1

Residual Risk Assessment for the Shipbuilding and Ship Repair 

Operations Source Category

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

August 2011
2

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 human inhalation exposure ....................................................................7

2.4 Acute Risk Screening and Refined Assessments......................................................8

2.5 Multipathway and environmental risk screening......................................................9

2.6 Dose-Response Assessment ..................................................................................10

2.6.1 Sources of chronic dose-response information ...............................................10

2.6.2 Sources of acute dose-response information ..................................................17

2.7 Risk Characterization ............................................................................................21

2.7.1 General..........................................................................................................21

2.7.2 Mixtures........................................................................................................23

2.7.3 Facility-wide Risks........................................................................................23

3 Risk Results for the Shipbuilding and Ship Repair Operations Source Category........24

3.1 Source Category Description and Results..............................................................24

3.2 Risk Characterization ............................................................................................26

4 General Discussion of Uncertainties and How They Have Been Addressed...................29

4.1 Exposure Modeling Uncertainties..........................................................................29

4.2 Uncertainties in the Dose-Response Relationships.................................................30

5 References....................................................................................................................38

Index of Tables

Table 2.2-1 AERMOD version 09292 model options for RTR modeling ...............................5

Table 2.6-1 (a) Dose-Response Values for Chronic Inhalation Exposure to Carcinogens.....15

Table 2.6-1 (b) Dose-Response Values for Chronic Oral Exposure to Carcinogens.............15

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

.............................................................................................................................................16

Table 2.6-2 Dose-Response Values for Acute Exposure.......................................................20

Table 3.1-1 Summary of Emissions from the Shipbuilding and Ship Repair Operations 

Source Category and Availability of Dose-Response Values.................................................25

Table 3.2-1 Summary of Source Category Level Inhalation Risks for Shipbuilding and Ship 

Repair Operations.................................................................................................................27

Table 3.2-2 Summary of NPRM Acute Refined Results for Shipbuilding and Ship Repair 

Operations Facilities.............................................................................................................28

Table 3.2-3 Shipbuilding Source Category Contribution to Facility-Wide Cancer Risks ......29

Appendices

Appendix 1 Emissions Inventory Support Memorandum

Appendix 2 Technical Support Document for HEM-AERMOD Modeling

Appendix 3 Meteorological Data for HEM-AERMOD Modeling
3

Appendix 4 Analysis of data on short-term emission rates relative to long-term emission 

rates

Appendix 5 Technical Support Document for TRIM-Based Multipathway Screening 

Scenario for RTR: Summary of Approach and Evaluation

Appendix 6 Detailed Risk Modeling Results

Appendix 7 Acute Impacts Refined Analysis Figures

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

ERPG Emergency Response Planning Guideline

HAP Hazardous Air Pollutant

HEM Human Exposure Model

HI Hazard index

HQ Hazard quotient

IRIS Integrated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of action

NAC National Advisory Committee

NATA National Air Toxics Assessment

NEI National Emissions Inventory

NPRM Notice of Proposed Rulemaking

PB-HAP Persistent and Bioaccumulative - HAP

POM Polycyclic organic matter

REL Reference exposure level

RfC Reference concentration

RfD Reference dose

RTR Risk and Technology

TOSHI Target-organ-specific hazard index

URE Unit risk estimate
4

1 Introduction

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

addressing emissions of hazardous air pollutants (HAPs) from stationary sources. In the first 

stage, section 112(d) 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. 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. 

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

implementation of the respective MACT standards) performed for the Shipbuilding and Ship 

Repair Operations source category. The methods discussion includes descriptions of the 

methods used to develop refined estimates of chronic inhalation exposures and human health 

risks for cancer and 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. Since none of the screening assessments indicated any significant potential for 

chronic non-inhalation health effects or environmental impacts, including effects to threatened 

and endangered species, no further refinement of these assessments was performed.

2 Methods

2.1 Emissions and source data

The 2005 National-Scale Air Toxics Assessment (NATA) National Emissions Inventory 

(NEI) served as the starting point for this assessment. The 2005 NEI contains information on 
5

actual emissions during the entire 2005 base year. Using the process MACT code1, we 

developed a subset of this inventory that contains emissions and facility data for the 

Shipbuilding and Ship Repair Operations source category. Next, we performed an 

engineering review of the information using EPA engineers who were directly involved in the 

development of the MACT standards for the source category, and/or who have extensive 

knowledge of the characteristics of this industry. NEI data was updated with industry 

supplied data as available. The goal of the engineering review was to identify readilyapparent limitations and issues with the emissions data (particularly those that would have the 

potential to influence risk estimates) and to make changes to the data set where possible to 

address these issues and decrease the uncertainties associated with the assessment. 

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

discussed in Section 3. The emissions data and modifications made to the NEI data are 

discussed in the Appendix 1, entitled ―Emissions Inventory Support Memorandum.‖ 

2.2 Dispersion modeling for inhalation exposure assessment

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

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

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

dispersion modeling system (HEM-AERMOD). The approach used in applying this modeling 

system is outlined below, and further details are provided in Appendix 2. HEM-AERMOD 

performs three main operations: atmospheric dispersion modeling, estimation of individual 

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

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

discussed in other subsections of Sections 2 and 3.

The dispersion model in the HEM-AERMOD system, AERMOD version 09292, is a state-ofthe-science Gaussian plume dispersion model that is preferred by EPA for modeling point, 

area, and volume sources of continuous air emissions from facility applications [3]. Further 

details on AERMOD can be found in the AERMOD Users Guide [4]. The model is used to 

develop annual average ambient concentrations through the simulation of hour-by-hour 

dispersion from the emission sources into the surrounding atmosphere. Hourly emission rates 

used for this simulation are generated by evenly dividing the total annual emission rate from 

the inventory into the 8,760 hours of the year.

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

concentrations at locations of interest. The AERMOD model options employed are 

summarized in Table 2.2-1 and are discussed further below.

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

Modeling Option Selected Parameter for chronic exposure

 

1 The tagging of data with MACT codes allows EPA to determine reductions attributable to the MACT program. 

The NEI associates MACT codes corresponding to MACT source categories with stationary major and area 

source data. MACT codes are assigned at the process level for the point source. 
6

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point, area represented as pseudo point source

Receptor orientation Polar (13 rings and 16 radials)

Discrete (census block centroids)

Terrain characterization Actual from USGS 1-degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option No

Meteorology 1 year representative NWS from nearest site (158 stations)

In HEM-AERMOD, meteorological data are selected from a list of 158 National Weather 

Service (NWS) surface observation stations across the continental United States, Alaska, 

Hawaii, and Puerto Rico. In most cases the nearest station is selected as representative of the 

conditions at the subject facility. Ideally, when considering off-site meteorological data most 

site specific dispersion modeling efforts will employ up to five years of data to capture 

variability in weather patterns from year to year. However, because we had insufficient 

number of appropriately formatted model input files derived from available meteorological 

data, we modeled only a single year, typically 1991. While the selection of a single year may 

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

in over-prediction at others. For each facility identified by its characteristic latitude and 

longitude coordinates, the closest meteorological station was used in the dispersion modeling. 

The average distance between a modeled facility and the applicable meteorological station 

was 40 miles (72 km). Appendix 3 (Meteorological Data Processing Using AERMET for 

HEM-AERMOD) provides a complete listing of stations and assumptions along with further 

details used in processing the data through AERMET. The sensitivity of model results to the 

selection of the nearest weather station and the use of one year of meteorological data is 

discussed in ―Risk and Technology Review (RTR) Risk Assessment Methodologies‖ [2].

The HEM-AERMOD system estimates ambient concentrations at the geographic centroids of 

census blocks (using the 2000 Census), and at other receptor locations that can be specified by 

the user. The model accounts for the effects of multiple facilities when estimating 

concentration impacts at each block centroid. Typically we combined only the impacts of 

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

census blocks with at least one resident (i.e., locations where people may reasonably be 

assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient 

concentrations were calculated as the annual average of all estimated short-term (one-hour) 

concentrations at each block centroid. Possible future residential use of currently uninhabited 

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

are typically comprised of approximately 40 people or about ten households. 
7

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

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

concentrations were estimated both at the census block centroids and at points nearer the 

facility that represent locations where people may be present for short periods, but generally 

no nearer than 100 meters from the center of the facility (note that for large facilities, this 

100-meter ring could still contain locations inside the facility property). Since short-term 

emission rates were needed to screen for the potential for hazard via acute exposures, and 

since the NEI contains only annual emission totals, we generally apply the general assumption 

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

times the average annual hourly emission rate for that source.

The average hourly emissions rate is defined as the total emissions for a year divided by the 

total number of operating hours in the year. This choice of a factor of ten for screening was 

originally based on engineering judgment. To develop a more robust peak-to-mean emissions 

factor, and in response to one of the key messages from the SAB consultation on our RTR 

Assessment Plan, we performed an analysis using a short-term emissions dataset from a 

number of sources located in Texas (originally reported on by Allen et al. 2004)[5]. In that 

report, the Texas Environmental Research Consortium Project compared hourly and annual 

emissions data for volatile organic compounds for all facilities in a heavily-industrialized 4-

county area (Harris, Galveston, Chambers, and Brazoria Counties, TX) over an eleven-month 

time period in 2001. We obtained the dataset and performed our own analysis, focusing that 

analysis on sources which reported emitting high quantities of HAP over short periods of time

(see Appendix 4, ―Analysis of data on short-term emission rates relative to long-term 

emission rates‖). Most peak emission events were less than twice the annual average, and the 

highest was a factor of 11 times the annual average. Based on these results, we chose the 

factor of ten for all initial screening; it is intended to cover routinely-variable emissions as 

well as startup, shutdown, and malfunction (SSM) emissions. While there have been some 

documented emission excursions above this level, our analysis of the data from the Texas 

Environmental Research Consortium suggests that this factor should cover more than 99% of 

the short-term peak gaseous or volatile HAP emissions from typical industrial sources. 

 

Census block elevations for HEM-AERMOD modeling were determined nationally from the 

US Geological Service 1-degree digital elevation model (DEM) data files, which have a 

spatial resolution of about 90 meters. Polar grid elevations (used in estimating short- and 

long-term ambient concentrations) were evaluated at the highest elevation of any census block 

in that sector. If a sector does not contain any blocks, the model defaults to the elevation of 

the nearest block. If the elevation is not provided for the emission source, the model takes the 

average elevation of all sectors of the nearest model ring.

In addition to using receptor elevation to determine plume height, AERMOD adjusts the 

plume’s flow if nearby elevated hills are expected to influence the wind patterns. For details 

on how hill heights were estimated and used in the AERMOD modeling see Appendix 2. 

2.3 Estimating human inhalation exposure

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

centroid as a surrogate for the lifetime inhalation exposure concentration of all the people who 
8

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 for two reasons. First, our experience with the 

1996, 1999, 2002, and 2005 NATA assessments (which modeled daily activity using EPA’s 

HAPEM model) suggests that, given our current understanding of microenvironment 

concentrations and daily activities, modeling short-term activity would, on average, reduce 

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

HAPs, but typically by much less. Second, basing exposure estimates on average ambient 

concentrations at census block centroids may underestimate or overestimate actual exposure 

concentrations at some residences. Further reducing exposure estimates for the most highlyexposed 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; 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 nor 

does it affect the estimate of cancer incidence since the total population number remains the 

same. It does, however, affect the shape of the distribution of individual risks across the 

affected population, shifting it toward higher estimated individual risks at the upper end and 

reducing the number of people estimated to be at lower risks, thereby biasing the risk 

estimates high. When screening for potentially significant acute exposures, we used an 

estimate of the highest hourly ambient concentration at any off-site location as the surrogate 

for the maximum potential acute exposure concentration for any individual.

2.4 Acute Risk Screening and Refined Assessments

In establishing a scientifically-defensible approach for the assessment of potential health risks 

due to acute exposures to HAP, we followed the same general approach that has been used for 

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

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

been endorsed by the National Academy of Sciences in its 1993 publication ―Science and 

Judgment in Risk Assessment‖ and subsequently was endorsed in the EPA’s ―Residual Risk 

Report to Congress‖ in 1999. 

The assessment methodology is designed to eliminate from further consideration those 

facilities for which we have confidence that no acute adverse health effects of concern will 

occur. To do so, we use what is called a tiered, iterative approach to the assessment. This 

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

uses conservative assumptions that in combination approximate a worst-case exposure. The 

result of this screening process is that either the facility being assessed poses no acute health 

risks (i.e., it ―screens out‖), or that it requires further, more refined assessment. A refined 
9

assessment could use industry- or site-specific data on the temporal pattern of emissions, the 

layout of emission points at the facility, the boundaries of the facility, and/or the local 

meteorology. In some cases, all of these site-specific data would be needed to refine the 

assessment; in others, lesser amounts of site-specific data could be used to determine that 

acute exposures are not a concern, and significant additional data collection would not be 

necessary. 

Acute health risk screening was performed as the first step. We used conservative 

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

worst-case assumptions in our screening approach:

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

rates.

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

occur at all emission points at the same time.

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

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

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

hour. 

Worst-case meteorology (from one year of local meteorology) was assumed to occur 

at the same time the peak emission rates occur. The recommended EPA local-scale 

dispersion model, AERMOD, is used for simulating atmospheric dispersion.

A person was assumed to be located downwind at the point of maximum impact 

during this same 1-hour period, but no nearer to the source than 100 meters.

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

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

benchmarks are described in the next section of this report.

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

benchmarks, we pursue refining our acute screening estimates. In some cases, this includes 

use of a refined emissions multiplier to estimate the peak hourly emission rates from the 

average rates.

2.5 Multipathway and environmental risk screening

The potential for significant human health risks due to exposures via routes other than 

inhalation (i.e., multipathway exposures) was screened by first determining whether any 

sources emitted any hazardous air pollutants known to be persistent and bioaccumulative in 

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

the screening from the EPA’s Air Toxics Risk Assessment Library [6], and they are cadmium 

compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, heptachlor, 

hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury compounds, 

methoxychlor, polychlorinated biphenyls, polycyclic organic matter (POM), toxaphene, and 

trifluralin. Emissions of 3 different PB HAP were identified in the emissions inventory for 

the Shipbuilding and Ship Repair Operations source category; they are POM, lead, and 

cadmium. These emissions were evaluated for potential non-inhalation risks and adverse 

environmental impacts using our recently-developed screening scenario which was developed 
10

for use with the TRIM.FaTE2 model. This screening scenario uses environmental media 

outputs from the peer-reviewed TRIM.FaTE to estimate the maximum potential ingestion 

risks for any specified emission scenario by using a generic farming/fishing exposure scenario 

that simulates a subsistence environment. The screening scenario retains many of the 

ingestion and scenario inputs developed for EPA’s Human Health Risk Assessment Protocols 

(HHRAP) for hazardous waste combustion facilities.3 In the development of the screening 

scenario a sensitivity analysis was conducted to ensure that its key design parameters were 

established such that environmental media concentrations were not underestimated, and to 

also minimize the occurrence of false positives for human health endpoints. See Appendix 5 

for a complete discussion of the development and testing of the screening scenario, as well as 

for the values of facility-level de minimis emission rates developed for screening potentially 

significant multi-pathway impacts.. For the purpose of developing de minimis emission rates 

for our multi-pathway screening, we derived emission levels for each PB HAP at which the 

maximum human health risk would be 1 in a million for lifetime cancer risk or a hazard 

quotient of 1.0 for noncancer impacts. In evaluating the potential multi-pathway risks from 

emissions of lead compounds, rather than developing a de minimis emission rate, we 

compared maximum estimated chronic (3-month average) 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 multi-pathway risks of any significance.

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

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

facilities. Human health dose-response threshold values are generally derived from studies 

conducted on laboratory animals (such as rodents) and developed with the inclusions of 

uncertainty factors that could be as high as 3000. As a result, these human threshold values 

are often significantly lower than the level expected to cause an adverse effect in an exposed 

rodent. It should be noted that there is a scarcity of data on the direct atmospheric impact of 

these HAPs on other receptors, such as plants, birds, and wildlife. Thus, if the maximum 

inhalation hazard in an ecosystem is below the level of concern for humans, we have 

generally concluded that mammalian receptors should be at no risk of adverse effects due to 

inhalation exposures from non PB-HAP, and have assurance that other ecological receptors 

are also not at any significant risk from direct atmospheric impact. In some isolated cases 

where we have data indicating potential adverse impacts on plants, birds, or other wildlife due 

to the direct atmospheric impacts of specific HAPs, we note that as an uncertainty and, where 

possible, refine our analysis by comparing our modeled impacts to available threshold values 

from the scientific literature.

2.6 Dose-Response Assessment

2.6.1 Sources of chronic dose-response information 

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

by inhalation or ingestion) for the HAPs reported in the emissions inventory for Shipbuilding 

 

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

3 EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous Waste Combustion Facilities;

http://www.epa.gov/epaoswer/hazwaste/combust/riskvol.htm#volume1
11

and Ship Repair Operations sources were based on the EPA Office of Air Quality Planning 

and Standards’ existing recommendations for HAPs [7], also used for NATA 1999, 2002, and 

2005 [8]. This information has been obtained from various sources and prioritized according 

to (1) conceptual 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 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% 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) [9] 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 

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) [10] 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 
12

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 assessments4: ―The 

guidelines for developing chronic inhalation exposure levels incorporate many 

recommendations of the U.S. EPA [11] and NAS [12].‖ The non-cancer information 

includes available inhalation health risk guidance values expressed as chronic inhalation 

reference exposure levels (RELs) [13]. 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 [14], defined similarly to EPA's URE.

 

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

on professional judgment, as follows: 

1) 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 HAPs that lack doseresponse values may pose an unacceptable risk and require further examination, or screen 

out from further assessment. 

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) In 2004, the EPA determined that the Chemical Industry Institute of Toxicology (CIIT) 

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

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

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

 regulatory actions. However, subsequent research published by the EPA suggests that the 

 CIIT model was not appropriate and in 2010 EPA returned to using the 1991 IRIS value, 

 which is more health protective.[ ] 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 in May of 2011. EPA is reviewing the public comments and the NAS 

 independent scientific peer review, and the draft IRIS assessment will be revised and the 

 

4 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III - Technical Support Document

for the Determination of Non-cancer Chronic Reference Exposure Levels. Air Toxicology and Epidemiology 

Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. 

February 2000 (http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf)
13

 final assessment will be posted on the IRIS database. In the interim, we will present 

 findings using the 1991 IRIS value as a primary estimate, and may also consider other

 information as the science evolves.

4) The IRIS URE for nickel inhalation was derived from evidence of the carcinogenic effects

 of insoluble nickel compounds in crystalline form. Soluble nickel species, and insoluble 

 species in amorphous form, do not appear to produce genotoxic effects by the same toxic 

 mode of action as insoluble crystalline nickel. Nickel speciation information for some of 

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

 others) suggests that at least 35% of total nickel emissions may be soluble compounds. 

 The remaining insoluble nickel emissions are not well-characterized. Consistent with this 

 limited information, this assessment will conservatively assume that 65% of emitted 

 nickel is insoluble and that all insoluble nickel is crystalline. The nickel URE (based on 

 nickel subsulfide, and representative of pure insoluble crystalline nickel) was adjusted to 

 reflect an assumption that 65% of the total mass of nickel may be carcinogenic. The 

 noncancer dose-response values were not adjusted because noncancer effects of nickel are 

 not thought to be limited to the crystalline, insoluble form.

5) A substantial proportion of POM reported to EPA’s national emission inventory (NEI) are 

 not speciated into individual compounds. As a result, it is necessary to apply the same 

 simplifying assumptions to assessments that were used for the 1999 NATA study [15]. 

 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. 

6) For carcinogenic substances, that lack inhalation assessments, oral carcinogenic potency 

 estimates are converted to inhalation UREs. The conversion from oral risk (per mg/kg/d 

 oral intake) to inhalation risk (per μg/m3inhaled) is based on EPA’s standard assumptions 

 of a 70-kg body mass and 20 m3/d inhalation rate, as follows:

Where: URE = Unit risk estimate for inhalation (risk per μg/m3)

CPS = Carcinogenic potency slope for ingestion (risk per mg oral intake per 

kg body mass per day)

 EPA understands that conversion of oral dose-response information to inhalation exposure 

may add significant uncertainty to the resulting risk estimates. However, the alternative to 

this would be to omit these substances from quantitative inhalation risk estimates altogether, 

thereby making a de facto assumption of zero carcinogenic potency. For the purposes of the 

residual risk assessment, EPA prefers to use the approach described above to screen these 

carcinogens for their potential contributions to risk. If a substance is determined to be a 

potentially important contributor to risk, it will be prioritized for further dose-response 

development through EPA’s IRIS process.

g

mg

d

m

k g d k g

mg CPS

m

g

URE

1000

1

20

70

1

3

1 1

3
14

The emissions inventory for the shipbuilding and ship repair source category includes 

emissions of 30 HAP with available chronic quantitative inhalation dose-response values. 

These HAP, their dose-response values, and the source of the values are listed in Tables 2.6-1 

(a) through (c).
15

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/m3of average lifetime exposure. 

Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of 

Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the 

EPA Office of Air Quality Planning and Standards.

Pollutant CAS Number6 URE5

(1/μg/m3)

Source

Acetaldehyde 75070 2.2E-06 IRIS

Benzene771432 7.8E-06 IRIS

p-Dichlorobenzene 106467 1.1E-05 CAL

Epichlorohydrin 106898 1.2E-06 IRIS

Ethyl benzene 100414 2.5E-6 CAL

Formaldehyde 50000 1.3E-05 IRIS

4,4-Methylene bis(2-chloroaniline) 101144 4.3E-04 CAL

Methylene chloride 75092 4.7E-07 IRIS

Naphthalene 91203 3.4E-05 CAL

Polycyclic Organic Matter 246 8EPA OAQPS

 - Benzo(a)anthracene 56553 1.1E-04 EPA OAQPS

 - Benzo(a)pyrene 50328 1.1E-03 EPA OAQPS

 - Benzo(b)fluoranthene 205992 1.1E-04 EPA OAQPS

 - Benzo(k)fluoranthene 207089 1.1E-04 EPA OAQPS

 - Chrysene 218019 1.1E-05 EPA OAQPS

 - Dibenzo(a,h)anthracene 53703 1.2E-03 EPA OAQPS

 - Indeno(1,2,3-cd)pyrene 193395 1.1E-04 EPA OAQPS

Trichloroethylene 79016 2.0E-06 CAL

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

 

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 HAPs.

7 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.

8 Assigned the URE associated with a mixture of POM compounds having a similar potency. Details of this 

method, also used in the 1999 National Air Toxics Assessment, are available at 

http://www.epa.gov/ttn/atw/nata1999/99pdfs/pomapproachjan.pdf
16

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/OAQPS = interim value recommended by the EPA Office of Air Quality 

Planning and Standards.

Pollutant CAS Number10

SF

(1/mg/kg/d) Source

Polycyclic organic matter (POM) 246 0.5 EPA OAQPS

 - Benzo(a)anthracene 56553 1 EPA OAQPS

 - Benzo(a)pyrene 50328 7 EPA OAQPS

 - Benzo(b)fluoranthene 205992 1 EPA OAQPS

 - Benzo(k)fluoranthene 207089 1 EPA OAQPS

 - Chrysene 218019 0.1 EPA OAQPS

 - Dibenz(a,h)anthracene 53703 4 EPA OAQPS

 - Indeno(1,2,3-cd)pyrene 193395 1 EPA OAQPS

Table 2.6-1 (c) 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, HEAST = EPA Health Effects Assessment Summary Table

Pollutant CAS Number6 RfC 

(mg/m3)

Source9

Acetaldehyde 75070 0.009 IRIS -- L

Acrolein 107-02-8 0.00002 IRIS - H

Benzene 71432 0.03 IRIS – M

Chlorobenzene 108907 1 CAL

Chloroprene 126998 0.007 HEAST

Cumene 98828 0.4 IRIS – L

p-Dichlorobenzene 106467 0.8 IRIS – M

Epichlorohydrin 106898 0.001 IRIS – M

Ethyl benzene 100414 1 IRIS – L

Ethylene glycol 107211 0.4 CAL

Formaldehyde 50000 0.0098 ATSDR

Glycol Ethers 10 181 0.02 IRIS – M

 - Diethylene glycol monobutyl ether (DEGBE) 112345 0.02 HEAST

 - Ethylene glycol ethyl ether 110805 0.2 IRIS - M

 - Ethylene glycol methyl ether (EGME) 109864 0.02 IRIS - M

 - 2-Butoxyethyl acetate * 112072 0.02

 - Ethylene glycol ethyl ether acetate 111159 0.3 CAL

 

9 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.

10The RfC value for ethylene glycol methyl ether (EGME) was used as a surrogate for all glycol ethers without 

an RfC; (denoted with an *).
17

Table 2.6-1 (c) 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, HEAST = EPA Health Effects Assessment Summary Table

Pollutant CAS Number6 RfC 

(mg/m3)

Source9

 - Methoxytriglycol * 112356 0.02

Hexamethylene-1,6-diisocyanate 822060 0.00001 IRIS - L

n-Hexane 110543 0.7 IRIS – M

Hydrochloric acid 7647010 0.02 IRIS – L

Hydrofluoric acid 7664393 0.014 CAL

Methanol 67561 4 CAL

Methyl isobutyl ketone 108101 3 IRIS – L/M

Methylene chloride 75092 1 ATSDR

Naphthalene 91203 0.003 IRIS – M

Phenol 108952 0.2 CAL

Styrene 100425 1 IRIS – M

Toluene 108883 5 IRIS – H

Methyl Chloroform (1,1,1-Trichloroethane) 71556 5 IRIS

Trichloroethylene 79016 0.6 CAL

Vinyl acetate 108054 0.2 IRIS – H

Xylenes (mixed) 1330207 0.1 IRIS – M

m-Xylene11 108383 0.1 IRIS – M

o-Xylene1195476 0.1 IRIS – M

p-Xylene11106423 0.1 IRIS – M

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 

HAPs [16]. Depending on availability, the results from screening acute assessments are 

compared to both ―no effects‖ reference levels for the general public, such as the California 

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

Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelines 

(ERPGs), with the recognition that emergency response values are not an equivalent substitute 

for RELs and that the ultimate interpretation of any potential risks associated with an 

estimated exceedance of a particular reference level depends on the definition of that level 

and any limitations expressed therein. Comparisons among different available inhalation 

health effect reference values (both acute and chronic) for selected HAPs can be found in a 

newly released EPA document (Reference: U.S. EPA. Graphical Arrays of ChemicalSpecific Health Effect Reference Values for Inhalation Exposures [Final Report]. (U.S. 

 

11 The RfC for mixed xylene was used as a surrogate.
18

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

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

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

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

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

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

―the concentration level at or below which no adverse health effects are anticipated for a 

specified exposure duration. [17]. RELs are based on the most sensitive, relevant, 

adverse health effect reported in the medical and toxicological literature. RELs are 

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

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

uncertainties, exceeding the REL does not automatically indicate an adverse health 

impact.‖ Acute RELs are developed for 1-hour (and 8-hour) exposures. The values 

incorporate uncertainty factors similar to those used in deriving EPA’s Inhalation 

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

developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs). AEGLs are developed by the National Advisory 

Committee (NAC) on Acute Exposure Guideline Levels for Hazardous Substances, and then 

reviewed and published by the National Research Council As described in the Committee’s 

―Standing Operating Procedures (SOP)‖ (http://www.epa.gov/opptintr/aegl/pubs/sop.pdf),

AEGLs ―represent threshold exposure limits for the general public and are applicable to 

emergency exposures ranging from 10 min to 8 h.‖ Their intended application is ―for 

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

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

releases at fixed facilities and from transport carriers.‖ The document states that ―the primary 

purpose of the AEGL program and the NAC/AEGL Committee is to develop guideline levels 

for once-in-a-lifetime, short-term exposures to airborne concentrations of acutely toxic, highpriority chemicals.‖ In detailing the intended application of AEGL values, the document 

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

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

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

programs.‖ It is important to note that a potential for effects exists even if the airborne 

concentration is below the AEGL-1 value. 

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

―AEGL-1 is the airborne concentration (expressed as ppm or mg/m3) of a substance above 

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

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

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

exposure.‖
19

―AEGL-2 is the airborne concentration (expressed as ppm or mg/m3) of a substance above 

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

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

ability to escape.‖

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

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

irritation or certain asymptomatic, nonsensory effects. With increasing airborne 

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

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

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

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

other illnesses, it is recognized that individuals, subject to unique or idiosyncratic 

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) [18] 

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

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

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

irreversible or serious (ERPG-2), and potentially life-threatening (ERPG-3). 

ERPG values (http://www.aiha.org/1documents/Committees/ERP-erpglevels.pdf) are

described in their supporting documentation as follows: ―Emergency Response Planning 

Guidelines (ERPGs) were developed for emergency planning and are intended as health based 

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

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

adequacy of accident prevention and emergency response plans, including transportation 

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

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

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

levels, these levels reflect consideration of only single exposure events, not repeated 

exposures. 

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

―ERPG-1 is the maximum airborne concentration below which it is believed that nearly all 

individuals could be exposed for up to 1 hour without experiencing other than mild 

transient adverse health effects or without perceiving a clearly defined, objectionable 

odor.‖

―ERPG-2 is the maximum airborne concentration below which it is believed that nearly all 

individuals could be exposed for up to 1 hour without experiencing or developing 

irreversible or other serious health effects or symptoms which could impair an individual's 

ability to take protective action.‖
20

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

The emissions inventory for the Shipbuilding and Ship Repair Operations source category

includes emissions of 23 HAP with relevant and available quantitative acute dose-response 

threshold values. These HAPs, their acute threshold values, and the source of the value are 

listed below in Table 2.6-2.

Table 2.6-2 Dose-Response Values for Acute Exposure

Pollutant

CAS 

Number

AEGL-1

(1-hr)

(mg/m3)

AEGL-2

(1-hr)

(mg/m3)

ERPG-1

(mg/m3)

ERPG-2

(mg/m3) REL 

Acetaldehyde 75070 81 490 81 490 0.47

Acrolein 107028 0.069 0.23 0.069 0.23 0.0025

Benzene 71432 170 2600 170 2600 1.3

Chlorobenzene 108907 46 690

Cumene 98828 250 1500

Epichlorohydrin 106898 22 91 22 91 1.3

Ethyl Benzene 100414 140 4800

Formaldehyde 50000 1.1 17 1.1 17 0.055

Glycol ethers12 0.093 

 - 2- Butoxyethyl Acetate * 112072 0.093

 - Ethylene Glycol Ethyl Ether 110805 0.37

 - Ethylene Glycol Ethyl Ether Acetate 111159 0.14

 - Ethylene Glycol Methyl Ether 109864 0.093

 - Diethylene Glycol Monobutyl Ether * 112345 0.093

Hexane 110543 12000

Hydrochloric acid 7647010 2.7 33 2.7 33 2.1

Hydrogen fluoride 7664393 0.82 20 0.82 20 0.24

Methanol 67561 690 2700 690 2700 28

Methyl Chloroform (1,1,1-

Trichloroethane) 71556 1300 3300 1300 3300 68

Methyl Isobutyl Ketone 108101

Methylene Chloride 75092 690 1900 690 1900 14

Phenol 108952 58 89 58 89 5.8

Styrene 100425 85 550 85 550 21

Toluene 108883 750 4500 190 1130 37

Trichloroethylene 79016 700 2400 700 2400

Vinyl Acetate 108054 24 630 18 260

Xylenes (mixed) 1330207 560 4000 22

 

12 The acute REL for ethylene glycol methyl ether (EGME) was used as a surrogate for glycol ether compounds 

without an acute REL.
21

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 [19] 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 [20], in 2002 by the Agency’s information quality guidelines [21], and in the 

OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis13, 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 HAPs 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 HAPs that act by a mutagenic mode-of-action [22], we applied 

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

Carcinogens [23]. 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 

 

13Memorandum for the Heads of Executive Departments and Agencies - Updated Principles for Risk Analysis

(September 19, 2007), From Susan E. Dudley, Administrator, Office of Information and Regulatory Affairs, 

Office of Management and Budget; and Sharon L. Hays, Associate Director and Deputy Director for Science, 

Office of Science and Technology Policy (http://www.whitehouse.gov/omb/memoranda/fy2007/m07-24.pdf)
22

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 [24] 

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.
23

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’ 

[25,26] 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 HAPs that act by similar 

toxic modes of action, or (where this information is absent) that affect the same target organ. 

This process creates, for each target organ, a target-organ-specific hazard index (TOSHI), 

defined as the sum of hazard quotients for individual HAPs that affect the same organ or 

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

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

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

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

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

included in the TOSHI calculations, some TOSHIs may have been underestimated. As with 

the HQ, the TOSHI should not be interpreted as a probability of adverse effects, or as strict 

delineation of ―safe‖ and ―unsafe‖ levels. Rather, the TOSHI is another measure of the 

potential for adverse health outcomes associated with pollutant exposure, and needs to be 

interpreted carefully by health scientists and risk managers.

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 

facility-wide and source category data files developed by EPA thru emission data updates 

from industry and refined EPA profiles for this source category. For the facilities in the 

Shipbuilding and Ship Repair Operations source category, we modeled facility-wide risks 

from these files, to estimate the maximum inhalation cancer and chronic non-cancer risks for 

all HAP emissions sources at the facility. These emissions include all sources that are located 

within a contiguous area and are under common control by the facility. 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 assessments are provided for in Table 2 of Appendix 

5. 
24

3 Risk Results for the Shipbuilding and Ship Repair Operations Source 

Category

3.1 Source Category Description and Results

The shipbuilding and ship repair operations industry consists of establishments that build, 

repair, repaint, convert, and alter ships. In general, activities and processes involved in ship 

repair and new ship construction are relatively similar. Operations include fabrication of 

basic components from raw materials, welding to join components and parts together, 

painting and repainting, overhauls, ship conversions, and other alterations. Nearly all 

shipyards that construct new ships also perform major ship repairs. Marine coatings used on 

offshore oil and gas well drilling and production platforms are not included in this source 

category. Emissions of hazardous air pollutants (HAP) from shipbuilding and ship repair 

facilities are primarily the result of emissions from painting operations and cleaning 

operations. The HAP emitted include a range of organic compounds used as solvents, 

including toluene, xylene, ethylbenzene, methanol, methyl isobutyl ketone, ethylene glycol, 

and glycol ethers.

We currently estimate that there are 90 shipbuilding and ship repair operations facilities 

operating in the U.S. The NPRM data set contains 85 facilities identified with a shipbuilding 

and ship repair operations (surface coating) MACT code in the 2005 National-Scale Air 

Toxics Assessment (NATA) National Emissions Inventory (NEI). While the NEI identifies 

44 of these 85 facilities as area sources of HAP (and 41 as major sources), the uncertainty 

associated with these major/area classifications is significant. Without verification of the area 

source status of individual facilities, EPA will consider all facilities in the NEI to be major 

sources in this and any future RTR risk assessments. 

 

The emissions for the shipbuilding and ship repair operations NPRM data set (of 85 facilities) 

are summarized in Table 3.1-1. The total HAP emissions for the source category are 

approximately 950 tons per year. Based on these data, the HAP emitted in largest quantities 

by the source category are xylenes, ethyl benzene, toluene, methanol, glycol ethers, and 

methyl isobutyl ketone. Emissions of these six HAP make up 99 percent of the total 

emissions by mass. Xylenes are reported as an emission at 82 facilities (96 percent); ethyl 

benzene and toluene are reported as emissions at 72 facilities (85 percent) and 68 facilities (80 

percent), respectively. Persistent and bioaccumulative HAP (PB HAP)14 emissions reported 

in the data set for the shipbuilding and ship repair source category include polycyclic organic 

matter (POM).

 

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

EPA-453K-04-001A, which is accessible from the EPA’s Technology Transfer Network website for Fate, 

Exposure, and Risk Assessment at http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 
25

Table 3.1-1 Summary of Emissions from the Shipbuilding and Ship Repair Operations Source 

Category and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (85

facilities in 

ANPRM 

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate for 

Cancer?

Reference 

Concentration 

for Noncancer?

Health 

Benchmark 

Values for Acute 

Noncancer?

Xylenes (Mixture of o, m, and 

p Isomers)

717 82

Ethyl Benzene 138 72

Toluene 55 68

Styrene 0.3 3

Methanol 13 7

Glycol Ethers 11 2

Methyl Isobutyl Ketone 5 11

Hexane 3 3

Methylene Chloride 2 1

Dibutylphthalate 1 5

Cumene 0.8 7

Phenol 0.2 4

Methyl Chloroform 0.03 2

Ethylene Glycol 0.2 3

Naphthalene 0.1 6

Diethylene Glycol Monobutyl 

ether

0.2 1

Benzene 0.08 3

Methoxytriglycol 0.1 1

Vinyl Acetate 0.08 1

Ethylene Glycol Methyl Ether 0.03 1

2-Butoxyethyl Acetate 0.03 1

Trichloroethylene 0.05 1

Chlorobenzene 0.04 1

Ethylene Glycol Ethyl Ether 

Acetate

0.02 1

Acetaldehyde 0.01 1

p-Dichlorobenzene 0.008 1

Chloroprene 0.007 1

Formaldehyde 0.007 2

POM 0.007 2 Y

Hydrochloric Acid 0.006 1

4,4’-Methylene bis(2-

chloroaniline)

0.002 1

Hydrogen Fluoride 0.0006 1

Epichlorohydrin 0.0005 1

Hexamethylene-1,6-

diisocyanate

0.0005 1
26

Table 3.1-1 Summary of Emissions from the Shipbuilding and Ship Repair Operations Source 

Category and Availability of Dose-Response Values

HAPa Emissions 

(tpy)

Number of 

Facilities 

Reporting 

HAP (85

facilities in 

ANPRM 

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP? Unit Risk 

Estimate for 

Cancer?

Reference 

Concentration 

for Noncancer?

Health 

Benchmark 

Values for Acute 

Noncancer?

Acrolein 0.0003 1

a

 Notes for how HAP were speciated for risk assessment

For emissions of any chemicals or chemical groups classified as polycyclic organic matter (POM), emissions were 

grouped into POM subgroups as found on EPA’s Technology Transfer Network website for the 2002 National-Scale Air 

Toxics Assessment at http://www.epa.gov/nata2002/methods.html#pom. (Approach to Modeling POM). 

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 and are also available in Appendix 5 of the Development of 

Preliminary Risk Estimates for Source Categories Previously Subjected to Technology-based Standards document.

3.2 Risk Characterization

This section presents the results of the preliminary risk assessment for the wood furniture

source category. 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 assessments in the form of maximum 

hazard quotients, as well as the results of our screen for potential non-inhalation risks from 

PB HAP. Also 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 a summary of the results of our facility-wide assessments and our analysis 

of risks associated with the maximum allowed emissions under the current MACT standards. 

A detailed summary of the facility-specific risk assessment results is available in Appendix 6.

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

this source category. The results of the chronic inhalation cancer risk assessment indicate the 

maximum lifetime individual cancer risk could be as high as 10 in a million. The maximum 

cancer risks for this source category exceeded a cancer risk of 1 in a million at 26 facilities, 

with emissions of ethylbenzene dominating the risk. The total estimated cancer incidence 

from this source category based on actual emission levels is 0.003 excess cancer cases per 

year, or one case in every 330 years. Approximately 20 people were estimated to have cancer 

risks above 10 in a million and approximately 3,700 people were estimated to have cancer 

risks above 1 in a million. 
27

Table 3.2-1 Summary of Source Category Level Inhalation Risks for Shipbuilding and Ship 

Repair Operations

Result HAP “Drivers”

Facilities in Source Category

Number of Facilities Estimated to be in Source 

Category 90 n/a

Number of Facilities Identified in the NEI and 

Modeled in Preliminary Risk Assessment 85 n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 1 

million) 10 ethyl 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 1 ethyl benzene

Greater than or equal to 1 in 1 million 26

ethyl benzene, naphthalene, 

methylene chloride

Chronic Noncancer Risks

Maximum Hazard Index (Neurological) 0.5 xylenes (REL)

Number of Facilities with Maximum Reproductive Hazard Index:

Greater than 1 0 n/a

Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 4 glycol ethers (REL)

Number of Facilities With Potential for Acute 

Effects 1 glycol ethers

Refined Acute Noncancer Results

Maximum Acute Hazard Quotient 0.1 glycol ethers (REL)

Population Exposure

Number of People Living Within 50 Kilometers 

of Facilities Modeled 63,000,000 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 20 n/a

Greater than or equal to 1 in 1 million 3,700 n/a

Number of People Exposed to Noncancer Hazard Index:

Greater than 1 0 n/a

Estimated Cancer Incidence (excess cancer cases 

per year) 0.003 n/a

Contribution of HAP to Cancer Incidence:

ethyl benzene 99% n/a

naphthalene 1% n/a
28

Table 3.2-2 Summary of NPRM Acute Refined Results for Shipbuilding and Ship 

Repair Operations Facilities

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)

glycol ethers 0.0093 0.1 n/a n/a 0.093

Notes on Refined Process:

1) The 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.

The maximum chronic noncancer TOSHI value is less than 0.5, with emissions of xylene(s)

dominating those impacts, indicating no significant potential for chronic noncancer impacts. 

The primary process contributing to the source category cancer and chronic non-cancer risks 

for shipbuilding and repair is painting operations.

The maximum screening acute HQ exceeded a value of 1 based upon the REL for emissions 

of glycol ethers at 1 facility; this required a refined assessment be conducted at that facility. 

The result of refining the assessment was that the maximum off-site HQ was 0.1, indicating 

that there are no concerns for potential acute health impacts for this source category. Refer to 

Appendix 7 for details on the refined assessment. 

In performing the screening for potential multi-pathway exposures and risks of concern, we 

determined that emissions of cadmium and POM were not significant enough to pose multipathway impacts of concern for human health or the environment. We also determined that 

emissions of lead were not significant enough to cause an exceedance of the lead NAAQS, 

indicating that potential multipathway impacts for lead from this source category are not 

significant.

The results of the facility-wide assessments are summarized in Table 3.2-3. The results 

indicate that 35 facilities containing Shipbuilding and Ship Repair Operations have a facilitywide cancer MIR greater than 1 in a million. The maximum facility-wide cancer MIR is 200 

in a million, with the source category contributing less than 1 percent at 1 in a million. There 

are also 6 facilities with a facility-wide TOSHI value greater than 1. The maximum facility-
29

wide TOSHI value of 4 (nervous system), has a source category contribution of less than 2%. 

In general, the contribution of the source category to elevated facility-wide cancer or 

noncancer risks is low throughout the facilities in this source category. The primary processes

driving the facility-wide cancer and noncancer risks are welding and blasting.

Table 3.2-3 Shipbuilding Source Category Contribution to Facility-Wide Cancer Risks

Number of Facilities Binned by Facility-Wide 

MIR (in 1 million)

Source Category MIR Contribution 

to Facility-Wide MIR

<1 ≥ 1 <10 ≥ 10 <100 > 100 Total

100% 23 8 1 0 32

90-99% 4 2 0 0 6

50-89% 4 4 0 0 8

10-49% 7 6 0 13

1-9% 1 4 8 0 13

0% 5 4 1 3 13

Total 50 20 12 3 85

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

allowable under the MACT standards indicated that MACT allowable emission levels may be 

up to 2 times greater than actual emission levels. Considering this difference, the risk results 

from the inhalation risk assessment indicate that the maximum excess lifetime individual 

cancer risk could be as high as 20 in a million, and that the maximum chronic noncancer 

TOSHI value could be as high as1 at the MACT-allowable emissions level. For more details 

about the estimate of the ratio of actual to MACT-allowable emissions, see the memo in the 

docket entitled, ―Actual vs. Allowable Emissions for Shipbuilding and Ship Repair 

Operations - Emission Standards Technical Support and Post Promulgation Activities‖ [27].

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 our exposure 

modeling estimates. The chronic exposure modeling uncertainties are considered relatively 

small in comparison, since we are using EPA’s refined local dispersion model with sitespecific parameters and reasonably representative meteorology. If anything, the population 

exposure estimates are biased high by not accounting for short- or long-term population 
30

mobility, and by neglecting processes like deposition, plume depletion, and atmospheric 

degradation. 

A sensitivity analysis performed for the 1999 NATA found that the selection of the 

meteorology dataset location could result in a range of chronic ambient concentrations which 

varied from as much as 17% below the predicted value to as much as 84% higher than the 

predicted value. This variability translates directly to the predicted exposures and risks in our 

assessment, indicating that the actual risks could vary from 17% lower to 84% higher than the 

predicted values.

We have purposely biased the acute screening results high, considering that they depend upon 

the joint occurrence of independent factors, such as hourly emissions rates, meteorology and 

human activity patterns. 

4.2 Uncertainties in the Dose-Response Relationships

In the sections that follow, 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% 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 HAPs

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 [28] (herein 

referred to as Cancer Guidelines). ―The primary goal of EPA actions is protection of human 
31

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 

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).15 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.16 

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.17 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 

 

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

16 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.

17 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.
32

characterizations present estimates demonstrating the impact on the assessment of alternative 

choices, data, models and assumptions [29]. 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 is 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.18 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% 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).

 

18 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.‖
33

(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. A recent National Research Council (NRC) report [30] 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 
34

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) [31]. 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 values19 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 

 

19

 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. 
35

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.20 To derive values that are intended to be ―without 

appreciable risk,‖ EPA’s methodology relies upon an uncertainty factor (UF) approach (U.S. 

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

 

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

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

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

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

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

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

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

level (LOAEL).

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

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

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

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

for: (1) variation in susceptibility among the members of the human population (i.e., interindividual variability); (2) uncertainty in extrapolating from experimental animal data to 

humans (i.e., interspecies differences); (3) uncertainty in extrapolating from data obtained in a 

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

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

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

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

available, default adjustment values are selected for the individual UFs. For each type of 

uncertainty (when relevant to the assessment), EPA typically applies an UF value of 10 or 3 

with the cumulative UF value leading to a downward adjustment of 10-3000 fold from the 

selected POD. An UF of 3 is used when the data do not support the use of a 10-fold factor. If 

an extrapolation step or adjustment is not relevant to an assessment (e.g., if applying human 

toxicity data and an interspecies extrapolation is not required) the associated UF is not used. 

The major adjustment steps are described more fully below.

1) Heterogeneity among humans is a key source of variability as well as uncertainty. 

Uncertainty related to human variation is considered in extrapolating doses from a subset or 

 

20 See IRIS glossary
36

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. 
37

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.

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. 
38

5 References

 

1. US EPA. National Emission Standards for Hazardous Air Pollutants. 

http://www.epa.gov/ttn/atw/mactfnlalph.html. 

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, 2005. Revision to the Guideline on Air Quality Models: Adoption of a Preferred

General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final Rule. 

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

4. 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.

5. Allen, D., C. Murphy, Y. Kimura, W. Vizuete, T. Edgar, H. Jeffries, B.-U. Kim, M. Webster, 

and M. Symons, 2004. Variable industrial VOC emissions and their impact on ozone formation 

in the Houston Galveston Area. Final Report: Texas Environmental Research Consortium 

Project H-13. http://files.harc.edu/Projects/AirQuality/Projects/H013.2003/H13FinalReport.pdf

6. US EPA, 2004. Air Toxics Risk Assessment Reference Library, Volume 1. EPA-453-K-04- 

001A. http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 

7. US EPA, 2005. Table 1. Prioritized Chronic Dose-Response Values (2/28/05). Office of 

Air Quality Planning and Standards. http://www.epa.gov/ttn/atw/toxsource/table1.pdf

8. US EPA, 2005. 1999 National Air Toxics Risk Assessment. 

http://www.epa.gov/ttn/atw/nata1999

9. US EPA, 2006. Integrated Risk Information System. http://www.epa.gov/iris/index.html.

10. US Agency for Toxic Substances and Disease Registry. 2006. Minimum Risk Levels (MRLs) 

for Hazardous Substances. http://www.atsdr.cdc.gov/mrls/index.html.

11. US EPA, 1994. US Environmental Protection Agency. Methods for Derivation of 

Inhalation Reference Concentrations and Application of Inhalation Dosimetry. 

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

12. NRC, 1994. National Research Council. Science and Judgment in Risk Assessment. 

Washington, DC: National Academy Press.

13. CA Office of Environmental Health Hazard Assessment, 2005. Chronic Reference 

Exposure Levels Adopted by OEHHA as of December 2008. 

http://www.oehha.ca.gov/air/chronic_rels/AllChrels.html. 

14. CA Office of Environmental Health Hazard Assessment, 2005. Technical Support Document 

for Describing Available Cancer Potency Factors, May 2005. 
39

 

http://www.oehha.ca.gov/air/hot_spots/may2005tsd.html.

15. US EPA, 2006. Approach for modeling POM. Technical support information for the 1999 

National Air Toxics Assessment. 

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

16. US EPA, 2005. Table 2. Acute Dose-Response Values for Screening Risk Assessments 

(6/02/2005). Office of Air Quality Planning and Standards. 

http://www.epa.gov/ttn/atw/toxsource/table2.pdf

17. CA Office of Environmental Health Hazard Assessment, 2000. All Acute Reference 

Exposure Levels developed by OEHHA as of May 2000. 

http://www.oehha.ca.gov/air/acute_rels/allAcRELs.html

18. American Industrial Hygiene Association , 2009. Current AIHA ERPG Values. 

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

19. US EPA, 1995. Guidance for Risk Characterization. Science Policy Council. 

http://www.epa.gov/OSA/spc/pdfs/rcguide.pdf.

20. US EPA, 2000. Risk Characterization Handbook. EPA 100-B-00-002.

21. US EPA, 2002. EPA’s Guidelines for Ensuring and Maximizing the Quality, Objectivity, 

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

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

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

22. US EPA, 2006. Performing risk assessments that include carcinogens described in the 

Supplemental Guidance as having a mutagenic mode of action. Science Policy Council Cancer 

Guidelines Implementation Workgroup Communication II: Memo from W.H. Farland dated 

14 June 2006. http://www.epa.gov/osa/spc/pdfs/CGIWGCommunication_II.pdf

23. US EPA, 2005. Supplemental guidance for assessing early-life exposure to carcinogens. 

EPA/630/R-03003F. http://www.epa.gov/ttn/atw/childrens_supplement_final.pdf.

24. US EPA, 2005. Science Policy Council Cancer Guidelines Implementation Workgroup 

Communication I: Memo from W.H. Farland dated 4 October 2005 to Science Policy 

Council. http://www.epa.gov/osa/spc/pdfs/canguid1.pdf

25. 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

26. US EPA, 2000. Supplementary Guidance for Conducting Health Risk Assessment of 

Chemical Mixtures. EPA-630/R-00-002. 

http://www.epa.gov/ncea/raf/pdfs/chem_mix/chem_mix_08_2001.pdf.

27 US EPA, August 5, 2010. Maximum Available Control Technology (MACT) Allowable 

Emissions Estimate Memorandum from Kaye Whitfield, Project Lead to Dave Guinnup, 

SBAG Leader
40

 

28. US EPA, 2005. Guidelines for Carcinogen Risk Assessment (2005). U.S. Environmental 

Protection Agency, Washington, DC, EPA/630/P-03/001F, 2005. 

http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=116283

29. US EPA, 2000. Risk Characterization Handbook. EPA 100-B-00-002.

30. NRC (National Research Council) 2006. Assessing the Human Health Risks of 

Trichloroethylene. National Academies Press, Washington DC.

31. 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.