Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 1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 Quality Planning and Standards

Office of Air and Radiation July 2010Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 2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 inhalation exposure assessment ......................................... 5 2.3 Estimating human inhalation exposure ...................................................................... 8 2.4 Acute Risk Screening and Refined Assessments....................................................... 9 2.5 Multipathway and environmental risk screening ..................................................... 10 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 Un certainties and How They Have Been Addressed................... 20 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 Chronic Inhalation Exposure to Noncarcinogens .... 12 Table 3.1-1 Summary of Emissions from the Steel Pickling Source Category ...................... 18 Table 3.1-2 Summary of Source Category Level Risks for Steel Pickling............................. 18

Appendices

Appendix 1 Emissions Inventory Support Memorandum Appendix 2 Technical Support Document for HEM-AERMOD Modeling Appendix 3 Meteorological Data 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 Pickling 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 Subs tances 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 Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 4



### 1 Introduction

Section 112 of the Clean Air Act (CAA) establishes a two-stage regulatory process for addressing emissions of hazardous air pollutants (H APs) from stationary sources. In the first stage, section 112(d)(2) requires the Environmental Protection Agency (EPA, or the Agency) to develop technology-based standards for catego ries of industrial sources (e.g., petroleum refineries, pulp and paper mills, etc.) [ 1 ]. EPA has largely completed the initial Maximum Achievable Control Technology (MACT) standard s as required under this provision. Under section 112(d)(6), EPA must review each of these technology-based standards at least every eight years and revise a standard, as necessa ry, “taking into account developments in practices, processes and control technologies.” In the second stage, EPA is required under section 112(f)(2) to assess the health and environmental risks that remain after implementation of the MACT standards. If additional risk reductions are necessary to protect public health with an ample margin of 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 ri sk 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 pa nel from the EPA's Science Advisory Board (SAB) on the “Risk and Technology Review (RTR) Assessment Plan” and in June of 2007, we received a letter with the results of that consultation. Subsequent to the consultation, in June of 2009 a meeting was held with an SAB pa nel for a formal peer review of the “Risk and Technology Review (RTR) Assessment Methodologi es”. 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 assess ment for this source category. We are providing this draft risk assessment document through the National Emission Standards for Hazardous

Air Pollutant Emissions: Hard and Decora tive Chromium Electroplating and Chromium Anodizing Tanks; Group I Polymers and Resins; Marine Tank Vessel Loading Operations; Pharmaceuticals Production; The Printing and Pu blishing Industry; and Steel Pickling--HCl Process Facilities and Hydrochloric Acid Rege neration 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 results of baseline risk assessment (i.e., after the implementation of the respective MACT standard) performed for the Steel Pickling (formally known as Steel Pickling – HCl Pr ocess Facilities and Hydrochloric Acid regeneration Plants) source category.

The methods discussion includes descriptions of the methods used to develop refined estimates of chronic inhalation exposures and hu man health risks for noncancer endpoints, as well as descriptions of the methods used to screen for acute health risks, chronic noninhalation health risks, and adverse environmen tal effects. No HAP reported as emissions from the facilities in the source category ha ve cancer dose response values and therefore

cancer risk was not assessed for the source cate gory. Since none of th e screening assessmentsDraft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 5

indicated any significant potential for chronic n on-inhalation health effects, or environmental impacts including effects to threatened and endang ered species, no further refinement of these assessments was 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 Assessm ent (NATA) National Emissions Inventory (NEI) served as the starting point for this as sessment. The 2005 NEI purportedly contains information on actual emissions during the entire 2005 base year. Using the process MACT

code 1 , we developed a subset of this inventory that contains 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 directly 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 industry supplied data as available. The goal of the engineering review was to identify readily-apparent limitations and issues with the emissions data (particularly th ose that would greatly influence risk estimates) and to make changes to the data set where po ssible to address these issues and decrease the

uncertainties associated with the assessment.

Details on the development of the emissions and 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 “Emissions Inventory Support Memorandum.”



### 2.2 Dispersion modeling for inhalation exposure assessment

Both long- and short-term inhalation exposure co ncentrations and associated health risk from each facility in the source category of intere st 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 details are provided in Appendix 2. HEM-AERMOD performs three main operations: atmospheric disp ersion modeling, estimation of individual human exposures and health risks, and estimation of population risks. This section focuses on the dispersion modeling component. The expo sure and risk character ization components are

discussed in other subsections of Sections 2 and 3.

The dispersion model in the HEM-AERMOD system, AERMOD version 09292, is a state-ofthe-science Gaussian plume dispersion model that is preferred by EPA for modeling point, area, and volume sources of continuous air emissions from facility applications [ 2 ]. Further

1 The tagging of data with MACT codes allows EPA to determine reductions attributable to the MACT program. The NEI associates MACT codes corresponding to MA CT source categories with stationary major and area source data. MACT codes may be assigned either at the process 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 cracking is assigned at the process level).Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 6

details on AERMOD can be found in the AERMOD Users Guide [ 3 ]. The model is used to develop annual average ambient concentrations through the simulation of hour-by-hour dispersion from the emission sources into the su rrounding atmosphere. Hourly emission rates used for this simulation are generated by even ly 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 represe nted 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 NWS from nearest site (158 stations)

Meteorological data for HEM-AERMOD is se lected from a list of 158 National Weather Service (NWS) surface observation stations across 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 formatted model input files derived from available meteorological data, we modeled only a single year, typically 19 91. While the selection of a single year may result in under-prediction of long-term ambient le vels at some locations, likewise it may result in over-prediction at others. For each facili ty identified by its characteristic latitude and longitude coordinates, the closest meteorological station was used in the dispersion modeling. The average distance between a modeled facility and the applicable meteorological station was 40 miles (72 km). A sensitivity analysis performed for the 1996 NATA examined the chronic inhalation risk variability attributable to the selection of the meteorology dataset location [7]. The analysis found that predicte d risk estimates were up to 17% below and 84% above the risk estimates predicted by utilizing the closest station. Appendix 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 AERMET.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 7

The HEM-AERMOD system estimates ambient conc entrations at the geographic centroids of census blocks (using the 2000 Census), and at ot her receptor locations that can be specified by the user. The model accounts for the effects of multiple facilities when estimating concentration impacts at each block centroid. Typically we combined only the impacts of facilities within the same source category, and assessed chronic exposure and risk only for census blocks with at least one 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 cent roid. Possible future residential use of currently uninhabited areas was not considered. Census blocks, the finest resolution available in the census data, are typically comprised of approximately 40 people or about ten households.

In contrast to the development of ambient conc entrations for evaluating long-term exposures, which was performed only for occupied census blocks, worst-case short-term (one-hour) concentrations were estimated both at the census block centroids and at points nearer the facility that represent locations where people ma y 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 contai n locations inside the facility property). Since short-term

emission rates were needed to screen for th e potential for hazard via acute exposures, and since the NEI contains only annual emission to tals, we applied the general assumption to all source categories that the maximum one-hour emis sion rate from any so urce was ten times the average annual hourly emission rate for that sour ce. 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 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 datase t from a number of sources located in Texas (originally reported on by Allen et al. 2004)[ 4 ]. In that report, the Texas Environmental Research Consortium Project compared hourly and annual emissions data for volatile organic compounds for all facilities in a heavily-industrialized 4-county area (Harris, Galveston, Chambers, and Brazoria Counties, TX) over an eleven-month time period in 2001. We obtained the dataset and 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 re lative to long-term emission rates”). Most peak emission events were less than twice the a nnual average, and the hi ghest was a factor of 11 times the annual average. The factor of ten is intended to cover both routinely-variable emissions as well as startup, shutdown, and malfunction (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 should cover more than 99% of the short-term peak gaseous or vola tile HAP emissions from typical industrial

sources.

Census block elevations for HEM-AERMOD m odeling were determined nationally from the US Geological Service 1-degree digital elevat ion model (DEM) data files, which have a spatial resolution of about 90 meters. Polar grid elevations (used in estimating short- andDraft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 8

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 elevation is not provided for the emission source, the model takes the average elevation of all sectors of the nearest model ring.

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 patterns. 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 average ambient air concentration of each HAP at each census block centroid as a surrogate for the lifetime inhalation exposure concentration of all the people who reside in the census block. That is, 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 NATA assessments (which modeled daily activity using EPA’s HAPEM model) suggests that, given our current understanding of microenvironment concentrations and daily activ ities, modeling short-term activity would, on average, reduce risk estimates about 25% for particulate HAPs; it will also reduce risk estimates for gaseous HAPs, but typically by much less. Second, basing exposure estimates on average ambient concentrations at cens us block centroids may underestimate or overestimate actual exposure c oncentrations 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 this assessment nor populatio n growth or decrease over 70 years, instead basing the assessment on th e assumption that each person’s predicted exposure is constant over the course of their li fetime which is assumed to be 70 years. In assessing cancer risk, three metr ics are generally 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 incidence. This assumption of not considering short or long-term population mobility does not bias the estimate of the theoretical MIR nor does it affect the estimate of cancer incidence since the total population number remains the same. It does, however, affe ct the shape of the distribution of individual risks across the affected population, shifting it toward higher estimated individual risks at the upper end and reducing the number of people esti mated to be at lower risks, thereby biasing the risk estimates high. When screening for po tentially significant acute exposures, we used an estimate of the highest hourly ambient concentration at any off-site location as the surrogate for the maximum potential acute exposure concentration for any individual.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 9



### 2.4 Acute Risk Screening and Refined Assessments

In establishing a scientifically-defensible approach for the assessment of potential health risks due to acute exposures to HAP, we followed the sa me general approach that has been used for developing chronic health risk assessments unde r the residual risk program. That is, we developed a tiered, iterative approach. This ti ered, iterative approach to risk assessment has been endorsed by the National Academy of Scie nces in its 1993 publication “Science and 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 eliminate from further consideration those

facilities for which we have confidence that no acute adverse health effects of concern will occur. To do so, we use what is called a 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 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 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-specific data would be needed to refine the assessment; in others, lesser amounts of site-specific data could be us ed to determine that acute exposures are not a concern, and significant a dditional data collection woul d 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 maxi mum concentrations due to each emission point, regardless of whether those maximu m 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 poss ible 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.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 10



### 2.5 Multipathway and environmental risk screening

The potential for significant human health risks due to exposures via routes other than inhalation (i.e., multipathway exposures) were screened by first determining whether any sources emitted any hazardous air pollutants kno wn 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 T oxics Risk Assessment Library [ 5 ]. Examples of PB-HAP are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, heptachlor, hexachlorobenzene, hexach lorocyclohexane, lead compounds, mercury compounds, methoxychlor, polychlorinated biphe nyls, 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 sensitive 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 significant 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 expect ed to cause an adverse effect in an exposed

rodent. It should be noted that there is a scarc ity of data on the 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 should 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 risk from direct atmospheric impact. In some isolated cases where we have 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 possible, refine our analysis by comparing our modeled impacts to avai lable threshold values

from the scientific literature.



### 2.6 Dose-Response Assessment

2.6.1 Sources of chronic do se-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 carcinog enic. Dose-response assessment information for the noncancer effects due to chronic exposure (e ither by inhalation or ingestion) for the HAPs reported in the emissions inventory for Steel Pickling sources were based on the EPA Office of Air Quality Planning and Standards’ existing recommendations for HAPs [ 6 ],, also used for NATA 1999, 2002, and 2005 [ 7 ]. This information has been obtained from various sourcesDraft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 11

and prioritized according to (1) conceptual cons istency with EPA risk assessment guidelines and (2) level of peer review received. The prioritization process was aimed at incorporating

into our assessments the best available science with respect to dose-response information. The recommendations are based on the following sources, in order of priority:

1) US Environmental Protection Agency (EPA). EPA has developed a dose-response assessment for chronic exposure for one of the pollutants in this risk assessment. This assessment provides a qualitative statement regarding the strength of scientific data and specify a reference concentration (RfC, for inhalation) or reference dose (RfD, for inges tion) to protect agains t effects other than cancer The RfC is defined as “an estimate (w ith uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime”. EPA disseminates dose-re sponse assessment information in several forms, based on the level of review. The Integrated Risk Information System (IRIS) [ 8 ] is

an EPA database that contains scientific he alth assessment information, including doseresponse information. All IRIS assessments since 1996 have also undergone independent external peer review. The current IRIS pr ocess 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 and 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 significant external scientific peer review. As cited in the CalEPA Technical Support Document for developing their chronic assessments 2 : “The guidelines for developing chronic inhalation 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) [ 9 ]. CalEPA defines the REL as “the concentration level at or below which no health effects are anticipated in the general human population”.

The emissions inventory for the source category includes emissions of 2 HAP with quantitative inhalation chronic noncancer thres hold values available. These 2 HAP, their threshold values, and the source of th e 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 Reference Exposure Levels. Air Toxicology and Epidemiology Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. February 2000 (http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf)

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 Council. Science and Judgment in Risk Assessment. Washington, DC: National Academy Press.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 12

Table 2.6-1 Dose-Response Values fo r Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources : IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental 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 do se-response information

Hazard identification and dose-response as sessment information for preliminary acute exposure were based on the existing re commendations of OAQPS for HAPs [ 10 ]. Depending on availability, the results from screening acute assessments are compared to both “no effects” reference levels for the general publ ic, such as the California Reference Exposure Levels (RELs), as well as emergency response levels, such as Acute Exposure Guideline Levels (AEGLs) and Emergency Response Pl anning Guidelines (ERPGs), with the recognition that emergency response values are no t 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 any limitations expressed therein. Comparisons among different availabl e inhalation health effect reference values (both acute and chronic) for selected HAPs ca n 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 Report]. (U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R-09/061, 2009. http://cfpub.epa.gov/ncea/cfm/r ecordisplay.cfm?deid=211003.)

California Acute Referenc e Exposure Levels (RELs ). The California Environmental Protection Agency (CalEPA) has developed acute dose-response reference values for many substances, expressing the results as Acute inha lation 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. [ 11 ]. 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

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 value, as reported in the IRIS file.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 13

uncertainties, exceeding the REL does not automatically indicate an adverse health impact.” Acute RELs are developed for 1-hour (and 8-hour) exposures. The values incorporate uncertainty factors similar to those used in deriving EPA’s Inhalation Reference Concentrations (RfCs) for chronic exposures (and, in fact, California also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory Committee (NAC) on Acute Exposure Guideline Levels 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 fo r the general public an d are applicable to emergency exposures ranging from 10 min to 8 h.” Their intended application is “for conducting risk assessments to aid in the development of emergency preparedness and prevention plans, as well as real time emergency response actions, for accidental chemical releases at fixed facilities and from transport carriers.” The document st ates 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 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 em ergency response, planning, and prevention programs. It is important to note that a potential 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 concentration (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 reversib le upon cessation of exposure.”

“AEGL-2 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that th e general population, including su sceptible individuals, could experience irreversible or other serious, long-lasting adverse health 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 nondisabling odor, taste, and sensory irritation or certain asymptom atic, nonsensory effects. With increasing airborne concentrations above each AEGL, there is a progressive increase in the likelihood of occurrence and the severity of effects desc ribed 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 idiosyncraticDraft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 14

responses, could experience the effects described at concentrations below the corresponding AEGL.”

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergenc y Response Planning Guidelines (ERPGs) [ 12 ] for acute exposures at three different levels of severity. These guidelines represent concentrations for exposure of the general popu lation (but not particular ly sensitive persons) for up to 1 hour associated with effects expected 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: “Eme rgency Response Planning Guidelines (ERPGs) were developed for emerge ncy planning and are intended as health based guideline concentrations for single exposures to chemicals. These guidelines (i.e., the ERPG Documents and ERPG values) are 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 actual chemical emergency occurs there is seldom

time to measure airborne concentrations and then to take action.” As with other emergency levels, these levels reflect consid eration of only single exposures, not repeated exposures.

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

“ERPG-1 is the maximum airborne concentratio n 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 effects or without perceiving a clearly defined, objectionable

odor.”

“ERPG-2 is the maximum airborne concentratio n below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing or developing

irreversible or other serious health effects or symptoms which could impair an individual's ability to take protective action.”

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

The emissions inventory for the Steel Pickling source category includes emissions of 2 HAP with relevant and available quantitative acute dose-response threshold values. These HAPs, their acute threshold values, and the source of the value are listed below in Table 2.6-2.Draft Risk Assessment for the Steel Pickling 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 assessment is the risk characterization, 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 information available, the application of the risk information and the resources available. In all cases, major issues associated with determining the nature

and extent of the risk are iden tified and discussed. Further, the EPA Administrator’s March

1995 Policy for Risk Characterization [ 13 ] specifies that a risk characterization “be prepared in a manner that is clear, transparent, re asonable, and consistent with other risk characterizations of similar scope prepared across programs in the Agency.” These principles of transparency and consistenc y have been reinforced by the Agency’s Risk Characterization

Handbook [ 14 ], in 2002 by the Agency’s information quality guidelines [ 15 ], and in the OMB/OSTP September 2007 Memorandum on Updated 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 analytical 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 fo r each source category (including maximum individual cancer risks and noncancer hazards, as well as cancer incidence estimates) along with a discussion of the major uncertainties associated with their derivation to provide decision makers with the fullest picture of the assessment and its limitations.

“Risk” for noncancer effects is expressed by comp aring an exposure 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 exposures 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 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 Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 16

increasingly greater than 1), the potential fo r adverse effects increases. For exposures predicted to be above the RfC, the risk charact erization includes the degree of confidence ascribed to the RfC values for the compound(s) of concern (i.e., high, medium, or low confidence) and discusses the impact of th is on possible health interpretations.

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

Screening for potentially significant acute inhalation exposures also followed the HQ approach. In this case, we divided the maximum estimated acute exposure by each available short-term threshold value to develop an array of HQ values relative to the various acute endpoints and thresholds. In general, when none of these HQ values are greater than one, there is no potential for acute risk. In those 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 assessm ents receive e xposures to multip le pollutants rather than a single pollutant, we estimated the aggregate health risks associated with all the exposures from a particular source category combined.

In assessing noncancer hazard from chronic exposures, in cases where different pollutants cause adverse health effects via completely diff erent 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 differen t substances in specific 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 affe ct the same organ or organ system. All TOSHI calculations presen ted here were based exclusively on effects occurring at the “critical dose” (i.e., the lowest dose that produces adverse health effects). Although HQs associated with some pollutants have been aggregated into 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 th at occur above the critical dose have not been included in the TOSHI calculations, some TOSH Is 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. 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.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 17

Because of the conservative nature of the acut e 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 National Air Toxics Asse ssment (NATA). For the facilities in the Steel Pickling source category, we extracted the NATA results, based on facility ID, the

estimates of the inhalation cancer and chronic non-cancer risks associated with the HAP emissions sources at the facility, including emissi ons sources that are not part of this source category but that are located within a contig uous area and are under common control. We analyzed risks due to the inhalation of HAP fo r the populations residing within 50 kilometers of each facility. The results of this “facility-wide” assessment are provided for the highest-risk facility below in the Risk Results section of this document. The complete results of the “facility-wide” assessment are provided in Appendix 5.



### 3 Risk Results for the Steel Pickling Source Category

3.1 Source Category Description 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 does not include facilities which pickle steel using acids other than HCl. Steel pickling operations can be conducted via continuous, semicontinuous, or batch processes. Five type s of pickling processes have been identified: (1) continuous strip; (2) push-pul l strip; (3) rod/wire; (4) tube; and (5) batch. The hazardous air pollutants (HAP) emitted from steel picklin g sources are HCl and chlorine (which is generated as a by-product of the regeneration pr ocess). A complete description of the steel pickling source category can be found in the text of the NPRM.

It is currently estimated that there are approximately 80 faci lities performing steel pickling and/or acid regeneration in the U.S. The NPRM data set contains 51 facilities identified witha steel pickling maximum achievable control technology (MACT) code in the 2005 NationalScale Air Toxics Assessment (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 thes e major/area classifications is significant 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.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 18

Table 3.1-1 summarizes the emissions for the Steel Pickling source category. The total HAP emissions for the source category 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 an emission at 51 of the 51 facilities and chlorine is reported for 6 facilities. There are no persistent and bioaccumulative HAP (PB HAP) em issions 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 from the Steel Pickling Source Category

Table 3.1-2 Summary of Source Cate gory 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 Maximum Respiratory Hazard Index:

Greater than 1 1 n/a

a Specific dose-response values for each chemical are identified on EPA’s Technology Transfer Network website for air

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

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

HAP 7 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 Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 19

Table 3.1-2 Summary of Source Cate gory Level Risks for Steel Pickling

Result HAP “Drivers”
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: 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, there is no associated cancer risk for this source category. The chronic noncancer inhalation risk corresponds to a maximum chronic respiratory HI of 2. An HI value greater than 1 is found at only this one facility. The ne xt highest source category HI is 0.1, with the remaining source category HI values even lower than 0.1 (significantly lower than the HI of 2). There were no reported emissions of persis tent HAP from this source category; therefore we have no concerns about any po tential multi-pathway risks from this category. Chlorine and hydrochloric acid can contribute to acidificat ion, but the extent to which that might be a problem for this source category was not assessed. No other potential environmental risks, including those as a direct result of exposure of flora and fauna to ambient air concentrations, were identified. Additionally, potential acute impacts on human health associated with hydrochloric acid were all well below the level of concern.

The result of the “fac ility-wide” assessment is that th e Steel Pickling source category’s highest chronic non-cancer risk, an HI value of 2 for chlorine, is equal to the “facility-wide” HI (2) at that facility. The highest facility-wide HI is 10 and at this facility the source category contributes very minimally 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 category MIR. However, the facility-wide MIR

associated with other emissions sources at facili ties with Steel Pickling pr ocesses is as high as

100.

The analysis of potential differences between act ual emission levels and emissions allowable

under the MACT standards indicate that actual emissions and allowable emissions are approximately the same as allowable emissions. The available data indicate that picklingDraft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 20

processes throughout the industry are equippe d with controls that achieve the HCL and chlorine emission limits required by the MACT stan dards. For more detail about this estimate

of the ration of actual to MACT-allowable emis sions, see the memo in the emissions can be

found in “Actual vs. Allowable Emissions for Steel Pickling - Emission Standards Technical Support and Post Promulgation Activities” [ 16 ] (to be referenced when final)

.


### 4 General Discussion of Uncertainties and How They Have Been

Addressed

While each of the preceding sections discussed specific uncertainties unique to the source category, the following includes a general discu ssion 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 indicates 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 sources 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 dispersion model wi th site-specific parameters and reasonably representative meteorology. If anything, the po pulation exposure estimates are biased high by not accounting for short- or long-term populat ion mobility, and by neglecting processes like deposition, plume depletion, a nd atmospheric degradation.

As previously discussed in section 1.2, a se nsitivity analysis performed for the 1999 NATA found that the selection of the meteorology data set location could result in a range of chronic ambient concentrations which varied from as much as 17% below the predicted value to as much as 84% higher than the predicted value. This variability translates directly to the predicted exposures and risks in our assessment , indicating that the actual risks could vary from 17% lower to 84% higher than the predicted values.

We have purposely biased the acute screening re sults high, considering 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 Dose-Response Relationships

In the sections that follow, a discussion is provided on uncerta inty 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 ex posure throughout the duration specified. For the purposes of assessing all potential health risks associated with the emissions included Deleted:Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 21

in this assessment, we rely on both chronic and acute benchmarks, which are described in

more detail below.

Although every effort is made to identify pee r-reviewed dose-response 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 pollut ants 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 response values for either of the HAP (HCl and chlorine) compounds assessed and no other carcinogenic HA P emissions were reported for this source category; therefore no cancer assessment was done for the Steel Pickling source category. Further, while these 2 pollutants have been wi dely studied, there are no data or studies indicating that either chlorine or HCl might be associated with cancer. Therefore, we 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 chro nic exposure levels that are intended to be health-protective. That is, EP A and other organizations whic h develop noncancer reference values (e.g., the Agency for Toxic Substances and Disease Registry – ATSDR) utilize an approach that is intended not to underestimate ri sk in the face of uncertainty and variability. When there are gaps in the available information, uncertainty factors (UFs) are applied to derive reference values that are intended to be protective against appreciable risk of deleterious effects. Uncertainty factors are commonly default values 8 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 fact ors 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 ma y be underestimated.

8 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 depart from them in evaluating the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate 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 Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 22

For non-cancer endpoints related to chronic ex posures, EPA derives a Reference Dose (RfD) for exposures via ingestion, and a Reference Co ncentration (RfC) for inhalation exposures. These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or of a continuous inhalation exposure (RfC) to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. 9 To derive values that are intended to be “without appreciable risk,” EPA’s methodology relies upo n 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 qual ity, strengths and limitations of the available studies. EPA typically chooses the relevant end point that occurs at the lowest dose, often using statistical modeling of the available data, and then determines the appropriate point of departure (POD) for derivation of the reference va lue. A POD is determined by (in order of preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of

the dose or concentration at which the toxic response was not signifi cantly 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). While collectively termed “UFs”, these factors account for a number of different quantitative c onsiderations when utilizing observed animal (usually rodent) or human toxicity data in a risk assessment. The UFs are intended to accountfor: (1) variation in susceptibility among the members of the human population (i.e., interindividual variability); (2) uncertainty in extrapolating from experimental animal data to humans (i.e., interspecies differences); (3) uncer tainty in extrapolating from data obtained in a study with less-than-lifetime exposure (i.e ., extrapolating from subchronic to chronic exposure); (4) uncertainty in extrapolating from a LOAEL in the absence of a NOAEL; and (5) uncertainty when the database is incomplete or there are problems with applicability of available studies. When scientifically sound, peer-reviewed assessment-specific data are not available, default adjustment values are selected for the individual UFs. For each type of uncertainty (when relevant to the assessment), EPA typically applies an UF value of 10 or 3 with the cumulative UF value leading to a downward adjustment of 10-3000 fold from the selected POD. An UF of 3 is used when the data do not support the use of a 10-fold factor. If an extrapolation step or adjustment is not relevant to an assessment (e.g., if applying human toxicity data and an interspecies extrapolation is not required) the associated UF is not used. 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 vari ation is considered 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 variability are often unavailable. In some

9 See IRIS glossaryDraft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 23

situations, a smaller UF of 3 ma y be applied to reflect a known lack of significant variability among humans.

2) Extrapolation from results of studies in experimental animals to humans is a necessary step for the majority of chemical risk assessments. When interpreting animal data, the concentration at the POD (e.g. NOAEL, BMDL) in an animal model (e.g. rodents) is extrapolated to estimate the human response. While there is long-standing scientific support for the use of animal studies as indicators of potential toxicity to humans, there are uncertainties in such extrapolations. 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 averag e human. Typically, compound specific data to evaluate relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty in this extrapolation. Size-related differences (allometric relationships) indicate that typically

humans are more sensitive than rodents when compared on a mg/kg/day basis. The default choice of 10 for the interspecies UF is consistent with these differences. For a specific chemical, differences in species responses ma y be greater or less than this value.

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

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

4) Toxicity data are typically limited as to the dose or exposure levels that have been tested in individual studies; in an animal study, for example, treatment groups may differ in exposure by up to an order of magnitude. The preferred approach to arrive at a POD is to use BMD analysis; however, this approach requires adequate 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 account for the potential for deriving an underprotective RfD/RfC due to a data gap preventing complete characterization of the chemical’s toxicity. In the ab sence of studies for a known or suspected endpoint of concern, a UF of 10 or 3-fold is typically applied.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 24

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 th at may be less than 10. UFs are applied based on chemicalspecific or health effect-specific information (e.g., simple irritation effects do not vary appreciably between human individuals, hence a va lue of 3 is typically used), or based on the purpose for the reference value (see the follo wing paragraph). The UFs applied in acute reference value derivation include: 1) heterogeneity among humans; 2) uncertainty in extrapolating from animals to humans; 3) unce rtainty in LOAEL to NOAEL adjustments; and 4) uncertainty in accounting for an incomplete da tabase on toxic effects of potential concern. Additional adjustments are often applied to account for uncertainty in extrapolation from observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an

acute reference value at another ex posure duration (e.g., 1 hour).

Not all acute reference values are developed for the same purpose and care must be taken when interpreting the results of an acute assess ment of human health effects relative to the reference value or values being exceeded. Wh ere relevant to the es timated exposures, the

lack of threshold values at different levels of severity should be factored into the risk characterization as potential uncertainties.Draft Risk Assessment for the Steel Pickling 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, 2005. Revision to the Guideline on Air Quality Models: Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final

Rule. 40 CFR Part 51. http://www.epa.gov/EPA-AIR/2005/November/Day-09/a21627.htm

3 . US EPA, 2004. Users’ guide for the AMS/ EPA regulatory model – AERMOD. EPA-454/B03-001. http://www.epa.gov/scram001/7thconf/aermod/aermodugb.pdf

.

4 . Allen, D., C. Murphy, Y. Kimura, W. Vizuete, T. Edgar, H. Jeffries, B.-U. Kim, M. Webster, and M. Symons, 2004. Variable industrial VOC emissions and their impact on ozone

formation in the Houston Galv eston Area. Final Report: Texas Environmental Research Consortium Project H-13. http://files.harc.edu/Projects/AirQuality/Projects/H013.2003/H13FinalReport.pdf

5 . 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.

6 . 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/atw/toxsource/table1.pdf

7 . US EPA, 2005. 1999 National Air Toxics Risk Assessment. http://www.epa.gov/ttn/atw/nata1999

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

.

9 . 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

.

10 . US EPA, 2005. Table 2. Acute Dose-Res ponse Values for Screening Risk Assessments (6/02/2005). Office of Air Quality Planning and Standards. http://www.epa.gov/ttn/atw/toxsource/table2.pdf

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

12 . American Industrial Hygiene Associatio n , 2009. Current AIHA ERPG Values. http://www.aiha.org/insideaiha/volunte ergroups/Documents/ERP-erpglevels.pdf

.

13 . US EPA, 1995. Guidance for Risk Ch aracterization. Science Policy Council. http://www.epa.gov/OSA/spc/pdfs/rcguide.pdf

.

14 . US EPA, 2000. Risk Characterization Handbook. EPA 100-B-00-002.Draft Risk Assessment for the Steel Pickling Source Category -- FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 26

15 . US EPA, 2002. EPA’s Guidel ines for Ensuring and Maximi zing the Quality, Objectivity, Utility, and Integrity of Information Dissemina ted by the Environmental Protection Agency.

EPA Office of Environmental Information. EPA/260R-02-008. http://www.epa.gov/quality/informationguidelin es/documents/EPA_InfoQualityGuidelines.pdf

16 Not finalized at this time.