1



## Residual Risk Assessment for the Shipbuild ing and Ship Repair

Operations Source Category

by EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation August 20112



### 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 Be en 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 In halation Risks for Shipbuilding and Ship Repair Operations

................................ ................................ ................................ ................. 27

Table 3.2

- 2 Summary of NPRM Acute Refined Results for Shipbuilding an d 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 Modeling3

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 Ap pendix 6 De tailed Risk Modeling Results Appendix 7 Acute Impacts Refined Analysis Figures

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model

AEGL Acute exposure guideline l evel

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 a ction

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 Polycyc lic organic m atter

REL Reference exposure l evel

RfC Reference c oncentration

RfD Reference d ose
RTR Risk and Technology

TOSHI Target

- organ

- specific hazard index

URE Unit risk e stimate4



### 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 tec hnology

- 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,

processe s and control technologies.‖ In the second stage, EPA is required u nder 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 enviro nmental 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 co mpleted 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 wit h 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 receiv ed 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 assessment s 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 assessment s (i.e., after the implementation of the respective MACT standard s ) performed for the Ship building and Ship Repair Operations source categor y

. 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 descri ptions 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 e nvironmental impacts

, including effects to threatened and endangered species , no further refinement of these assess m ents w as performed.



### 2 Methods

2.1 Emissions and source data

The 200 5 National

- Scale Air Toxics Assessment (NATA) National Emissions Inventory (NEI) served as the starting point for this assessment. The 200 5 NEI contains information on5

actual emissions during the entire 200 5 base year. Using the process MACT code 1 , we developed a subset of this inventory that contai ns emissions and facility data for the Shipbuilding and Ship Repair Operations source categor y . 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 so urce categor y , and/or who have extensive knowledge of the characteristics of th i s industr y . NEI data was updated with industry supplied data as available. The goal of the engineering review was to identify readily

apparent limitations and issues with the emissions data (parti cularly 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 devel opment of the emissions and source data for th i s source categor y are discussed in Section 3. The emissions data and modification s made to the NEI data are

discussed in th e Appendix 1, entitled ― Emissions Inventory Support Memorand um

. ‖



### 2.2 Dispersion modelin g for inhalation exposure assessment

Both long

- and short

- term inhalation exposure concentrations and associated health risk from each facility in the source categor y 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 furt her 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 mode ling component. The exposure and risk characterization components a re discussed in other subsections of S ection s 2 and 3

.

The dispersion model in the HEM

- AERMOD system, AERMOD version 0 9292 , is a state

- of

the

- science Gaussian plume dispersion model that is preferred by EPA for modeling point, area, and volume sources of continuous air emissions from facility applications [ 3 ]. Further details on AERMOD can be found in the AERMOD Users Guide [ 4 ]. The model is used to develop annual average ambient concent ration s 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 0 9292 mo del 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 N E I 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 (1 3 rings a nd 1 6 radials ) Discrete (census block centroids)

Terrain characterization Actual from USGS 1

- degree DEM data

Building downwash Not Included

Plume d eposition/ d epletion Not Included

Urban s ource o ption No

Meteorology 1 year representative NWS from nearest site (1 58 stations)

In HEM

- AERMOD, m eteorological 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

cond itions at the subject facility. Ideally, w hen considering off

- site meteorological data most site specific dispersion modeling effo rts will employ up to five years of data to capture variability in weathe r 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 s ingle 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 latitud e 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 Processin g 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 bl ocks with at least one resident ( i.e., locations where people may reasonably be

assumed to resi de rather than receptor p oints a t the fenceline of a facility ) . Chronic ambient

concentrations were calculated a s the annual average of all estimated short

- term ( one

- ho ur)

concentrations at each block centroid . Possible future residential use of currentl y uninhab ited

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 m ay 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 appl y the general assumption to all source categories that the maximum one

- hour emission rate from any source was ten

t imes the average annual hourly emission rate for that source.

The a verage 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 orig inally 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 data set from a

number of source s located in Texas (originally reported on by Allen et al

. 2004) [ 5 ]. In that
report, t h e Texas Environmental Research Consortium Project compared hourly and annual

emissions data for volatile organic compound s 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 whic h reported emitting hi gh 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 t imes the annual average

. Based on these results, we chose t he

factor of ten for all initial screening; it is intended to cove r routinely

- variable emissions as well as startup, shutdown, an d 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 indu strial 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 (us ed 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 u sing receptor elevation to determine plume height, AERMOD adjusts the plume’s flow if nearby elevated hills are expect ed 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

W e used the annual average ambient air concentration of each HAP at each census blo ck centroid as a surrogate for the lifetime inhalation exposure concentration of all the people who8

reside in the census block. That is, th e risk analysis did not consider either the short

- term or long

- term behavior (mobility) of the exposed populations a nd 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 a ctivity 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 typical ly by much less

. Second, basing exposure estimates on average ambient concentrations at census block centroids may underestimate or overestimate actual exposure concentrations at some residences. Further reducing exposure estimates for the most highly

ex posed 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 perso n’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. Th e assumption of not considering short or long

- term population mobility does not bias the esti mate 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 towa rd 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 ass essment of potential health risks due to acute exposures to HAP , we f ollowed 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 t he asse ssment. This means that we bega n 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 f acility being assessed poses no acute health risks (i.e., it ―screens out‖), or that it requires further , more refined assessment. A refined9

assessment could u s e 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 amount s 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 we re assumed to equal 10 times the average 1

- hour emission

rates. For facilities with multiple emission points, peak 1

- hour emissions we re assumed to

occur at a ll emission points at the same time. For facilities with multiple emission points, 1

- hour co ncentrations at each receptor

we re assumed to be the sum of the maximum conc entrations due to each emission point, regardless of whether those maximum concentration s occurred during the same

hour.

Worst

- case meteorology (from o ne year of local meteorology) wa s 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 wa s 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

th e screening from the EPA’s Air Toxics Risk Assessment Library [ 6 ] , and they are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, heptachlor, hexachlorobenzene, hexachlorocyclohexa ne, lead compounds, mercury compounds, methoxychlor, polychlorinated biphenyls, polycyclic organic matter (POM) , toxaphene, and

trifluralin

. E missions of 3 different PB HAP were identified in the emissions inventory for

the Shipbuilding and Ship Repair Op erations 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 developed10

for use with the TRIM.FaTE 2 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 su bsistence 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 Appen dix 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 no ncancer 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 Natio nal 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

fro m 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 i nclusions 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 advers e effect in an exposed

rodent. It should be noted that there is a scarcity o f 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 rece ptors should be at no risk of adverse effects due to inhalation exposures from non PB

- HAP, and have assur ance that other ecological receptors are also not at any significant risk fr om direct atmospheric impact. In some isolated cases

where we have data in dicating 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 v alues

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 R isk Assessment Protocol (HHRAP) for Hazardous Waste Combustion Facilities; http://www.epa.gov/epaoswer/hazwaste/combust/riskvol.htm#volume111

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 obta ined 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 scie nce with respec t 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, f or 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 a s 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/m 3 in

air. ‖ The SF is ―a n upper bound, approximating a 95% confidence limit, on the increased

cancer r isk 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 dose

response assessment information in several forms, based on the level of review. The

In tegrated 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 I RIS 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 scientist s 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 neopl astic 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 be12

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 effect s 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 effect s 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 c hronic assessments 4 : ―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 carcinoge nicity 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 i s used as a surrogate for other compounds in the group f or which dose

- response values are not available. This i s done in

order to e xamine, under conservative assumptions, whether these HAPs that lack dose

response 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 ca tegories such as met al 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 p er μg/m3), and we switched from using the IRIS value to the CI IT 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 prote ctive.[ ] 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 scien tific 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

f indings 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 amorpho us 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. Cons istent 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 effe cts of nickel are not thought to be limited to the crystalline, insoluble form

.

5) A substantial proportion of POM reported to EPA’s nati onal emission inventory (NEI) a re not speciated into individua l compounds. As a result, it i s necessar y to apply the same simplifying assumptions to assessment s that were used for the 1999 NATA study [ 15 ]. The NATA approach partitions POM into eight different non

- overlapping ―groups‖ that

a re modeled as separate pollutants. Each POM gro up comprises POM species of similar carcinogenic potency, for which we can apply the same URE.

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

estimates are converted to inhalation UREs. The co nversion from oral risk (per mg/kg/d oral intake) to inhalation risk (per μ g/m 3 inhaled) i s based on EPA’s standard assumptions

of a 70

- kg body mass and 20 m 3 /d inhalation rate, as follows:

Where: URE = Unit risk estimate for inhalation (risk per μ g/m 3 )

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 alt ernative 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.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/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of

Environmental Health Hazard Ass essment, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards

. Pollutant CAS Number 6 URE 5
(1/μg/m3) Source

Acetaldehyde 75070 2.2E

- 06 IRIS

Benzene

7 71432 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 1.3 E

- 0 5 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 8 EPA OAQPS

- Benzo(a)anthracene 56553 1.1 E

- 04 EPA OAQPS

- Benzo(a)pyrene 50328 1.1 E

- 03 EPA OAQPS

- Benzo(b)fluoranthene 205992 1.1 E

- 04 EPA OAQPS

- Benzo(k)fluoranthene 207089 1.1 E

- 04 EPA OAQPS

- Chrysene 218019 1.1 E

- 05 EPA OAQPS

- Dibenzo(a,h)anthracene 53703 1.2 E

- 03 EPA OAQPS

- Indeno(1,2,3

- cd)pyrene 193395 1.1 E

- 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/m 3 in air. URE’s are considered upper bound estimates meaning they represent a plausible up per 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 asse ssment 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/m 3

. 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.pdf16

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 Number 10 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 Number 6 RfC (mg/m3) So urce 9

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 0.0 2 IRIS

– M

- Die thylene glycol m onobutyl ether (DEGBE) 1 12345 0.0 2 HEAST

- Ethylene glycol ethyl ether 110805 0.2 IRIS

- M

- Ethylene glycol methyl ether (EGME) 109864 0.02 IRIS

- M

- 2

- Butoxyethyl acetate * 112072 0.0 2

- Ethylene glycol ethyl ether acetate 111159 0.3 CAL

9 The descr iptors 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.

10 The 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 Number 6 RfC (mg/m3) So urce 9

- Methoxytriglycol * 112356 0.0 2
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

- Xylene 11 108383 0.1 IRIS

– M

o

- Xylene 1 1 95476 0.1 IRIS

– M

p

- Xylene 1 1 106423 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 a re 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 Le vels (RELs), a s 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 th e ultimate interpretation of any potential risks associated with an estimated exceedance of a particular reference level depends on the definition of that level and any limitations expressed therein. Comparisons among different available inhalation

health effect reference values (both acute and chronic) for selected HAPs can be found in a newly released EPA document (Reference: U.S. EPA. Graphical Arrays of Chemical

Specific Health Effect Reference Values for Inhalation Exposures [Final Report]. ( U.S.

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

En vironmental 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.pd f ) is defined by CalEPA as

― t he 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 toxic ological 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 exposur es (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 publis hed by the National Research Council A s described in the Committee’s ―Standing Operating Procedures (SOP) ‖ ( http://www.epa.gov/opptintr/aegl/pubs/sop.pdf ),

AEGLs ―represent threshold exposure lim its 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

- lifet ime , short

- term exposures to airborne concentrations of acutely toxic, high

priority chemicals.‖ In detailing the intended application of AEGL values, the document
states that ― It is anticipated that the AEGL values will be used for regulatory and

nonregu latory purposes by U.S. Federal and State agencies, and possibly the international community in conjunction with chemical emergency response, pla nning, and prevention

programs. ‖ It is important to note that a potential for effects exists even if the airbo rne concentration is below the AEGL

- 1 value.

The NAC

- AEGL defines AEGL

- 1 and AEGL

- 2 as:

― AEGL

- 1 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, including susceptible individuals, could experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. However, the effects are not disabling and are transi ent and reversible upon cessation of

exposure. ‖19

― AEGL

- 2 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, including susceptible individuals, could experience irreversible or o ther 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 sensor y 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 i diosyncratic responses, could experience the effects described at concentration s below the corresponding AEGL.‖

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergency Response Planning G uidelines (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 guide lines (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 comm unity 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 event s, 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, objectionab le

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 impai r an individual's ability to take protective action. ‖20

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

The emissions inventor y for the Shipbuilding and Ship Repair Operations source ca tegor y include s emissions of 23 HAP with relevant and available quantitative acute dose

- response threshold values. These HAP s , the ir acute threshold values, and the source of the val ue 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/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

- 1

(mg/m 3 ) ERPG

- 2

(mg/m 3 ) 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 ethers 12 0.093

- 2

- Butoxyethyl A cetate * 112072 0.093

- Ethylene Glycol Ethyl E ther 110805 0.37

- Ethylene Glycol Ethyl Ether A cetate 111159 0.14

- Ethylene Glycol Methyl E ther 109864 0.093

- Diethylene Glycol Monobutyl E ther * 112345 0.093

Hexane 110543 12000 Hydrochloric acid 7647010 2.7 33 2.7 33 2.1 Hydrogen f luoride 766439 3 0.82 20 0.82 20 0.24

Methanol 67561 690 2700 690 2700 28 Methyl C hloroform (1,1,1

- Trichloroethane) 71556 1300 3300 1300 3300 68 Methyl Isobutyl K etone 108101 Methylene C hloride 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

Vi nyl A cetate 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. Furthe r, 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 a c ross 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 Memo rand um on Updated Principles for Risk Analysis 13 , 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 noncan cer 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 in cluded in an assessment that has a potency estimate available,

individu al and population cancer risks we re 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

- y r 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

z ero.

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

13 Memorandum f

or t he Heads o f Executive Departments a nd 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 implem entation policy [ 24 ] recommends applyi ng the Supplemental Guidance to all carcinogenic PAH s 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 wa s estimated by multip lying 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 wa s divided by 70 years to obtain an

estimat e of the number of cancer cases per year.

In the case of benzene, the high end of the reported cancer URE range wa s used in our assessments to provide a conservative estimate of potential cancer risks. Use of the high end of the range provides risk estim ates 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 evaluate d 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, ― r isk‖ 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 lev el (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., hi gh, 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 ca nnot 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. W e 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

p otential 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 mu ltiple 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 guidelin es’ [ 25

, 26 ] default assumption of additivity of effects, and combine risks by summing them using the independence formula in the mixtures guidelines.

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

cause adverse hea lth effects via completely d ifferent 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. A ll TOSHI calculations presented here were based exclusively on effects occurring at the ― critical dose‖ (i.e., the lowest dose t hat 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 sy stems 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

- w ide Risk s To help place the source category risks in context, w e examined ―facility

- wide‖ risks using facility

- wide and source category data files developed by EPA t hru emission data updates from industry and refined EPA profiles for this source category. For the facilities in the Shipbuilding and Ship Repa ir Operations source category, we modeled facility

- wide risks

from the se 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

with in a contiguous area and are under common control by the facility

. W e analyzed risks due to the inhalation of HAP for the populations residing within 5 0 kilometers of each facility

. The results of th e facility

- wide assessment s 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 an d 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 the se 85 facilities as area sources of HAP (and 41 as major sources), the uncertainty associated with these major/area classifications is significant. Without verificatio n of the area source status of individual facilities, EPA will consider all facilities i n 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 faci lities)

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 keto ne. 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

p ercent), 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

- 4 53K

- 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 Shipbuildin g and Ship Repair Operations Source

Category and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting

HAP ( 85

facilities in

ANPRM data set) Prioritized Inhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? 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 1 38 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 0.0 3 1

2

- Butoxyethyl Acetate 0.0 3 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 126

Table 3.1

- 1 Summary of Emissions from the Shipbuildin g and Ship Repair Operations Source

Category and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting

HAP ( 85

facilities in

ANPRM data set) Prioritized Inhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? 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 a t 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 Technolo gy

- 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 max imum 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 ass essment results is available in Appendix 6.

Table s 3

. 2

- 1 and 3.2

- 2 summarize the preliminary chronic and acute inhalation risk results for this source category

. T he results of the chronic inhalation cancer risk assessment indicate the

maximum lifetime in dividual cancer risk could be as high as 10 i n a m illion. 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 incidenc e from th is source category based on actual emission levels is 0.00 3 e xcess cancer cases per year, or one case in eve ry 33 0 years. A pproximately 20 people were estimated to have cancer

risks above 10 in a million and approximately 3,7 00 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 2 6 ethyl benzene, naphthalene, methylene chloride

Chronic Noncancer Risks

Maximum Hazard Index (Neurological) 0.5 xylene s (REL)

Num ber 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 3,7 00 n/a

Number of People Exposed to Noncancer Hazard Index:

Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.00 3 n/a

Contribution of HAP to Cancer Incidence: ethyl benzene 9 9 % n/a naphthalene 1% n/a28

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/m 3 ) Based on

REL Based on

AEGL

- 1/

ERPG

- 1 Based on

AEGL

- 2/

ERPG

- 2 REL

(mg/m 3 ) AEGL

- 1

(1

- hr) (mg/m 3 ) ERPG

- 1

(mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

- 2

(mg/m 3 )

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 t hat 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 Progr am 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 indivi dual’s ability to take protective action.

The maximum chronic non cancer 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 fo r 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 multi

pathway impacts of concern for human h ealth 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 result s o f the facility

- wide assessment s are summarized in Table 3 .2

- 3 . The results

indicate that 35 facilities containing Shipbuilding and Ship Repair Operations have a facility

wide cancer MIR greater than 1 in a million. The maximum facility

- wide cancer MIR is 2 00

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. Th e maximum facility

-29

wide TOSHI value of 4 (nervous system), has a source catego ry contribution of less than 2 %. In general, the contribution o f the source category to elevated facili ty

- wide cancer or

noncancer risks is low throughout the facilities in this source category

. The primary process es driving the facility

- wide cancer and noncancer risk s 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, t he risk results

from the inhalation risk assessment indicate that the maximum excess l ifetime 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 detail s 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 H ave 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 unc ertainties 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 site

specific parameters and reasonably representative m eteorology. If anything, the population exposure estimates are biased high by not accounting for short

- or long

- term population30

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, c onsidering 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 ar e 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 lifet ime), bu t 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 s pecified. For the purposes of assessing all potential health risks associated wit h

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. Althoug h every effort is made to identify peer

- review ed 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 (i nhalation 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 ce rtain 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

- dev eloped 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 human31

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 estim ation 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 a pproach, 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 population s 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 uppe r 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 expres sed 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 a bsence 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 E PA 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

choi ces, 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 experimen tal 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 spe cies 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 do se 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 t hemselves 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 c ancer 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 estimate s.

(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 p oint 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 exces s 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 st udy 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 experim ental 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 c an 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 science

policy 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 a ppropriately 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

- th reshold 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 populat ion: ―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 f or 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 li nearity 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 approac h 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 line34

risk estimat es 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 no te 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 mak e 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 car cinogen 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

rec ommendations 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 addre ss 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 deve lop 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 values 19 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) ―[De fault] 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 Asse ssment 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 op tions 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, de fault 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 pollutan ts 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

dele terious 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 variabil ity.

EPA begins by evaluating all of the available peer

- reviewed literature to determine non

cancer endpoints of concern, evaluating the quality, strengths and limitations of the available studies. EPA typically chooses the relevant endpoint that occu rs 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 estimatio n 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 observe d animal (usually rodent) or human toxicity data in a risk assessment. The UFs are intended to account for: (1) variation in susceptibility among the members of the human population (i.e., inter

individual variability); (2) uncertainty in extrapolating fr om 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 extrapolat ing 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 adj ustment 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 assoc iated 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 sub set or

20 See IRIS glossary36

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 re flect 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

uncertaint ies 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 compare d on a mg/kg/day basis. The default choice of 10 for the interspecies UF is consistent with these differences. For a s pecific 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 ani mals 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 chr onic 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 avail able 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 b y 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 a pproach 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 L OAEL, 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 ba sed on chemical

specific 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 par agraph). 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 a t 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 b eing exceeded. W here 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/B

03

- 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 Refere nce 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 Qualit y 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. Scie nce 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/cangu id1.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 Leader40

28

. US EPA, 2005. Guidelines for Carcinogen Risk Assessment (2005). U.S. Enviro nmental 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 differe nt statistical approaches, Risk Anal. Vol 26, p. 825

– 830.