From: Shine, Brenda <Shine.Brenda@epa.gov> 

Sent: Tuesday, May 13, 2014 4:46 PM 

To: Cortney Higgins 

Cc: Palma, Ted; Lassiter, Penny; Thundiyil, Karen; Rimer, Kelly; Tierney, Jan 

Subject: Response to Interagency Comments on Petroleum Refinery Risk Report 

Hi Cortney, 

Here is the latest draft (redline) of the risk report that addresses your comments. 

<< Risk and Technology Review Assessment 051314 with OMB Comments addressed.pdf >> 
Draft Risk Assessment for the Petroleum Refining Source Sector –

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Draft 

Residual Risk Assessment for the Petroleum Refining Source 

Sector

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

May 2014
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Table of Contents

1 Introduction ....................................................................................................................4

2 Methods..........................................................................................................................4

2.1 Emissions and source data ........................................................................................4

2.2 Dispersion modeling for inhalation exposure assessment ..........................................5

2.3 Estimating chronic human inhalation exposure .........................................................8

2.4 Acute Risk Screening and Refined Assessments.......................................................9

2.5 Multipathway human health and environmental risk screening ...............................10

2.6 Dose-response assessment ......................................................................................14

2.6.1 Sources of chronic dose-response information .................................................14

2.6.2 Sources of acute dose-response information ................................................2524

2.7 Risk characterization ..........................................................................................2928

2.7.1 General........................................................................................................2928

2.7.2 Mixtures......................................................................................................3130

2.7.3 Facility-wide Risks..........................................................................................31

2.7.4 MACT-Allowable Risk ...............................................................................3231

3 Risk results for the petroleum refining source sector ....................................................3231

3.1 Source category emissions and results ................................................................3231

3.2 Baseline risk characterization .................................................................................37

3.3 Post-control risk characterization........................................................................4847

4 General discussion of uncertainties and how they have been addressed .....................4948

4.1 Exposure modeling uncertainties........................................................................4948

4.2 Uncertainties in the dose-response relationships .................................................5049

5 References................................................................................................................5958

Index of Tables

Table 2.2-1 AERMOD version 12345 model options for RTR modeling ...............................6

Table 2.6-1 (A) Dose-Response Values for......................................................................1817

Chronic Inhalation Exposure to Carcinogens ....................................................................1817

Table 2.6-1 (B) Dose-Response Values for Chronic Oral Exposure to Carcinogens .........2120

Table 2.6-2 (A) Dose-Response Values for Chronic Inhalation Exposure to Noncarcinogens

.............................................................................................................................................21

Table 2.6-2 (B) Dose-Response Values for Chronic Oral Exposure to Noncarcinogens....2524

Table 2.6-3 Dose-Response Values for Acute Exposure...................................................2726

Table 3.2-5 Source Category Contribution to Facility-Wide.............................................4846

Chronic Cancer Risks (Actual Emissions).........................................................................4846

Appendices

Appendix 1 Technical Support Document for HEM3 Modeling

Appendix 2 Meteorological Data for HEM3 Modeling

Appendix 3 Analysis of data on short-term emission rates relative to long-term emission 

rates
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Appendix 4 Technical Support Document for TRIM-Based Multipathway Tiered Screening 

Methodology for RTR 

Appendix 5 Detailed Risk Modeling Results

Appendix 6 Acute Impacts Refined Analysis

Appendix 7 Dispersion Model Receptor Revisions and Additions for the Petroleum 

Refinery Source Sector

Appendix 8 Development of the Chronic Screening Level for Carbonyl Sulfide

Appendix 9 Refinery Emissions and Risk Estimates for Modeled “Allowable” Emissions

Appendix 10 Technical Support Document: Human Health Multipathway Residual Risk 

Assessment for the Petroleum Refineries Sector - A Site Specific Analysis

Appendix 11 Environmental Risk Screen

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model

AEGL Acute exposure guideline level

ASTDR US Agency for Toxic Substances and Disease Registry

CalEPA California Environmental Agency

CTE Central Tendency Estimate

ERPG Emergency Response Planning Guideline

HAP Hazardous Air Pollutant

HEM Human Exposure Model

HI Hazard index

HQ Hazard quotient

IRIS Integrated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of action

NAC National Advisory Committee

NAAQS National Ambient Air Quality Standards

NATA National Air Toxics Assessment

NEI National Emissions Inventory

NPRM Notice of Proposed Rulemaking

PB-HAP Persistent and Bioaccumulative - HAP

POM Polycyclic organic matter

REL Reference exposure level

RfC Reference concentration

RfD Reference dose

RME Reasonable Maximum Exposure

RTR Risk and Technology

TOSHI Target-organ-specific hazard index

URE Unit risk estimate
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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 (HAP) from stationary sources. In the first 

stage, section 112(d) requires the Environmental Protection Agency (EPA, or the Agency) to 

develop technology-based standards for categories of sources (e.g., petroleum refineries, pulp 

and paper mills, etc.) [1]. EPA has 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” [2]. We received the final SAB 

report on this review in May of 2010 [3]. Where appropriate, we have responded to the key 

messages from this review in developing our current risk assessments and we will be 

continuing our efforts to improve our assessments by incorporating updates based on the SAB 

recommendations as they are developed and become available. Our responses to the key 

recommendations of the SAB are outlined in a memo entitled, “EPA’s Actions in Response to 

Key Recommendations from the SAB Review of RTR risk Assessment Methodologies” [4].

This document contains the methods and the results of baseline risk assessments (i.e., after the 

implementation of the MACT standard) and the results of the post-control scenario risk 

assessment performed for the Petroleum Refining Source Sector. The methods discussion 

includes descriptions of the methods used to develop refined estimates of chronic inhalation 

exposures and human health risks for cancer and noncancer endpoints, as well as descriptions 

of the methods used to screen for acute health risks, chronic non-inhalation health risks, and 

adverse environmental effects.

2 Methods

2.1 Emissions and source data

The first and primary source category for which regulations were developed, Petroleum 

Refineries - Other Sources Not Distinctly Listed (Refinery MACT 1), includes all emission 

sources from petroleum refinery process units except those that were expected to be regulated 

elsewhere, such as the NESHAP for Boilers and Process Heaters (40 CFR part 63 subpart 
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DDDDD). The Refinery MACT 1 rule, which focuses on evaporative emissions, was 

published in 40 CFR part 63, subpart CC on August 18, 1995 (60 FR 43620) and specifically 

excludes three types of process vents: catalytic cracking unit (CCU) catalyst regeneration 

vents, catalytic reforming unit (CRU) catalyst regeneration vents, and sulfur plant vents. 

These specific vents are regulated by the NESHAP for Petroleum Refineries: Catalytic 

Cracking Units, Catalytic Reforming Units, and Sulfur Recovery Units (Refinery MACT 2) in 

40 CFR part 63, subpart UUU. The Refinery MACT 2 standards, which focus on combustion 

sources, were promulgated on April 11, 2002 (67 FR 17762. This analysis will evaluate the 

risks associated with both the MACT 1 and MACT 2 emissions.

In support of the residual risk and technology review required by CAA sections 112(f) and 

112(d)(6) for this source sector, on April 1, 2011 EPA sent out an information collection 

request (ICR) under the authority of Section 114 of the CAA to the petroleum refining 

industry. The ICR requested available information regarding process equipment, control 

devices, point and fugitive emissions, practices used to control fugitive emissions, and other 

aspects of facility operations, including stack parameters and locations. Details on the 

development of the emissions and source data for this source category can be found in the 

docket.[5] Section 3 below provides a summary of the emissions. 

2.2 Dispersion modeling for inhalation exposure assessment

Both long- and short-term inhalation exposure concentrations and associated health risks from 

each facility in the source category were estimated using the Human Exposure Model in 

combination with the American Meteorological Society/EPA Regulatory Model dispersion 

modeling system (HEM-AERMOD, or HEM3). The approach used in applying this modeling 

system is outlined below, and further details are provided in Appendix 1 to this document

(Technical Support Document for HEM3 Modeling). The HEM3 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 HEM3 system, AERMOD version 12345 (the version of 

AERMOD that was available at the time of the risk analysis), is a state-of-the-science 

Gaussian plume dispersion model that is preferred by EPA for modeling point, area, and 

volume sources of continuous air emissions from facility applications [6]. Further details on 

AERMOD can be found in the AERMOD Users Guide [7]. 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 HEM3 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.
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Table 2.2-1 AERMOD version 12345 model options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point, area represented as pseudo point source

Receptor orientation Polar (13 rings and 16 radials)

Discrete (census block centroids) and user-supplied receptors

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 ( 824 stations)

In HEM3, meteorological data are ordinarily selected from a list of over 800 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. When considering off-site 

meteorological data most site specific dispersion, EPA modeling guidelines suggest that 

modeling efforts employ up to five years of data to capture variability in weather patterns 

from year to year. However, because dispersion model runtimes using five years of 

meteorological data would be too long for RTR source categories with many sources, we

modeled only a single year, 2011. While the selection of a single year may result in underprediction of long-term ambient levels at some locations, likewise it may result in overprediction 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 22 

miles. Appendix 2 to this document (Meteorological Data Processing Using AERMET for 

HEM3) provides a complete listing of stations and assumptions along with further details used 

in processing the data through AERMET, the AERMOD meteorological data processing 

program. The document “Risk and Technology Review (RTR) Risk Assessment 

Methodologies: For Review by the EPA’s Science Advisory Board with Case Studies –

MACT I Petroleum Refining Sources and Portland Cement Manufacturing” (US EPA, 2009) 

provides more details on these modeling approaches.

Beginning with version 12345, AERMET allows for a minimum wind speed of 0.5 m/s to be 

utilized when processing monitoring stations that are equipped with sonic anemometers and 

for an adjustment to the surface friction velocity (u*). The public version of AERMET 

available at the time we conducted the modeling did not include the surface friction velocity 

adjustment. Also at the time, an updated version of AERMET (and AERMOD) was under 

development that incorporated further surface friction velocity adjustments to AERMET 

version 12345. In anticipation of the update, EPA processed meteorological data using a prepublic release version of AERMET and incorporated the updated surface friction velocity 

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adjustment in the output. It was EPA’s judgement that the pre-public release version of 

AERMET would generate AERMOD ready meteorological data very close to that generated 

with the final public release version. 

EPA has posted the AERMET meteorological data used in the refinery analysis on the EPA’s 

FERA (Fate, Exposure, and Risk Analysis) website under the HEM model page. AERMET 

and AERMOD (version 13350) were released to the public in late December 2013 on the 

EPA’s Support Center for Regulatory Atmospheric Modeling (SCRAM) website.

While it was not feasible to remodel the entire source category using the public released 

version of AERMOD and AERMET, we were able to compare modeling results for 14 

refineries using the using meteorological data processed with the pre-public release version of 

AERMET and data processed with the current 13350 version. In addition, the 13350 version 

of AERMOD was run with the meteorological data processed with the 13350 version of 

AERMET. The comparison was conducted by examining the maximum individual risk 

(MIR) at 14 refinery facilities, including the 4 facilities with the highest risk, the 5 with the 

lowest risks, and 5 randomly selected facilities. The largest difference in MIR values between 

the runs was 3 percent for one facility. The other 13 facilities had differences in their MIR 

values between runs of less than 1 percent. These results of this comparison are presented in 

Appendix 5.

The HEM3 system estimates ambient concentrations at the geographic centroids of census 

blocks (using the 2010 Census) and at other receptor locations that can be specified by the 

user. See Appendix 7 of this document (Dispersion Model Receptor Revisions and Additions

for the Petroleum Refining Sector) for a discussion of user receptors and centroid location 

changes specific to this source category. The model accounts for the effects of multiple 

facilities when estimating concentration impacts at each block centroid. When evaluating the 

risks associated with a particular source category we combined the impacts of all facilities 

within the same source category, and assessed chronic exposure and risk for all 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 

where ICR data only contains annual emission totals.

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The average hourly emissions rate used for chronic risks modeling is defined as the total 

emissions for a year divided by the total number of operating hours in the year. If a source 

operated 8,760 hours per year this emissions rate would be appropriate for predicting potential 

acute impacts. However, many sources in this source sector emit on a more intermittent basis 

and thus specific hourly emissions may be higher than those utilized for annual or chronic 

risks modeling. While hourly emissions data for each source are not available, in this 

assessment, we utilized source category specific engineering judgment to determine what the 

peak hourly emissions for any given process could be. For processes in which no 

“engineering judgment” information was available we utilized a generic factor of ten times 

actual annual emissions to estimate peak hourly emissions In addition, for past RTR analyses, 

EPA developed a generic emissions adjustment factor of ten for acute screening which was 

based on engineering judgment. This factor of ten and tthe petroleum refinery specific factors 

along with the generic factor of ten are discussed in Appendix 3, (Analysis of data on shortterm emission rates relative to long-term emission rates) of this document. 

Census block elevations for HEM3 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. Elevations of polar grid points used in estimating short- and 

long-term ambient concentrations were assumed to be equal to the highest elevation of any 

census block falling within the polar grid sector corresponding to the grid point. If a sector 

does not contain any blocks, the model defaults the elevation to that of the nearest block. If 

an elevation is not provided for the emission source, the model uses the average elevation of 

all sectors within the innermost 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 1 of 

this document. 

2.3 Estimating chronic human inhalation exposure

We used the estimated annual average ambient air concentration of each HAP, at each census 

block centroid, as a surrogate for the lifetime inhalation exposure concentration of all the 

people who reside in the census block. That is, the risk 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, including indoor air concentrations, for two 

reasons. First, our experience with the 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 percent for particulate HAP; it will also reduce risk 

estimates for gaseous HAP, 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 

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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 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, we generally estimated three metrics; the maximum individual risk (MIR), which is 

defined as the risk associated with a lifetime of exposure at the highest concentration where 

people are likely to live; the population risk distribution; and the cancer incidence. The 

assumption of not considering short or long-term population mobility does not bias the 

estimate of the theoretical MIR (assumes a person stays in one location for 70 years) 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 increasing the estimated number 

of people at specific risk levels. 

When screening for potentially significant acute exposures, we used an estimate of the highest 

hourly ambient concentration at any off-site location as the surrogate for the maximum 

potential acute exposure concentration for any individual. This was generally the Fenceline.

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 approach to risk assessment was endorsed by the 

National Academy of Sciences in its 1993 publication “Science and Judgment in Risk 

Assessment” and subsequently was adopted in the EPA’s “Residual Risk Report to Congress” 

in 1999. 

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 potential 

acute health risks (i.e., it “screens out”), or that it requires further, more refined assessment. 

A more refined acute assessment could use industry- or site-specific data on the temporal 

pattern of emissions, the layout of emission points at the facility, the boundaries of the 

facility, and/or the local meteorology. In some cases, all of these site-specific data are used to 

refine the assessment; in others, lesser amounts of site-specific data can be used to determine 

that acute exposures are not a concern, and significant additional data collection is not 

necessary. 

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add to discussion.

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comment
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Acute health risk screening was performed for each facility as the first step. We used 

conservative assumptions for emission rates, meteorology, and exposure location. We used 

the following worst-case assumptions in our screening approach:

 Peak 1-hour emissions were obtained from the ICR and based on the operating 

characteristics of refinery emission sources as described in Appendix 3. 

 We assumed that the peak emissions 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 assumed to be located downwind at the point of maximum modeled 

impact during this same worst-case 1-hour period, but no nearer to the source than 100 

meters.

 The maximum impact was compared to multiple short-term health benchmarks for the 

HAP being assessed to determine if a possible acute health risk might exist. These 

benchmarks are described in section 2.6 of this report.

As mentioned above, when we identify acute impacts which exceed their relevant 

benchmarks, we pursue refining our acute screening estimates to the extent possible. 

In some cases, this may include the use of a facility-specific emissions multiplier to estimate 

the peak hourly emission rates from the average rates (rather than the default factor of 10). In 

other cases, this may entail determining the actual physical layout and boundaries of a facility 

to more accurately gauge where people might reasonably be exposed for an hour. 

For the petroleum refinery source category, the refinement included a review of the layout of 

the emission points at the facilities with the facility boundaries to determine the maximum 

off-site acute impact for the facilities that did not screen out during the initial run. We also 

used petroleum refinery specific factors, as described above. Refer to Appendices 5 and 6 for 

the detailed results for these sites. 

2.5 Multipathway human health and environmental risk analysis

The EPA conducted a screening analysis examining the potential for significant human health 

risks due to exposures via routes other than inhalation (i.e., ingestion). We first determined 

whether any sources in the source categories emitted any hazardous air pollutants known to be 

persistent and bio-accumulative in environment (PB-HAP)1. The PB-HAP compounds or 

compound classes are identified for the screening from the EPA’s Air Toxics Risk 

 

1 Although the two-letter chemical symbol for lead is Pb, in this assessment PB-HAP refers to the many air 

pollutants known to be persistent and bioaccumulative in the environment. In instances where the report is 

specifically referring to lead, it is spelled out (i.e., the two-letter chemical symbol for lead is not used in this 

document). 
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Assessment Library [8]. With respect to PB-HAP emissions other than lead, emissions were 

evaluated for potential non-inhalation risks impacts using a Tiered screening approach. We 

first determined whether the facility-specific emission rates of each of the emitted PB–HAP 

were large enough to create the potential for significant non-inhalation human health risks 

under reasonable worst-case conditions. To facilitate this step, we developed emissions rate 

thresholds for each PB–HAP using a hypothetical upper-end screening exposure scenario 

developed for use in conjunction with the EPA’s Total Risk Integrated Methodology. Fate, 

Transport, and Ecological Exposure (TRIM.FaTE[9]) model. We conducted a sensitivity 

analysis on the screening scenario to ensure that its key design parameters would represent the 

upper end of the range of possible values, such that it would represent a conservative but not 

impossible scenario. The facility-specific emissions rates of each of the PB–HAP were 

compared to the emission rate threshold values for each of the PB–HAP identified to assess 

the potential for significant human health risks via non-inhalation pathways. We call this 

application of the TRIM.FaTE model the Tier I TRIM- Screen.

For the purpose of developing emissions rates for our Tier I TRIM-Screen, we derived 

emission levels for each PB-HAP (other than lead) at which the maximum excess lifetime 

cancer risk would be 1-in-1 million or, for HAP that cause non-cancer health effects, the 

maximum HQ would be 1. If the emissions rate of any PB-HAP exceeds the Tier I screening 

emissions rate for any facility, we conduct a Tier II multi-pathway screen. In the Tier II 

screen, the location of each facility that exceeded the Tier I emission rate is used to refine the 

assumptions associated with the environmental scenario while maintaining the exposure 

scenario assumptions. We then adjust the risk-based Tier I screening level for each PB-HAP 

for each facility based on an understanding of how exposure concentrations estimated for the 

screening scenario change with meteorology and environmental assumptions. PB-HAP 

emissions that do not exceed these new Tier II screening levels are considered to pose no 

unacceptable risks. When facilities exceed the Tier II screening levels, it does not mean that 

multi-pathway impacts are significant, only that we cannot rule out that possibility based on 

the results of the screen. These facilities may be further evaluated for multi-pathway risks 

using the TRIM.FaTE model and more site specific information. Appendix 4 of this 

document (Technical Support Document for TRIM-Based Multipathway Tiered Screening 

Methodology for RTR) contains a complete discussion of the multipathway Tier I and II 

screening approach. A detailed discussion of the site specific multipathway approach is 

discussed in Appendix 10, “Technical Support Document: Human Health Multipathway 

Residual Risk Assessment for the Petroleum Refineries Sector –A Site Specific Analysis.”

In evaluating the potential multipathway risks from emissions of lead compounds, rather than 

developing a screening emission rate for them, we compared maximum estimated chronic 

atmospheric concentrations with the current National Ambient Air Quality Standard 

(NAAQS) for lead. Values below the NAAQS were considered to have a low potential for 

multipathway risks of any significance.

The NAAQS value, a public health policy judgment, incorporated the Agency’s most recent 

health evaluation of air effects of lead exposure for the purposes of setting a national ambient 

air quality standard. In setting this value, the Administrator promulgated a standard that was 

requisite to protect public health with an adequate margin of safety. We consider values 

below the level of the primary NAAQS to protect against multipathway risks because as 
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mentioned above, the primary NAAQS is set as to protect public health with an adequate 

margin of safety. However, ambient air lead concentrations above the NAAQS are 

considered to pose the potential for increased risk to public health. We consider this NAAQS 

assessment to be a refined analysis given: 1) the numerous health studies, detailed risk and 

exposure analyses, and level of external peer and public review that went into the 

development of the primary NAAQS for lead, combined with: 2) the site-specific dispersion 

modeling used in this assessment to estimated ambient lead concentrations due to the source 

category emissions. It should be noted, however, that this comparison does not account for 

possible population exposures to lead from sources other than the one being modeled; for 

example, via consumption of water from untreated local sources or ingestion of locally grown 

food. Nevertheless, the Administrator judged that such a standard would protect, with an 

adequate margin of safety, the health of children and other at-risk populations against an array 

of adverse health effects, most notably including neurological effects, particularly 

neurobehavioral and neurocognitive effects, in children (73 FR 67007). The Administrator, in 

setting the standard, also recognized that no evidence-or risk based bright line indicated a 

single appropriate level. Instead a collection of scientific evidence and other information was 

used to select the standard from a range of reasonable values (73 FR 67006).

We further note that comparing ambient lead concentrations to the NAAQS for lead, 

considering the level, averaging time, form and indicator, also informs whether there is the 

potential for adverse environmental effects. This is because the secondary lead NAAQS, set 

to protect against adverse welfare effects (including adverse environmental effects), has the 

same averaging time, form, and level as the primary standard. Thus, ambient lead 

concentrations above the NAAQS for lead also indicate the potential for adverse 

environmental effects.

Adverse environmental effects

The EPA has developed a screening approach to examine the potential for adverse 

environmental effects as required under section 112(f)(2)(A) of the CAA. The environmental 

screen focuses on the following seven environmental HAP: 

 Five persistent bioaccumulative HAP (PB-HAP) – cadmium, dioxins/furans, 

polycyclic organic matter (POM), mercury (both inorganic mercury and 

methyl mercury) and lead.

 Two acid gases - hydrogen chloride (HCl), and hydrogen fluoride (HF). 

HAP that persist and bioaccumulate are of particular environmental concern because they 

accumulate in the soil, sediment and water. The acid gases, HCl and HF, were included due to 

their well-documented potential to cause direct damage to terrestrial plants.

For the environmental risk screening analysis, EPA first determined whether any facilities in 

the source category emitted any of the seven environmental HAP. If one or more of the seven 

environmental HAP evaluated are emitted by at least one facility in the source category we 

proceed to the second step of the evaluation.
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For cadmium, mercury, POM and dioxins/furans, the environmental screening analysis 

consists of two tiers. In the first tier, TRIM.FaTE modeling was conducted under worst-cast 

environmental conditionals to determine whether the facility-specific off-site emission rates 

of each of the emitted environmental HAP exceeded ecological benchmarks represented as 

emissions threshold values. If off-site emissions from a facility do not exceed the Tier I

thresholds the facility “passes” the screen, and therefore, is not evaluated further under the 

screening approach. If off-site emissions from a facility exceed the Tier I thresholds, we 

evaluate the facility further in Tier II.

In Tier II of the environmental screening analysis, the screening emission thresholds are 

adjusted to account for local meteorology and the actual location of lakes in the vicinity of 

facilities that did not pass the Tier I screen. If off-site emissions from a facility do not exceed 

the Tier II thresholds, the facility passes the screen, and is typically not evaluated further. If 

off-site emissions from a facility exceed the Tier II thresholds, the facility does not pass the 

screen and, therefore, may have the potential to cause adverse environmental effects. Such 

facilities are evaluated further to investigate factors such as the magnitude and characteristics 

of the area of exceedance. 

For acid gases, the environmental screening analysis evaluates the potential phytotoxicity and 

reduced productivity of plants due to chronic exposure to acid gases. The environmental risk 

screening methodology for acid gases is a single-tier screen that compares the average off-site 

ambient air concentration over the modeling domain to ecological benchmarks for each of the 

acid gases. For purposes of ecological risk screening, EPA identifies a potential for adverse 

environmental effects to plant communities from exposure to acid gases when the average 

concentration of the HAP around a facility exceeds the LOAEL ecological benchmark. In 

such cases, we further investigate factors such as the magnitude and characteristics of the area 

of exceedance (e.g., land use of exceedance area, size of exceedance area) to determine if 

there is an adverse environmental effect. 

For lead compounds, we currently do not have the ability to calculate media concentrations 

using the TRIM.FaTE model. However, air concentrations of lead are already calculated as 

part of the human health exposure and risk analysis using the HEM-3 AERMOD air 

dispersion model. To evaluate the potential for adverse environmental effects from lead, we 

compare the average modeled air emission concentrations of lead from each facility in the 

source category emissions to the level of the secondary National Ambient Air Quality 

Standard (NAAQS) for lead. The secondary lead NAAQS is a reasonable means of evaluating 

environmental risk because it is set to provide substantial protection against adverse welfare 

effects which can include “effects on soils, water, crops, vegetation, man-made materials, 

animals, wildlife, weather, visibility and climate, damage to and deterioration of property, and 

hazards to transportation, as well as effects on economic values and on personal comfort and 

well-being.”2

 

2 A secondary standard, as defined in Section 109(b)(2), must “specify a level of air quality the attainment and 

maintenance of which, in the judgment of the Administrator, based on criteria, is requisite to protect the public 

welfare from any known or anticipated adverse effects associated with the presence of [the] pollutant in the 

ambient air.” Welfare effects as defined in section 302(h) (42 U.S.C. 7602(h)) include, but are not limited to, 

“effects on soils, water, crops, vegetation, man-made materials, animals, wildlife, weather, visibility and climate, 
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Ecological benchmarks included in the environmental risk screen are presented in Appendix 

11.

2.6 Dose-response assessment

2.6.1 Sources of chronic dose-response information 

Dose-response assessment (carcinogenic and non-carcinogenic) for chronic exposure (either 

by inhalation or ingestion) for the HAP reported in the emissions inventory for the petroleum 

refinery source sector were based on the EPA Office of Air Quality Planning and Standards’ 

(OAQPS) existing recommendations for HAP [10], also used for NATA [11]. This 

information has been obtained from various sources 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 dose-response 

assessments for chronic exposure for many of the pollutants in this study. These 

assessments typically provide a qualitative statement regarding the strength of scientific 

data and specify a reference concentration (RfC, for inhalation) or reference dose (RfD, 

for ingestion) to protect against effects other than cancer and/or a unit risk estimate (URE, 

for inhalation) or slope factor (SF, for ingestion) to estimate the probability of developing 

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

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

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

during a lifetime.” The RfD is “an estimate (with uncertainty spanning perhaps an order 

of magnitude) of a daily oral exposure to the human population (including sensitive 

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

lifetime.” The URE is defined as “the upper-bound excess cancer risk estimated to result 

from continuous lifetime exposure to an agent at a concentration of 1 μg/m3in air.” The 

SF is “an upper bound, approximating a 95 percent confidence limit, on the increased 

cancer risk from a lifetime exposure to an agent. This estimate, [is] usually expressed in 

units of proportion (of a population) affected per mg/kg-day...” EPA disseminates doseresponse assessment information in several forms, based on the level of review. The 

Integrated Risk Information System (IRIS) [12] is an EPA database that contains scientific 

health assessment information, including dose-response 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. 

EPA’s science policy approach, under the current carcinogen guidelines, is to use linear 

low-dose extrapolation as a default option for carcinogens for which the mode of action 

(MOA) has not been identified. We expect future EPA dose-response assessments to 

 

damage to and deterioration of property, and hazards to transportation, as well as effects on economic values and 

on personal comfort and well-being.”

Commented [TP7]: Added Appendix 11 as per 

OMB comments
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identify nonlinear MOAs where appropriate, and we will use those analyses (once they are 

peer reviewed) in our risk assessments. At this time, however, there are no available 

carcinogen dose-response assessments for inhalation exposure that are based on a 

nonlinear MOA.

2) US Agency for Toxic Substances and Disease Registry (ATSDR). ATSDR, which is part 

of the US Department of Health and Human Services, develops and publishes Minimum 

Risk Levels (MRLs) [13] for inhalation and oral exposure to many toxic substances. As 

stated on the ATSDR web site: “Following discussions with scientists within the 

Department of Health and Human Services (HHS) and the EPA, ATSDR chose to adopt a 

practice similar to that of the EPA's Reference Dose (RfD) and Reference Concentration 

(RfC) for deriving substance specific health guidance levels for non neoplastic endpoints.” 

The MRL is defined as “an estimate of daily human exposure to a substance that is likely 

to be without an appreciable risk of adverse effects (other than cancer) over a specified 

duration of exposure.” ATSDR describes MRLs as substance-specific estimates to be 

used by health assessors to select environmental contaminants for further evaluation. 

Exposures above an MRL do not necessarily represent a threat, and MRLs are therefore 

not intended for use as predictors of adverse health effects or for setting cleanup levels.

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

Environmental Health Hazard Assessment has developed dose-response assessments for 

many substances, based both on 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 assessments [14]: “The 

guidelines for developing chronic inhalation exposure levels incorporate many 

recommendations of the U.S. EPA [15] and NAS [16].” The non-cancer information 

includes available inhalation health risk guidance values expressed as chronic inhalation 

reference exposure levels (RELs) [17]. CalEPA defines the REL as “the concentration 

level at or below which no health effects are anticipated in the general human population.” 

CalEPA's quantitative dose-response information on carcinogenicity by inhalation 

exposure is expressed in terms of the URE [18], defined similarly to EPA's URE. 

 

In developing chronic risk estimates, we adjusted dose-response values for some HAP based 

on professional judgment, as follows: 

1) In the case of nickel compounds, to provide a health-protective estimate of potential 

cancer risks, we used the IRIS URE for nickel subsulfide in this assessment. Based on 

past scientific and technical considerations, the determination of the percent of nickel 

subsulfide was considered a major factor for estimating the extent and magnitude of the 

risks of cancer due to nickel-containing emissions. Nickel speciation information for 

some of the largest nickel-emitting sources (including oil combustion, coal combustion, 

and others) suggested that at least 35 percent of total nickel emissions may be soluble 

compounds and that the URE for the mixture of inhaled nickel compounds (based on 

nickel subsulfide, and representative of pure insoluble crystalline nickel) could be derived 

to reflect the assumption that 65 percent of the total mass of nickel may be carcinogenic. 
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Based on consistent views of major scientific bodies (i.e., National Toxicology Program 

(NTP) in their 12th Report of the Carcinogens (ROC) [19], International Agency for 

Research on Cancer (IARC) [20], and other international agencies) [21] that consider all 

nickel compounds to be carcinogenic, we currently consider all nickel compounds to have 

the potential of being carcinogenic to humans. The 12th Report of the Carcinogens states 

that the “combined results of epidemiological studies, mechanistic studies, and 

carcinogenic studies in rodents support the concept that nickel compounds generate nickel 

ions in target cells at sites critical for carcinogenesis, thus allowing consideration and 

evaluation of these compounds as a single group.” Although the precise nickel compound 

(or compounds) responsible for the carcinogenic effects in humans is not always clear, 

studies indicate that nickel sulfate and the combinations of nickel sulfides and oxides 

encountered in the nickel refining industries cause cancer in humans (these studies are 

summarized in a review by Grimsrud et al., 2010 [22]). The major scientific bodies 

mentioned above have also recognized that there are differences in toxicity and/or 

carcinogenic potential across the different nickel compounds. In this inhalation risk 

assessment, to take a conservative approach, we have considered all nickel compounds to 

be as carcinogenic as nickel subsulfide and have applied the IRIS URE for nickel 

subsulfide without a factor to reflect the assumption that 100 percent of the total mass of 

nickel may be as carcinogenic as pure nickel subsulfide. In addition, given that there are 

two additional URE values3derived for exposure to mixtures of nickel compounds, as a 

group, that are 2-3 fold lower than the IRIS URE for nickel subsulfide, the EPA also 

considers it reasonable to use a value that is 50 percent of the IRIS URE for nickel 

subsulfide for providing an estimate of the lower end of the plausible range of cancer 

potency values for different mixtures of nickel compounds. 

2) Where possible for emissions of unspecified mixtures of HAP categories such as metal 

compounds and POM, we apply category-specific chemical speciation profiles appropriate 

to the source category to develop a composite dose-response value for the category. 

3) Where POM emissions were not speciated into individual compounds, we applied the 

same simplifying assumptions to assessments that are used in NATA [23]. The NATA 

approach partitions POM into eight different non-overlapping “groups” that are modeled 

as separate pollutants. Each POM group comprises POM species of similar carcinogenic 

potency, for which we can apply the same URE.

4) In the case of HAP categories such as glycol ethers and cyanide compounds, the most 

conservative dose-response value of the chemical category is used as a surrogate for other 

compounds in the group for which dose-response values are not available. This is done in 

order to examine, under conservative assumptions, whether these HAP that lack doseresponse values may pose an unacceptable risk and require further examination, or screen 

out from further assessment. 

 

3

 Two UREs (other than the current IRIS values) have been derived for nickel compounds as a group: one 

developed by the California Department of Health Services 

(http://www.arb.ca.gov/toxics/id/summary/nickel_tech_b.pdf) and the other by the Texas Commission on 

Environmental Quality (http://www.epa.gov/ttn/atw/nata1999/99pdfs/healtheffectsinfo.pdf).

Commented [TP8]: In response to OMB 

Comment:

The approaches and rationale for the technical and 

scientific considerations used to derive inhalation 

cancer risks of emissions of nickel and the views of 

expert independent reviewers on EPA’s approach can 

be found at 

http://cfpub.epa.gov/si/si_public_record_report.cfm?d

irEntryId=238881. In brief, EPA’s current approach 

is to use 100 percent of the current IRIS URE for 

nickel subsulfide (rather than assuming that 65 

percent of the total mass of emitted nickel might be of 

nickel subsulfide, as used in previous analyses) to 

reflect the potential carcinogenicity of all forms of 

nickel. The EPA also recognized that there are 

potential differences in toxicity and thus carcinogenic 

potential across the different nickel compounds, and 

given that there have been two URE values derived 

for exposure to mixtures of nickel compounds that are 

2-3 fold lower than the IRIS URE for nickel 

subsulfide, the EPA also considers it reasonable to 

use a value that is 50 percent of the IRIS URE for 

nickel subsulfide for providing an estimate of the 

lower end of a plausible range of cancer potency 

values for different mixtures of nickel compounds.

Although the review focused primarily on cancer 

risks associated with emissions containing nickel 

compounds, it is important to note that comparative 

quantitative analyses across nickel compounds have 

shown that nickel sulfate is as toxic or more toxic 

than nickel subsulfide or nickel oxide which does not 

support the notion that the solubility of nickel 

compounds is a strong determinant of its toxicity.

1,2

 

It is important to add that nickel is not a driver of 

carcinogenic risk in the current assessment, and 

therefore we do not present a range of cancer potency 

for this chemical.

1 Haber LT, Allen BC, Kimmel CA. Non-Cancer Risk 

Assessment for Nickel Compounds: Issues Associated 

with Dose-Response Modeling of Inhalation and Oral 

Exposures. Toxicol Sci. 1998. 43:213-229.

National Toxicology Program, Technical Report Series 

No. 454, Toxicology and carcinogenesis studies of 

nickel sulfate hexahydrate. Available online at 

http://ntp.niehs.nih.gov/ntp/htdocs/LT_rpts/tr454.pdf.

1 National Toxicology Program, Technical Report 

Series No. 454, Toxicology and carcinogenesis studies 

of nickel sulfate hexahydrate. Available online at 

http://ntp.niehs.nih.gov/ntp/htdocs/LT_rpts/tr454.pdf.
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5) In 2004, the EPA determined that the Chemical Industry Institute of Toxicology (CIIT) 

cancer dose-response value for formaldehyde (5.5 x 10-9per μg/m3) was based on better 

science than the IRIS cancer dose-response value (1.3 x 10-5per μg/m3), and we switched 

from using the IRIS value to the CIIT value in risk assessments supporting regulatory 

actions. Subsequent research published by EPA suggests that the CIIT model was not 

appropriate and, in 2010, EPA returned to using the 1991 IRIS value. The EPA has been 

working on revising the formaldehyde IRIS assessment and the National Academy of 

Sciences (NAS) completed its review of the EPA’s draft assessment in April of 20114 The 

EPA will follow the NAS Report recommendations and will present results obtained by 

implementing the biologically-based dose-response (BBDR) model for formaldehyde. The 

EPA will compare these estimates with those currently presented in the External Review 

draft of the assessment and will discuss their strengths and weaknesses. As recommended 

by the NAS committee, appropriate sensitivity and uncertainty analyses will be an integral 

component of implementing the BBDR model. In the interim, we will present findings 

using the 1991 IRIS value as a primary estimate; EPA may also consider other information 

as the science evolves. 

6) A chronic screening level of 163 μg/m3 was developed by EPA for carbonyl sulfide 

(COS) from a No Observed Adverse Effects Level (NOAEL) of 200 ppm based on brain 

lesions and neurophysiological alterations in rodents. A more detailed discussion of the 

studies used to develop the COS chronic screening level is provided in Appendix 8 of this 

document (Development of the Chronic Screening Level for Carbonyl Sulfide). The 

screening level includes a total uncertainty factor (UF) of 3,000: 10 times for 

extrapolation for interspecies differences, 10 times for consideration of intraspecies 

variability, 10 times for extrapolation from subchronic to chronic duration, and 3 times for 

database insufficiencies. See Section 5 of this document for a detailed discussion of 

exposure modeling uncertainties. 

The emissions inventory for the petroleum refinery source sector includes emissions of 135 

HAP with available chronic quantitative inhalation dose-response values. Of these, 69 are 

classified as known, probably, or possible carcinogens, with quantitative cancer dose-response 

values available. These 69 HAP, their quantitative inhalation chronic cancer dose-response 

values, and the source of each value are listed in Table 2.6-1.A. The 14 compounds with 

chronic oral cancer dose-response values available (for which multipathway screening 

assessments were performed) are listed in Table 2.6-1.B. Ninety-five HAP have quantitative 

inhalation chronic noncancer threshold values available; 7 of these 95 HAP, for which a 

multipathway assessment was performed, also have quantitative oral chronic noncancer 

threshold values available. These 95 HAP, their threshold values, and the source of the value 

are listed in Table 2.6-2.A and Table 2.6-2.B. 

 

4

 http://www.nap.edu/catalog.php?record_id=13142

Commented [TP9]: OMB asked if this was peer 

reviewed. 

Response: While this value itself was not peer 

reviewed the underlying data has been peer reviewed. 

The SAB did suggest that we use the best available 

science in our risks characterization. ORD believes 

this is the best available science and thus it is 

appropriate to use as a screening level.
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Table 2.6-1 (A) Dose-Response Values for 

Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer)5 = cancer risk per μg/m3 of average lifetime exposure. 

Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of Research & 

Development, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California 

EPA Office of Environmental Health Hazard Assessment. HEAST = EPA Health Effects 

Assessment Tables.

Pollutant CAS Number6 URE5

(1/μg/m3)

Source

1,1,2,2-Tetrachloroethane 79345 5.8E-05 IRISCAL

1,1,2-Trichloroethane 79005 1.6E-05 IRIS

1,3-Butadiene 106990 3.0E-05 IRIS

1,3-Dichloropropene 542756 4.0E-06 IRIS

1,4-Dichlorobenzene 106467 1.1E-05 CAL

2-Nitroproprane 79469 5.6E-06 EPA OAQPS7

Acetaldehyde 75070 2.2E-06 IRIS

Acrylamide 79061 1.6E-04 IRIS

Acrylonitrile 107131 6.8E-05 IRIS

Aniline 62533 1.6E-06 CAL

Arsenic 7440382 4.3E-03 IRIS

Benzene8

71432 7.8E-06 IRIS

Benzidine 92875 0.1072 IRIS

Beryllium 7440417 2.4E-03 IRIS

Bis(2-Ethylhexyl)Phthalate 117817 2.4E-06 CAL

Cadmium 7440439 1.8E-03 IRIS

Chromium (VI) 18540299 1.2E-02 IRIS

Dioxins/Furans:9

1,2,3,4,6,7,8-

Heptachlorodibenzofuran 67562394 3.3E-01 EPA ORD

1,2,3,4,6,7,8-Heptachlorodibenzop-dDioxin 35822469 3.3E-01 EPA ORD

1,2,3,4,7,8,9-

Heptachlorodibenzofuran 55673897 3.3E-01 EPA ORD

1,2,3,4,7,8- 70648269 3.3E+00 EPA ORD

 

5 The URE is the upper-bound excess cancer risk estimated to result from continuous lifetime exposure to an 

agent at a concentration of 1 μg/m3in air. URE’s are considered upper bound estimates meaning they represent 

a plausible upper limit to the true value. 

6 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have 

used a surrogate 3-digit identifier corresponding to the group’s position on the CAA list of HAP.

7 URE of 5.6 x 10-6 per ug/m3

for 2-nitropropane. This value was derived in 1999

by the Health Council of the Netherlands (available at: http://www.gr.nl/sites/default/files/OSH@13.PDF), based 

on induction of hepatocellular nodules in rats, and is consistent with weight-of-evidence determinations by the 

U.S. National Toxicology Program (“reasonably anticipated to be a human carcinogen”) and the IARC 

(“possibly carcinogenic to humans”).

8 The EPA IRIS assessment for benzene provides a range of plausible UREs. This assessment used the highest 

value in that range, 7.8E-06 per ug/m3. The low end of the range is 2.2E-06 per ug/m3.

9 Dioxins/Furans URE based on 2005 WHO evaluation of TEF 

(http://www.who.int/foodsafety/chem/tef_update/en/); URE=Group URE x TEF; RfC = 2,3,7,8-TCDD 

RfC/TEF

Formatted: Superscript
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Table 2.6-1 (A) Dose-Response Values for 

Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer)5 = cancer risk per μg/m3 of average lifetime exposure. 

Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of Research & 

Development, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California 

EPA Office of Environmental Health Hazard Assessment. HEAST = EPA Health Effects 

Assessment Tables.

Pollutant CAS Number6 URE5

(1/μg/m3)

Source

Hexachlorodibenzofuran

1,2,3,4,7,8-Hexachlorodibenzo-pdDioxin 39227286 3.3E+00 EPA ORD

1,2,3,6,7,8-

Hexachlorodibenzofuran 57117449 3.3E+00 EPA ORD

1,2,3,6,7,8-Hexachlorodibenzo-pdDioxin 57653857 3.3E+00 EPA ORD

1,2,3,7,8,9-

Hexachlorodibenzofuran 72918219 3.3E+00 EPA ORD

1,2,3,7,8,9-Hexachlorodibenzo-pdDioxin 19408743 3.3E+00 EPA ORD

1,2,3,7,8-

Pentachlorodibenzofuran 57117416 9.9E-01 EPA ORD

1,2,3,7,8-Pentachlorodibenzo-pdDioxin 40321764 3.3E+01 EPA ORD

2,3,4,6,7,8-

Hexachlorodibenzofuran 60851345 3.3E+00 EPA ORD

2,3,4,7,8-

Pentachlorodibenzofuran 57117314 9.9E+00 EPA ORD

2,3,7,8-Tetrachlorodibenzofuran 51207319 3.3E+00 EPA ORD

2,3,7,8-Tetrachlorodibenzo-pdDioxin 1746016 3.3E+01 EPA ORD

1,2,3,4,6,7,8,9-

Octochlorodibenzofuran 39001020 9.9E-03 EPA ORD

1,2,3,4,6,7,8,9-Octohlorodibenzop-dDioxin 3268879 9.9E-03 EPA ORD

Ethyl Benzene 100414 2.5E-06 CAL

Ethylene Dibromide 106934 6.0E-04 IRIS

Ethylene Dichloride 107062 2.6E-05 IRIS10

Ethylene Oxide 75218 8.8E-05 CAL

Ethylidene Dichloride (1,1-

Dichloroethane) 75343 1.6E-06 CAL

Formaldehyde11 50000 1.3E-05 IRIS

Methyl Tert-Butyl Ether 1634044 2.6E-07 CAL

Methylene Chloride 75092 1.3E-07 IRIS

Naphthalene 91203 3.4E-05 CAL

Nickel 7440020 4.8E-04 EPA OAQPS12

 

10 The EPA IRIS assessment for ethylene dibromide provides a range of plausible UREs. This assessment used 

the highest value in that range, 6.0E-04 per ug/m3. The low end of the range is equal to 50% of the URE for 

ethylene dibromide is 3.0E-04 per ug/m3.

11 The EPA has used the CIIT value (5.5x10-9 per mg/m3

) to characterize formaldehyde cancer risks in some 

instances. 
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Table 2.6-1 (A) Dose-Response Values for 

Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer)5 = cancer risk per μg/m3 of average lifetime exposure. 

Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of Research & 

Development, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California 

EPA Office of Environmental Health Hazard Assessment. HEAST = EPA Health Effects 

Assessment Tables.

Pollutant CAS Number6 URE5

(1/μg/m3)

Source

Nickel Oxide 1313991 4.8E-04 EPA OAQPS9

Polychlorinated Biphenyls 1336363 1.0E-04 IRIS

Polycyclic Organic Matter

13:

14

1-Methylnaphthalene 90120 8.8E-05 CAL

2-Methylnaphthalene 91576 8.8E-05 CAL

3-Methylcholanthrene 56495 1.008E-02 CAL

7,12-Dimethylbenz[a]aAnthracene 57976 1.136E-01 CAL

Acenaphthene 83329 8.8E-05 CAL

Acenaphthylene 208968 8.8E-05 CAL

Benz[a]aAnthracene 56553 1.76E-04 CAL

Benzo[a]pPyrene 50328 1.76E-03 CAL

Benzo[b]fFluoranthene 205992 1.76E-04 CAL

Benzo[e]pPyrene 192972 8.8E-05 CAL

Benzo[g,h,i,]pPerylene 191242 8.8E-05 CAL

Benzo[k]fFluoranthene 207089 1.76E-04 CAL

Chrysene 218019 1.76E-05 CAL

Dibenzo[a,h]aAnthracene 53703 1.918E-03 CAL

Dibenzo[a,i]pPyrene 189559 1.76E-02 CAL

Dibenz[a,j]aAcridine 224420 1.76E-04 CAL

Fluoranthene 206440 8.8E-05 CAL

Fluorene 86737 8.8E-05 CAL

Indeno[1,2,3-c,d]pPyrene 193395 1.76E-04 CAL

Perylene 198550 8.8E-05 CAL

POM72002 - 8.8E-05 CAL,OAQPS15,

Tetrachloroethene 127184 2.6E-07 IRIS

Trichloroethylene 79016 4.8E-06 IRIS

Vinyl Bromide 593602 3.2E-05 HEAST

Vinyl Chloride 75014 8.8E-06 IRIS

 

12 The EPA IRIS assessments for nickel compounds provide a range of plausible UREs. This assessment used 

the highest value in that range which is equal to the URE for nickel subsulfide, 4.8E-04 per ug/m3. The low end 

of the range is equal to 50% of the URE for nickel subsulfide, 2.4E-04 per ug/m3.

13 POM without a chemical-specific URE are assigned a URE associated with a mixture of POM compounds 

having a similar characteristics. Details of this method, also used in the National Air Toxics Assessments, are 

available at http://www.epa.gov/ttn/atw/nata2005/methods.html#pom

14 All POM act by a mutagenic mode-of-action, therefore the UREs have been adjusted by a factor of 1.6 (see 

section 2.7.1 for more details).

15 POM72002 represents unspecified POM. For more information on this group and the assigned URE see 

http://www.epa.gov/ttn/atw/nata1999/99pdfs/pomapproachjan.pdf

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Table 2.6-1 (B) Dose-Response Values for Chronic Oral Exposure to Carcinogens

SF (oral slope factor for cancer) = cancer risk per mg/kg/d of average lifetime exposure. Sources: IRIS 

= EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Health 

Hazard Assessment, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number16

SF

(1/mg/kg/d) Source

Dioxin/Furans:

 Hexachlorodibenzo-p-dioxin 19408743 6200 IRIS

 2,3,7,8-Tetrachlorodibenzo-p-dioxin 1746016 150000 EPA ORD

Polychlorinated biphenyls 1336363 2 IRIS

Polycyclic Organic Matter:

 3-Methlycholanthrene 56495 22 CAL

 7,12-Dimethylbenz(a)anthracene 57976 250 CAL

Benz[a]Anthracene 56553 1.2 CAL

Benzo[a]Pyrene 50328 7.3 IRIS

Benzo[b]Fluoranthene 205992 1.2 CAL

Benzo[k]Fluoranthene 207089 1.2 CAL

Chrysene 218019 0.12 CAL

Dibenzo[a,h]Anthracene 53703 4.1 CAL

 Dibenzo(a,i)pyrene 189559 120 CAL

 Dibenz(a,j)acridine 224420 1.2 CAL

Indeno[1,2,3-c,d]Pyrene 193395 1.2 CAL

Table 2.6-2 (A) 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, ATSDR = US Agency for Toxic Substances Disease 

Registry, HEAST = EPA Health Effects Assessment Tables, EPA OAQPS = EPA Office of Air Quality 

Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number6 RfC 

(mg/m3)

Source17

1,1,2-Trichloroethane 79005 0.4 CAL

1,3-Butadiene 106990 0.002 IRIS - M

1,3-Dichloropropene 542756 0.02 IRIS - H

1,4-Dichlorobenzene 106467 0.8 IRIS - M

2-Nitroproprane 79469 0.02 IRIS - L

Acetaldehyde 75070 0.009 IRIS - L

Acetonitrile 75058 0.06 IRIS - M

Acrolein 107028 0.00002 IRIS - M

Acrylamide 79061 0.006 IRIS - M

 

16 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we 

have used a surrogate 3-digit identifier corresponding to the group’s position on the CAA list of HAP.

17 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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Table 2.6-2 (A) 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, ATSDR = US Agency for Toxic Substances Disease 

Registry, HEAST = EPA Health Effects Assessment Tables, EPA OAQPS = EPA Office of Air Quality 

Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number6 RfC 

(mg/m3)

Source17

Acrylonitrile 107131 0.002 IRIS - M

Aniline 62533 0.001 IRIS - L

Antimony 7440360 0.0002 IRIS - L

Arsenic 7440382 0.000015 CAL

Benzene 71432 0.03 IRIS - M

Beryllium 7440417 0.00002 IRIS - M

Bis(2-Ethylhexyl)Phthalate 117817 0.01 CAL

Cadmium 7440439 0.00001 ATSDR

Carbon Disulfide 75150 0.7 IRIS - M

Carbonyl Sulfide 463581 0.163 EPA ORD18

Chlorine 7782505 0.00015 ATSDR

Chlorobenzene 108907 1 CAL

Chloroform 67663 0.098 ATSDR

Chromium (VI) 18540299 0.0001 IRIS - M

Cobalt 7440484 0.0001 ATSDR

Cobalt Oxide 1307966 0.0001 ATSDR

Cresols (mixed) 1319773 0.6 CAL

m-Cresol 108394 0.6 CAL

o-Cresol 95487 0.6 CAL

p-Cresol 106445 0.6 CAL

Cumene 98828 0.4 IRIS - M

Hydrogen Cyanide 74908 0.0008 IRIS – L/M

Diethanolamine 111422 0.003 CAL

Dioxin/Furans:

1,2,3,4,6,7,8-Heptachlorodibenzofuran 67562394 0.000004 CAL

1,2,3,4,6,7,8-Heptachlorodibenzo-p-Dioxin 35822469 0.000004 CAL

1,2,3,4,7,8,9-Heptachlorodibenzofuran 55673897 0.000004 CAL

1,2,3,4,7,8-Hexachlorodibenzofuran 70648269 0.0000004 CAL

1,2,3,4,7,8-Hexachlorodibenzo-p-Dioxin 39227286 0.0000004 CAL

1,2,3,6,7,8-Hexachlorodibenzofuran 57117449 0.0000004 CAL

1,2,3,6,7,8-Hexachlorodibenzo-p-Dioxin 57653857 0.0000004 CAL

1,2,3,7,8,9-Hexachlorodibenzofuran 72918219 0.0000004 CAL

1,2,3,7,8,9-Hexachlorodibenzo-p-Dioxin 19408743 0.0000004 CAL

1,2,3,7,8-Pentachlorodibenzofuran 57117416 0.0000013 CAL

1,2,3,7,8-Pentachlorodibenzo-p-Dioxin 40321764 0.00000004 CAL

 

18 A chronic screening level of 0.163 mg/m3 was developed for carbonyl sulfide by EPA ORD from a No 

Observed Adverse Effects Level of 200 ppm based on brain lesions and neurophysiological alteration in rodents.
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Table 2.6-2 (A) 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, ATSDR = US Agency for Toxic Substances Disease 

Registry, HEAST = EPA Health Effects Assessment Tables, EPA OAQPS = EPA Office of Air Quality 

Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number6 RfC 

(mg/m3)

Source17

2,3,4,6,7,8-Hexachlorodibenzofuran 60851345 0.0000004 CAL

2,3,4,7,8-Pentachlorodibenzofuran 57117314 0.00000013 CAL

2,3,7,8-Tetrachlorodibenzofuran 51207319 0.0000004 CAL

2,3,7,8-Tetrachlorodibenzo-p-Dioxin 1746016 0.00000004 CAL

1,2,3,4,6,7,8,9-Octochlorodibenzofuran 39001020 0.00013 CAL

1,2,3,4,6,7,8,9-Octochlorodibenzo-p-Dioxin 3268879 0.00013 CAL

Ethyl Chloride 75003 10 IRIS - M

Ethyl Benzene 100414 1 IRIS - L

Ethylene Dibromide 106934 0.009 IRIS - M

Ethylene Dichloride 107062 2.4 ATSDR

Ethylene Glycol 107211 0.4 CAL

Ethylene Oxide 75218 0.03 CAL

Ethylidene Dichloride (1,1-Dichloroethane) 75343 0.5 HEAST

Formaldehyde 50000 0.0098 ATSDR

Diethylene Glycol Monomethyl Ether 111773 0.02 IRIS - M

Hexachloroethane 67721 0.03 IRIS – L

Hexane 110543 0.7 IRIS – M

Hydrochloric Acid 7647010 0.02 IRIS – L

Hydrofluoric Acid 7664393 0.014 CAL

Lead 7439921 0.00015 EPA OAQPS

Manganese 7439965 0.0003 ATSDR

Elemental Gaseous Mercury 201 0.0003 IRIS - M

Gaseous Divalent Mercury 184 0.0003 IRIS – M

Mercuric Chloride 7487947 0.0003 IRIS – M

Mercury (elemental) 7439976 0.0003 IRIS – M

Mercuric Oxide 21908532 0.0003 IRIS - M

Particulate Divalent Mercury 202 0.0003 IRIS - M

Methanol 67561 4 CAL

Methyl Bromide 74839 0.005 IRIS - H

Methyl Chloride 74873 0.09 IRIS - M

Methyl Isobutyl Ketone 108101 3 IRIS - L/M

Methyl Tert-Butyl Ether 1634044 3 IRIS - M

Methylene Chloride 75092 1 ATSDR

Dimethyl formamide 68122 0.03 IRIS - M

Naphthalene 91203 0.003 IRIS - M

Nickel 7440020 0.00009 ATSDR

Nickel Oxide 1313991 0.00002 CAL
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Table 2.6-2 (A) 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, ATSDR = US Agency for Toxic Substances Disease 

Registry, HEAST = EPA Health Effects Assessment Tables, EPA OAQPS = EPA Office of Air Quality 

Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number6 RfC 

(mg/m3)

Source17

Phenol 108952 0.2 CAL

Propionaldehyde 123386 0.008 IRIS – L/M

Selenium 7782492 0.02 CAL

Styrene 100425 1 IRIS - M

Tetrachloroethene 127184 0.04 IRIS – M

Toluene 108883 5 IRIS - H

Trichloroethylene 79016 0.002 IRIS - H

Triethylamine 121448 0.007 IRIS - L

Vinyl Bromide 593602 0.003 IRIS - H

Vinyl Chloride 75014 0.1 IRIS - M

Vinylidene Chloride 75354 0.2 IRIS – H/M

Xylenes (mixed) 1330207 0.1 IRIS - M

m-Xylene 108383 0.1 IRIS - M

o-Xylene 95476 0.1 IRIS - M

p-Xylene 106423 0.1 IRIS - M
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Table 2.6-2 (B) Dose-Response Values for Chronic Oral Exposure to Noncarcinogens

RfD (reference dose) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a 

continuous oral 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, ATSDR = US Agency for Toxic Substances and 

Disease Registry

Pollutant CAS Number

RfD

(mg/kg/d) Source 19

Cadmium compounds 7440439 0.0005 IRIS - H

Mercuric chloride20 7439976 0.0003 IRIS - H

Polycyclic Organic Matter (POM)

 Anthracene 120127 0.3 IRIS - L

 Fluoranthene 206440 0.04 IRIS - L

 1-Methylnaphthalene 90120 0.07 ATSDR

 2-Methylnaphthalene 91576 0.04 ATSDR

2,3,7,8-Tetrachlorodibenzo-p-dioxin 1746016 0.0000000007 IRIS - H

2.6.2 Sources of acute dose-response information 

Hazard identification and dose-response assessment information for preliminary acute 

inhalation exposure assessments are based on the existing recommendations of OAQPS for 

HAP [24]. 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 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 HAP can be 

found in recently released EPA documents [25] [26].

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. [27]. 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

 

19 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.

20 The multipathway exposure assessment for mercury included fate and transport analysis, that included 

separate oral exposure estimates for divalent mercury and methylmercury.
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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 (NAC/AEGL) 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, high-priority 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. More specifically, the AEGL values will be used for 

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

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

releases at fixed facilities and from transport carriers.” 

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

“AEGL-1 is the airborne concentration (expressed as ppm or mg/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 
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other illnesses, it is recognized that individuals, subject to unique or idiosyncratic 

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) [28] 

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

concentrations for once in a lifetime 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), and potentially life-threatening (ERPG-3). 

ERPG values are described in their supporting documentation [29] as follows: “ERPGs are air 

concentration guidelines for single exposures to agents and are intended for use as tools to 

assess the adequacy of accident prevention and emergency response plans, including 

transportation emergency planning, community emergency response plans and incident 

prevention and mitigation.”

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.”

The emissions inventory for the petroleum refinery source sector includes emissions of 48

HAP with relevant and available quantitative acute dose-response threshold values. These 

HAP, their acute threshold values, and the source of the value are listed below in Table 2.6-3.

Table 2.6-3 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)

1,3-Butadiene 106990 1500 12000 22 440

Acetaldehyde 75070 81 490 18 360 0.47

Acetonitrile 75058 22 540

Acrolein 107028 0.069 0.23 0.11 0.34 0.0025

Acrylonitrile 107131 10 130 22 77

Aniline 62533 30 46

Arsenic 7440382 0.0002

Benzene 71432 170 2600 160 480 1.3

Beryllium 7440417 0.025
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Table 2.6-3 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)

Biphenyl 92524 61

Carbon Disulfide 75150 40 500 3.1 160 6.2

Carbonyl Sulfide 463581 140

Chlorine 7782505 1.5 5.8 2.9 8.7 0.21

Chlorobenzene 108907 46 690

Chloroform 67663 310 240 0.15

Cumene 98828 250 1500

Hydrogen Cyanide 74908 2.2 7.8 11 0.34

Ethyl Benzene 100414 140 4800

Ethylene Dibromide 106934 130 180

Ethylene Dichloride 107062 200 810

Ethylene Oxide 75218 81 90

Formaldehyde 50000 1.1 17 1.2 12 0.055

Diethylene Glycol 

Monomethyl Ether 111773 0.093

Hexane 110543 12000

Hydrochloric Acid 7647010 2.7 33 4.5 30 2.1

Hydrogen Fluoride 7664393 0.82 20 1.6 16 0.24

Elemental Gaseous Mercury 200 1.7 2 0.0006

Mercury (elemental) 7439976 1.7 2 0.0006

Methanol 67561 690 2700 260 1300 28

Methyl Bromide 74839 820 190 3.9

Methyl Chloride 74873 1900 830

Methyl Tert-Butyl Ether 1634044 180 2100

Methylene Chloride 75092 690 1900 1000 2600 14

Dimethyl formamide 68122 270 6 300

Nickel 7440020 0.0002

Nickel Oxide 1313991 0.0002

Phenol 108952 58 89 38 190 5.8

Propionaldehyde 123386 110 620

Styrene 100425 85 550 210 1100 21

Tetrachloroethene 127184 240 1600 680 1400 20

Toluene 108883 750 4500 190 1100 37

Trichloroethylene 79016 700 2400 540 2700

Triethylamine 121448 2.8

Vinyl Chloride 75014 640 3100 1300 13000 180

m-Xylene 108383 22

o-Xylene 95476 22

p-Xylene 106423 22

Xylenes (Mixture of o, m, and 

p Isomers) 1330207 560 4000 22
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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 [30] 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 [31], in 2002 by the Agency’s information quality guidelines [32], and in the 

OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis [33], 

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, within 

the limitations of available time and resources. We provide summaries of risk metrics 

(including maximum individual cancer risks and noncancer hazards, as well as cancer 

incidence estimates) along with a discussion of the major uncertainties associated with their 

derivation to provide decision makers with the fullest picture of the assessment and its 

limitations.

For each carcinogenic HAP included in an assessment that has a potency estimate available, 

individual and population cancer risks were calculated by multiplying the corresponding 

lifetime average exposure estimate by the appropriate URE. This calculated cancer risk is 

defined as the upper-bound probability of developing cancer over a 70-yr period (i.e., the 

assumed human lifespan) at that exposure. Because UREs for most HAP are upper-bound 

estimates, actual risks at a given exposure level may be lower than predicted, and could be 

zero.

For EPA’s list of carcinogenic HAP that act by a mutagenic mode-of-action [34], we applied 

EPA’s Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to 

Carcinogens [35]. This guidance has the effect of adjusting the URE by factors of 10 (for 

children aged 0-1), 3 (for children aged 2-15), or 1.6 (for 70 years of exposure beginning at 

birth), as needed in risk assessments. In this case, this has the effect of increasing the 

estimated life time risks for these pollutants by a factor of 1.6. In addition, although only a 

small fraction of the total POM emissions may be reported as individual compounds, EPA 

expresses carcinogenic potency for compounds in this group in terms of benzo[a]pyrene 

equivalence, based on evidence that carcinogenic POM have the same mutagenic mechanism 

of action as does benzo[a]pyrene. For this reason, EPA implementation policy [36] 
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recommends applying the Supplemental Guidance to all carcinogenic PAHs for which risk 

estimates are based on relative potency. Accordingly, we applied the Supplemental Guidance 

to all unspeciated POM mixtures.

Increased cancer incidence for the entire receptor population within the area of analysis was 

estimated by multiplying the estimated lifetime cancer risk for each census block by the 

number of people residing in that block, then summing the results for the entire modeled 

domain. This lifetime population incidence estimate was divided by 70 years to obtain an 

estimate of the number of cancer cases per year.

In the case of benzene, the high end of the reported cancer URE range was used in our 

assessments to provide a conservative estimate of potential cancer risks. Use of the high end 

of the range provides risk estimates that are approximately 3.5 times higher than use of the 

equally plausible low end value. If the estimated benzene–associated risks exceed 1 in a 

million, we also evaluated the impact of using the low end of the URE range on our risk 

results.

Unlike linear dose-response assessments for cancer, noncancer health hazards generally are 

not expressed as a probability of an adverse occurrence. Instead, “risk” for noncancer effects 

is expressed by comparing an exposure to a reference level as a ratio. The “hazard quotient” 

(HQ) is the estimated exposure divided by a reference level (e.g., the RfC). For a given HAP, 

exposures at or below the reference level (HQ≤1) are not likely to cause adverse health 

effects. As exposures increase above the reference level (HQs 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. 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 a potential for significant acute risks.
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2.7.2 Mixtures

Since most or all receptors in these assessments receive exposures to multiple pollutants 

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

exposures from a particular source category combined.

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

[37,38] default assumption of additivity of effects, and combine risks by summing them using 

the independence formula in the mixtures guidelines.

In assessing noncancer hazard from chronic exposures, in cases where 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 HAP 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 HAP 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.

Because of the conservative nature of the acute inhalation screening and the variable nature of 

emissions and potential exposures, acute impacts were screened on an individual pollutant 

basis, not using the TOSHI approach.

2.7.3 Facility-wide Risks

To help place the source category risks in context, we examined “facility-wide” risks using 

the emissions data and modeling as described in Section 2.2. For the facilities in the 

petroleum refining source category, we estimated the maximum inhalation cancer and chronic 

noncancer risks associated with all HAP emissions sources at the facility, including emissions 

sources that are not part of the source categories but 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 the facility-wide 

assessment are summarized below in the risk characterization section of this document.
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2.7.4 MACT-Allowable Risk

The emissions data in the data set for the petroleum refining source category are estimates of 

actual emissions on an annual basis. For the petroleum refining source category, allowable 

emissions were also estimated and inhalation assessment results obtained. The docket memo 

Refinery Emissions and Risk Estimates for Modeled “Allowable” Emissions provides a full 

explanation of the development of these allowable emissions.as is described in Appendix 

9[39] 

3 Risk results for the petroleum refining source sector

3.1 Source category emissions and results

The petroleum refining source sector consists of 142 facilities regulated under the refinery 

MACT 1 and MACT 2 standards. Petroleum refineries are facilities that engage in producing 

liquid petroleum gases (LPG), motor gasoline, jet fuels, kerosene, distillate fuel oils, residual 

fuel oils, lubricants, asphalt (bitumen), and other products through distillation of crude oil or 

through redistillation, cracking, or reforming of unfinished petroleum derivatives. The first 

and primary source category for which regulations were developed, Petroleum Refineries –

Other Sources Not Distinctly Listed (Refinery MACT 1), includes all emission sources from 

petroleum refinery process units except those that were expected to be regulated elsewhere, 

such as the NESHAP for Boilers and Process Heaters (40 CFR part 63 subpart DDDDD). 

The Refinery MACT 1 rule, which focuses on evaporative emissions, was published in 40 

CFR part 63, subpart CC on August 18, 1995 (60 FR 43620) and specifically excludes three 

types of process vents: catalytic cracking unit catalyst regeneration vents, catalytic reforming 

unit catalyst regeneration vents, and sulfur plant vents. These specific vents are regulated by 

the NESHAP for Petroleum Refineries: Catalytic Cracking Units, Catalytic Reforming Units, 

and Sulfur Recovery Units (Refinery MACT 2) in 40 CFR part 63, subpart UUU. The 

Refinery MACT 2 standards, which focus on combustion sources, were promulgated on April 

11, 2002 (67 FR 17762). This analysis will evaluate the risks associated with both the 

MACT 1 and MACT 2 emissions.

We currently estimate that of the 148 Petroleum Refinery facilities operating in the U.S., that 

142 of these are identified as major sources and 6 identified as area sources. Only the major 

sources are included in this assessment.

The emissions for this source category data set were obtained from the ICR, as mentioned 

above [5]. The emissions from the source category are summarized in Table 3.1-1. The total 

HAP emissions for the source category are approximately 17,200 tons per year. Based on 

these data, the HAP emitted in the largest quantities across these 142 facilities are: hydrogen 

cyanide, n-hexane, toluene, xylenes (mixed), benzene, 2,2,4-trimethylpentane, hydrochloric 

acid, hydrogen sulfide, ethyl benzene, methanol, carbonyl sulfide, styrene, naphthalene, 

formaldehyde, cumene, methyl isobutyl ketone, p-xylene, carbon disulfide, 1,3-butadiene, 

methyl tert-butyl ether, m-xylene, o-xylene, hydrofluoric acid, 2-methylnapthalene, phenol, 

cresols (mixed), diethanolamine, acetaldehyde, methylene chloride, biphenyl, ethylene 

dibromide, and tetrachloroethene. These 32 HAP account for 99 percent of the total emissions 
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by mass. Persistent and bioaccumulative HAP (PB HAP)21 reported as emissions from these 

facilities include cadmium compounds, chlorinated dibenzodioxins and furans (analyzed as 

2,3,7,8-tetrachlorodibenzo-p-dioxin), mercury compounds, lead compounds, polychrorinated 

biphenyls (PCBs), and polycyclic organic matter (POM) (analyzed as benzo(a)pyrene). The 

following environmental HAP are emitted from the petroleum refineries source category and 

are included in the environmental risk screen: lead compounds, mercury compounds, 

cadmium compounds, POM, chlorinated dibenzodioxins and furans, hydrogen chloride, and 

hydrogen fluoride.

Table 3.1-1. Summary of Emissions from the Petroleum Refinery Source Category

and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (148 

facilities in 

NPRM 

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate 

for Cancer?

Reference 

Concentration 

for Chronic 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

Hydrogen Cyanide 3,682 80  

n-Hexane 2,513 142  

Toluene 2,284 142  

Xylenes (mixed) 1,840 139  

Benzene 1,174 142   

2,2,4-Trimethylpentane 1,086 129

Hydrochloric Acid 931 98  

Ethyl Benzene 491 141   

Methanol 466 66  

Carbonyl Sulfide 366 82  

Styrene 345 114  

Naphthalene 265 140  

Formaldehyde 196 119   

Cumene 163 135  

Methyl Isobutyl Ketone 128 21 

Carbon Disulfide 122 100  

p-Xylene 122 51  

Methyl Tert-butyl Ether 116 76   

1,3-butadiene 113 125   

m-Xylene 108 74  

o-Xylene 66 65  

Hydrofluoric Acid 63 24  

Polycyclic Organic Matter  

 2-methylnaphthalene 60 106  

 

21 Persistent and bioaccumulative HAP are defined in the EPA’s Air Toxics Risk Assessment Library, Volume 1, 

EPA-453K-04-001A, as referenced in the NPRM and provided on the EPA’s Technology Transfer Network 

website for Fate, Exposure, and Risk Assessment at http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 
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Table 3.1-1. Summary of Emissions from the Petroleum Refinery Source Category

and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (148 

facilities in 

NPRM 

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate 

for Cancer?

Reference 

Concentration 

for Chronic 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

 Anthracene 16 110 

 Phenanthrene 14 109 

 Fluorene 8 104  

 Pyrene 3 101 

 Chrysene 3 106  

 Acenaphthene 2 103  

 Fluoranthene 2 104  

 POM 72002 1 5  

 Benzo(ghi)perylene 0.8 110  

 Benz[a]anthracene 0.6 106  

 Perylene 0.6 14  

 Benzo[a]pyrene 0.5 105  

 Benzo(e)pyrene 0.5 84  

 Indeno[1,2,3-c,d]pyrene 0.5 104  

 1-methylnaphthalene 0.4 1  

 Dibenzo[a,h]anthracene 0.2 106  

 Benzo[b]fluoranthene 0.2 105  

 Acenaphthylene 0.2 104  

 Benzo[k]fluoranthene 0.1 105  

 7,12-dimethylbenz[a]anthracene 0.02 61  

 3-methylcholanthrene 0.01 61  

 Dibenzo[a,i]pyrene 0.0002 1  

 Dibenz[a,j]acridine 0.0001 1  

Phenol 59 117  

Cresols (mixed) 58 97 

Diethanolamine 49 31 

Acetaldehyde 47 107   

Methylene Chloride 43 8   

Biphenyl 41 116 

Ethylene Dibromide 27 12   

Tetrachloroethene 22 31   

2-nitropropane 20 2  

Acetonitrile 12 4  

Chlorine 10 76  

Nickel Compounds  

 Nickel Compounds 9 103   

 Nickel Oxide 0.01 1   

Acrylonitrile 9 2   
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Table 3.1-1. Summary of Emissions from the Petroleum Refinery Source Category

and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (148 

facilities in 

NPRM 

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate 

for Cancer?

Reference 

Concentration 

for Chronic 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

Aniline 7 44   

Acrolein 6 104  

Chlorobenzene 5 3  

Antimony Compounds 5 97 

Trichloroethylene 5 11   

1,4-dichlorobenzene 3 39  

o-Cresol 3 24 

Ethylene Dichloride 3 13   

Methyl Bromide 2 57  

1,3-dichloropropene 2 2  

Selenium Compounds 2 99 

Lead Compounds 1 101 c 

Chromium Compounds 

 Chromium (III) 1 98

 Chromium (VI) 0.2 101  

1,1,2-trichloroethane 1 7  

Manganese Compounds 1 97 

Phosphorus, White 1 41

m-Cresol (3-methylphenol) 1 21 

Methyl Chloride 1 5  

Chloroform 0.9 15  

Vinyl Chloride 0.7 3   

1,1,2,2-tetrachloroethane 0.7 6 

Ethyl Chloride 0.7 2 

Mercury Compounds   

 Mercury (elemental) 0.6 106   

 Gaseous Divalent Mercury 0.08 106  

 Particulate Divalent Mercury 0.08 106  

 Mercuric Chloride 0.009 3  

 Mercuric Oxide 0.0001 1  

Ethylidene Dichloride 0.6 2  

Cadmium Compounds 0.5 97   

Cobalt Compounds  

 Cobalt Compounds 0.4 95 

 Cobalt Oxide 0.007 1 

Arsenic Compounds 0.2 96   

p-Cresol (4-methy Phenol) 0.2 14 

Bis(2-ethylhexyl)phthalate 0.2 7  
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Table 3.1-1. Summary of Emissions from the Petroleum Refinery Source Category

and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (148 

facilities in 

NPRM 

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate 

for Cancer?

Reference 

Concentration 

for Chronic 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

Dibenzofuran 0.2 21

Nitrobenzene 0.2 1  

Ethylene Oxide 0.1 1   

Dibutylphthalate 0.1 5

Hexachloroethane 0.1 1 

Beryllium Compounds 0.08 94   

Triethylamine 0.06 2  

Vinyl Bromide 0.03 1  

Quinoline 0.02 2

Dimethyl Formamide 0.005 1  

Acrylamide 0.004 2  

Vinylidene Chloride 0.004 1 

Benzidine 0.002 1  

Diethylene Glycol Monomethyl Ether 0.001 1  

Polychlorinated Biphenyls 0.001 57  

3,3'-dimethylbenzidine 0.0009 1  

3,3'-dimethoxybenzidine 0.0004 1  

N,N-dimethylaniline 0.0004 1  

p-Phenylenediamine 0.0004 1  

Propionaldehyde 0.0004 3  

Ethylene Glycol 0.0001 1 

o-Toluidine 0.00009 1  

Isophorone 0.00006 1   

Dioxins and Furans 

 2,3,7,8-tetrachlorodibenzo-p-dioxin 0.000002 52   

 1,2,3,4,6,7,8-heptachlorodibenzofuran 0.000002 16   

 1,2,3,4,6,7,8-heptachlorodibenzo-p-dioxin 0.000001 61   

 1,2,3,6,7,8-hexachlorodibenzofuran 0.0000009 54   

 1,2,3,4,6,7,8,9-octochlorodibenzo-p-dioxin 0.0000006 18   

 1,2,3,4,7,8-hexachlorodibenzofuran 0.0000005 19   

 2,3,4,7,8-pentachlorodibenzofuran 0.0000005 53   

 1,2,3,4,6,7,8,9-octochlorodibenzofuran 0.0000004 13   

 2,3,4,6,7,8-hexachlorodibenzofuran 0.0000003 13   

 1,2,3,7,8-pentachlorodibenzofuran 0.0000002 17   

 1,2,3,4,7,8,9-heptachlorodibenzofuran 0.0000001 14   

 2,3,7,8-tetrachlorodibenzofuran 0.00000009 15   

 1,2,3,7,8,9-hexachlorodibenzofuran 0.00000008 12   

 1,2,3,6,7,8-hexachlorodibenzo-p-dioxin 0.00000008 11   
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Table 3.1-1. Summary of Emissions from the Petroleum Refinery Source Category

and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (148 

facilities in 

NPRM 

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate 

for Cancer?

Reference 

Concentration 

for Chronic 

Noncancer?

Health 

Benchmark 

Values for 

Acute 

Noncancer?

 1,2,3,7,8-pentachlorodibenzo-p-dioxin 0.00000007 15   

 1,2,3,7,8,9-hexachlorodibenzo-p-dioxin 0.00000005 11   

 1,2,3,4,7,8-hexachlorodibenzo-p-dioxin 0.00000003 13   

a Notes for how HAP were speciated for risk assessment:

 For most metals, emissions reported as the elemental metal are combined with metal compound emissions (e.g., 

“cadmium” emissions modeled as “cadmium & compounds”). In the absence of speciation information, we assume 

the reported mass is 100 percent metal.

 For emissions of certain chemicals or chemical groups classified as POM, some (not that are not already speciated) 

emissions were grouped into POM subgroups as found on EPA’s Technology Transfer Network website for the 

2005 National-Scale Air Toxics Assessment at http://www.epa.gov/ttn/atw/nata2005/methods.html#pom

(Approach to Modeling POM). These POM subgroups (e.g., POM 72002) all have unit risk estimates for cancer, 

and are considered PB-HAP. Pollutants previously grouped under POM 73002, POM 74002, POM 75002, and 

POM 76002 are listed individually in this table.

 For emissions reported generically as “Glycol Ethers” or specific glycol ethers not found on EPA’s Technology 

Transfer network for air toxics (see footnote b), emissions will be treated as ethylene glycol methyl ether.

 For emissions reported generically as “chromium” or “chromium & compound,” emissions are speciated 

“chromium (III) compounds” and “chromium (VI) compounds” according to the individual emitting process 

speciation profile for this source category. Chromium speciation profiles can be found on the EPA’s Technology 

Transfer Network website for emissions inventories at http://www.epa.gov/ttn/chief/net/2005inventory.html.

 For emissions reported generically as “mercury” or “mercury & compounds,” emissions are speciated for this 

category as 80% “mercury (elemental)”, 10% “gaseous divalent mercury”, and 10% “particulate divalent 

mercury”. Mercury speciation profiles can be found on the EPA’s Technology Transfer Network website for 

emissions inventories at http://www.epa.gov/ttn/chief/net/2005inventory.html. 

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

toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html

c There is no reference concentration for lead. In considering noncancer hazards for lead in this assessment, we compared 

maximum annual ambient exposure estimates to the National Ambient Air Quality Standards (NAAQS) for lead (0.15 

μg/m3). These NAAQS for lead were reviewed with revisions adopted in October 2008 

(http://www.epa.gov/air/lead/actions.html). The primary (health-based) standard is a maximum or not-to-be-exceeded, rolling 

three-month average, measured as total suspended particles (TSP). The secondary (welfare-based) standard is identical to the 

primary standard.

3.2 Baseline risk characterization

This section presents the results of the baseline risk assessment for the petroleum refining 

source sector based on the modeling methods described in the previous sections. All baseline 

risk results are developed using the best estimates of actual HAP emissions summarized in the 

previous section. The basic chronic inhalation risk estimates presented here are the maximum 

individual lifetime cancer risk, the maximum chronic hazard index, and the cancer incidence. 

We also present results from our acute inhalation impact screening assessment in the form of 
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maximum hazard quotients, as well as the results of our preliminary screen for potential noninhalation risks from PB-HAP. Also presented are the HAP “drivers,” which are the HAP 

that collectively contribute 90 percent of the maximum cancer risk or maximum hazard at the 

highest exposure location, as well as our analysis of risks associated with the maximum 

allowed emissions under the current MACT standards. Definitions of these and other relevant 

risk-related terms can be found on the 2005 National-Scale Air Toxics Assessment Glossary 

Web page. A detailed summary of the facility-specific risk assessment results is available in 

Appendix 5 of this document (Detailed Risk Modeling Results).

MACT-level Inhalation Assessment Results

Tables 3.2-1 and 3.2-2 summarize the chronic and acute inhalation risk results for this source 

category. The results of the chronic inhalation cancer risk assessment are that the maximum 

lifetime individual cancer risk posed by the 142 facilities could be 60 in a million considering 

both the maximum facility, and the entire source sector. Emissions of naphthalene and 

benzene from process equipment leaks and storage tanks are the major contributors to the risk. 

The total estimated cancer incidence from this source category is 0.3 excess cancer cases per 

year, or one excess case in every 3 years. Approximately 100,000 people were estimated to 

have cancer risks above 10 in a million and approximately 5,000,000 people were estimated 

to have cancer risks above 1 in a million considering the 142 facilities in this source category. 

The maximum chronic noncancer TOSHI value for the source category could be up to 0.9

driven by emissions of hydrogen cyanide from catalytic cracking unit vents. 

Analysis of potential differences between actual emissions levels and the maximum emissions 

allowable under the MACT standards (i.e., MACT-allowable emissions) were also calculated 

for the source category. MACT-allowable emissions were estimated by using two different 

methods, a model plant approach (Refinery Emissions Model (REM), approach) and an 

approach that combined the results of the actual and REM emissions estimates to develop a 

more conservative allowable risk estimate.

Appendix 9 provides a memo that describes in details these two approaches as well as the risk 

estimates using from both approaches. Risk results from the inhalation risk assessment using 

the MACT-allowable emissions indicate that the maximum lifetime individual cancer risk 

could be higher than those from the actual analysis, or 90 to 100 in a million, and that the 

maximum chronic noncancer Hazard Index value is about 1. The total estimated cancer 

incidence from this source category considering allowable emissions is expected to range 

between 0.4 and 0.6 excess cancer cases per year or one excess case in every 1.5 to 2.5 years. 

The REM model approach predicts that approximately 90,000 people were estimated to have 

cancer risks above 10 in a million and approximately 7,000,000 people were estimated to 

have cancer risks above 1 22. Chronic noncancer risks from the MACT-allowable emissions 

are expected to remain at or below 1.

 

22 Population risks from allowable emissions were only calculated for the 

model plant emissions (REM) approach. For the 138 facilities modeled using 

the modeled plant approach the population risks greater than 10-in-1 

million was estimated to be 90,000. If we consider the second approach to 

determining allowable emissions (combined the results of the actual and REM 

emissions estimates) we estimate that the allowable population risks 
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Worst-case acute hazard quotients (HQs) were calculated for every HAP shown in 

Table 3.1-1 that has an acute benchmark, and the highest refined screening acute HQ value of 

5 (based on the acute REL for nickel) is shown in Table 3.2-1. This value includes a 

refinement of determining the highest HQ value that is outside facility boundaries. It’s also 

important to note that the HQ of 5 for Nickel assumes that the primary source of the nickel 

emissions, the fluid catalytic cracking unit vent, was modeled with an hourly emissions 

multiplier of 60 times the annual emissions rate. There are also refined acute HQ values 

(based on RELs) greater than 1 for acetaldehyde, acrolein,

arsenic compounds, benzene, and nickel compounds. In all, six facilities are estimated to 

have a refined acute HQ (based on an REL) greater than 1 (four of these facilities are 2 or 

less). No facilities are estimated to have a AEGL-1 greater than 1. Acute estimates for each 

plant and pollutant are provided in Appendix 5 of this document, while refined estimates are 

provided in Appendix 6 of this document (Acute Impacts Refined Analysis). 

Table 3.2-1. Summary of Source Category Level Risks for Petroleum Refineries

Result HAP “Drivers”

Facilities in Source Category

Number of Facilities Estimated to be in 

Source Category 142 n/a

Number of Facilities Identified by ICR and 

Modeled in Risk Assessment 142 n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk 

(in 1 million) 60 naphthalene, benzene

Number of Facilities with Maximum Individual Lifetime Cancer Risk:

Greater than or equal to 100 in 1 

million 0 n/a

Greater than or equal to 10 in 1 

million 48

naphthalene, benzene, ethyl benzene, 

ethylene dibromide, 7,12-

dimethylbenz[a]anthracene, benzidine, 

dibenzo[a,h]anthracene, benzo[a]pyrene, 

1,1,2-trichloroethane, 2-

methylnaphthalene, acetaldehyde, POM 

72002, fluorene, benzo[b]fluoranthene, 

formaldehyde, 3-methylcholanthrene, 

acrylonitrile, nickel compounds, 

1-methylnaphthalene, benz[a]anthracene, 

indeno[1,2,3-c,d]pyrene, chrysene, arsenic 

compounds, tetrachloroethene, cadmium 

compounds, fluoranthene, 

benzo(ghi)perylene, chromium (VI) 

compounds, 1,3-butadiene, 1,1,2,2-

tetrachloroethane, ethylene dichloride, 2-

 

greater than 10-in-1 million would be greater than 90,000 people. 

Further,theFurther, the number of people above 1-in-1 million would also be 

higher than the 7,000,000 estimated using the REM model.
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Table 3.2-1. Summary of Source Category Level Risks for Petroleum Refineries

Result HAP “Drivers”

nitropropane, acenaphthene, beryllium 

compounds, 2,3,7,8-tetrachlorodibenzo-pdioxin, methyl tert-butyl ether, 

benzo(e)pyrene

Greater than or equal to 1 in 1 

million 111

naphthalene, benzene, ethyl benzene, 

ethylene dibromide, 7,12-

dimethylbenz[a]anthracene, benzidine, 

dibenzo[a,h]anthracene, benzo[a]pyrene, 

1,1,2-trichloroethane, 2-

methylnaphthalene, acetaldehyde, POM 

72002, fluorene, benzo[b]fluoranthene, 

formaldehyde, 3-methylcholanthrene, 

acrylonitrile, nickel compounds, 

1-methylnaphthalene, benz[a]anthracene, 

indeno[1,2,3-c,d]pyrene, chrysene, arsenic 

compounds, tetrachloroethene, cadmium 

compounds, fluoranthene, 

benzo(ghi)perylene, chromium (VI) 

compounds, 1,3-butadiene, 1,1,2,2-

tetrachloroethane, ethylene dichloride, 2-

nitropropane, acenaphthene, beryllium 

compounds, 2,3,7,8-tetrachlorodibenzo-pdioxin, methyl tert-butyl ether, 

benzo(e)pyrene, ethylene oxide, pdichlorobenzene, vinyl chloride, 1,3-

dichloropropene, perylene, aniline

Chronic Noncancer Risks

Maximum Neurological Hazard Index 0.9 hydrogen cyanide

Number of Facilities with Maximum Neurological Hazard Index:

Greater than 1 0 n/a

Acute Noncancer Screening Results

Maximum Acute Hazard Quotient23

5

2

2

2

2

nickel compounds (REL)

arsenic compounds (REL)

acrolein (REL)

benzene (REL)

acetaldehyde (REL)

Number of Facilities With Potential for 

Acute Effects 6

nickel compounds, arsenic compounds, 

acrolein, benzene, acetaldeyhyde

Population Exposure

Number of People Living Within 50 

Kilometers of Facilities Modeled 83,000,000 n/a

Number of People Exposed to Cancer Risk:

Greater than or equal to 100 in 1 

million 0 n/a

Greater than or equal to 10 in 1 

million 100,000 n/a

Greater than or equal to 1 in 1 5,000,000 n/a

 

23 As shown in Tables 2.6.3 and 3.2-2 there are no AEGL or ERPG values for nickel or arsenic compounds. 

Additionally, there are no short-term occupational values for these metals to compare to the REL values.
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Table 3.2-1. Summary of Source Category Level Risks for Petroleum Refineries

Result HAP “Drivers”

million

Number of People Exposed to Noncancer Neurological Hazard Index:

Greater than 1 0 n/a

Estimated Cancer Incidence (excess cancer 

cases per year) 0.3 n/a

Contribution of HAP to Cancer Incidence

naphthalene 22% n/a

benzene 21% n/a

2-methylnaphthalene 13% n/a

7-12-dimethylbenz[a]anthracene 10% n/a

1,3-butadiene 6% n/a

nickel compounds 5% n/a

ethylene dibromide 5% n/a

ethyl benzene 4% n/a

benzo[a]pyrene 2% n/a

formaldehyde 2% n/a

Contribution of Process to Cancer Incidence

Coking unit vents & coke handling 31% n/a

Process equipment leaks 23% n/a

Wastewater treatment 12% n/a

Catalytic cracking unit vent 10% n/a

Storage tanks 7% n/a

Cooling towers 6% n/a

Flares 5% n/a

Marine vessel loading & unloading 2% n/a

Catalytic reforming unit vents 1% n/a

Refinery processes (other, general) 1% n/a

Incinerators 1% n/a

 

Table 3.2-2. Summary of Refined Acute Results for Petroleum 

Refining Source Sector

Refined Results Maximum Acute Hazard Quotients Acute Dose-Response Values

HAP

Max. 1-

hr. Air 

Conc. 

(mg/m3)

Based on 

REL

Based on 

AEGL-1/

ERPG-1

Based on 

AEGL-2/

ERPG-2

REL

(mg/m3)

AEGL-1 

(1-hr) 

(mg/m3)

ERPG-1 

(mg/m3)

AEGL-2

(1-hr)

(mg/m3)

ERPG-2 

(mg/m3)

Acetaldehyde 1.0 2 0.05 .003 0.47 81 18 490 360

Acrolein 0.005 2 0.1 0.03 0.0025 0.069 0.11 0.23 0.34
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Arsenic 

compounds 0.0004 2 na na 0.0002 na na na na

Benzene 2.7 2 0.02 0.006 1.3 170 160 2600 480

Nickel 

compounds 0.001 5 na na 0.002 na na na na

Notes on Refined Process:

1) The initial screening was performed for all emitted HAP with available acute dose-response values. Only those pollutants whose 

screening HQs were greater than 1 for at least one acute threshold value are shown in the table.

2) HAP with available acute dose-response values which are not in the table do not carry any potential for posing acute health risks, 

based on an analysis of currently available emissions data.

Notes on Acute Dose-Response Values:

REL – California EPA reference exposure level for no adverse effects. Most, but not all, RELs are for 1-hour exposures.

AEGL – Acute exposure guideline levels represent emergency exposure (1-hour) limits for the general public.

AEGL-1 is the exposure level above which it is predicted that the general population, including susceptible individuals, could 

experience effects that are notable discomfort, but which are transient and reversible upon cessation of exposure.

AEGL-2 is the exposure level above which it is predicted that the general population, including susceptible individuals, could 

experience irreversible or other serious, long-lasting adverse health effects of an impaired ability to escape.

EPRG – Emergency Removal Program guidelines represent emergency exposure (1-hour) limits for the general public.

ERPG-1 is the maximum level 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.

ERPG-2 is the maximum exposure 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.

MACT-level Multipathway Assessment Results

To identify potential multipathway health risks from PB-HAP other than lead, we first 

performed a screening analysis (Tier I and II) that compared emissions of PB-HAP emitted 

from the petroleum refining source sector (based on actual emissions) to screening emission 

rates (see section 2.5). The PB-HAP emitted by facilities in this category include cadmium

compounds (97 facilities), chlorinated dibenzodioxins and furans (analyzed as 2,3,7,8-

tetrachlorodibenzo-p-dioxin TEQ) (78 facilities), polychlorinated biphenyls (58 facilities), 

mercury compounds (106 facilities), and polycyclic organic matter (POM) (analyzed as 

benzo(a)pyrene toxicity equivalence or (TEQ))(113 facilities). 

Following the above approach, 1 facility emitted cadmium compounds above the Tier I

screening level, 42 facilities emitting chlorinated dibenzodioxins and furans as 2,3,7,8-

tetrachlorodibenzo-p-dioxin TEQ above the Tier I screening level, 14 facilities emit mercury

compounds above the Tier I screening level, and 57 facilities emit POM as benzo(a)pyrene 

TEQ above the screening level. Polychlorinated biphenyl is a PB-HAP but does not currently 

have a multipathway screening value and so was not evaluated for potential non-inhalation 

risks. As shown in Table 3.1-1, this HAP is not emitted in appreciable quantities. Due to the 

theoretical construct of the screening model, these factors are not directly translatable into 

estimates of risk or hazard quotients for these facilities. Table 3.2-3 summarizes the results of 

this screening (Tier I) comparison.

For the PB-HAP that did not screen out during our initial “Tier I” multipathway screening 

analysis, we refined our analysis somewhat by including some additional site-specific 

information to develop an “intermediate” or Tier II screen. (See Appendix 4 of this document 

for more information about the Tier II screen.) The additional site-specific information 

included the land use around the facilities, the location of fishable lakes, and local wind 
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direction and speed. The result of this analysis was the development of site-specific emission 

screening thresholds for cadmium, chlorinated dibenzodioxins and furans, POM and mercury. 

Based on this Tier II screening analysis, as presented in Table 3.2-3, 1 facility’s emissions 

remained above the screening threshold for cadmium with the highest at about 2 times the 

threshold. Emissions from 23 facilities remained above the threshold for chlorinated 

dibenzodioxins and furans with the highest at about 40 times the threshold. No facility’s 

emissions remained above the threshold for mercury. For POM, 44 facility’s emissions 

exceeded the site-specific screening threshold for POM with the highest by a factor of about 

30. A Tier II exceedance cannot be equated with a risk value or a hazard quotient or index. 

Rather it represents a high-end estimate of what the risk or hazard may be. For example, an 

exceedance of 2 for a non carcinogen can be interpreted to mean that we have high confidence 

that the hazard would be lower than 2. Similarly, an exceedance of 30 for a carcinogen means 

that we have high confidence that the risk is lower than 30-in-1-million. Our confidence 

comes from the conservative, or health-protective, assumptions that are in the Tier II screen: 

we choose inputs from the upper end of the range of possible values for the influential 

parameters used in the Tier II screen; and we assume that the exposed individual exhibits 

ingestion behavior that would lead to a high total exposure. 

Table 3.2-3. Summary of Multipathway Screening Results

for Petroleum Refining Source Sector

 

Tier I Tier II

PBHAP

Num 

Facilities 

Emitting 

This 

PBHAP

(142 in 

source 

category)

Max 

Emissions of 

this PBHAP 

(TPY)

Max 

Emissions 

of this 

PBHAP, 

Div by the 

Screening 

Level

Num 

Facilities 

Exceeding 

the 

Screening 

Level of 

this 

PBHAP

Max 

Emissions 

of this 

PBHAP, 

Div by the 

Screening 

Level

Num 

Facilities 

Exceeding 

the 

Screening 

Level of 

this 

PBHAP

Cadmium Compounds 97 6.05E-02 5 1 2 1

Chlorinated Dibenzodioxins and 

Furans as 2,3,7,8-

Tetrachlorodibenzo-p-dioxin

78 2.81E-09 100 42 40 23

Divalent Mercury 106 1.73E-03 5 14 1 0

Polycyclic Organic Matter as 

Benzo(a)Pyrene 113 2.58E-03 400 57 30 44

In evaluating the potential for multipathway effects from emissions of lead, modeled 

maximum annual lead concentrations were compared to the NAAQS for lead (0.15 μg/m3). 

Lead emissions were reported from 103 facilities. Results of this analysis estimate that with 

the exception of one facility, the NAAQS for lead would not be exceeded by any facility. At 

the one facility, the lead NAAQS is exceeded 1.5 times at an on-site location. Off-site at this 

facility, the concentrations are below the NAAQS. 

To gain a better understanding of the uncertainty associated with the multipathway Tier I and 

2 screening analysis, a more refined multipathway case study using the TRIM.Fate model was 

conducted for a single petroleum refinery. The site, Marathon Ashland Petroleum facility 
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(NEI6087) near Garyville in St. John the baptist Parish, Louisiana, was among those that 

exceeded the Tier I screen for any PB-HAP and it was among the highest of the refineries that 

exceeded a Tier II threshold for any PB-HAP. It also was selected based on the feasibility, 

with respect to the modeling framework, of obtaining model parameters for the region

surrounding the refinery. The exposure scenarios assessed for the selected facility are not 

necessarily representative of the highest potential exposures for human receptors from the 

petroleum refineries sector, but the results for exposures (and the risks calculated for those 

exposures) are anticipated to be among the highest that might be encountered for this source 

category. The approach, data, assumptions, and results of the site-specific assessment are 

presented in Appendix 10 (Technical Support Document: Human Health Multipathway 

Residual Risk Assessment for the Petroleum Refineries Sector – A site Specific Analysis) of 

this document. 

As in the screening assessments, hypothetical farmer and angler scenarios were included in 

the site-specific assessment, as well as children in different age ranges and adults. It is 

important to note that even during the refined multipathway analysis ,that no data exists to 

verify existence of either the farmer or angler scenario outlined below. These scenarios are 

included as part of the exercise of evaluating the uncertainty associated with the multipathway 

screens. The farmer scenario involves an individual living for a 70-year lifetime on a farm 

homestead in the vicinity of the source and consuming produce grown on, and meat and 

animal products raised on, the farm. The individual also incidentally ingests surface soil at 

the location of the farm homestead. The angler scenario involves an individual who regularly 

consumes fish caught in freshwater lakes in the vicinity of the source of interest over the 

course of a 70-year lifetime. In addition, exposure estimates and risks for infants consuming 

contaminated breast milk were evaluated in the case of dioxins, with the assumption that the 

nursing mother was exposed to chemicals via one of the two basic scenarios described above. 

Variations of these two scenarios were evaluated using different assumptions regarding food 

source (i.e., location of the farm homestead or the water body from which fish are obtained),

the age of the individual exposed (for non-cancer hazards), the assumed ingestion rate of each 

food type, and other factors. In particular, a range of fish ingestion rates was evaluated to 

determine the possible health risks associated with that pathway.

Cancer risk estimates, as presented in table 3.2-4, from exposure to PAHs include an 

incremental lifetime cancer risk of 2 in 1 million, with farm exposure at 90th percentile 

ingestion rates driving the risk. Cancer results from exposure to dioxins also include an 

incremental lifetime cancer risk of 2 in 1 million, with fish exposure by the adult female

angler at 99

th percentile ingestion rates driving the risk. Noncancer HQs, also presented in 

Table 3.2-4, did not exceed 1 for any scenario for exposure to mercury or cadmium. For 

methyl mercury, the highest HQ was 0.04 with the Child Age 1-2 group driving the risk, 

while the highest noncancer HQ for cadmium was 0.02, also with the Child Age 1-2 group

driving the risk. As explained in Appendix 4, the scenarios included in the screening and 

refined assessments include children at different age ranges, as well as adults, and the Child 

Age 1-2 group has the highest risks for the noncancer endpoints [40].
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Table 3.2-4. Summary of Refined Multipathway Results

for Marathon Ashland Petroleum facility (NEI6087) St. John the Baptist Parish, 

Louisiana

PB-HAP Group

Ratio of Emissions to the 

Emission Screening 

Threshold Site-specific Hazard Quotient or Risk

Tier I Tier II

Via Fish Only, Lac des 

Allemands Via Farm Only, Farm_W_S Combined Fish + Farm

Mercury

(non-cancer) 2 0.3 0.04 0.0001 0.04

Cadmium

(non-cancer) 0.3 0.05 0.02 0.0007 0.02

PAHs

(cancer) 100 20 0.4 2 2

Dioxins

(cancer) 40 5 1 0.5 2

Total Incremental Lifetime 

Cancer Risk (PAH+Dioxin) 200 30 1 2 4

The site-specific analysis for this facility showed that the potential risk was lower than the 

Tier II screen for each pollutant over-predicted the potential risk when compared to the 

refined analysis results. In the site-specific analysis, for mercury emissions, the potential HQ 

was about 7 times lower than the exceedance of the Tier II screening threshold. For cadmium 

emissions, the site-specific results (HQ) are about 3 times lower than the exceedance of the 

Tier II screening threshold. For PAH emissions, the site-specific analysis had a cancer risk 14

times the exceedance of the Tier II screening threshold. Finally, for the site-specific analysis, 

the cancer risk from emissions of dioxins is 3 times lower than the exceedance of the Tier II

screening threshold. 

While this more refined assessment was only performed on a single facility, the results of this 

analysis lead us to the conclusion that if refined analyses were performed for other sites, the 

risk estimates would consistently be lower than those estimated by the Tier1 and 2 analyses. 

As shown in Table 3.2.-5, the overall trend when the analyses rely less on defaults and more 

on site-specific data is an increase in the emissions threshold. For example, between the Tier 

I and Tier II screens, the screening threshold for mercury emissions increased by 6 times. For 

this source category, the threshold for mercury increased by 45 times between the Tier I

screen and the site-specific assessment. 
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Table 3.2 – 5. Summary of Trends in Threshold Exceedances for the Multipathway Screening 

and Site-Specific Analyses

PB-HAP Group

Increase in Emissions Threshold (or Increase in Ration of 

Emissions to Screening Threshold)

Tier I to Tier II Tier II to SiteSpecific

Tier I to SiteSpecific

Mercury 6 7 45

Cadmium 6 3 20

PAHs 4 14 58

Dioxins 8 3 23

Total Cancer 5 9 45

MACT-level Environmental Assessment Results

We conducted a screening-level evaluation of the potential adverse environmental risks 

associated with emissions of the following environmental HAP from the petroleum refineries 

source category: lead compounds, mercury compounds, cadmium compounds, POM, 

chlorinated dibenzodioxins and furans, hydrogen chloride, and hydrogen fluoride. The results 

of the environmental screening analysis are summarized in Table 3.2-6. 

In the Tier I screening analysis for PB-HAP (other than lead, which was evaluated differently 

as noted in section III.A.5 of this preamble) the individual modeled Tier I concentrations for 

one facility in the source category exceeded soil ecological benchmarks for mercuric chloride. 

In addition, Tier I modeled concentrations for four facility exceeded sediment and soil 

ecological benchmarks for PAH. Therefore, we conducted a Tier II assessment. In the Tier II

screening analysis for PB-HAP none of the individual modeled concentrations for any facility 

in the source category exceeded any of the ecological benchmarks (either the LOAEL or 

NOAEL). For lead, we did not estimate any exceedances of the secondary lead NAAQS.

For hydrogen fluoride and hydrogen chloride, the average modeled concentration around each 

facility (i.e., the average concentration of all off-site data points in the modeling domain) did 

not exceed the ecological benchmarks. In addition, each individual modeled concentration of 

hydrogen chloride and hydrogen fluoride (i.e., each off-site data point in the modeling 

domain) was below the ecological benchmarks for all facilities. 

Table 3.2-6. Summary of Environmental Risk Screen Results for the Petroleum 

Refineries Source Category 

Environmental 

HAP

Number of Facilities In Category 

Exceeding

Percent of Modeled 

Area in Category 
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Exceeding2

Tier I Screen Tier II Screen1

NOAEL LOAEL NOAEL LOAEL NOAEL LOAEL

PBHAP

Pb None None None None 0% 0%

HgCl2 NA 1 None None 0% 0%

Cd None None None None 0% 0%

PAH 4 None None None 0% 0%

Dioxin None None None None 0% 0%

Acid 

Gases

HF3 NA None - - NA 0%

HCL4 NA None - - NA 0%

NA – Not Applicable. 

1- Tier II screen is performed for PB-HAP when there are exceedances of the Tier I screen. 

The acid gas screen is a one tier screen.

2 - A value of 0% indicates that none of the modeled data points exceeded the benchmark. For 

PB-HAP the percent area is based on the Tier II results, if a Tier II analysis is performed. 

Otherwise, the percent area is based on the Tier I results. 

3 – For HF, we evaluated two benchmarks, one from Canada and the other from the State of 

Washington. Although, they are both considered to be LOELs - the level between a NOAEL 

and a LOAEL, we have listed the results under the LOAEL column.

4 – For HCL, we evaluated one benchmark at the LOAEL level.

 

Facility-wide Inhalation Assessment Results

The facility-wide chronic MIR and TOSHI, available in Appendix 5, are based on emissions 

from all sources at the identified facilities. The results of the facility-wide assessment for 

cancer risks are summarized in Table 3.2-7. The results indicate that 115 facilities with 

petroleum refining processes (covered by MACT 1 or MACT 2) have a facility-wide cancer 

MIR greater than or equal to 1 in a million. The maximum facility-wide cancer MIR is 70 in 

a million, at one facility. The 70 in a million is mainly driven by naphthalene, chromium (VI) 

compounds, and arsenic compounds from storage tanks, fugitive dust/blasting/construction, 

and coking unit vents & coke handling processes. The maximum facility-wide TOSHI for the 

source category is estimated to be 4, at one facility, mainly driven by emissions of chlorine

from catalytic reforming unit vents and cooling towers.
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Table 3.2-7 Source Category Contribution to Facility-Wide 

Chronic Cancer Risks (Actual Emissions)

Petroleum Refining Source Sector Number of Facilities Binned by Facility-Wide MIR 

(in 1 million)

Source Sector MIR Contribution 

to Facility-Wide MIR

<1 1≤ MIR<10 10≤ MIR<100 > 100 Total

> 90% 14 37 38 0 89

50-90% 9 20 12 0 41

10-50% 3 4 3 0 10

< 10% 1 0 1 0 2

Total 27 61 54 0 142

3.3 Post-control risk characterization

As shown in Table 3.2-1 above, the baseline cancer risks (as shown in the Incidence Driver 

rows) are primarily driven by coking unit vents and coke handling and process equipment 

leaks. Given this, using the same risk assessment methods described above, we estimated 

what the risks would be if all of the petroleum refinery facilities adopted control measures to 

limit emissions from coking units, equipment leaks, and storage and loading processes in one 

control scenario. This scenario includes an 896 percent reduction in HAP emissions from 

coking units, a 4 percent reduction in HAP emissions from equipment leaks, and a 4051

percent reduction in HAP emissions from storage and loading processes. (The scenario is 

described in more detail in the emissions memo in the docket. [5]) Based on this control 

scenario, we estimated (based on use of the same modeling assumptions and methodologies 

used for the baseline risk assessment) that the maximum individual lifetime cancer risk 

for one facility would be reduced from 60 in a million to 50 in a million. These controls 

would reduce the cancer risk to the individual most exposed from 60-in-1 million to 50-in-1 

million based on actual emissions at the facility where storage tank emissions were driving 

the risk. However, the post-control MIR remains unchanged for the refinery source category, 

at 60-in 1-million, because the several facilities combine for an MIR of 60-in-1 million at a 

census block location. The post-control cancer risk is primarily driven by naphthalene, 

dibenzo[a,h]anthracene, and benzo[a]pyrene from process equipment leaks. The number of 

people estimated to have a cancer risk greater than or equal to 10 in a million would be 

reduced from 100,000 people to 80,000 people. And, the number of people estimated to have 

a cancer risk greater than or equal to 1 in a million would be reduced from 5,000,000 people 

to 4,000,000 people. There is a similar percentage reduction in incidence (17 percent);

however this is not readily apparent with the presentation of the results to one significant 

figure (0.3 both in the baseline and post-control scenarios). 

A closer look at the controls driving the exposed population reductions shows that 

approximately 7,300 people will have risks less than 10 in a million and 985,000 people will 

fall below 1 in a million as a result of proposed delayed coker units (DCU) controls. The 

number of people with a cancer risk greater than 10-in-1 million from storage tank emissions 
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will be reduced from 3,000 to 60 and the number of people with a cancer risk greater than 1-

in-1 million from storage tank emissions will fall from 140,000 to 72,000 as a result of 

proposed storage tank controls. Similarly, a closer look at the controls driving the incidence 

reductions shows that approximately 15 percent (0.05 incidence) of the incidence reduction is 

attributable to proposed delayed coker units (DCU) controls and about 2 percent (0.01 

incidence) from proposed storage vessel controls.

The results of the post-control assessment also indicate that, based on actual emissions, there 

would be no reduction in chronic noncancer inhalation values because we did not identify any 

cost effective control technologies that would further reduce these risks. There is a slight 

reduction in acute noncancer inhalation values, with the maximum off-site HQ reduced from 

5 (actual emissions) to 3 (post-control emissions), based on the REL for nickel compounds. 

Considering post-control emissions of multipathway HAP, there are expected to be minimal 

reductions in PB-HAP with the control scenario (see Appendix 5 - Table 4b). 

4 General discussion of uncertainties and how they have been 

addressed

4.1 Exposure modeling uncertainties

Although every effort has been made to identify all the relevant facilities and emission points, 

as well as to develop accurate estimates of the annual emission rates for all relevant HAP, the 

uncertainties in our emission inventory likely dominate the uncertainties in the exposure

analysis. The chronic ambient modeling uncertainties are considered relatively small in 

comparison, 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. 

Additionally, estimates of the MIR contain uncertainty, because they are derived at census 

block centroid locations rather than actual residences. This uncertainty is known to create 

potential underestimates and overestimates of the actual MIR values for individual facilities, 

but, overall, it is not thought to have a significant impact on the estimated MIR for a source 

category. Finally, we did not factor in the possibility of a source closure occurring during the 

70-year chronic exposure period, leading to a potential upward bias in both the MIR and 

population risk estimates; nor did we factor in the possibility of population growth during the 

70-year chronic exposure period, leading to a potential downward bias in both the MIR and 

population risk estimates.

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 percent below the predicted value to as much as 84 percent 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 percent lower to 84

percent higher than the predicted values.
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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. Furthermore, in cases where multiple acute threshold values are 

considered scientifically acceptable we have chosen the most conservative of these threshold 

values, erring on the side of overestimating potential health risks from acute exposures. In the 

cases where these results indicated the potential for exceeding short-term health thresholds, 

we refined our assessment by developing a better understanding of the geography of the 

facility relative to potential exposure locations. 

4.2 Uncertainties in the dose-response relationships

In the sections that follow, separate discussions are provided on uncertainty associated with 

cancer potency factors and for noncancer reference values. Cancer potency values are derived 

for chronic (lifetime) exposures. Noncancer reference values are generally derived for 

chronic exposures (up to a lifetime), but may also be derived for acute ( -

term (>24 hours up to 30 days), and subchronic (>30 days up to 10 percent of lifetime) 

exposure durations, all of which are derived based on an assumption of continuous exposure 

throughout the duration specified. For the purposes of assessing all potential health risks 

associated with the emissions included in an assessment, we rely on both chronic (cancer and 

noncancer) and acute (noncancer) benchmarks, which are described in more detail below.

Although every effort is made to identify peer-reviewed dose-response values for all HAP

emitted by the source category included in an assessment, some HAP have no peer-reviewed 

cancer potency values or reference values for chronic non-cancer or acute effects (inhalation 

or ingestion). Since exposures to these pollutants cannot be included in a quantitative risk 

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

possible.

Additionally, chronic dose-response values for certain compounds included in the assessment 

may be under EPA IRIS review and revised assessments may determine that these pollutants 

are more or less potent than currently thought. We will re-evaluate risks if, as a result of these 

reviews, a dose-response metric changes enough to indicate that the risk assessment may 

significantly mischaracterize human health risk

Cancer assessment

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

on the uncertainties associated with the specific approach currently used by the EPA to 

develop cancer potency factors. In general, these same uncertainties attend the development 

of cancer potency factors by CalEPA, the source of peer-reviewed cancer potency factors 

used where EPA-developed values are not yet available. To place this discussion in context, 

we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [41] (herein 

referred to as Cancer Guidelines). “The primary goal of EPA actions is protection of human 

health; accordingly, as an Agency policy, risk assessment procedures, including default 

options that are used in the absence of scientific data to the contrary, should be health 
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protective.” The approach adopted in this document is consistent with this approach as 

described in the Cancer Guidelines.

For cancer endpoints EPA usually derives an oral slope factor for ingestion and a unit risk 

value for inhalation exposures. These values allow estimation of a lifetime probability of 

developing cancer given long-term exposures to the pollutant. Depending on the pollutant 

being evaluated, EPA relies on both animal bioassay and epidemiological studies to 

characterize cancer risk. As a science policy approach, consistent with the Cancer 

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

when other human cancer risk data are unavailable. 

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

EPA’s assessment of the scientific database for a pollutant using EPA’s guidance documents 

and other peer-reviewed methodologies. The EPA Cancer Guidelines describes the Agency’s 

recommendations for methodologies for cancer risk assessment. EPA believes that cancer 

risk estimates developed following the procedures described in the Cancer Guidelines and 

outlined below generally provide an upper bound estimate of risk. That is, EPA’s upper 

bound estimates represent a “plausible upper limit to the true value of a quantity” (although 

this is usually not a true statistical confidence limit).24 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.25 

When developing an upper bound estimate of risk and to provide risk values that do not 

underestimate risk, EPA generally relies on conservative default approaches.26 EPA also 

uses the upper bound (rather than lower bound or central) estimates in its assessments, 

although it is noted that this approach can have limitations for some uses (e.g. priority setting, 

expected benefits analysis).

Such health risk assessments have associated uncertainties, some which may be considered 

quantitatively, and others which generally are expressed qualitatively. Uncertainties may vary 

substantially among cancer risk assessments associated with exposures to different pollutants, 

since the assessments employ different databases with different strengths and limitations and 

the procedures employed may differ in how well they represent actual biological processes for 

the assessed substance. EPA’s Risk Characterization Handbook also recommends that risk 

characterizations present estimates demonstrating the impact on the assessment of alternative 

 

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

25 The exception to this is the URE for benzene, which is considered to cover a range of values, each end of 

which is considered to be equally plausible, and which is based on maximum likelihood estimates.

26 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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choices, data, models and assumptions [42]. Some of the major sources of uncertainty and 

variability in deriving cancer risk values are described more fully below. 

(1) The qualitative similarities or differences between tumor responses observed in 

experimental animal bioassays and those which would occur in humans are a source of 

uncertainty in cancer risk assessment. In general, EPA does not assume that tumor sites 

observed in an experimental animal bioassay are necessarily predictive of the sites at which 

tumors would occur in humans.27 However, unless scientific support is available to show 

otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target 

organ concordance. For a specific pollutant, qualitative differences in species responses can 

lead to either under-estimation or over-estimation of human cancer risks. 

(2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead 

to differences in risk predictions. For example, the measure of dose is commonly expressed 

in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, data may 

support development of a pharmacokinetic model for the absorption, distribution, metabolism 

and excretion of an agent, which may result in improved dose metrics (e.g., average blood 

concentration of the pollutant or the quantity of agent metabolized in the body). Quantitative 

uncertainties result when the appropriate choice of a dose metric is uncertain or when dose 

metric estimates are themselves uncertain (e.g., as can occur when alternative 

pharmacokinetic models are available for a compound). Uncertainty in dose estimates may 

lead to either over or underestimation of risk.

(3) For the quantitative extrapolation of cancer risk estimates from experimental animals to 

humans, EPA uses scaling methodologies (relating expected response to differences in 

physical size of the species), which introduce another source of uncertainty. These 

methodologies are based on both biological data on differences in rates of process according 

to species size and empirical comparisons of toxicity between experimental animals and 

humans. For a particular pollutant, the quantitative difference in cancer potency between 

experimental animals and humans may be either greater than or less than that estimated by 

baseline scientific scaling predictions due to uncertainties associated with limitations in the 

test data and the correctness of scaled estimates. 

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, 

are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which 

there is a specified excess risk of cancer, which is used as the point of departure (or POD) for 

the remainder of the calculation. Statistical uncertainty in developing a POD using a 

benchmark dose (BMD) approach is generally addressed though use of the 95 percent lower 

confidence limit on the dose at which the specified excess risk occurs (the BMDL), 

decreasing the likelihood of understating risk. EPA has generally utilized the multistage 

model for estimation of the BMDL using cancer bioassay data (see further discussion below).

 

27 Per the EPA Cancer Guidelines: “The default option is that positive effects in animal cancer studies indicate 

that the agent under study can have carcinogenic potential in humans.” and “Target organ concordance is not a 

prerequisite for evaluating the implications of animal study results for humans.”
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(5) Extrapolation from high to low doses is an important, and potentially large, source of 

uncertainty in cancer risk assessment. EPA uses different approaches to low dose risk 

assessment (i.e., developing estimates of risk for exposures to environmental doses of an 

agent from observations in experimental or epidemiological studies at higher dose) depending 

on the available data and understanding of a pollutant’s mode of action (i.e., the manner in 

which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use 

of reliable, compound-specific, biologically-based risk models when feasible; however, such 

models are rarely available. The mode of action for a pollutant (i.e., the manner in which a 

pollutant causes cancer) is a key consideration in determining how risks should be estimated 

for low-dose exposure. A reference value is calculated when the available mode of action 

data show the response to be nonlinear (e.g., as in a threshold response). A linear low-dose 

(straight line from POD) approach is used when available mode of action data support a linear 

(e.g., nonthreshold response) or as the most common default approach when a compound’s 

mode of action is unknown. Linear extrapolation can be supported by both pollutant-specific 

data and broader scientific considerations. For example, EPA’s Cancer Guidelines generally 

consider a linear dose-response to be appropriate for pollutants that interact with DNA and 

induce mutations. Pollutants whose effects are additive to background biological processes in 

cancer development can also be predicted to have low-dose linear responses, although the 

slope of this relationship may not be the same as the slope estimated by the straight line 

approach. 

EPA most frequently utilizes a linear low-dose extrapolation approach as a baseline sciencepolicy choice (a “default”) when available data do not allow a compound-specific 

determination. This approach is designed to not underestimate risk in the face of uncertainty 

and variability. EPA believes that linear dose-response models, when appropriately applied 

as part of EPA’s cancer risk assessment process, provide an upper bound estimate of risk and 

generally provide a health protective approach. Note that another source of uncertainty is the 

characterization of low-dose nonlinear, non-threshold relationships. The National Academy 

of Sciences has encouraged the exploration of sigmoidal type functions (e.g., log-probit 

models) in representing dose response relationships due to the variability in response within 

human populations. Another National Research Council (NRC) report [43] suggests that 

models based on distributions of individual thresholds are likely to lead to sigmoidal-shaped 

dose-response functions for a population. This report notes sources of variability in the 

human population: “One might expect these individual tolerances to vary extensively in 

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

susceptibility factors...” Thus, if a distribution of thresholds approach is considered for a 

carcinogen risk assessment, application would depend on ability of modeling to reflect the 

degree of variability in response in human populations (as opposed to responses in bioassays 

with genetically more uniform rodents). Note also that low dose linearity in risk can arise for 

reasons separate from population variability: due to the nature of a mode of action and 

additivity of a chemical’s effect on top of background chemical exposures and biological 

processes.

As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight 

line approach from the BMDL. This is equivalent to using an upper confidence limit on the 

slope of the straight line extrapolation. The impact of the choice of the BMDL on bottom line 
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risk estimates can be quantified by comparing risk estimates using the BMDL value to central 

estimate BMD values, although these differences are generally not a large contributor to 

uncertainty in risk assessment (Subramaniam et. al., 2006) [44]. It is important to note that 

earlier EPA assessments, including the majority of those for which risk values exist today, 

were generally developed using the multistage model to extrapolate down to environmental 

dose levels and did not involve the use of a POD. Subramaniam et. al. (2006) also provide 

comparisons indicating that slopes based on straight line extrapolation from a POD do not 

show large differences from those based on the upper confidence limit of the multistage 

model.

(6) Cancer risk estimates do not generally make specific adjustments to reflect the variability 

in response within the human population — resulting in another source of uncertainty in 

assessments. In the diverse human population, some individuals are likely to be more 

sensitive to the action of a carcinogen than the typical individual, although compound-specific 

data to evaluate this variability are generally not available. There may also be important life 

stage differences in the quantitative potency of carcinogens and, with the exception of the 

recommendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic 

mode of action, risk assessments do not generally quantitatively address life stage differences. 

However, one approach used commonly in EPA assessments that may help address variability 

in response is to extrapolate human response from results observed in the most sensitive 

species and sex tested, resulting typically in the highest URE which can be supported by 

reliable data, thus supporting estimates that are designed not to underestimate risk in the face 

of uncertainty and variability.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure 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 values28 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 

 

28

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

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

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

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

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

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

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

of daily oral exposure (RfD) or 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.29 To derive values that are intended to be “without 

appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach [45], 

[46] 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 [47]. 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., inter-individual 

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 

 

29 See IRIS glossary
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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 

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. 
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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.

There is no RfD or other comparable chronic health benchmark value for lead compounds. 

Thus, to address multipathway human health and environmental risks associated with 

emissions of lead from this facility, ambient lead concentrations were compared to the 

NAAQS for lead. In developing the NAAQS for lead, EPA considered human health 

evidence reporting adverse health effects associated with lead exposure, as well as an EPA 

conducted multipathway risk assessment that applied models to estimate human exposures to 

air-related lead and the associated risk (73FR at 66979). EPA also explicitly considered the 

uncertainties associated with both the human health evidence and the exposure and risk 

analyses when developing the NAAQS for lead. For example, EPA considered uncertainties 

in the relationship between ambient air lead and blood lead levels (73FR at 66974), as well as 

uncertainties between blood lead levels and loss of IQ points in children (73FR at 66981). In 

considering the evidence and risk analyses and their associated uncertainties, the EPA 

Administrator noted his view that there is no evidence- or risk-based bright line that indicates 

a single appropriate level. Instead, he noted, there is a collection of scientific evidence and 

judgments and other information, including information about the uncertainties inherent in 

many relevant factors, which needs to be considered together in making this public health 

policy judgment and in selecting a standard level from a range of reasonable values (73FR at 

66998). In so doing, the Administrator decided that, a level for the primary lead standard of 

0.15 μg/m3, in combination with the specified choice of indicator, averaging time, and form, 

is requisite to protect public health, including the health of sensitive groups, with an adequate 

margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and 

exposure analyses, and their associated uncertainties can be found in EPA’s final rule revising 

the lead NAAQS (73 FR 66970-66981, November 12, 2008). 

We also note the uncertainties associated with the health-based (i.e., primary) NAAQS are 

likely less than the uncertainties associated with dose-response values developed for many of 

the other HAP, particularly those HAP for which no human health data exist. In 1988, EPA’s 

IRIS program reviewed the health effects data regarding lead and its inorganic compounds 

and determined that it would be inappropriate to develop an RfD for these compounds, 

saying, “A great deal of information on the health effects of lead has been obtained through 

decades of medical observation and scientific research. This information has been assessed in 

the development of air and water quality criteria by the Agency's Office of Health and 

Environmental Assessment (OHEA) in support of regulatory decision-making by the Office 

of Air Quality Planning and Standards (OAQPS) and by the Office of Drinking Water 

(ODW). By comparison to most other environmental toxicants, the degree of uncertainty 

about the health effects of lead is quite low. It appears that some of these effects, particularly 

changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral 

development, may occur at blood lead levels so low as to be essentially without a threshold. 

The Agency's RfD Work Group discussed inorganic lead (and lead compounds) at two 

meetings (07/08/1985 and 07/22/1985) and considered it inappropriate to develop an RfD for 
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inorganic lead.” EPA’s IRIS assessment for Lead and compounds (inorganic) (CASRN 7439-

92-1), http://www.epa.gov/iris/subst/0277.htm. 

We note further that because of the multi-pathway, multi-media impacts of lead, the risk 

assessment supporting the NAAQS considered direct inhalation exposures and indirect airrelated multi-pathway exposures from industrial sources like primary and secondary lead 

smelting operations. It also considered background lead exposures from other sources (like 

contaminated drinking water and exposure to lead-based paints). In revising the NAAQS for 

lead, we note that the Administrator placed more weight on the evidence-based framework 

and less weight on the results from the risk assessment, although he did find the risk estimates 

to be roughly consistent with and generally supportive of the evidence-based framework 

applied in the NAAQS determination (73FR at 67004). Thus, when revising the NAAQS for 

lead to protect public health with an adequate margin of safety, EPA considered both the 

evidence-based framework and the risk assessment, albeit to different extents.

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. National Emission Standards for Hazardous Air Pollutants. 

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2. US EPA, 2009. Risk and Technology Review (RTR) Risk Assessment Methodologies: For 

Review by the EPA’s Science Advisory Board with Case Studies – MACT I Petroleum 

Refining Sources and Portland Cement Manufacturing. EPA-452/R-09-006. 

http://www.epa.gov/ttn/atw/rrisk/rtrpg.html.

3. US EPA, 2010. SAB’s Response to EPA’s RTR Risk Assessment Methodologies. 

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PA-SAB-10-007-unsigned.pdf

4. US EPA, 2010. Memorandum from Dave Guinnup to Docket EPA-HQ-OAR-2010-0600, 

entitled, “EPA’s Actions in Response to Key Recommendations of the SAB Review of RTR 

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5. RTI International, 2012. Memorandum: Development of the Risk Model Input File Based 

Upon the Responses to Component 2 of the Petroleum Refinery Information Collection 

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7. 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.

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11. US EPA, 2005. 1999 National Air Toxics Risk Assessment. 

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for Describing Available Cancer Potency Factors, May 2005. 

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National Air Toxics Assessment. 

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24. US EPA, 2011. Table 2. Acute Dose-Response Values for Screening Risk Assessments 

(12/19/2011). Office of Air Quality Planning and Standards. 

http://www.epa.gov/ttn/atw/toxsource/table2.pdf

25. U.S. EPA, 2009. Graphical Arrays of Chemical-Specific Health Effect Reference Values for 

Inhalation Exposures [Final Report]. EPA/600/R-09/061, 2009. 

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

26 U.S. EPA. Mn and BTEX Reference Value Arrays (Final Reports). U.S. Environmental 
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Protection Agency, Washington, DC, EPA/600/R-12/047F, 2013. 

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27. CA Office of Environmental Health Hazard Assessment, 2000. All Acute Reference 

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28. American Industrial Hygiene Association, 2011. Current AIHA ERPG Values. 

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

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33. 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. 

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24.pdf

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36. US EPA, 2005. Science Policy Council Cancer Guidelines Implementation Workgroup 

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37. US EPA, 1986. Guidelines for the Health Risk Assessment of Chemical Mixtures. EPA-630-

R-98-002. http://www.epa.gov/NCEA/raf/pdfs/chem_mix/chemmix_1986.pdf
Draft Risk Assessment for the Petroleum Refining Source Sector –

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

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38. US EPA, 2000. Supplementary Guidance for Conducting Health Risk Assessment of 

Chemical Mixtures. EPA-630/R-00-002. 

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39. RTI International, 2012. Memorandum: Refinery Emissions and Risk Estimates for Modeled 

“Allowable” Emissions. From: Jeff Coburn, RTI International, To: Brenda Shine, 

EPA/OAQPS

40 Burger, J. 2002. Daily consumption of wild fish and game: Exposures of high end 

recreationists. International Journal of Environmental Health Research 12:343-354

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Protection Agency, Washington, DC, EPA/630/P-03/001F, 2005. 

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44. R.P. Subramaniam, P. White and V.J. Cogliano. 2006. Comparison of cancer slope factors 

using different statistical approaches, Risk Anal. Vol 26, p. 825–830.

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Application of Inhalation Dosimetry. 

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47. US EPA. 2002. A Review of the Reference Dose and Reference Concentration Processes. 

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