ 3 ]. Where appropriate, we have responded to the key messages from this review in developing our current risk assessment s and we will be continuing our efforts to improve our assessments by incorporating updates based on the SAB recommendations as they ar e 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 the Key Recommendations of S cience A dvisory B oard Review of R isk and T echnology
R eview R isk Assessment Met hodologies” [ 4 ].

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

- control scenario risk

assessment performed for the f erroalloys source catego ry. 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 he alth risks, chronic non

- inhalation health risks, and adverse environmental effects

.



### 2 Methods

2.1 Emissions and source data

Data from several CAA section 114 information collection request s (ICR) were used for this assessment. In 2010 a n d 2012 we sent ICR s to the two companies which own the two facilities in the U.S

. which we are aware are covered by the Ferroalloys Production MACTResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

5 standard . The ICR s requested available information regarding process equipment, control devices, point and fugitive emissions, pra ctices used to control fugitive emissions, and other aspects of facility operations, including stack parameters and locations. Additionally, we requested that the two facilities conduct emissions tests for certain HAP from specific processes that were con sidered representative of the industry. Pollutants tested included metal HAP (e.g., manganese, nickel compounds) hydrochloric acid (HCl)

, hydrogen fluoride (HF)

, 1 formaldehyde, mercury compounds , poly nuclear aromatic hydrocarbons (PAH)

, polychlorinated bi phenyls (PCB), and chlorodibenzo dioxins and chlorodibenzo furans (CDD/CDF)

. Also, additional test data were received during the comment period for the September 2014 supplemental proposal, and those data were incorporated into the emissions dataset. The r esults of th ese tests and data collection efforts are described in more detail in the memo Revised Development of the Risk and Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category for the 2015 Final Rule

, available in th e docket (EPA

- HQ

- OAR

- 2010

- 0895) and as Appendix 1 to this document . Section 3 below provides a summary of the emissions.



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

- and short

- term inhalation exposure concentrations and associate d health risk s from each facility in the source category were estimated using the Human Exposure Model (HEM) in combination with the American Meteorological Society/EPA Regulatory Model (AERMOD) dispersion modeling system ( HEM 3 ). The approach used in appl ying this modeling system is outlined below, and further details are provided in Appendix 2 of this document ( Technical Support Document for HEM3 Modeling )

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

The dispersion mo del in the HEM 3 system, AERMOD version 13350 , is a state

- of

- the

science Gaussian plume dispersion model that is preferred by EPA for modeling point, area, and volume sources of continuous air emissions from facility applications [ 5 ]. Further details on AE RMOD 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 fo r this simulation are generated by evenly dividing the total annual emission rate from the inventory into the 8,760 hours of the year.

1 As explained in the memo Revised Development of the Risk and Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category for the 2015 Final Rule , test data were received from 4 fur naces for HF. All test results were below the detection limit of the test method. While we initially calculated numerical estimates based on the assumption that non

- detects were equal to one

- half of the detection limit and included these estimates in the inputs to the risk assessment, we have no evidence that HF is emitted from these

sources.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

6 The first step in the application of the HEM 3 modeling system is to predict ambient concentrations at locations of inter est. The AERMOD model options employed are summarized in Table 2.2

- 1 and are discussed further below.

Table 2.2

- 1 AERMOD version 13350 mo del options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Poin t and area

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 Included if source in urbanized area

Meteorology 1 year representative NWS from nearest site ( over 800 stations )

In HEM 3 , meteorological dat a are ordinarily selected from a list of over 800 National Weather Service (NWS) surface observation stations across the continental United States, Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is selected as representative of the con ditions at the subject facility. Ideally, when considering off

- site meteorological data most site specific dispersion modeling efforts will employ up to five years of data to capture variability in weather patterns from year to year. However, because

we had an insufficient number of appropriately formatted model input files derived from available meteorological data, we modeled only a single year, typically 2011 . While the selection of a single year may result in under

- prediction of long

- term ambient lev els 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 distanc e between a modeled facility and the applicable meteorological station was approxima tely 3 0 miles ( 50 km). Ap pendix 3 of this document ( Meteorological Data Processing Using AERMET for HEM 3 ) provides a complete listing of stations and assumptions along wit h further details used in processing the data through AERMET (the AERMOD meteorological data pre

- processing program)

. The sensitivity of model results to the selection of the nearest weather station and the use of one year of meteorological data is discus sed in “ Risk and Technology Review (RTR) Risk Assessment Methodologies ” [ 2 ].

Beginning with version 12345, AERMET allows for a minimum wind speed of 0.5 m/s to be utilized when processing monitoring stations that are equipped with sonic anemometers and fo r an adjustment to the surface velocity (u*). The public version of AERMET available at the time we conducted the modeling for this source category did not include the surfaceResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

7 friction velocity adjustment. Also at that time, an updated version of AERMET (and AERMOD) was under development that incorporated further surface friction velocity adjustments to AERMET version 12345. In anticipation of the update, EPA processed meteorological data using a pre

- public release version of AERMET and incorporated the updated surface friction velocity adjustment in the output. It was EPA’ s judgment that the

pre

- public release version of AERMET would generate AERMOD

- ready meteorological data very close to that generated with the final public release version.

EPA has posted the AERMET meteorological data used in the ferroalloys analysis on the EPA’s FERA (Fate, Exposure, and Risk Analysis) website 2 under the HEM model page. AERMET and AERMOD (version 13350) were released to the public in late December 2013 on the EPA’ s Support Center for Regulatory Atmospheric Modeling (SCRAM) website. 3

The HEM 3 system estimates ambient concentrations at the geographic centroids of census blocks (using the 20 10 Census) and at other receptor locations that can be specified by the

user. See Appendix 8 to this document ( Dispersion Model Receptor Revisions and Addition s for the Ferroalloys Source Category ) for a discussion of user receptors and centroid location changes specific to this source category. The model accounts for the effects of multiple facilities when estimating concentration impacts at each block centroid. Typically we combined only the impacts of facilities within the same source category, and assessed chronic exposure and risk only for census blocks with at least one res ident (i.e., locations where people may reasonably be assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient concentrations were calculated as the annual average of all estimated short

- term (one

- hour) concentrations at each block centroid. Possible future residential use of currently uninhabited areas was not considered. Census blocks, the finest resolution available in the census data, are typically comprised of approximately 5 0 people or about 20 households.

In contrast to the development of ambient concentrations for evaluating long

- term exposures, which was performed only for occupied census blocks, worst

- case short

- term (one

- hour) concentrations were estimated both at the census block centroids and at point s nearer the facility that represent locations where people may be present for short periods, but generally no nearer than 100 meters from the center of the facility (note that for large facilities, this 100

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

- term emission rates were needed to screen for the potential for hazard via acute exposures, and since the ICR data contain s only annual emission totals, we generally apply the assumption to all source categories that th e maximum one

- hour emission rate from any source is ten times the average annual hourly emission rate for that source. More description of our short

- term assessment can be found in Section 2.4 of this document

- Acute Risk Screening and Refined Assessment

s

.

Census block elevations for HEM 3 modeling were determined nationally from the US Geological Service 1/3 Arc Second National Elevation Dataset, which have a spatial

2 The FERA webpage is http://www2.epa.gov/fera and the HEM3 webpage is http://www2.epa.gov/fera /risk

assessment

- and

- modeling

- human

- exposure

- model

- hem

3 The SCRAM webpage is http://www.epa.gov/ttn/scram/

.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

8 resolution of about 1 0 meters. Elevations of polar grid points used in estimating sh ort

- and long

- term ambient concentrations were assumed to be equal to the highest elevation of any census block falling within the polar grid sector corresponding to the grid point. If a sector does not contain any blocks, the model defaults the elevation to that of the nearest block. If an elevation is not provided for the emission source, the model uses the average elevation of all sectors within the innermost model ring. AERMOD adjusts the plume’s flow if nearby elevated hills are expected to influenc e the wind patterns. For details on how hill heights were estimated and used in the AERMOD modeling, see Appendix 2 of this document, Technical Support Document for HEM3 Modeling

.



### 2.3 Estimating chronic human inhalation exposure

We used the estimated a nnual average ambient air concentration of each HAP at each census block centroid as a surrogate for the lifetime inhalation exposure concentration of all the people who reside in the census block. That is, the risk analysis did not consider either the sh ort

- term or long

- term behavior (mobility) of the exposed populations and its potential influence on their exposure.

We did not address short

- term human activity for two reasons. First, our experience with the NATA assessments (which modeled daily activ ity using EPA’s HAPEM model) suggests that, given our current understanding of microenvironment concentrations and daily activities, modeling short

- term activity would, on average, reduce risk estimates about 25 percent for particulate HAP; it will also re duce 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 re ducing exposure estimates for the most highly exposed residents by modeling their short

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

We did not address long

- term migration nor population growth or decrease over 70 years, instead basing the assessment on the assumption that each person’s predicted exposure is constant over the course of their lifetime which is assumed to be 70 years. In assessing cancer risk, we generally estimated three metrics; the maximum individual risk (MIR), which is defined as the risk associated with a lifetime of exposure at the highest concentration; the population risk distribution; and the cancer incidence. The assumption of not considering short or long

- term population mobility does not bias the estimate of the theoretical MIR nor does it affect the estimate of cancer incidence since the total population number remains the same. It does, however, affect the shape of the distribution of individual risks across the affected population, shifting it toward highe r estimated individual risks at the upper end and reducing the number of people estimated to be at lower risks, thereby increasing the estimated number of people at specific risk levels.



### 2.4 Acute Risk Screening and Refined Assessments In establishing a s cientifically 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 under the residual risk program. That is, weResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

9 developed a tiered, iterative approach. This approach to risk assessment was endorsed by the National Academy of Sciences in its 1993 publication “Science and Judgment in Risk Assessment” and subsequently was adopted in the EPA’s “Residual Risk Report to Congress” in 1999.

The assessment methodology is designed to eliminate from further consideration those facilities for which we have confidence that no acute adverse health effects of concern will occur. To do so, we use what is called a tiered, it erative 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 exposure . The result of this screening process is that either the facility being assessed poses no potential acute health risks (i.e., it “screens out”), or that it requires further , more refined assessment. A more refined acute assessment could u s e industry

- or site

- specific data on the temporal pat tern of emissions, the layout of emission points at the facility, the boundaries of the facility, and /or the local meteorology. In some cases, all of these site

- specific data are used to refine the assessment; in others, lesser amount s of site

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

Acute health risk screening was performed for each facility as the first step. When we identify acute impacts which exceed their relevant benchmarks, we pursue refining our acute screening estimates to the extent possible. In some cases, this may include the use of a facility

- specific emissions multiplier to estimate the peak hourly emission rates from the average rates (rath er than the default factor of 10). In other cases, this may entail determining the actual physical layout and boundaries of a facility to more accurately gauge where people might reasonably be exposed for an hour.

W hen screening for potentially significa nt acute exposures, we used an estimate of the highest hourly ambient concentration at any off

- site location as the surrogate for the maximum potential acute exposure concentration for any individual. These hourly concentrations are based on hourly emissi ons, as described above. Since information is not usually available on short

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

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

sourc e. ( The average hourly emissions rate is defined as the total emissions for a year divided by the total number of operating hours in the year. ) This choice of a factor of ten for acute screening was originally based on engineering judgment

.
To develop a more robust peak

- to

- mean emissions factor, and in response to one of the key messages from the SAB consultation on our RTR Assessment Plan, we performed an analysis using a short

- term emissions data set from a number of source s located in Texas (original ly reported on by Allen et al

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

- industrialized 4

- county area (Harris, Ga lveston, Chambers, and Brazoria Counties ) over an eleven

- month time period in 2001 . We obtained the dataset and performed our own analysis, focusing on sources which reported emitting high quantities of HAP over short periods of time (see Appendix 5 of th is document, Analysis ofResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

10 data on short

- term emission rates relative to long

- term emission rates ). Most peak emission events were less than twice the annual average, and the highest was a factor of 74 times the annual average , and the 99 th percentile ratio of peak hourly emission rate to the annual hourly emission rate was 9. Based on these results, we generally chose the factor of ten for all initial screening. Th is factor is intended to cover all possible hourly peaks associated with routinely

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

- term peak gaseous or volatile HAP emissions from typical industrial sources. We have no data relating specifically to peak short

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

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

For the ferroalloys source category, however, maximum hourly emissions estimates were available, so we did not use the default emissions multiplier of 10. See Appendix 1 to this document, Revised Development of the Risk and Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category for the 2015 Final Rule , which is also available separately in the docket, for the detailed description of how the maximum hourly emissions were developed for the ferroalloys source category

. In general, some processes operate continuously so there are no peak emissions and these processes received a factor of 1 (i.e., maximum hourly emissions equal annual average hourly emissions). Other processes, for example tapping and casting, have spe cific cycles, with peak emissions occurring for a part of that cycle (e.g., 30 minutes during a 2

- hour period). For these processes, we used a factor of 4 in the acute assessment.

As mentioned above, when we identify acute impacts which exceed their re levant benchmarks, we pursue refining our acute screening estimates to the extent possible. For the ferroalloys production source category, we conducted a review of the layout of the polar receptors around the facilities compared to the facility boundarie s to determine the maximum off

- site acute impact for the facilities that did not screen out during the initial run. Appendix 6 to this document ( Detailed Risk Modeling Results ) contains the initial acute results for the source category, while Append ix 7 to this document ( Acute Impacts Refined Analysis ), contains the refined acute results.

In summary, we used conservative assumptions for emission rates, meteorology, and exposure location , and refined data where available

. We used the following a ssumptions in our acute
assessment approach:

 Peak 1

- hour emissions were obtained from the emissions memo and based on the operating characteristics of ferroalloys production emission sources as described in Appendix 1.

 For facilities with multiple emissio n points, peak 1

- hour emissions were assumed to occur at all emission points at the same time.

 We assumed that the peak emissions occur at all emission points at the same time.

 For facilities with multiple emission points, 1

- hour concentrations at each rec eptor were assumed to be the sum of the maximum concentrations due to each emissionResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

11 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

a t 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 wor st

- case 1

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

meters.

 The maximum impact was compared to multiple short

- term health benchmarks for the HAP being assessed to determine if a possible acute health risk might exist. These benchmarks are describe d in section 2.6 of this report.



### 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) 4 . The PB

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

- HAP are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury compounds, methoxychlor, polychlorinated biphenyls (PCB) , polycyclic organi c matter (POM) , toxaphene, and triflurali n. Emissions of cadmium compounds, chlorinated dibenzodioxins and furans, lead compounds , mercury compounds

, PCBs, and POM (of which PAH are a subset) were identified in the emissions inventory for the ferroalloys source category.

With respect to PB

- HAP emissions other than lead, e missions were evaluated for potential

non

- inhalation risks using a tiered s creening approach which was developed for use with the EPA’s peer

- reviewed Total Risk Integrated Methodology

– Fate, Transport, and Ecological Exposure ( TRIM.FaTE 5 ) model. With this approach, w e first determine whether the facility

specific emission rates of each of the emitted PB

- HAP are large enough to create the potential for significant non

- inhalation human h ealth risks under reasonable worst

- case conditions. T o facilitate this step, we developed emission rate screening levels for each PB

- HAP using a hypothetical upper

- end screening exposure scenario developed for use in conjunction with TRIM.FaTE. The expos ure scenario includes a generic farming/fishing exposure scenario that simulates a subsistence environment. We conducted a sensitivity analysis on the screening scenario to ensure that its key design parameters would represent the upper end of the range o f possible values, such that it would represent a conservative but not impossible scenario. The PB

- HAP emissions from each facility in the source category were compared to

4 Although the two

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

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

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

5 EPA’s Tot al Risk Integrated Methodology (General Information) http://www2.epa.gov/fera/total

- risk

integrated

- methodology

- trim

- generalResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

12 the emission rate screening levels for each of the PB

- HAP identified to assess the potential for significant human health risks via non

- inhalation pathways. For the purpose of developing emission rates for the multipathway screen, we derived emission levels for each PB

- HAP (other than lead) at which the maximum human health risk would b e 1 in a million for lifetime cancer risk or a hazard quotient of 1.0 for noncancer impacts. We call this application of the TRIM.FaTE model the Tier I Screen. Se e Appendix 4 of this document ( Technical Support Document for TRIM

- Based Multipathway Screen ing Scenario for RTR: Summary of Approach and Evaluation ) for a complete discussion of the development and testing of the screening scenario, as well as for the values of facility

- level emission rates developed for screening potentially significant multip athway impacts.

If the PB

- HAP emissions for a facility exceed the Tier I screening emission rate, we conduct a Tier II multipathway screen. In the Tier II screen, the location of each facility that exceeded the Tier I emission rate is used to refine so me of the assumptions associated with the environmental scenario while maintaining the exposure scenario assumptions. We th en adjust the risk

- based Tier I screening level for each PB

- HAP for each facility based on an understanding of how exposure concentr ations estimated for the screening scenario change with meteorology and environmental assumptions. The screening scenarios developed include 2 separate receptors; 1) subsistence fisher and 2) subsistence farmer. This step creates a facility

- specific emis sion rate for each PB

- HAP (i.e., the threshold for cadmium could be different for every facility), for each scenario unlike the Tier 1 emission rate threshold which was constant for the same PB

- HAP at different facilities (i.e., the threshold for cadmium w as the same for every facility).

The subsistence fisher scenario assumes a high

- end fish consumption rate of 373 grams/day. 6 Also, the assessment uses the assumption that the biological productivity limitation of each lake is 1 gram of fish per acre o f water Thus, in order to fulfill the adult ingestion rate, we may need to model more than one lake . R efer to Appendix 4 of this document ( Technical Support Document for TRIM

- Based Multipathway Screening Scenario for RTR: Summary of Approach and Evaluati on ) for a complete discussion of the bioassay studies used to support this assumption.

If we need to include more than one lake to achieve the 373 g/day ingestion rate, we begin with the lake with highest chemical concentration of a given PB

- HAP group, and “fish” up to the lake’s biological productivity. We then systematically proceed to other lakes based on concentration, until the 373 g/day limit is met. A maximum travel radius of 50 km relative to the facility is used to maintain a realistic scenari o. The final Tier 2 screening result for the fisher can be expressed as the sum of the risk from each lake that is fished (which is based on the amount of fish ingested for each lake multiplied by the fish concentration). If the highest

concentration lake is at least 373 acres, the ingestion rate is not altered (i.e., remains 373 g/d for adults). If the cumulative size of multiple visited lakes exceeds 373 acres, the model includes from the final lake only the amount of fish necessary to satisfy the ingest ion rate (i.e., to reach the 373 g/d). If there are not 373 acres of lake, the risk reflects a reduced ingestion rate based on the lake acreage. The farmer scenario (same approach for all Tiers) involves an

6 Burger, J. 2002. Daily consumption of wild fish and game: Exposures of high end recreationalists. Environmental Health Research. 12(4):343

– 354Residual Risk Assessment for the Ferroalloys Source Category

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13 individual living for a 70

- year lifetime on a fa rm homestead in the vicinity of the source and consuming produce grown on, and meat and animal products raised on, the farm. The ingestion rate used for these food groups are set at the 90 th percentile of EPA’s “Exposure Factors Handbook: 2011 Edition”, and is considered an upper

- bound level. 7

Facility emissions of PB

- HAP that do not exceed these new Tier II screening levels are considered to pose no significant risks. When facilities exceed the Tier II screening levels, it does not mean that multipath way impacts are significant, only that we cannot rule out that possibility based on the results of the screen. Se e Appendix 4 of this document ( Technical Support Document for TRIM

- Based Multipathway Screen ing Scenario for RTR: Summary of Approach and Eva luation ) for a complete discussion of the Tier II screen.

If the PB

- HAP emissions for a facility exceed the Tier II screening emissions rate, and data are available, we may decide to conduct a more refined multipathway assessment. A refined

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

. The refined assessment also uses the TRIM.FaTE model and facility

- specific emission

rate levels that are created for each PB

- HAP. There are many variables to consider i n a refined multipathway assessment and we have developed a protocol to maintain consistency across source categories. This protocol can be found in Appendix 9 of this document ( Protocol for Developing a TRIM.FaTE Model Scenario to Support a Site

- Specific Risk Assessment in the RTR Program ). For the ferroalloys production source category, we did conduct a refined multipathway assessment for one facility in the category. A detailed discussion of the approach for this assessment can be found in Appendix 10 of this document ( Technical Support Document: Human Health Multipathway Residual Risk Assessment for the Ferroalloys Production Source Category ).

In evaluating the potential multipathway risks from emissions of lead compounds, rather than developing a screening emission rate for them , we compared maximum estimated chronic atmospheric concentrations with the current National Ambient Air Quality Standard (NAAQS) for lead. Values below the NAAQS were considered to have a low potential for multipathway ri sks.

The NAAQS value, a public health policy judgment, incorporated the Agency’s most recent health evaluation of air effects of lead exposure for the purposes of setting a national ambient air quality standard. In setting this value, the Administrator promulgated a standard that was requisite to protect public health with an adequate margin of safety. We consider values below the level of the primary NAAQS to protect against multipathway risks because as mentioned above, the primary NAAQS is set as to protect public health with an adequate margin of safety. However, ambient air lead concentrations above the NAAQS are considered to pose the potential for increased risk to public health. We consider this NAAQS assessment to be a refined analysis given: 1) the numerous health studies, detailed risk and exposure analyses, and level of external peer and public review that went into the development of the primary NAAQS for lead, combined with: 2) the site

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

7 US EPA, September 2011. Exposure Factors Handbook: 2011 Edition; http://www.epa.gov/ncea/efh/pdfs/efh

- complete.pdfResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

14 emissions. It should be noted, however, that this comparison does not account for possible population exposures to lead from sources other than the one being modeled; for example, via consumption of water from untreated local sources or ingestion of locally grown food. Nevertheless, the Administrator judged that such a standard would protect, with an adequate margin of safety, the health of children and other at

- risk populations against an array of adverse health effects, most notably including neurological effects, particularly neurobehavioral and neurocognitive effects, in children (73 FR 67007). The Administrator, in setting the standard, also recognized that no evidence

- or risk based bright l ine indicated a single appropriate level. Instead a collection of scientific evidence and other information was used to select the standard from a range of reasonable values (73 FR 67006).

We further note that comparing ambient lead concentrations to the NAAQS for lead, considering the level, averaging time, form and indicator, also informs whether there is the potential for adverse environmental effects. This is because the secondary lead NAAQS, set to protect against adverse welfare effects (including adverse environmental effects), has the same averaging time, form, and level as the primary standard. Thus, ambient lead concentrations above the NAAQS for lead also indicate the potential for adverse environmental effects.

The EPA has developed a screen ing approach to examine the potential for adverse environmental effects as required under section 112(f)(2)(A) of the CAA. The environmental screen focuses on the following seven environmental HAP:

 Five persistent bioaccumulative HAP (PB

- HAP)

– cadmium, dioxins/furans, POM, mercury (both inorganic mercury and methyl mercury), and lead,

 Two acid gases

– hydrogen chloride (HCl) and hydrogen fluoride (HF).

HAP that persist and bioaccumulate are of particular environmental concern because they accumulate in the soil, sediment, and water. The acid gases

– HCl and HF

– were included due to their well

- documented potential to cause direct damage to terrestrial plants. See A ppendix 11 of this document, Environmental Risk Screen

, for the PB

- HAP and acid gas bench marks included in the environmental risk screen.

For the environmental risk screening analysis, EPA first determined whether any facilities in the source category emitted any of the seven environmental HAP. If one or more of the seven environmental HAP e valuated are emitted by at least one facility in the source category we proceed to the second step of the evaluation.

For cadmium, mercury, POM, and dioxins/furans, the environmental screening analysis consists of two tiers. In the first tier, TRIM.FaTE modeling was conducted under worst

- case environmental conditions to determine whether the facility

- specific off

- site emission rates of each of the emitted environmental HAP exceeded ecological benchmarks represented as emissions screening levels . If off

- s ite emissions from a facility do not exceed the Tier I screening levels the facility “passes” the screen, and therefore, is not evaluated further under the screening approach. If off

- site emissions from a facility exceed the Tier I screening levels , we ev aluate the facility further in Tier II

.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

15 In Tier II of the environmental screening analysis, the screening emission levels are adjusted to account for local meteorology and the actual location of lakes in the vicinity of facilities that did not pass the Ti er I screen. If off

- site emissions from a facility do not exceed the Tier
II screening levels , the facility passes the screen, and is typically not evaluated further. If off

site emissions from a facility exceed the Tier II screening levels , the facility does not pass the screen, and, therefore, may have the potential to cause adverse environmental effects. Such facilities are evaluated further to investigate factors such as the magnitude and characteristics of the area of exceedance.

For acid gases, th e environmental screening analysis evaluates the potential phytotoxicity and reduced productivity of plants due to chronic exposure to acid gases. The environmental risk screening methodology for acid gases is a single

- tier screen that compares the averag e off

- site ambient air concentration over the modeling domain to ecological benchmarks for each of the acid gases. For purposes of ecological risk screening, EPA identifies a potential for adverse environmental effects to plant communities from exposure t o acid gases when the average concentration of the HAP around a facility exceeds the LOAEL ecological benchmark. In such cases, we further investigate factors such as the magnitude and characteristics of the area of exceedance (e.g., land use of exceedanc e area, size of exceedance area) to determine if there is an adverse environmental effect.

For lead compounds, we currently do not have the ability to calculate media concentrations using the TRIM.FaTE model. However, air concentrations of lead are alrea dy calculated as part of the human health exposure and risk analysis using the HEM3

- AERMOD air dispersion model. To evaluate the potential for adverse environmental effects from lead, we compare the average modeled air emission concentrations of lead from each facility in the source category emissions to the level of the secondary National Ambient Air Quality Standard (NAAQS) for lead. The secondary lead NAAQS is a reasonable means of evaluating environmental risk because it is set to provide substantial protection against adverse welfare effects which can include “effects on soils, water, crops, vegetation, man

- made materials, animals, wildlife, weather, visibility and climate, damage to and deterioration of property, and hazards to transportation, as wel l as effects on economic values and on personal comfort and well

being.” 8

8 A secondary standard, as defined in Section 109(b)(2), must “specify a level of air quality t he attainment and maintenance of which, in the judgment of the Administrator, based on criteria, is requisite to protect the public welfare from any known or anticipated adverse effects associated with the presence of [the] pollutant in the ambient air.” Welfare effects as defined in section 302(h) (42 U.S.C. 7602(h)) include, but are not limited to, “effects on soils, water, crops, vegetation, man

- made materials, animals, wildlife, weather, visibility and climate, damage to and deterioration of property, and hazards to transportation, as well as effects on economic values and on personal comfort and well

- being.”Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

16 

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

- response information. The recommendations are based on the following sources, in order of priority :

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

- response assessments for chronic exposure f or many of the pollutants in this study. These assessments typically provide a qualitative statement regarding the strength of scientific data and specify a reference concentration (RfC, for inhalation) or reference dose (RfD, for ingestion) to protect ag ainst effects other than cancer and/or a unit risk estimate (URE, for inhalation) or slope factor (SF, for ingestion) to estimate the probability of developing

cancer. The RfC is defined as an “ estimate (with uncertainty spanning perhaps an order of magni tude) 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 ord er 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 estimat ed 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 percent confidence limit, on the increased cancer risk from a lifetime exposure to an agent. This estimate, [is ] usually expressed in units of proportion (of a population) affected per mg/kg

- day ...” EPA disseminates dose

response assessment information in several forms, based on the level of review. The Integrated Risk Information System (IRIS) [ 11 ] is an EPA databa se that contains scientific health assessment information, including dose

- response information. All IRIS assessments since 1996 have also undergone independent external peer review. The current IRIS process includes review by EPA scientists, interagency r eviewers from other federal agencies, and the public, and peer review by independent scientists external to EPA. New IRIS values are developed and old IRIS values are updated as new health effects data become available. Refer to the “IRIS Track” website 9 for detailed information on status and scheduling of current individual IRIS assessments and updates. EPA’s science policy approach , under the current carcinogen guidelines, is to use linear low

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

- response assessments to identify nonlinear MOAs where appropriate, and we will use those analyses (once they are peer reviewed) in our

9 http://cfpub.epa.gov/ncea/iristrac/Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

17 risk assessments. At this time, howev er, there are no available carcinogen dose

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

.

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

- neoplastic endpoints .” The MRL is defined as “an estimate of daily human e xposure 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 environmen tal contaminants for further evaluation. Exposures above an MRL do not necessarily represent a threat, and MRLs are therefore not intended for use as predictors of adverse health effects or for setting cleanup levels.

3) California Environmental Protection Agency (CalEPA). The CalEPA Office of Environmental Health Hazard Assessment has developed dose

- response assessments for many substances, based both on carcinogenicity and health effects other than cancer. The process for developing these assessments is similar to that used by EPA to develop IRIS values and incorporates significant external scientific peer review. As cited in the CalEPA Technical Support Document for developing their chronic assessments 10 : “The guidelines for developing chronic inhalation exposure levels incorporate many recommendations of the U.S. EPA [ 13 ] and NAS [ 14 ].” The non

- cancer information includes available inhalation health risk guidance values expressed as chronic inhalation reference exposure levels (RELs) [ 15 ]. CalEPA defines the REL as “the concentration level at or below which no health effects are anticipated in the general human population.” CalEPA's quantitative dose

- response information on carcinogenicity by inhalation exposure is expressed in terms of the URE [ 16 ], defin ed similarly to EPA's URE.

In developing chronic risk estimates, we adjusted dose

- response values for some HAP based on professional judgment, as follows:

1) Consistent with Agency policy (a s mentioned above )

, which was supported by the SAB, 11
the EPA ha s chosen in this instance to rely on the ATSDR MRL for manganese in the current ferroalloys supplemental proposal. There is an existing IRIS RfC for manganese

10 Air Toxics Hot Spots Program, Risk Assessment Gu idelines, Part III

- Technical Support Document for the Determination of Non

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

11 The SAB peer review of RTR Risk Assessment Methodologies is available at: http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/EPA

- SAB

- 10

- 007

- unsigned.pdfResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

18 (Mn) published in 1993 12 . This value was in the RTR risk assessment supporting the 2011 Ferroall oys Notice of Proposed Rulemaking

. However, since the 2011 proposal ATSDR has published an assessment of manganese toxicity (2012) which includes a chronic inhalation reference value (i.e., an ATSDR Minimal Risk Level or MRL ) 13

. Both the 1993 IRIS Rf

C and the 2012 ATSDR MRL were based on the same study (Roels et al., 1993). In developing th e i r assessment
, ATSDR us ed updated dose

- response modeling methodology ( benchmark dose approach ) and considered recent pharmacokinetic findings to support their MRL deri vation. Consistent with Agency policy, which was supported by SAB, the EPA has chosen to rely on the ATSDR MRL for manganese in the current ferroalloys final rule

.

2) In the case of nickel compounds, to provide a conservative estimate of potential cance r risks, we used t he IRIS URE value for nickel subsulfide (which is considered the most potent carcinogen among all nickel compounds) in th e assessment for the 2011 proposed rule for ferroalloys production

. In the 2011 proposal rule, the determination of the percent of nickel subsulfide was considered a major factor for estimating the risks of cancer due to nickel

- containing emissions. Nickel speciation information for some of the largest 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 cancer risk for the mixture of inhaled nickel compounds (based on nickel subsulfide, and representative of pure insoluble crystalline nickel) wa s derived to reflect the assumption that 65 percent of the total mass of nickel may be carcinogenic.

Based on consistent views of major scientific bodies (i.e., National Toxicology Program ( NTP ) in their 12 th Report of the Carcinogens ( ROC ) 14 , I nternatio nal Agency for Research on Cancer (I ARC ) 15 , and other international agencies) 16 that consider all nickel compounds to be carcinogenic, we currently consider all nickel compounds to have the potential of being carcinogenic to humans

. The 12th Report of the C arcinogens states that the “combined results of epidemiological studies, mechanistic studies, and carcinogenic studies in rodents support the concept that nickel compounds generate nickel ions in target cells at sites critical for carcinogenesis, thus allo wing consideration and evaluation of these compounds as a single group.” Although the precise nickel compound (or compounds) responsible for carcinogenic effects in humans is not always clear, studies indicate that nickel sulfate and the combinations of n ickel sulfides and oxides encountered

12 USEPA Integrated Risk Information System Review of Manganese (1993) available at http://www.epa.gov/iris/subst/0373.htm

13 Agency for Toxic Substances & Disease Registry Toxicological Profile for Manganese (2012) available at http://www.atsdr.cdc.gov/toxprofiles/tp.asp?id=102&tid=23

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

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

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

.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

19 in the nickel refining industries cause cancer in humans (these studies are summarized in a review by Grimsrud et al., 2010 17 ). The major scientific bodies mentioned above have also recognized that there are difference s in toxicity and/or carcinogenic potential across the different nickel compounds.

In th e inhalation risk assessment for the 2011 proposal

, to take a conservative approach, we considered all nickel compounds to have the same carcinogenic potential as ni ckel subsulfide and used the IRIS URE for nickel subsulfide to estimate risks due to all nickel emissions from the source category

. However, given that there are two additional URE values 18 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 potenc y values for different mixtures of nickel compounds. In the public comments provided in response to the proposal and available in the docket , one facility provided additional data in the form of a laboratory test report that indicated it would be unlikely that 100 percent of the nickel from the furnace would be in the form of nickel subsulfide. Therefore, g iven our current knowledge of the carcinogenic potential of all nickel compounds, and the potential differences in carcinogenic potential across nickel compounds, we consider ed it reasonable to use a value that is 50 percent of the IRIS URE for nickel subsulfide for providing an estimate of the cancer potency for different mixtures of nickel compounds in the revised dataset for the 2014 supplemental prop os al

. We also consider it reasonable for the 2015 final rule.

3) Where possible for emissions of unspecified mixtures of HAP categories such as metal compounds and POM, we apply category

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

- response value for the category.

4) Where POM emissions were not speciated into individual compounds, we applied the same sim plifying a ssumptions to assessments that are used in NATA [ 17 ]. The NATA approach partitions POM int o eight different non

- overlapping “groups” that are modeled as separate pollutants. Each POM group comprises POM species of similar carcinogenic potency, for which we can apply the same URE.

5) In 2004, the EPA determined that the Chemical Industry Institut e of Toxicology (CIIT)

cancer dose

- response value for formaldehyde (5.5 x 10

- 9 per μg/m 3 ) was based on better science than the IRIS 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 su ggested that the CIIT model was not

17 Grimsrud TK and Andersen A. Evidence of carcinogenicity in humans of water

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

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

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

18 Two UREs (other than the current IRIS values) have been derived for nickel compounds as a group : one developed by the California Department of Health Services ( http://www.arb.ca.gov/toxics/id/summary/nickel_tech_b.pdf ) and the other by the Texas Commission on Environmental Quality ( http: //www.epa.gov/ttn/atw/nata1999/99pdfs/healtheffectsinfo.pdf ).Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

20 appropriate and

, in 2010 EPA returned to using the 1991 IRIS value. The EPA has been working on revising the formaldehyde IRIS assessment and the National Academy of Sciences (NAS) completed its review of the EPA’s draf t assessment in April of 2011

. 19
The EPA will follow the NAS Report recommendations and will present results obtained by implementing the biologically

- based dose

- response ( BBDR ) model for formaldehyde. The EPA will compare these estimates with those curr ently presented in the External Review draft of the assessment and will discuss their strengths and weaknesses. As recommended by the NAS committee, appropriate sensitivity and uncertainty analyses will be an integral component of implementing the BBDR mo del. The draft IRIS assessment will be revised in response to the NAS peer review and public comments and the final assessment will be posted on the IRIS database. In the interim, we will present findings using the 1991 IRIS value as a primary estimate ; EPA may also consider other information as the science evolves.

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

- response values. Of these, 3 8 are classified as kn own, probably, or possible carcinogens, with quantitative cancer dose

- response values available. These 3 8 HAP, their quantitative inhalation chronic cancer dose

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

- 1 ( A )

. The dioxin and PO M compounds with chronic oral cancer dose

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

- 1 ( B )

. Thirty HAP have quantitative inhalation chronic noncancer threshold values available; t wo of th ese thirty H AP ( cadmium and mercury), for which a multipathway assessment w as performed, also ha ve quantitative oral chronic noncancer threshold values available. These 30 HAP, their threshold values, and the source of the value are listed in Table 2.6

- 2 ( A ) and Table 2.6

- 2 ( B )

.

Table 2.6

- 1 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 20 = cancer risk per μg/m 3 of a verage lifetime exposure. Sources: IRIS = EPA Integrated Risk Information Sys tem, 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 21 URE 5

(1/μg/m 3 ) Source

Arsenic c ompounds 7440382 4.3E

- 3 IRIS Cadmium c ompounds 7440439 0.0018 IRIS Chlorinated Dioxin/Furans 1,2,3,4,6,7,8,9

- Octachlorodibenzo

- p

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

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

- Heptachlorodibenzo

- p

- dioxin 35822469 0.33 EPA ORD

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

20 The URE is the upper

- bound excess cancer risk estimated to result from conti nuous 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.

21 Chemical Abstract Services identification number. For groups of comp ounds that lack a CAS number we have used a surrogate 3

- digit identifier corresponding to the group’s position on the CAA list of HAP.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

21 Table 2.6

- 1 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 20 = cancer risk per μg/m 3 of a verage lifetime exposure. Sources: IRIS = EPA Integrated Risk Information Sys tem, 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 21 URE 5

(1/μg/m 3 ) Source

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

- Heptachlorodibenzofuran 67562394 0.33 EPA ORD 1,2,3,4,7,8,9

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

- Hexachlorodibenzo

- p

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

- Hexachlorodibenzo furan 70648269 3.3 EPA ORD 1,2,3,6,7,8

- Hexachlorodibenzo

- p

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

- Hexachlorodibenzofuran 57117449 3.3 EPA ORD 1,2,3,7,8,9

- Hexachlorodibenzo

- p

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

- Hexachlorodibenzo furan 72918219 3.3 EPA ORD 1,2,3,7,8

- Pentachlorodibenzo

- p

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

- Pentachlorodibenzofuran 57117416 0.99 EPA ORD 2,3,4,6,7,8

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

- Pentachlorodibenzofuran 5 7117314 9.9 EPA ORD 2,3,7,8

- Tetrachlorodibenzo

- p

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

- Tetrachlorodibenzofuran 51207319 3.3 EPA ORD Chromium (VI) 18540299 1.2E

- 2 IRIS Formaldehyde 22 50000 1.3E

- 5 IRIS Naphthalene 91203 3.4E

- 5 CAL
Nickel c ompounds 7440020 2.4E

- 4 23 IRIS Polycyclic Organic Matter 246 24

2

- Methylnaphthalene 91576 8.8E

- 5 CAL Acenaphthene 83329 8.8E

- 5 CAL Acenaphthylene 206968 8.8E

- 5 CAL Benz[a] a nthracene 56553 1.76E

- 4 CAL Benzo[a] p yrene 50328 1.76E

- 3 CAL Benzo[b] f

luoranthene 2059 92 1.76E

- 4 CAL Benzo[e] p yrene 192972 8.8E

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

- 5 CAL Benzo[k] f

luoranthene 207089 1.76E

- 4 CAL Chrysene 218019 1.76E

- 5 CAL

22 The EPA has used the CIIT value (5.5x10

- 9 per mg/m 3 ) to characterize formaldehyde cancer risks in some instances.

23 We typically use the value of 4.8E

- 4 (1/μg/m 3 ) for nickel compounds, as explained earlier in this report. For this source category, we had information to indicate that a value of 2.4E

- 4 (1/μg/m 3 ) was appropriate.

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

in Support of the 2015 Final Rule

22 Table 2.6

- 1 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 20 = cancer risk per μg/m 3 of a verage lifetime exposure. Sources: IRIS = EPA Integrated Risk Information Sys tem, 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 21 URE 5

(1/μg/m 3 ) Source

Dibenzo[a,h] a nthracene 53703 1.92E

- 3 CAL
Fluoranthene 206440 8.8E

- 5 CAL Fluorene 86737 8.8E

- 5 CAL Indeno[1,2,3

- cd] p yrene 193395 1.76E

- 4 CAL Perylene 198550 8.8E

- 5 CAL

Table 2.6

- 1 ( B ) Dose

- Response Values for Chronic Oral Exposure to Carcinogens

SF (oral slope factor for cancer) = cancer risk per mg/kg/d of average lifetime exposure. Sour ces : 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 Dioxin/Furans Hexachlorodibenzo

- p

- dioxin 19408743 6200 IRIS 2,3,7,8

- Tetra chlorodibenzo

- p

- dioxin 1746016 150000 EPA ORD Polycyclic Organic Matter 246 Benz[a] a nthracene 56553 1.2 CAL Benzo[a] p yrene 50328 7.3 IRIS Benzo[b] f

luoranthene 205992 1.2 CAL Benzo[k] f

luoranthene 207089 1.2 CAL Chrysene 218019 0.12 CAL Dibenzo[a,h ] a nthracene 53703 4.1 CAL Indeno[1,2,3

- cd] p yrene 193395 1.2 CALResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

23 Table 2.6

- 2 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens
RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CA L = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry

, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards Pollutant CAS Number 6 RfC (mg/m 3 ) Source 25

Arsenic compounds 7440382 0.000015 CAL Cadmium compounds 7440439 0.00001 ATSDR Chlorinated dioxins and furans 1,2,3,4,6,7,8,9

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

- Octochlorodibenzo

- p

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

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

- Heptachlorodibenzo

- p

- dioxin 35822469 0.000004 CAL 1,2,3,4,7,8,9

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

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

- Hexa chlorodibenzo

- p

- dioxin 39227286 0.0000004 CAL 1,2,3,6,7,8

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

- Hexachlorodibenzo

- p

- dioxin 57653857 0.0000004 CAL 1,2,3,7,8,9

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

- Hexachlorodibenz o

- p

- dioxin 19408743 0.0000004 CAL 1,2,3,7,8

- Pentachlorodibenzo

- p

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

- Pentachlorodibenzofuran 57117416 0.0000013 CAL 2,3,4,6,7,8

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

- Pentachlorodibenzofuran 5711731 4 0.00000013 CAL 2,3,7,8

- Tetrachlorodibenzo

- p

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

- Tetrachlorodibenzofuran 51207319 0.0000004 CAL Chromium (VI) compounds 18540299 0.0001 IRIS

- M Formaldehyde 50000 0.0098 ATSDR Hydrochloric acid 7647010 0.02 IRIS

- L Hydrofluoric acid 7664393 0.014 CAL

Lead compounds 7439921 0.00015 EPA OAQPS Manganese compounds 7439965 0.0003 ATSDR Mercury (elemental) 7439976 0.0003 IRIS

- M
Gaseous d ivalent m ercury 201 0.0003 IRIS

- M Particulate d ivalent m ercury 184 0.0003 IR IS

- M Naphthalene 91203 0.003 IRIS

- M

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

in Support of the 2015 Final Rule

24 Table 2.6

- 2 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens
RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CA L = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry

, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards Pollutant CAS Number 6 RfC (mg/m 3 ) Source 25

Nickel compounds 7440020 0.00009 ATSDR

Table 2.6

- 1 ( B ) Dose

- Response Values for Chronic Oral Exposure to Noncarcinogens

RfD (reference dose) = an estimate (with u ncertainty 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 Integra ted Risk Information System

Pollutant CAS Number RfD (mg/kg/d) Source 26 Cadmium compounds 7440439 0.0005 IRIS

- H Mercuric chloride 27 7439976 0.0003 IRIS

- H

2.6.2 Sources of acute dose

- response information

Hazard identification and dose

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

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

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

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

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

27 The multipathway exposure assessment for mercury included fate and transport analysis, that included separate oral exposure estimates for diva lent mercury and methylmercury.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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

“ 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 health effect reported in the medical and toxicological literatu re. RELs are designed to protect the most sensitive individuals in the population by the inclusion of margins of safety. Since margins of safety are incorporated to address data gaps and uncertainties, exceeding the REL does not automatically indicate an adverse health impact. ” Acute RELs are developed for 1

- hour (and 8

- hour) exposures. The values incorporate uncertainty factors similar to those used in deriving EPA’s Inhalation Reference Concentrations (RfCs) for chronic exposures (and, in fact, Califor nia 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 Substances , and then reviewed and published by the Nat ional 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 preparedness and prevention plans, as well as real time emergency response actions, for accidental chemical releases at fixed facilities and from transport carriers.” The document states that “the primary purpose of the AEGL program and the NAC/AEGL Committee is to develop guideline levels for once

- in

- a

- lifetime , short

- term exposures to airborne concentrations of acutely toxic, high

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

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

- time emergency response actions, for accidental chemical releases at fixed facilities and from transport carriers.”

The NAC/AEGL defines AEGL

- 1 and AEGL

- 2 as:

“ AE GL

- 1 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, including susceptible individuals, could experience notable discomfort, irritation, or certain asymptomatic nonsensory ef fects. 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, includin g susceptible individuals, could experience irreversible or other serious, long

- lasting adverse health effects or an impaired ability to escape. ”Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

26 “ Airborne concentrations below AEGL

- 1 represent exposure levels that can produce mild and progressively incr easing 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 severit y of effects described for each corresponding AEGL. Although the AEGL values represent threshold levels for the general public, including susceptible subpopulations, such as infants, children, the elderly, persons with asthma, and those with other illness es, it is recognized that individuals, subject to unique or idiosyncratic responses, could experience the effects described at concentration s below the corresponding AEGL.”

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene A ssociation (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [ 21 ] for acute exposures at three different levels of severity. These guidelines represent concentrations for exposure of the general population (but not particularly sensitive persons) for up to 1 hour associated with effects expected to be mild or transient (ERPG

- 1), irreversible or serious (ERPG

- 2), and potentially life

- threatening (ERPG

- 3).

ERPG values ( https://www.aiha.org/get

involved/aihaguidelinefoundation/emergencyresponseplanningguidelines/Pages/default.aspx )

are described in their supporting documentation as follows: “ ERPGs are air conce ntration guidelines for single exposures to agents and are intended for use as tools to assess the adequacy of accident prevention and emergency response plans, including transportation

emergency planning

, comm unity emergency response plans , and incident p revention and mitigation

. ”

ERPG

- 1 and ERPG

- 2 values are defined by AIHA as follows:

“ ERPG

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

“ ERPG

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

In the RTR program, EPA assesses acute risk using toxicity values derived from one hour exposures. Based on an in

- depth examination of the available acute value for nickel [California EPA’s acute (1

- hour) REL], we have concluded that this value is not appropriate to use to support EPA’s risk and technology reviews rules. This conclusion takes into account: the ef

fect on which the acute REL is based; aspects of the methodology used in its derivation; and how this assessment stands in comparison to the ATSDR toxicological assessment, which considered the broader nickel health effects database.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

27 The broad nickel non cancer health effects database strongly suggests that the respiratory tract is the primary target of nickel toxicity following inhalation exposure. The available database on acute noncancer respiratory effects is limited and was considered unsuitable for

q uantitative analysis of nickel toxicity by both California EPA 28 and ATSDR 29

. The California EPA’s acute (1

- hour) REL is based on an alternative endpoint, immunotoxicity in mice, specifically depressed antibody response measured in an antibody plaque assay.

In addition, the current California acute (1

- hour) REL for nickel includes the application of methods that are different from those described in EPA guidelines. Specifically, the (1

- hour) REL applies uncertainty factors that depart from the defaults in EPA guidelines and does not apply an inhalation dosimetric adjustment factor.

Further, the ATSDR’s intermediate MRL (relevant to nickel exposures for a time frame between 14 and 364 days), was established at the same concentration as the California EPA (1

- hour) REL, indicating that exposure to this concentration “is likely to be without appreciable risk of adverse noncancer effects” (MRL definition) 30 for up to 364 days.

We have high confidence in the nickel ATSDR intermediate MRL. Our analysis of the b road toxicity database for nickel indicates that this value is based on the most biologically

- relevant endpoint. That is, the intermediate MRL is based on a scientifically sound study of acute respiratory toxicity. Furthermore, this value is supported by a robust subchronic nickel toxicity database and was derived following guidelines that are consistent with EPA guidelines. 31 Finally, there are no AEGL

- 1/ERPG

- 1 or AEGL

- 2/ERPG

- 2 values available for nickel. Thus, for all the above mentioned reasons, we wil l not include nickel in our acute analysis for this source category or in future assessments unless and until an appropriate value becomes available.

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

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

- 3

.

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

29 http://www.atsdr.cdc.gov/substances/toxsubstance.asp ?toxid=44
30 Agency for Toxic Substances and Disease Registry (ATSDR), Toxic Substances Port al. Minimal Risk Levels (MRLs) http://www.atsdr.cdc.gov/mrls/index.asp

31 US EPA 2002. Review of the referen ce dose and reference concentration processes (EPA/630/P

- 02/002F December 2002, http://www.epa.gov/raf/publications/pdfs/rfd

- final.pdfResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

28

Table 2.6

- 3 Dose

- Response Values for Acute Exposure

Pollutant CAS Number AEGL

- 1 (1

- hr) (mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

- 1

(mg/m 3 ) ERPG

- 2

(mg/m 3 ) REL

(mg/m 3 ) Arsenic c ompounds 7440382 0.0002 Formaldehyde 50000 1.1 17 1.2 12 0.055 Hydrochloric a cid 7647010 2.7 33 4.5 3 0 2.1 Hydrofluoric a cid 7664393 0.82 20 1.6 16 0.24
M ercury (el emental) 7439976 1.7 2 0 .0006



### 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 i s complete, informative, and useful for decision makers. In general, the nature of this risk characterization depends on the information available, the application of the risk information and the resources available. In all cases, major issues associated with determining the nature and extent of the risk are identified and discussed. Further, the EPA Administrator’s March 1995 Policy for Risk Characterization [ 22 ] specifies that a risk characterization “be prepared in a manner that is clear, transparent, reasonable, and consistent with other risk characterizations of similar scope prepared across programs in the Agency.” These principles of transparency and consistency have been reinforced by the Agency’s Risk Characterization Handbook [ 23 ], in 2002 by the Agency’s information quality guidelines [ 24 ], and in the OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis 32 , and are incorporated in these assessments.

Estimates of health risk are presented in the context of uncertainties and lim itations in the data and methodology. Through our tiered, iterative analytical approach, we have attempted to reduce both uncertainty and bias to the greatest degree possible in these assessments, within the limitations of available time and resources. W e provide summaries of risk metrics (including maximum individual cancer risks and noncancer hazards, as well as cancer incidence estimates) along with a discussion of the major uncertainties associated with their derivation to provide decision makers with the fullest picture of the assessment and its limitations.

32 Memorandum f

or t he Heads o f Executive Department s a nd Agencies

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

- 24.pdfResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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

- bound probability of developing cancer over a 70

- y r period (i.e., the assumed human lifespan) at that exposure. Because UREs for most HAP are upper

- bound estim ates, actual risks at a given exposure level may be lower than predicted, and could be

zero.

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

- of

- action [ 25 ], we applied EPA’s Supplemental Guidance for Assessing Susceptibility from Early

- Life Exposure to Carcinogens [ 26 ]

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

- 1), 3 (for children aged 2

- 15), or 1.6 (for 70 years of exposure beginning at birth), as needed in risk assessments . In this case, this has the effect of increasing the estimated life time risks for these pollutants by a factor of 1.6. In addition, although only a small fraction of the total POM emissions may be reported as individual compounds, EPA expresses carcinogenic potency for comp ounds 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 Gui dance to all carcinogenic PAHs for which risk estimates are based on relative potency. Accordingly, we applied the Supplemental Guidance to all unspeciated POM mixtures.

Increased cancer incidence for the entire receptor population within the area of ana lysis wa s estimated by multiplying the estimated lifetime cancer risk for each census block by the number of people residing in that block, then summing the results for the entire modeled domain. This lifetime population incidence estimate wa s divided by 70 years to obtain an estimate of the number of cancer cases per year.

Unlike linear dose

- response assessments for cancer, noncancer health hazards generally are not expressed as a probability of an adverse occurrence. Instead, “risk” for noncancer effec ts 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 likel y to cause adverse health effects. As exposures increase above the reference level (HQs increasingly greater than 1), the potential for adverse effects increases. For exposures predicted to be above the RfC, the risk characterization includes the degree of confidence ascribed to the RfC values for the compound(s) of concern (i.e., high, medium, or low confidence) and discusses the impact of this on possible health interpretations.

The risk characterization for chronic effects other than cancer is expres sed in terms of the HQ for inhalation, calculated for each HAP at each census block centroid. As discussed above, RfCs incorporate generally conservative uncertainty factors in the face of uncertain extrapolations, such that an HQ greater than one does no t necessarily suggest the onset of adverse effects. The HQ cannot be translated to a probability that adverse effects will occur, and is unlikely to be proportional to adverse health effect outcomes in a population

.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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

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

2.7.2 Mixtures

Since most or all receptors in these assessments receive exposures to multiple pollutants rather than a single pollutant, we estimated the aggregate health risks associated with all the exposures from a particular source category combined.

To combine risks across m ultiple carcinogens, our assessments use the mixtures guidelines’ [ 28

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

In assessing noncancer hazard from chronic ex posures, in cases where different pollutants cause adverse health effects via completely different modes of action, it may be inappropriate to aggregate HQs. In consideration of these mode

- of

- action differences, the mixtures guidelines support aggregating effects of different substances in specific and limited ways. To conform to these guidelines , we aggregated non

- cancer HQs of HAP that act by similar toxic modes of action, or (where this information is absent) that affect the same target organ. This pr ocess 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 effec ts occurring at the “ critical dose” (i.e., the lowest dose that produces adverse health effects). Although HQs associated with some pollutants have been aggregated into more than one TOSHI, this has been done only in cases where the critical dose affects more than one target organ

. Because impacts on organs or systems that occur above the critical dose have not been included in the TOSHI calculations, some TOSHIs may have been underestimated. As with the HQ, the TOSHI should not be interpreted as a proba bility of adverse effects, or as strict delineation of “safe” and “unsafe” levels. Rather, the TOSHI is another measure of the potential for adverse health outcomes associated with pollutant exposure, and needs to be interpreted carefully by health scient ists and risk managers.

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

2.7.3 MACT

- Al lowable Risks The emissions data in the dataset for the ferroalloys source category are estimates of actual emissions on an annual basis. The risk results presented in the following sections are based on these actual emissions. For the ferroalloys produc tion source category, estimates of MACT

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

in Support of the 2015 Final Rule

31 are presented below as well. For more detail, please refer to the emissions memo in the docket, which is also Appendix 1 to this document, Revised Development of the Risk and Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category for the 2015 Final Rule

.



### 3 Risk 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, chr omium, manganese, and/or silicon. Silicon metal is also typically considered a ferroalloy product. Ferroalloy products are consumed primarily in iron and steel making, where they are used to produce steel and cast iron products with enhanced or special p roperties. 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 a nd screening operations) also occur as part of the ferroalloy production process. The HAP emission sources at ferroalloys production facilities include EAFs, tapping operations, metal oxygen refining (MOR) processes , crushing and screening operations, lad le treatment, casting, and fugitive dust sources. The specific HAP that are emitted, and the quantity of these emissions, are related to the amount of HAP compounds present in the raw materials used. Metallic HAP expected to be emitted by the furnaces in clude arsenic, chromium, manganese, and nickel. Emissions of polycyclic organic matter (POM), such as PAH, are also expected. Additionally, chlorine is present in coal, which is used as a raw material in the furnace, and thus hydrochloric acid emissions can be expected.

T here are 2 ferroalloys production facilities operating in the U.S. Both facilities are identified as major sources of HAP. The emissions for the ferroalloys source category dataset are summarized in Table 3.1

- 1. The total HAP emis sions for the so urce category are approximately 200 tons per year. Based on these data, the HAP emitt ed in the largest quantities are manganese compounds, hydrofluoric acid, hydrochloric acid, phenanthrene, fluoranthene, formaldehyde , pyrene, and naphthal ene

. 33 Emissions of these eight HAP make

up more than 9 5 percent of the total emissions by mass. Persistent and bioaccumulative HAP (PB

- HAP) 34 reported as emissions from these facilities include lead compounds, mercury compounds, PCBs, dioxins/furans, ca dmium compounds, and polycyclic organic matter. The following environmental HAP are emitted from the ferroalloys production source category

33 As described in the emissions memo Revised Development of the Risk and Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category , numerical estimates for HF were provided for input to the risk assessment. Upon closer investigation, we found that all test results were below the detection limit of the test method and therefore we believe HF is not emitted from these sources.

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

- 453K

- 04

- 001A, as refer enced in the ANPRM and provided on the EPA’s Technology Transfer Network website for Fate, Exposure, and Risk Assessment at http://www2.epa.gov/sites/production/files/2013

- 08/documents/volume_1_reflibrary.pdfResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

32 and are included in the environmental risk screen: cadmium, dioxins/furans, hydrogen chloride, hydrofluoric acid, lead, mercury , and PAHs

.

Table 3.1

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

Assessment and Availability of Dose

- Response Values

HAP a Emission

Estimates (tpy) Number of

Facilities where HAP Repor ted or Es timated ( 2 facilities in dataset) 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 c ompounds 109 2  Hydro fluoric a cid 39 2   Hydrochloric a cid 24 2   Formaldehyde 5 2    Polycyclic Organic Matter
2

- Methylnaphthalene 1 2   Acenaphthene 0.3 2   Acenaphthylene 1 2  
Anthracene 0.6 2  Benz[a] a nthracene 0.5 2   Benzo[a] p yrene 0.07 2   Benzo[b] f

luoranthene 0.4 2   Benzo[g,h,i] p erylene 0.03 2   Benzo[e] p yrene 0.2 2   Benzo[k] f

luoranthene 0.12 2   Chrysene 1 2   Dibenzo[a,h] a nthracene 0.005 2  
Fluorene 0.5 2  
Fluoranthene 5 2   Indeno[1,2,3

- cd] p yrene 0.03 2   Perylene 0.01 2  
Phenanthrene 5 2  Pyrene 4 2  Naphthalene 3 2  
Lead c ompounds 1 2 c 
Nickel c ompounds 0.4 2   Mercury c ompounds Mercury (elemental) 0.2 2   
Gaseou s d ivalent m ercury 0.02 5 2  
Particulate d ivalent m ercury 0.02 5 2  
Chromium c ompounds
Chromium III 0.2 2 Chromium (VI) 0.02 2  
Cadmium c ompounds 0.1 2   Y
Arsenic c ompounds 0.04 2   Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

33 Table 3.1

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

Assessment and Availability of Dose

- Response Values

HAP a Emission

Estimates (tpy) Number of

Facilities where HAP Repor ted or Es timated ( 2 facilities in dataset) 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?

Polychlorinated Biphenyls 0.0003 2  Y
Chlorinated Dibenzodioxins and furans 1,2,3,4,6,7,8,9

- Octochlorodibenzofuran 2. 14 E

- 07 2   Y

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

- Octochlorodibenzo

- p

- dioxin 5.63 E

- 07 2   Y

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

- Heptachlorodibenzofuran 1.64 E

- 07 2   Y

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

- Hep tachlorodibenzo

- p

dioxin 1.22 E

- 07 2   Y

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

- Heptachlorodibenzofuran 4.32 E

- 08 2   Y

1,2,3,4,7,8

- Hexachlorodibenzofuran 2.30 E

- 07 2   Y

1,2,3,4,7,8

- Hexachlorodibenzo

- p

- dioxin 4.66 E

- 08 2   Y

1,2,3,6,7,8

- Hexachlorodibenzofuran 1.14 E

- 07 2   Y

1,2,3,6,7,8

- Hexachlorodibenzo

- p

- dioxin 4.78 E

- 08 2   Y

1,2,3,7,8,9

- Hexachlorodibenzofuran 4.46 E

- 08 2   Y

1,2,3,7,8,9

- Hexachlorodibenzo

- p

- dioxin 5.64 E

- 08 2   Y

1,2,3,7,8

- Pentachlorodibenzofuran 3.05 E

- 07 2   Y

1,2,3,7,8

- Pentachlorod ibenzo

- p

dioxin 7.50 E

- 07 2   Y

2,3,4,6,7,8

- Hexachlorodibenzofuran 8.39 E

- 07 2   Y

2,3,4,7,8

- Pentachlorodibenzofuran 2.91 E

- 07 2   Y

2,3,7,8

- Tetrachlorodibenzofuran 1.55 E

- 06 2   Y

2,3,7,8

- Tetrachlorodibenzo

p

- dioxin 9.24 E

- 0 8 2   Y

a Notes for how HAP were speciated for risk assessment:

 For most metals, emissions reported as the elemental metal are combined with metal compound emissions (e.g., “cadmium” emissions modeled as “cadmium & compounds”). In the absence of speciation information, we assume the reported mass is 100 percent metal.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

34  Chromium emissions wer e speciated based on test data . S ee Appendix 1 of this document ( Revised Development of the Risk and Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Ca tegory for the 2015 Final Rule ) for more information.

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

as 80 percent “mer cury (elemental),” 10 percent “gaseous divalent mercury,” and 10 p ercent “particulate divalent mercury.” Mer cury speciation profiles can be found on the EPA’s Technology Transfer Network website for emissions inventories at http://www. epa.gov/ttn/chief/net/2005inventory.html#inventorydata

b Specific dose

- response values for each chemical are identified on EPA’s Technology Transfer Network website for air toxics at http://www2.epa.gov/fera/dose

- response

- assessment

- assessing

- health

- risks

- associated

- exposure

- hazardous

- air

pollutants

c There is no reference concentration for lead. In cons idering noncancer hazards for lead in this assessment, we compared the average exposure estimates to the National Ambient Air Quality Standards (NAAQS) for lead (0.15 μg/m 3 ). These NAAQS for lead were 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) standar d is identical to the primary standard.



### 3.2 Baseline r isk c haracterization This section presents the results of the baseline risk assessment for the f erroalloys production source category based on the modeling methods described in the previous sections

. All baseline risk results are developed using the best estimates of actual HAP emissions summarized in the previous section. The basic chronic inhalation risk estimates presented here are the maximum individual lifetime cancer risk, the maximum chronic hazard index, and the cancer incidence. We also present results from our acute inhalation impact screening assessments in the form of maximum hazard quotients, as well as the results of our preliminary screen for potential non

- inhalation risks from PB

- HAP. Als o presented are the HAP “drivers,” which are the HAP that collectively contribute 90 percent of the maximum cancer risk or maximum hazard at the highest exposure location , as well as our analysis of risks associated with the maximum allowed emissions under the current MACT standards. A detailed summary of the facility

- specific risk assessment results is available in Appendix 6 of this document, Detailed Risk Modeling Results

.

Baseline Inhalation Risk Assessment Results Based on Actual Emissions

Tab le s 3 .2

- 1 and 3.2

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

. T he results of the chronic inhalation cancer risk assessment estimate that the maximum lifetime individual cancer risk posed by these two facilities coul d be as high as 20 in a million , with PAHs, chromium compounds, and nickel compounds from process fugitives as the major contributors to the risk. The total estimated cancer incidence from this source category is 0.00 3 ex cess cancer cases per year, or one excess case in every 333 years. A pproximate ly 90 pe ople are estimated to have cancer risks above 10 in a million and approximatel y 4 1,000 peop le are estimated to have cancer risks above 1 in a million considering the two facilities in this source categor y . The maximum chronic noncancer TOSHI value for the source category could be up to 4 from emissions of man ganese from process fugitives as the major contributors to the HI. A n estimated 1, 3 00 people are exposed to TOSHI levels above 1 due to manganese e missions

.

Worst

- case a cute hazard quotients (HQs) were calculated for every emitted HAP that has an acute benchmark, as shown in Table 3.1

- 1 . For cases where the screening HQ was greaterResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

35 than 1, we further refined the estimates by determining the hig hest HQ value that might occur outside facility boundaries. Based on actual, baseline emissions, th e high est acute screening HQ value is 1 (based on the acute REL s for arsenic compounds and hydrofluoric acid ) and is shown in Table 3 .2

- 1

. This value inclu des a refinement of determining the highest HQ value that is outside facility boundaries

.

Table 3.2

- 1 Summary of Source Category Level Inhalation Risks for Ferroalloys

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

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

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 20 chromium compounds, PAH, nickel compounds Number of Facilities with Ma ximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a

Greater than or equal to 10 in 1 million 2 chromium compounds, PAH, nickel compounds, arsenic compounds, formaldehyde, dioxins, cadmium compounds

Greater than or e qual to 1 in 1 million 2 chromium compounds, PAH, nickel compounds, arsenic compounds, formaldehyde, dioxins, cadmium compounds Chronic Noncancer Risks Maximum Neurological Hazard Index 4 manganese compounds Number of Facilities with Maximum Neurologica l Hazard Index: Greater than 1 2 manganese compounds Acute Noncancer Refined Screening Results

Maximum Acute Hazard Quotient 35 1 1 <1 <1 <1 arsenic compounds (REL)

hydrofluoric acid (REL) formaldehyde (REL) hydrochloric acid (REL) mercury (REL) Number of Facilities With Potential for Acute Effects 0 n/a
Population Exposure

35 There are no reference values available (including a lack of short

- term occupational values) to assess any potential risks from acute exposure to manganese. In addition, as described earlier, we do not believe that HF is emitted from these sources.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

36 Table 3.2

- 1 Summary of Source Category Level Inhalation Risks for Ferroalloys

Result HAP “Drivers” Number of People Living Within 50 Kilometers of Facilities Modeled 3 80 ,000 n/a
Number of People Exposed to Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a

Greater than or equal to 10 in 1 million 90 n/a
Greater than or equal to 1 in 1 million 4 1 ,000 n/a Number of People Exposed to Noncancer Neurological Hazard Index: Greater than 1 1, 3 00 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.00 3 n/a
Contribution of HAP to Cancer Incidence
P AH 4 9 % n/a Chromium compounds 1 5 % n/a Cadmium compounds 1 2 % n/a

Baseline Inhalation Assessment Results Based on Allowable Emissions

Analysis of potential differences between actual emissions levels and the maximum emissions allowable under the MACT standards (i.e., MACT

- allowable emissions) were also calculated for stack emissions for the two facilities. 36 Risk estimates based on the actual emissions were then scaled up using these factors. (See Revised Dev elopment of the Risk and Technology Review (RTR) Emissions Dataset for the Ferroalloys Production Source Category for the 2015 Final Rule in Appendix 1 of this document , or separately in the docket, for a discussion of the development of the allowable fact ors.) In addition, an idled furnace at Eramet was included in the calculation of allowable risks. Risk results from the inhalation risk assessment using the MACT

- allowable stack emissions indicate that the maximum lifetime individual cancer risk could be as high as 100 in a million with arsenic and cadmium emissions driving the risks , and that the maximum chronic noncancer TOSHI value could be as high as 40 at the MACT

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

are likely higher than these presented here because process fugitive emissions increase with increased stack emissions (for which there are current MACT standards) , and emissions of pollutants for which there are currently no MACT standards would also increase with increased stack emissions.

36 MACT

- allowable emissions were not calculated for process fugitive or fugitive emissions because the current MACT standard only has emission limits for stack emissions. In addition, MACT

- allowable emissions were not calculated for those HAP (e.g., PAH) that do not currently have a MACT sta ndard. Finally, for Eramet, the allowable estimates include emissions for an idle furnace that was not included in the calculation of actual emissions because it is not currently operating. MACT

- allowable emissions, and associated risks, are likely under estimated.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

37 Baseline Multipathway Assessment Results Based on Actual Emissions

To identify potential multipathway health risks from PB

- HAP other than lead, we first performed a screening analysis (Tier I ) that compared emissions o f PB

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

- HAP emitted by facilities in this category include cadmium compounds, chlorinated dibenzodioxins and furans (as 2,3,7,8

- TCDD toxicity equivalents, or TEQ),

mercury compounds, polychlorinated biphenyls (PCBs), and P OM ( as benzo(a)pyrene TEQ). PCBs are PB

- HAP but do not currently have multipathway screening value s and so w ere not evaluated for potential non

- inhalation risks . As shown in Table 3.1

- 1, this PB

- HAP is not emitted in appreciable quantities.

The two facilities in the source category both reported emissions of these PB

- HAP, and with the exception of cadmium emissions from one facility, both facilities had emiss ion rates greater than the Tie r I screening emission levels for all four PB

- HAP indicating that the initial multipathway screening model does not rule out the potential for multipathway impacts of

concern

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

. One facility’s emission rates of

mercury exceeded the screening level by 100 times, while the other facility ’s mercury emission rates exceeded the level by 10 times. F or dioxins, one facility’s emission rates exceeded the level by 100 times, while the other facility’s emission rates exceeded the level by 4 0 times. For POM, one facility ’s emission rates exceeded the screening level by 5 00 times, while the other facility ’s emission rates exceeded the level by 2 0 times. Due to the theoretical construct of the screening model, these factors are not directly translatable into estimates of risk or hazard quotients for these facilities. Table 3.2

- 2 summarizes the results of this Tier I screen.

For the PB

- HAP and facilities that did not screen out during our initial Tier I multipathway screening analysis, we improved our analysis with some additional site

- specific information to develop a Tier II screen. (See Appendix 4 of this document, Technical Support Document for TRIM

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

, for more information about th e Tier II screen.) T he additional site

- specific information included the land use around t he facilities

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

- specific emission screening levels for each of the four PB

- HAP

. Based on this Tier II screening analysis, the cadmi um emission rates for both facilities were below site

- specific levels for that
PB

- HAP. For mercury, one facility’s emissions was below the screening level , while the other facility had emissions of mercury that exceeded its site

- specific level by eight ti mes. The PAH and dioxin emissions at both facilities exceeded their respective site

- specific levels by a range of 2 to 5 0. Table 3.2

- 2 presents these results.

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

c annot be equated with a risk value or a hazard quotient (or hazard index). Rather, it represents a high

- end estimate of what the risk or hazard may be. For example, an exceedance of 2 for a non

- carcinogen can be interpreted to mean that we have high conf idence that the hazard would be lower than 2. Similarly, an exceedance of 30 for aResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

38 carcinogen means that we have high confidence that the risk is lower than 30 in a million. Our confidence comes from the conservative, or health

- protective, assumptions th at are in the

screen s : we choose inputs from the upper end of the range of possible values for the influential parameters used in the screens; and we assume that the exposed individual exhibits ingestion behavior that would lead to a high total exposure.

T able 3.2

- 2 Summary of Source Category Level Multipathway Screening Assessment Risk Result s for Ferroalloys

Tier I Tier II

PBHAP Facilities

Emitting PBHAP (2 in

source category) Max

Emissions of this PBHAP (TPY) a Max

Emissions Div ided by Scr eening Level Facilities

Exceeding Screening Level Max

Emissions Div ided by Screening Level (fish only) Max

Emissions Div ided by Screening Level (farm only) Facilities

Exceeding Either Screening Level
Carcinogens Chlorinated Dibenzodioxins and Furans as 2,3,7,8

- Tetrachlorodibenzo

- p

dioxin TEQ 2 3.53E

- 7 100 2 7 7 2

Polycyclic Organic Matter as Benzo(a)Pyrene TEQ 2 1.25E

- 00 5 00 2 10 30 2

Non

- carcinogens Cadmium Compounds 2 1.17E

- 1 10 1 0. 7 0.07 0 Divalent Mercury 2 4.19E

- 2 100 2 8 0.009 1

Notes:

a

– PAH and dioxin emissions in this column were normalized to BaP and 2,3,7,8

- TCDD, respectively, for oral toxicity and Tier I modeled environmental fate and transport. Emissions were further normalized in Tier II for environmental fate and transport.

We cond u cted a more refined multipathway assessment f or one of the facilities in the ferroalloys production source category. This facility, the Eramet facility in Marietta, Ohio was selected (1) because of its Tier II screening results and (2) based on th e feasibility, with respect to the modeling framework, of obtaining parameter values for the region surrounding the facility. We expect that t he exposure scenarios we assessed are among the highest that might be encountered for this source category , altho ugh not the absolute highest . The approach, data, assumptions, and results of the site

- specific assessment are presented in Appendix 10 of this document ( Technical Support Document: Human Health Multipathway Residual Risk Assessment for the Ferroalloys P roduction Source Category ).

The site

- specific assessment, a s in the screening assessments, includes some hypothetical elements, namely the hypothetical farmer and angler scenarios . We also included children in different age ranges and adults. It is imp ortant to note that even though the multipathway assessment has been conducted, no data exist to verify the existence of either the farmer or angler scenario outlined below. The farmer scenario involves an individual living for a 70

- year lifetime on a far m homestead in the vicinity of the source and consuming produce grown on, and meat and animal products raised on, the farm. The individual also incidentally ingestsResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

39 surface soil at the location of the farm homestead. The angler scenario involves an indiv idual who regularly consumes fish caught in freshwater lakes in the vicinity of the source of interest over the course of a 70

- year lifetime. In addition, exposure estimates and risks for infants consuming contaminated breast milk were evaluated in the ca se of dioxins, with the assumption that the nursing mother was exposed to chemicals via one of the two scenarios described above. We evaluated v ariations of these two scenarios u sing different assumptions regarding food source (i.e., location of the farm homestead or the water body from which fish are obtained), the age of the individual exposed (for noncancer hazards), the assumed ingestion rate of each food type, and other factors. In particular, a range of fish ingestion rates was evaluated to determin e the possible health risks associated with that pathway.

Results of the Site

- Specific Multipathway Assessment:

 Cancer risk estimates from the site

- specific assessment are presented in Table 3.2

- 3 (Maximum Site

- Specific Results column)

.
o Incremental lifet ime cancer risk from exposure to PAHs is 10

- in

- 1 million from the farm pathway and 7

- in

- 1 million from the fish pathway

.
o Incremental lifetime cancer risk from exposure to dioxins is 1

- in

- 1 million from the farm pathway and 0.5 from the fish pathway

.
o For bo th the PAHs and dioxins, farm ingestion at the 90 th percentile ingestion rate drives the risk.

 Noncancer hazards from the site

- specific assessment are also presented in Table 3.2

- 3 (Maximum Site

- Specific Results column)

.
o Noncancer hazard quotients did no t exceed one for any scenario (farm or fish) for exposure to cadmium, and was driven by fish ingestion by the adult female angler at the 99 th percentile ingestion rate.

o The noncancer hazard quotient f or mercury was estimated to be 1 from the fish pathway , with methyl mercury exposure to the adult female angler at the 99 th percentile ingestion rate for the subsistence fisherman or at a rate of 373 grams/day driving the ris k. These risk estimates are the maximum results from the refined assessment.

Beca use th is mor e refined assessment uses location

- specific information where appropriate and available (e.g., location of actual lakes rather than a generic lake as in Tier I 1 ) , the water body producing the maximum risk results can change between the Tier I s creen and the refined assessments. Since the Tier II screen employs the “ subsistence ” method, multiple lakes are included in that screening scenario, while only one is the “maximum” lake in the site

- specific assessment. We can also show the comparison o f results from the Tier I screen, the Tier II screen, and the site

- specific assessment in order to observe the trend in screening level exceedances , however given the differences just described, it is not a comparison of equivalent scenarios. The trend al so shows how obtaining more site

- specific data can decrease the emission rate screening level . For example, for mercury, we can see that the Tier I exceedance is 100 times the Tier I emission rate level for mercury, the Tier II exceedance for the fish pat hway is 8 times the facility

- specific Tier II emission rate level for mercury, and the site

- specific assessment produces an HQ of 1 . (As stated above, Tier I and Tier II results are not risk estimates.)Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

40 T able 3.2

- 3 Summary of Source Category Level Site

- Specifi c Multipathway Risk

Results for Ferroalloys Baseline Scenario

PB

- HAP Emissions Divided by Screening Level Site

- Specific Assessment Cancer Risk or Hazard Quotient

Tier I (farm and fish) b Tier II

(farm only) Tier II (fish

only) Maximum

Site

- Specific Results (fish only) c Maximum Site

Specific Results (farm only) d

Dioxins (cancer) 40 2 2 0.5 1

PAH (cancer) 500 10 30 7 10

Cadmium (noncancer) 10 0.7 0.07 0.09 0.05

Mercury a (noncancer) 100 8 0.009 1 0.01

Notes:

a Exposure to methyl mercu ry was evaluated for the fish pathway, while exposure to divalent mercury was evaluated for the farm pathway.

b Tier I assessments do not separately assess risks or hazards from fish and farm; they are aggregated. To be congruent with the setup of the scr eening assessments, the site

- specific values use the Chile 1

- 2 age group for HQs (the ingestion amount per body weight is largest for the Child 1

- 2 category), a lifetime defined as age 1 through age 70) including infant breast milk for dioxin exposure) for cancer risk, the “subsistence angler” scenario for fish exposure, and the 90 th percentile ingestion rate for subsistence farmer exposure.

c Site

- specific assessments assess risks or hazards from individual lakes, while Tier II assessments assess risks or hazards from potentially multiple lakes in combination. For mercury, Wolf Run Lake is the maximum lake, while for the other PB

- HAP, Veto Lake was the maximum lake.

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

- HAP, the NNW farm wa s the maximum farm.

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

. Results of this analysis estimate that the NAAQS for lea d w ould not be exceeded at either of the two facilities. T his analysis estimates that the annual lead concentrations could be up to about 20 percent of the value of the NAAQS for lead ( maximum concentration is 0.02 7 μg/m 3 ) . The maximum post

- control conce ntration of lead at either facility is 0.0 1 μg/m 3 , or about seven percent of the NAAQS value.

Baseline Environmental Risk Screening Based on Actual Emissions

We conducted a screening

- level evaluation of the potential adverse environmental risks associ ated with emissions of the following environmental HAP from the ferroalloysResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

41 production source category: cadmium, dioxins/furans, hydrogen chloride, hydrofluoric acid, 37 lead, mercury, and P AHs . The results of the environmental screening analysis are

summa rized in Table 3.2

- 4

.

In the Tier I screening analysis for PB

- HAP (other than lead, which was evaluated differently) , the individual modeled Tier I concentrations for one facility in the source category exceeded some sediment, fish

– avian piscivorus, a nd surface soil benchmarks for PAHs, methyl mercury, and mercuric chloride. Therefore, we conducted a Tier II screen for PAHs, methyl mercury, and mercuric chloride.

In the Tier II screen for PAHs and methyl mercury, none of the individual modeled

con centrations for any facility in the source category exceeded any of the ecological benchmarks (either the LOAEL or NOAEL). For mercuric chloride, soil benchmarks were exceeded for one facility for some individual modeled points that collectively accounted for 11 percent of the modeled area ( 6 percent of the area modeled in the category) . However, the weighted average modeled concentration for all soil parcels was well below the soil benchmarks. For lead, we did not estimate any exceedances of the seconda ry lead NAAQS.

For HCl, each individual concentration (i.e., each off

- site data point in the modeling domain) was below the ecological benchmarks for all facilities. The average modeled HCl concentration around each facility (i.e., the average concentrat ion of all off

- site data points in the modeling domain) did not exceed any ecological benchmark.

For HF, some individual modeled points exceeded the ecological benchmarks for one facility but accounted for less than 0. 02 percent of the modeled area for that facility (0.0 1 percent of the modeled area for the category) . The average modeled HF concentration around each facility (i.e., the average concentration of all off

- site data points in the modeling domain) did not exceed any ecological benchmark. 38

37 As described earlier, we do not believe that HF is emitted from these sources.

38 As described earlier, we do not believe that HF is emitted from these sources.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

42 Table 3.2

- 4 Summary of Source Category Environmental Risk Screen ing Results for Ferroalloys

Environmental HAP Number of Facilities In Category Exceeding Percent of Modeled Area in Category Exceeding 2
Tier I Screen Tier II Screen 1 NOAEL LOAEL NOA EL LOAEL NOAEL LOAEL

PB

HAP Pb None None None None 0% 0%

HgCl 2 NA 1 NA None NA 6 % Methyl Hg 1 None None None 0% 0%
PAH 1 N one None None 0% 0% Dioxins None None None None 0% 0% Acid Gases HF 3 NA N one

- - NA 0 .0 1 %

HC l 4 N A N one

- - NA 0%

NA

– Not Applicable. 1

- Tier II screen is performed for PB

- HAP when there are exceedances of the Tier I screen. The acid gas screen is a one tier screen. 2

- A value of 0% indicates that none of the modeled data points exceeded the benchmark. For PB

- HAP th e percent area is based on the Tier II results, if a Tier II analysis is performed. Otherwise, the percent area is based on the Tier I results. 3

– For HF, we evaluated two benchmarks, one from Canada and the other from the State of Washington. Although , they are both considered to be LOELs

- the level between a NOAEL and a LOAEL, we have listed the results under the LOAEL column. 4

– For HC l , we evaluated one benchmark at the LOAEL level.



### 3.3 Post

- control risk characterization Process fugitive emissions of metal HAP are primarily driving the baseline risks. Given this, using the same risk assessment methods described above, we estimated what the risks would be if the two manganese facilities adopted control measures to limit process fugitive emissions by 9 5 percent (e.g., enhanced local capture ). 39 Based on this scenario, we estimated that the maximum chronic noncancer inhalation TOSHI value would be reduced to 1 , from the baseline estimate of 4 , with manganese emissions from the MOR process baghouse outlet driving the risk

. The re would be no people estimated to have a TOSHI greater than 1

. With respect to cancer risk, given the control scenario described above, the cancer MIR would be reduced from 20 in a million (i.e., pre

- controls) to approximately 10 i n a million (i.e., post

controls), with PAH, cadmium compounds, arsenic compounds, and naphthalene driving the risk. There is an estimated reduction in cancer incidence to 0.00 2 excess cancer cases per year , from 0.00 3 excess cancer cases per year. In ad dition, the number of people estimated to have a cancer risk greater than or equal to 1 in a million would be reduced from 4 1,000 to 2 6, 0 00

. We also note that post

- control, the maximum worst

- case acute refined HQ value

39 This post control scenario also includes the assumption that one facility will in stall controls for mercury.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

43 would be reduced from a potential va lue of 1 to less than 1 (using the REL value s and the refinements described for the baseline acute assessment).

For the baseline emissions scenario, we conducted both multipathway screening assessments and a more refined assessment (results shown above) . For the post

- control scenario, however, we only conducted a screening assessment , with the following results :

 B oth facilities ’ cadmium emissions are below the Tier II facility

- specific emission rate levels for that PB

- HAP for both the farm and fish sce narios

.

 For mercury, the facility with the largest exceedance of the screening value had an exceedance of eight times higher than its Tier II screening emission rate level for the fish scenario . However, as shown above, for the baseline emissions scenar io, which had higher mercury emissions, the refined multipathway assessment produced an HQ of 1 for mercury for this facility

.

 For dioxins, the facility with the largest exceedance of the screening value had an exceedance of 5 times its facility

- specif ic emission rate level for that PB

- HAP for the fish scenario and 5 times its facility

- specific emission rate level for that PB

- HAP for the farm scenario.

 For PAH, the facility with the largest exceedance of the screening value had an exceedance of 3 0 t imes its facility

- specific emission rate level for that PB

- HAP for the farm scenario and 10 times its facility

- specific emission rate level for that PB

- HAP for the fish scenario.

Appendix 4 of this document ( Technical Support Document for TRIM

- Based Multipathway Screening Scenario for RTR: Summary of Approach and Evaluation ) contains a full description of the tiered multipathway screening approach, while Appendix 10 of this document ( Technical Support Document: Human Health Multipathway Residual Risk Assessment for the Ferroalloys Production Source Category ) contains the results of the tiered screening assessment.

As mentioned above, the highest lead concentration after controls, 0.0 1 μg/m3, is below the NAAQS for lead, indicating a low potential f or multipathway impacts of concern due to lead.



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

a ddressed

4.1 E xposure m odeling u ncertainties Although every effort has been made to identify all the relevant facilities and emission points, as well a s to develop accurate estimates of the annual emission rates for all relevant HAP, the uncertainties in our emission inventory likely dominate the uncertainties in the exposure analysis . The chronic ambient modeling uncertainties are considered relatively small in comparison, since we are using EPA’s refined local dispersion model with site

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

- or long

- term population mobility, and by neglecting processes like deposition, plume depletion, and atmospheric degradation.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

44 Additionally, estimates of the maximum individual risk (MIR) contain uncertainty , because they are deriv ed at census block centroid locations rather than actual residences. This uncertainty is known to create potential underestimates and overestimates of the actual MIR values for individual facilities, but, overall, it is not thought to have a significant impact on the estimated MIR for a sourc e category. Finally, we did not factor in the possibility of a source closure occurring during the 70

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

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

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

We have purposely biased the acute screening results high, considering that they depend upon the joint occurrence of in dependent factors, such as hourly emissions rates, meteorology and human activity patterns. Furthermore, i n cases where multiple acute threshold values are considered scientifically acceptable we have chosen the most conservative of these threshold values , erring on the side of overestimating potential health risks from acute exposures. In the cases where these results indicated the potential for exceeding short

- term health thresholds, we refined our assessment by developing a better understanding of the geography of the facility relative to potential exposure locations.



### 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 r eference values. Cancer potency values are derived for chronic (lifetime) exposures. Noncancer reference values are generally derived for chronic exposures (up to a lifetime), bu t may also be derived for acute ( <24 hours), short

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

Although every effort is made to identify peer

- 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 includ ed in a quantitative risk estimate, an understatement of risk for these pollutants at environmental exposure levels is possible.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

45 Additionally, chronic dose

- response values for certain compounds included in the assessment may be under EPA IRIS review and r evised assessments may determine that these pollutants are more or less potent than currently thought. We will re

- evaluate risks if, as a result of these reviews, a dose

- response metric changes enough to indicate that the risk assessment may significantly mischaracterize human health risk

Cancer assessment

The discussion of dose

- response uncertainties in the estimation of cancer risk below focuses on the uncertainties associated with the specific approach currently used by the EPA to develop cancer poten cy factors. In general, these same uncertainties attend the development of cancer potency factors by CalEPA, the source of peer

- reviewed cancer potency factors used where EPA

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

we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [ 30 ] (herein referred to as Cancer Guidelines ). “The primary goal of EPA actions is protection of human health; accordingly, as an Agency policy, risk assessment procedures, includin g default options that are used in the absence of scientific data to the contrary, should be health protective.” The approach adopted in this document is consistent with this approach as described in the Cancer Guidelines

.
For cancer endpoints EPA usuall y 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 evaluat ed, EPA relies on both animal bioassay and epidemiological studies to characterize cancer risk. As a science policy approach, consistent with the Cancer Guidelines , EPA uses animal cancer bioassays as indicators of potential human health risk when other h uman cancer risk data are unavailable.

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

- reviewed methodo logies. 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 genera lly provide an upper bound estimate of risk. That is, EPA’s upper bound estimates represent a “plausible upper limit to the true value of a quantity” (although this is usually not a true statistical confidence limit). 40 In some circumstances, the true ri sk could be as low as zero; however, in other circumstances the risk could also be greater. 41 When developing an upper bound estimate of risk and to provide risk values that do not underestimate risk, EPA generally relies on conservative default approache s. 42 EPA also

40 IRIS glossary http://ofmpub.epa.gov/sor_internet/registry/termreg/s earchandretrieve/glossariesandkeywordlists/search.do?detai ls=&glossaryName=IRIS%20Glossary

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

42 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are generic approaches, based on general scientific knowledge and policy judgment, that are applied to variousResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

46 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 assessm ents have associated uncertainties, some which may be considered quantitatively, and others which generally are expressed qualitatively. Uncertainties may vary substantially among cancer risk assessments associated with exposures to different pollutants, since the assessments employ different databases with different strengths and limitations and the procedures employed may differ in how well they represent actual biological processes for the assessed substance. EPA’s Risk Characterization Handbook also r ecommends 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 descri bed more fully below.

(1) The qualitative similarities or differences between tumor responses observed in experimental animal bioassays and those which would occur in humans is a source of uncertainty in cancer risk assessment. In general, EPA does not assume that tumor sites observed in an experimental animal bioassay are necessarily predictive of the sites at which tumors would occur in humans. 43 However, unless scientific support is available to show otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target organ concordance. For a specific pollutant, qualitative differences in species responses can lead to either under

- estimation or over

- estimation of human cancer risks.

(2) Uncertainties regarding the most appro priate dose metric for an assessment can also lead to differences in risk predictions. For example, the measure of dose is commonly expressed in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, data may support developmen t of a pharmacokinetic model for the absorption, distribution, metabolism and excretion of an agent, which may result in improved dose metrics (e.g., average blood concentration of the pollutant or the quantity of agent metabolized in the body). Quantitat ive 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 estima tes may lead to either over or underestimation of risk.

ele ments of the risk

- assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessme nt 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 su bstance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An Examination of EPA Risk Assessment Principles and Practices, EPA/100/B

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

- final.pdf

43 Per the EPA Cancer Gui delines: “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 st udy results for humans.”Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

47 (3) For the quantitative extrapolation of cancer risk estimates from experimental animals to humans, EPA uses scaling methodologies (relating expected response to differences in physical size of the species), which introduce another source of uncertainty. These methodologies are based on both biological data on differences in rates of process according to species size and empirical comparisons of toxicity between experimental animals and humans. For a particular pollutant, the quantitative difference in cancer potency between experimental animals and humans may be either greater than or less than that estimated by baseline scientific scaling predictions due to uncertainties associated with limitation s in the test data and the correctness of scaled estimates.

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

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

- specific, biologically

- based risk models when feasible; however, such models are rarely available. The mode of action for a pollutant (i.e., the manner in which a pollutant causes c ancer) 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

- do se (straight line from POD) approach is used when available mode of action data support a linear (e.g., nonthreshold response) or as the most common default approach when a compound’s mode of action is unknown. Linear extrapolation can be supported by bot h pollutant

- specific data and broader scientific considerations. For example, EPA’s Cancer Guidelines generally consider a linear dose

- response to be appropriate for pollutants that interact with DNA and induce mutations. Pollutants whose effects are add itive to background biological processes in cancer development can also be predicted to have low

- dose linear responses, although the slope of this relationship may not be the same as the slope estimated by the straight line approach.

EPA most frequently utilizes a linear low

- dose extrapolation approach as a baseline science

policy choice (a “default”) when available data do not allow a compound

- specific determination. This approach is designed to not underestimate risk in the face of uncertainty and var iability. 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 u ncertainty is theResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

48 characterization of low

- dose nonlinear, non

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

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

- shaped dose

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

processes.

As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight line approach from the BMDL. This is equivalent to using an upper confidence limit on the slope of the straight line extrapolation. T he impact of the choice of the BMDL on bottom line risk estimates can be quantified by comparing risk estimates using the BMDL value to central estimate BMD values, although these differences are generally not a large contributor to uncertainty in risk ass essment (Subramaniam et. al., 2006) [ 33 ]. It is important to note that earlier EPA assessments, including the majority of those for which risk values exist today, were generally developed using the multistage model to extrapolate down to environmental dose levels and did not involve the use of a POD. Subramaniam et. al. (2006) also provide comparisons indicating that slopes based on straight line extrapolation from a POD do not show large differences from those based on the upper confidence limit of the mu ltistage model.

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

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

- specific data to evaluate this variability are generally not available. There may also be important life stage differences in the quantit ative potency of carcinogens and, with the exception of the recommendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic mode of action, risk assessments do not generally quantitatively address life stage differences. However, on e approach used commonly in EPA assessments that may help address variability in response is to extrapolate human response from results observed in the most sensitive species and sex tested, resulting typically in the highest URE which can be supported by reliable data, thus supporting estimates that are designed not to underestimate risk in the face of uncertainty and variability.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

49 Chronic noncancer assessment

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

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

– ATSDR) utilize an approach that is intended not to underestimate risk in the face of uncertainty and variability. When there are gaps in the available information, uncertainty factors (UFs) are applied to derive reference values that are intended to be protective against appreciable risk of deleterious effects . Uncertainty factors are commonly default values 44 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 f actors 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 p ollutants 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 p rovide an estimate (with uncertainty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or of a continuous inhalation exposure (RfC) to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. 45 To derive values that are intended to be “without appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach [ 34 ], [ 35 ] which includes consideration of both uncertainty and variability.

EPA begins by evaluating all of the available peer

- reviewed literature to determine non

cancer endpoints of concern, evaluating the quality, strengths and limitations of the available studies. EPA typically chooses the relevant endpoint that occurs at t he lowest dose, often using statistical modeling of the available data, and then determines the appropriate point of departure (POD) for derivation of the reference value. A POD is determined by (in order of preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of the dose or concentration at which the toxic response was not significantly elevated (no observed adverse effect level

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

44 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are generic approaches, based on general scientific knowledge and policy judgment, that are applied to various elements of the ri sk

- assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate ri sk). See EPA 2004 An examination of EPA Risk Assessment Principles and Practices, EPA/100/B

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

- final.pdf

45 See IRIS glossaryResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

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

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

- than

- lifetime exposure (i.e., extrapolating from subchronic to chronic exposure); (4) uncertainty in extrapolating from a LOAEL in the a bsence 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 select ed for the individual UFs. For each type of uncertainty (when relevant to the assessment) , EPA typically applies an UF value of 10 or 3 with the cumulative UF value leading to a downward adjustment of 10

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

- fold factor. If an extrapolation step or adjustment is not relevant to an assessment (e.g., if applying human toxicity data and an interspecies extrapolation is not required) the associated UF is not used. Th e 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 popu lation, 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 uncertain ty 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 sig nificant 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, BMD L) 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 extrapolation s. 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 relativ e 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 p harmacokinetic processing and associated uncertainties; however, such dosimetric adjustments are not alwaysResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

51 possible. Information may not be available to quantitatively assess toxicokinetic or toxicodynamic differences between animals and humans, and in m any cases a 10

- fold UF (with separate factors of 3 for toxicokinetic and toxicodynamic components) is used to account for expected species differences and associated uncertainty in extrapolating from laboratory animals to humans in the derivation of a refe rence value. If information on one or the other of these components is available and accounted for in the cross

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

3) In the case of reference values for chronic exposures where only data from shorter durations are available (e.g., 90

- day subchronic studies in rodents) or when such data are judged more appropriate for development of an RfC, an additional UF of 3 or 10

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

4) Toxicity data are typically limited as to the dose or exposure levels that have been tested in individual studies; in an animal study, for example, treatment groups may differ in exposure by up to an order of magni tude. The preferred approach to arrive at a POD is to use BMD analysis; however, this approach requires adequate quantitative results for a meaningful analysis, which is not always possible. Use of a NOAEL is the next preferred approach after BMD analysi s 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

- fol d is often applied.

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

- fold is typically applied.

There is no RfD or other comparable chronic health benchmark value for lead compounds. Thus, to address multipathway human health and environmental risks associated with emissions of lead f

rom this facility, ambient lead concentrations were compared to the NAAQS for lead. In developing the NAAQS for lead, EPA considered human health evidence reporting adverse health effects associated with lead exposure, as well as an EPA conducted multipat hway risk assessment that applied models to estimate human exposures to air

- related lead and the associated risk (73FR at 66979). EPA also explicitly considered the uncertainties associated with both the human health evidence and the exposure and risk

ana lyses when developing the NAAQS for lead. For example, EPA considered uncertainties in the relationship between ambient air lead and blood lead levels (73FR at 66974), as well as uncertainties between blood lead levels and loss of IQ points in children (7 3FR at 66981). In considering the evidence and risk analyses and their associated uncertainties, the EPA Administrator noted his view that there is no evidence

- or risk

- based bright line that indicates a single appropriate level. Instead, he noted, there is a collection of scientific evidence and judgments and other information, including information about the uncertainties inherent in many relevant factors, which needs to be considered together in making this public health policy judgment and in selecting a standard level from a range of reasonable values (73FR at 66998). In so doing, the Administrator decided that, a level for the primary lead standard ofResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

52 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 sensi tive groups, with an adequate margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and exposure analyses, and their associated uncertainties can be found in EPA’s final rule revising the lead NAAQS (73 FR 66970

- 66981, Novem ber 12, 2008).

We also note the uncertainties associated with the health

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

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

- making by the Office of Air Quality Planning and Standards (OAQPS) and by the Office of Drinking Water (ODW). By comparison to most other environmental toxicants, the degree of uncertainty about the health effects o f lead is quite low. It appears that some of these effects, particularly changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral development, may occur at blood lead levels so low as to be essentially without a threshold

. The Agency's RfD Work Group discussed inorganic lead (and lead compounds) at two meetings (07/08/1985 and 07/22/1985) and considered it inappropriate to develop an RfD for inorganic lead.” EPA’s IRIS assessment for Lead and compounds (inorganic) (CASRN 7439

- 92

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

.

We note further that because of the multi

- pathway, multi

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

related multi

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

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

- based framework and less weight on the results from the risk assessment, although he did find the risk estimates to be roughly consistent w ith and generally supportive of the evidence

- based framework applied in the NAAQS determination (73FR at 67004). Thus, when revising the NAAQS for lead to protect public health with an adequate margin of safety, EPA considered both the evidence

- based frame work and the risk assessment, albeit to different extents.

Acute noncancer assessment

Many of the UFs used to account for variability and uncertainty in the development of acute reference values are quite similar to those developed for chronic durations, but more often using individual UF values that may be less than 10. UFs are applied based on 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 paragraph). The UFs applied in acute reference value derivation include: 1) heterogeneity among humans; 2) uncertainty inResidual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

53 extrapolating from animals to humans; 3) uncert ainty in LOAEL to NOAEL adjustments; and 4) uncertainty in accounting for an incomplete database on toxic effects of potential concern. Additional adjustments are often applied to account for uncertainty in extrapolation from observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an acute reference value at another exposure duration (e.g., 1 hour).

Not all acute reference values are developed for the same purpose and care must be taken when interpreting the results of an acute assessment of human health effects relative to the reference value or values being exceeded. W here relevant to the estimated exposures, the lack of threshold values at different levels of severity should be factored into the risk characterizatio n as potential uncertainties.Residual Risk Assessment for the Ferroalloys Source Category

in Support of the 2015 Final Rule

54 

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