Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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## Revised Draft Residual Risk As sessment for the Primary Aluminum Reduction Plants Source Category

by EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation September 2014Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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### Table of Contents

1 Introduction

................................ ................................ ................................ ......................... 5 2 Methods

................................ ................................ ................................ ............................... 5 2.1 Emissions and source data

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

................................ ............ 6 2.3 Estimating chronic human inhalation exposure

................................ ........................... 9 2.4 Screening for potential acute impacts of concern

................................ ........................ 9 2.5 Multipathway human health and environmental risk screening

................................ . 12 2.6 Dose

- response assessment

................................ ................................ .......................... 17 2.6.1 Sources of chronic dose

- response information

................................ ................... 17 2.6.2 Sources of acute dose

- response information

................................ ....................... 25 2.7 Risk characterization

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

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

................................ ................................ ................................ .................. 30 2.7.3 Facility

- wide risks

................................ ................................ ................................ ... 31 2.7.4 MACT

- Allowable Risks

................................ ................................ ......................... 31 3 Risk results for the Primary Aluminum Reduction source category

............................ 31 3.1 Source category emissions and results

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

................................ ................................ ..................... 35 4 General discussion of uncertainties and how they have been addressed

.......................... 41 4.1 Exposure modeling uncertainties

................................ ................................ ............... 41 4.2 Uncertainties in the dose

- response relationships

................................ ....................... 42 5 References

................................ ................................ ................................ ......................... 50Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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Index of Tables

Table 2.2

- 1 AERMOD version 13350 model options for RTR modeling

................................ . 7 Table 2.6

- 1 (a) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

..... 21 Table 2.6

- 1 (b) Dose

- Response Values for Chronic Oral Exposure to Carcinogens

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

- 1 (c) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

................................ ................................ ................................ ................................ ................... 24 Table 2.6

- 1 (d) Dose

- Response Values for Chronic Oral Exposure to Noncarcinogens

......... 25 Table 2.6

- 3 Dose

- Response Values for Acute Exposure

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

- 1 Summary of Emissions from the Primary Aluminum Reduction Source Category Used in the Residual Risk Assessment Availability of Dose

- Response Values

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

- 1 Summary of Source Category Level Inhalation Risks for Primary Aluminum Reduction Sources

................................ ................................ ................................ .................... 36 Table 3.2

- 2 Summary of the “Tier 1 and Tier 2” Multipathway Screening Analysis for the Primary Aluminum Reduction Source Category

................................ ................................ ...... 39 Table 3.2

- 3 Summary of Environmental Risk Screen Results for the Primary Aluminum Reduction Source Category

................................ ................................ ................................ ...... 40

Appendices

Appendix 1 Draft Development of the Risk and Technology Review (RTR) Emissions

Dataset for the Primary Aluminum Red uction Source Category Appendi x 2 Technical Support Document for HEM

- 3 Modeling Appendix 3 Meteorological Data for HEM

- 3 Modeling Appendix 4 Analysis of data on short

- term emission rates relative to long

- term emission

rates Appendix 5 Technical Support Document for TRIM

- Based Multipath way Screening

Scenario for RTR: Summary of Approach and Evaluation Appendix 6 Draft Detailed Risk Modeling Results Appendix 7 Dispersion Model Receptor Revisions and Additions Appendix 8 Draft Detailed Acute Risk Modeling Results Appendix 9 Techn ical Support Document: Human Health Multipathway Residual Risk

Screening Assessment for the P rimary Aluminum Reduction Source CategoryDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model AEGL A cute exposure guideline level ASTDR US Agency for Toxic Substances and Disease Registry BDL Below Detection Limit CalEPA California Environmental Agency CTE Central Tendency Estimate ERPG Emergency Response Planning Guideline HAP Hazardou s Air Pollutant HEM Human Exposure Model HI Hazard index HQ Hazard quotient IR Information Request IRIS Integrated Risk Information System MACT Maximum Achievable Control Technology MIR Maximum Individual Risk MOA Mode of action N AC National Advisory Committee NAAQS National Ambient Air Quality Standards NATA National Air Toxics Assessment NEI National Emissions Inventory NPRM Notice of Proposed Rulemaking PB

- HAP Persistent and Bioaccumulative

- HAP POM Polycyclic organic matt er REL Reference exposure level RfC Reference concentration RfD Reference dose RME Reasonable Maximum Exposure RTR Risk and Technology TOSHI Target

- organ

- specific hazard index URE Unit risk estimateDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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### 1 Introduction

S ection 112 of the Clean Air Act (CA A) establishes a two

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

- b ased 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 secti on 112(f)(2) to assess the health and environmental risks that remain after implementation of the MACT standards. If additional risk reductions are necessary to protect public health with an ample margin of safety or to prevent an adverse environmental ef fect, EPA must develop standards to address these remaining risks. This second stage of the regulatory process is known as the residual risk stage. For each source category for which EPA issued MACT standards, the residual risk stage must be completed wi thin eight years of promulgation of the initial technology

- based standard.

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

, ” and in June of 2007, we receive d a letter with the results of that consultation. Subsequent to the consultation, in June of 2009

, a meeting was held with an SAB panel for a formal peer review of the “Risk and Technology Review (RTR) Assessment Methodologies” [ 2 ]. We received the final SAB report on this review in May of 2010 [ 3 ]. Where appropriate, we have responded to the key messages from this review in developing our current risk assessment s and we will be continuing our efforts to improve our assessments by incorporating updates b ased on the SAB recommendations as they are developed and become available . Our responses to the key recommendations of the SAB are outlined in a memo entitled, “EPA’s Actions in Response to Key Recommendations of the SAB Review of RTR 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) performed for the p rimary a luminum r eduction p lants source category. The methods discussion includes de scriptions of the methods used to develop refined estimates of chronic inhalation exposures and human health risks for cancer and noncancer endpoints , as well as descriptions of the methods used to screen for acute health risks , chronic non

- inhalation heal th risks, and adverse environmental effects.



### 2 Methods

2.1 Emissions and source data In an effort to gather information on emissions from the p rimary a luminum r eduction p lants source category, a section 114 information request (IR) was sent by the EPA to ten th en

operating primary aluminum reduction plants in March 2013

. The IR requested available information regarding process equipment, control devices, point and fugitive emissions,Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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practices used to control fugitive emissions, and other aspects of facility op erations, including stack parameters and locations

. Additionally, all ten of those facilities provided emissions tests for certain HAP from specific processes that were considered representative of the industry. Pollutants tested included POM’s, arseni c, lead, nickel, chromium (VI), and dioxins/furans.

. T he data from th ese tests were used to develop speciation profiles and emission factors for HAP metals and HAP organics. These IR data were also used to develop a model

- ready emissions dataset for th is source category

. W e performed an engineering review of the information to identify readily apparent limitations and issues with the emissions data

. Details on the development of the emissions and source data for this source category can be found in th e emissions memo , Draft Development of the Risk and Technology Review (RTR) Emissions Dataset for the Primary Aluminum Reduction Source Category

, available in the docket ( Docket No. EPA

- HQ

- OAR

- 2011

- 0797)

, and as Appendix 1 to this risk assessment document. Section 3 of this risk assessment document provides a brief summary of the emissions.



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

- and short

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

- 3)

. The approach used in applying this modeling system is outline d below, and further details are provided in Appendix 2

. The HEM

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

The dispersion model in the HEM

- 3 system , AERMOD version 1 3350

, 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 AERMOD can be found in the AERMOD Users Guide [ 6 ]. The model is used to develop annual average amb ient concentrations through the simulation of hour

- by

- hour dispersion from the emission sources into the surrounding atmosphere. Hourly emission rates used for this simulation are generated by evenly dividing the total annual emission rate from the invent ory into the 8,760 hours of the year.

The first step in the application of the HEM

- 3 modeling system is to predict ambient concentrations at locations of interest. The AERMOD model options employed are summarized in Table 2.2

- 1 and are discussed further below.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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Table 2.2

- 1 AERMOD version 1 3350 mo del options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point and area sources
Receptor orientation Polar (13 rings and 16 radials) Discrete (census block centroids) and user supplied receptors

Terrain characterization Actual from USGS 1

- degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Inclu ded

Urban source option Included if source in urbanized area

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

In HEM

- 3 , meteorological data are ordinarily selected from over 800 National Weather Service (NWS) surface observat ion stations across the continental United States, Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is selected as representative of the conditions at the subject facility. Ideally, when considering off

- site meteorological data most sit e 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 me teorological data, we modeled only a single year, typically 2011 . While the selection of a single year may result in under

- prediction of long

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

- prediction at others. For each facility id entified by its characteristic latitude and longitude coordinates, the closest meteorological station was used in the dispersion modeling. Appendix 3 ( Meteorological Data Processing Using AERMET for HEM

- 3 ) provides a complete listing of stations and as sumptions along with further details used in processing the data through AERMET (the AERMOD meteorological data pre

- processing program)

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

Beginning with version 12345, AERMET allows for a minimum wind speed of 0.5 m/s to be utilized when processing monitoring stations that are equipped with sonic anemometers and for an adjustment to the surface velocity (u*). The public version of AERMET available at the time we conducted the modeling for this source category did not include the surface 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 an d incorporated the updated surface friction velocity adjustment in the output. It was EPA’s judgment that theDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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pre

- public release version of AERMET would generate AERMOD

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

EPA has posted the AERMET meteorological data used in the primary aluminum analysis on the EPA’s FERA (Fate, Exposure, and Risk Analysis) website 1 under the HEM model page. AERMET and AERMOD (version 13350) were released to the public in late D ecember 2013 on the EPA’s Support Center for Regulatory Atmospheric Modeling (SCRAM) website. 2

The HEM

- 3 system estimates ambient concentrations at the geographic centroids of census blocks (using the 201 0 Census) and at other receptor locations that can be specified by the

user. See Appendix 7 to this document ( Dispersion Model Receptor Revisions and Additions for the Primary Aluminum 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 censu s blocks with at least one resident (i.e., locations where people may reasonably be assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient concentrations were calculated as the annual average of all estimated short

- term (one

- hour) concentrations at each block centroid. Possible future residential use of currently uninhabited areas was not considered. Census blocks, the finest resolution available in the census data, are typically comprised of approximately 40 peopl e or about ten households.

In contrast to the development of ambient concentrations for evaluating long

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

- case short

- term (one

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

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

- term emission rates were needed to screen for the potential for hazard via acute exposures, and since the ICR data contains only annual emission totals, we generally apply the assumption
t hat the maximum one

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

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

- Acute Risk Screening and Refined Asse ssments

.

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 resolution of about 10 meters. Elevations of polar grid points used in estima ting short

- and long

- term ambient concentrations were assumed to be equal to the highest elevation of any census block falling within the polar grid sector corresponding to the grid point. If a sector does not contain any blocks, the model defaults the el evation to that of the nearest block. If an elevation is not provided for the emission source, the model uses the average elevation of

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

assessment

- and

- modeling

- human

- expos ure

- model

- hem

.

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

.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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all sectors within the innermost model ring. AERMOD adjusts the plume’s flow if nearby elevated hills are expected to i nfluence 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 an nual 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 sho rt

- 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 NATA assessments (which modeled daily activity u sing 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 HAPs; it will also reduce risk estimates for gaseous HAPs, 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 reduc ing 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 (note that the MIR can be estimated for each source as well as for the entire source category) ; the population risk distribution; and the cancer incidence. The assumpt ion of not considering short or long

- term population mobility does not bias the estimate of the 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 distribut ion of individual risks across the affected population, shifting it toward higher estimated individual risks at the upper end and reducing the number of people estimated to be at lower risks, thereby increasing the estimated number of people at specific ri sk levels.



### 2.4 Screening for potential acute impacts of concern In establishing a scientifically defensible approach for the assessment of potential health risks due to acute exposures to HAP, we f ollowed the same general approach that has been used for dev eloping chronic health risk assessments for other rules under the residual risk program. That is, we developed a tiered, iterative approach. This approach to risk assessment was endorsed by the National Academy of Sciences in its 1993 publication “Scienc e and Judgment in Risk Assessment” and subsequently was adopted in the EPA’s “Residual Risk Report to Congress” in 1999.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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The assessment methodology is designed to eliminate from further consideration those facilities for which we have confidence that no acute adverse health effects of concern will occur. To do so, we use what is called a tiered, iterative approach to the asse ssment. This means that we bega n with a screening assessment, which relies on readily available data and uses conservative assump tions 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 assessme nt. A more refined acute assessment could u s e industry

- or site

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

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

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

Acute health risk screenin g 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 using available data . In some cases, this may include the use of a facility

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

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

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

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

- hour emission rate from any source is ten times the average annual hourly emission rate for that source. (The average hourly emissions rate is defined as the total emissions for a year divided by the total numbe r 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 consulta tion on our RTR Assessment Plan, we performed an analysis using a short

- term emissions data set from a number of source s located in Texas (originally reported on by 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, Galveston, Chambers, and Brazoria Counties ) over an eleven

- month time period in 2001 . We obtained the dataset a nd performed our own analysis, focusing on sources which reported emitting high quantities of HAP over short periods of time (see Appendix 4 of this document, Analysis of data on short

- term emission rates relative to long

- term emission rates ). Most peak e mission 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 initialDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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screening. This 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 da ta 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

- t erm 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 p rimary aluminum source category, however, we did not use the default multiplier of 10 fo r all emission points. See Appendix 1 to this document, Revised Development of the Risk and Technology Review (RTR) Emissions Dataset for the Primary Aluminum Source Category , for the detailed description of how the hourly multipliers were developed for t he primary aluminum source category. In general, based on ICR data and engineering knowledge of the category, we note that fugitive emissions from the potline roof vents are not subject to significant hourly fluctuations in emissions over the year so were assigned an acute multiplier of 1.5 (i.e., maximum hourly emissions equal annual average hourly emissions). Other processes do have emissions cycles, or peak emissions (e.g., anode bake furnaces) and these processes received factor s of 2 (i.e., maximum h ourly emissions were estimated to be 2 times greater than annual average hourly emissions).

As mentioned above, when we identify acute impacts which exceed their relevant benchmarks, we pursue refining our acute screening estimates to the extent pos sible. For the
p rimary aluminum source category, we conducted a review of the layout of the polar receptors around the facilities compared to the facility boundaries to determine the maximum off

- site acute impact for the facilities that did not screen out during the initial run. We also examined the locations and concentrations at residential receptors, the temporal variability in exposure concentrations, and a range of dose

- response values. Appendix 6 to this document ( Draft Detailed Risk Modeling Resu lts ) contains the initial results for the source category, while Appendix 8 to this document ( Acute Impacts Refined Analysis ) contains the refined acute results

. In summary, we used conservative assumptions for emission rates, meteorology, and exposure lo cation, and refined data where available. We used the following assumptions in our acute assessment approach:

 Peak 1

- hour emissions were obtained from the emissions memo and based on the operating characteristics of specific emission sources varying from 1.5 to 2 times the average 1

- hour emission rates , as described in Appendix 1

.

 For facilities with multiple emission points, peak 1

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

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

 For facilities with multiple emission points emitting the same pollutant , 1

- hour concentrations at each receptor were assumed to be the sum of the maximum concentrations due to each emission point, regardless of whethe r those maximum concentrations occurred during the same hour.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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 Worst

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

- scale dispersion model, AERMOD, is us ed for simulating atmospheric dispersion.

 A person was assumed to be located downwind at the point of maximum modeled impact during this same worst

- case 1

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

 The maximum impact was compared to multiple short

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



### 2.5 Multipathway human health and environmental risk screening

Multipathway Human Health Screening

The potential for significant human health risks due to exposures via routes other than inhalation (i.e., multipathway exposures) was screened by first determining whether any sources emitted any hazardous air pollutants known to be pers istent and bioaccumulative in the environment (PB

- HAP) 3 . 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 dib enzodioxins and furans, DDE, heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury compounds, methoxychlor, polychlorinated biphenyls (PCB) , polycyclic organic matter (POM) , toxaphene, and triflurali n. Emissions of cadmium compound s, chlorinated dibenzodioxins and furans, lead compounds, mercury compounds and POM (of which PAH are a subset) were identified in the emissions inventory for the p rimary aluminum source category.

With respect to PB

- HAP emissions other than lead, emissi ons were evaluated for potential

non

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

- reviewed Total Risk Integrated Methodology

– Fate, Transport, and Ecological Exposure (TRIM.FaTE 4 ) model. With this app roach, we 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 health risks under reasonable worst

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

- HAP using a hypothetical
upper

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

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

3 Although the two

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

- HAP refers to the many air pollutants known to be persis tent 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).

4 EPA’s Total Risk Integrated Methodology (Gener al Information) http://www2.epa.gov/fera/total

- risk

integrated

- methodology

- trim

- generalDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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for each of the PB

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

non

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

- HAP (other than lead) at which the maximum human health risk would be 1 in a million for lifetime cancer risk or a hazard quotient of 1.0 for noncancer impacts. We call this application of the TRIM.FaTE model the Tier 1 Screen. Se e Appendix 5 of this document

, ( Technical Support Document for TRIM

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

- level emission rates developed for screening potentially significant multipathway impacts.

If the PB

- HAP emissions for a facility exceed the Tier screening emission ra te, we conduct a Tier 2 multipathway screen. In the Tier 2 screen, the location of each facility that exceeded the Tier 1 emission level is used to refine some of the assumptions associated with the environmental scenario while maintaining the exposure sc enario assumptions. We then adjust the risk

- based Tier 1 screening level for each PB

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

- specific emission level for each PB

- HAP ( i.e., the level for cadmium could be different for every facility), un like the Tier 1 emission level which was constant for the same PB

- HAP at different facilities (i.e., the level for cadmium was the same for every facil ity).

The subsistence fisher scenario assumes a high

- end fish consumption rate of 373 grams/day

. 5 Also

, the assessment uses the assumption that the biological productivity limitation of each lake is 1 gram of fish per acre of water Thus, in order to fulfill the adult ingestion rate, we may need to model more than one lake , refer to Appendix 5 of this docum ent ( Technical Support Document for TRIM

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

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

- HAP group, and “fish” up to the lake’s biological productivity. We then systematically proceed to other lakes based on concentration, until the 3 73 g/day limit is met. A maximum travel radius of 50 km relative to the facility is used to maintain a realistic scenario. The final Tier 2 screening result for the fisher can be expressed as the sum of the risk from each lake that is fished (which is bas ed 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 ingestion rate (i.e., to reach the 373 g/d). If there are not 373 acres of lake, the risk reflects a reduced ingestion rate based on the lake acreage. The farmer scenario (same approach for all Tiers) involves an individual living for a 70

- year lifetime on a farm homestead in the vicinity of the source and

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

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consuming produce grown on, and meat and animal products raised on, the farm. The ingesti on 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. [ 9 ]

Facility emissions of PB

- HAP that do not exceed these new Tier 2 screening levels are consi dered to pose no significant risks. When facilities exceed the Tier 2 screening levels, it does not mean that multipathway impacts are significant, only that we cannot rule out that possibility based on the results of the screen. Se e Appendix 5 of this d ocument ( Technical Support Document for TRIM

- Based Multipathway Screening Scenario for RTR: Summary of Approach and Evaluation ) for a complete discussion of the Tier 2 screen.

If the PB

- HAP emissions for a facility exceed the Tier 2 screening emission s rate, and data are available, we may decide to conduct a more refined multipathway assessment. This next iteration of assessment could be an extensive refined assessment that replaces as many of the assumptions made in the Tier 2 screen with site

- specif ic data as possible or it could be focused on a few parameters such as adequacy of the lake, and/or the effective plume height

. We refer to the latter as the Tier 3 screen . In the Tier 3 screen, the lakes included in the screen are scrutinized for access ibility (i.e., private or public) and appropriateness (i.e., fishable lake v. industrial waste pond). In addition, a Tier 3 screen may include an examination of the site

- specific meteorological mixing height relative to the effective plume rise. As with the Tier 2 screen, the Tier 3 step creates a facility

- specific emission rate level for each PB

- HAP (i.e., the level for cadmium could be different for every facility). Also as with the Tier 2 screen, if facilities exceed the Tier 3 screening levels, it do es not mean that multipathway impacts are significant, only that we cannot rule out that possibility based on the results of the screen. See Appendix 5 of this document ( Technical Support Document for TRIM

- Based Multipathway Screening Scenario for RTR: S ummary of Approach and Evaluation ) for a complete discussion of the Tier 3 screen. For the primary aluminum source category we did conduct a Tier 3 assessment for the facility with the highest Tier 2 excess

cancer results.

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

The NAAQS value, a public health policy judgment, incorporated the Agency’s most recent health evaluation of air effects of lead exposure for the purposes of setting a natio nal 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 mu ltipathway 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, comb ined with: 2) the site

- specific dispersionDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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

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

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

We further note that comparing ambient lead concentrations to the NAAQS for lead, considering the level, averaging time, form and indicator, also informs whether there is the potential for adverse environmental effects. This is because the p rimary 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 t he potential for adverse environmental effects.

Environmental Risk Screening

The EPA has developed a screening approach to examine the potential for adverse environmental effects as required under section 112(f)(2)(A) of the CAA. The environmental

scre en 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 terre strial plants.

For the environmental risk screening analysis, EPA first determined whether any facilities in the source category emitted any of the seven environmental HAP. If one or more of the seven environmental HAP evaluated are emitted by at least o ne 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 levels . If off

- site emissions from a facility do not exceed the Tier 1 levels the facility “passes” the screen, and therefore, is not evaluated further under the screeningDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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approach. If off

- site emissions from a facility exceed the Tier 1 levels , we evaluate the facility further in Tier 2

.

In Tier 2 of the environ mental screening analysis, the screening emission levels are adjusted to account for local meteorology and the actual location of lakes in the vicinity of facilities that did not pass the Tier 1 screen. If off

- site emissions from a facility do not exceed the Tier 2 levels , the facility passes the screen, and is typically not evaluated further. If off

- site emissions from a facility exceed the Tier 2 levels , the facility does not pass the screen, and, therefore, may have the potential to cause adverse envir onmental effects. Such facilities are evaluated further to investigate factors such as the magnitude and characteristics of the area of exceedance.

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

- tier screen that compares the average off

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

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

- AERM OD 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 A mbient 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, c rops, 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.” 6

6 A secondary standard, as defined in Section 109(b)(2), must “specify a level of air quality the attainment and maintenance of which, in the judgment of the Administrator, based on crit eria, 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 limit ed 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 comfor t and well

- being.”Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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### 2.6 Dose

- r espon se 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 p rimary

a luminum r educ tion p lant source category were based on the EPA Office of Air Quality Planning and Standards’ (OAQPS) existing recommendations for HAP [ 10 ], which were also used for NATA [ 11 ]. This information has been obtained from various sources and prioritized accor ding to (1) conceptual consistency with EPA risk assessment guidelines and (2) level of peer review received. The prioritization process was aimed at incorporating into our assessments the best available science with respect to dose

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

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

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

cancer. The RfC is defined as an “ estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. ” Similarly, the RfD is “a n estimate (with uncertainty spanning perhaps an order of magnitude) of a daily oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. ” The URE is defined as “ the upper

- bound excess cancer risk estimated to result from continuous lifetime exposure to an age nt 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 populat ion) 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) [ 12 ] is an EPA database that contains scientific health assessment informatio n, including dose

- response information. All IRIS assessments since 1996 have also undergone independent external peer review. The current IRIS process includes review by EPA scientists, interagency reviewers from other federal agencies, and the public, an d 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 for detailed information on status and scheduling of cur rent individual IRIS assessments and updates ( http://cfpub.epa.gov/ncea/iristrac/index.cfm )

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

- dose extra polation 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 review ed) in our risk assessments. At this time, however, there are no available carcinogen dose

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

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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) [ 13 ] for inhalation and oral exposure to many toxic substances. As stated on the ATSDR web site: “ Following discussions with scientists within the Departme nt 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 .” Th e MRL is defined as “an estimate of daily human exposure to a substance that is likely to be without an appreciable risk of adverse effects (other than cancer) over a specified duration of exposure.” ATSDR describes MRLs as substance

- specific estimates to be used by health assessors to select environmental contaminants for further evaluation. Exposures above an MRL do not necessarily represent a threat, and MRLs are therefore not intended for use as predictors of adverse health effects or for setting clea nup 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 7 : “The guidelines for developing chronic inhalation exposure levels incorporate many recommendations of the U.S. EPA [ 14 ] and NAS [ 15 ].” The non

- cancer information includes available inhalation health risk guidance values expressed as chronic inhalation refer ence exposure levels (RELs) [ 16 ]. 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
exp osure is expressed in terms of the URE [ 17 ], defined similarly to EPA's URE.

As mentioned above, in order to characterize non

- cancer chronic effects, and in response to key recommendations from the SAB, the EPA selects dose

- response values that reflect the best available science for all HAP included in RTR risk assessments 8 . More specifically, for a given HAP, EPA examines the availability of inhalation reference values from the sources included in our tiered approach (e.g., IRIS first, ATSDR second, Ca l EPA third) and determines which inhalation reference value represents the best available science. Thus, as new inhalation reference values become available, EPA will typically evaluate them and determine whether they should be given preference over those currently being used in RTR risk assessments. In developing chronic risk estimates, we adjusted dose

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

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

- Technical Support Document For the Determination of Non

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

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

- SAB

- 1 0

- 007

- unsigned.pdf

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1) There is an existing IRIS RfC for manganese (Mn) published in 1993 9 . This va lue was in the RTR risk assessment supporting the 2011 Ferroalloys Notice of Proposed Rulemaking. However, since the 2011 proposal ATSDR has published an assessment of Mn toxicity (2012) which includes a chronic inhalation reference value (i.e., an ATSDR Minimal Risk Level or MRL) 10 . Both the 1993 IRIS RfC and the 2012 ATSDR MRL were based on the same study (Roels et al., 1993). In developing their assessment, ATSDR used updated dose

- response modeling methodology (benchmark dose approach) and considered r ecent pharmacokinetic findings to support their MRL derivation. In the interest of using the best available science, the EPA has chosen to rely on the ATSDR MRL for Mn in the current secondary aluminum proposal.

2) In the case of nickel compounds, to provi de a health

- protective estimate of potential cancer risks, we used the IRIS URE value for nickel subsulfide in th is risk assessment. Based on past scientific and technical considerations, the determination of the percent of nickel subsulfide was considere d a major factor for estimating the extent and magnitude of the risks of cancer due to nickel

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

- emitting sources (including oil combustion, coal combustion, and others) sugge sted that at least 35 percent of total nickel emissions may be soluble compounds and that the URE for the mixture of inhaled nickel compounds (based on nickel subsulfide, and representative of pure insoluble crystalline nickel) could be derived to reflect the assumption that 65 percent of the total mass of nickel may be carcinogenic.

Based on consistent views of major scientific bodies (i.e., National Toxicology Program (NTP) in their 12 th Report of the Carcinogens (ROC) 11 , International Agency for Resear ch on Cancer (IARC) 12 , and other international agencies) 13 that consider all nickel compounds to be carcinogenic, we currently consider all nickel compounds to have the potential of being carcinogenic to humans. The 12th Report of the Carcinogens states tha t the “combined results of epidemiological studies, mechanistic studies, and carcinogenic studies in rodents support the concept that nickel compounds generate nickel ions in target cells at sites critical for carcinogenesis, thus allowing consideration an d evaluation of these compounds as a single group.” Although the precise nickel compound (or compounds) responsible for the carcinogenic effects in humans is not always clear, studies indicate that nickel sulfate and the combinations of nickel sulfides an d oxides encountered in the nickel refining industries cause cancer in humans (these studies are summarized in a

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

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

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

12 Inte rnational 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.

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

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review by Grimsrud et al., 2010 14 ). The major scientific bodies mentioned above have also recognized that there are differences in toxicity and /or carcinogenic potential across the different nickel compounds.

Therefore, i n the inhalation risk assessment for this supplemental proposal, to take a conservative approach, we considered all nickel compounds to be as carcinogenic as nickel subsulfide and applied the IRIS URE for nickel subsulfide without a factor to reflect the assumption that 100 percent of the total mass of nickel may be as carcinogenic as pure nickel subsulfide. However, given that there are two additional URE values 15 derived for exposure to mixtures of nickel compounds, as a group, that are 2

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

.
3) Where possible for emissions of unspecified mixtures of HAP categories such as metal compounds and POM

, we apply category

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

- response value for the category.

4) Where POM emissions were not speciated into individual compounds, we applied the same sim plifying a ssumptions to assessments that are used in NATA [ 18 ]. The NATA approach partitions POM into eight different non

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

The emissions in ventory for the p rimary aluminum source category includes emissions of HAP with availa b le ch r onic quantitative inhalation dose

- response values. Of these, 2 3 are classified as known, probably, or possible carcinogens, with quantitative cancer dose

- respons e values available. These 2 3 HAP, their quantitative inhalation chronic cancer dose

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

- 1 ( a )

. The dioxin and POM compounds with chronic oral cancer dose

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

- 1 ( b )

. Sixteen HAP have quantitative inhalation chronic noncancer threshold values available; t wo of these sixteen HAP (cadmium and mercury), for which a multipathway screen was performed, also have quantitative oral chronic noncancer threshold values available. These two HAP, their threshold values, and the source of the value are listed in Table 2.6

- 2 ( a ) and Table 2.6

- 2 ( b )

.

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

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

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

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

. 15 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 ).Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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Table 2.6

- 1 (a) Dose

- Response Values for Chroni c Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 16 = cancer risk per μg/m 3 of a verage lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Health Hazard Assessm e nt, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standard s. EPA ORD = EPA Office of Research and Development Pollutant CAS Number 17 URE 5 (1/μg/m 3 ) Source

Dioxins/Furans 18 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 1,2,3,4,6,7,8

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

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

- Hexachlorodibenzo

- p

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

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

- Hexachlorodibenzo

- p

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

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

- Hexachlorodibenzo

- p

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

- 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

16 The URE is the upper

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

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

- digi t identifier corresponding to the group’s position on the CAA list of HAPs.

18 Dioxins/Furans URE based on 2005 WHO evaluation of TEF ( http://www.who.int/foodsafety/chem/tef_update/en/ ); URE =Group URE x TEF; RfC = 2,3,7,8

- TCDD RfC/TEFDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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Table 2.6

- 1 (a) Dose

- Response Values for Chroni c Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 16 = cancer risk per μg/m 3 of a verage lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Health Hazard Assessm e nt, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standard s. EPA ORD = EPA Office of Research and Development Pollutant CAS Number 17 URE 5 (1/μg/m 3 ) Source

2,3,4,7,8

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

- Tetrachlorodibenzo

- p

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

- Tetrachlorodibenzofuran 51207319 3.3 EPA ORD

Arsenic c ompounds 7440382 4.3E

- 03 IRIS Beryllium c ompounds 7440417 2.4E

- 03 IRIS

Cadmium c ompounds 7440439 1.8E

- 03 IRIS

Chromium c ompounds Chromium (VI) 18540299 1.2E

- 02 IRIS Naphthalene 91203 3.4E

- 05 CAL

Nickel c ompounds 19 7440020 4.8E

- 04 EPA OAQPS Polychlorinated b iphenyls 1336363 1.0E

- 04 IRIS Polycyclic Organic Matter 20

, 21

2

- Methylnaphthalene 91576 8.8E

- 05 CAL Acenaphthene 83329 8.8E

- 0 5 CAL
Acenaphthylene 206968 8.8E

- 0 5 CAL
Benz[a]anthracene 56553 1.8E

- 04 CAL Benzo[a]pyrene 50328 1.8E

- 03 CAL

19 The EPA IRIS assessments for nickel compounds provide a range of plausible UREs. This assessment used the highest value in that range which is equal to the URE for nickel subsulfide, 4.8E

- 04 per ug/m 3 . The l ow end of the range is equal to 50% of the URE for nickel subsulfide, 2.4E

- 04 per ug/m 3

.

20 All POM act by a mutagenic mode

- of

- action, therefore the UREs have been adjusted by a factor of 1.6 (see section 2.7.1 for more details)

.

21 Assigned the URE assoc iated 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/na ta2005/methods.html#pomDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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Table 2.6

- 1 (a) Dose

- Response Values for Chroni c Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 16 = cancer risk per μg/m 3 of a verage lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Health Hazard Assessm e nt, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standard s. EPA ORD = EPA Office of Research and Development Pollutant CAS Number 17 URE 5 (1/μg/m 3 ) Source

Benzo[e]pyrene 192972 8.8E

- 05 CAL Benzo[b]fluoranthene 205992 1.8E

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

- 0 5 CAL
Benzo[k]fluoranthene 207089 1.8E

- 04 CAL Chrysene 218019 1.8E

- 05 CAL Dibenzo[a,h]anthracene 53703 1.9E

- 03 CAL
F luoranthene 206440 8.8E

- 0 5 CAL

Fluorene 86737 8.8E

- 0 5 CAL
Indeno[1,2,3

- c,d]pyrene 193395 1.8E

- 04 CAL Perylene 198550 8.8 E

- 05 CAL

Table 2.6

- 1 (b) Dose

- Response Values for Chronic Oral Exposure to Carcinogens
SF (oral slope factor for cancer) = cancer risk per mg/kg/d of average lifetime exposure. Sources : IRIS = EPA Integrated Risk Information System, CAL = Californ ia EPA Office of Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards.

Pollutant CAS Number 1 9 SF (1/mg/kg/d) Source 2,3,7,8

- tetrachlorodibenzo

- p

- dioxin 1746016 150000 EPA OR D Polychlorinated Biphenyls 1336363 2 IRIS Polycyclic Organic Matter POM 246 Benz[a]anthracene 56553 1.2 CAL Benzo[b]fluoranthene 205992 1.2 CAL Benzo[k]fluoranthene 207089 1.2 CAL Benzo[a]pyrene 50328 7.3 IRIS Chrysene 21 8019 0.12 CAL Dibenzo [a,h]anthracene 53703 4.1 CAL Indeno[1,2,3

- c,d]Pyrene 193395 1.2 CALDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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Table 2.6

- 1 ( c ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens
RfC (reference inhalation concentration) = an estimate (with unce rtainty 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 Integ rated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry.
Pollutant CAS Number 19 RfC (mg/m3) Source 22

Antimony c ompounds 7440360 0.0002 IRIS

- L Arseni c c ompounds 7440382 0.000015 CAL Beryllium c ompounds 7440417 0.00002 IRIS

– M Cadmium c ompounds 7440439 0.00001 ATSDR Carbonyl sulfide 463581 0.163 EPA ORD 23 Chromium (VI) c ompounds 18540299 0.0001 IRIS

– M Cobalt c ompounds 7440484 0.0001 ATSDR Dioxin s/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 0.0000 04 CAL 1,2,3,4,7,8,9

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

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

- Hexachlorodibenzo

- p

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

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

- Hexachlorodibenzo

- p

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

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

- Hexachlorodibenzo

- p

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

- Pentachlorodibenzo

- p

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

- Pent achlorodibenzofuran 57117416 0.0000013 CAL 2,3,4,6,7,8

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

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

- Tetrachlorodibenzo

- p

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

- Tetrachlorodibenzofuran 51 207319 0.0000004 CAL Hydrofluoric acid 7664393 0.014 CAL Lead Compounds 7439921 0.00015 EPA OAQPS Manganese Compounds 7439965 0.000 3 ATSDR

22 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.

23 A chronic screening level of 0.163 mg/m 3 was dev eloped for carbonyl sulfide by EPA ORD from a No Observed Adverse Effects Level of 200 ppm based on brain lesions and neurophysiological alteration in rodents. see Mineral Wool Report, Section 2.6.1, item 5 for report language on carbonyl sulfideDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 25

Table 2.6

- 1 ( c ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens
RfC (reference inhalation concentration) = an estimate (with unce rtainty 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 Integ rated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry.
Pollutant CAS Number 19 RfC (mg/m3) Source 22

Mercury Compounds 184 0.0003 IRIS

– M Mercuric Chloride 7487947 0.0003 IRIS

– M Mercury (elemental) 7 439976 0.0003 IRIS

– M Naphthalene 91203 0.003 IRIS

– M Nickel Compounds 7440020 0.00009 ATSDR Selenium Compounds 7782492 0.02 CAL

Table 2.6

- 1 ( d ) Dose

- Response Values for Chronic Oral Exposure to Nonc arcinogens

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

Pollutant CAS Number RfD (mg/kg/d) Source 24 Cadmium compounds 7440439 0.0005 IRIS

- H Mercuric chloride 25 7439976 0.0003 IRIS

- H

2.6.2 Sources of acute dose

- response informati on Hazard identification and dose

- response assessment information for preliminary acute inhalation exposure assessments is based on the existing recommendations of OAQPS for HAPs [ 19 ]

. Depending on availability, the results from screening acute assessment s 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 Guid elines (ERPGs), with the recognition that the ultimate interpretation of any potential risks associated with an estimated exceedance of a particular reference level depends on the definition of that level and any limitations expressed therein. Comparisons among different available

24 The de scriptors 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.

25 The multipathway exposure assessment for mercury included fate and transport analy sis, that included separate oral exposure estimates for divalent mercury and methylmercury.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 26

inhalation health effect reference values (both acute and chronic) for selected HAPs can be found in a n EPA document of graphical arrays

. 26

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

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

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

“ t he concentration level at or below which no adverse health effects are anticipated for a specified exposure duration . [ 20 ]

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

- hour (and 8

- hour) exposures. The values incorporate uncertainty factors similar to those used in deriving EPA’s Inhalation Reference Concentrations (RfCs) for chronic exposures (and, in fact, California also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory Committee (NAC) on Acute Exposure Guideline Levels (NAC/AEGL) f or Hazardous Sub stances , and then reviewed and published by the National Research Council

. A s described in the Committee’s “Standing Operating Procedures (SOP) ” ( http://www.epa.gov/opptintr/aegl/pubs/sop.pdf ), A EGLs “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 : “the primary purpose of the AEGL program and the NAC/AEGL Committee is to develop gu ideline levels for once

- in

- a

- lifetime , short

- term exposures to airborne concentrations of acutely toxic, high

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

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

- time emergency response actions, for accidental chemical releases at fixed facilities and from transport carriers.” The NAC/AEGL defines AEGL

- 1 and AEGL

- 2 as:

“ AEGL

- 1 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, including susceptible individuals, could experience notable discomfort, irrita tion, or certain asymptomatic nonsensory effects.

26 See : U.S. EPA. Graphical Arrays of Chemical

- Specific Health Effect Reference Values for Inhalation Exposures [Final Report]. (U.S. Environmental Protection Agen cy, Washington, D.C., EPA/600/R

- 09/061, 2009. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003 .)Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 27

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 pred icted that the general population, including susceptible individuals, could experience irreversible or other serious, long

- lasting adverse health effects or an impaired ability to escape. ”

“ Airborne concentrations below AEGL

- 1 represent exposure levels t hat can produce mild and progressively increasing but transient and nondisabling odor, taste, and sensory irritation or certain asymptomatic, nonsensory effects. With increasing airborne concentrations above each AEGL, there is a progressive increase in t he likelihood of occurrence and the severity of effects described for each corresponding AEGL. Although the AEGL values represent threshold levels for the general public, including susceptible subpopulations, such as infants, children, the elderly, person s with asthma, and those with other illnesses, it is recognized that individuals, subject to unique or idiosyncratic responses, could experience the effects described at concentration s below the corresponding AEGL.”

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

- 1), irreversible or serious (ERPG

- 2), and potentially life

- threatening (ERPG

- 3).

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

involved/AIHAGuidelineFoundation/EmergencyResponsePlanningGuidelines/Pages/default.a
spx ) are described in their supporting documen tation as follows: “ Emergency Response Planning Guidelines (ERPGs) were developed for emergency planning and are intended as health based guideline concentrations for single exposures to chemicals. These guidelines (i.e., the ERPG Documents and ERPG value s) are intended for use as planning tools for assessing the adequacy of accident prevention and emergency response plans, including transportation emergency planning and for developing comm unity emergency response plans. The emphasis is on ERPGs as planni ng values: When an actual chemical emergency occurs there is seldom time to measure airborne concentrations and then to take action. ” ERPG

- 1 and ERPG

- 2 values are defined by AIHA as follows:

“ ERPG

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

“ ERPG

- 2 is the maximum airborne concentration bel ow 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'sDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 28

ability to take protective action. ”

In ass essing the potential risks associated with acute exposures to HAP, we do not follow a prioritization scheme and therefore we consider available dose

- response values from multiple authoritative sources.

The emissions inventory for the p rimary a lum inum r eduction source category includes emissions of six HAP with relevant and available quantitative acute dose

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

- 3

.

Table 2.6

- 3 Dose

- Response Values for Acute Exposure

Pollutant CAS Number AEGL

- 1 (1

- hr) (mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

- 1

(mg/m 3 ) ERPG

- 2

(mg/m 3 ) REL

(mg/m 3 ) Arsenic compounds 7440382 0.0002 Beryllium compounds 7440417 0.025 Carbon yl sulfide 463581 140 Hydro fluoric acid 76 64393 0.82 20 1.6 16 0.24 Mercury (elemental) 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 i ntegrated and an overall conclusion about risk is synthesized that is complete, informative, and useful for decision makers. In general, the nature of this risk characterization depends on the information available, the application of the risk information and the resources available. In all cases, major issues associated with determining the nature and extent of the risk are identified and discussed. Further, the EPA Administrator’s March 1995 Policy for Risk Characterization [ 22 ] specifies that a risk ch aracterization “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 reinforce d 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 27 , and are incorporated in these assessments.

Estimates of health risk are presented in the context of uncertainties and limitations in the data and methodology. Through our tiered, iterative analytical approach, we have attempted to reduce both uncertainty and bias to the greatest degree possible in these ass essments, within

27 Memorandum f

or t he Heads o f Executive Departments a nd Agencies

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

- 24.pdf )Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 29

the limitations of available time and resources. We provide summaries of risk metrics (including maximum individual cancer risks and noncancer hazards, as well as cancer incidence estimates) along with a discussion of the major uncertaint ies associated with their derivation to provide decision makers with the fullest picture of the assessment and its limitations.

For each carcinogenic HAP included in an assessment that has a potency estimate available, individu al and population cancer ris ks 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 HAPs are upper

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

zero.
For EPA’s list of carcinogenic HAPs that act by a mutagenic mode

- of

- action [ 25 ], we applied EP A’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 be ginning 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 reporte d as individual compounds, EPA expresses carcinogenic potency for compounds in this group in terms of benzo[a]pyrene equivalence, based on evidence that carcinogenic POM have the same mutagenic mechanism of action as does benzo[a]pyrene. For this reason

, EPA implem entation policy [ 27 ] recommends applyi ng the Supplemental Guidance to all carcinogenic PAHs for which risk estimates are based on relative potency. Accordingly, we applied the Supplemental Guidance to all unspeciated POM mixtures.

Increased canc er incidence for the entire receptor population within the area of analysis 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 modele d 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 prob ability of an adverse occurrence. Instead, “risk” for noncancer effects is expressed by comparing an exposure to a reference level as a ratio. The “hazard quotient” (HQ) is the estimated exposure divided by a reference level (e.g., the RfC). For a given HAP, exposures at or below the reference level (HQ≤1) are not likely to cause adverse health effects. As exposures increase above the reference level (HQs increasingly greater than 1), the potential for adverse effects increases. For exposures predicted to be above the RfC, the risk characterization includes the degree of confidence ascribed to the RfC values for the compound(s) of concern (i.e., high, medium, or low confidence) and discusses the impact of this on possible health interpretations.

The r isk characterization for chronic effects other than cancer is expressed in terms of the HQDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 30

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

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

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

e xposures from a particular source category combined.

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

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

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

- of

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

- cancer HQs of HAPs that act by similar toxic modes of action, or (where this information is absent) that affect the same target organ. This process creates, for each target organ, a target

- organ

- specific hazard index (TOSHI), defined as the sum of hazard quotients for individual HAPs that affect the same organ or

o rgan system. A ll TOSHI calculations presented here were based exclusively on effects occurring at the “ critical dose” (i.e., the lowest dose that produces adverse health effects). Although HQs associated with some pollutants have been aggregated into mor e 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 b een underestimated. As with the HQ, the TOSHI should not be interpreted as a probability of adverse effects, or as strict delineation of “safe” and “unsafe” levels. Rather, the TOSHI is another measure of the potential for adverse health outcomes associa ted with pollutant exposure, and needs to be interpreted carefully by health scientists and risk managers.

Because of the conservative nature of the acute inhalation screening and the variable nature of emissions and potential exposures, acute impacts wer e screened on an individual pollutant basis, not using the TOSHI approach.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 31

2.7.3 Facility

- wide risks To help place the source category risks in context, we examined “facility

- wide” risks using 2005 NEI data and modeling as described in Section 2.2. For t he facilities in th i s source categor y , we estimated the maximum inhalation cancer and chronic noncancer risks associated with all HAP emissions sources at the facility, including emissions sources that are not part of the primary aluminum source categor y b ut are located within a contiguous area and are under common control. We analyzed risks due to the inhalation of HAP for the populations residing within 50 kilometers of each facility. The results of these facility

- wide assessments are summarized below i n the Risk Characterization section (Section 3.2) of this document. The complete results of the facility

- wide assessments are provided in Appendix 6 of this document ( Draft Detailed Risk Modeling Results )

.
2.7.4 MACT

- Allowable R isks
The emissions data in the dataset for the p rimary aluminum 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 p rimary aluminum r eduction source category,

e stimates of MACT

- allowable emissions were also estimated, and the risk results based on those emissions are presented below as well. For more detail, please refer to the emissions memo in Appendix 1 to this document, Draft Development of the Risk and Tech nology Review (RTR) Emissions Dataset for the Primary Aluminum Reduction Source Category.



### 3 Risk r esults for the Primary Aluminum Reduction s ource c ategory

3.1 Source c ategory emissions and r esults
The p rimary a luminum r e duction source category consists of one facility that does not produce aluminum directly but produces anodes for use in the aluminum producing facilities and thir teen major source facilities that produce aluminum from refined ore (alumina) using a reduction process whereby the alumina is dissol ved in an electrolytic bath in reduction cells which are connected electrically in series to form “potlines” in the presence of fluoride. The main raw materials in this process are alumina (Al 2 O 3 ), coke, pitch, and fluoride salts . The process of aluminum reduction includes passing a high electrical direct current from a carbon anode to a carbon cathode which results in purified molten aluminum sinking to the bottom of the reduction cell, beneath the electrolytic bath. The HAP emission sources at primary

a luminum reduction facilities include anode bake furnaces, potline s , and pitch storage tanks

, The HAP expected to be emitted from these facilities include: hydrofluoric acid, HAP metals, PAH’s, and dioxin/furans

There are fourteen facilities subject to t he primary aluminum NESHAP with operations in the U.S. One facility is undergoing bankruptcy procedures and it is believed will no longer operate. Emissions data, required for modeling, is available from the remaining t hirteen facilities and are summariz ed in Table 3.1

- 1. Further, current as well as future operations at two other facilities is uncertain. C omplete details about the status of these facilities can be found in the emissions memo available in Appendix 1 of this document , “ Draft Development

o f the Risk and Technology Review (RTR) Emissions Dataset for the Primary Aluminum Reduction Source Category

.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 32

The actual emissions for the primary aluminum reduction source category (of 1 3 sources) are summarized in Table 3.1

- 1. The total HAP emissions f or the source category are

a pproximately 4,5 00 tons per year. Based on these data, the HAP emitted in the largest quantities are carbonyl sulfide

, hydrofluoric acid, and POM, . Emissions of these three HAP make up more than 90 percent of the total emissio ns by mass for the source category

. Persistent and bioaccumulative HAP (PB

- HAP) 28 reported as emissions from these facilities include lead compounds, mercury compounds, PCBs, dioxins/furans, cadmium compounds, and polycyclic organic matter. The follow ing environmental HAP are emitted from the primary aluminum reduction source category and are included in the environmental risk screen: cadmium compounds, dioxins/furans, lead compounds, mercury compounds, PAHs, and hydrogen fluoride. Stack test data of dioxins/furans, mercury, and PCB’s indicate “these emissions are very low and may be non

- existent” but, to be conservative, we estimate below detection limit ( BDL ) sample results as 1⁄2 the detection limit and incl ude them in the emission estimates that a re used in the risk model file

.

Table 3.1

- 1 Summary of Emissions from the P rimary Aluminum Reduction Source Category Used in

the Residual Risk Assessment Availability of Dose

- Response Values

HAP a Emission

Estimates (tpy) Number of

Facilities where HAP Repor ted or Estimated ( 13 facilities in d ata set) Prioritized Inhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk Estimate for Cancer? Reference

Concentration for Chronic Noncancer? Health

Benchmark Values for Acute Noncancer? Carbonyl sulfide 3400 13   Hydrofluoric acid 1000 13 

 

 Polycyclic Organic Matter

  Fluoranthene 7.0 13   Phenanthrene 6.1 13

 

 Acenaphthene 5.0 13 

 

 2

- Methylnaphthalene 2.2 13 

 

 Benzo[ b]fluoranthene 1.6 13 

 

 Chrysene 1.4 13 

 

 Fluorene 1.0 13 

 

 Pyrene 0.87 13

 

 Benzo(e)pyrene 0.73 13 

 

 Acenaphtylene 0.58 13 

   Benzo[k]fluoranthene 0. 51 13 

   

 Benz[a]anthracene 0. 3 7 13 

   

 Anthracene 0.35 13

 

 Benzo[g,h,i]perylene 028 13 

 



28 Persistent and bioaccumulative HAP are defined in the EPA’s Air Toxics Risk Assessment Libra ry , Volume 1, EPA

- 453K

- 04

- 001A, provided on the EPA’s Technology Transfer Network website for Fate, Exposure, and Risk Assessment at http://w ww2.epa.gov/fera/risk

- assessment

- and

- modeling

- air

- toxics

- risk

- assessment

reference

- libraryDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 33

Table 3.1

- 1 Summary of Emissions from the P rimary Aluminum Reduction Source Category Used in

the Residual Risk Assessment Availability of Dose

- Response Values

HAP a Emission

Estimates (tpy) Number of

Facilities where HAP Repor ted or Estimated ( 13 facilities in d ata set) Prioritized Inhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk Estimate for Cancer? Reference

Concentration for Chronic Noncancer? Health

Benchmark Values for Acute Noncancer? Indeno[1,2,3

- c,d]
pyrene 0. 23 13 

 

 Benzo[a]pyrene 0. 18 13 

 

 D ibenzo[a,h]anthracene 0.0 7 13 

   Perylene 0.05 13 

   Nickel compounds 16.6 13  

 Lead c ompounds 10.6 13

 c

   Naphthalene 9.5 13  

  Manganese compounds 6.9 13

 

  Arsenic c ompounds 5.2 13 

 

 

 Chromium (III)

c ompounds 4 13

   Chromium (VI) compounds 0 .24 13 

 

  Antimony c ompounds 3.2 13

 

 Selenium c ompounds 2.8 13 

 Cobalt compounds 1.0 13

 Cadmium compounds 0.52 13  

  Beryllium compounds 0.22 

 

 

 Mercury c ompounds

   Mercury (elemental) 0.06 13

 

 

 Gaseous Divalent Hg 0.007 13

 

 

 Particulate Divalent Hg 0.007 13

 

 

 Polychlorinated biphenyls 0.0006 13

   D ioxin /furans (TEQ)

   1,2,3,4,6,7,8

- Heptachlorodibenzo

- p

- dioxin 4.88E

- 07 13    1,2,3,4,6,7 ,8

- Heptachlorodibenzofuran 2.05E

- 06 13 

 

   1,2,3,4,7,8,9

-
Heptachlorodibenzofuran 3.30E

- 7 13 

 

   1,2,3,4,7,8

- Hexachlorodibenzo

- p

- dioxin 1.67E

- 07 13    1,2,3,4,7,8

- Hexachlorodibenzofuran 6.55E

- 07 13   Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 34

Table 3.1

- 1 Summary of Emissions from the P rimary Aluminum Reduction Source Category Used in

the Residual Risk Assessment Availability of Dose

- Response Values

HAP a Emission

Estimates (tpy) Number of

Facilities where HAP Repor ted or Estimated ( 13 facilities in d ata set) Prioritized Inhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk Estimate for Cancer? Reference

Concentration for Chronic Noncancer? Health

Benchmark Values for Acute Noncancer?
1, 2,3,6,7,8

- Hexachlorodibenzo

- p

- dioxin 2.47E

- 07 13 

  

 1,2,3,6,7,8

- Hexachlorodibenzofuran 5.89E

- 07 13 

  

 1,2,3,7,8,9

- Hexachlorodibenzo

- p

- dioxin 2.63E

- 07 13 

  

 1,2,3,7,8,9

- Hexachlorodibenzofuran 1.74E

- 07 13 

  

 1,2,3,7,8

- Pentachlorodibenzo

- p

- dioxin 9.83E

- 07 13 

  

 1,2,3,7,8

- Pentachlorodibenzofuran 5.1E

- 07 13    2,3,4,6,7,8

- Hexachlorodibenzofuran 5.58E

- 07 13 

  

 2,3,4,7,8

- Pentachlorodibenzofuran 1.19E

- 06 13 

  

 2,3,7,8

- Tetrachlorodibenzo

- p

- dioxin 1.09E

- 06 13 

  

 2,3,7,8

- Tetrachlorodibenzofuran 9.68E

- 07 13 

  

 1,2,3,7,8,9

- Hexachlorodibenzo

- p

dioxin 2.63E

- 07 13   

a Notes for how HAP were speciated for risk assessment:

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

 Chromium emission s were speciated based on test data . See Appendix 1 of this document ( Revised Development of the Risk and Technology Review (RTR) Emissions Dataset for the Primary Aluminum Reduction Source Category ) for more information.

 For emissions reported generica lly as “mercury” or “mercury & compounds,” emissions are speciated for this category as 80 percent “mer cury (elemental),” 10 percent “gaseous divalent mercury,” and 10 percent “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 valu es for each chemical are identified on EPA’s Technology Transfer Network website for air toxics at http://www2.epa.gov/f era/dose

- response

- assessment

- assessing

- health

- risks

- associated

- exposure

- hazardous

- air

pollutants

. C There is no reference concentration for lead. In considering noncancer hazards for lead in this assessment, we comparedDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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maximum annual ambient exposu re estimates to the National Ambient Air Quality Standards (NAAQS) for lead (0.15 μg/m 3 ). These NAAQS for lead were reviewed with revisions adopted in October 2008 http://www.epa.gov/air/lead/a ctions.html . The primary (health

- based) standard is a maximum or not

- to

- be

- exceeded, rolling three

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

- based) standard is identical to the primary standard.



### 3.2 Baseline r i sk c haracterization This section presents the results of the risk assessment for the primary aluminum production source category based on the modeling methods described in the previous sections

. All baseline risk results are developed using the best estim ates 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 resul ts from our acute inhalation impact screening in the form of maximum hazard quotients, as well as the results of our preliminary screen for potential non

- inhalation risks from PB

- HAP. Also presented are the HAP “drivers,” which are the HAP that collectivel y contribute 90 percent of the maximum cancer risk or maximum hazard index 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 facilit y

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

.

Baseline Inhalation Risk Assessment Results Based on Actual Emissions

Table 3 .2

- 1 summarize s the preliminary chronic and acute inhalat ion 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 the active operating plants could be as high as 70 in a million , with e missions of arsenic compounds , nickel compounds , and chromium compounds from the potline roof vents a s the major contributors to the risk. The total estimated cancer incidence from this source category is 0.0 6 excess cancer cases per year, or about one excess case in every 1 7 years. A pproximately 65

, 000 pe ople were estimated to have cancer risks above 10 in a million and approximatel y 880,000 peop le were estimated to have cancer risks above 1 in a million

. The maximum chronic noncancer TOSHI value for the source category could be up to 1 driven by nickel and cadmium emissions from the potline roof vents.

Worst

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

- 1 . For cases where the screen ing HQ was greater than 1, we further refined the estimates by determining the highest HQ value that might occur outside facility boundaries and at residential locations . Based on actual, baseline emissions, the highest off

- site acute screening value is 3 0 and 10 at a residential location , (based on the acute REL for arsenic compounds) there were no AEGL or ERPG values for comparison refer
to Table 3.2

- 1. Further refinement of the arsenic acute assessment was done to characterize the exposure for this sou rce category, we had 8 active facilities exceeding the REL at a residential location, with the potential for 8,500 people being exposed above an HQ of 1. From these 8 facilities we had 3 facilities with an HQ of 10 with 160 people being potentially
expose d. The population impact estimates are based upon worst case meteorology for a single hour for each facility. Also, the population effected are based upon an acute modelingDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 36

domain of 3 kilometers, refer to Appendix 8

, Draft Detailed Acute Risk Modeling R esults for more information.

There are also screening HQs greater than 1 for hydrofluoric acid (REL) ). The highest off

site acute screening value for hydrofluoric acid (REL) is 3 and 2 for a residential location.

Table 3.2

- 1 Summary of Source Catego ry Level Inhalation Risks f or Primary Aluminum Reduction Sources Result HAP “Drivers” Facilities in Source Category Number of Facilities Estimated to be i n Source Category 14 n/a

Number of Facilities Identified in NEI and Modeled in Preliminary Risk A ssessment 13 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 70 a rsenic compounds , nickel compounds , P AH Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a

Great er than or equal to 10 in 1 million 12 n/a

Greater than or equal to 1 in 1 million 1 2 n/a

Chronic Noncancer Risks Maximum Respiratory Hazard Index 1 nickel compounds Num ber of Facilities with Maximum Respiratory Hazard Index: Greater than 1 0 n/a A cute Noncancer Refined Screening Results
Maximum Acute Hazard Quotient 29 (Residential) 10 2 0.6 arsenic compounds (REL)

hydrofluoric acid (REL) hydrofluoric acid (AEGL

- 1) Number of Facilities With Potential for Acute Effects 8 arsenic c ompounds

, hydrof luoric acid Population Exposure Number of People Living Within 50 Kilometers of Facilities Modeled 3 ,000,000 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 65,00 0 n/a
Greater than or equal to 1 in 1 million 881,000 n/a Number of People Exposed to Noncancer Respiratory Hazard Index: Greater than 1 0 n/a

29 As shown in Table 2.6

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

- term occupational values for these metals to c ompare to the REL values.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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Table 3.2

- 1 Summary of Source Catego ry Level Inhalation Risks f or Primary Aluminum Reduction Sources Result HAP “Drivers” Estimated Cancer Incidence (excess cancer cases per year) 0.06 n/a
Contribution of HAP to Cancer Incidence

Arsenic compounds 64 % n/a
Nickel compounds 21% n/a Chromium compounds 8% n/a

Baseline Inhalation Assessment Results Based on Allowable Emissions

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

- allowable emissions) were also calculated for the source category. (See Draft Development of the Risk and Technology Review (RTR) Emissions Dataset for the Primary Aluminum Reduction Plants Source Category in Appendix 1 of this document for a discussion of the development of the allowable emissions dataset.) Risk results from the inhalation risk assessment using the MACT

- allowable emissions indicate that the maximum lifetime individual cancer risk could be as high as 30 0 in a million

, and that the maximum chronic noncancer TOSHI value could be as high as 2 at the MACT

allowable emissions level. The MACT

- allowable cancer risks are driven by emissions of arsenic compounds , nickel compounds , and PAH s, while the MACT

- allowa ble TOSHI is driven by emissions of arsenic compounds and nickel compounds. A pproximately 200 people were estimated to have cancer risks above 1 0 0 in a million

, approximately 76 ,000 people were estimated to have cancer risks above 10 in a million and appr oximatel y 950 ,000 peop le were estimated to have cancer risks above 1 in a million resulting from MACT

- allowable emissions. It was also estimated that approximately 30 people maybe exposed to a noncancer TOSHI value greater than 1. The facility with the h ighest MACT

- allowable risks ( Columbia Falls Aluminum , NEI12468) has not been operating over the last 5 years but they still retain their operating permits for the site. If this facility was not included in the dataset, the MIR based on MACT

- allowable emis s i ons is estimated to be 70 in a million , while the TOSHI is estimated to be 1

.

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 1 ) that compared emissions of PB

- HAP emitted from the
p rimary aluminum source category (based on actual emissions) to screening emission rates ( see section 2.5 or Appendix 5 of this document for a more detailed discussion of the screening e mission rates )

. The PB

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

- TCDD toxicity equivalents, or TEQ), mercury compounds, polychlorinated biphenyls (PCBs), and POM (as benzo(a)pyr ene TEQ). PCBs are PB

- HAP but do not currently have multipathway screening values and so were not evaluated for potential non

- inhalation risks. As shown in Table 3.1

- 1, this PB

- HAP is not emitted in appreciable quantities.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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All thirteen facilities emit ted each of the PB

- HAP listed above. Emissions of POM and dioxins at all thirteen facilities were greater than the Tier 1 screening levels for these compounds. The maximum exceedance for an active facility of the Tier 1 screening level for POM was 50 tim es, while the maximum exceedance of the Tier 1 screening level for dioxins

was 200 times. Six facilities emitted cadmium compounds at rates exceeding the Tier 1 screening level, with the maximum being 30 times the level. And, nine facilities emitted

mer cury compounds at rates exceeding the Tier 1 screening level, with the maximum being 10 times the level. D ue to the theoretical construct of the screening model, these factors are not directly translatable into estimates of risk or hazard quotients for t hese facilities. Table 3.2

- 2 summarizes the results of this Tier 1 screen.

For the PB

- HAP and facilities that did not screen out during our initial Tier 1 multipathway screening analysis, we improved our analysis with some additional site

- specific info rmation to develop a Tier 2 screen. (See Appendix 5 of this document, Technical Support Document for TRIM

- Based Multipathway Screening Scenario for RTR: Summary of Approach and Evaluation , for more information about the Tier 2 screen.) The additional si te

- specific information included the location of fishable l akes 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 for the farmer and fisher scenarios

.

Emissions of both dioxins and P OM exceed ed the Tier 2 Screen for cancer for all operating plants

. The highest cancer exceedance for dioxins was 40 times and 7 times for POM for the subsistence fisherman scenario (total cancer screen value of 50 for the MIR site) from the Alcoa facility in Newburgh, Indiana . For the subsiste nce farmer scenario , the highest cancer exceedance for dioxin was 10 times and POM was 4 times (total cancer screen value of 2 0 for the MIR site), refer to Table 3.2

- 2

. Based on th e Tier 2 non

- cancer screening analysis for operating plants

, emissions of mercury and cadmium also exceed ed the site

- specific levels for those PB

- HAP s by a factor of 2 from 2 different facilities

. The facilities that exceeded are Alumax from Goose Creek, Sou th Carolina for mercury emissions and Alcoa Primary Metals for their cadmium emissions

, refer to Appendix 6, Table 4 for a summary of the screened results from Tier 1 and 2

.

Similar to the results from the Tier 1 screen, an exceeda nce of a screening level in Tier 2 cannot be equated with a risk value or a hazard quotient (or hazard index). Rather, it represents a high

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

- carcinogen can be interp reted to mean that we have high confidence that the hazard would be lower than 2. Similarly, an exceedance of 30 for a carcinogen means that we have high confidence that the risk is lower than 3 0 in a million. Our confidence comes from the conservative, or health

- protective, assumptions that are in the screens: we choose inputs from the upper end of the range of possible values for the influential parameters used in the screens; and we assume that the exposed individual exhibits ingestion behavior that w ould lead to a high total exposure. If exceedance s above an acceptable level are observed from the Tier 2 screen we may proceed to the Tier 3 screen to fu rther refine this assessment

.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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Table 3.2

- 2 Summary of the “Tier 1 and Tier 2” Multipathway Screening Analysis for the Primary Aluminum Reduction Source Category

a.

– D ioxin and POM screen values were based upon the emissions normal ized to 2,3,7,8

– TCDD and BaP respectively for oral toxicity and Tier 1 modeled environmental fate and transport b.

-- Maximum Screening Values for Tier 1 and Tier 2 Fisher and Farmer Scenario reflect the maximum screening value for primary aluminum plants that are currently operating based upon actual emissions

A Tie r 3 screen was conducted for 3 facilities, including a facility that is no longer operating, this plant had the highest exceedance of Tier 2 cancer screening levels for POM and dioxins at 70 time s the screening level ( Reynolds Metals

, NEI46970

, in Massena, New York ). Since this site is no longer operating their S oderberg process it was not included as part of the MIR assessment for the source category.

In the Tier 3 screen s , we examined the set of lakes from which the fisher ingested fish to determine if they were fishable and also analyzed plume rise data in relation to the time

- series meteorology to calculate effective stack release heights

. The results of the Tier 3 screen for the 3 facilities based upon the fisher scenario are as follows : PAH ’ s exceed ed the cancer screening level by 60 times and for dioxins 10 times , resulting in a total exceedance for carcinogens of 7 0 time s resulting in no change from the Tier 2 cancer screen value ; m ercury and cadmium non

- cancer screen values dropped to a value of 1 due to loss of mass associ ated with plume

- rise , refer to Appendix 6, Table 4 for a summary of the Tier Screen 1

– 3 results

. For the subsistence farmer scenario, the highest cancer exceedance for dioxin was 20 times and POM was 100 times (total cancer screen value of 200 after rounding ), f or further discussion on the methods and results for each of the three Tiers see Appendix 9 of this document ( Technical Support Document: Human Health Multipathway Residual Risk Screening Assessment for the Primary Aluminum Reduction Source Category ).

The multipathway s creen s includes some hypothetical elements, namely the hypothetical farmer and fisher scenarios. We also included children in different age ranges and adults. It is important to note that even though the multipathway assessment has been conducted, no data exist to verify the existence of either the farmer or fisher scenario outlined above. The farmer scenar io involves an individual living for a 70

- year lifetime on a farm homestead in the vicinity of the source and consuming produce grown on, and meat and animal products raised on, the farm. The individual also incidentally ingests surface soil at the locati on of the farm homestead. The fisher scenario involves an individual who regularly consumes fish caught in freshwater lakes in the vicinity of the source of interest over the course of a 70

- year lifetime. In addition, exposure estimates and risks for inf ants consuming contaminated breastDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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milk were evaluated in the case of dioxins, with the assumption that the nursing mother was exposed to chemicals via one of the two scenarios described above.

I n evaluating the potential for multipathway effects from emissions of lead, modeled maximum annual lead concentrations were compared to the secondary NAAQS for lead (0.15 μg/m 3 ) . Results of this analysis estimate that the NAAQS for lead w ould not be exceeded at any off

- site locations.

Baseline Environme ntal Risk Screening Based on Actual Emissions

We conducted a screening

- level evaluation of the potential adverse environmental risks associated with emissions of the following environmental HAP from the primary aluminum reduction source category: cadmium

, PAH’s, dioxins/furans, hydrogen fluoride, lead, and mercury. The results of the environmental screening analysis are summarized in Table 3.2

- 3

.

Table 3.2

- 3 Summary of Environmental Risk Screen Results for the Primary Aluminum Reduction Sourc e Category

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

PB

HAP Dioxins /Furans None None

- - 0.4 0% 0%

Cd 1 1 None N one 0% 0% MeHg None None

- -- 0% 0% PAH 1 1 1 None NA 4 0% Acid Gases HF 3 N A N one

- - NA 0.2%

NA

– Not Applicable. 1

- Tier 2 screen is performed for PB

- HAP when there are exceedances of the Tier 1 screen. The acid gas screen is a one tier scre en. 2

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

- HAP the percent area is based on the Tier 2 results, if a Tier 2 analysis is performed. Otherwise, the percent area is based on the Tier 1 results. 3

– Fo r 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 for the Canadian bench mark, which is the more protective of the two. 4

– One facility had a T ier 2 exceedance for the sediment NOAEL benchmark at one lake. For PB

- HAP the percent area is calculated for soil benchmarks only.

In our Tier 1 analysis, emissions of dioxins and m ethyl mercury did not exceed the threshold emission rates for any of the ecological benchmarks for any facility in the source category . In our Tier 1 analysis, emissions of cadmium and PAHs exceeded some ecological benchmarks for one facility, therefore, a Tier 2 analysis was performed. In the Tier 2 analysis, emissionsDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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of cadmium did not exceed the threshold emission rates for any of the ecological benchmarks for any facility in the source category. In the Tier 2 analysis, emissions of PAHs exceeded the NOAEL sediment benchmark for one lake by 2 times, but did not exceed the threshold effect level. For hydrogen fluoride, the average modeled concentration around each facility (i.e., the average concentration of all off

- site data points in the modeling do main) did not exceed the ecological benchmark s

. For lead, we did not estimate any exceedances of the secondary lead NAAQS.

Facility

- wide Inhalation Assessment Results

The facility

- wide chronic MIR and TOSHI, available in Appendix 6, are based on actual emissions from all sources at the identified facilities. Considering facility

- wide emissions, the MIR is estimated to be 70 in a million driven by emissions of arsenic compounds

, nickel compounds , and chromium compounds and the chronic non

- cancer TOHSI va lue is calculated to be 1 driven by emissions of cadmium compounds. In both cases, the source of these emissions are from pot line roof vents from the primary aluminum source category

. 

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

4.1 E xposure m odeling u ncertainties

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

specific parameter s 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 degrada tion. 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 overestima tes of the actual MIR values for individual facilities, but, overall, it is not thought to have a significant impact on the estimated MIR for a source category. Finally, we did not factor in the possibility of a source closure occurring during the 70

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

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

A sensitivity analysis performed for the 1999 NATA found that the selection of the meteorology dataset location could result in a range of chronic ambient concentrations which varied from as much as 17 percent below t he predicted value to as much as 84 percent higher than the predicted value. This variability translates directly to the predicted exposures and risks in our assessment, indicating that the actual risks could vary from 17 percent lower to 84 percent highe r than the predicted values.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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We have purposely biased the acute screening results high, considering that they depend upon the joint occurrence of independent factors, such as hourly emissions rates, meteorology and human activity patterns

. 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 in dicated the potential for exceeding short

- term health thresholds post

controls , 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 noncancer reference values. Cancer potency values are derived for chronic (lifetime) exposures. Noncancer reference val ues 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 bas ed 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 (nonca ncer) benchmarks, which are described in more detail below.

Although every effort is made to identify peer

- review ed dose

- response values for all HAPs emitted by the source s included in an assessment, some HAP have no peer

- reviewed cancer potency values o r reference values for chronic non

- cancer or acute effects (inhalation or ingestion) . Since exposures to these pollutants cannot be included in a quantitative risk estimate, an understatement of risk for these pollutants at environmental exposure levels i s possible.

Additionally, chronic dose

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

- ev aluate 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 estimatio n of cancer risk below focuses on the uncertainties associated with the specific approach currently used by the EPA to develop cancer potency factors. In general, these same uncertainties attend the development of cancer potency factors by CalEPA, the sou rce 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 Guideline s ). “The primary goal of EPA actions is protection of human health; accordingly, as an Agency policy, risk assessment procedures, including default options that are used in the absence of scientific data to the contrary, should be healthDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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protective.” The approach adopted in this document is consistent with this approach as described in the Cancer Guidelines

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

- term exposures to the pollutant. Depending on the pollutant being evaluated, EPA relies on both animal bioassay and epidemiological studies to characterize cancer risk. As a science policy approach, consistent with the Cancer Guidelines , EPA uses animal cancer bioassays as indicators of potential human health risk when other human cancer risk data are unavailable.

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

- reviewed methodologies. The EPA Cancer Guidelines describes the Agency’s recommendations for methodologies for cancer risk assessmen t. EPA believes that cancer risk estimates developed following the procedures described in the Cancer Guidelines and outlined below generally provide an upper bound estimate of risk. That is, EPA’s upper bound estimates represent a “plausible upper limit to the true value of a quantity” (although this is usually not a true statistical confidence limit). 30 In some circumstances, the true risk could be as low as zero; however, in other circumstances the risk could also be greater. 31 When developing an uppe r bound estimate of risk and to provide risk values that do not underestimate risk, EPA generally relies on conservative default approaches. 32 EPA also uses the upper bound (rather than lower bound or central) estimates in its assessments, although it is n oted that this approach can have limitations for some uses (e.g. priority setting, expected benefits analysis).

Such health risk assessments have associated uncertainties, some which may be considered quantitatively, and others which generally are express ed 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 m ay differ in how well they represent actual biological processes for the assessed substance. EPA’s Risk Characterization Handbook also recommends that risk

30 IRIS glossary ( http://ofmpub.epa.gov/sor_internet/registry/termreg /searchandretrieve/glossariesandkeywordlists/search.do?deta ils=&glossaryName=IRIS%20Glossary ).

31 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 whi ch is based on maximum likelihood estimates.

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

- assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk asse ssment 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 specifi c 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 ove rtly 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

.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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characterizations present estimates demonstrating the impact on the assessment of alternative choic es, data, models and assumptions [ 31 ]. Some of the major sources of uncertainty and variability in deriving cancer risk values are described more fully below.

(1) The qualitative similarities or differences between tumor responses observed in experiment al animal bioassays and those which would occur in humans are 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. 33 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 spec ies responses can lead to either under

- estimation or over

- estimation of human cancer risks.

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

(3) For the quantitative extrapolation of cancer risk estimate s 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 diff erences 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 e ither greater than or less than that estimated by baseline scientific scaling predictions due to uncertainties associated with limitations in the test data and the correctness of scaled estimates.

(4) EPA cancer risk estimates, whether based on epidemio logical 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 calculatio n. Statistical uncertainty in developing a POD using a benchmark dose (BMD) approach is generally addressed though use of the 95 percent lower confidence limit on the dose at which the specified excess risk occurs (the BMDL), decreasing the likelihood of understating risk. EPA has generally utilized the multistage model for estimation of the BMDL using cancer bioassay data (see further discussion below).

33 Per the EPA Cance r Guidelines: “The default option is that positive effects in animal cancer studies indicate that the agent under study can have carcinogenic potential in humans.” and “Target organ concordance is not a prerequisite for evaluating the implications of anim al study results for humans.”Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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(5) Extrapolation from high to low doses is an important, and potentially large, source of uncertaint y 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) depend ing on the available data and understanding of a pollutant’s mode of action (i.e., the manner in which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use of reliable, compound

- specific, biologically

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

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

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

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

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

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

EPA most frequently utilizes a linear low

- dose extrapolation approach as a baseline science

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

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

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

- dose nonlinear, non

- threshold relationships. The National Academy of Science s 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 tha t 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 v ary 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 depen d 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 popu lation variability: due to the nature of a mode of action and additivity of a chemical’s effect on top of background chemical exposures and biological
processes.
As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straigh t line approach from the BMDL. This is equivalent to using an upper confidence limit on the slope of the straight line extrapolation. The impact of the choice of the BMDL on bottom lineDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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risk estimates can be quantified by comparing risk estimates using t he BMDL value to central estimate BMD values, although these differences are generally not a large contributor to uncertainty in risk assessment (Subramaniam et. al., 2006) [ 33 ]. It is important to note that earlier EPA assessments, including the majority of those for which risk values exist today, were generally developed using the multistage model to extrapolate down to environmental dose levels and did not involve the use of a POD. Subramaniam et

., al. (2006) also provide comparisons indicating that slop es based on straight line extrapolation from a POD do not show large differences from those based on the upper confidence limit of the multistage model.

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

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

- s pecific data to evaluate this variability are generally not available. There may also be important life stage differences in the quantitative potency of carcinogens and, with the exception of the recommendations in EPA’s Supplemental Cancer Guidance for c arcinogens with a mutagenic mode of action, risk assessments do not generally quantitatively address life stage differences. However, one approach used commonly in EPA assessments that may help address variability in response is to extrapolate human respo nse 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 var iability.

Chronic noncancer assessment

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

- protective. That is, EPA and other organizations which develop noncancer reference values (e.g., the Agency for Tox ic 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 refere nce values that are intended to be protective against appreciable risk of deleterious effects . Uncertainty factors are commonly default values 34 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

34 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 t he risk

- assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may depart from them in evaluating the risks posed by a specific substance whe n 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 overestima te 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

.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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assumptions are needed and more default factors are used. Thus there may be a greater tendency to overestimate risk

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

For non

- cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) for exposures via ingestion, and a Reference Concentration (RfC) for inhalation exposures. These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or a continuo us 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. 35 To derive values that are intended to be “without appreciable risk,” EPA’s met hodology 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, eval uating the quality, strengths and limitations of the available studies. EPA typically chooses the relevant endpoint that occurs at the lowest dose, often using statistical modeling of the available data, and then determines the appropriate point of depart ure (POD) for derivation of the reference value. A POD is determined by (in order of preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of the dose or concentration at which the toxic response was not significantly elevated (no observed adverse effect level

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

A series of downward adjustments using default UFs is then applied to the POD to estimate the reference value [ 36 ] . While collectively term ed “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 t he members of the human population (i.e., inter

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

- tha n

- lifetime exposure (i.e., extrapolating from subchronic to chronic exposure); (4) uncertainty in extrapolating from a LOAEL in the absence of a NOAEL; and (5) uncertainty when the database is incomplete or there are problems with applicability of availabl e studies

. When scientifically sound, peer

- reviewed assessment

- specific data are not available, default adjustment values are selected for the individual UFs. For each type of uncertainty (when relevant to the assessment) , EPA typically applies an UF val ue 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 a ssessment (e.g., if applying human toxicity data and an interspecies extrapolation is not required) the associated UF is not used. The major adjustment steps are described more fully below.

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

35 See IRIS glossaryDraft Risk Assessment for the Primary Aluminum Reduction Source Category

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smaller

- sized population, often of one sex or of a narrow range of life stages (typical of occupational epidemiologic studies), to a larger, more diverse population. In the absence of pollutant

- specific data on human variation, a 10

- fold UF is used to account for uncertainty associated with human variation. Human variation may be larger or smaller; however, data to examine the potential magn itude of human variability are often unavailable. In some situations, a smaller UF of 3 may be applied to reflect a known lack of significant variability among humans.

2) Extrapolation from results of studies in experimental animals to humans is a

neces sary step for the majority of chemical risk assessments . When interpreting animal data, the concentration at the POD (e.g. NOAEL, BMDL) in an animal model (e.g. rodents) is extrapolated to estimate the human response. While there is long

- standing scienti fic support for the use of animal studies as indicators of potential toxicity to humans , there are uncertainties in such extrapolations. In the absence of data to the contrary, the typical approach is to use the most relevant endpoint from the most sensit ive species and the most sensitive sex in assessing risks to the average human. Typically

, compound specific data to evaluate relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty in this extrapolation. Size

- related diffe rences (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, differenc es in species responses may be greater or less than this value

. Pharmacokinetic models are useful to examine species differences in pharmacokinetic processing and associated uncertainties; however, such dosimetric adjustments are not always possible. Inf

ormation may not be available to quantitatively assess toxicokinetic or toxicodynamic differences between animals and humans, and in many cases a 10

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

- species

e xtrapolation, a UF of 3 may be used for the remaining component.

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

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

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

4) Toxicity data are typically limited as to the dose or exposure levels that have been tested in individual studies; in an animal study, for example, treatment groups may differ in exposure by up to an order of magnitude. The preferred approach to arrive at a POD is to use BMD analysis; however, this approach requires adequate quantita tive results for a meaningful analysis, which is not always possible. Use of a NOAEL is the next preferred approach after BMD analysis in determining a POD for deriving a health effect reference value. However, many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3

- fold is often applied.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 49

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.

Acute noncancer assessment

Many of the UFs used to acc ount 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 i n acute reference value derivation include: 1) heterogeneity among humans; 2) uncertainty in extrapolating from animals to humans; 3) uncertainty in LOAEL to NOAEL adjustments; and 4) uncertainty in accounting for an incomplete database on toxic effects o f 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 relev ant to the estimated exposures, the lack of threshold values at different levels of severity should be factored into the risk characterization as potential uncertainties.Draft Risk Assessment for the Primary Aluminum Reduction Source Category

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