**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

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## Draft Residual Risk As **sessment for the Secondary**  **Alum inum** 

**Pro duction**  **Source Category**

**by EPA’s Office of Air Quality Planning and Standards** 

**Office of Air and Radiation January**  **201 2** **Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

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### Table of Contents 1 Introduction ................................ ................................ ................................ ........................ 4 2 Methods ................................ ................................ ................................ .............................. 4 2.1 Emissions and source data ................................ ................................ ........................... 4 2.2 Dispersion modeling for inhalation exposure assessment ................................ ........... 5 2.3 Estimating chronic human inhalation exposure ................................ .......................... 8 2.4 Screening for potential acute impacts of concern ................................ ........................ 8 2.5 Multipathway

human health and environmental risk screening ................................ 10 2.6 Dose - response assessment ................................ ................................ ......................... 11 2.6.1 Sources of chronic dose - response information ................................ .................. 11 2.6.2 Sources of acute dose - response information ................................ ...................... 17 2.7 Risk characterization ................................ ................................ ................................ . 20 2.7.1 General ................................ ................................ ................................ ............... 20 2.7.2 Mixtures ................................ ................................ ................................ ............. 22 2.7.3 Facilit y - wid e risks ................................ ................................ .............................. 22 3 Risk results for the Secondary Aluminum production source category ....................... 23 3.1 Source category

description and results ................................ ................................ .... 23 3.2 Baseline risk characterization ................................ ................................ .................... 25 4 General discussion of uncertainties and how they have been addressed ......................... 28 4.1 Exposure modeling uncertainties ................................ ................................ .............. 28 4.2 Uncertainties in the dose - response relationships ................................ ....................... 29 5 References ................................ ................................ ................................ ........................ 38 **Index of Tables** Table 2.2 - 1 AERMOD version 09292 model options for RTR modeling ................................ 6 Table 2.6 - 1 (a) Dose - Response Values for Chronic Inhalation Exposure to Carcinogens .... 14 Table 2.6 - 1 (b) Dose - Response Values for Chronic Oral Exposure to Carcinogens ............. 15 Table 2.6 - 1 (c) Dose - Response Values for Chronic Inhalation Exposure to Noncarcinogens

................................ ................................ ................................ ................................ .................. 16 Table 2.6 - 2 Dose - Response Values for Acute Exposure ................................ ........................ 19 Table 3.1 - 1 Summary

of Emissions from the Major Secondary Aluminum Production Source Category Facilities and Availability of Dose - Response Values ................................ .............. 23 Table 3.2 - 1 Summary

of Source Category

L evel Inhalation Risks for Major Secondary Aluminum Production Sources ................................ ................................ ................................ 27 **Appendices** Appendix 1 Technical Support Document for HEM - 3 Modeling Appendix 2 Meteorological Data for HEM - 3 Modeling Appendix 3 Analy sis of data on short - term emission rates relative to long - term emission

rates Appendix 4 Technical Support Document for T RI M - Based Multipathway Screening Scenario for RTR: Summary of Approach and Evaluation**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 3 Appendix 5 Draft Detailed Risk Modeling Results Appendix 6 Dispersion Model Receptor Revisions and Additions **Index of Acronyms** AERMOD American Meteorological Society /EPA Regulatory

Model AEGL Acute exposure guideline level ASTDR US Agency for Toxic Substances and Disease Registry CalEPA California Environmental Agency CTE Central Tendency Estimate ERPG Emergency Response Planning Guideline HAP Hazardous Air Pollutant HEM Human Exposure Model HI Hazard index HQ Hazard quotient IR IS Integrated Risk Information Sy stem MACT Maximum Achievable Control Technology MIR Maximum Individual Risk MOA Mode of action NAC National Advisory Committee NAAQS National Ambient Air Quality Standards NATA National Air Toxics Assessment NEI National Emissions Inventory NPRM Notice of Proposed Rulemaking PB - HAP Persistent and Bioaccumulative - HAP POM Polycyclic organic matter REL Reference exposure level RfC Reference concentration RfD Reference dose RME Reasonable Maximum Exposure RTR Risk and Technology TOSHI Target - organ - specific hazard index URE Unit risk estimate**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

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### 1 **Introduction** Section 112 of the Clean Air Act (CAA) establishes a two - stage regulatory process fo r 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 - based standards for categories of sources (e.g., petroleum refineries, pulp and paper mills, etc.) [ 1 ]. EPA has largel y 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 ye ars and revise a standard, as necessary , “taking into account developments in practices, processe s and control technologies.” In the second stage, EPA is required under section 112(f)(2) to assess the health and environmental risks that remain after implementation of the MACT standards. If additional risk reductions are necessary to protect public health with an ample margin of safet y or to prevent an adverse environmental effect, EPA must develop standards to address thes e remaining risks. This second stage of the regulatory process is known as the residual risk stage. For each source category for which EPA issued MACT standards, the residual risk stage must be completed within eight years of promulgation of the initial technology - based standard. In December of 2006 we consulted with a panel from the EPA's Science Advisory Board (SAB) on the “Risk and Technology Review (RTR) Assessment Plan , ” and in June of 2007, we received a letter with the results of that consultation. Subsequent to the consultation, in June of 2009 , a meeting was held with an SAB panel for a formal peer review of the “Risk and Technology

Review (RTR) Assessment Methodologies” [ 2 ]. We received the final SAB report on this review in May of 2010 [ 3 ]. Where appropriate, we have responded to the key messages from this review in developing our current risk assessment s and we will be continuing our efforts to improve our assessments by incorporating updates based on the SAB recommendations as they are developed and become 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 Risk Assessment Methodologies” [ 4 ]. This document cont ains the methods and the results of baseline risk assessments performed for the Secondary

Aluminum Pro duction source category . The methods discussion includes descriptions of the methods used to screen for acute health risks, chronic non - inhalation health risks, and adverse environmental effects, as well as descriptions of the methods used to develop refined estimates of chronic inhalation exposures and human health risks for cancer and noncancer endpoints. 

### 2 **Methods 2.1**  **Emissions and source data** Although there are 53 major sources and 108 area sources covered b y the subpart RRR MACT standards, 52 major sources and 103 area sources were modeled due to the other sources’ lack of equipment with applicable emission standards. Notabl y, while all HAP are covered und er MACT standards for major sources, only dioxins and furans are regulated under the MACT standards for area sources. Thus, the risk assessment presents two sets of**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 5 results. For major sources, we present risk results associated with all HAP emitted, and for area sources, we present risk results associated with dioxins and furans only. T he preli minary dataset for both major and area sources was based on information in an Infor mation Collection Request (I CR) sent to all facilities . The dataset for major sources was also based on a testing ICR sent to nine companies; the data from this testing I CR were used to develop speciation profiles for HAP metals and HAP organics. These ICR data were then used to develop the emissions dataset for this source category . W e performed an engineering review of the information to identify readil y 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 the emissions memo : Development of the RTR Risk Modeling Dataset for the Secondary

Aluminum Production Source Category , available in the docket for the proposed rulemaking . In addition, Section 3 below provides a brief summary of the emissions. 

### 2.2 **Dispersi on modeling for inhalation exposure assessment**  Both long - and short - term inhalation exposure concentrations and associated health risk 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 Model dispersion modeling s ys tem (HEM - 3 ). The approach used in appl yi ng this modeling s ys tem is outlined below, and further details are provided in Appendix 1 . HEM - 3 performs three main operations: atmosp heric dispersion modeling, estimation of individual human exposures and health risks, and estimation of population risks. This section focuses on the dispersion modeling component. The exposure and risk characterization components are discussed in other subsections of Sections 2 and 3. The dispersion model in the HEM - 3 sy stem is a state - of - the - science Gaussian plume dispersion model that is preferred b y EPA for modeling point, area, and volume sources of continuous air emissions from facilit y application s [ 5 ]. Further details on AERMOD can be found in the AERMOD Users Guide [ 6]. The model is used to develop annual average ambient concentrations through the simulation of hour - by - hour dispersion from the emission sources into the surrounding atmosphere. Hourl y emission rates used for this simulation are generated b y evenl y dividing the total annual emission rate from the inventory into the 8,760 hours of the ye ar. The first step in the application of the HEM - 3 modeling s ys tem 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 Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 6 **Table 2.2**  **- 1**  **AERMOD version 11103**  **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) Terrain characterization Actual from USGS 1 - degree DEM data Building downwash Not Included Plume deposition/depletion Not Included Urban source option No Meteorology 1 year representative NWS from nearest site ( over 200 stations) In HEM - 3 , meteorological data are ordinarily selected from over 200 National Weather Service (NWS) surface observation stations across the continental United States, Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is selected as representative of the conditions at the subject facility . Ideall y, when considering off - site meteorological data most site specific dispersion modeling efforts will employ up to five ye ars of data to capture variability

in weather patterns from ye ar to year. However, to minimize data processing time and resources for this assessment , we modeled only a single year, t ypically 1991. While the selection of a single ye ar may result in under - prediction of long - term ambient levels at some locations, likewise it may result in over - prediction at others. For each facility identified by

its characteristic latitude and longitude coordinates, the closest meteorological station was used in the dispersion modeling. The average distance between a modeled facility and the applicable meteorological station was 40 miles (72 km). Appendix 2 (Meteorological Data Processing Using AERMET for HEM - 3 ) provides a complete listing of stations and assumptions along with further details used in processing the data through AERMET. The sensitivity of model results to the selection of the nearest weather station and the use of one ye ar of meteorological data is discussed in “ Risk and Technology Review (RTR) Risk Assessment Methodologies ” [ 2 ]. The HEM - 3 sy stem estimates ambient concentrations at the geographic centroids of census blocks (using the 2000 Census) and at other receptor locations that can be specified b y the user. The model accounts for the impa cts of multiple facilities when estimating concentration impacts at each block centroid. Ty pi cally we combined only

the impacts of facilities within the same source category, and assessed chronic exposure and risk onl y for census blocks with at least one resident (i.e., locations where people may reasonably

be assumed to reside rather than recepto r 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 currentl y uninhabited areas wa s not**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 7 considered. Census blocks, the finest resolution available in the census data, are typically comprised of approximately 40 people or about ten households. In contrast to the development of ambient concentrations for evaluating long - term exposures, which was performed only for occupied census blocks, worst - case short - term (one - hour) concentrations were estimated both at the census block centroids and at point s nearer the facility that represent locations where people may be present for short periods, but generall y 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 facilit y property). Since short - term emission rates were needed to screen for the potential for hazard via acute exposures, and since the emissions data for this source category were based on annual emission totals, we ty pica lly appl ied the general as sumption to all source categories that the maximum one - hour emission rate from an y s ource w as ten times the average annual hourl y emission rate for that source . The average hourly emissions rate is defined as the total emissions for a ye ar divided by the t otal number of operating hours in the year. This choice of a factor of ten for screening was originally based on engineering judgment . To develop a more robust peak - to - mean emissions factor, and in response to one of the key messages from the SAB consult ation on our RTR Assessment Plan, we performed an anal ysis using a short - term emissions data set from a number of source s located in Texas (originally reported b y Allen et al
. 2004)[ 7]. In that report, the Texas Environmental Research Consortium Project co mpared hourly and annual emissions data for volatile organic compound s for all facilities in a heavily industrialized 4 - county

area (Harris, Galveston, Chambers, and Brazoria Counties , TX) over an eleven - month time period in 2001 . We obtained the dataset and performed our own anal ys is, focusing on sources which reported emitting high quantities of HAP over short periods of time ( see Appendix 3 , “ Analy sis of data on short - term emission rates relative to long - term emission rates”). Most peak emission events were less than twice the annual average, the highest was a factor of 74 times the annual average , and the 99 th percentile ratio of peak hourl y emission rate to the annual hourl y emission rate was 9. Based on these results, we chose the factor of ten for all initial screening; it 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 anal ys is of the data from the Texas Environmental Resear ch Consortium suggests that this factor should cover more than 99% of the short - term peak gaseous or volatile HAP emissions from ty pical industrial sources. We have no data relating specifically

to peak short - term emissions of particulate HAP. In the abs ence of source category - specific data, we use this same default approach for particulate emissions as well. 1

. Census block elevations for HEM - 3 modeling were determined nationally from the US Geological Service 1 - degree digital elevation model (DEM) d ata files, which have a spatial resolution of about 90 meters. Elevations of polar grid points used in estimating short - and long - term ambient concentrations were assumed to be equal to the highest elevation of any census block falling within the polar grid sector corresponding to the grid point. I f a sector does not contain an y blocks, the model defaults the elevation to that of the nearest block. If

1 In situations where we have information on hourly emissions, we will take this into account when evaluating acute risks.**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 8 an elevation is not provided for the emission source, the model uses the average elevation of all sector s within the innermost model ring. In addition to using receptor elevation to determine plume height, AERMOD adjusts the plume’s flow if nearb y el evated hills are expected to influence the wind patterns. For details on how hill heights were estimated an d used in the AERMOD modeling see Appendix 1 . 

### 2.3 **Estimating chronic**  **human inhalation exposure** We used the annual average ambient air concentration of each HAP at each census block centroid as a surrogate for the lifetime inhalation exposure concentration of all the people who reside in the census block. That is, the risk anal ysis did not consider either the short - term or long - term behavior (mobility ) of the exposed populations and its potential influence on their exposure. We did not address short - term human activity for two reasons. First, our experience with NATA assessments (which modeled dail y activity using EPA’s HAPEM model) suggests that, given our current understanding of microenvironment concentrations and daily activities, modeling short - term activity would, on average, reduce risk estimates about 25% for particulate HAPs; it will also reduce risk estimates for gaseous HAPs, but ty pically by much less. Second, basing exposure estimates on average ambient concentrations at census block centroi ds may

underestimate or overestimate actual exposure concentrations at some residences. Further reducing exposure estimates for the most highl y exposed residents b y modeling their short - term behavior could add a sy stematic low bias to these results. We d id 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 ass essing cancer risk, we generall y 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 assumption 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 si nce the total population number remains the same. It does, however, affect the shape of the distribution of individual risks across the affected population, shifting it toward higher estimated individual risks at the upper end and reducing the number of p eople estimated to be at lower risks, thereb y increasing the estimated number of people at specific risk levels. When screening for potentially significant acute exposures, we used an estimate of the highest hourly ambient concentration at any off - site lo cation as the surrogate for the maximum potential acute exposure concentration for an y individual. 

### 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 developing chronic health risk assessments for other rules under the residual risk program.**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 9 That is, we developed a tiered, iterative approach. This approach to risk assess ment was endorsed b y the National Academ y of Sciences in its 1993 publication “Science and Judgment in Risk Assessment” and subsequently was adopted in the EPA’s “Residual Risk Report to Congress” in 1999. With respect to screening for potential acute h ealth risk s , 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 began with a screening assessment, which relies on readil y available data and uses conservative assumptions that in combination approximate a worst - case exposure . The result of this screening process is that either the facility

being assessed poses no potential acute health risks (i.e., it “screens out”), or that it requires further , more refined assessment with respect to potential acute exposure s from emitted HAP . 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 site - specific data are used to refine the assess ment; 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 screening was performed for each facility as the first step. We used conservative assumptions for emission rates, meteorology , and exposure location. We used the following worst - case assumptions in our screening approach:

 Peak 1 - hour emissions were assumed to equal 10 times the average 1 - hour emission rates .  For facilities with multiple emission points, peak 1 - hour emissions were assumed to occur at all emission points at the same time.  For facilities with multiple emission points, 1 - hour concentrations at each receptor were assumed to be the sum of the maximum concentrations due to each emission point, regardless of whether those maximum concentrations occurred during the same hour.  Worst - case meteorology (from one ye ar at the nearest NWS site ) was assumed to occur at the same time the peak emission rates occur. The recommended EPA local scale dispersion model, AERMOD, wa s used for simulating atmospheric dispersion.  A person was assumed to be located downwind at the point of maximum modeled impact during this same worst - case 1 - hour period, but no nearer to the source than 100 meters. As a result, the maximum modeled 1 - hour off - site concentration equals the worst - case acute exposure concentration.  The maximum impact was compared to multiple sho rt - term health benchmarks for the HAP being assessed to determine whether a possible acute health risk might exist. These benchmarks are described in section 2.6 of this report. As mentioned above, when we identify acute impacts which exceed their relevant benchmarks, we pursue refining our acute screening estimates to the extent possible . For example, this may include the use of a facility - specific emissions multiplier to estimate the**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 10 peak hourl y emission rates from the average rates (rather than using the default factor of 10 ) and/or determining the actual phy sical layout and boundaries of a facility to more accurately gauge where people might reasonabl y be exposed for an hour. 

### 2.5 **Multipathway human health**  **and env**  **ironmental risk screening**  The potential for significant human health risks and adverse environmental impacts due to exposures via routes other than inhalation (i.e., multipathway exposures) was screened b y first determining whether an y sources emitted an y hazardous air pollutants known to be per sistent and bioaccumulative in the environment (PB - HAP). The PB - HAP compounds or compound classes are identified for the screening from the EPA’s Air Toxics Risk Assessment L ibrary [ 8 ], and they

are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury compounds, methoxychlor, polychlorinated biphenyls, pol yc yclic organic matter (POM) , toxaphene, and trifluralin . With respect to PB - HAP other than lead, emis sions were evaluated for potential non inhalation risks and adverse environmental impacts using our recentl y - developed screening scenario which was developed for use with the TRIM.FaTE 2 model. This screening scenario uses environmental media outputs from the peer - reviewed TRIM.FaTE to estimate the maximum potential ingestion risks for any specified emission scenario b y using a generic farming/fishing exposure scenario that simulates a subsistence environment. The screening scenario retains man y of the ing estion and scenario inputs developed for EPA’s Human Health Risk Assessment Protocols (HHRAP) for hazardous waste combustion facilities. 3 In the development of the screening scenario a sensitivity anal ys is was conducted to ensure that its key design param eters were established such that environmental media concentrations were not underestimated, and to also minimize the occurrence of false positives for human health endpoints. See Appendix 4 for a complete discussion of the development and testing of the screening scenario, as well as for the values of facility - level screening emission rates developed for screening potentially significant multi - pathway impacts. Ingeneral, f

or the purpose of developing emission rates for our multi - pathway screening, we de rived emission levels for each PB HAP 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. In evaluating the potential multi - pathway risks from emissions of lead compo unds, rather than developing a screening emission rate, we generally compare maximum estimated chronic (3 - month average) atmospheric concentrations with the current primary National Ambient Air Quality Standard (NAAQS) for lead. Values be low the NAAQS are considered to have a low potential for multi - pathway risks. Notabl y, for this source category , dioxins and furans, POM , and cadmium w ere the PB - HAP identified in the emissions inv entory. We also evaluated the potential for significant direct environmental exposures to HAP by
2 EPA’s Total Risk Integrated Methodology (General Information) http://epa.gov/ttn/fera/trim_gen.html 3 EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous Waste Combustion Facilities; http://www.epa.gov/epaoswer/hazwaste/combust/riskvol.htm#volume1**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 11 evaluating the potential for exceedances of chronic human health inhalation reference value s in the ambient air near these facilities. Human health dose - response reference values are generall y derived from studies conducted on laboratory animals (such as rodents) and developed with the inclusions of uncertainty factors that could be as high as 3000. As a result, these human reference values are often significantly lower than the level expected to cause an adverse e ffect in an exposed rodent. It should be noted that there is a scarcity of data on the direct atmospheric impact of these HAP on other receptors, such as plants, birds, and wildlife. Thus, if the maximum inhalation hazard in an ecos ys tem is below the lev el of concern for humans (i.e. , is below the human health reference value which is itself a lower reference value than would be expected for an ecologic effect) , we have generall y concluded that mammalian receptors should be at no risk of adverse effects d ue to inhalation exposures from non - PB - HAP, and have assurance that other ecological receptors are also not at any significant risk from direct atmospheric impact. In some isolated cases where we have data indicating potential adverse impacts on plants, b irds, or other wildlife due to the direct atmospheric impacts of specific HAP, we note that as an uncertainty and, where possible, refine our anal ys is by

comparing our modeled impacts to available reference values from the scientific literature. 

### 2.6 **Dose -**  **r esp**  **onse 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 Secondary Aluminum P ro duction sources were based on the EPA Office of Air Quality Planning and Standards’ (OAQPS) existing recommendations for HAP [ 9 ], also used for NATA [ 10 ]. This information has been obtained from various sources and prioritized according to (1) conceptua l 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 ty

pically 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 “an estimate (with uncertaint y spanning perhaps an order of magnitude) of a dail y oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. ” The URE is defined as “ the upper - bound excess cancer risk estimated to result from continuous lifetime exposure to an agent at a concentration of 1 μg/m 3 in**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 12 air. ” The SF is “an upper bound, approximating a 95% confidence limit, on the increas ed cancer risk from a lifetime exposure to an agent. This estimate, [is] usually expressed in units of proportion (of a population) affected per mg/kg - day ...” EPA disseminates dose response assessment information in several forms, based on the level of revi ew. The Integrated Risk Information Sy stem (IRIS) [ 11 ] is an EPA database that contains scientific health assessment information, including dose - response information. All IRI S assessments since 1996 have also undergone independent external peer review. Th e current IRI S process includes review by EPA scientists, interagency reviewers from other federal agencies, and the public, and peer review b y independent scientists external to EPA. New IR IS values are developed and old IRI S values are updated as new he alth effects data become available. Refer to the “IRI S Track” website for detailed information on status and scheduling of current individual IRI S assessments and updates ( http://cfpub.epa.gov/nce a/iristrac/index.cfm )

. EPA’s science policy approach , under the current carcinogen guidelines, is to use linear low - dose extrapolation as a default option for carcinogens for which the mode of action (MOA) has not been identified. We expect future EPA dose - response assessments to identify nonlinear MOAs where appropriate, and we will use those analy ses (once they are peer reviewed) in our risk assessments. At this time, however, there are no available carcinogen dose - response assessments for inhalation exposure that are based on a nonlinear MOA
. 2) US Agency

for Toxic Substances and Disease Registry (ATSDR). ATSDR, which is part of the US Department of Health and Human Services, develops and publishes Minimum Risk L evels (MRLs) [ 12 ] for inhalation and oral exposure to many toxic substances. As stated on the ATSDR web site: “ Following discussions with scientists within the Department of Health and Human Services (HHS) and the EPA, ATSDR chose to adopt a practice similar to that of the EPA's Reference Do se (RfD) and Reference Concentration (RfC) for deriving substance specific health guidance levels for non neoplastic endpoints .” The MRLis defined as “an estimate of dail y 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 MRL s as substance - specific estimates to be used by health assessors to select environmental contaminants for further evaluation. Exposures above an MRL do not nec essarily represent a threat, and MRLs are therefore not intended for use as predictors of adverse health effects or for setting cleanup levels. 3) California Environmental Protection Agency (CalEPA). The CalEPA Office of Environmental Health Hazard Assessme nt 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 signifi cant external scientific peer review. As cited in the CalEPA Technical Support Document for developing their chronic assessments 4 : “The guidelines for developing chronic inhalation exposure levels incorporate many recommendations of the U.S. EPA [ 13 ] and NAS [ 14 ].” The non - cancer information

4 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III - Technical Support Docume nt for the Determination of Non - cancer Chronic Reference Exposure Levels. Air Toxicology and Epidemiology Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. February 2000 ( http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf )**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 13 includes available inhalation health risk guidance values expressed as chronic inhalation reference exposure levels (REL s) [ 15 ]. CalEPA defines the RELas “the concentration level at or below which no health effects are anticipated in the general human population.” CalEPA's quantitative dose - response information on carcinogenicity by inhalation exposure is expressed in terms of the URE [ 16], defined similarly to EPA's URE. In developing chronic risk estimates, we adj usted dose - response values for some HAPs based on professional judgment, as follows: 1) In the case of HAP categories such as gl ycol ethers and cyanide compounds, the most conservative dose - response value of the chemical category i s used as a surrogate for other compounds in the group f or which dose - response values are not available. This i s done in order to examine, under conservative assumptions, whether these HAPs that lack dose response values may

pose an unacceptable risk and require further examinatio n, or screen out from further assessment. 2) Where possible for emissions of unspecified mixtures of HAP categories such as POM (see Tables 2.6 - 1 (a) to 2.6 - 1 (c) , we appl y category - specific chemical speciation profiles appropriate to the source category to develop a composite dose - response value for the category . 3) Emissions from Secondary Aluminum Pro duction facilities include POM. Some of the POM reported to EPA’s national emission inventory (NEI) are not s pe ciated int o individual compounds. As a result, it is necessary to appl y the same s implifying a ssumptions to assessments that were used for the 1999 NATA study [ 17]. The NATA approach partitions POM into eight different non - overlapping “groups” that are modeled as separate pollutants. Each POM group comprises POM species of similar carcinogenic potency , for which we can apply the same URE. The emissions inventory

for the Secondary

Aluminum Pro duction source category includes emissions of HAP with availa b le chr onic quantitative inhalation dose - response values. These HAP, their dose - response values, and the source of the values are listed in Tables 2.6 - 1 (a) through (c).**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 1 4

**Table 2.6 -**  **1 (a) Dose -**  **Response Values for Chronic Inhalation Exposure to Carcinogens**  URE (unit risk estimate for cancer) 5 = 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 Qu ality Planning and Standards. EPA ORD = EPA Office of Research and Development **Pollutant CA** **S Number 6**  **URE 5**  **(1/μg/m 3**  **) Source**  1,1,1 - trichloroethane 79005 0.000016 IR IS 1,1,2 - trichloroethane 79005 0.000016 IR IS 1,3 - dichloropropene 542756 0.000004 IR IS 2,3,7,8 - tetrachlorodibenzo - p dioxin 1746016 33 EPA ORD Acrylonitrile 107131 0.000068 IR IS Arsenic Compounds 7440382 0.0043 IR IS Benzene 7 71432 0.0000078 IR IS Beryl lium Compounds 7440417 0.0024 IR IS Cadmium Compounds 7440439 0.0018 IR IS Carbon Tetrachloride 56235 0.000006 IR IS Chloroprene 126998 0.00048 IR IS Chromium Compounds Chromium (VI) 18540299 0.012 IR IS Ethylene Dichloride 107062 0.000026 IR IS Ethylidene Dichloride 107062 0.000026 IR IS Methylene Chloride 75092 0.00000047 IR IS Naphthalene 91203 0.000034 CAL Nickel Compounds 7440020 0.00048 EPA OAQPS 8
5 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. 6 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have used a surrogate 3 - digit identifier corresponding to the group’s position on the CAA list of HAPs. 7 The EPA IRI S assessment for benzene provides a range of plausible UREs. This assessment used the highest value in that range, 7.8E - 06 per ug/m 3 . The low end of the range is 2.2E - 06 per ug/m 3

. 8 The EPA IRIS assessments for nickel compounds provide a range of plausi ble UREs. This assessment used the highest value in that range which is equal to the URE for nickel subsulfide, 4.8E - 04 per ug/m3 . The low end of the range is equal to 50% of the URE for nickel subsulfide, 2.4E - 04 per ug/m3

.**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 15 **Table 2.6 -**  **1 (a) Dose -**  **Response Values for Chronic Inhalation Exposure to Carcinogens**  URE (unit risk estimate for cancer) 5 = 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 Qu ality Planning and Standards. EPA ORD = EPA Office of Research and Development **Pollutant CA** **S Number 6**  **URE 5**  **(1/μg/m 3**  **) Source**  Polycyclic Organic Matter Chry sene 218019 0.0000176 CAL Benz[a]anthracene 56553 0.000176 CAL Benzo[b]fluoranthene 205992 0.000176 CAL Benzo[k] fluoranthene 207089 0.000176 CAL Benzo[a]py

rene 50328 0.00176 CAL In deno[1,2,3 - c,d]py

rene 193395 0.000176 CAL Dibenzo[a,h]anthracene 53703 0.0019184 CAL Propylene Dichloride 78875 0.000019 Conv. Oral Tetrachloroethene 127184 0.0000059 CAL Trichloroeth yl ene 79016 0.000002 CAL **Table 2.6**  **- 1 (b)**  **Dose -**  **Response Values for Chronic Oral Exposure to Carcinogens** SF (oral slope factor for cancer) = cancer risk per mg/kg/d of average lifetime exposure. Sources : IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards. **Pollutant CA** **S Number** 10 **SF (1/mg/kg/d)**  **Source** 2,3,7,8 - tetrachlorodibenzo - p - dioxin 1746016 150000 EPA ORD Polycyclic Organic MatterPOM Benz[a]anthracene 56553 1.2 CAL Benzo[b]fluoranthene 205992 1.2 CAL Benzo[k]fluoranthene 207089 1.2 CAL Benzo[a]py

rene 50328 7.3 IR IS**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 16

**Table 2.6**  **- 1 (c) Dose**  **- Response Values for Chronic Inhalation Exposure to Noncarcinogens**  RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of ma gnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of de leterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry. **Pollutant CA** **S Number 6**  **RfC (mg/m3)**  **Source 9**  1,1,1 - trichloroethane 71556 5 IR IS - M 1,1,2 - trichloroethane 79005 0.4 CAL 1,3 - dichloropropene 542756 0.02 IR IS - H Acrylonitrile 107131 0.002 IR IS - M Antimony

Compounds 7440360 0.0002 IR IS - L Arsenic Compounds 7440382 0.000015 CAL Benzene 71432 0.03 IR IS - M Beryl lium Compounds 7440417 0.00002 IR IS - M Cadmium Compounds 7440439 0.00001 ATSDR Carbon Disulfide 75150 0.7 IR IS - M Carbon Tetrachloride 56235 0.1 IR IS - M Chloroform 67663 0.098 ATSDR Chloroprene 126998 0.02 IR IS

– M/H Chromium (VI) Compounds 18540299 0.0001 IR IS - M Cobalt Compounds 7440484 0.0001 ATSDR Dioxins/furans 51207319 0.0000004 CAL Ethylene Dichloride 107062 2.4 ATSDR Ethylidene Dichloride 107062 2.4 ATSDR Hydrochloric Acid 7647010 0.02 IR IS - L Lead Compounds 7439921 0.00015 EPA OAQPS Manganese Compounds 7439965 0.00005 IR IS - M Mercury Compounds 184 0.0003 IR IS - M Mercuric Chloride 7487947 0.0003 IR IS - M Mercury (elemental) 7439976 0.0003 IR IS - M Methylene Chloride 75092 1 ATSDR Naphthalene 91203 0.003 IR IS - M Nickel Compounds 7440020 0.00009 ATSDR Propylene Dichloride 75569 0.03 IR IS - M Selenium Compounds 7782492 0.02 CAL Tetrachloroethene 127184 0.27 ATSDR Toluene 108883 5 IR IS - H

9 The descriptors L (low), M (medium), and H (high) have been added for IRIS RfC values to indicate the overall level of confidence in the RfC value, as reported in the IRIS file.**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 17 **Table 2.6**  **- 1 (c) Dose**  **- Response Values for Chronic Inhalation Exposure to Noncarcinogens**  RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of ma gnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of de leterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry. **Pollutant CA** **S Number 6**  **RfC (mg/m3)**  **Source 9**  Trichloroeth yl ene 79016 0.6 CAL Vinylidene Chloride 75354 0.2 IR IS

– H/M **2.6.2 Sources of acute dose**  **- response information**  Hazard identification and dose - response assessment information for preliminary acute inhalation exposure assessments is based on the existing recommendations of OAQPS for HAPs [ 18 ] . Depending on availability , the results from screening acute assessments are compared to both “no effects” reference levels for the general public, such as the California Reference Exposure Levels (REL s), as well as emergency response levels, su ch as Acute Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelines (ERPGs), with the recognition that the ultimate interpretation of an y potential risks associated with an estimated exceedance of a particular reference level depends o n the definition of that level and an y limitations expressed therein. Comparisons among different available inhalation health effect reference values (both acute and chronic) for selected HAPs can be found in an EPA document . 10 **California Acute Reference Exposure Levels (RELs**  **).** The California Environmental Protection Agency

(CalEPA) has developed acute dose - response reference values for man y substances, expressing the results as Acute inhalation Reference Exposure Levels (RELs). The acute REL (http://www.oehha.ca.gov/air/pdf/acuterel.pdf ) is defined by

CalEPA as “ the concentration level at or below which no adverse health effects are anticipated for a specified exposure duration . [ 19 ] . REL s are based on the most sensitive, relevant, adverse health effect reported in the medical and toxicological literature. REL s are designed to protect the most sensitive individuals in the population by the inclusion of margins of safety . Since margins of safety are incorporated to address data gaps and uncertainties, exceeding the REL does not automatically

indicate an adverse health impact. ” Acute RELs are developed for 1 - hour (and 8 - hour) exposures. The values incorporate uncertainty

factors similar to those used in deriving EPA’s Inhalation Reference Concentrations (RfCs) for chronic exposures (and, in fact, California also has developed chronic RELs). **Acute Exposure Guideline Levels (AEGLs** ). AEGL s are developed by the National Advisory
10 See : U.S. EPA. Graphical Arrays of Chemical - Specific Health Effect Reference Values for Inhalation Exp osures [Final Report]. (U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R - 09/061, 2009. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003.)**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 18 Committee (NAC) on Acute Exposure Guideline Levels (NAC/AEGL) f or Hazardous Substances , and then reviewed and published b y the National Research Council . A s described in the Committee’s “Standing Operating Procedures (SOP) ” ( http://www.epa.gov/opptintr/aegl/pubs/sop.pdf ), AEGLs “represent threshold exposure limits for the general public and are applicable to emergency exposures ranging from 10 min to 8 h.” Their intended application is “for conducting risk asses sments 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 AEGLprogram and the NAC/AEGLCommittee is to develop guideline levels for once - in - a - lifetime , short - term exposures to airborne concentrations of acutel y toxic, high - priority chemicals.” In detailing the intended application of AEGL values, the doc ument 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 pr evention 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 r eleases 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, irritation, or certain asy mptomatic nonsensory

effects. However, the effects are not disabling and are transient and reversible upon cessation of exposure. ”

“ AEGL - 2 is the airborne concentration (e xpressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, including susceptible individuals, could experience irreversible or other serious, long - lasting adverse health effects or an impaired ability to escape. ”

“ A irborne concentrations below AEGL - 1 represent exposure levels that can produce mild and progressivel y increasing but transient and nondisabling odor, taste, and sensory irritation or certain as ymptomatic, nonsensory effects. With increasing airborne concentrations above each AEGL, there is a progressive increase in the likelihood of occurrence and the severity of effects described for each corresponding AEGL . Although the AEGL values represent threshold levels for the general public, including susceptible subpopulations, such as infants, children, the elderly , persons with asthma, and those with other illnesses, it is recognized that individuals, subject to unique or idiosy ncratic 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) [ 20 ] for acute exposures at three different levels of severity . These guidelines represent concentrations for exposure of the general population (but not particularly sensitive persons)**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 19 for up to 1 hour associated with effects expected to be mild or transient (ERPG - 1), irreversible or serious (ERPG - 2), and potentially life - threatening (ERPG - 3). ERPG values ( http://www.aiha.org/1documents/Committees/ERP - erpglevels.pdf ) are described in their supporting documentation as fol lows: “ 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 values) are intend ed for use as planning tools for assessing the adequacy of accident prevention and emergency response plans, including transportation emergency planning and for developing community emergency

response plans. The emphasis is on ERPGs as planning values: When an actual chemical emergency occurs there is seldom time to measure airborne concentrations and then to take action. ” ERPG - 1 and ERPG - 2 values are defined by

AIHA as follows:

“ ERPG - 1 is the maximum airborne concentration below which it is believed th at nearl y all individuals could be exposed for up to 1 hour without experiencing other than mild transient adverse health effects or without perceiving a clearly defined, objectionable odor. ”

“ ERPG - 2 is the maximum airborne concentration below which it is believed that nearl y all individuals could be exposed for up to 1 hour without experiencing or developing irreversible or other serious health effects or s ymptoms which could impair an individu al's ability to take protective action. ” The emissions inventory

for the Secondary

Aluminum Pro duction source category includes emissions of two 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 - 2.

**Table 2.6 -**  **2 Dose -**  **Response Values for Acute Exposure Pollutant**  **CA S 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**  1,1,1 - Trichloroethane (methyl chloroform) 71556 1300 3300 1900 3800 68 Acrylonitrile 107131 10 130 22 77 Benzene 71432 170 2600 160 480 1.3 Beryl lium compounds 7440417 0.025 Carbon disulfide 75150 40 500 3.1 160 6.2 Carbon tetrachloride 56235 280 1200 130 630 1.9 Chloroform 67663 310 240 0.15 Ethylene dichloride 107062 200 810 Hydrochloric acid 7647010 2.7 33 4.5 30 2.1 Mercury (elemental) 7439976 1.7 2 0.0006 Methylene chloride 75092 690 1900 1000 2600 14**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 20

**Table 2.6 -**  **2 Dose -**  **Response Values for Acute Exposure Pollutant**  **CA S 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**  Nickel compounds 7440020 0.006 Tetrachloroethene 127184 240 1600 680 1400 20 Trichloroeth yl ene 79016 700 2400 540 2700 Toluene 108883 750 4500 190 1100 37 

### 2.7 **Risk c**  **haracterization 2.7.1**  **General** The final product of the risk assessment is the risk characterization, in which the information from the previous steps is integrated and an overall conclusion about risk is sy nthesized that is complete, informative, and useful for decision makers. In gen eral, the nature of this risk characterization depends on the information available, the application of the risk information and the resources available. In all cases, major issues associated with determining the nature and extent of the risk are identifi ed and discussed. Further, the EPA Administrator’s March 1995 Policy for Risk Characterization [ 21 ] specifies that a risk characterization “be prepared in a manner that is clear, transparent, reasonable, and consistent with other risk characterizations of similar scope prepared across programs in the Agency .” These principles of transparency

and consistency

have been reinforced by

the Agency’s Risk Characterization Handbook [ 22 ], in 2002 by the Agency ’s information quality guidelines [ 23 ], and in the OMB/OST P September 2007 Memorandum on Updated Principles for Risk Analy sis 11 , 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 analy tical approach, we have attempted to reduce both uncertainty

and bias to the greatest degree possible in these assessments, within the limitations of available time and resources. We provide summaries of risk metrics (including maximum individual cancer risks and noncancer hazards, as well as cancer incidence estimates) along with a discussion of the major uncertainties associated with their derivation to provide decision makers with the fullest picture of the assessment and its limitations. For each carcinogenic HAP included in an assessment that has a potency estimate available, individu al and population cancer risks we re calculated by multiplying the corresponding lifetime average exposure estimate by the appropriate URE. This calculated cancer risk is defined as the upper - bound probability of developing cancer over a 70 - y r period (i.e., the

11 Memorandum f

or the Heads o f Executive Departments and Agencies - Updated Principles for Risk Analysis ( September 19, 2007 ), From Susan E. Dudley, Administrator, Office of Information and Regulatory Affairs, Office of Management and Budget; and Sharon L. Hays, Associate Director and Deputy Director for Science, Office of Science and Technolog y Policy ( http://www.whitehouse.gov/omb/memoranda/fy2007/m07 - 24.pdf )**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 21 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 b y a mutagenic mode - of - action [ 24 ], we applied EPA’s Supplemental Guidance for Assessing Susceptibility from Early
- Life Exposure to Carcinogens [ 25 ] . 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 ye ars of exposure beginning at birth), as needed in risk assessments . In this case, this has the effect of increasing the estimated life time risks for these pollutants by a factor of 1.6. Inaddition, although onl y a small fraction of the total POM emissions may be reported as individual compounds, EPA expresses carcinogenic potency for compounds in this group in terms of benzo[a]py rene equivalence, based on evidence that carcinogenic POM have the same mutagenic mechanism of action as does benzo[a]py rene. For this reason , EPA implem entation policy [ 26] recommends appl yi ng the Supplemental Guidance to all carcinogenic PAH s for which risk estimates are based on relative potency . Accordingl y, we applied the Supplemental Guidance to all unspeciated POM mixtures. In creased cancer incidence for the entire receptor population within the area of anal ys is wa s estimated by

multip lying the estimated lifetime cancer risk for each census block by the number of people residing in that block, then summing the results for the entire modeled domain. This lifetime population incidence estimate wa s divided by 70 years to obtain an estimat e of the number of cancer cases per ye ar. Unlike linear dose - response assessments for cancer, noncancer health hazards generally are not expressed as a probability of an adverse occurrence. Instead, “risk” for noncancer effects is expressed by

comparing an exposure to a reference level as a ratio. The “hazard quotient” (HQ) is the estimated exposure divided by a reference level (e.g., the RfC). For a given HAP, exposures at or below the reference level (HQ ≤1) are not likel y to cause adverse health effec ts. As exposures increase above the reference level (HQs increasingl y greater than 1), the potential for adverse effects increases. For exposures predicted to be above the RfC, the risk characterization includes the degree of confidence ascribed to the R fC values for the compound(s) of concern (i.e., high, medium, or low confidence) and discusses the impact of this on possible health interpretations. The risk characterization for chronic effects other than cancer is expressed in terms of the HQ for inha lation, calculated for each HAP at each census block centroid. As discussed above, RfCs incorporate generally conservative uncertainty factors in the face of uncertain extrapolations, such that an HQ greater than one does not necessarily suggest the onset of adverse effects. The HQ cannot be translated to a probability that adverse effects will occur, and is unlikely

to be proportional to adverse health effect outcomes in a population . Screening for potentially

significant acute inhalation exposures also followed the HQ approach. We divided the maximum estimated acute exposure by each available short - term threshold value to develop an array of HQ values relative to the various acute endpoints and thresholds. In general, when none of these HQ values are greater than one, there is no**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 22 potential for acute risk. In those cases where HQ values above one are seen, additional information is used to determine whether there is a potential for significant acute risks. **2.7.2 Mixtures**  Since most or all receptors in these assessments receive exposures to multiple pollutants rather than a single pollutant, we estimated the aggregate health risks associated with all the exposures from a particular source category combined. To combine risks across multiple carcinogens, our a ssessments use the mixtures guidelines’ [ 27 , 28 ] default assumption of additivity of effects, and combine risks by summing them using the independence formula in the mixtures guidelines. In assessing noncancer hazard from chronic exposures, in cases where di fferent pollutants cause adverse health effects via completel y different modes of action, it may be inappropriate to aggregate HQs. In consideration of these mode - of - action differences, the mixtures guidelines support aggregating effects of different subs tances in specific and limited way s. 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 organ s ys tem. A ll TOSHI calculations presented here were based exclusively on effects occurring at the “ c ritical dose” (i.e., the lowest dose that produces adverse health effects). Although HQs associated with some pollutants have been aggregated into more than one TOSHI , this has been done only in cases where the critical dose affects more than one target o rgan . Because impacts on organs or s ys tems that occur above the critical dose have not been included in the TOSHI calculations, some TOSHIs may have been underestimated. As with the HQ, the TOSHI should not be interpreted as a probability of adverse effe cts, or as strict delineation of “safe” and “unsafe” levels. Rather, the TOSHI is another measure of the potential for adverse health outcomes associated with pollutant exposure, and needs to be interpreted carefully

by health scientists and risk managers . Because of the conservative nature of the acute inhalation screening and the variable nature of emissions and potential exposures, acute impacts were screened on an individual pollutant basis, not using the TOSHI approach. **2.7.3 Facility**  **- wide**  **r isks**  To help p lace the source category risks in context, we ty

picall y examine “facility - wide” risks using facility - wide and source category data files developed by

EPA thr ough emission data updates from industry

and refined EPA profiles for the source category . F or this source category , a facility - wide assessment was performed for major sources .**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 23 

### 3 **Risk r** **esults for the Secondary**  **A luminum**  **production s**  **ource c**  **ategory 3.1**  **Source c**  **ategory d**  **escription and r**  **esults** The Secondary

Aluminum Production source category consists of facilities that process scrap aluminum, including size reduction and removal of oils, coatings, and other contaminants . Furnace operations at these facilities includ e melting, holding, fluxing and tapping of molten aluminum . There are approximately 160 facilities subject to the S econdary A luminum NESHAP operating in the U.S. (including both major and area sources). We performed risk modeling for 155 of these sources (52 major and 103 area sources). The sources that were not modeled consisted of area sources that did not have equipment that were subject to the area source dioxins/furans limits, and a single major source with only Group 2 furnaces (which are not subject to emission limits under the secondary aluminum N ESHAP). The emissions in the Secondary

Aluminum Pro duction source category NPRM data set for major sources are summarized in Table 3.1 - 1. The total HAP emissions for the major source facilities in the source category

are approximately 900 tons per year. Air emissions from Secondary Aluminum Production major sources inclu de HAP such as hydrochloric a cid , polycyclic organic matter (POM), benzene , dioxin, and naphthalene. With respect to the 103 area sources in the secondary

aluminum production source category , we note that a total of 0.000007 tons per year of dioxin/furans (TEQ) is emitted. **Table 3.1**  **- 1**  **Summary of Emissions from the Major**  **Secondary Aluminum Production**  **Source**

**Category Fa**  **cilities and Availability of Dose**  **- Response Values** 

**HAP a**  **Emission**

**Estimates (tpy)**  **Number of**

**Facilities where HAP**  **Repor ted or**  **Estimated (**  **52 facilities**  **in NPRM**  **data set) Prioritized Inhalation Dose**  **- Response Value**  **Identified by OAQPS b**  **PB**   ** HAP?** **Unit Risk Estimate for**  **Cancer? Reference** 

**Concentration for**  **Chronic Noncancer**  **? Health** 

**Benchm ark**  **Values for Acute Noncancer?**  Hydrochloric Acid 892 50   Methylene Chloride 21 19    Polycyclic Organic Matter Chry sene 0.04 20   Benz[a]anthracene 0.03 20   Benzo[b]fluoranthene 0.0006 20   Benzo[k]fluoranthene 0.00009 7   Benzo[a]py

rene 0.00002 7   In deno[1,2,3 - c,d]py rene 0.00001 7   Dibenzo[a,h]anthracene 0.00001 7   Benzene 1 19   **Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 24 **Table 3.1**  **- 1**  **Summary of Emissions from the Major**  **Secondary Aluminum Production**  **Source**

**Category Fa**  **cilities and Availability of Dose**  **- Response Values** 

**HAP a**  **Emission**

**Estimates (tpy)**  **Number of**

**Facilities where HAP**  **Repor ted or**  **Estimated (**  **52 facilities**  **in NPRM**  **data set) Prioritized Inhalation Dose**  **- Response Value**  **Identified by OAQPS b**  **PB**   ** HAP?** **Unit Risk Estimate for**  **Cancer? Reference** 

**Concentration for**  **Chronic Noncancer**  **? Health** 

**Benchm ark**  **Values for Acute Noncancer?**  Tetrachloroethene 1 19    Naphthalene 1 20   Carbon Disulfide 1 19   Acrylonitrile 0.4 19    Manganese Compounds 0.3 51  Ethylene Dichloride 0.2 19    Trichloroeth yl ene 0.1 19    Lead Compounds 0.1 51 c  Chloroform 0.08 19   Chromium Compounds

  Chromium (III) 0.05 51 Chromium (VI) 0.0002 51   Toluene 0.03 19   Nickel Compounds 0.02 51    Antimony

Compounds 0.02 51  Cadmium Compounds 0.01 51    Carbon Tetrachloride 0.01 19    Selenium Compounds 0.004 51  Cobalt Compounds 0.002 51  Arsenic Compounds 0.002 51   1,3 - dichloropropene 0.002 6   Beryl lium Compounds 0.0007 51    Mercury Compounds Mercury (elemental) 0.0004 51    Mercuric Chloride 0.0001 51   Vinylidene Chloride 0.0002 6  Chloroprene 0.0001 6   1,1,1 - trichloroethane 0.00008 6   Propylene Dichloride 0.00008 6   1,1,2 - trichloroethane 0.00008 6   Ethylidene Dichloride 0.00006 6   dioxin /furans (TEQ) c 0.00002 46    a Notes for how HAP were speciated for risk assessment:  There were 15 total facilities, but actual emission estimates were not provided for the Columbia Falls facility.  For emissions of any chemicals or chemical groups classified as polycyclic organic matter (POM), emissions were grouped into POM subgroups as found on EPA’s Technology Transfer Network website for the 2002 National - Scale Air**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 25 Toxics Assessment at http://www.epa.gov/nata2002/methods.html#pom . ( Approach to Modeling POM ). For this source category, all POMs are PAHs. b Specific dose - response values for each chemical are identified on EPA’s Technology Transfer Network website for air toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html . C C hlorinated dibenzodioxins and furans were modeled and analyzed as 2,3,7,8 - tetrachlorodibenzo - p - dioxin equivalent . 

### 3.2 **Baseline r**  **isk c**  **haracterization** This section presents the results of the risk assessment for the Secondary Aluminum Pro duction source category based on the modeling methods described in the previous sections . All baseline risk results are developed using the best estimates of actual and MACT - allowable HAP emissions. The basic chronic inhalation risk estimates presented here are the maximum ind ividual lifetime cancer risk, the maximum target organ specific chronic hazard index, and the cancer incidence. We also present results from our acute inhalation impact screening assessments in the form of maximum hazard quotients, as well as the results of our 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 at the highest exposure location . A detailed summary of the facility specific risk assessment results is available in Appendix 5 . Table 3 .2 - 1 summarize s the preliminary chronic and acute inhalation risk results for this source category . T he results of the chronic inhalation cancer risk assessment for majo r sources indicate s that the maximum lifetime individual cancer risk , consi dering actual emissions , could be up to 1 in a million , driven by primarily by dioxin emissions from group 1 furnaces handling other than clean charge . The maximum cancer risks for this source category exceeded a cancer risk of 1 in a million at 1 of 52 f acilities. The total estimated cancer incidence from this source category based on actual emission levels is 0.00 06 excess cancer cases per year, or one excess case in every 1,666 ye ars. No people were estimated to have cancer risks above 10 in a million and approximately 2 people were estimated to have cancer risks above 1 in a million considering all major source facilities in this source category . Ba sed on MACT - allowable emissions for th e major source s in this category , the MIR could be up to 2 0 in a million for the facilities presented in Table 3.2 - 1 - driven mostly by dioxins from group 1 furnaces handling other than clean charge and POM emissions from scrap dryers . With respect to chronic inhalation non cancer risk from major sources, we estimate a maximum TOSHIvalue of 0.05 for the Secondary Aluminum source category , primarily from hydrochloric acid (HCL) from Group 1 furna ces (handling clean charge only). Considering MACT - allowable emissions, this maximum TOSHI value is estimated to be 1 driven b y HC L from Group 1 furna ces (handling clean charge only) and scrap dryers. Considering facility - wide emissions at the 5 2 major sources, the M IR i s estimated to be 2 0 in a million driven by

POM emissions and the chr onic non - cancer TOHSI value is calculated to be 0. 4 driven b y emissions of chlorine . In addition to the facilities presented in Table 3.2 - 1, we also estimated risk s associated with dioxi n emissions at the 103 area sources in the Secondary Aluminum Production S ource category . The results of th e cancer assessment indi cate that cancer risk could be as high as**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 26 0.4 in a million from Group 1 furna ces (handling other than clean charge) . Considering MACT - allowable emissions, the MIR could be up to 6 in a million from Group 1 furna ces (handling other than clean charge) . With respect to chronic inhalation non cancer risk from dioxin emissions, we estimate a maximum TOSHI value of 0.0003 f rom Group 1 furna ces (handling other than clean charge ) . Considering MACT - allowable emissions for area sources , this maximum TOSHIvalue is estimated to be 0.00 5 from Group 1 furna ces (handling other than clean charge) .**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 27 **Table 3.2 -**  **1 Summary of S**  **ource Category Level Inhalation Risks f or**  **Major Secondary**  **Aluminum Production**  **Sources Based on Actual Emissions**  **Result HAP “Drivers”**  **Facilities in Source Category** Number of Facilities Estimated to be i n Source Category 52 n/a Number of Facilities Identified in NEI and Modeled in Preliminary Risk Assessment 52 n/a **Cancer Risks** Maximum Individual Lifetime Cancer Risk (in 1 million) 1 Dioxins/furans Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 0 n/a Greater than or equal to 1 in 1 million 1 n/a **Chronic Noncancer Risks** Maximum Respiratory Hazard Index 0.05 hydrochloric acid Num ber of Facilities with Maximum Respiratory Hazard Index: Greater than 1 0 n/a **Acute Noncancer Results** Maximum Acute Hazard Quotient 0.7 hydrochloric acid Number of Facilities With Potential for Acute Effects 0 **Population Exposure** Number of People Living Within 50 Kilometers of Facilities Modeled 29,000,000 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 0 n/a Greater than or equal to 1 in 1 million 2 n/a Number of People Exposed to Noncancer Hazard Index: Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.0006 n/a Contribution of HAP to Cancer Incidence Dioxins/Furans POM Napthalene 63% 15% 5% n/a

Our worst - case screening - level acute anal ys is in dicated that no major sources had acute HQ values greater than 1 (highest HQ value was 0.7 based on the RELfor HCL) . With respect to**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 28 area sources, there are no acute health benchmark values for dioxins , and thus , we did not calculate HQ value s for any area sources. In addition to the anal ys es presented above, to screen for potential multipathway e ffects from emissions of cadmium, mercury , and PAHs we compared actual emission rates from major source facilities in this source category to the screening value for cadmium, mercury , and PAHs described in section 2.5 . Similarly , to screen for potential multipathway effects from emissions of dioxins, we compared actual emission rates from both major and are a sources to the screening value for dioxins described in section 2.5. (A lso see Appendix 4 for a more detailed discussion of screening emission rates). Results of this worst - case screen estimate that actual PAH emissions from 10 of the 53 major source facilities exceed the PAH screening emission rate by

as much as approximately 80 times . With respect to diox i ns /fur an s , we note that of the 46 major sources that emitted dioxins, 39 exceeded our screening emission rate b y as much as approximately 2 , 500 times. Similarly , 76 out of 103 area sources exceeded our screeing rate b y as much as approximately 1000 times. W ith respect to the se exceed ance s of the worst - case multipathway screening level for PAHs and dioxins /furans , we note that this only ind icates the potential for multipathway - related cancer risks of concern f rom PAHs and dioxins . That is, while in general, emission rates below the worst - case multipathway screening level indicate no significant potential for multipathway related health effects, emission levels above this worst - case screening level only indicate the potential for multipathway - related health risks of concern based on a worst - case scenario. Due to site specific data limitations, we were not able to refine our multi - pathway analy s is beyond the worst - case screening assessment. Thus, we note that these results are biased high for purposes of screening and are therefore subject to significant uncertainties. As a result, we cannot say

whether multi - pathway

risks may

be a concern ; we c an only say that we cannot rule them out . With respe ct to the potential for significant and widespread environmental effects from non PB - HAP, we note that for both major and area sources. all chronic non - cancer HQ values for all pollutants considering ac tual emissions are well below 1 using human health reference values. Thus, we believe that it is unlikely that adverse environmental effects would occur at the actual HAP concentrations estimated in our human health risk assessment. 

### 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 likel y dominate the uncertainties in our exposure modeling estimates. The chronic exposure modeling uncertainties are considered relativel y small in comparison, since we are using EPA’s refined local dispersion model with site specific parameters and reasonabl y representative meteorology. If an ything, the population exposure estimates are biased high b y not accounting for short - or long - term population**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 29 mobility and b y neglecting process es like deposition, plume depletion, and atmospheric degradation. Additionally , estimates of the maximum individual risk (MIR) contain uncertaint y , because they are deriv ed at census block centroid locations rather than actual residences. This uncertainty is known to create potential underestimates and overestimates of the actual MIR values for individual facilities, but, overall, it is not thought to have a significant impact on the estimated MIR for a source category . Finally , we did not factor in the possibility

of a source closure occurring during the 70 - ye ar 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 exp osure period, leading to a potential downward bias in both the MIR and population risk estimates. A sensitivity

anal ys is performed for the 1999 NATA found that the selection of the meteorology

dataset location could result in a range of chronic ambient co ncentrations which varied from as much as 17% below the predicted value to as much as 84% 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% lower to 84% higher than the predicted values. We have purposel y 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 ac tivity

patterns . In cases where multiple acute threshold values are considered scientifically

acceptable we have chosen the most conservative of these threshold values , erring on the side of overestimating potential health risks from acute exposures. In the cases where these results indicated the potential for exceeding short - term health thresholds post controls , we refined our assessment by developing a better understanding of the geography of the facility

relative to potential exposure locations. 

### 4.2 **Unc ertainties**  **in the d**  **ose -**  **r esponse**  **r elationships**  Inthe 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) e xposures. Noncancer reference values are generall y derived for chronic exposures (up to a lifetime), but may also be derived for acute ( <24 hours), short - term (>24 hours up to 30 day s), and subchronic (>30 day s up to 10% of lifetime) exposure durations, all of which are derived based on an assumption of continuous exposure throughout the duration specified. For the purposes of assessing all potential health risks associated with the emissions included in an assessment, we rel y on both chronic (cancer and noncancer) and acute (noncancer) benchmarks, which are described in more detail below. Although every

effort is made to identify peer - review ed dose - response values for all HAPs emitted by

the source s included in an assessment, some HAP have no peer - reviewed cancer potency values or reference values for chronic non - cancer or acute effects (inhalation or ingestion) . Since exposures to these pollutants cannot be included in a quantitative risk estimate, an understatement of risk for these pollutants at environmental exposure levels is possible.**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 30 Additionally , chronic dose - response values for certain compounds included in the assessment may be under EPA IRI S review and revised assessments may determine that these pollutants are more or less potent than currently thought. We will re - evaluate risks if, as a result of these reviews, a dose - response metric changes enough to indicate that the risk assessment may significantl y mischaracterize human health risk **Cancer assessment** The discussion of dose - response uncertainties in the estimation of cancer risk below focuses on the uncertainties associated with the specific approach currentl y used by the EPA to develop cancer potency

factors. In general, these same uncertainties atten d the development of cancer potency

factors by

CalEPA, the source of peer - reviewed cancer potency factors used where EPA - developed values are not yet available. To place this discussion in context, we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [ 29 ] (herein referred to as Cancer Guidelines ). “The primary goal of EPA actions is protection of human health; accordingl y, as an Agency policy , risk assessment procedures, including default options that are used in the absence of scientific data to the contrary , should be health protective.” The approach adopted in this document is consistent with this approach as described in the Cancer Guidelines . For cancer endpoints EPA usually derives an oral slope factor for ingestion and a unit risk value for inhalation exposures. These values allow estimation of a lifetime probability of developing cancer given long - term exposures to the pollutant. Depending on the pollutant being evaluated, EPA relies on both animal bioassay and epidemiologi cal studies to characterize cancer risk. As a science policy approach, consistent with the Cancer Guidelines , EPA uses animal cancer bioassay s as indicators of potential human health risk when other human cancer risk data are unavailable. Extrapolatio n of study

data to estimate potential risks to human populations is based upon EPA’s assessment of the scientific database for a pollutant using EPA’s guidance documents and other peer - reviewed methodologies. The EPA Cancer Guidelines describes the Agency ’s recommendations for methodologies for cancer risk assessment. EPA believes that cancer risk estimates developed following the procedures described in the Cancer Guidelines and outlined below generally

provide an upper bound estimate of risk. That is, EPA’s upper bound estimates represent a “plausible upper limit to the true value of a quantity” (although this is usually

not a true statistical confidence limit). 12 In some circumstances, the true risk could be as low as zero; however, in other circumstan ces the risk could also be greater. 13 When developing an upper bound estimate of risk and to provide risk values that do not underestimate risk, EPA generall y relies on conservative default approaches. 14 EPA also uses 12 IRIS glossary (www.epa.gov/NCEA/iris/help_gloss.htm). 13 The exception to this is the URE for benzene, which is considered to cover a range of values, each end of which is considered to be equally plausible, and which is based on maximum likelihood estimates. 14 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**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 31 the upper bound (rather than lower bo und or central) estimates in its assessments, although it is noted that this approach can have limitations for some uses (e.g. priority setting, expected benefits anal ys is). Such health risk assessments have associated uncertainties, some which may be con sidered quantitatively , and others which generally are expressed qualitativel y. Uncertainties may vary substantially

among cancer risk assessments associated with exposures to different pollutants, since the assessments employ different databases with dif ferent strengths and limitations and the procedures emplo yedmay differ in how well they

represent actual biological processes for the assessed substance. EPA’s Risk Characterization Handbook also recommends that risk characterizations present estimates d emonstrating the impact on the assessment of alternative choices, data, models and assumptions [ 30 ]. Some of the major sources of uncertaint y and variability

in deriving cancer risk values are described more full y below. (1) The qualitative similarities or differences between tumor responses observed in experimental animal bioassay s and those which would occur in humans are a source of uncertaint y in cancer risk assessment. In general, EPA does not assume that tumor sites observed in an experimental ani mal bioassay are necessarily

predictive of the sites at which tumors would occur in humans. 15 However, unless scientific support is available to show otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target organ concordan ce. For a specific pollutant, qualitative differences in species responses can lead to either under - estimation or over - estimation of human cancer risks. (2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead to dif ferences in risk predictions. For example, the measure of dose is commonly expressed in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, data may support development of a pharmacokinetic model for the absorption, distribution, metabolism and excretion of an agent, which may result in improved dose metrics (e.g., average blood concentration of the pollutant or the quantity of agent metabolized in the body). Quantitative uncertainties result when the appropriate choice of a dose metric is uncertain or when dose metric estimates are themselves uncertain (e.g., as can occur when alternative pharmacokinetic models are available for a compound). Uncertainty in dose estimates may lead to either over or underestimation of risk. (3) For the quantitative extrapolation of cancer risk estimates from experimental animals to humans, EPA uses scaling methodologies (relating expected response to differences in phy sical size of the species), which introduce another source of uncertaint y. These option ch osen 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 evaluatin g the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although de faults are not intended to overtly overestimate risk). See EPA 2004 An Examination of EPA Risk Assessment Principles and Practices, EPA/100/B - 04/001 available at: http://www.epa.gov/osa/pdfs/ratf - final.pdf. 15 Per the EPA Cancer Guidelines: “The default op tion is that positive effects in animal cancer studies indicate that the agent under study can have carcinogenic potential in humans.” and “Target organ concordance is not a prerequisite for evaluating the implications of animal study results for humans.”**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 32 methodologies are based on both biological data on differences in rates of process according to species size and empirical comparisons of toxicity between experimental animals and humans. For a particular pollutant, the quantitative difference in c ancer potency between experimental animals and humans may be either greater than or less than that estimated by baseline scientific scaling predictions due to uncertainties associated with limitations in the test data and the correctness of scaled estimate s. (4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, are generally

developed using a benchmark dose (BMD) anal ys is to estimate a dose at which there is a specified excess risk of cancer, which is used as the p oint of departure (or POD) for the remainder of the calculation. Statistical uncertainty in developing a POD using a benchmark dose (BMD) approach is generally addressed though use of the 95% lower confidence limit on the dose at which the specified exces s risk occurs (the BMDL), decreasing the likelihood of understating risk. EPA has generall y utilized the multistage model for estimation of the BMDL using cancer bioassay data (see further discussion below). (5) Extrapolation from high to low doses is an important, and potentially large, source of 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 experim ental or epidemiological studies at higher dose) depending on the available data and understanding of a pollutant’s mode of action (i.e., the manner in which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use of reliable, compound - specific, biologicall y - based risk models when feasible; however, such models are rarel y available. The mode of action for a pollutant (i.e., the manner in which a pollutant causes cancer) is a key consideration in determining how risks should be estimated for low - dose exposure. A reference value is calculated when the available mode of action data show the response to be nonlinear (e.g., as in a threshold response). A linear low - dose (straight line from POD) approach is used when available mode of action data support a linear (e.g., nonthreshold response) or as the most common default approach when a compound’s mode of action is unknown. L inear extrapolation can be supported by both pollutant - specific data and broader scientific considerations. For example, EPA’s Cancer Guidelines generally consider a linear dose - response to be appropriate for pollutants that interact with DNA and induce mutations. Pollutants whose effects are additive to background biological processes in cancer development c an also be predicted to have low - dose linear responses, although the slope of this relationship may not be the same as the slope estimated by the straight line approach. EPA most frequently

utilizes a linear low - dose extrapolation approach as a baseline science policy choice (a “default”) when available data do not allow a compound - specific determination. This approach is designed to not underestimate risk in the face of uncertainty and variability . EPA believes that linear dose - response models, when a ppropriately

applied as part of EPA’s cancer risk assessment process, provide an upper bound estimate of risk and generall y provide a health protective approach. Note that another source of uncertainty is the characterization of low - dose nonlinear, non - threshold relationships. The National Academy of Sciences has encouraged the exploration of sigmoidal ty pe functions (e.g., log - probit models) in representing dose response relationships due to the variability in response within**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 33 human populations. Another National Research Council (NRC) report [ 31 ] suggests that models based on distributions of individual thresholds are likel y to lead to sigmoidal - shaped dose - response functions for a population. This report notes sources of variability in the human populati on: “One might expect these individual tolerances to vary extensively

in humans depending on genetics, coincident exposures, nutritional status, and various other susceptibility

factors...” Thus, if a distribution of thresholds approach is considered fo r a carcinogen risk assessment, application would depend on ability of modeling to reflect the degree of variability

in response in human populations (as opposed to responses in bioassay s with geneticall y more uniform rodents). Note also that low dose lin earit y in risk can arise for reasons separate from population variability : due to the nature of a mode of action and additivity of a chemical’s effect on top of background chemical exposures and biological processes. As noted above, EPA’s current approach to cancer risk assessment ty pically utilizes a straight line approach from the BMDL . This is equivalent to using an upper confidence limit on the slope of the straight line extrapolation. The impact of the choice of the BMDL on bottom line risk estimate s can be quantified by comparing risk estimates using the BMDLvalue to central estimate BMD values, although these differences are generall y not a large contributor to uncertaint y in risk assessment (Subramaniam et. al., 2006) [ 32 ]. It is important to not e 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 ., a l. (2006) also provide comparisons indicating that slopes based on straight line extrapolation from a POD do not show large differences from those based on the upper confidence limit of the multistage model. (6) Cancer risk estimates do not generall y make specific adjustments to reflect the variability in response within the human population

— resulting in another source of uncertainty in assessments. In the diverse human population, some individuals are likely to be more sensitive to the action of a carc inogen than the t yp ical individual, although compound - specific data to evaluate this variability are generally

not available. There may also be important life stage differences in the quantitative potency of carcinogens and, with the exception of the reco mmendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic mode of action, risk assessments do not generall y quantitatively address life stage differences. However, one approach used commonly in EPA assessments that may help addres s variability in response is to extrapolate human response from results observed in the most sensitive species and sex tested, resulting ty pically in the highest URE which can be supported by reliable data, thus supporting estimates that are designed not t o underestimate risk in the face of uncertainty

and variability . **Chronic noncancer assessment** Chronic noncancer reference values represent chronic exposure levels that are intended to be health - protective. That is, EPA and other organizations which develop noncancer reference values (e.g., the Agency

for Toxic Substances and Disease Registry

– ATSDR) utilize an app roach that is intended not to underestimate risk in the face of uncertainty and variability .**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 34 When there are gaps in the available information, uncertainty factors (UFs) are applied to derive reference values that are intended to be protective against appr eciable risk of deleterious effects . Uncertainty factors are commonly

default values 16 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 info rmation. When data are limited, more assumptions are needed and more default factors are used. Thus there may be a greater tendency to overestimate risk

—in the sense that further study might support development of reference values that are higher (i.e., less potent) because fewer default assumptions are needed. However, for some pollutants it is possible that risks may be underestimated. For non - cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) for exposures via ingestion , and a Reference Concentration (RfC) for inhalation exposures. These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or a continuous inhalation exposure (RfC) to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. 17 To derive values that are intended to be “without appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach (U.S. EPA, 1993 (see US EPA. 1993. Reference Dose (RfD): Description and Use in Health Risk Assessments. http://www.epa.gov/iris/rfd.htm.),and U.S. EPA 1994 (see reference 13 below) which includes consid eration of both uncertaint y and variability. EPA begins b y evaluating all of the available peer - reviewed literature to determine non cancer endpoints of concern, evaluating the quality, strengths and limitations of the available studies. EPA ty

picall y chooses the relevant endpoint that occurs at the lowest dose, often using statistical modeling of the available data, and then determines the appropriate point of departure (POD) for derivation of the reference value. A POD is determined by (in order of preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of the dose or concentration at which the toxic response was not significantl y 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 (U.S. EPA 1994 (see reference 13 below) and U.S. EPA 2002 ( A Review of the Reference Dose and Reference Concentrati on Processes.
16 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 whe n 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 ch oice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be appro priate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An exam ination of EPA Risk Assessment Principles and Practices, EPA/100/B - 04/001 available at: http://www.epa.gov/osa/pdfs/ratf - final.pdf. 17 See IRIS glossary**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 35 http://www.epa.gov/ncea/iris/RFD_FINAL1.pdf.) ). While collectively termed “UFs”, these factors account for a number of different quantitative considerations when utilizing observed animal (usually

rodent) or human toxicity data in a risk ass essment. The UFs are intended to account for: (1) variation in susceptibility among the members of the human population (i.e., inter - individual variability); (2) uncertaint y in extrapolating from experimental animal data to humans (i.e., interspecies diff erences); (3) uncertainty

in extrapolating from data obtained in a study with less - than - lifetime exposure (i.e., extrapolating from subchronic to chronic exposure); (4) uncertainty in extrapolating from a LOAEL in the absence of a NOAEL ; and (5) uncertainty when the database is incomplete or there are problems with applicability of available studies . When scientifically sound, peer - reviewed assessment - specific data are not available, default adjustment values are selected for the individual UFs. For each t yp e of uncertaint y (when relevant to the assessment) , EPA ty pically applies an UF value of 10 or 3 with the cumulative UF value leading to a downward adjustment of 10 - 3000 fold from the selected POD. An UF of 3 is used when the data do not support the use of a 10 - fold factor. If an extrapolation step or adjustment is not relevant to an assessment (e.g., if applying human toxicity data and an interspecies extrapolation is not required) the associated UF is not used. The major adjustment steps are describe d more fully below. 1) Heterogeneit y among humans is a key source of variability

as well as uncertaint y. Uncertaint y related to human variation is considered in extrapolating doses from a subset or smaller - sized population, often of one sex or of a narr ow range of life stages (ty pical of occupational epidemiologic studies), to a larger, more diverse population. In the absence of pollutant - specific data on human variation, a 10 - fold UF is used to account for uncertainty associated with human variation. Human variation may be larger or smaller; however, data to examine the potential magnitude of human variability are often unavailable. In some situations, a smaller UF of 3 may be applied to reflect a known lack of significant variability among humans. 2) Extrapolation from results of studies in experimental animals to humans is a necessary step for the majority

of chemical risk assessments . When interpreting animal data, the concentration at the POD (e.g. NOAEL, BMDL) in an animal model (e.g. rodents) is extrapolated to estimate the human response. While there is long - standing scientific support for the use of animal studies as indicators of potential toxicity to humans , there are uncertainties in such extrapolations. Inthe absence of data to the contrary , the ty pical approach is to use the most relevant endpoint from the most sensitive species and the most sensitive sex in assessing risks to the average human. Ty picall y , compound specific data to evaluate relative sensitivity in humans versus rodent s are lacking, thus leading to uncertainty in this extrapolation. Size - related differences (allometric relationships) indicate that ty picall y humans are more sensitive than rodents when compared on a mg/kg/day basis. The default choice of 10 for the interspecies UF is consistent with these differences. For a s pecific chemical, differences in species responses may be greater or less than this value . Pharmacokinetic models are useful to examine speci es differences in pharmacokinetic processing and associated uncertainties; however, such dosimetric adjustments are not alway s possible. Information may not be available to quantitatively assess toxicokinetic or toxicody namic differences between animals and humans, and in many cases a 10 - fold UF**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 36 (with separate factors of 3 for toxicokinetic and toxicody namic components) is used to account for expected species differences and associated uncertainty in extrapolating from laboratory

animals to humans in the d erivation of a reference value. If information on one or the other of these components is available and accounted for in the cross - species extrapolation, a UF of 3 may be used for the remaining component. 3) In the case of reference values for chronic e xposures where onl y 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 ty picall y applied unless the available s cientific information supports use of a different value. 4) Toxicity

data are t ypically 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 t o an order of magnitude. The preferred approach to arrive at a POD is to use BMD analy sis; however, this approach requires adequate quantitative results for a meaningful anal ys is, which is not alway s possible. Use of a NOAEL is the next preferred approac h after BMD analy sis in determining a POD for deriving a health effect reference value. However, many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3 - fold is often applied. 5) The database UF is intended to account for the potential for deriving an underprotective RfD/RfC due to a data gap preventing complete characterization of the chemical’s toxicity . In the absence of studies for a known or suspected endpoint of concern, a UF of 10 or 3 - fold is ty

pically applied. **Acute noncancer assessment** Many of the UFs used to account for variabilit y and uncertaint y in the development of acute reference values are quite similar to those developed for chronic durations, but more often using individual UF values that may be less than 10. UFs are applied ba sed on chemical specific or health effect - specific information (e.g., simple irritation effects do not vary appreciably

between human individuals, hence a value of 3 is ty picall y used), or based on the purpose for the reference value (see the following paragraph). The UFs applied in acute reference value derivation include: 1) heterogeneity among humans; 2) uncertainty in extrapolating from animals to humans; 3) uncertainty in LOAEL to NOAEL adjustments; and 4) uncertainty

in accounting for an incomplete database on toxic effects of potential concern. Additional adjustments are often applied to account for uncertainty in extrapolation from observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an acute reference value at another exposure duration (e.g., 1 hour). Not all acute reference values are developed for the same purpose and care must be taken when interpreting the results of an acute assessment of human health effects relative to the reference value or values b eing exceeded. Where relevant to the estimated exposures, the**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 37 lack of threshold values at different levels of severity should be factored into the risk characterization as potential uncertainties.**Draft Risk Assessment for the Secondary Aluminum Production Source Category --** 

**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 38 

### 5 **References** 1 . US EPA. National Emission Standards for Hazardous Air Pollutants . http://www.epa.gov/ttn/atw/mactfnlalph.html . 2 US EPA, 2009. Risk and Technology Review (RTR) Risk Assessment Methodologies: For Review by

the EPA’s Science Advisory Board with Case Studies

– MACT I Petroleum Refining Sources and Portland Cement Manufacturing . EPA - 452/R- 09 - 006. http://www.epa.gov/ttn/atw/rrisk/rtrpg.html. 3 . US EPA, 2010. SAB’s Response to EPA’s RTR Risk Assessment Methodologies. http://y osemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/EP A - SAB - 10 - 007 -unsigned.pdf 4 . US EPA, 2010. Memorandum from Dave Guinnup to RTR Wood Furniture Docket, entitled, “EPA’s Actions in Response to Key Recommendations of the SAB Review of RTR Risk Assessment Methodologies. 5 . US EPA, 2005. Revision to the Guideline on Air Quality Models: Adoption of a Pre ferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final Rule. 40 CFR Part 51. http://www.epa.gov/EPA - AI R/2005/November/Day- 09/a21627.htm 6 . US EPA, 2004. Users’ guide for the AMS/EPA regulatory model

– AERMOD. EPA - 454/B 03 - 001 . http://www.epa.gov/scram001/7thconf/aermod/aermodugb.pdf . 7 . Allen , D. , C . Murphy, Y . Kimura, W . Vizuete, T . Edgar , H . Jeffries, B . - U . Kim, M . Webster , and M . Sy mons , 2004. Variable industrial VOC emissions and their impact on ozone formation in the Houston Galveston Area. Final Report: Texas Environmental Research Consortium Project H - 13. http://files.harc.edu/Projects/AirQuality /Projects/H013.2003/H13FinalReport.pdf 8 . US EPA, 2004. Air Toxics Risk Assessment Reference Library, Volume 1. EPA - 453 - K- 04 - 001A. http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 9 . US EPA, 2005. Table 1. Prioritized Chronic Dose - Response Values (2/28/05). Office of Air Quality

Planning and Standards. http://www.epa.gov/ttn/atw/toxsource/table1.pdf 10 . US EPA, 2005. 1999 National Air Toxics Risk Assessment. http://www.epa.gov/ttn/atw/nata1999 11
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ntegrated Risk I

nformation System. http://www.epa.gov/iris/index.html . 12
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for Toxic Substances and Disease Registry. 2006. Minimum Risk Levels (MRL s) for Hazardous Substances. http://ww w.atsdr.cdc.gov/mrls/index.html . 13
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**FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE** 39 14
. NRC, 1994. National Research Council. Science and Judgment in Risk Assessment. Washington, DC: National Academy Press. 15
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2000. http://www.oehha.ca.gov/air/acute_rels/allAcRELs.html 20 . American I

ndustrial Hy

giene Association , 2009. Current AI HA ERPG Values. http://www.aiha.org/insideaiha/volunteergroups/Documents/ERP - erpglevels.pdf . 21 . US EPA, 1995. Guidance for Ri sk Characterization. Science Policy Council. http://www.epa.gov/OSA/spc/pdfs/rcguide.pdf . 22 . US EPA, 2000. Risk Characterization Handbook. EPA 100 - B - 00 - 002. 23 . US EPA, 2002. EPA’s Guidelines for Ensuring and Maximizing the Quality, Objectivity, Utility, and Integrity

of Information Disseminated by the Environmental Protection Agency. EPA Office of Environmental I nformation. EPA/260R- 02 - 008 . http://www.epa.gov/quality/informationguidelines/documents/EPA_I nfoQualityGuidelines.pdf 24 . US EPA, 2006. Performing risk assessments that include carcinogens described in the Supplemental Guidance as having a mutagenic mode of action. Science Policy Council Cancer Guidelines I

mplementation Workgroup Communication II : Memo from W.H. Farland dated 14 June 20 06. http://www.epa.gov/osa/spc/pdfs/CGIWGCommunication_II.pdf 25 . US EPA, 2005. Supplemental guidance for assessing earl y - life exposure to carcinogens. EPA/630/R - 03003F. http://www.epa.gov/ttn/atw/childrens_supplement_final.pdf . 26
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