Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 1



## Draft Residual Risk Assessme nt for the Steel Pickling Source Category

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

Office of Air and Radiation July 2010Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 2



### Table of Contents

1 Introduction................................................................................................................. ....... 4
2 Methods...................................................................................................................... ........ 5
2.1 Emissions and source data ......................................................................................... 5 2.2 Dispersion modeling for inha lation exposure assessment ......................................... 5 2.3 Estimating human inhalation exposure ...................................................................... 8 2.4 Acute Risk Screening a nd Refined Assessments....................................................... 8 2.5 Multipathway and environm ental risk screening ....................................................... 9 2.6 Dose-Response Assessment..................................................................................... 10 2.6.1 Sources of chronic dose-response information ................................................ 10 2.6.2 Sources of acute dose-response information.................................................... 12
2.7 Risk Characterization............................................................................................... 15
2.7.1 General ............................................................................................................. 15
2.7.2 Mixtures ........................................................................................................... 16 2.7.3 Facility Wide Risk ........................................................................................... 17 3 Risk Results for the Steel Pickling Source Category................................................... 17 3.1 Source Category Description and Results................................................................ 17
3.2 Risk Characterization............................................................................................... 19
4 General Discussion of Uncertainties a nd How They Have Been Addressed................... 19 4.1 Exposure Modeling Uncertainties............................................................................ 20 4.2 Uncertainties in the Dose-Response Relationships.................................................. 20
5 References................................................................................................................... ..... 25

Index of Tables

Table 2.2-1 AERMOD version 09292 model options for RTR II modeling ............................ 6 Table 2.6-1 Dose-Response Values for Chroni c Inhalation Exposure to Noncarcinogens .... 12 Table 3.1-1 Summary of Em issions from the Steel Pickling Source Category ...................... 18 Table 3.1-2 Summary of Source Categor y Level Risks for Steel Pickling............................. 18

Appendices

Appendix 1 Emissions Inventory Support Memorandum Appendix 2 Technical Support Docu ment for HEM-AERMOD Modeling Appendix 3 Meteorological Da ta for HEM-AERMOD Modeling Appendix 4 Analysis of data on short-term emission rates relative to long-term emission

rates Appendix 5 Detailed Risk Modeling Results

Index of AcronymsDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 3

AERMOD American Meteorological Society/EPA Regulatory Model AEGL Acute exposure guideline level ASTDR US Agency for Toxic Substances and Disease Registry CalEPA California Environmental Agency ERPG Emergency Response Planning Guideline
HAP Hazardous Air Pollutant HEM Human Exposure Model
HI Hazard index HQ Hazard quotient IRIS Integrated Risk Information System MACT Maximum Achievable Control Technology
MIR Maximum Individual Risk
MOA Mode of action NAC National Advisory Committee
NATA National Air Toxics Assessment NEI National Emissions Inventory NPRM Notice of Proposed Rulemaking
PB-HAP Persistent and Bioaccumulative - HAP POM Polycyclic organic matter REL Reference exposure level
RfC Reference concentration
RfD Reference dose RTR Risk and Technology TOSHI Target-organ-specific hazard index
URE Unit risk estimateDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 4



### 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 stationary sources. In the first stage, section 112(d)(2) requires the Environmental Protectio n Agency (EPA, or the Agency) to develop technology-based standards for categ ories of industrial sources (e.g., petroleum refineries, pulp and paper mills, etc.) [ 1 ]. EPA has largely completed the initial Maximum Achievable Control Technology (MACT) standa rds as required under this provision. Under section 112(d)(6), EPA must review each of thes e technology-based standards at least every eight years and revise a sta ndard, as necessary, “taking in to 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 addi tional risk reductions ar e necessary to protect public health with an ample margin of safety or to prevent an adverse environmental effect, EPA must develop standards to address these remaining risks. This second stage of the regulatory process is known as the residual risk stage. For each source category for which EPA issued MACT standards, the residual risk st age must be completed within eight years of promulgation of the initial technology-based standard.

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board (SAB) on the “Risk and Technology Review (R TR) Assessment Plan” and in June of 2007,
we received a letter with the results of that c onsultation. 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) Risk Assessment Methodologies” [ 2 ]. We received the final SAB report on this review in May of 2010. Where appropriate, we have responded to the key messages from this review in developing the risk assessment for this source category. We are providing this draft risk assessment documen t through the National Emission Standards for
Hazardous Air Pollutant Emissions: Hard a nd Decorative Chromium Electroplating and Chromium Anodizing Tanks; Group I Polymers and Resins; Marine Tank Vessel Loading Operations; Pharmaceuticals Production; The Pr inting and Publishing Industry; and Steel Pickling--HCl Process Facilities and Hydroc hloric Acid Regeneration Plants rulemaking docket and thereby soliciting public comment on both the contents of this main report and the
materials contained in the Appendices.

This document contains the methods and the result s of baseline risk asse ssment (i.e., after the implementation of the respective MACT standard ) performed for the Steel Pickling (formally known as Steel Pickling – HCl Process Facilities and Hydrochloric Acid regeneration Plants) source category. The methods discussion incl udes descriptions of the methods used to develop refined estimates of chronic inhala tion exposures and human health risks for noncancer endpoints, as well as de scriptions of the methods used to screen for acute health risks, chronic non-inhalation he alth risks, and adverse environmental effects. No HAP reported as emissions from the facilities in the source category have cancer dose response
values and therefore cancer risk was not assessed for the sour ce category. Since none of the screening assessments indicated any significan t potential for chronic non-inhalation health effects, or environmental impacts including eff ects to threatened and endangered species, noDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 5

further refinement of these assessments wa s performed. Screening assessments did not
indicate a concern for acute health effects for this source category.



### 2 Methods

2.1 Emissions and source data

The 2005 National-Scale Air Toxics Assessmen t (NATA) National Emissions Inventory (NEI) served as the starting point for this assessment. The 2005 NEI purportedly contains information on actual emissions during the enti re 2005 base year. Using the process MACT
code 1 , we developed a subset of this inventory that contai ns emissions and facility data for the Steel Pickling source category addressed. Next, we performed an engineering review of the information using EPA engineers who were dire ctly involved in the development of the MACT standards for the source category, and/ or who have extensive knowledge of the characteristics of this industry. NEI data was updated with indus try supplied data as available. The goal of the engineering review was to identify readily-apparent limitations and issues with the emissions data (particularly t hose that would greatly influence risk estimates) and to make changes to the data set where possi ble to address these 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 the Appendix 1, entitled “Emi ssions Inventory Support Memorandum.”



### 2.2 Dispersion modeling for in halation exposure assessment
Both long- and short-term inhalation exposure co ncentrations and associated health risk from each facility in the source category of interest were estimated using the Human Exposure
Model in combination with the American Meteorological Society/ EPA Regulatory Model dispersion modeling system (HEM-AERMOD). Th e approach used in applying this modeling system is outlined below, and further deta ils are provided in Appendix 2. HEM-AERMOD performs three main operations: atmospheric dispersion modeling, estimation of individual human exposures and health risks, and estimatio n of population risks. This section focuses on the dispersion modeling component. The expos ure and risk characterization components are
discussed in other subsecti ons of Sections 2 and 3.

The dispersion model in the HEM-AERMOD sy stem, AERMOD version 09292, is a state-ofthe-science Gaussian plume di spersion model that is prefer red by EPA for modeling point, area, and volume sources of continuous ai r emissions from facility applications [ 3 ]. Further details on AERMOD can be found in the AERMOD Users Guide [ 4 ]. The model is used to develop annual average ambient concentra tions through the simulation of hour-by-hour

1 The tagging of data with MACT codes allows EPA to de termine reductions attributable to the MACT program. The NEI associates MACT codes corresponding to MACT source categories with stationary major and area source data. MACT codes may be assigned either at the pro cess level or at the site level in the point source data (e.g., the MACT code for municipal waste combustors (M WCs) is assigned at the site level whereas the MACT code for petroleum refinery catalytic crack ing is assigned at the process level).Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 6

dispersion from the emission sources into the su rrounding atmosphere. Hourly emission rates used for 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 interest. The AERMOD model options employed are
summarized in Table 2.2-1 and are discussed further below.

Table 2.2-1 AERMOD version 09292 model options for RTR II 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 representative NW S from nearest site (158 stations)

Meteorological data for HEM-AERMOD is sele cted from a list of 158 National Weather Service (NWS) surface observation stations ac ross the continental United States, Alaska, Hawaii, and Puerto Rico. In most cases the neares t station is selected as representative of the conditions at the subject facility. Ideally, when considering off-site meteorological data most site specific dispersion modeling efforts will em ploy up to five years of data to capture variability in weather patterns from year to year. However, because we had insufficient number of appropriately forma tted model input files derived from available meteorological data, we modeled only a single y ear, typically 1991. While the se lection of a single year may result in under-prediction of l ong-term ambient levels at some locations, likewise it may result in over-prediction at others. For each facility identified by its characteristic latitude and longitude coordinates, the clos est meteorological station was us ed in the dispersion modeling. The average distance between a modeled facility and the applicable meteorological station was 40 miles (72 km). Appe ndix 3 (Meteorological Data Processing Using AERMET for HEM-AERMOD) provides a complete listing of stations and assumptions along with further details used in processing the data through AERM ET. The sensitivity of model results to the
selection of the nearest weathe r station and the use of one y ear of meteorological data is discussed in “Risk and Technology Review (R TR) Risk Assessment Methodologies” [2].

The HEM-AERMOD system estimates ambient con centrations at the ge ographic centroids of census blocks (using the 2000 Census), and at othe r receptor locations that can be specified by
the user. The model accounts for the effect s of multiple facili ties when estimatingDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 7

concentration impacts at each block centroid. Typically we combined only the impacts of facilities within the same source category, and assessed chronic exposur e and risk only for census blocks with at least one resident (i .e., locations where people may reasonably be assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient
concentrations were calculated as the annual average of all estimated short-term (one-hour)
concentrations at each block centroid. Possible future residential use of currently uninhabited areas was not considered. Census blocks, the fi nest resolution availa ble in the census data, are typically comprised of approximately 40 people or about ten households.

In contrast to the developmen t of ambient concentrations fo r evaluating long-term exposures, which was performed only for occupied censu s blocks, worst-case short-term (one-hour)
concentrations were estimated both at the censu s block centroids and at points nearer the facility that represent locations where people may be present for short periods, but generally
no nearer than 100 meters from the center of the facility (note that for large facilities, this 100-meter ring could still contain locations inside the facility property). Since short-term emission rates were needed to screen for the potential for hazard via acute exposures, and since the NEI contains only annual emission tota ls, we applied the gene ral assumption to all source categories that the maxi mum one-hour emission rate from any source was ten times the average annual hourly emission rate for that sour ce. Average hourly emi ssions 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 wa s originally based on engineering judgment. To develop a more robust peak-to-mean emissions factor, and in response to one of the key messages from the SAB consultation on our RTR Assessment Plan, we recently performed an analysis using a short-term emissions dataset from a number of sources located in Texas (originally reported on by Allen et al. 2004)[ 5 ]. In that report, the Texas Environmental Research Consortium Project compared hourly a nd annual emissions data for volatile organic compounds for all facilities in a heavily-industr ialized 4-county area (Harris, Galveston, Chambers, and Brazoria Counties, TX) over an eleven-month time period in 2001. We obtained the dataset and performe d our own analysis, focusing that analysis on sources which reported emitting high quantities of HAP over short periods of time (see Appendix 4, “Analysis of data on short-term emission rates relative to long-term emission rates”). Most peak emission events were less than twice the annual average, and the highest was a factor of 11 times the annual average. The factor of te n is intended to cover both routinely-variable emissions as well as startup, shutdown, and ma lfunction (SSM) emissions. While there are
some documented emission excursions above this level, our analysis of the data from the Texas Environmental Research Consortium suggest s that this factor s hould 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 modeling were determined nationally from the US Geological Service 1-degree digital elevation model (DEM ) data files, which have a spatial resolution of about 90 meters. Polar gr id elevations (used in estimating short- and long-term ambient concentrations) were evaluated at the highest elevation of any census block
in that sector. If a sector does not contain a ny blocks, the model defaults to the elevation of
the nearest block. If the eleva tion is not provided for the emi ssion source, the model takes the average elevation of all sectors of th e nearest model ring.Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 8

In addition to using receptor elevation to determine plume height, AERMOD adjusts the plume’s flow if nearby elevated hills are expected to influence the wind pa tterns. For details on how hill heights were estimated and used in the AERMOD modeling see Appendix 2.



### 2.3 Estimating human inhalation exposure

For this assessment, we used the annual aver age ambient air concentration of each HAP at each census block centroid as a surrogate for the lifetime inhalation exposure concentration of all the people who reside in the ce nsus block. That is, this risk analysis did not consider either the short-term or long-term behavior (mobility ) of the exposed populations and its potential influence on their exposure.

We did not address short-term human activity in this assessment for two reasons. First, our experience with the 1996, 1999, 2002, and 2005 NAT A assessments (which modeled daily activity using EPA’s HAPEM m odel) suggests that, given ou r current understanding of microenvironment concentrations and daily ac tivities, modeling short-term activity would, on average, reduce risk estimates about 25% for particulate HAP s; it will also reduce risk estimates for gaseous HAPs, but typically by much less. Second, basing exposure estimates on average ambient concentra tions at census block centr oids may underestimate or overestimate actual exposure conc entrations at some residences . Further reducing exposure estimates for the most highly-exposed residents by modeling their short-term behavior could add a systematic low bias to these results.

We did not address long-term migration in th is assessment nor populati on growth or decrease over 70 years, instead basing the assessment on the assumption that each person’s predicted exposure is constant over the cour se of their lifetime which is assumed to be 70 years. In assessing cancer risk, three metrics are gene rally estimated, the maximum individual risk (MIR) which is defined as the risk associated with a lifetime of exposure at the highest concentration, the population risk distribution, and the cancer inci dence. This assumption of not considering short or long- term population mobility does not bias the estimate of the
theoretical MIR nor does it aff ect the estimate of cancer inci dence since the total population number remains the same. It does, however, a ffect the shape of the di stribution of individual risks across the affected populati on, shifting it toward higher estim ated individual risks at the upper end and reducing the number of people estima ted to be at lower risks, thereby biasing the risk estimates high. When screening for pot entially significant acute exposures, we used an estimate of the highest hourly ambient co ncentration at any off-site location as the surrogate for the maximum potential acute e xposure concentration for any individual.



### 2.4 Acute Risk Screening and Refined Assessments

In establishing a scientifically-defensible approa ch for the assessment of potential health risks due to acute exposures to HAP, we followed the same general appr oach that has been used for developing chronic health risk assessments under the residual risk program. That is, we developed a tiered, iterative approach. This tier ed, iterative approach to risk assessment has been endorsed by the National Academy of Sc iences in its 1993 publication “Science andDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 9

Judgment in Risk Assessment” and subsequently was endorsed 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 tier ed, iterative approach to the assessment. This means that we began with a screening assessmen t, which relies on readily-available data and uses conservative assumptions that in combina tion approximate a worst-case exposure. The result of this screening process is that either the facility be ing assessed poses no acute health risks (i.e., it “screens out”), or that it requires further, more refined assessment. A refined assessment could use site-specific data on the te mporal pattern of emissions, the layout of emission points at the facility, the boundaries of the facility, and the local meteorology. In some cases, all of these site-spe cific data would be needed to refine the assessment; in others, lesser amounts of site-specific da ta could be used to determine that acute exposures 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, an d exposure location. We used the following worst-case assumptions in our screening approach:

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

rates.

• For facilities with multiple emission points, peak 1-hour emissions were assumed to occur at all emission points at the same time.

• For facilities with multiple emission points, 1-hour concentrations at each receptor
were assumed to be the sum of the maximum concentrations due to each emission point, regardless of whether those maximum concentrations occurred during the same
hour.

• Worst-case meteorology (from one 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 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 determine if a possi ble acute health risk might exist. These benchmarks are described in the next section of this report.

The Steel pickling source category “screened out” for acute risk.



### 2.5 Multipathway and envi ronmental risk screening

The potential for significant hum an health risks due to expos ures via routes other than inhalation (i.e., multipathway exposures) were 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 co mpounds or compound classes are identified forDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 10

the screening from the EPA’s Air Toxics Risk Assessment Library [ 6 ]. Examples of PB-HAP are cadmium compounds, chlordane, chlo rinated dibenzodioxins and furans, DDE, heptachlor, hexachlorobenzene, hexachlo rocyclohexane, lead compounds, mercury compounds, methoxychlor, polychlor inated biphenyls, polycyclic organic matter, toxaphene,
and trifluralin. PB-HAP emissions were not identified from the Steel Pickling source category, indicating that exposures due to non-inhalation routes of exposure were not significant. The lack of PB- HAP emissions from this source category indicates a very low potential for adverse environmental effects due to exposures resulting from atmospheric deposition of PB-HAPs. Thus, even if sensit ive species are present in the areas surrounding these facilities with no PB-HAP emissions, it is still reasonable to assume that there are no adverse effects to populations in th e areas surrounding these facilities.

Additionally, we evaluated the potential for significan t ecological exposures to non PB-HAP
from exceedances of chronic human health inhala tion thresholds in the ambient air near these
facilities. Human health dose -response threshold values are generally derived from studies conducted on laboratory animals (such as rodent s) and developed with the inclusions of uncertainty factors that could be as high as 3000. As a result, these human threshold values are often significantly lower than the level expected to cause an adverse effect in an exposed
rodent. It should be noted that there is a scarcity of data on th e direct atmospheric impact of these HAPs on other receptors, 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 mammalian receptors shoul d be at no risk of adverse effects due to inhalation exposures from non PB-HAP, and have assurance that other ecological receptors are also not at any significant ri sk from direct atmospheric imp act. In some isolated cases where we have data indicating po tential adverse impacts on plants, birds, or other wildlife due to the direct atmospheric impacts of specific HAP s, we note that as an uncertainty and, where possible, refine our analysis by comparing our modeled impacts to available threshold values
from the scientific literature.



### 2.6 Dose-Response Assessment

2.6.1 Sources of chronic dose-response information

There are only 2 HAP emitted by the sources in the Steel Pickling source category, and neither of them is considered to be carcinoge nic. Dose-response assessment information for the noncancer effects due to chronic exposure (e ither by inhalation or i ngestion) for the HAPs reported in the emissions invent ory for Steel Pickling sources were based on the EPA Office of Air Quality Planning and Standards’ existing recommendations for HAPs [ 7 ], also used for NATA 1999, 2002, and 2005 [ 8 ]. This information has been obtained from various sources and prioritized according to (1) conceptual c onsistency with EPA risk assessment guidelines and (2) level of peer review received. The pr ioritization process was aimed at incorporating
into our assessments the best available scien ce with respect to dose -response information.
The recommendations are based on the follo wing sources, in or der of priority:

1) US Environmental Protection Agency (EPA).Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 11

EPA has developed a dose-response assessmen t for chronic exposure for one of the pollutants in this risk assessment. This assessment provides a qualitative statement regarding the strength of scie ntific data and specify a refe rence concentration (RfC, for inhalation) or reference dose (RfD, for ingestion) to protec t against effects other than cancer The RfC is defined as “an estimate (w ith uncertainty spanning perhaps an order of magnitude) of a continuous inhalation e xposure to the human population (including sensitive subgroups) that is likely to be without an appreciabl e risk of deleterious effects during a lifetime”. EPA disseminates dose-res ponse assessment information in several forms, based on the level of review. The Integrated Risk Information System (IRIS) [ 9 ] is
an EPA database that contains scientific health assessment information, including doseresponse information. All IRIS assessment s since 1996 have also undergone independent external peer review. The current IRIS process includes review by EPA scientists, interagency reviewers from other federal ag encies, and the public, and peer review by independent scientists external to EPA.

2) California Environmental Protection Agency (CalEPA). The CalEPA Office of
Environmental Health Hazard Assessment ha s developed dose-response assessments for many substances, based both on carcinogenicity a nd health effects other than cancer. The process for developing these assessments is si milar to that used by EPA to develop IRIS values and incorporates signifi cant external scientific peer review. As cited in the CalEPA Technical Support Document fo r developing their chronic assessments 2 : “The guidelines for developing chronic inhala tion exposure levels incorporate many recommendations of the U.S. EPA (1994) 3 and NAS (NRC, 1994) 4 .” The non-cancer
information includes available inhalation health risk guidance values expressed as chronic inhalation reference exposure levels (RELs) [ 10 ]. CalEPA defines the REL as “the
concentration level at or below which no hea lth effects are anticip ated in the general human population”.

The emissions inventory for the source cat egory includes emissions of 2 HAP with quantitative inhalation chronic noncancer thresh old values available. These 2 HAP, their threshold values, and the source of the value are listed in Table 2.6-1.

2 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III - Technical Support Document
for the Determination of Noncancer Chronic Referen ce Exposure Levels. Air Toxicology and Epidemiology Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. February 2000 (http://www.oehha.ca.gov/ air/chronic_rels/pdf/relsP32k.pdf)

3 U.S. EPA. 1994. U.S. Environmental Protection Agency. Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation Dosimetry. EPA/600/8-90/066F. Office of Research and Development. Washington, DC: U.S.EPA.

4 NRC. 1994. National Research Co uncil. Science and Judgment in Risk Assessment. Washington, DC: National Academy Press.Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 12

Table 2.6-1 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 i nhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources : IRIS = EPA Integrated Risk Information System, CAL =
California EPA Office of Environment al Human Health Assessment,

Pollutant CAS
Number RfC (mg/m 3 ) Source 5

Chlorine 7782505 0.0002 CAL Hydrochloric acid 7647010 0.02 IRIS -- L

2.6.2 Sources of acute dose-response information
Hazard identification and dose-response assessment information for preliminary acute exposure were based on the existing r ecommendations of OAQPS for HAPs [ 11 ]. Depending on availability, the results from screening acu te assessments are compared to both “no effects” reference levels for the general publ ic, such as the Califor nia Reference Exposure Levels (RELs), as well as emergency respons e levels, such as Acute Exposure Guideline Levels (AEGLs) and Emergency Response Pl anning Guidelines (E RPGs), with the recognition that emergency response values are not an equivalent substitute for RELs and that the ultimate interpretation of any potential risks associated with an estimated exceedance of a particular reference level depends on the defini tion of that level and a ny limitations expressed therein. Comparisons among different available inhalation health effect reference values (both acute and chronic) for selected HAPs can be found in a newly released EPA document (Reference: U.S. EPA. Graphical Arrays of Chemical-Specific Health Effect Reference Values for Inhalation Exposures [Final Repor t]. (U.S. Environmental 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 acu te dose-response refe rence values for many substances, expressing the results as Acute i nhalation Reference Exposure Levels (RELs).

The acute REL ( http://www.oehha.ca.gov/air/pdf/acuterel.pdf ) is defined by CalEPA as
“the concentration level at or below which no adverse health effects are anticipated for a specified exposure duration. [ 12 ]. RELs are based on the most sensitive, relevant, adverse health effect reported in the medi cal 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 auto matically indicate an adverse health impact.” Acute RELs are developed fo r 1-hour (and 8-hour) exposures. The values incorporate uncertainty factors similar to those used in deriving EPA’s Inhalation

5 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 va lue, as reported in the IRIS file.Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 13

Reference Concentrations (RfCs) for chronic exposures (and, in fact, California also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory Committee (NAC) on Acute Exposure Guideline Le vels for Hazardous Substances, and then reviewed and published by the National Research Council As described in the Committee’s “Standing Operating Procedures (SOP)” ( http://www.epa.gov/opptintr/aegl/pubs/sop.pdf ), AEGLs “represent threshold exposure limits for the general public a nd are applicable to emergency exposures ranging from 10 min to 8 h.” Their intended application is “for conducting risk assessments to aid in the development of emerge ncy preparedness and prevention plans, as well as real time emer gency response actions, for accidental chemical releases at fixed facilities and from transport ca rriers.” The document states that “the primary purpose of the AEGL program and the NAC/AEGL Committee is to develop guideline levels
for once-in-a-lifetime , short-term exposures to airborne co ncentrations of acutely toxic, highpriority chemicals.” In detailing the inte nded application of AEGL values, the document states that “It is anticipated that the AE GL values will be used for regulatory and nonregulatory purposes by U.S. Federal and St ate agencies, and possi bly the international community in conjunction with chemical emergency response, planning, and prevention programs. It is important to note that a poten tial for effects exists even if the airborne
concentration is below the AEGL-1 value.

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 th e general population, including su sceptible individuals, could experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. However, the effects are not disabling and ar e transient and revers ible 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 th e general population, including su sceptible individuals, could experience irreversible or other serious, long-lasting adverse h ealth effects or an impaired ability to escape.”

“Airborne concentrations below AEGL-1 repr esent exposure levels that can produce mild and progressively increasing but transient and nondisabli ng odor, taste, and sensory irritation or certain asymptomatic, nonsenso ry 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 el derly, persons with asthma, and those with other illnesses, it is recognized that indivi duals, subject to unique or idiosyncratic responses, could experience the effects de scribed at concentr ations below the corresponding AEGL.”Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 14

Emergency Response Planni ng Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergenc y Response Planning Guidelines (ERPGs) [ 13 ] for acute exposures at three different levels of severity. Thes e guidelines represent concentrations for exposure of the general population (but not pa rticularly sensitive persons) for up to 1 hour associated with effects expe cted to be mild or transient (ERPG-1), irreversible or serious (ERPG-2).

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 emerge ncy planning and are intended as health based guideline concentrations for single exposures to chemicals. These gui delines (i.e., the ERPG Documents and ERPG values) are intended fo r use as planning tools for assessing the adequacy of accident prevention and emergenc y response plans, including transportation emergency planning and for developing community emergency response plans. The emphasis is on ERPGs as planning values: When an actua l chemical emergency occurs there is seldom
time to measure airborne concentrations and then to take action.” As with other emergency levels, these levels reflect consideration of onl y single exposures, not repe ated 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 could be exposed for up to 1 hour without experiencing other than mild
transient adverse health eff ects or without perceiving a clearly defined, objectionable
odor.”

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

As with AEGLs, these levels do not ensure protection for any repeated exposure.

The emissions inventory for the Steel Pickli ng source category include s emissions of 2 HAP with relevant and available qua ntitative acute dose-response th reshold values. These HAPs, their acute threshold values, and the source of the value are listed below in Table 2.6-2.Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 15

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 (mg/m 3 )

Chlorine 7782505 1.5 5.8 1.5 5.8 0.21 Hydrochloric acid 7647010 2.7 33 2.7 33 2.1



### 2.7 Risk Characterization

2.7.1 General

The final product of the risk as sessment is the risk characteri zation, in which the information from the previous steps is integrated and an overa ll conclusion about risk is synthesized that is complete, informative, and useful for decision ma kers. In general, the nature of this risk characterization depends on the in formation available, the application of the risk information and the resources available. In all cases, majo r issues associated with determining the nature
and extent of the risk are identified and disc ussed. Further, the EPA Administrator’s March

1995 Policy for Risk Characterization [ 14 ] specifies that a risk ch aracterization “be prepared in a manner that is clear, transparent, r easonable, and consistent with other risk characterizations of similar scope prepared acro ss programs in the Agency.” These principles of transparency and consistency have been reinforced by the Agency’s Risk Characterization
Handbook [ 15 ], in 2002 by the Agency’s information quality guidelines [ 16 ], and in the OMB/OSTP September 2007 Memorandum on U pdated Principles for Risk Analysis 6 , and are incorporated in these assessments.

Estimates of health risk are pres ented in the context of uncertainties and limitations in the data and methodology. Through our tiered, iterative an alytical approach, we have attempted to reduce both uncertainty and bias to the greate st degree possible in these assessments. We have provided summaries of risk metrics for each source category (including maximum
individual cancer risks and non cancer hazards, as well as can cer incidence estimates) along with a discussion of the major uncertainties associated with their derivation to provide decision makers with the fullest pictur e of the assessment and its limitations.

“Risk” for noncancer effects is expressed by comparing an exposur e to a reference level as a ratio. The “hazard quotient” (HQ) is the estim ated exposure divided by a reference level (e.g., the RfC). For a given HAP, exposures at or below the reference level (HQ ≤ 1) are not likely to cause adverse health effects. As expos ures increase above the reference level (HQs

6 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 Depu ty Director for Science, Office of Science and Technology Policy (http://www.whitehouse.gov/omb/memoranda/fy2007/m07-24.pdf)Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 16

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.

The risk characterization for chronic effects othe r than cancer is expressed in terms of the HQ for inhalation, calculated for each HAP at each census block centroid. As discussed above, RfCs incorporate generally conservative uncer tainty factors in the face of uncertain extrapolations, such that an HQ greater than one does not necessarily suggest the onset of adverse effects. The HQ cannot be translated to a probability that adve rse effects will occur, and is unlikely to be proportional to adve rse health effect outcomes in a population.

Screening for potentially signi ficant acute inhalation exposures also followed the HQ approach. In this case, we divided the maxi mum estimated acute exposure by each available short-term threshold value to develop an arra y of HQ values relative to the various acute endpoints and thresholds. In ge neral, when none of these HQ values are greater than one, there is no potential for acute risk. In t hose cases where HQ values above one are seen, additional information is used to determine if 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 the aggregate health risks a ssociated with all the exposures from a particular source category combined.

In assessing noncancer hazard from chronic expo sures, in cases where different pollutants
cause adverse health effects via completely different modes of action, it may be inappropriate to aggregate HQs. In consideration of th ese mode-of-action differences, the mixtures guidelines support aggregating effects of different substances in specif ic and limited ways. To conform to these guidelines, we aggregated non-cancer HQs of HAPs that act by similar toxic modes of action, or (where this information is absent) that affect the same target organ. This process creates, for each target organ, a target-organ-specific hazard index (TOSHI), defined as the sum of hazard quotients for indi vidual HAPs that affect the same organ or organ system. All TOSHI calcu lations presented here were based exclusively on effects occurring at the “critica l dose” (i.e., the lowest dose that pr oduces adverse health effects). Although HQs associated with some pollutants ha ve been aggregated into more than one TOSHI, this has been done only in cases where th e critical dose affects more than one target organ. Because impacts on organs or systems that occur above the critical dose have not been included in the TOSHI calculations, some TOSHIs may have been underestimated. As with the HQ, the TOSHI should not be interpreted as a probability of adverse effects, or as strict
delineation of “safe” and “unsafe” levels. Ra ther, the TOSHI is another measure of the potential for adverse health outcomes associated with pollutant exposur e, and needs to be interpreted carefully by health scientists and risk managers.Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 17

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

2.7.3 Facility Wide Risk

To help place the source category risks in cont ext, we examined “facility-wide” risks using
the results of the 2005 NATA. For the faciliti es in the Steel Pickli ng source category, we extracted the NATA results (based on facility ID) the NATA estimates of the inhalation
cancer and chronic non-cancer risk s associated with the HAP emi ssions sources at the facility, including emissions sources that are not part of this source category but that are located within a contiguous area and are under common control. We analyzed risks due to the inhalation of HAP for the populations residing within 50 kilomete rs of each facility. The results of this “facility-wide” assessment are provided for the hi ghest-risk facility below in the Risk Results section of this document. The complete result s of the “facility-wide” assessment are provided in Appendix 5.



### 3 Risk Results for the Stee l Pickling Source Category

3.1 Source Category Desc ription and Results

The steel pickling source categor y includes facilities that are e ngaged in the pickling of steel using hydrochloric acid (HCl) as the pickling acid, and facilities that regenerate the HCl after use. Steel pickling is a process in which the heavy oxide crust or mill scale that develops on the surface of steel during hot forming or heat treating is removed chemically in a bath of aqueous acid solution. This source category do es not include faciliti es which pickle steel using acids other than HCl. Steel pickli ng operations can be conducted via continuous, semicontinuous, or batch processes. Five type s of pickling processes have been identified: (1) continuous strip; (2) push-pu ll strip; (3) rod/wire; (4) tube ; and (5) batch. The hazardous air pollutants (HAP) emitted from steel pickli ng sources are HCl and chlorine (which is generated as a by-product of the regeneration pro cess). A complete description of the steel pickling source category can be f ound in the text of the NPRM.

It is currently estimated that there are appr oximately 80 facilities performing steel pickling and/or acid regeneration in the U.S. The NPRM data set contains 51 fac ilities identified with a steel pickling MACT code in the 2005 NATA National Emissions Inventory (NEI). While
the NEI identifies 25 of these 51 facilities as area sources of HAP (and 26 as major sources), the uncertainty associated with these major/area classifications is si gnificant enough that we will consider all of them to be major sources for the purposes of this rule making and include
them in this risk assessment.

Table 3.1-1 summarizes the emissions for the St eel Pickling source cate gory. The total HAP emissions for the source categor y are approximately 265 tons per year. Based on these data, HCl and Chlorine are the only HAP emitted by steel pickling sources. HCl is reported as anDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 18

emission at all of the facilities and chlorine is re ported for 6 facilities. There are no persistent and bioaccumulative HAP (PB HAP) emissions included in the NPRM data set.

Table 3.1-2 provides information summarizing health risks for this source category.

Table 3.1-1 Summary of Emissions fr om the Steel Pickling Source Category

Table 3.1-2 Summary of Source Categor y Level Risks for Steel Pickling

Result HAP “Drivers” Facilities in Source Category Number of Major Facilities Estimated to be Subject to MACT in Source Category 80 n/a

Number of Facilities Identified in NEI and
Modeled in NPRM Risk Assessment 51 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) from any Facility in the Category b n/a

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million b n/a

Chronic Noncancer Risks Maximum Respiratory Hazard Index 2 chlorine Number of Facilities with Maximu m Respiratory Hazard Index:

Greater than 1 1 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 0.4

0.2

0.02 chlorine(REL) hydrochloric acid (AEGL-1) hydrochloric acid (AEGL-2)

Number of Facilities With Potential for Acute
Effects 0 n/a

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 50,000,000 n/a

Number of People Exposed to Cancer Risk:

a Specific dose-response values fo r each chemical are identified on EPA’s Technology Tr ansfer Network website for air

toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html and are available in Appendix 5 of the Development of Preliminary Risk Estimat es for Source Categories Previously Subj ected to Technology-based Standards document.

b The facilities in this category do not report emissi ons of any HAP with cancer dose-response values. Prioritized Inhalation Dose-Response Value Identified by OAQPS a

HAP b NPRM
Emissions (tpy) Number of

Facilities Reporting HAP (51 facilities in data set) Unit Risk

Estimate for

Cancer? Reference

Concentration

for Chronic

Noncancer? Health

Benchmark
Values for

Acute

Noncancer? PBHAP

?

Hydrochloric Acid 247 51 Υ Υ

Chlorine 18 6 Υ ΥDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 19

Table 3.1-2 Summary of Source Categor y Level Risks for Steel Pickling

Result HAP “Drivers” Greater than or equal to 1 in 1 million b n/a Number of People Exposed to Noncancer Respiratory Hazard Index:

Greater than 1 30 n/a Estimated Cancer Incidence (excess cancer cases per year) b n/a



### 3.2 Risk Characterization

No compounds emitted from the Steel Pickling source category have cancer potency factors; therefore, we did not access cancer risk for this source category. The chronic noncancer inhalation risk correspon ds to a maximum chronic respirator y HI of 2. An HI value greater than 1 is found at only this one facility. The next highest so urce category HI is 0.1, with the remaining source category HI values even lowe r than 0.1 (significantly lower than the HI of 2). There were no reported emissions of PB-H AP from this source ca tegory; therefore we have no concerns about any potential multi-pathway risks from this category. Chlorine and hydrochloric acid can cont ribute to acidification, but the ex tent to which that might be a problem for this source category was not assessed . No other potential environmental risks, including those as a direct resu lt of exposure of flora and fauna to ambient air concentrations, were identified. Additionally, potential acut e impacts on human health associated with hydrochloric acid were all well be low the level of concern.

The result of the “facility-wide” assessment is that the Steel Pickling source category’s highest chronic non-cancer risk, an HI value of 2 for chlorine, is equal to th e “facility-wide” HI (2) at that facility. The highest facility -wide HI is 10 and at this facility the source category contributes very minima lly to the facility-wide HI (maximum source category HI at this facility is 0.0004). Due to the absence of HAP with cancer dose-response values for the source category emissions, there is no source ca tegory MIR. However, the facility-wide MIR
associated with other emissions sources at facili ties with Steel Pickling processes is as high as

100.

The analysis of potential differences between ac tual emission levels and emissions allowable
under the MACT standards indicate that actu al emissions and allowable emissions are approximately the same as allowable emissions. The available data indicate that pickling processes throughout the industr y are equipped with controls that achieve the HCL and chlorine emission limits required by the MACT sta ndards. For more detail about this estimate
of the ratio of actual to MACT-allowable emissions, see the September 1, 2010 memo “Maximum Achievable Control Technology (MACT) Allowable Emission Estimates” available in the proposal docket.



### 4 General Discussion of Uncertaint ies and How They Have Been
AddressedDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 20

While each of the preceding sections discussed specific uncertainties unique to the source category, the following includes a general discus sion of uncertainties associated with RTR

assessments.



### 4.1 Exposure Modeling Uncertainties

Emission inventory uncertainties were previously discussed for the source category in section
2.1 and 3.1. Our estimated number of facilities indi cates that there may be more facilities in this category than represented in the NPRM data set. As previously noted, there is significant uncertainty in the identification of so urces as major or area in the NEI.

The chronic exposure modeling uncertainties ar e considered relatively small since we are using EPA’s refined local disp ersion model with site-specifi c parameters and reasonably representative meteorology. If anything, the po pulation exposure estimates are biased high by not accounting for short- or long-term popula tion mobility, and by neglecting processes like deposition, plume depletion, and atmospheric degradation.

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



### 4.2 Uncertainties in the Do se-Response Relationships

In the sections that follow, a discussion is pr ovided on uncertainty associated with noncancer
reference values. Noncancer reference values are generally derived for chronic exposures (up to a lifetime), 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 which are derived based on an assumption of continuous exposure throughout the duration specified. For the purposes of assessing all potential health risks associated with the emissions included in this assessment, we rely on both chronic and acute benchmarks, wh ich are described in
more detail below.

Although every effort is made to identify p eer-reviewed dose-respons e values for all HAPs emitted by the sources included in this assessm ent, both HAP have no peer-reviewed cancer potency values. Since exposures to these polluta nts cannot be included in a quantitative risk estimate, an understatement of risk for these po llutants at environmental exposure levels is possible.

Cancer assessment

There are no cancer dose res ponse values for either of the HAP (HCl and chlorine) compounds assessed and no other carcinogenic HAP emissions were reported for this source category; therefore no cancer assessment was done for the Steel Pick ling source category. Further, while these 2 pollutants have been widely studied, there are no data or studies indicating that either chlorine or HCl might be associated with cancer. Therefore, weDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 21

maintain that the uncertainties associated with the results of our cancer assessment (i.e., that there are no significant cancer risks) are small.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure leve ls that are intended to be health-protective. That is, EPA and other or ganizations which develop noncancer reference values (e.g., the Agency for Toxic Substances and Disease Registry – ATSDR) utilize an approach that is intended not to underestimate risk in the face of uncertainty and variability. When there are gaps in the available informa tion, uncertainty factors (UFs) are applied to
derive reference values that are intended to be protective against appreciable risk of deleterious effects. Uncertainty factors are commonly default values 7 e.g., factors of 10 or 3, used in the absence of compound-specific data; wh ere data are available, uncertainty factors may also be developed using compound-specific information. When data are limited, more assumptions are needed and more default fact ors are used. Thus there may be a greater tendency to overestimate risk—in the sense th at further study might support development of reference values that are higher (i.e., less pot ent) because fewer default assumptions are needed. However, for some pollutants it is possible that risks ma y be underestimated.

For non-cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) for exposures via ingestion, and a Reference C oncentration (RfC) for inhalation exposures. These values provide an estimate (with uncerta inty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or of a conti nuous inhalation exposure (RfC) to the human population (including sensitive subgroups) that is lik ely to be without an appreciable risk of deleterious effects during a lifetime. 8 To derive values that are intended to be “without appreciable risk,” EPA’s methodol ogy relies upon an uncertainty factor (UF) approach (U.S. EPA, 1993, 1994) which includes considerati on of both uncertainty and variability.

EPA begins by evaluating all of the availabl e peer-reviewed literature to determine noncancer endpoints of concern, eval uating the quality, strengths and limitations of the available studies. EPA typically chooses th e relevant endpoint that occu rs at the lowest dose, often using statistical modeling of the available data, and then determines th e appropriate point of departure (POD) for derivation of the reference value. A POD is determined by (in order of preference): (1) a statistical estimation using the benchmark dos e (BMD) approach; (2) use of

7 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are generic approaches, based on general scientific knowle dge 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 depart from them in evaluating the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions
are used to ensure that risk to chemicals is not under estimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An examination of EPA Risk Assess ment Principles and Practices, EPA/100/B-04/001 available at: http://w ww.epa.gov/osa/pdfs/ratf-final.pdf.

8 See IRIS glossaryDraft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 22

the dose or concentration at which the toxic response was not signi ficantly elevated (no observed adverse effect level— NOAEL); or (3) use of the lowest observed adverse effect level (LOAEL).

A series of downward adjustments using defau lt UFs is then applied to the POD to estimate the reference value (U.S. EPA 1994, 2002). Whil e collectively termed “UFs”, these factors account for a number of different quantitative co nsiderations when utilizing observed animal (usually rodent) or human toxicity data in a risk assessment. The UFs are intended to account for: (1) variation in susceptibility among th e members of the human population (i.e., interindividual variability); (2) uncer tainty in extrapolating from experimental animal data to humans (i.e., interspecies diffe rences); (3) uncertainty in extr apolating from data obtained in a study with less-than-lifetime exposure (i.e., extrapolating from subchronic to chronic exposure); (4) uncertainty in extrapolating fr om a LOAEL in the absence of a NOAEL; and (5) uncertainty when the database is incomplete or there are problems with applicability of available studies. When scientifically sound, peer-reviewed assessment- specific data are not available, default adjustment values are sele cted for the individual UFs. For each type of uncertainty (when relevant to the assessment), EPA typically applies an UF value of 10 or 3 with the cumulative UF value leading to a downward adjustment of 10-3000 fold from the
selected POD. An UF of 3 is used when the da ta do not support the use of a 10-fold factor. If an extrapolation step or adjustment is not re levant to an assessment (e.g., if applying human toxicity data and an interspecies extrapolation is not required) the associated UF is not used. The major adjustment steps are described more fully below.

1) Heterogeneity among humans is a key sour ce of variability as well as uncertainty. Uncertainty related to human variation is consid ered in extrapolating doses from a subset or smaller-sized population, often of one sex or of a narrow range of life stages (typical of occupational epidemiologic studies), to a larger , more diverse population. In the absence of pollutant-specific data on human variation, a 10 -fold UF is used to account for uncertainty
associated with human variation. Human variatio n may be larger or smaller; however, data to examine the potential magnitude of human va riability are often una vailable. In some situations, a smaller UF of 3 ma y be applied to reflect a known l ack of significant variability among humans.

2) Extrapolation from results of studie s in experimental animals to humans is a necessary step for the majority of chemical ri sk assessments. When interpreting animal data, the concentration at the POD (e.g. NOAEL, BM DL) in an animal model (e.g. rodents) is extrapolated to estimate the human response. While there is long-sta nding scientific support
for the use of animal studies as indicators of potential toxicity to humans, there are uncertainties in such extrapolat ions. In the absence of data to the contrary, the typical approach is to use the most relevant endpoint from the most sensitive species and the most sensitive sex in assessing risks to the aver age human. Typically, compound specific data to evaluate relative sensitivity in humans versus rodents are lacki ng, thus leading to uncertainty in this extrapolation. Size-related differences (allometric relationships) indicate that typically
humans are more sensitive than rodents when compared on a mg/kg/day basis. The default choice of 10 for the interspecies UF is consis tent with these differences. For a specific chemical, differences in species responses may be greater or less than this value.Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 23

Pharmacokinetic models are useful to examine species differences in pharmacokinetic processing and associated uncertainties; however , such dosimetric adjustments are not always possible. Information may not be available to quantitatively a ssess toxicokinetic or toxicodynamic differences between animals a nd humans, and in many cases a 10-fold UF (with separate factors of 3 for toxicokinetic and toxicodyna mic components) is used to account for expected species differences and as sociated uncertainty in extrapolating from laboratory animals to humans in the derivation of a reference value. If information on one or the other of these components is availabl e and accounted for in the cross-species extrapolation, a UF of 3 may be used for the remaining component.

3) In the case of reference values for ch ronic exposures where only data from shorter durations are available (e.g., 90-da y subchronic studies in rodent s) or when such data are judged more appropriate for development of an RfC, an additional UF of 3 or 10-fold is typically applied unless th e available scientific information supports use of a different value.

4) Toxicity data are typically limited as to the dose or exposure levels that have been tested in individual studies; in an animal study, for example, treatment groups may differ in exposure by up to an order of magnitude. The pref erred approach to arrive at a POD is to use BMD analysis; however, this approach requires ad equate 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 wh ich an adverse effect is not observed (i.e., a NOAEL is not identified). When using data lim ited 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 variability and uncertainty in the development of acute reference values are quite similar to those de veloped for chronic durations, but more often using individual UF values that may be less than 10. UFs are applied based on chemicalspecific or health effect-specific informati on (e.g., simple irritation effects do not vary appreciably between human indivi duals, hence a value of 3 is t ypically used), or based on the purpose for the reference value (see the followi ng paragraph). The UFs applied in acute reference value derivation include: 1) he terogeneity among humans ; 2) uncertainty in extrapolating from animals to humans; 3) unc ertainty in LOAEL to NOAEL adjustments; and 4) uncertainty in accounting for an incomplete database on toxic effect s of potential concern. Additional adjustments are often applied to a ccount for uncertainty in extrapolation from observations at one exposure dura tion (e.g., 4 hours) to arrive at a POD for derivation of an
acute reference value at another exposure duration (e.g., 1 hour).Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 24

Not all acute reference values are developed for the same purpose and care must be taken when interpreting the results of an acute asse ssment of human health effects relative to the reference value or values being exceeded. Wh ere relevant to the estimated exposures, the
lack of threshold values at di fferent levels of severity shoul d be factored into the risk characterization as potential uncertainties.Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 25



### 5 References

1 . US EPA, 2006. Emission Standards for Hazardous Air Pollutants. http://www.epa.gov/ttn /atw/mactfnlalph.html

.

2 . US EPA, 2009. Risk and Technology Review (RTR) Risk Assessmen t 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, 2005. Revision to the Guideline on Air Quality Models: Adop tion of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Ot her Revisions; Final
Rule. 40 CFR Part 51. http://www.epa.gov/EPA-AIR/2005 /November/Day-09/a21627.htm

4 . US EPA, 2004. Users’ guide for the AMS/EPA regulatory model – AERMOD. EPA-454/B03-001. http://www.epa.gov/scram 001/7thconf/aermod/aermodugb.pdf

.

5 . Allen, D., C. Murphy, Y. Kimura, W. Vizuete, T. Edgar, H. Jeffries, B.-U. Kim, M. Webster, and M. Symons, 2004. Variab le industrial VOC emissions and their impact on ozone
formation in the Houston Galveston Area. Final Report: Texas Environmental Research Consortium Project H-13. http://files.harc.edu/Pr ojects/AirQua lity/Projects/H013.2003 /H13FinalReport.pdf

6 . US EPA, 2004. Air Toxics Risk Assessment Reference Library, Volume 1. EPA-453-K-04- 001A. http://www.epa.gov/ttn/ fera/risk_atra_vol1.html.

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

8 . US EPA, 2005. 1999 National Air Toxics Risk Assessment. http://www.epa.gov/t tn/atw/nata1999

9 . US EPA, 2008. Integrated Risk Information System. http://www.epa.gov/iris/index.html

.

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

.

11 . US EPA, 2005. Table 2. Acute Dose-Respons e Values for Screening Risk Assessments (6/02/2005). Office of Air Quality Planni ng and Standards. http://www.epa.gov/ttn/a tw/toxsource/table2.pdf

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

13 . American Industrial Hygi ene Association , 2009. Current AIHA ERPG Values.Draft Risk Assessment for the Steel Pi ckling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 26

http://www.aiha.org/insid eaiha/volunteergr oups/Documents/ER P-erpglevels.pdf

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

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15 . US EPA, 2000. Risk Charac terization Handboo k. EPA 100-B-00-002.

16 . US EPA, 2002. EPA’s Guidelines for Ensu ring and Maximizing the Quality, Objectivity, Utility, and Integrity of Inform ation Disseminated by the Envi ronmental Protection Agency.
EPA Office of Environmental In formation. EPA/260R-02-008. http://www.epa.gov/quality/inf ormationguidelines/documents/EP A_InfoQualityGuidelines.pdf