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Draft Residual Risk Assessment for the Steel Pickling 

Source Category 

by 

EPA’s Office of Air Quality Planning and Standards 

Office of Air and Radiation 

July 2010 
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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 Uncertainties 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 Acronyms 
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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 estimate
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1 Introduction 

Section 112 of the Clean Air Act (CAA) establishes a two-stage regulatory process for 

addressing emissions of hazardous air pollutants (HAPs) 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 categories of industrial sources (e.g., petroleum 

refineries, pulp and paper mills, etc.) [1]. EPA has largely completed the initial Maximum 

Achievable Control Technology (MACT) standards as required under this provision. Under 

section 112(d)(6), EPA must review each of these technology-based standards at least every 

eight years and revise a standard, as necessary, “taking into account developments in 

practices, 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 risk stage. For each source category for which 

EPA issued MACT standards, the residual risk stage must be completed within eight years of 

promulgation of the initial technology-based standard. 

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board 

(SAB) on the “Risk and Technology Review (RTR) Assessment Plan” and in June of 2007, 

we received a letter with the results of that consultation. Subsequent to the consultation, in 

June of 2009 a meeting was held with an SAB panel for a formal peer review of the “Risk and 

Technology Review (RTR) Assessment Methodologies”. 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 document through the National Emission Standards for Hazardous 

Air Pollutant Emissions: Hard and Decorative Chromium Electroplating and Chromium 

Anodizing Tanks; Group I Polymers and Resins; Marine Tank Vessel Loading Operations; 

Pharmaceuticals Production; The Printing and Publishing Industry; and Steel Pickling--HCl 

Process Facilities and Hydrochloric 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 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 Process 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 human 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 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 source category. Since none of the screening assessments 
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indicated any significant potential for chronic non-inhalation health effects, or environmental 

impacts including effects to threatened and endangered 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 Assessment (NATA) National Emissions Inventory 

(NEI) served as the starting point for this assessment. The 2005 NEI purportedly contains 

information on actual emissions during the entire 2005 base year. Using the process MACT 

code1

, 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 those that would greatly influence risk estimates) 

and to make changes to the data set where possible 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 concentrations and associated health risk from 

each facility in the source category of interest were estimated using the Human Exposure 

Model in combination with the American Meteorological Society/EPA Regulatory Model 

dispersion modeling system (HEM-AERMOD). The 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 dispersion modeling, estimation of individual 

human exposures and health risks, and estimation of population risks. This section focuses on 

the dispersion modeling component. The exposure and risk characterization components are 

discussed in other subsections of Sections 2 and 3. 

The dispersion model in the HEM-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 MACT 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 (MWCs) is assigned at the site level whereas the MACT 

code for petroleum refinery catalytic cracking is assigned at the process level). 
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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 surrounding 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 NWS from nearest site (158 stations) 

Meteorological data for HEM-AERMOD is selected 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 nearest 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 employ 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 1991. While the selection of a single year may 

result in under-prediction of long-term ambient levels at some locations, likewise it may result 

in over-prediction at others. For each facility 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 predicted 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. 
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The HEM-AERMOD system estimates ambient concentrations at the geographic centroids of 

census blocks (using the 2000 Census), and at other 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 centroid. Possible future residential use of currently uninhabited 

areas was not considered. Census blocks, the finest resolution available in the census data, 

are typically comprised of approximately 40 people or about ten households. 

In contrast to the development of ambient concentrations for evaluating long-term exposures, 

which was performed only for occupied census blocks, worst-case short-term (one-hour) 

concentrations were estimated both at the census block centroids and at 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 totals, we applied the general assumption to all 

source categories that the maximum one-hour emission rate from any source was ten times the 

average annual hourly emission rate for that source. 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 dataset 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 performed 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 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 suggests that this factor should cover more than 

99% of the short-term peak gaseous or volatile 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 grid elevations (used in estimating short- and 
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long-term ambient concentrations) were evaluated at the highest elevation of any census block 

in that sector. If a sector does not contain any 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 activities, modeling short-term activity would, on 

average, reduce risk estimates about 25% for particulate HAPs; it will also reduce risk 

estimates for gaseous HAPs, but typically by much less. Second, basing exposure estimates 

on average ambient concentrations at census block centroids may underestimate or 

overestimate actual exposure concentrations at some residences. Further 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 population growth or decrease 

over 70 years, instead basing the assessment on the assumption that each person’s predicted 

exposure is constant over the course of their lifetime which is assumed to be 70 years. In 

assessing cancer risk, three metrics 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, affect the shape of the distribution of individual 

risks across the affected population, shifting it toward higher estimated individual risks at the 

upper end and reducing the number of people estimated to be at lower risks, thereby biasing 

the risk estimates high. When screening for potentially 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. 
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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 same general approach that has been used for 

developing chronic health risk assessments under the residual risk program. That is, we 

developed a tiered, iterative approach. This tiered, iterative approach to risk assessment has 

been endorsed by the National Academy of Sciences 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 tiered, iterative approach to the assessment. This 

means that we began with a screening assessment, which relies on readily-available data and 

uses conservative assumptions that in combination 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 temporal 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 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, and exposure location. We used the following 

worst-case assumptions in our screening approach: 

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

rates. 

• For facilities with multiple emission points, peak 1-hour emissions were assumed to 

occur at all emission points at the same time. 

• For facilities with multiple emission points, 1-hour concentrations at each receptor 

were assumed to be the sum of the maximum concentrations due to each emission 

point, regardless of whether those maximum concentrations occurred during the same 

hour. 

• Worst-case meteorology (from one 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 possible 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. 
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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 known to be persistent and bioaccumulative in 

the environment (PB-HAP). The PB-HAP compounds or compound classes are identified for 

the screening from the EPA’s Air Toxics Risk Assessment Library [5]. Examples of PB-HAP 

are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, 

heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury 

compounds, methoxychlor, polychlorinated 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 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 the areas surrounding these facilities. 

Additionally, we evaluated the potential for significant ecological exposures to non PB-HAP 

from exceedances of chronic human health inhalation 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 rodents) 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 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 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 carcinogenic. Dose-response assessment information for 

the noncancer effects due to chronic exposure (either 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 sources 
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and prioritized according to (1) conceptual consistency with EPA risk assessment guidelines 

and (2) level of peer review received. The prioritization process was aimed at incorporating 

into our assessments the best available science with respect to dose-response information. 

The recommendations are based on the following sources, in order of priority: 

1) US Environmental Protection Agency (EPA). 

EPA has developed 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 ingestion) to protect against effects other than 

cancer The RfC is defined as “an estimate (with uncertainty spanning perhaps an order of 

magnitude) of a continuous inhalation exposure to the human population (including 

sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects 

during a lifetime”. EPA disseminates dose-response 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 health assessment information, including doseresponse information. All IRIS assessments since 1996 have also undergone independent 

external peer review. The current IRIS process includes review by EPA scientists, 

interagency reviewers from other federal agencies, and the public, and peer review by 

independent scientists external to EPA. 

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

Environmental Health Hazard Assessment has developed dose-response assessments for 

many substances, based both on carcinogenicity and health effects other than cancer. The 

process for developing these assessments is similar to that used by EPA to develop IRIS 

values and incorporates significant external scientific peer review. As cited in the 

CalEPA Technical Support Document for developing their chronic assessments2

: “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 threshold 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 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. 
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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 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/m3) 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 recommendations 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 public, such as the California Reference Exposure 

Levels (RELs), as well as emergency response levels, such as Acute Exposure Guideline 

Levels (AEGLs) and Emergency Response Planning Guidelines (ERPGs), with the 

recognition that 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 definition of that level and any 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 Report]. (U.S. Environmental Protection Agency, 

Washington, D.C., EPA/600/R-09/061, 2009. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003.) 

California Acute Reference Exposure Levels (RELs). The California Environmental 

Protection Agency (CalEPA) has developed acute dose-response reference values for many 

substances, expressing the results as Acute inhalation Reference Exposure Levels (RELs). 

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

“the concentration level at or 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 medical and toxicological literature. RELs are 

designed to protect the most sensitive individuals in the population by the inclusion of 

margins of safety. Since margins of safety are incorporated to address data gaps and 

 

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. 
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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 for the general public and are applicable to 

emergency exposures ranging from 10 min to 8 h.” Their intended application is “for 

conducting risk assessments to aid in the development of emergency preparedness and 

prevention plans, as well as real time emergency response actions, for accidental chemical 

releases at fixed facilities and from transport carriers.” The document states 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 concentrations of acutely toxic, highpriority chemicals.” In detailing the intended application of AEGL values, the document 

states that “It is anticipated that the AEGL values will be used for regulatory and 

nonregulatory purposes by U.S. Federal and State agencies, and possibly the international 

community in conjunction with chemical emergency response, planning, and prevention 

programs. 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/m3

) of a substance above 

which it is predicted that the general population, including susceptible individuals, could 

experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. 

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

exposure.” 

“AEGL-2 is the airborne concentration (expressed as ppm or mg/m3

) of a substance above 

which it is predicted that the general population, including susceptible individuals, could 

experience irreversible or other serious, long-lasting adverse health effects or an impaired 

ability to escape.” 

 “Airborne concentrations below AEGL-1 represent exposure levels that can produce mild 

and progressively increasing but transient and nondisabling odor, taste, and sensory 

irritation or certain asymptomatic, nonsensory effects. With increasing airborne 

concentrations above each AEGL, there is a progressive increase in the likelihood of 

occurrence and the severity of effects described for each corresponding AEGL. Although 

the AEGL values represent threshold levels for the general public, including susceptible 

subpopulations, such as infants, children, the elderly, persons with asthma, and those with 

other illnesses, it is recognized that individuals, subject to unique or idiosyncratic 
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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 Emergency Response Planning Guidelines (ERPGs) [12] 

for acute exposures at three different levels of severity. These guidelines represent 

concentrations for exposure of the general population (but not particularly sensitive persons) 

for up to 1 hour associated with effects expected to be mild or transient (ERPG-1), 

irreversible or serious (ERPG-2). 

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 emergency planning and are intended as health based 

guideline concentrations for single exposures to chemicals. These guidelines (i.e., the ERPG 

Documents and ERPG values) are intended for use as planning tools for assessing the 

adequacy of accident prevention and emergency response plans, including transportation 

emergency planning and for developing community emergency response plans. The emphasis 

is on ERPGs as planning values: When an actual chemical emergency occurs there is seldom 

time to measure airborne concentrations and then to take action.” As with other emergency 

levels, these levels reflect consideration 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 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 effects 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 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. 
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Table 2.6-2 Dose-Response Values for Acute Exposure 

Pollutant CAS Number 

AEGL-1 

(1-hr) 

(mg/m3) 

AEGL-2 

(1-hr) 

(mg/m3) 

ERPG-1

(mg/m3) 

ERPG-2 

(mg/m3) 

REL 

(mg/m3) 

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 overall conclusion about risk is synthesized that is 

complete, informative, and useful for decision makers. In general, the nature of this risk 

characterization depends on the information available, the application of the risk information 

and the resources available. In all cases, major issues associated with determining the nature 

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

1995 Policy for Risk Characterization [13] specifies that a risk characterization “be prepared 

in a manner that is clear, transparent, reasonable, and consistent with other risk 

characterizations of similar scope prepared across programs in the Agency.” These principles 

of transparency and consistency have been reinforced by the Agency’s Risk Characterization 

Handbook [14], in 2002 by the Agency’s information quality guidelines [15], and in the 

OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis6

, and 

are incorporated in these assessments. 

Estimates of health risk are presented in the context of uncertainties and limitations in the data 

and methodology. Through our tiered, iterative analytical approach, we have attempted to 

reduce both uncertainty and bias to the greatest degree possible in these assessments. We 

have provided summaries of risk metrics for 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 comparing an exposure to a reference level as a 

ratio. The “hazard quotient” (HQ) is the estimated exposure divided by a reference level (e.g., 

the RfC). For a given HAP, exposures at or below the reference level (HQ≤1) are not likely 

to cause adverse health effects. As exposures increase above the reference level (HQs 

 

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) 
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increasingly greater than 1), the potential for adverse effects increases. For exposures 

predicted to be above the RfC, the risk characterization includes the degree of confidence 

ascribed to the RfC values for the compound(s) of concern (i.e., high, medium, or low 

confidence) and discusses the impact of this on possible health interpretations. 

The risk characterization for chronic effects other 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 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 assessments receive exposures to multiple pollutants 

rather than a single pollutant, we estimated the aggregate health risks associated with all the 

exposures from a particular source category combined. 

In assessing noncancer hazard from chronic exposures, in cases where different pollutants 

cause adverse health effects via completely different modes of action, it may be inappropriate 

to aggregate HQs. In consideration of these mode-of-action differences, the mixtures 

guidelines support aggregating effects of different 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 individual HAPs that affect the same organ or 

organ system. All TOSHI calculations presented here were based exclusively on effects 

occurring at the “critical dose” (i.e., the lowest dose that produces adverse health effects). 

Although HQs associated with some pollutants have been aggregated into more than one 

TOSHI, this has been done only in cases where the critical dose affects more than one target 

organ. Because impacts on organs or systems that occur above the critical dose have not been 

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. 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. 
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Because of the conservative nature of the acute inhalation screening and the transient nature 

of emissions fluctuations and potential exposures, 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 context, we examined “facility-wide” risks using 

the results of the 2005 National Air Toxics Assessment (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 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 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 category includes facilities that are engaged 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 types of pickling processes have been identified: 

(1) continuous strip; (2) push-pull strip; (3) rod/wire; (4) tube; and (5) batch. The hazardous 

air pollutants (HAP) emitted from steel pickling sources are HCl and chlorine (which is 

generated as a by-product of the regeneration process). 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 facilities performing steel pickling 

and/or acid regeneration in the U.S. The NPRM data set contains 51 facilities identified with 

a 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 these 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. 
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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) 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 from the Steel Pickling Source Category 

Table 3.1-2 Summary of Source Category 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 emissions of any HAP with cancer dose-response values. 

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSa 

HAP7 

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 Υ 
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Table 3.1-2 Summary of Source Category 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 next 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 persistent HAP from this source category; therefore 

we have no concerns about any potential multi-pathway risks from this category. Chlorine 

and hydrochloric acid can contribute to acidification, 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 “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 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 facilities with Steel Pickling processes is as high as 

100. 

The analysis of potential differences between actual 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 pickling 
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processes throughout the industry are equipped with controls that achieve the HCL and 

chlorine emission limits required by the MACT standards. For more detail about this estimate 

of the ration of actual to MACT-allowable emissions, 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 discussion 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 are considered relatively small since we are 

using EPA’s refined local dispersion model with site-specific parameters and reasonably 

representative meteorology. If anything, the population exposure estimates are biased high by 

not accounting for short- or long-term population mobility, and by neglecting processes like 

deposition, plume depletion, and atmospheric degradation. 

As previously discussed in section 1.2, a sensitivity analysis performed for the 1999 NATA 

found that the selection of the meteorology dataset location could result in a range of chronic 

ambient concentrations which varied from as much as 17% 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 results high, considering that they depend upon 

the joint occurrence of independent factors, such 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 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 

Deleted: 
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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 peer-reviewed dose-response values for all HAPs 

emitted by the sources included in this assessment, both HAP have no peer-reviewed cancer 

potency values. Since exposures to these pollutants cannot be included in a quantitative risk 

estimate, an understatement of risk for these pollutants at environmental exposure levels is 

possible. 

Cancer assessment

There are no cancer dose response 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 Pickling 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, 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 chronic exposure levels that are intended to be 

health-protective. That is, EPA and other organizations which develop noncancer reference 

values (e.g., the Agency for Toxic Substances and Disease Registry – ATSDR) utilize an 

approach that is intended not to underestimate risk in the face of uncertainty and variability. 

When there are gaps in the available information, uncertainty factors (UFs) are applied to 

derive reference values that are intended to be protective against appreciable risk of 

deleterious effects. Uncertainty factors are commonly default values8 e.g., factors of 10 or 3, 

used in the absence of compound-specific data; where data are available, uncertainty factors 

may also be developed using compound-specific information. When data are limited, more 

assumptions are needed and more default factors are used. Thus there may be a greater 

tendency to overestimate risk—in the sense that further study might support development of 

reference values that are higher (i.e., less potent) because fewer default assumptions are 

needed. However, for some pollutants it is possible that risks may be underestimated.

 

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. 
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For non-cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) 

for exposures via ingestion, and a Reference Concentration (RfC) for inhalation exposures. 

These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) 

of daily oral exposure (RfD) or 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 upon an uncertainty factor (UF) approach (U.S. 

EPA, 1993, 1994) which includes consideration of both uncertainty and variability. 

 

EPA begins by evaluating all of the available peer-reviewed literature to determine noncancer endpoints of concern, evaluating the quality, strengths and limitations of the available 

studies. EPA typically chooses the relevant endpoint that occurs at the lowest dose, often 

using statistical modeling of the available data, and then determines the appropriate point of 

departure (POD) for derivation of the reference value. A POD is determined by (in order of 

preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of 

the dose or concentration at which the toxic response was not significantly elevated (no 

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

level (LOAEL). 

A series of downward adjustments using default UFs is then applied to the POD to estimate 

the reference value (U.S. EPA 1994, 2002). While collectively termed “UFs”, these factors 

account for a number of different quantitative considerations when utilizing observed animal 

(usually rodent) or human toxicity data in a risk assessment. The UFs are intended to account 

for: (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) uncertainty in extrapolating from data obtained in a 

study with less-than-lifetime exposure (i.e., extrapolating from subchronic to chronic 

exposure); (4) uncertainty in extrapolating from a LOAEL in the absence of a NOAEL; and 

(5) uncertainty when the database is incomplete or there are problems with applicability of 

available studies. When scientifically sound, peer-reviewed assessment-specific data are not 

available, default adjustment values are selected for the individual UFs. For each 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 source of variability as well as uncertainty. 

Uncertainty related to human variation 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 variation may be larger or smaller; however, data to 

examine the potential magnitude of human variability are often unavailable. In some 

 

9

 See IRIS glossary 
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situations, a smaller UF of 3 may be applied to reflect a known lack of significant variability 

among humans. 

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

necessary step for the majority of chemical risk assessments. When interpreting animal data, 

the concentration at the POD (e.g. NOAEL, BMDL) in an animal model (e.g. rodents) is 

extrapolated to estimate the human response. While there is long-standing scientific support 

for the use of animal studies as indicators of potential toxicity to humans, there are 

uncertainties in such extrapolations. 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 average human. Typically, compound specific data to 

evaluate relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty 

in this extrapolation. Size-related 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 may be greater or less than this value. 

Pharmacokinetic models are useful to examine species differences in pharmacokinetic 

processing and associated uncertainties; however, such dosimetric adjustments are not always 

possible. 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 toxicokinetic and toxicodynamic components) is used to 

account for expected species differences and associated uncertainty in extrapolating from 

laboratory animals to humans in the derivation of a reference value. If information on one or 

the other of these components is available and accounted for in the cross-species 

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 absence of studies for a known or suspected endpoint of concern, a 

UF of 10 or 3-fold is typically applied. 
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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 developed 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 information (e.g., simple irritation effects do not vary 

appreciably between human individuals, hence a value of 3 is typically used), or based on the 

purpose for the reference value (see the following paragraph). The UFs applied in acute 

reference value derivation include: 1) heterogeneity among humans; 2) uncertainty in 

extrapolating from animals to humans; 3) uncertainty in LOAEL to NOAEL adjustments; and 

4) uncertainty in accounting for an incomplete database on toxic effects of potential concern. 

Additional adjustments are often applied to account for uncertainty in extrapolation from 

observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an 

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

 

Not all acute reference values are developed for the same purpose and care must be taken 

when interpreting the results of an acute assessment of human health effects relative to the 

reference value or values being exceeded. Where relevant to the estimated exposures, the 

lack of threshold values at different levels of severity should be factored into the risk 

characterization as potential uncertainties. 
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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 Galveston 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 Chronic 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 Hazard 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-Response 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 assessment, 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 Association , 2009. Current AIHA ERPG Values. 

http://www.aiha.org/insideaiha/volunteergroups/Documents/ERP-erpglevels.pdf. 

13. US EPA, 1995. Guidance for Risk Characterization. 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 Guidelines for Ensuring and Maximizing the Quality, Objectivity, 

Utility, and Integrity of Information Disseminated by the Environmental Protection Agency. 

EPA Office of Environmental Information. EPA/260R-02-008. 

http://www.epa.gov/quality/informationguidelines/documents/EPA_InfoQualityGuidelines.pdf

16 Not finalized at this time.