Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

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## Draft Residual Risk Assessment for the Primary Lead Smelting Source Category

by EPA’s Office of Air Qualit y Planning and Standards

Office of Air and Radiation

December 2010Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

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### Table of Contents

Table of Tables ............................................................................................................... .... 3

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 human inhalation exposure ..................................................................... 7 2.4 Acute Risk Screening and Refined Assessments ...................................................... 8 2.5 Multipathway and environmental risk screening and refine d assessments .............. 9 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 .................................................... 15

2.7 Risk Characterization .............................................................................................. 17

2.7.1 General ............................................................................................................. 17

2.7.2 Mixtures ........................................................................................................... 19 2.7.3 Facility-wide Risks .......................................................................................... 20 3. Risk Results for the Primary L ead Smelting Source Category ................................. 20 3.1 Source Category Descri ption and Results ............................................................... 20

3.2 Baseline Risk Characterization ............................................................................... 22

3.3 Assessment of Emission Reductions Scenarios ...................................................... 26

4. General Discussion of Uncertainties a nd How They Have Been Addressed .............. 26 4.1 Exposure Modeling Uncertainties ........................................................................... 26 4.2 Uncertainties in the Dose-Response Relationships ................................................. 26

5. References ................................................................................................................ .... 35Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

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### Table of Tables

Table 2.2-1 AERMOD version 09292 m odel 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 Inhalation Exposure to Noncarcinogens................................................................................................................. 14 Table 2.6-2 Dose-Response Valu es for Acute Exposure ................................................. 17 Table 3.1-1 Summary of Emissions from th e Primary Lead Smelting Source Category and Availability of Do se-Response Values ...................................................................... 22 Table 3.2-1 Summary of Sour ce Category Level Inhalation Risks for the Primary Lead Smelting Facility – non-lead HAP .................................................................................... 23 Table 3.2-2 Summary of Lead Concentrati ons Relative to the NAAQS Given Actual

2008 and MACT Allowable Emissions ............................................................................ 25Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

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## 1. Introduction

Section 112 of the Clean Air Act (CAA) establ ishes a two-stage regu latory process for addressing emissions of hazardous air pollutants (HAPs) from stationa ry sources. In the first stage, section 112(d) re quires the Environmental Prot ection Agency (EPA, or the Agency) to develop technology-based standard s for categories of s ources (e.g., petroleum refineries, pulp and paper mills, etc.) [ 1 ]. EPA has largely completed the initial Maximum Achievable Control Technology (M ACT) standards as required under this provision. Under section 112(d)(6), EPA must review each of these technology-based standards at least every eight years and revise a standar d, as necessary, “taking into account developments in practices, processes and control technologies .” In the second stage, EPA is required under section 112(f)(2) to assess th e health and environmental risks that remain after implementation of the MACT standards. If additional risk reductions are necessary to prot ect public health with an am ple margin of safety or to prevent an adverse environmental effect, EP A must develop standa rds to address these remaining risks. This second stage of the re gulatory process is known as the residual risk stage. For each source category for which EP A issued MACT standards, the residual risk stage must be completed within eight year s of promulgation of the initial technologybased standard.

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board (SAB) on the “Risk and Technology Review (R TR) 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) A ssessment 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 th is review in devel oping our current risk assessments, and we will be continuing our efforts to improve our assessments by incorporating updates based on the SAB reco mmendations as they are developed and become available. Our responses to the ke y recommendations of the SAB are outlined in a memo to this rulemaking docket [ 4 ].

This document contains the methods and the re sults of baseline risk assessments (i.e., after the implementation of the respective MA CT standards) performed for the Primary Lead Smelting source category. The methods discussion includes descriptions of the methods used to develop refined estimates of chronic inhalation exposures and human

health risks for cancer and non cancer endpoints, as well as descriptions of the methods used to assess the potential for acute health risks, chronic non-inhala tion health risks, and

adverse environmental effects.



## 2. Methods

2.1 Emissions and source data

Since there is only one primary lead smelter currently operating in th e U.S., the data set for the source category is represented by the da ta set for this one facility. The preliminary

emissions dataset was based on data in the 2002 National Emissions Inventory (NEI)Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

5 Final Inventory, Version 1 (made publicly available on February 26, 2006), and the 2005 National Emissions Inventory (NEI), versi on 2.0 (made publicly available in October 2008). The 2005 NEI was updated to develop the 2005 National Air Toxics Assessment (NATA) Inventory. NATA invent ory updates for the primary lead category included SIP data provided by the state of MO to EP A. The 2005 NATA inventory was used with updated 2008 data received in an Information Collection Request (ICR) response from the facility. In addition, we performed an engineering revi ew of the information using EPA engineers who were directly involved in the development of the MACT standards for the source category and/or who have ex tensive knowledge of th e characteristics of this industry. The goal of the engineering review was to identify readily apparent

limitations and issues with the emissions da ta and/or source parameters (particularly those that would have the poten tial to influence risk estima tes) and to make changes to the data set where possible to address thes e issues and decrease the uncertainties

associated with the assessment.

Details on the development of the emissions a nd source data for this source category are

discussed in Section 3. The emissions data and modifications made to the NEI data are discussed in Appendix 1, entitled “Emissi ons Inventory Support Memorandum.”



### 2.2 Dispersion modeling for inhalation exposure assessment

Both long- and short-term inhalation exposure concentrations and asso ciated health risk from each facility in the source category of interest were estimated using the Human Exposure Model in combination with th e American Meteorological Society/EPA Regulatory Model dispersion modeling system (HEM-AERMOD). The approach used in applying this modeling system is outlined be low, and further deta ils are provided in Appendix 2. HEM-AERMOD performs three ma in operations: atmospheric dispersion modeling, estimation of individua l human exposures and health risks, and estimation of population risks. This section focuses on the dispersion modeling component. The exposure and risk characteri zation components are discusse d in other subsections of

Sections 2 and 3.

The dispersion model in the HEM-AE RMOD system, AERMOD version 09292, is a state-of-the-science Gaussian plume disper sion model that is preferred by EPA for modeling point, area, and volume sources of continuous air emissions from facility applications [ 5 ]. Further details on AERMOD can be found in the AERMOD Users Guide [ 6 ]. The model is used to develop annua l average ambient con centrations through the simulation of hour-by-hour dispersion from the emission sources into the surrounding atmosphere. Hourly emission rates used fo r this simulation are generated by evenly dividing the total annual emission rate from the inventory into the 8,760 hours of the

year.

The first step in the application of the HEM-AERMOD modeling system is to predict

ambient concentrations at locations of in terest. The AERMOD model options employed

are summarized in Table 2.2-1 and are discussed further below.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

6 Table 2.2-1 AERMOD version 09292 model options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point, area represented as pseudo point source

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 site-specific

In HEM-AERMOD, meteorological data are ordinarily selected from a list of 158 National Weather Service (NWS) surface obser vation stations acro ss the continental United States, Alaska, Hawaii, and Puerto Ric o. In most cases the nearest station is selected as representative of the conditions at the subject facility. However, in this instance, site-specific meteorologi cal data for the one facility in this source category were supplied by the state of Miss ouri and used for the modeli ng. The data provided by the

state of Missouri were for ei ght quarters (i.e., eight three- month periods) from April 1997 through June 1999. To obtain one year of meteorological data, we used the middle portion of these data, the year 1998, in our modeling.

The HEM-AERMOD system estimates ambient concentrations at the geographic centroids of census blocks (using the 2000 Cens us) and at other receptor locations that can be specified by the user. Chronic ambi ent concentrations were calculated as the annual average of all estimated short-term (one-hour) concentrations at each block

centroid. Possible future residential us e of currently uninhabited areas was not considered. Census blocks, the finest resolu tion available in the census data, are typically comprised of approximately 40 people or about ten households.

In contrast to the development of ambien t concentrations for evaluating long-term exposures, which was performed only for occ upied census blocks, wo rst-case short-term (one-hour) concentrations were estimated both at the census block centroids and at points nearer the facility that repr esent locations where people may be present for short periods, but generally no nearer than 100 meters from th e center of the facility (note that for large facilities, this 100-meter ring could still contai n locations inside the facility property).

Since short-term emission rates were needed to screen for the potential for hazard via acute exposures, and since the NEI contains only annual emission totals, we generally apply the general assumption to all sour ce categories that the maximum one-hour emission rate from any source was ten times the average annual hourly emission rate forDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

7 that source. The average hourly emissions rate is defined as the total emissions for a year divided by the total number of operating hours in the year. This choice of a factor of ten for screening was originally based on engine ering judgment. To develop a more robust peak-to-mean emissions factor, and in respons e to one of the key messages from the SAB consultation on our RTR Assessment Plan, we pe rformed an analysis using a short-term

emissions dataset from a number of sources located in Texas (originally reported by

Allen et al. 2004)[ 7]. In that report, the Texas Environmental Research Consortium Project compared hourly and annual emissions data for volatile organic compounds for

all facilities in a h eavily-industrialized 4-county area (H arris, Galveston, Chambers, and Brazoria Counties, TX) over an eleven-m onth time period in 2001. We obtained the dataset and performed our own analysis, focusing on sources which reported emitting high quantities of HAP over short periods of time (see Appendix 3, “Analysis of data on

short-term emission rates rela tive to long-term emission rate s”). Most peak emission events were less than twice the annual averag e, and the highest was a factor of 11 times the annual average. Based on these results, we chose the factor of ten for all initial screening; it is intended to cover routinely variable em issions as well as startup, shutdown, and malfunction (SSM) emissions. While there have been some documented emission excursions above this level, our analysis of the data from the Texas Environmental Research Consortium suggests th at this factor should cover more than 99% of the short-term peak gaseous or vol atile HAP emissions from typical industrial

sources.

Census block elevations for HEM-AERMOD m odeling were determined nationally from the US Geological Service 1-de gree digital elevation model (D EM) data files, which have a spatial resolution of about 90 meters. Elevat ions of polar grid points used in estimating short- and long-term ambient concentrations were assumed to be equal to the highest elevation of any census block falling within the polar grid sector corresponding to the grid point. If a sector does not contain any blocks, the model defau lts the elevation to

that of the nearest block. If an elevati on is not provided for the emission source, the model uses the average elevation of all sectors within the i nnermost model ring.

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



### 2.3 Estimating human inhalation exposure

We used the annual average ambient air concen trations of each HAP at each census block centroid as a surrogate for the lifetime inhala tion exposure concentra tion of all the people who reside in the census block. That is, the ri sk analysis did not consider either the shortterm or long-term behavior (mobility) of the exposed populations and its potential influence on their exposure.

We did not address short-term human activity fo r two reasons. First, our experience with the 1996, 1999, 2002, and 2005 NATA assessments (w hich modeled daily activity using EPA’s HAPEM model) suggests that, given our current understanding ofDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

8 microenvironment concentrations and daily activities, modeling short-term activity would, on average, reduce risk estimates a bout 25% for particulate HAPs; it will also reduce risk estimates for gaseous HAPs, but typically by much less. Second, basing exposure estimates on average ambient concen trations at census block centroids may underestimate or overestimate actual exposure concentrations at some residences. Further reducing exposure estimates for the most highly exposed residents by modeling their short-term behavior could add a sy stematic low bias to these results.

We did not address long-term migration nor population growth or decrease over 70 years, instead basing the assessment on the assumpti on that each person’s predicted exposure is

constant over the course of their lifetime whic h is assumed to be 70 years. In assessing cancer risk, we generally estimated three metr ics: the maximum individual risk (MIR),

which is defined as the risk associated w ith a lifetime of expo sure at the highest concentration; the population ri sk distribution; and the cancer incidence. The assumption of not considering short- or long-term popula tion mobility does not bias the estimate of

the theoretical MIR nor does it affect the es timate of cancer incidence since the total population number remains the same. It doe s, however, affect the shape of the

distribution of individual risk s across the affected population, shifting it toward higher

estimated individual risks at the upper end and reducing the number of people estimated to be at lower risks, thereby bi asing the risk estimates high.

When screening for potentially significant ac ute exposures, we used an estimate of the highest hourly ambient concentration at any off-site location as the surrogate for the maximum potential acute exposure c oncentration for any individual.



### 2.4 Acute Risk Screening and Refined Assessments

In establishing a scientifically defensible ap proach for the assessment of potential health risks due to acute exposures to HAP, we fo llowed the same general approach that has been used for developing chronic health risk assessments under the residual risk program. That is, we developed a tiered, iterative approach. This approach to risk assessment was endorsed by the National Academy of Scien ces in its 1993 public ation “Science and Judgment in Risk Assessment” and subseque ntly was adopted in the EPA’s “Residual Risk Report to Congress” in 1999.

The assessment methodology is designed to el iminate 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 assessment. This means that we began with a screening assessment, which relies on readily available data and uses conservative assumptions that in combination appr oximate a worst-case exposure. The result of this screening proce ss is that either the facility being assessed poses no acute health risks (i.e ., it “screens out”), or that it requires further, more refined assessment. A refined assessment could use 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 would be needed to refine the assessment; in others, lesser amounts of site-specific dataDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

9 could be used to determine that acute e xposures are not a concern, and significant additional data collection would not be necessary.

Acute health risk screening was performed as the first step. We used conservative assumptions for emission rates, meteorology, and exposure location. We used the following worst-case assumptions in our screening approach:

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

emission rates.

 Peak 1-hour emissions were assumed to o ccur at all emission points at the same

time.

 1-hour concentrations at each receptor were assumed to be the sum of the

maximum concentrations due to each em ission point, regardless of whether those maximum concentrations occurred during the same hour.

 Worst-case meteorology (from one year of local meteorology) was assumed to occur at the same time the peak emission rates occur. The recommended EPA local-scale dispersion model, AERMOD, is used for simulating atmospheric dispersion.

 A person was assumed to be located downwind at the point of maximum impact during this same 1-hour period, but no nearer to the source than 100 meters.

 The maximum impact was compared to multiple short-term health benchmarks for the chemical being assessed to determin e if a possible acute health risk might

exist. These benchmarks are descri bed 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 screeni ng estimates. In this case, this included use of a refined emissions multiplier to more accurately estimate the peak hourly emission rates from the average rates.



### 2.5 Multipathway and environmental risk screening and refined

assessments

The potential for significant hum an health risks due to expos ures via routes other than inhalation (i.e., multipathway exposures) or ad verse environmental impacts was screened by first determining whether any sources emitted any hazardous air pollutants known to be persistent 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 Library [ 8 ], and they are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds , mercury compounds, methoxychlor, polychlorinated biphenyls, polyc yclic organic matter (POM), t oxaphene, and trifluralin.

Emissions of two different PB-HAP were id entified in the emissi ons inventory for the Primary Lead Smelting source category: lead and cadmium.

Cadmium emissions were evaluated for pot ential non-inhalation risks and adverse environmental impacts using our recently developed screening scenario which wasDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

10 developed for use with the TRIM.FaTE 1 model. This screening scenario uses environmental media outputs from the peer -reviewed TRIM.FaTE to estimate the maximum potential ingestion risks for any spec ified emission scenario by using a generic farming/fishing exposure scenario that si mulates a subsistence environment. The screening scenario retains ma ny of the ingestion and scenar io inputs developed for EPA’s

Human Health Risk Assessment Protocol s (HHRAP) for hazardous waste combustion

facilities. 2 In the development of the screeni ng scenario a sensitivity analysis was conducted to ensure that its key design pa rameters 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 de minimis emission rates developed fo r screening potentially significant multi-pathway impacts. For the purpose of developing de minimis emission rates for our multi-pathway screening, we deri ved 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 air-related multi-pathway risks from the emissions of lead compounds from the one facility in this source category, rather than developing a de

minimis emission rate, we compared its maximum modeled 3-month rolling average atmospheric lead concentration at any off-s ite location with the current primary National Ambient Air Quality Standard (NAAQS) for l ead, which is set to a level of 0.15 μg/m 3
based on a rolling 3-month period with a not- to-be-exceeded form. 73 FR 66964. Valuesbelow the primary NAAQS are considered to have a low potential for significant multipathway risks because the primary NAAQS is set as to protect public health with an adequate margin of safety.. However, ambien t air lead concentrati ons above the primary NAAQS, regardless of whether these concen trations occurred at a populated census block, are considered to pose a si gnificant risk to public health. This is because: 1) the primary NAAQS for lead is a standard that a pplies anywhere in the ambient air; 2) the primary NAAQS was established to account fo r the air-related multi- pathway impacts of lead sources, which due to the multi-media transport of lead after it is deposited from the atmosphere, may be experienced by individuals in areas distal to the original site of deposition; and 3) lead levels above the primary NAAQS have been associated with significant neurological effect s, including loss of IQ points in children. Moreover, we

also consider this assessment to be a refined risk analysis given the combination of: 1) numerous health studies, detail ed risk and exposure analyses, and level of external peer and public review that went into the devel opment of the primary NAAQS for lead; and 2) the site-specific dispersion modeling perfor med to develop the ambient concentration estimates. It should be noted, however, that this comparison to the NAAQS for lead does not account for possible populati on exposures to lead from sources other than the one being modeled; for example, via consumption of water from untreated local sources or ingestion of locally grown food.

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

2 EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous Waste Combustion Facilities; http://www.epa.gov/epaoswer/hazwa ste/combust/riskvol.htm#volume1Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

11 We further note that comparing ambient lead concentrations to the NAAQS for lead also informs whether there is the potential for advers e environmental effects. This is because the secondary lead NAAQS, set to protect ag ainst adverse welfare effects (including adverse environmental effects), has the same averaging time, form, and level as the primary standard. Thus, ambient lead con centrations above the NAAQS for lead also indicate the potential for a dverse environmental effects.

We also evaluated the potential for signifi cant ecological exposure s to non PB-HAP from

exceedances of chronic human health inhalation thresholds in the ambient air near these

facilities. Human health dos e-response threshold values are generally derived from studies conducted on laboratory animals (s uch as rodents) and developed with the

inclusions of uncertain ty factors that could be as high as 3000. As a result, these human threshold values are often signi ficantly lower than the level expected to cause an adverse effect in an exposed rodent. It should be noted that there is a scarcity of data on the direct atmospheric impact of these HAPs on other recept ors, such as plants, birds, and wildlife. Thus, if the maximum inhalation hazard in an ecosystem is below the level of concern for humans, we have generally concluded that ma mmalian receptors should be at no risk of adverse effects due to inhalation exposures from non PB-HAP, and ha ve assurance that other ecological receptors are also not at a ny significant risk from direct atmospheric impact. In some isolated cases where we ha ve data indicating potential adverse impacts on plants, birds, or other wildlife due to the direct atmospheric impacts of specific HAPs, we note that as an uncertainty and, where pos sible, refine our anal ysis by comparing our modeled impacts to availabl e threshold values from the scientific literature.



### 2.6 Dose-Response Assessment

2.6.1 Sources of chronic dos e-response information

Dose-response assessment (carcinogenic and non-carcinogenic) for chronic exposure (either by inhalation or ingestion) for the HAPs reported in the emissions inventory for the one facility in the Primary Lead Sm elting source category was based on the EPA Office of Air Quality Planning and Standa rds’ existing recommendations for HAPs [ 9 ], also used for NATA 1999, 2002, and 2005 [ 10 ]. This information has been obtained from various sources and prioritized accordi ng to (1) conceptual consistency with EPA risk assessment guidelines and (2) level of peer review re ceived. The prioritization process was aimed at incorporating into our assessments the best available science with respect to dose-response inform ation. 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 typically provide a qualitativ e statement regardin g the strength of scientific data and specify a reference con centration (RfC, for inha lation) or reference dose (RfD, for ingestion) to protect against effects other than cancer and/or a unit risk estimate (URE, for inhalation) or slope fact or (SF, for ingestion) to estimate the probability of developing cancer. The RfC is defined as an “estimate (withDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

12 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 duri ng a lifetime.” The URE is defined as “the upper-bound excess cancer ri sk estimated to result from continuous lifetime exposure to an agent at a concentration of 1 μg/m 3 in air.” The SF is “an upper bound, approximating a 95% confidence li mit, on the increased cancer risk from a lifetime exposure to an agent. This es timate, [is] usually expressed in units of proportion (of a population) affected per mg/kg-day...” EPA disseminates doseresponse assessment information in several fo rms, based on the level of review. The Integrated Risk Information System (IRIS) [ 11 ] is an EPA database that contains scientific health assessment information, including dose-response information. All

IRIS assessments since 1996 have also under gone independent extern al peer review. The current IRIS process includes review by EPA scientists, interagency reviewers from other federal agencies, and the public, and peer review by i ndependent scientists external to EPA. EPA’s science polic y approach, under the current carcinogen guidelines, is to use linear low-dose extrap olation as a default option for carcinogens for which the mode of action (MOA) has not been identified. We expect future EPA dose-response assessments to identify nonlinear MOAs where appropriate, and we will use those analyses (once they are peer re viewed) in our risk assessments. At this time, however, there are no available car cinogen 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 a nd Human Services, develops and publishes Minimum Risk Levels (MRLs) [ 12 ] for inhalation a nd oral exposure to many toxic

substances. As stated on the ATSDR web s ite: “Following discussions with scientists within the Department of Health and Hu man Services (HHS) and the EPA, ATSDR chose to adopt a practice similar to that of the EPA's Reference Dose (RfD) and Reference Concentration (RfC) for deriving substance specific health guidance levels for non neoplastic endpoints.” The MRL is defined as “an estimate of daily human exposure to a substance that is likely to be without an appreciable risk of adverse effects (other than cancer) over a specifie d duration of exposure.” ATSDR describes MRLs as substance-specific estimates to be used by health assessors to select

environmental contaminants for further ev aluation. Exposures above an MRL do not necessarily represent a threat, and MRLs are therefore not intended for use as predictors of adverse health effects or for setting cleanup levels.

3) California Environmental Protection Agency (CalEPA). The CalEPA Office of

Environmental Health Hazard Assessment has developed dose-response assessments for many substances, based both on carcinogeni city and health effects other than cancer. The process for developing these asse ssments is similar to that used by EPA to develop IRIS values and incorporates sign ificant external scientific peer review. As cited in the CalEPA Technical Suppor t Document for developing their chronic

assessments 3 : “The guidelines for developing ch ronic inhalation exposure levels

3 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III - Technical Support DocumentDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

13 incorporate many recommendations of the U.S. EPA [ 13 ] and NAS [ 14 ].” The noncancer information includes available i nhalation health risk guidance values expressed as chronic inhalation re ference exposure levels (RELs) [ 15 ]. CalEPA

defines the REL as “the concentration leve l at or below which no health effects are anticipated in the general human population.” CalEPA's quantitative dose-response information on carcinogenicity by inhalation ex posure is expressed in terms of the URE [ 16 ], defined similarly to EPA's URE.

In developing chronic risk estimates, we ad justed dose-response values for some HAPs based on professional ju dgment, as follows:

1) In the case of antimony compounds, the most conservative dose-response value of the chemical category is used as a surrogat e for other compounds in the group for which dose-response values are not available. This is done in order to examine, under conservative assumptions, whether the HAP that lack dose-response values may pose an unacceptable risk and require further ex amination, or screen out from further

assessment.

2) The IRIS URE for nickel inhalation was derived from evidence of the carcinogenic effects of insoluble nickel compounds in crys talline form. Soluble nickel species, and insoluble species in amorphous form, do not appear to produce genotoxic effects by

the same toxic mode of action as insolubl e crystalline nickel. Nickel speciation information for some of the largest nick el-emitting sources (including oil combustion, coal combustion, and others) suggests that at least 35% of total nickel emissions may be soluble compounds. The remaining inso luble nickel emissions are not wellcharacterized. Consistent with this limited information, this assessment will conservatively assume that 65% of emitted nickel is insoluble and that all insoluble nickel is crystalline. The nickel URE (bas ed on nickel subsulfide , and representative of pure insoluble crystalline ni ckel) was adjusted to reflect an assumption that 65% of the total mass of nickel may be carcinogeni c. The noncancer dos e-response values were not adjusted because non cancer effects of nickel are not thought to be limited to the crystalline, insoluble form

.

The emissions inventory for the primar y lead smelting source category includes

emissions of six HAP with available ch ronic quantitative in halation dose-response values. These HAP, their dose-response values, and the source of the values are listed in Tables 2.6-1 (a) and (b).

for the Determination of Non-cancer Chronic Re ference Exposure Levels. Air Toxicology and Epidemiology Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. February 2000 (http://www.o ehha.ca.gov/air/chronic_ rels/pdf/relsP32k.pdf)Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

14 Table 2.6-1 (a) Dose-Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 4 = cancer risk per μ g/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System.

Pollutant CAS Number 5 URE (1/ μ g/m 3 ) Source

Arsenic Compounds 174 4.3E-03 IRIS Cadmium Compounds 7440439 1.8E-03 IRIS Chromium Compounds
Chromium VI Compounds 18540299 0.012 IRIS Nickel Compounds 186 4.8E-04 IRIS

Table 2.6-1 (b) Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposur e to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Informat ion System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances and Disease Registry, NAAQS = National Ambient Air Quality Standard.

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

Antimony Compounds 7440360 0.0002 IRIS-M
Arsenic Compounds 174 0.000015 CAL
Cadmium Compounds 176 0.00001 ATSDR
Chromium Compounds
Chromium VI Compounds 18540299 0.0001 IRIS-M
Cobalt Compounds 178 0.0001 ATSDR
Lead & Compounds 182 0.00015 NAAQS
Nickel Compounds 186 0.00009 ATSDR

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

5 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.

6 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 Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

15 

### 2.6.2 Sources of acute dos e-response information

Hazard identification and dose-response assess ment information for the acute inhalation exposure assessment are based on the exis ting recommendations of OAQPS for HAPs [ 17]. Depending on availability, the results from screening acute assessments are compared to both “no effects” reference le vels for the general public, such as the California Reference Exposure Levels (RELs), as well as emergency response levels, such as Acute Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelines (ERPGs), with the recognition that the ultimate interpretation of any potential

risks associated with an estim ated exceedance of a particular reference level depends on

the definition of that level and any limitations expressed therein. Comparisons among

different available inhalation he alth effect reference values (both acute and chronic) for selected HAPs can be found in a newly releas ed EPA document (Reference: U.S. EPA. Graphical Arrays of Chemical-Specific Heal th Effect Reference Values for Inhalation Exposures [Final Report]. (U.S. Environm ental Protection Agency, Washington, D.C., EPA/600/R-09/061, 2009. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003.)

California Acute Reference Exposure Levels (RELs ). The California Environmental Protection Agency (CalEPA) has developed acute dose-response re ference values for many 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 be low which no adverse health effects are anticipated for a specified exposure duration. [ 18 ]. RELs are based on the most sensitive, relevant, adverse health effect reported in the medical and toxicological literature. RELs are designed to protect the most sensitive individuals in the population by the inclusion of margins of safety. Since margins of safety are incorporated to address data gaps and uncertainties, exceeding the REL does not automatically indicate an adverse health impact.” Acute RELs are developed for 1- hour (and 8-hour) exposures. The values inco rporate uncertainty factors similar to those used in deriving EPA’s Inhalation Reference Concentrations (RfCs) for chronic exposures (and, in fact, Californi a also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory Committee on Acute Exposure Guid eline Levels (NAC/AEGL) for Hazardous Substances, and then reviewed and publis hed by the National Research Council As

described in the Committee’s “Standi ng Operating Procedures (SOP)” ( http://www.epa.gov/op ptintr/aegl/pubs/sop.pdf ), AEGLs “represent threshold exposure limits for the general public and are applicable to emerge ncy exposures ranging from 10 min to 8 h.” Their intended application is “for conducting risk assessments to aid in the development of emergency preparedness and prevention plans, as well as real time emergency response actions, for accidental chemi cal releases at fixed facilities and from transport carriers.” The document states th at “the primary purpose of the AEGL program

and the NAC/AEGL Committee is to develop guideline levels for once-in-a-lifetime, short-term exposures to airborne concentr ations of acutely to xic, high-priorityDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

16 chemicals.” In detailing the intended applic ation of AEGL values , the document states that “It is anticipated that the AEGL values will be used for regulatory and nonregulatory purposes by U.S. Federal and State agencies, and possibly the international community in conjunction with chemical emergency respons e, planning, and prevention programs. More specifically, the AEGL values will be used for conduc ting various risk assessments to aid in the development of emergency pr eparedness and prevention plans, as well as real-time emergency response actions, for accident al chemical releases at fixed facilities and from transport carriers.”

The NAC/AEGL defines AEGL-1 and AEGL-2 as:

“AEGL-1 is the airborne concentr ation (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, incl uding susceptible individuals, could experience notable discomfort, irritati on, or certain asymptomatic nonsensory effects. However, the effect s are not disabling and are transient and reversible upon cessation of exposure.”

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

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

Emergency Response Planni ng Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emerge ncy Response Planning Guidelines (ERPGs) [ 19 ] for acute exposures at three different levels of severity. These guidelines represent concentrations for exposure of the general population (but not part icularly sensitive persons) for up to 1 hour associated with effect s expected to be mild or transient (ERPG1), irreversible or serious (ERPG-2), a nd potentially life-threatening (ERPG-3).

ERPG values ( http://www.aiha.org/1documents /Committees/ERP-erpglevels.pdf ) are described in their supporting documentation as follows: “Emergency Response Planning Guidelines (ERPGs) were developed for emer gency planning and are intended as health based guideline concentrations for single expos ures to chemicals. These guidelines (i.e., the ERPG Documents and ERPG values) ar e intended for use as planning tools for assessing the adequacy of accident preventi on and emergency response plans, includingDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

17 transportation emergency planning and for developing community emergency response plans. The emphasis is on ERPGs as pl anning values: When an actual chemical emergency occurs there is seldom time to m easure airborne concentr ations and then to take action.” As with other emergency levels , these levels reflect consideration of only single exposure events, not re peated exposures.

ERPG-1 and ERPG-2 values are defined by AIHA as follows:

“ERPG-1 is the maximum airborne concentration below which it is believed that nearly all individuals coul d be exposed for up to 1 hour without experiencing other

than mild transient adverse health effect s or without perceivi ng a clearly defined, objectionable odor.”

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

The emissions inventory for the Primary Lead Smelting source category includes

emissions of two HAP with relevant and available quantitativ e acute dose-response threshold values. Specifically, REL values for arsenic and nickel are listed below in

Table 2.6-2.

Table 2.6-2 Dose-Response Values for Acute Exposure

Pollutant CAS

Number AEGL-1 (1-hr) (mg/m 3 ) AEGL-2 (1-hr) (mg/m 3 ) ERPG-1 (mg/m 3 ) ERPG-2 (mg/m 3 ) REL
Arsenic Compounds 7440382 0.0002
Nickel Compounds 7440020 0.006



### 2.7 Risk Characterization

2.7.1 General

The final product of the risk assessment is the risk characterization, in which the information from the previous steps is integr ated and an overall conclusion about risk is synthesized that is complete, informative, and useful for decision makers. In general, the

nature of this risk character ization depends on the informati on available, the application

of the risk information and the resources availa ble. In all cases, major issues associated with determining the nature a nd extent of the risk are identified and di scussed. Further,

the EPA Administrator’s March 1995 Policy for Risk Characterization [ 20 ] specifies that a risk characterization “be prepared in a manner that is clear, transp arent, reasonable, and

consistent with other risk characterizations of similar scope prepared across programs inDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

18 the Agency.” These principles of transparen cy and consistency have been reinforced by

the Agency’s Risk Characterization Handbook [ 21 ], in 2002 by the Agency’s information quality guidelines [ 22 ], and in the OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis 7 , and are incorporated in these assessments.

Estimates of health risk are pr esented in the context of uncertainties and limitations in the data and methodology. Through our tiered, iter ative analytical approach, we have attempted to reduce both uncer tainty and bias to the grea test degree possible in these assessments. 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 associat ed 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, individual and population cancer risks were calculated by multiplying the corresponding lifetime average exposure es timate by the appropriate URE. This

calculated cancer risk is defined as th e upper-bound probability of developing cancer over a 70-yr period (i.e., the assumed human lif espan) at that exposure. Because UREs for most HAPs are upper-bound estimates, actual risks at a given e xposure level may be lower than predicted, and could be zero.

In addition, increased cancer incidence for the entire recept or population within the area of analysis was estimated by multiplying th e 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 was divided by 70 years to obtain an estimate of th e number of cancer cases per year.

Unlike linear dose-response assessments for cancer, noncancer health hazards generally are not expressed as a probability of an adve rse occurrence. Instead, “risk” for noncancer effects is expressed by comparing an exposur e to a reference level as a ratio. The “hazard quotient” (HQ) is the estimated expos ure divided by a reference level (e.g., the RfC). For a given HAP, exposures at or below the reference level (HQ ≤ 1) are not likely to cause adverse health effects. As expos ures increase above the reference level (HQs increasingly greater th an 1), the potential for adverse effects increases. For exposures predicted to be above the RfC, the risk char acterization includes th e degree of confidence ascribed to the RfC values for the compound( s) of concern (i.e., high, medium, or low confidence) and discusses the impact of this on possible health interpretations.

7 Memorandum for the Heads of 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 Technology Policy (http://www.whitehouse.gov/omb/memoranda/fy2007/m07-24.pdf)Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

19 The risk characterization for chronic effects ot her than cancer is expr essed in terms of the HQ for inhalation, calculated for each HAP at each census block centroid. As discussed above, RfCs incorporate generally conservati ve uncertainty factors in the face of uncertain extrapolations, such that an HQ gr eater 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 proporti onal to adverse health effect outcomes in a population.

Screening for potentially signi ficant acute inhalation exposures also followed the HQ approach. In this case, we divided th e maximum estimated acute exposure by each

available short-term threshold value to deve lop an array of HQ values relative to the various acute endpoints and thresholds. In general, when none of these HQ values are greater than one, there is no potential for acu te risk. In those cases where HQ values above one are seen, additional information is used to determine whet her there is truly 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 th e aggregate health risks associated with all the exposures from a particular source category combined.

To combine risks across multiple carcinogens, our assessments use the mixtures guidelines’ [ 23

, 24 ] 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 expo sures, in cases where different pollutants

cause adverse health effect s via completely different modes of action, it may be inappropriate to aggregate HQs. In consid eration of these mode-of-action differences, the mixtures guidelines support aggregating effect s of different substan ces in specific and limited ways. To conform to these guidelin es, we aggregated non-cancer HQs of HAPs that act by similar toxic modes of action or (whe re 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 system. All TOSHI calculations presented here were based exclusively on effects o ccurring at the “critical dose” (i.e., the lowest dose that produces adverse health effects). Although HQs associated with some pollutants have been aggregated into more than one TOSHI, this has been done only in cases where the critical dose affects more than one target organ. Because impacts on organs or systems

that occur above the critical dose have not been include d in the TOSHI calculations, some TOSHIs may have been underestimated. As with the HQ, the TOSHI should not be interpreted as a probability of adverse effects or as st rict delineation of “safe” andDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

20 “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 pot ential exposures, acute impacts were screened on an individual pollutant basis, not using the TOSHI approach.



### 2.7.3 Facility-wide Risks

To help place the source category risks in c ontext, we typically examine “facility-wide” risks using facility-w ide and source category data files developed by EPA thru emission data updates from industry and refined EPA profiles for the source category. In this instance, there are no other HAP emission sour ces present-- all HAP sources have been included in the risk analysis. Therefore, the facility-wide risk is the same as the source category risk; no separate facili ty-wide analysis was necessary.



### 3. Risk Results for the Primary Lead Smelting Source Category

3.1 Source Category Description and Results

The primary lead smelting source category includes one facility that smelts lead-bearing ore concentrates to produce lead metal. This metal is used to make various construction and consumer products such as batteries, pain t, glass, piping, and f iller. Lead sulfide (PbS) ore concentrates are the main feed mate rial to primary lead smelters. The primary lead smelting process consists of PbS concen trate storage and handling, sintering of ore concentrates, sinter crushing and handling, smelti ng of sinter to lead metal, drossing (i.e., removing the solid oxide deposits), refining a nd alloying of lead metal, and smelting of the drosses. Hazardous air pollutants (HAP) can be emitted during these steps as process emissions, process fugitive emissions, and fug itive dust emissions. Across all three of these types of emission points, lead and lead compounds are the main HAP emitted. Other emissions include other metal HAP, su ch as arsenic, antimony, and cadmium.

As noted above, there is only one primary lead smelter currently operating in the U.S., and the NPRM data set for this source category contains data for this one facility. Figure 3.1-1 shows the facility, mode ling receptor locations along its boundary, as well as the locations of nearby ambient lead monitors. Figure 3.1-1 also identifies the census block MIR, and the location of the highest ambient lead concentr ation (see results in section 3.2). The data set for this facility was de veloped based on site-spe cific information and represents a base year of 2008 (see section 2.1). A complete discussion of the creation of

the NPRM data set can be found in the NPRM.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

21 Figure 3.1-1 Discrete Receptors and Maxi mum Risk Receptors for the Doe Run Primary Lead Smelter in Herculaneum, Missouri

The emissions in the primary lead sme lting source category NPRM data set are

summarized in Table 3.1-1. The total HAP emissions for the source category are approximately 21 tons per year. Based on th ese data, lead is th e HAP emitted in the largest quantity and constitutes more than 99 percent of the total mass emitted of HAP. Persistent and bioaccumulative HAP (PB HAP ) emissions reported in the NPRM dataset

include lead and cadmium.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

22 Table 3.1-1 Summary of Emissions from the Primary Lead Smelting Source Category and Availability of Dose-Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting

HAP (1 facility in

ANPRM data set) Prioritized Inhalation Dose-Response Value Identified by OAQPS b

PBHAP? Unit Risk

Estimate for

Cancer? Reference

Concentration

for Noncancer? Health

Benchmark

Values for Acute

Noncancer?

Lead & Compounds 21 1 Y c 
Cadmium Compounds 0.1 1   

Antimony Compounds 0.03 1 

Arsenic Compounds 0.02 1   
Nickel Compounds 0.02 1   
Chromium Compounds
Chromium III Compounds 0.005 1
Chromium VI Compounds 0.0002 1  
Cobalt Compounds 0.005 1 

a Note for how HAP were speciated for risk assessment: For most metals, emissions reported as the elemental metal are combined with metal compound emissions (e.g., “cadmium” emissi ons modeled as “cadmium & compounds”). In the absence of speciation information, we assu me the reported mass is 100 percent metal.

b Specific dose-response values for each chemical are identified on EPA’s Te chnology Transfer Network website for

air toxics at http://www.epa.gov/ttn/atw/ toxsource/summary.html . See tables 2.6-1 and 2.6-2 above.

c In considering the air-related multipathway hazards for lead in this assessment, we used the National Ambient Air Quality Standards (NAAQS) for lead, which were adopted in October 2008 ( http://www.epa.gov/air /lead/actions/html ). The primary (health-based) standard is 0.15 μg/m 3 , as a maximum or not-to-be-exceeded, rolling three-month average, measured as total suspended particles (TSP). The seconda ry (welfare-based) standard is equal to the primary.



### 3.2 Baseline Risk Characterization

This section presents the resu lts of the preliminary risk assessment for the Primary Lead Smelting source category. The basic chronic in halation risk estimates presented here are the maximum individual lifetime cancer risk, the maximum chronic hazard index, and the cancer incidence. We also present results from our acute inhalation impact 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 presen ted are the HAP “drivers,” which are the HAP that collectively contribute 90 percent of the maximum cancer risk or maximum hazard at the highest e xposure location, as well as a summary of the results of

the maximum allowed emissions under the current MACT standards. .

Table 3.2-1 summarizes the preliminary chronic and acute inhalation risk results for this source category for all HAP except for lead. The results of the chronic inhalation cancer

risk assessment indicate the maximum lifetime i ndividual cancer risk could be as high asDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

23 30 in a million with fugitive dust emissions of cadmium dominating the risk. The total

estimated cancer incidence from this source category based on actual emission levels is 0.0008 excess cancer cases per year, or one cas e in every 1,250 years. Approximately 200 people were estimated to have cancer ri sks above 10 in a million, and approximately 4,900 people were estimated to have cancer ri sks above 1 in a million. Finally, when considering MACT allowable emissions, the MIR remains 30 in a million. This is because fugitive dust emissions, which are driving the risk, are covered by a work practice standard under the MACT and theref ore, MACT-allowable and actual fugitive dust emissions are equal.

Table 3.2-1 Summary of Source Category Le vel Inhalation Risks for the Primary Lead Smelting Facility – non-lead HAP

Result HAP “Drivers”

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 1 million) 30 cadmium compounds, arsenic compounds, nickel compounds

Chronic Noncancer Risks Maximum Kidney Hazard Index 1 cadmium compounds

Acute Noncancer Risks

Maximum Acute Hazard Quotient 6

0.4 arsenic compounds (REL) nickel compounds (REL)

Refined Acute Noncancer Risk Maximum Refined Acute Hazard Quotient 0.6 arsenic compounds (REL) Population Exposure Number of People Living Within 50 Kilometers of the Facility Modeled 1,509,000 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 200 n/a

Greater than or equal to 1 in 1

million 4900 n/a

Number of People Exposed to Noncancer Kidney Hazard Index:

Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.0008 n/a

Contribution of HAP to Cancer Incidence cadmium compounds 82% n/a arsenic compounds 16% n/a nickel compounds 2% n/a

The maximum chronic noncancer TOSHI value is 1, with fugitive dust emissions of cadmium dominating those impacts. When considering MACT allowable emissions, for the reason provided above, the maximum ch ronic noncancer TOSHI value remains 1. Taken together, these results indicate no significant potential for chronic noncancer impacts.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

24 Based on the acute REL value for arsenic, our screening analysis determined that the maximum off-site acute HQ value from this facility could be as high as 6, again dominated by the emissions of fugitive dust. Our refined acute assessment reduced the estimate to a maximum off-site acute HQ valu e of 0.6. The refined assessment took into

consideration that an emissions factor of 10 times the average hourly emissions rate (see above, section 2.4) is not appropriate in this instance, given that fugitive emissions are minimized during the meteorological conditions associated with the worst-case shortterm impacts (i.e., during low-wi nd, stable atmospheric conditions).

Table 3.2-2 presents the results of our l ead impact analysis broken down by emission point considering actual 2008 em issions as well as the maximum emissions of lead that

the MACT standard would have allowed for the 2008 base year. Resu lts indicate that estimated 3-month rolling aver age lead concentrations resulting from this facility’s fugitive dust emissions could exceed the primar y NAAQS for lead by as much as 50-fold. This analysis also indicates that emissions from the main stack do not result in estimated ambient lead concentrations that exceed the primary NAAQS anywhere within 50 km of the facility (likely due to st ack height), and that emissions from furnace area stacks could

result in estimated ambient lead concentra tions that exceed the NAAQS under both actual

2008 and MACT-allowable emissions scenarios. In addition, although refining operations were not subject to the emission limit under th e MACT, results of this analysis indicate that actual emissions from the refining st acks could result in estimated ambient lead concentrations that exceed the NAAQS. This an alysis also indicates that within 50 km of this facility, approximately 1,900 people could be exposed to ambient lead concentrations exceeding the primary NAAQS for lead.

As mentioned above, to evaluate the potential for adverse environmental effects, we also compared maximum 3-month rolling average a tmospheric concentratio ns with the current secondary NAAQS for lead (which is identical to the primary, health -based standard). Thus, the analyses presented in Table 3.2-2 also indicate the pot ential for adverse

environmental effects from emissions of lead.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

25 Table 3.2-2 Summary of Lead Concentratio ns Relative to the NAAQS Given Actual

2008 and MACT Allowable Emissions

Emission Point Actual 2008 Emissions (tpy) Maximum Impact- Actual

Emissions MACT Allowable

Emissions 1 MaximumImpactAllowable

Emissions

Main stack 2 13.31 0.05 times the NAAQS 65.8 0.25 times the NAAQS

Refining stacks 2.74 3 times the NAAQS NA NA

Furnace area: (controlled blast and

drossing fugitives) 1.81 2 times the NAAQS 8.94 10 times the NAAQS

Fugitive dust 3 2.85 50 times the NAAQS 2.85 50 times the NAAQS

1 Allowables for the main stack and furnace area emission points are based on 1 lb of Pb/ton production (MACT limit that is also codified in the state permit); refining operations were not subject to the emission limit under the MACT.

2 Main stack is the emission point for sinter m achine, blast furnace an d drossing operations.

3 Fugitives covered by work practices under current MACT and were calculated via emission factors assuming compliance with the MACT.

In addition to the results pr esented above, for calendar year 2008, we also compared

maximum AERMOD estimates of ambient lead c oncentrations with those measured at 4 monitors in close proximity to the only facil ity in this source category. Specifically, we compared the maximum 3-month rolling averag e lead concentrations reported at the Main Street, Circle Street, South Cross, a nd Church Street monitors to the maximum 3- month rolling average lead concentrations at model receptor locations at or near these monitoring sites. Results of this analysis indi cate that with respect to the Main Street and Circle Street monitors, AERMOD underestimates 3-month maximum lead concentrations by approximately 4.6- and 3-fo ld respectively. With resp ect to the South Cross and Church Street monitors, AERMOD overestimates 3-month maximum lead concentrations by approximately 2.8- and 4.2-fold, respect ively. Moreover, the maximum 3-month average lead concentration reported by any of these monitors is a pproximately equal to the maximum 3-month average lead concen tration estimated by AERMOD at any of these monitoring sites (i.e., both the South Cross monitor and the Main Street AERMOD

estimates indicate maximum 3-month aver age lead concentrations of 2.1 μg/m 3 ). Taken together, these results indicate that AERMOD estimates of ambient lead concentration provide a reasonable representation of the measured maximum lead concentrations present in the ambient ai r near this facility.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

26 

### 3.3 Assessment of Emission Reductions Scenarios

To inform possible risk management actions , we considered specific emission limits for those emission points that were modeled to resu lt in lead concentrations in excess of the NAAQS (see Table 3-2.2). In so doing, we f ound that in order to meet the NAAQS for lead, fugitive dust emissions would have to be reduced by approximately 98% to 0.064 tpy, refinery emissions would have to be reduced by approximately 66% to 0.94 tpy, and furnace area emissions would have to be reduced by approximately 52% to 0.86 tpy. Further, because the ambient impacts of each of the separate emission points do not overlap significantly on each other, we estimat e that lead emissions from all emission points other than the main stack would have to be limited to a total of approximately 1.86 tpy in order to ensure 3-month rolling aver age ambient lead concentrations do not exceed the primary lead NAAQS level of 0.15 μg/m 3 . Finally as noted above, emissions from the main stack (i.e., emission point for si nter machine, blast furnace and drossing operations) did not result in ambient lead c oncentrations in excess of the lead NAAQS at

modeled locations within 50 km of the fen celine and thus, we are not proposing any

reductions at the main stack in orde r to meet the NAAQS for lead.



## 4. General Discussion of Uncertainties and How They

Have Been Addressed

4.1 Exposure Modeling Uncertainties

Although every effort has been made to identif y all the relevant emission points, as well as to develop accurate estimates of the a nnual emission rates for all relevant HAP, the uncertainties in our emission inventory likely dominate the uncertainties in our exposure modeling estimates. The chronic exposure modeling uncertainties are considered relatively small in comparison, since we are using EPA’s refined local dispersion model with site-specific parameters and mete orology. If anything, the population exposure estimates are biased high by not accounting fo r short- or long-term population mobility and by neglecting processes like depos ition, plume depletion, and atmospheric degradation.

We have purposely biased the acute screeni ng results high, consider ing that they depend upon the joint occurrence of independent f actors, such as hourl y emissions rates, meteorology and human activity patterns.



### 4.2 Uncertainties in the Dose-Response Relationships

In the sections that follow, separate discus sions are provided on uncertainty associated with cancer potency factors a nd noncancer reference values. Cancer potency values are derived for chronic (lifetime) exposures. Noncancer reference values are generally derived for chronic exposures (up to a lifet ime), but may also be derived for acute (

 <24 hours), short-term (>24 hours up to 30 days), and subchronic (>30 days up to 10% of lifetime) exposure durations, all of whic h are derived based on an assumption ofDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

27 continuous exposure throughout the duration spec ified. For the purposes of assessing all potential health risks associated with the emissions included in an assessment, we rely on both chronic (cancer and noncancer) and acu te (noncancer) benchmarks, which are

described in more detail below.

Although every effort is made to identify peer-reviewed dose-res ponse values for all HAPs emitted by the source category included in an assessment, some HAP have no peer-reviewed cancer potency values or refere nce values for chronic non-cancer or acute effects (inhalation or ingestion). Since exposur es to these pollutants cannot be included in a quantitative risk estimate, an understa tement of risk for these pollutants at environmental exposure levels is possible.

Additionally, chronic dose-response values for certai n compounds included in the assessment may be under EPA IRIS review, a nd 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 revi ews, a dose-response metric cha nges enough to indicate that the risk assessment may significantly mi scharacterize human health risk

Cancer assessment

The discussion of dose-response uncertainties in the estimation of cancer risk below

focuses on the uncertainties associated with the specific approach currently used by the EPA to develop cancer potency factors. In general, these same uncertainties attend the development of cancer potency factors by Ca lEPA, the source of peer-reviewed cancer potency factors used where EPA-developed valu es are not yet available. To place this discussion in context, we pr ovide a quote from the EPA’s Guidelines for Carcinogen Risk

Assessment [ 25 ] (herein referred to as Cancer Guidelines ). “The primary goal of EPA actions is protection of human health; accord ingly, as an Agency policy, risk assessment procedures, including default optio ns that are used in the absenc e of scientific data to the contrary, should be health protective.” Th e approach adopted in this document is consistent with this approach as described in the Cancer Guidelines

.

For cancer endpoints EPA usually derives an or al slope factor for ingestion and a unit risk value for inhalation exposures. Thes e values allow estimation of a lifetime probability of developing cancer given long-te rm exposures to the pollutant. Depending on the pollutant being evaluated, EPA relies on both animal bioassay and epidemiological

studies to characterize cancer risk. As a sc ience policy approach, consistent with the

Cancer Guidelines , EPA uses animal cancer bioassays as indicators of potential human

health risk when other human cancer risk data are unavailable.

Extrapolation of study data to estimate poten tial risks to human populations is based upon

EPA’s assessment of the scientific data base 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 deve loped following the procedures described in

the Cancer Guidelines and outlined below generally provide an upper bound estimate ofDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

28 risk. That is, EPA’s upper bound estimates repr esent a “plausible upper limit to the true value of a quantity” (although th is is usually not a true statistical c onfidence limit). 8 In some circumstances, the true risk could be as low as zero; however, in other circumstances the risk could also be greater. 9 When developing an upper bound estimate of risk and to provide risk values that do not underestimate risk, EPA generally relies on conservative default approaches. 10 EPA also uses the upper bound (rather than lower bound or central) estimates in its assessments, although it is no ted that this approach can have limitations for some uses (e.g. priority setting, expected benefits analysis).

Such health risk assessments have asso ciated uncertainties, some which may be considered quantitatively, and others wh ich generally are expressed qualitatively. Uncertainties may vary substantially among cancer risk assessments associated with exposures to different polluta nts, since the assessments em ploy different databases with different strengths and limitations and the pr ocedures employed may differ in how well they represent actual biological processe s for the assessed substance. EPA’s Risk
Characterization Handbook also recommends that risk characterizations present estimates demonstrating the imp act on the assessment of alternative choices, data, models and assumptions [ 26 ]. Some of the major sources of uncertainty and variability in deriving cancer risk values are de scribed more fully below.

(1) The qualitative similarities or differen ces between tumor responses observed in experimental animal bioassays and those wh ich would occur in humans are a source of uncertainty in cancer risk assessment. In ge neral, EPA does not assume that tumor sites observed in an experimental animal bioassay are necessarily predictive of the sites at

which tumors would occur in humans. 11 However, unless scientif ic support is available to show otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target organ concordance. For a specific pollutant, qual itative differences in species responses can lead to either under-e stimation or over-estimation of human cancer

risks.

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

9 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, an d which is based on maximum likelihood estimates.

10 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are generic approaches, based on general scientific knowledge and policy judgment, that are applied to various elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may de part from them in evaluating the risks posed by a specific substance when it believes this to be appropriat e. In keeping w ith EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An Examination of EPA Risk Assessment Principles and Practices, EPA/100/B- 04/001 available at: http://www.epa.gov/osa/pdfs/ratf-final.pdf.

11 Per the EPA Cancer Guidelines: “The default option is that positive effects in animal cancer studies indicate that the agent under study can have carci nogenic 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 Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

29 (2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead to differences in risk predictions. For example, the measure of dose is commonly expressed in units of mg/kg/d ingested or the inhaled concentrati on 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 uncer tainties 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 phar macokinetic 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 (re lating expected response to differences in physical size of the species), which introdu ce another source of uncertainty. These methodologies are based on both biological data on differences in rates of process according to species size and empirical compar isons of toxicity between experimental animals and humans. For a particular pollu tant, the quantitative difference in cancer potency between experimental animals and hum ans 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 estimates.

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, are generally developed using a benchm ark dose (BMD) analysis to estimate a dose at which there is a specified ex cess risk of cancer, which is us ed as the point of departure (or POD) for the remainder of the calculati on. Statistical uncerta inty in developing a POD using a benchmark dose (BMD) approach is generally addresse d though use of the

95% lower confidence limit on the dose at whic h the specified excess risk occurs (the BMDL), decreasing the likelihood of understatin g risk. EPA has generally utilized the multistage model for estimation of the BMDL using cancer bioassay data (see further discussion below).

(5) Extrapolation from high to low doses is an important, and potential ly large, source of uncertainty in cancer risk assessment. EPA uses different approaches to low dose risk assessment (i.e., developing estimates of risk for exposures to environmental doses of an agent from observations in experimental or epidemiological studi es at higher dose) depending on the available data and understand ing of a pollutant’s mode of action (i.e., the manner in which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use of reliable, compound- specific, biologically based risk models when feasible; however, such models are rare ly 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 fo r low-dose exposure. A reference value is

calculated when the available mode of acti on 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 wh en a compound’s mode of action is unknown.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

30 Linear 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 po llutants that interact with DNA and induce

mutations. Pollutants whose effects are add itive to background biological processes in cancer development can also be predicted to have low-dose linear responses, although the slope of this relationship may not be the same as the slope estimate d by the straight line approach.

EPA most frequently utilizes a linear low-dose extrapolati on approach as a baseline science-policy choice (a “default”) when av ailable data do not al low a compound-specific determination. This approach is designed to not underestimate risk in the face of uncertainty and variability. EPA believe s that linear dose-re sponse models, when appropriately applied as part of EPA’s cance r risk assessment process, provide an upper bound estimate of risk and genera lly provide a health protective approach. Note that another source of uncertainty is the charac terization of low-dose nonlinear, non-threshold relationships. The National A cademy of Sciences has encouraged the exploration of sigmoidal type functions (e.g., log-prob it models) in representing dose response relationships due to the vari ability in response within hum an populations. A recent National Research Council (NRC) report [ 27] suggests that models based on distributions

of individual thresholds are li kely to lead to sigmoidal-sh aped dose-response functions for a population. This report notes sources of variability in the human population: “One might expect these individual tolerances to vary extensively in humans depending on genetics, coincident exposures, nutritiona l status, and various other susceptibility factors...” Thus, if a distri bution of thresholds approach is considered fo r a carcinogen risk assessment, application would depend on ab ility of modeling to reflect the degree of variability in response in human populations (as opposed to responses in bioassays with genetically more uniform rodents) . Note also that low dose li nearity in risk can arise for reasons separate from population variability: du e 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 can cer risk assessment typically utilizes a straight line approach from the BMDL. This is equivalent to using an upper confidence limit on the slope of the straight line extrap olation. The impact of the choice of the BMDL on bottom line risk estimates can be qua ntified by comparing risk estimates using

the BMDL value to central estimate BM D values, although these differences are generally not a large contributor to uncertain ty in risk assessment (Subramaniam et al., 2006) [ 28 ]. 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 al. (2006) also provide comparisons indicati ng that slopes based on straight line extrapolati on from a POD do not show larg e differences from those based on the upper confidence limit of the multistage model.

(6) Cancer risk estimates do not generally make specific adjustments to reflect the variability in response within the human population — resulting in another source ofDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

31 uncertainty in assessments. In the diverse human population, some individuals are likely

to be more sensitive to the action of a carcinogen than the typi cal individual, although compound-specific data to evalua te this variability are gene rally not available. There may also be important life stage differences in the quantitative potency of carcinogens and, with the exception of the recomme ndations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic mode of action, risk assessments do not generally quantitatively addr ess life stage differences. However, one approach used commonly in EPA assessments that may help address variability in response is to extrapolate human response from results observed in the most sensitive species and sex tested, resulting typical ly in the highest URE which can be supported by reliable data, thus supporting estimates that are designed not to underestimate risk in the face of uncertainty and variability.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure le vels 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 approach that is intended not to underestimate risk in the face of uncertainty and variability. When there are gaps in th e available information, uncertainty factors (UFs) are applied to derive reference values that are intended to be protective against appreciable risk of deleterious effects. Uncertainty fact ors are commonly default values 12
e.g., factors of 10 or 3, used in the absence of compound-specific data; where data are available, uncertainty factors may also be developed using compound-specific information. When data are limited, more assumptions are needed and more default factors are used. Thus there may be a greater tendency to overestimate risk—in the sense that further study might support development of reference values that are higher (i.e., less potent) because fewer default assumptions are needed. However, for some pollutants it is possible that risks may be underestimated.

To address multipathway risks associated with emissions of lead from this facility, ambient lead concentrations were compared to the NAAQS for lead. In developing the NAAQS for lead, uncertainties associated with th e health evidence and risk and exposure analyses were explicitly considered duri ng the standard-setting process. More

12 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are generic approaches, based on general scientific knowledge and policy judgment, that are applied to various elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process

defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may de part from them in evaluating the risks posed by a specific substance when it believes this to be appropriat e. In keeping w ith EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An examination of EPA Risk Assessment Principles and Practices, EPA/100/B-04/001 available at: http://www.epa.gov/osa/pdfs/ratf-final.pdf.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

32 specifically, these uncertainties were carefully considered when selecting the appropriate indicator, averaging time, form, and level of the NAAQS for lead. A description of the uncertainties and how they were considered in setting the NAAQS can be found in EPA’s final rule establishing the lead NAAQS (73F R66964). In general, the uncertainties

associated with the establ ishment of the NAAQS are small relative to those for doseresponse values developed for many of the other HAPs. This is because the development of the lead NAAQS used the re sults from numerous human ep idemiological studies rather than relying solely on the extr apolation of animal studies. In addition, because of the multi-pathway, multi-media impacts of lead, the development of the NAAQS considered direct inhalation exposures and indirect air-related multi-path way exposures from industrial sources like primary and secondary lead smelting operations, as well as background lead exposures from all other sour ces (like contaminated drinking water and exposure to lead-based paints) when derivi ng an ambient concentration level which is considered to protect human health w ith an adequate margin of safety.

For non-cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) for exposures via ingestion and a Re ference Concentration (RfC) for inhalation exposures. These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) of a daily oral exposure (RfD ) or a continuous inhalation exposure (RfC) to the human population (including sensitive su bgroups) that is likel y to be without an appreciable risk of deleteri ous effects during a lifetime. 13 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, 1994) which includes consideration of both uncertainty and variability.

EPA begins by evaluating all of the availabl e peer-reviewed literature to determine noncancer endpoints of concern, evaluating the quality, strengths and limitations of the available studies. EPA typically chooses the relevant endpoint that occurs at the lowest dose, often using statistical modeling of th e available data, and then determines the appropriate point of departur e (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 whic h the toxic response was not significantly elevated (no observed adverse effect level— NOAEL); or (3) use of the lowest observed adverse effect level (LOAEL).

A series of downward adjustments using de fault UFs is then applied to the POD to estimate the reference value (U.S. EPA 1994, 2002). While collectively termed “UFs”,

these factors account for a number of different quantitative considera tions when utilizing observed animal (usually rodent) or human toxi city data in a risk assessment. The UFs are intended to account for: (1) variation in susceptibility among the members of the human population (i.e., inter-indi vidual variability); (2) uncer tainty in extrapolating from experimental animal data to humans (i.e., in terspecies differences); (3) uncertainty in extrapolating from data obtained in a st udy with less-than-lifetime exposure (i.e., extrapolating from subchronic to chronic expos ure); (4) uncertainty in extrapolating from a LOAEL in the absence of a NOAEL; and (5) uncertainty when the database is

13 See IRIS glossaryDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

33 incomplete or there are problems with appl icability of available studies. When scientifically sound, peer-reviewed assessment- specific data are not available, default adjustment values are selected for the indi vidual UFs. For each type of uncertainty (when relevant to the assessment), EPA typically applies an UF value of 10 or 3 with the cumulative UF value leading to a downward adjustment of 10-3000 fold from the

selected POD. An UF of 3 is used when the data do not support the use of a 10-fold factor. If an extrapolation st ep or adjustment is not releva nt to an assessment (e.g., if applying human toxicity data and an inters pecies extrapolation is not required) the associated UF is not used. The major adjustment steps are described more fully below.

1) Heterogeneity among humans is a key source of variability as well as uncertainty. Uncertainty related to human vari ation is considered in extrapolating doses from a subset or smaller-sized population, ofte n of one sex or of a narrow range of life stages (typical of occupati onal epidemiologic studies), to a larger, more diverse population. In the absence of pollutant-specifi c 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 signi ficant variability among humans.

2) Extrapolation from results of studie s 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 hum an 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 extra polations. In the absence of data to the contrary, the typical approach is to use the most relevant endpoint from the most sensitive species and the most sensitive sex in assessi ng risks to the average human. Typically, compound specific data to evalua te relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty in this extrapolation. Size -related differences (allometric relationships) indica te that typically humans are more sensitive than rodents when compared on a mg/kg/day basis. The defa ult choice of 10 for the interspecies UF is

consistent with these differences. For a specific chemical, differences in species responses may be greater or less than this value.

Pharmacokinetic models are useful to examine species differences in pharmacokinetic processing and associated uncertainties; however, such dosimetric adjustments are not always possible. Inform ation may not be availa ble to quantitatively

assess toxicokinetic or toxi codynamic differences between animals and humans, and in many cases a 10-fold UF (with separate factor s of 3 for toxicokinetic and toxicodynamic components) is used to account for exp ected species differences and associated uncertainty in extrapolating from laboratory animals to humans in the derivation of a

reference value. If information on one or th e other of these components is available and accounted for in the cross-specie s extrapolation, a UF of 3 may be used for the remaining
component.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

34 3) In the case of reference values fo r chronic exposures where only data from shorter durations are available (e.g., 90-day s ubchronic studies in rode nts) or when such data are judged more appropriate for developmen t of an RfC, an additional UF of 3 or 10- fold is typically applied unless the availabl e scientific informa tion supports use of a

different value.

4) Toxicity data are typically limited as to the dose or exposure levels that have

been tested in individual st udies; in an animal study, for example, treatment groups may differ in exposure by up to an order of magnit ude. The preferred appr oach to arrive at a POD is to use BMD analysis; however, this approach requires adequate quantitative results for a meaningful analysis, which is not always possible. Use of a NOAEL is the next preferred approach after BMD analysis in determining a POD for deriving a health 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 a ccount for the potential for deriving an underprotective RfD/RfC due to a data gap pr eventing complete char acterization of the chemical’s toxicity. In the absence of studies for a known or suspected endpoint of concern, a UF of 10 or 3-fold is typically applied.

Acute noncancer assessment

Many of the UFs used to account for variabil ity and uncertainty in the development of acute reference values are quite similar to those developed for chronic durations, but more often using individual UF values that may be less than 10. UFs are applied based on chemical-specific or health effect-specifi c information (e.g., simp le irritation effects do not vary appreciably between human individuals, hence a valu e of 3 is typically used), or based on the purpose for the reference valu e (see the following paragraph). The UFs applied in acute reference va lue 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 observati ons at one exposure dur ation (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 fo r the same purpose, and care must be taken when interpreting the results of an acute a ssessment of human health effects relative to the reference value or values being exceeded. Where relevant to the estimated exposures,

the lack of threshold values at different levels of severity should be factored into the risk characterization as poten tial uncertainties.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

35 

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2 US EPA, 2009. Risk and Technology Revi ew (RTR) Risk Assessm ent Methodologies: For Review by the EPA’s Science Advisory Boar d with Case Studies – MACT I Petroleum Refining Sources and Portland Cement Manufacturing. EP A-452/R-09-006. http://www.epa.gov/ttn/a tw/rrisk/rtrpg.html.

3 . US EPA, 2010. SAB’s Response to EPA’s RTR Risk Assessment Methodologies. http://yosemite.epa.gov/sab/sabpr oduct.nsf/4AB3966E 263D943A8525771F00668381/$Fi le/EPA-SAB-10-007-unsigned.pdf

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

5 . US EPA, 2005. Revision to the Guideline on Air Quality Models: Adop tion of a Preferred General Purpose (Flat and Complex Terrai n) Dispersion Model and Other Revisions;

Final Rule. 40 CFR Part 51. http://www.epa.gov/EPA-A IR/2005/November/Day09/a21627.htm

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7 . Allen, D., C. Murphy, Y. Kimura, W. Vizuet e, T. Edgar, H. Jeffries, B.-U. Kim, M. Webster, and M. Symons, 2004. Variable indu strial VOC emissions and their impact on

ozone formation in the Houston Galveston Area. Final Report: Texas Environmental

Research Consorti um Project H-13. http://files.harc.edu/Pr ojects/AirQua lity/Projects/H013.2003 /H13FinalReport.pdf

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9 . US EPA, 2005. Table 1. Prioritized Chr onic Dose-Response Values (2/28/05). Office of Air Quality Planning and Standards. http://www.epa.gov/ttn/at w/toxsource/table1.pdf

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12. US Agency for Toxic Substances and Dise ase Registry. 2006. Minimum Risk Levels (MRLs) for Hazardous Substances. http://www.atsdr.cd c.gov/mrls/index.html

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Inhalation Reference Concentrations a nd Application of Inhalation Dosimetry.Draft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

36 EPA/600/8-90/066F. Office of Research and Development. Washington, DC:

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

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Chemical Mixtures. EPA-630/R-00-002. http://www.epa.gov/ncea/raf/ pdfs/chem_mix/chem_mix_08_2001.pdf

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25 . US EPA, 2005. Guidelines for Carcinogen Ri sk Assessment (2005). U.S. Environmental Protection Agency, Washington, DC, EPA/630/P-03/001F, 2005. http://cfpub.epa.gov/ncea/raf/ recordisplay.cfm?deid=116283

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27 . NRC (National Research Council) 2006. Assessing the Human Health Risks ofDraft Risk Assessment for the Primary Lead Smelting Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

37 Trichloroethylene. National Ac ademies Press, Washington DC.

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