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1 

## Draft
Residual Risk Assessment for the Off

- Site Waste and Recovery Operations Source Category

by EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation May 2014Draft Risk Assessment for the Of f

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2 

### Table of Contents

1 Introduction

................................ ................................ ................................ ........................ 4

2 Methods

................................ ................................ ................................ .............................. 4

2.1 Emissions and so urce data

................................ ................................ ........................... 4

2.2 Dispersion modeling for inhalation exposure assessment

................................ ........... 5

2.3 Estimating chronic human inhalation exposure

................................ .......................... 7
2.4 Acute Risk Screening and Refined Assessments

................................ ........................ 8

2.5 Multipathway and environmental risk screening

................................ ...................... 10

2.6 Dose

- Response Assessment

................................ ................................ ...................... 13

2.6.1 Sources of chronic dose

- response information

................................ .................. 13

2.6.2 Sources of acute dose

- response information

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

2.7 Risk Characterization

................................ ................................ ................................ 26

2.7.1 General

................................ ................................ ................................ ............... 26

2.7.2 Mixtures

................................ ................................ ................................ ............. 28

2.7.3 Facility

- wide Risks

................................ ................................ ............................ 28

2. 7.4 MACT

- Allowable Risk

................................ ................................ ...................... 29

3 Risk Results for the OSWRO Source Category

................................ ............................... 29

3.1 Source Category Description and Results

................................ ................................ . 29

3.2 Risk Characterization

................................ ................................ ................................ 34

4 General Discussion of Uncertainties and How They Have Been Addressed

................... 38

4.1 Exposure Modeling Uncertainties

................................ ................................ ............. 38

4.2 Uncertainties in the Dose

- Response Relationships

................................ ................... 39
5 References

................................ ................................ ................................ ........................ 48

Index of Tables

Table 2.2

- 1 AERMOD version 12345 model options for RTR modeling

................................ 6
Table 2.6

- 1 Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

.......... 16
Table 2.6

- 2 Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

.... 18
Table 2.6

- 3 Dose

- Response Values for Acute Exposure

................................ ........................ 24
Table 3.1

- 1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk Assessment and Availability of Dose

- Response Values

................................ ................. 30
Table 3.2

- 1 Summary of Source Category Level In halation Risks for OSWRO

................... 36
Table 3.2

- 2 Summary of Environmental Risks Screen Results for OSWRO

.......................... 37
Table 3.2

- 3 Source Category Contribution to Facility

- Wide Cancer Risks

............................ 38

Appendices

Appendix 1 Technical Support Document for HEM3 Modeling Appendix 2 Meteorological Data for HEM3 Modeling Appendix 3 Analysis of data on short

- term emission rates relative to long

- term emission

rates Appendix 4 Technical Support Document for TRIM

- Based Multipathway Screening

Scenari o for RTR: Summary of Approach and EvaluationDraft Risk Assessment for the Of f

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3 Appendix 5 Detailed Risk Modeling Results Appendix 6 Acute Impacts Refined Analysis Appendix 7 Dispersion Model Receptor Revisions and Additions for OSWRO

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

CTE Central Tendency Estimate

ERPG Emergency Response Planning Guideline

HAP Hazardous Air Pollutant

HEM Human Exposure Model

HI Hazard i ndex HQ Hazard q uotient

IRIS Integrated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of a ction

NAC National Advisory Committee NAAQS National Ambient Air Quality Standard

NATA National Air Toxics Assessment

NEI National Emissions Inventory

NPRM Notice of Proposed Rulemaking

PB

- HAP Persistent and Bioaccumulative

- HAP

POM Polycyclic organic matter

REL Reference exposure level
RfC Reference concentration

RfD Reference dose

RME Reasonable Maximum Exposure

RTR Risk and Technology

TOSHI Target

- organ

- specific hazard index

URE Unit risk estimateDraft Risk Assessment for the Of f

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4 

## 1 Introduction

Section 112 of the Clean Air Act (CAA) establishes a two

- stage regulatory process for addressing emissions of hazardous air pollutants (HAP) from stationary sources. In the first stage, section 112(d) requires the Environmental Protection Agency (EPA, or the Agency) to develop technology

- based standards for categories of sources (e.g., petroleum refineries, pulp and paper mills, etc.) [ 1 ]. EPA has largely completed the initial Maximum Achievable Control Technology ( MACT ) standards as required under this p rovision. 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 under section 112(f)(2) to assess the health and environmental risks that remain after implementation of the MACT standards. If additional risk reductions are necessary to protect public health with an ample margin of safety or to prevent an adverse environmental effect, EPA must develop standards to address these remaining risks. This second stage of the regulatory process is known as the residual risk stage. For each source category for which EPA issued MACT standards, the resid ual risk stage must be completed within eight years of promulgation of the initial technology

- based standard.

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board (SAB) on the “Risk and Technology Review (RTR) Assessment Pla n” and in June of 2007, we received a letter with the results of that consultation. Subsequ ent to the consultation, in

Ju ly of 2009 a meeting was held with an SAB panel for a formal peer review of the “Risk and Technology Review (RTR) Assessment Methodolo gies” [ 2 ]. We received the final SAB report on this review in May of 2010 [ 3 ]. Where appropriate, we have responded to the key messages from this review in developing our current risk assessment s and we will be continuing our efforts to improve our asses sments by incorporating updates based on the SAB recommendations as they are developed and become available . Our responses to the key
recommendations of the SAB are ou tlined in a memo entitled, “EPA’s Actions in Response to

the Key Recommendations of the Science Advisory Board Review of R isk and Technology Review (RTR) Risk Assessment Methodologies” [ 4 ].

This document contains the methods and the results of baseline risk assessments (i.e., after the implementation of the MACT standard) performed for the off

- site waste and recovery operations (OSWRO) source category . The methods discussion includes descriptions of the methods used to develop refined estimates of chronic inhalation exposures and human health risks for cancer and noncancer endpoints, as we ll as descriptions of the methods used to screen for acute health risks, chronic non

- inhalation health risks, and adverse environmental
effects.



## 2 Methods

2.1 Emissions and source data

The starting point for this assessment involved generating a list of facilities potentially subject to the OSWRO MACT. The initial list, which included over 400 facilities across the UnitedDraft Risk Assessment for the Of f

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5 States, was developed from databases maintained for the Resource C onservation and Recovery Act (RCRA) and the EPA’s Office of Enforcement and Compliance Assurance (OECA), as well as from databases used in development of the original OSWRO MACT
standards . The facilities were checked against compliance databases , including the Air Facility System (AFS), and title V operating permit information to ensure that the facilities

were still operating, were subject to the OSWRO MACT and were major sources of HAP
emissions. T he resulting facility list, which consisted of 53 f ac i liti es, was used to c r e a te a
subset of the 2005 NEI that included facility, process and emissions data. Data from nine corporate entities w ere also gathered through a CAA section 114 questionnaire. Where data for a facility was available from the questionnaire , th e questionnaire data was used ; NEI data

w ere used for the remaining facilities , where OSWRO emissions could be identified

. These data underwent a QA/QC procedure, and revisions were made to the dataset as necessary. In addition, f

acility and industry representatives were contacted to clarify details and resolve
issues with the data for several sources

. In the end, data for 38 facilities were included in the modeling dataset

. Details on the development of the emissions and source data for this source category are discussed in a memorandum entitled

, “ Development of the RTR Emissions
Dataset for the Off

- Site Waste and Recovery Operations Source Category ” available in the
docket for this rule making

. Section 3 below provides a summary of the emissions.



### 2.2 Dispersion modeling for inhalation exposure assessment
Both long

- and short

- term inhalation exposure concentrations and associated health risk from each facility in the source category of interest were estimated using the Human Exposure
Model in combinati on with the American Meteorological Society/EPA Regulatory Model (AERMOD) disper sion modeling system ( HEM3 ). The approach used in applying this modeling system is outlined below, and further details are provided in Appendix 1 of this document, Technical S upport document for HEM3 Modeling

. The HEM3 performs three main operations: atmospheric dispersion modeling, estimation of individual human exposures and health risks, and estimation of population risks. This section focuses on the dispersion modeling co mponent. The exposure and risk characterization components are discussed in
other subsections of Sections 2 and 3.

The di spersion model in the HEM3 system, AERMOD version 12345 , 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 [ 5 ]. Further details on AERMOD can be found in the AERMOD Users Guide [ 6 ]. The model is used to develop annual average ambient concentrations throu gh 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 t he application of the HEM3 modeling system is to predict ambient concentrations at locations of interest. The AERMOD model options employed are
summarized in Table 2.2

- 1 and are discussed further below.Draft Risk Assessment for the Of f

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6 Table 2.2

- 1 AERMOD version 1 2345 mo del options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point and Area

Receptor orientation Polar (13 rings and 16 radials) Discrete (census block centroids) and user

- supplied receptors

Terrain characterization Actual from USGS 1

- degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option Included if source in urbanized area

Meteorology 1 year represent ative NWS from nearest site (over 8 00 stations)

In HEM3 , meteorological data are ordina rily selected from a list of over 8 00 National Weather Service (NWS) surface observation stations acr oss the continental United States, Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is selected as representative of the conditions at the subject facility. Ideally, when considering off

- site meteorological data most site

- specific dispe rsion modeling efforts will employ up to five years of data to capture variability in weather patterns from year to year. However, because
we had an insufficient number of appropriately formatted model input files derived from available meteorological dat a, we modeled only a single year, typically 2011 . While the selection of a single year may result in under

- prediction of long

- term ambient levels at some locations, likewise it may result in over

- prediction at others. For each facility identified by its characteristic latitude and longitude coordinates, the closest meteorological station was used in the dispersion modeling. The average distance between a modeled facility and the applica b le meteorological station was 2 3 miles ( 37 km). Appendix 2 of this document ( Meteorological Data Processing Using AERMET for HEM 3 ) provides a complete listing of stations and assumptions along with further details used in processing the data through

AERMET (the AERMOD meteorological data pre

- processing program)

. 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 HEM3 system estimates ambient concen trations at the geographic centroids of census blocks (using the 20 1 0 Census), and at other receptor locations that can be specified by the

user. See Appendix 7 to this document ( Dispersion Model Receptor Revisions and Additions for the Off

- Site Waste and Recovery Operations Source Category ) for a discussion of user receptors and centroid location changes specific to this source category. The model accounts for the effects of multiple facilities when estimating concentration impacts at each block
centroid . Typically we combined only the impacts of facilities within the same source category, and assessed chronic exposure and risk only for census blocks with at least oneDraft Risk Assessment for the Of f

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7 resident (i.e., locations where people may reasonably be assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient concentrations were calculated as the annual average of all estimated short

- term (one

- hour) concentrations at each block centroid. Possible future residential use of currently uninhabited a reas was not considered. Census blocks, the finest resolution available in the census data, are typically comprised of approximately 40 people or about ten households

.

I n contrast to the development of ambient concentrations for evaluating long

- term exposures, which was performed only for occupied census blocks, worst

- case short

- term (one

- hour) concentrations were estimated both at the census block centroids and at points nearer the facility that represent locations where people may be present for sho rt 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 ac ute exposures, and
since the emissions data contain only annual emission totals, we generally apply the assumption to all source categories that the maximum one

- hour emission rate from any source
is ten times the average ann ual hourly emission rate for that source. More description of our
short

- term assessment can be found in Section 2.4 of this document

– Acute Risk Screening and Refined Assessments

.

Census block elevations for HEM3 modeling were determined nationally fr om the US Geological Service 1 /3 Arc Second National Elevation Dataset , which have a spatial
resolution of about 1 0 meters. Elevations of polar grid points used in estimating short

- and long

- term ambient concentrations were assumed to be equal to the high est elevation of any census block falling within the polar grid sector corresponding to the grid point. If a sector does not contain any blocks, the model defaults the elevation to that of the nearest block. If an elevation is not provided for the emissi on source, the model uses the average elevation of all sectors within the innermost model ring. AERMOD adjusts the plume’s flow if nearby elevated hills are expected to influence the wind patterns. For details on how hill heights
were estimated and used in the AERMOD modeling, see Appendix 1 of this document, Technical Support Document for HEM3 Modeling

.



### 2.3 Estimating chronic human inhalation exposure

We used the estimated annual average am bient air concentration of each HAP at each census
block centroid as a surrogate for the lifetime inhalation exposure concentration of all the people who reside in the census block. That is, the risk analysis did not consider either the
short

- term or long

- term behavior (mobility) of the exposed populations and its potential influence on their exposure.

We did not address short

- term human activity for two reasons. First, our experience with the NATA assessments (which modeled daily activity using EPA’s HAPEM model) suggests that, given our current understand ing of microenvironment concentrations and daily activities, modeling short

- term activity would, on average, reduce risk estimate s about 25 percent for particulate HAP ; it will also reduce risk estimates for gaseous HAP , but typically by much
less. Secon d, basing exposure estimates on average ambient concentrations at census blockDraft Risk Assessment for the Of f

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8 centroids may underestimate or overestimate actual exposure concentrations at some residences. Further reducing exposure estimates for the most highly exposed residents by
mode ling their short

- term behavior could add a systematic low bias to these results.

We did not address long

- term migration nor population growth or decrease over 70 years, instead basing the assessment on the assumption that each person’s predicted exposure is constant over the course of their lifetime which is assumed to be 70 years. In assessing cancer risk, we generally estimated three metrics; the maximum individual risk (MIR), which is defined as the risk associated with a lifetime of exposure at the hi ghest concentration; the population risk distribution; and the cancer incidence. The assumption of not considering short or long

- term population mobility does not bias the estimate of the theoretical MIR nor
does it affect the estimate of cancer incidence since the total population number remains the same. It does, however, affect the shape of the distribution of individual risks across the affected population, shifting it toward higher estimated individual risks at the upper end and reducing the number o f people estimated to be at lower risks, thereby increasing the estimated number of people at specific risk levels

.



### 2.4 Acute Risk Screening and Refined Assessments

In establishing a scientifically defensible approach for the assessment of potential health risks due to acute exposures to HAP, we 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 approach to risk assess ment was endorsed by the National Academy of Sciences in its 1993 publication “Science and Judgment in Risk Assessment” and subsequently was adopted in the EPA’s “Residual Risk Report to Congress”
in 1999.

The assessment methodology is designed to elimi nate from further consideration those
facilities for which we have confidence that no acute adverse health effects of concern will occur. To do so, we use what is called a tiered, iterative approach to the asse ssment. This means that we beg i n with a scre ening assessment, which relies on readily available data and uses conservative assumptions that in combination approximate a worst

- case exposure . The result of this screening process is that either the facility being assessed poses no potential
acute heal th risks (i.e., it “screens out”), or that it requires further , more refined assessment.
A more refined acute 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 bou ndaries of the facility, and /or the local meteorology. In some cases, all of these site

- specific data are used to refine the assessment; in others, lesser amount s of site

- specific data can be used to determine that acute exposures are not a concern, and significant additional data collection is not

necessary.

Acute health risk screening was performed as the first step. When we identify acute impacts which exceed their relevant benchmarks, we pursue refining our acute screening estimates to
the extent possible. In some cases, this may include the use of a facility

- specific emissions multiplier to estimate the peak hourly emission rates from the average rates (rather than the default factor of 10). In other cases, this may entail determining the actual physical layoutDraft Risk Assessment for the Of f

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9 and boundaries of a facility to more accurately gauge where people might reasonably be exposed for an hour.

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. These hourly concentrations are based on hourly emissions, as described above. Since information is not usually available on
short

- term emissio n rates, we generally apply the assumption that the maximum one

- hour emission rate from any source is ten times the average annual hourly emission rate for that source. (The average hourly emission rate is defined as the total emissions for a year divided by the total number of operating hours per year.) This choice of a factor of ten for acute screening was originally based on engineering judgement.

To develop a more robust peak

- to

- mean emissions factor, and in response to one of the key messages from t he SAB consultation on our RTR Assessment Plan, we performed an analysis using a short

- term emissions dataset from a number of sources located in Texas (originally reported on by Allen et al. 2004) [ 7 ]. In that report, the Texas Environmental Research

Con sortium Project compared hourly and annual emissions data for volatile organic compounds for all facilities in a heavily

- industrialized 4

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

- month time period in 2001. We obtaine d the dataset and performed our own analysis, focusing on sources which reported emitting high quantities of HAP over short periods of time (see Appendix 4 of this document, 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 74 times the annual average, and the 99 th percentile ratio of peak hourly emission rate to the annual hourly
emission rate was 9. Based on these results , we generally chose the factor of ten for all initial screening. This factor is intended to cover all possible hourly peaks associated with routinely

variable emissions. While there have been some documented emission excursions above this level, our ana lysis of the data from the Texas Environmental Research Consortium suggests that this factor should cover more than 99 percent of the short

- term peak gaseous or volatile HAP emissions from typical industrial sources. We have no data relating specifically to peak
short

- term emissions of particulate HAP. In the absence of source category

- specific data, we use this same default approach for particulate emissions as well.

W hen we identify acute impacts which exceed their relevant benchmarks, we pursue refini ng our acute screening estimates to the extent possible. For the off

- site waste and recovery operations source category, we conducted a review of the layout of the polar receptors around
the facilities to determine the maximum off

- site acute impact for th e facilities that did not screen out during the initial run. Appendix 5 to this document ( Draft Detailed Modeling
Results ) contains the initial acute results for the source category, while Appendix 6 to this document (

Acute Impacts Refined Analysis ) conta ins the refined acute results.

In summary, w e used conservative assumptions for emission rates, meteorology, and exposure
location , and refined data where available . We used the following worst

- case assumptions in our screening approach:Draft Risk Assessment for the Of f

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10  Peak 1

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

- hour emission

rates.

 For facilities with multiple emission points, peak 1

- hour emissions were assumed to occur at all emission points at the same time.

 For facilities with multiple emission points, 1

- h our concentrations at each receptor
were assumed to be the sum of the maximum concentrations due to each emission point, regardless of whether those maximum concentrations occurred during the same
hour.

 Worst

- case meteorology (from one year of local meteo rology) was assumed to occur at the same time the peak emission rates occur. The recommended EPA local

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

 A person was assumed to be located downwind at the point of maximum impac t during this same worst

- case 1

- hour period, but no nearer to the source than 100

meters.

 The maximum impact was compared to multiple short

- term he alth benchmarks for the

HAP being assessed to determine if a possible acute health risk might exist. These
b enchmarks are described in section 2.6 of this report.



### 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 de termining whether any sources emitted any hazardous air pollutants known to be persistent and bioaccumulative in the environment (PB

- HAP) 1 . The PB

- HAP compounds or compound classes are identified for the screening from the EPA’s Air Toxics Risk Assessment Library [ 8 ]. Examples of PB

HAP are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, DDE, heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury compounds, methoxychlor, polychlorinated biphenyls, polycyclic org anic matter (POM)

, toxaphene, and trifluralin

.

Currently, the multipathway screen can be used to quantitatively estimate exposures and risks for the following five PB

- HAP compounds: lead, cadmium compounds, chlorinated dibenzodioxins and furans, mercury compounds, and polycyclic organic matter (POM). These compounds are the focus of the screen because, based on current emissions and toxicity considerations, they are expected to pose the vast majority of the non

- inhalation risks to humans from air emissions at sources subject to residual risk provision s of the CAA. Potential impacts on human health from non

- inhalation exposures to cadmium compounds, chlorinated dibenzodioxins and furans, mercury compounds, and polycyclic organic matter are evaluated using our screening scenario developed for use with t he EPA’s peer

- reviewed Total Risk Integrated Methodology

– Fate, Transport, and Ecological Exposure

1 Although the two

- letter chemical symbol for lead is Pb, in this assessment PB

- HAP refers to the many air pollutants known to be persistent and bioaccumulative in the environment. In instances where the report is specifically referring to lead, it is spell ed out (i.e., the two

- letter chemical symbol for lead is not used in this

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11 ( TRIM.FaTE 2 ) model. With this approach, we first determine whether the facility

- specific
emission rates of each of the four PB

- HAP listed above are large e nough to create the potential for significant non

- inhalation human health risks under reasonable worst

- case conditions. To facilitate this step, we developed emission rate thresholds for each PB

- HAP using a hypothetical upper

- end screening exposure scenar io developed for use in conjunction with TRIM.FaTE. The exposure scenario includes a generic farming/fishing exposure
scenario that simulates a subsistence environment. We conducted a sensitivity analysis on the screening scenario to ensure that its key design parameters would represent the upper end of the range of possible values, such that it would represent a conservative but not impossible
scenario. The PB

- HAP emissions (of the four listed PB

- HAP above) from each facility in the
source category were compared to the emission rate threshold values for each of the four PB

HAP identified to assess the potential for significant human health risks via non

- inhalation pathways. For the purpose of developing emission rates for the multipathway screen, we
der ived emission levels for each of the four PB

- HAP listed above at which the maximum
human health risk would be 1

- in

- 1 million for lifetime cancer risk or a hazard quotient of 1.0 for noncancer impacts. We call this application of the TRIM.FaTE model the Ti er I screen. See Appendix 4 of this document ( Technical Support Document for TRIM

- Based Multipathway Screening Scenario for RTR: Summary of Approach and Evaluation ) for a complete discussion of the development and testing of the screening scenario, as we ll as for the values of facility

- level emission rates developed for screening potentially significant
multi

- pathway impacts.

In evaluating the potential multi

- pathway risks from emissions of lead compounds, rather than developing a screening emission ra te for them , we compared maximum est imated chronic atmospheric concentrations with the current National Ambient Air Quality Standard (NAAQS) for lead. Values below the NAAQS were considered to have a low potential for
multi

- p athway risks

.

Emissions of p olycyclic o rganic ma tter ( analyzed as benzo(a)pyrene ), polychlorinated biphenyls, lindane (gamma

- hch), chlordane, hexachlorobenzene, methoxychlor, toxaphene, heptachlor, and trifluralin were identified in the emissions inventories for the OSWRO source

cate gory.

The EPA has developed a screening approach to examine the potential for adverse environmental effects as required under section 112(f)(2)(A) of the CAA. The environmental screen focuses on the following seven environmental HAP:

 Five persistent bioaccumulative HAP (PB

- HAP)

– cadmium, dioxins/furans, polycycl ic organic matter (POM), mercury (both inorganic mercury and methyl mercury) and lead.

 Two acid gases

- hydrogen chloride (HCl), and hydrogen fluoride (HF).

2 EPA’s Total Risk Integrated Methodology (General Information) http://epa.gov/ttn/fera/trim_gen.htmlDraft Risk Assessment for the Of f

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12 HAP that persist and bioaccumulate are of particular environmental concern because they accumulate in the soil, sediment and water. The acid gases, HCl and HF, were included due to
their well

- documented potential to cause direct damage to terrestrial plants.

For the environmental risk screening analysis, EPA first determined whether any faci lities in the source categor y emitted any of the seven environmental HAP. If one or more of the seven environmental HAP evaluated are emitted by at least one facility in the source category we proceed to the second step of the evaluation.

For cadmium, me rcury, POM and dioxins/furans, the environmental screening analysis consists of two tiers. In the first tier, TRIM.FaTE modeling was conducted under worst

- cast environmental conditionals to determine whether the facility

- specific off

- site emission rates
of each of the emitted environmental HAP exceeded ecological benchmarks represented as
emissions threshold values . If off

- site emissions from a facility do not exceed the Tier I
thresholds the facility “passes” the screen, and therefore, is not evaluated fu rther under the screening approach. If off

- site emissions from a facility exceed the Tier I thresholds, we evaluate the facility further in Tier II

.

In Tier II of the environmental screening analysis, the screening emission thresholds are adjusted to acco unt for local meteorology and the actual location of lakes in the vicinity of facilities that did not pass the Tier I screen. If off

- site emission s from a facility do not exceed
the Tier II thresholds, the facility passes the screen, and is typically not e valuated further. If
off

- site emissions from a facility exceed the Tier II thresholds, the facility does not pass the screen and, therefore, may have the potential to cause adverse environmental effects. Such facilities are evaluated further to investigate factors such as the magnitude and characteristics
of the area of exceedance.

For acid gases, t he environmental screening analysis evaluates the p otential phytotoxicity and reduced productivity of plants due to chronic exposure to acid gases. The environmental risk screening methodology for acid gases is a single

- tier screen that compares the average off

- site
ambient air concentration over the model ing domain to ecological benchmarks for each of the acid gases. For purposes of ecological risk screening, EPA identifies a potential for adverse environmental effects to plant communities from exposure to acid gases when the average
concentration of the HAP around a facility exceeds the LOAEL ecological benchmark. In such cases, we further investigate factors such as the magnitude and characteristics of the area of exceedance (e.g., land use of exceedance area, size of exceedance area) to determine if
the re is an adverse environmental effect.

For lead compounds, we currently do not have the ability to calculate media concentrations using the TRIM.FaTE model. However, air concentrations of lead are already calculated as part of the human health exposure and risk analysis using the HEM

- 3 AERMOD air dispersion model. To evaluate the potential for adverse environmental effects from lead, we compare the average modeled air emission concentrations of lead from each facility in the source category emissions to the level of the secondary National Ambient Air Quality Standard (NAAQS) for lead. The secondary lead NAAQS is a reasonable means of evaluating environmental risk because it is set to provide substantial protection against adverse welfareDraft Risk Assessment for the Of f

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13 effects which ca n include “effects on soils, water, crops, vegetation, man

- made materials, animals, wildlife, weather, visibility and climate, damage to and deterioration of property, and hazards to transportation, as well as effects on economic values and on personal com fort and
well

- being.” 3



### 2.6 Dose

- Response Assessment

2.6.1 Sources of chronic dose

- response information

Dose

- response assessment (carcinogenic and non

- carcinogenic) for chronic exposure (either by inhalation or ingestion) for the HAP reported in the emissions inven tory for the OSWRO

source category were based on the EPA Office of Air Quality Planning and Standards’ existing recommendations for HAP [ 9 ], also used for NATA [ 10 ]. This information has been obtained from various sources and prioritized according to (1) c onceptual consistency with EPA risk assessment guidelines and (2) level of peer review received. The prioritization process was aimed at incorporating into our assessments the best available science with respect to dose

- response information. The recommen dations are based on the following sources, in order of priority :

1) US Environmental Protection Agency (EPA). EPA has developed dose

- response assessments for chronic exposure for many of the pollutants in this study. These assessments typically provide a qualitative statement regarding the strength of scientific data and specify a reference concentration (RfC, for inhalation) or reference dose (RfD, for ingestion) to protect against effects other than cancer and/or a unit risk estimate (URE,
for inhalatio n) or slope factor (SF, for ingestion) to estimate the probability of developing

cancer. The RfC is defined as an “ estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including

se nsitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. ” The RfD is “a n estimate (with uncertainty spanning perhaps an order of magnitude) of a daily oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a
lifetime. ” The URE is defined as “ the upper

- bound excess cancer risk estimated to result
from continuous lifetime exposure to an agent at a concentratio n of 1 μg/m 3 in air. ” The
SF is “a n upper bound, approximating a 95% confidence limit, on the increased cancer risk from a lifetime exposure to an agent. This estimate, [is] usually expressed in units of proportion (of a population) affected per mg/kg

- day ...” EPA disseminates dose

- response assessment information in several forms, based on the level of review. The Integrated Risk Information System (IRIS) [ 11 ] is an EPA database that contains scientific health

3 A secondary standard, as defined in Section 109(b)(2), must “specif y a level of air quality the attainment and maintenance of which, in the judgment of the Administrator, based on [air quality] criteria, is requisite to protect the public welfare from any known or anticipated adverse effects associated with the presence o f [the] pollutant
in the ambient air.” Welfare effects as defined in section 302(h) (42 U.S.C. 7602(h)) include, but are not limited to, “effects on soils, water, crops, vegetation, man

- made materials, animals, wildlife, weather, visibility

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

- being.”Draft Risk Assessment for the Of f

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14 assessment information, including dose

- response information. All IRIS assessments since 1996 have also undergone independent external peer review. The current IRIS process includes review by EPA scientists, interagency reviewers from other federal agencies, and the public, and peer review by independen t scientists external to EPA. New IRIS values are developed and old IRIS values are updated as new health effects data become
available. Refer to the “IRIS Track” website for detailed information on status and scheduling of current individual IRIS assess ments and updates ( http://cfpub.epa.gov/ncea/iristrac/index.cfm ). EPA’s science policy approach , under the current carcinogen guidelines, is to use linear low

- dose extrapolation as a default opt ion 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 assessmen ts. 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) [ 12 ] for inhalation and oral exposure to many toxic substances. As
stated on the ATSDR web site: “ Following discussions with scienti sts 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 neo plastic 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 substanc e

- specific estimates to be used by health assessors to select environmental contaminants for further evaluation. Exposures above an MRL do not necessarily represent a threat, and MRLs are therefore not intended for use as predictors of adverse health effe cts 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 effe cts other than cancer. The process for developing these assessments is similar to that used by EPA to develop IRIS values and incorporates significant external scientific peer review. As cited in the CalEPA Technical Support Document for developing their chronic assessments 4 : “The guidelines for developing chronic inhalation exposure levels incorporate many recommendations of the U.S. EPA [ 13 ] and NAS [ 14 ].” The non

- cancer information includes available inhalation health risk guidance values expressed as c hronic inhalation reference exposure levels (RELs) [ 15 ]. 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 carcinogen icity by inhalation exposure is expressed in terms of the URE [ 16 ], defined similarly to EPA's URE.

4 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III

- Technical Support Document

for th e 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_rel s/pdf/relsP32k.pdf )Draft Risk Assessment for the Of f

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15 In developing chronic risk estimates, we adjusted dose

- response values for some HAP 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 HAP 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 cat egories 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 Chemica l Industry Insti tute of Toxicol ogy ( CIIT )

cancer dose

- response value for formaldehyde (5.5 x 10

- 9 per μg/m 3 ) was based on better
science than the IRIS cancer dose

- response value (1.3 x 10

- 5 per μg/m 3 ), and we switched from using the IRIS value to the CIIT value in risk as sessments supporting regulatory
actions. S ubsequent research published by EPA suggested that the CIIT model was not appropriate and in 2010 EPA returned to using 1991 IRIS value

. EPA has been working on revising the formaldehyde IRIS assessment and the N ational Academy of Sciences (NAS) completed its review of the EPA’s draft assessment in April of 2011

. 5 EPA will
follow the NAS Report recommendations and will present results obtained by implementing the biologically

- based dose

- response (BBDR) model for formaldehyde. EPA will compare these estimates with those currently presented in the External Review draft of the assessment and will discuss their strengths and weaknesses. As recommended by the NAS committee, appropriated sensitivity and uncertainty an alyses will be an integral component of implementing the BBDR model

. The draft IRIS assessment will be revised in response to the NAS peer review and public comments and the final assessment will be posted on the IRIS database

. In the interim, we will p resent findings using the 1991 IRIS value as a primary estimate and EPA may also consider other information as
the science evolves.

4) A substantial propo rtion of POM reported to EPA’s N ati onal E mission I nventory (NEI) is not speciated into individua l comp ounds. As a result, it i s necessary to apply the same simplifying assumptions to assessment s that are used in NATA [ 17 ]. The NATA approach partitions POM into eight different non

- overlapping “groups” that a re modeled as separate pollutants. Each POM grou p comprises POM species of similar carcinogenic potency, for which we can apply the same URE.

The emissions inventor y for the OSWRO source category include s emissions of HAP with available chronic quantitative inhalat ion dose

- response values. Of these

, 5 6 are classified as known, probable, or possible carcinoge ns, with quantitative cancer do se

- response values

5 http://www.nap.edu/catalog.php?record_id=13142Draft Risk Assessment for the Of f

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16 available. These 5 6 HAP, their quantitati ve inhalation chronic cancer do se

- response values,
and the source of each value are listed in Table 2.6

- 1. Eighty

- two HAP have quantitative
inhalation chronic noncancer threshold values available

. These HAP, their threshold values,
and the source of the value are listed in Table 2.6

- 2

.

Table 2.6

- 1 Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 6 = cancer risk per μg/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of
Research & De velopment, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California EPA Office of Environmental Health Hazard Assessment.

HEAST = EPA Health Effects Assessment Tables , Conv. Oral = Oral unit risk converted to
inhalation.

Pollutant CAS

Number 7 URE 1 1

(1/μg/m3) Source

1,1,2,2

- Tetrachloroethane 79345 0.000058 IRIS 1,1,2

- Trichloroethane 79005 0.000016 IRIS 1,2

- Dibromo

- 3

- chloropropane 96128 0.002 CAL 1,2

- D iphenylhydrazine 122667 0.00022 IRIS 1,3

- Butadiene 106990 0.00003 IRIS 1,3

- Dichloropropene 542756 0.000004 IRIS 1,3

- Propane sultone 1120714 0.00069 CAL 1,4

- Dioxane 123911 0.00000 5 IRIS 8
2,4,6

- Trichlorophenol 88062 0.0000031 IRIS 2,4

- Dinitrotoluene 121142 0.000089 CAL 2,4

- Toluene diamine 95807 0.0011 CAL 2,4

- Toluene diisocyanate 584849 0.000011 CAL

2

- Nitropropane 79469 0.0000056 EPA OAQPS 3,3'

- Dichlorobenzidine 91941 0.00034 CAL

4,4'

- methylene Bis(2

- chloroaniline) 101144 0.00043 CAL 4,4'

- Methylenedianiline 101779 0.00046 CAL

4

- Dimethylaminoazobenzene (p

Dimethylaminoazobenzene 60117 0.0013 CAL Lindane (gamma

- HCH) 58899 0.00031 CAL Acetaldehyde 75070 0.0000022 IRIS

Acetamide 60355 0.00002 CAL Acrylamide 79061 0.00016 IRIS Acrylonitrile 107131 0.000068 IRIS Allyl c hloride 107051 0.000006 CAL

Aniline 62533 0.0000016 CAL

6 The URE is the upper

- bound excess cancer risk estimated to result from continuous lifetime exposure to an
agent at a conc entration of 1 μg/m 3 in air. URE’s are considered upper bound estimates meaning they represent a plausible upper limit to the true value.

7 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have
used a s urrogate 3

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

8 IRIS external review draft value, September 2011.Draft Risk Assessment for the Of f

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17 Table 2.6

- 1 Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 6 = cancer risk per μg/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of
Research & De velopment, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California EPA Office of Environmental Health Hazard Assessment.

HEAST = EPA Health Effects Assessment Tables , Conv. Oral = Oral unit risk converted to
inhalation.

Pollutant CAS

Number 7 URE 1 1

(1/μg/m3) Source

Benzene 9 71432 0.0000078 IRIS

Benzidine 92875 0.1072 IRIS Benzyl c hloride 100447 0.000049 CAL Bis(2

- ethylhexyl)phthalate 117817 0.0000024 CAL

Bromoform 75252 0.0000011 IRIS

Carbon t etrachloride 56235 0.000006 IRIS

Chlordane 57749 0.0001 IRIS

Chlorobenzilate 510156 0.000078 HEAST Dichloroethyl e ther 111444 0.00033 IRIS Epichlorohydrin (1

- Chloro

- 2,3

- e poxypropane) 106898 0.0000012 IRIS Ethyl b enzene 100414 0.0000025 CAL Ethyl c arbamate 51796 0.000464 CAL Ethylene d ibromide 106934 0.0006 IRIS Ethylene d ichloride 107062 0.000026 IRIS Ethylene o xide 75218 0.000088 CAL Ethylene t hiourea 96457 0.000013 CAL Ethylidene d ichloride (1,1

- Dichloroethane) 75343 0.0000016 CAL Formaldehyde 10 50000 0.000013 IRIS Heptachlor 76448 0.0013 IRIS

Hexachlorobenzene 118741 0.00046 IRIS

Hexachlorobutadiene 87683 0.000022 IRIS Hydrazine 302012 0.0049 IRIS Methyl tert

- butyl e ther 1634044 0.00000026 CAL Methylene c hloride 75092 0.000000 13 IRIS Naphthalene 91203 0.000034 CAL

Nitrobenzene 98953 0.00004 IRIS Nitrosodimethylamine 62759 0.0 22 IRIS

N

- nitrosomorpholine 59892 0.0019 CAL

o

- Toluidine 95534 0.000051 CAL

P

- dichlorobenzene (1,4

- dichlorobenzene ) 106467 0.000011 CAL Pentachlorophenol 87865 0.0000051 CAL Polychlorinated b iphenyls (PCB) 1336363 0.0001 IRIS

9 The EPA IRIS assessment for benzene provides a range of plausible UREs. This assessment used the highest
valu e in that range, 7.8E

- 06 per ug/m 3 . The low end of the range is 2.2E

- 06 per ug/m 3

. 10 The EPA has used the CIIT URE value, 5.5X10

- 9 per mg/m 3 , to characterize formaldehyde cancer risk in

some instances.Draft Risk Assessment for the Of f

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18 Table 2.6

- 1 Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 6 = cancer risk per μg/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of
Research & De velopment, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California EPA Office of Environmental Health Hazard Assessment.

HEAST = EPA Health Effects Assessment Tables , Conv. Oral = Oral unit risk converted to
inhalation.

Pollutant CAS

Number 7 URE 1 1

(1/μg/m3) Source

Polycyclic Organic Matter 11 (POM)

2

- Acetylaminofluorene 53963 0.00208 CAL Propylene oxide 75569 0.0000037 IRIS

Tetrachloroethene 127184 0.00000 026 IRIS Toxaphene 8001352 0.00032 IRIS Trichloroethylene 79016 0.00000 48 IRIS Vinyl c hloride 75014 0.0000088 IRIS

Table 2.6

- 2 Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry, HEAST = EPA Health Effects Assess ment Tables , EPA OAQPS = EPA Office of Air Quality Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number 12 RfC (mg/m 3 ) Source 12

1,1,1

- Trichloroethane (methyl chloroform) 71556 5 IRIS

- M 1,1,2

- Trichloroethane 79005 0.4 CAL 1,2,4

- Trichlorobenzene 120821 0.2 HEAST 1,2

- Dibromo

- 3

- chloropropane 9612 8 0.0002 IRIS

- M 1,2

- Epoxybutane 10688 7 0.02 IRIS

- M 1,3

- Butadiene 106990 0.002 IRIS

- M 1,3

- Dichloropropene 54275 6 0.02 IRIS

- H

11 POM without a chemical

- specific URE are assigned a URE associated with a mixture of POM compounds having similar characteristics. Details of this method, also used in the 2002 National Air Toxics Assessment, are
available at http ://www.epa.gov/ttn/atw/nata2002/02pdfs/pom_approach.pdf

.

12 The descriptors L (low), M (medium), and H (high) have been added for IRIS RfC values to indicate the overall level of confidence in the RfC value, as reported in IRIS.Draft Risk Assessment for the Of f

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19 Table 2.6

- 2 Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry, HEAST = EPA Health Effects Assess ment Tables , EPA OAQPS = EPA Office of Air Quality Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number 12 RfC (mg/m 3 ) Source 12

1,4

- Dichlorobenzene (P

- dichlorobenzene) 106467 0.8 IRIS

- M 1,4

- Dioxane 12391 1 0.03 IRIS

- D 13
2,4

- Dinitrotoluene 12114 2 0.007 CAL 2,4

- Toluene diisocyanate 58484 9 0.00007 IRIS

- M

2

- Nitropropane 7946 9 0.02 IRIS

- L 4,4'

- Methylenedianiline 10177 9 0.02 CAL 4,4 '

- Methylene diphenyl diisocyanate 10168 8 0.0006 IRIS

- M Acetaldehyde 75070 0.009 IRIS

- L

Acetonitrile 7505 8 0.06 IRIS

- M

Acrolein 107028 0.00002 IRIS

- M Acrylamide 79061 0.006 IRIS

- M Acrylic a cid 79107 0.001 IRIS

- M Acrylonitrile 10713 1 0.002 IRIS

- M Allyl chloride 10705 1 0.001 IRIS

- L

Aniline 6253 3 0.001 IRIS

- L

Benzene 71432 0.03 IRIS

- M

Benzidine 9287 5 0.01 CAL Bis(2

- ethylhexyl)phthalate 11781 7 0.01 CAL

Carbon d isulfide 75150 0.7 IRIS

- M

Carb on t etrachloride 56235 0.1 IRIS

- M

Chlordane 5774 9 0.0007 IRIS

- L

Chlorine 7782505 0.00015 ATSDR

Chlorobenzene 108907 1 CAL

Chloroform 67663 0.098 ATSDR

Cresol s (mixed) 1319773 0.6 CAL

m

- Cresol 10839 4 0.6 CAL

o

- Cresol 95487 0.6 CAL

p

- Cresol 10644 5 0.6 CAL

Cumene 98828 0.4 IRIS

- M

Dichlorvos 6273 7 0.0005 IRIS

- M

Diethanolamine 111422 0.003 CAL Dimethyl formamide 6812 2 0.03 IRIS

- M

13 IRIS external review dra ft value, September 2011.Draft Risk Assessment for the Of f

- Site Waste and Recovery Operations Source Category

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20 Table 2.6

- 2 Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry, HEAST = EPA Health Effects Assess ment Tables , EPA OAQPS = EPA Office of Air Quality Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number 12 RfC (mg/m 3 ) Source 12

Epichlorohydrin (1

- Chloro

- 2,3

e poxypropane ) 10689 8 0.001 IRIS

- M Ethyl b enzene 100414 1 IRIS

- L Ethyl chloride 7500 3 10 IRIS

- M Ethylene d ibromide 106934 0.009 IRIS

- M Ethylene d ichloride 107062 2.4 ATSDR Ethylene g lycol 107211 0.4 CAL Ethylene o xide 75218 0.03 CAL Ethylene thiourea 9645 7 0.003 CAL Ethylidene d ichloride (1,1

- Dichloroethane) 7 534 3 0.5 HEAST Formaldehyde 50000 0.0098 ATSDR Glycol Ethers 14 Ethylene glycol ethyl ether 11080 5 0.2 IRIS

- M Ethylene glycol methyl ether 10986 4 0.02 IRIS

- M Glycol ethers 18 1 0.02 IRIS

- M

Hexachlorobenzene 11874 1 0.003 CAL

Hexachlorobutadiene 8768 3 0.09 CAL Hexachlorocyclopentadiene 77474 0.0002 IRIS

– M/H

Hexachloroethane 67721 0.0 3 IRIS

- L

Hexane 11054 3 0.7 IRIS

- M Hydrazine 302012 0.0002 CAL Hydrochloric a cid (hydrogen chloride) 7647010 0.02 IRIS

- L Hydrof luori c acid (hydrogen fluoride) 766439 3 0.014 CAL Isophorone 7859 1 2 CAL Lindane (gamma

- HCH) 5889 9 0.0003 CAL Maleic anhydride 10831 6 0.0007 CAL

Methanol 67561 4 CAL Methyl b romide 74839 0.005 IRIS

- H Methyl c hloride 74873 0.09 IRIS

- M

Met hyl isobutyl k etone 108101 3 IRIS

- L/M Methyl m ethacrylate 80626 0.7 IRIS

- M/H Methyl tert

- butyl e ther 1634044 3 IRIS

- M Methylene c hloride 75092 0.6 IRIS

– M/H

14 The RfC value for ethylene glycol methyl ether was used as a surrogate for all glycol ethers without an RfC.Draft Risk Assessment for the Of f

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21 Table 2.6

- 2 Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry, HEAST = EPA Health Effects Assess ment Tables , EPA OAQPS = EPA Office of Air Quality Planning & Standards, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number 12 RfC (mg/m 3 ) Source 12

Naphthalene 91203 0.003 IRIS

- M

Nitrobenzene 9895 3 0.009 IRIS

- M Pentachlorophenol 87865 0.1 CAL

Phenol 108952 0.2 CAL Phosphine 780351 2 0.0003 IRIS

- L Phthalic anhydride 8544 9 0.02 CAL Propionaldehyde 123386 0.008 IRIS

– L/M Propylene d ichloride 78875 0.004 IRIS

- M Propylene oxide 7556 9 0.03 IRIS

- M Styrene 100425 1 IRIS

- M Styrene oxide 9609 3 0.006 CAL

Tetrachloroethene 12718 4 0. 04 IRIS

- M

Titanium tetrachloride 755045 0 0.0001 ATSDR

Toluene 108883 5 IRIS

- H Trichloroethylene 79016 0. 002 IRIS

- H Triethylamine 12144 8 0.007 IRIS

- L Vinyl a cetate 108054 0.2 IRIS

- H Vinyl c hloride 75014 0.1 IRIS

- M Vinylidene c hloride 75354 0.2 IRIS

– H/M Xylenes (mixed) 1330207 0.1 IRIS

- M

m

- Xylene 16 108383 0.1 IRIS

- M

o

- Xylene 15 95476 0.1 IRIS

- M

p

- Xylene 16 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 are based on the existing recommendations of OAQPS for

HAP [ 18 ]

. Depending on availability, the results from screening acute assessments ar e compared to both “no effects” reference levels for the general public, such as the California Reference Exposure Levels (RELs), as well as emergency response levels, such as Acute Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelin es

15 The RfC for mixed xylene was used as a surrogate.Draft Risk Assessment for the Of f

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22 (ERPGs), with the recognition that the ultimate interpretation of any potential risks associated with an estimated exceedance of a particular reference level depends on the definition of that level and any limitations expressed therein. Comparisons amo ng different available inhalation health effect reference values (both acute and chronic) for selected HAP can be
found in a n EPA document of graphical arrays [ 19 ].

California Acute Reference Exposure Levels (RELs ). The California Environmental
Protecti on Agency (CalEPA) has developed acute dose

- response reference values for many
substan ces, expressing the results as a cute inhalation Reference Exposure Levels (RELs).

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

“ t he concentration level at or below which no adverse health effects are anticipated for a specified exposure duration . [ 20 ]

. RELs are based on the most sensitive, relevant,
adverse heal th effect reported in the medical and toxicological literature. RELs are designed to protect the most sensitive individuals in the population by the inclusion of margins of safety. Since margins of safety are incorporated to address data gaps and

uncerta inties, 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 Concen trations (RfCs) for chronic exposures (and, in fact, California also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory
Committee (NAC) on Acute Exposure Guideline Levels (NAC/AEGL) f or Haza rdous
Substances , and then reviewed and published 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 limits for the general public and are applicable to emergency exposures ranging from 10 min to 8 h.” Their intended application is “for conducting risk assessments to aid in the development of emergency preparedness and prevention plans, as well as real time emergency response actions, for accidental chemical releases at fixed facilities and from transport carriers.” The
document states that “the primary purpose of the AEG L program and the NAC/AEGL Committee is to develop guideline levels for once

- in

- a

- lifetime , short

- term exposures to airborne concentrations of acutely toxic, high

- priority chemicals.” In detailing the intended application of AEGL values, the document stat es that

, “ It is anticipated that the AEGL values will be used for regulatory and nonregulatory purposes by U.S. Federal and State agencies, and possibly the international community in conjunction with chemical emergency response, planning, and prevention p rograms. More specifically, the AEGL values will be used for conducting various risk assessments to aid in the development of emergency preparedness and prevention plans, as well as real

- time emergency response actions, for accidental chemical
releases at fixed facilities and from transport carriers.”

The NAC/AEGL defines AEGL

- 1 and AEGL

- 2 as:

“ AEGL

- 1 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, including susceptible i ndividuals, couldDraft Risk Assessment for the Of f

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23 experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. However, the effects are not disabling and are transient and reversible upon cessation of

exposure. ”

“ AEGL

- 2 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, including susceptible individuals, could experience irreversible or other serious, long

- lasting adverse health effects or an impaired ability to escape. ”

“ Airborne concentrations below AEGL

- 1 represent exposure levels that can produce mild and progressively increasing but transient and nondisabling odor, taste, and sensory irritation or certain asymptomatic, nonsensory effects. With increasing airborne
concentration s 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 subpopu lations, such as infants, children, the elderly, persons with asthma, and those with other illnesses, it is recognized that individuals, subject to unique or idiosyncratic responses, could experience the effects described at concentration s below the

corres ponding AEGL.”

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [ 21 ] for acute exposures at three different levels of severity. These guideline s 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

- threatenin g (ERPG

- 3).

ERPG values (

- http://www.aiha.org/get

involved/AIHAGuidelineFoundation/EmergencyResponsePlanningGuidelines/Pages/default.a

spx ) are described in their supporting documentation as follows: “ERPGs are air concentration guidelines for single exposures to agen ts and are intended for use as tools to assess the adequacy of accident prevention and emergency response plans, including transportation emergency planning, community emergency response plans and incident prevention and mitigation.”

ERPG

- 1 and ERPG

- 2 va lues 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 pe rceiving a clearly defined, objectionable
odor. ”

“ ERPG

- 2 is the maximum airborne concentration below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing or developing
irreversible or other serious healt h effects or symptoms which could impair an individual's ability to take protective action. ”Draft Risk Assessment for the Of f

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2 4 The emissions inventory for the OSWRO source category include s emissions of 57 HAP with relevant and available quantitative acute dose

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

- 3

.

Table 2.6

- 3 Dose

- Response Values for Acute Exposure

Pollutant CAS

Number AEGL

- 1

(1

- hr) (mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

1 (mg/m 3 ) ERPG

- 2 (mg/m 3 ) REL

1,1

- Dimethylhydrazine 5714 7 7.4
1,2

- Epoxybutane 10688 7 210 410
1,3

- Butadiene 10699 0 1500 12000 22 440
1,4

- Dioxane 12391 1 61 1200 3
2,4

- Toluene diisocyanate 58484 9 0.14 0.59 0. 071 1.1 Acetaldehyde 75070 81 490 18 360 0.47

Acetonitrile 7505 8 22 540

Acrolein 107028 0.069 0.23 0. 11 0. 34 0.0025 Acrylic a cid 79107 4.4 140 3 15 0 6 Acrylonitrile 10713 1 10 130 22 77 Allyl chloride 10705 1 8.8 170 9.4 130

Aniline 6253 3 30 46

Benzene 71432 170 2600 16 0 48 0 1.3 Benzyl chloride 10044 7 5.2 52 0.24 Biphenyl 92524 61

Carbon d isulfide 75150 40 500 3.1 160 6.2

Carbon t etrachloride 56235 280 1200 130 63 0 1.9

Chlorine 7782505 1.5 5.8 2.9 8.7 0.21

Chlorobenzene 108907 46 690

Chloroform 67663 310 24 0 0.15 Chloromethyl methyl ether 10730 2 1.6 3.3

Cumene 98828 250 1500

Dichlorvos 6273 7 0.99 5.1 Dimethyl formamide 6812 2 270 6 30 0 Dimethyl sulfate 7778 1 0.12 0.62 Epichlorohydrin ( 1

- Chloro

- 2,3

-

e poxypropane) 106898 22 91 19 76 1.3 Ethyl a crylate 140885 34 150 0.041 12 0 Ethyl b enzene 100414 140 4800 Ethylene d ibromide 106934 130 180 Ethylene d ichloride 107062 200 810 Ethylene o xide 75218 81 90 Formaldehyde 50000 1.1 17 1. 2 1 2 0.055Draft Risk Assessment for the Of f

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25

Table 2.6

- 3 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
Glycol Ethers 16
Ethylene glycol ethyl ether 11080 5 0.37 Ethylene glycol methyl ether 10986 4 0.093 Glycol ethers 18 1 0.093

Hexachlorobutadiene 8768 3 11 32

Hexane 110543 12000 Hydrazine 302012 0.13 17 0. 65 6.5 Maleic anhydride 10831 6 0.8 8

Methanol 67561 690 2700 260 13 00 28 Methyl b romide 74839 820 19 0 3.9 Methyl c hloride 74873 1900 83 0 Methyl hydrazine 6034 4 3.2 Methyl iodide 7488 4 150 290 Methyl m ethacrylate 80626 70 490 Methyl tert

- butyl e ther 1634044 180 2100 Methylene c hloride 75092 690 1900 100 0 26 00 14

Phenol 108952 58 89 3 8 190 5.8 Phosphine 780351 2 2.8 0.7 Propionaldehyde 123386 110 620 Propylene oxide 7556 9 170 690 12 0 5 90 3.1 Styrene 100425 85 550 210 110 0 21

Tetrachloroethene 127184 240 1600 68 0 14 00 20

Titanium tetrachloride 755045 0 0.54 7.8 5 20

Toluene 108883 750 4500 190 110 0 37 Trichloroethylene 79016 700 2400 54 0 27 00 Triethylamine 12144 8 2.8 Vinyl a cetate 108054 24 630 18 260 Vinyl c hloride 75014 640 3100 130 0 130 00 180 Xylenes (mixed) 1330207 560 4000 22

m

- Xylene 17 108383 22

o

- Xylene 18 95476 22

p

- Xylene 18 106423 22

16 The acute REL for ethylene glycol methyl ether was used as a su rrogate for glycol ether compounds without

an acute REL.

17 The REL for mixed xylenes was used as a surrogate.Draft Risk Assessment for the Of f

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26 

### 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 gen eral, 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 identifi ed and discussed. Further, the EPA Administrator’s March

1995 Policy for Risk Characterization [ 22 ] specifies that a risk characterization “be prepared in a manner that is clear, transparent, reasonable, and consistent with other risk
characterizations of similar scope prepared across programs in the Agency.” These principles of transparency and consistency have been reinforced by the Agency’s Risk Characterization

Handbook [ 23 ], in 2002 by the Agency’s information quality guidelines [ 24 ], and in the

OMB/OST P September 2007 Memorandum on Updated Principles for Risk Analysis 18 , 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, itera tive 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 individua l cancer risks and noncancer hazards, as well as cancer incidence estimates) along with a discussion of the major uncertainties associated with their derivation to provide decision makers with the fullest picture of the assessment and its
limitations.

For each carcinogenic HAP included in the 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 can cer 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 HAP are upper

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

zero.

For EPA’s list of carcinogenic HAP that act by a mutagenic mode

- of

- action [ 25 ], we applied
EPA’s Supplemental Guidance for Assessing Susceptibility from Early

- Life Exposure to Carcinogens [ 26 ]

. 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

18 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/sites/default/files/omb/assets/omb/memoranda/fy2007/m07

- 24.pdf )Draft Risk Assessment for the Of f

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27 small fraction of the total POM emissions may be reported as individual compounds, EPA expresses carcinogenic potency for compounds in this group in terms of benzo[a]pyrene equivalence, based on evidence that carcinogenic POM have the same mutagenic mechanism
of action as does benzo[a]pyrene. For this reason

, EPA implem entation policy [ 27 ] 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 was 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, “risk” for noncancer effects is expressed by comparing an exposure to a reference level as a ratio. The “hazard quotient” (HQ) is the estimated exposure divided by a reference level (e.g., the RfC). For a given HAP, exposures at or below the reference level (HQ≤1) are not likely to cause adverse health effects. As exposures increase above the reference 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 blo ck centroid. As discussed above, RfCs incorporate generally conservative uncertainty factors in the face of uncertain extrapolations, such that an HQ greater than one does not necessarily suggest the onset of adverse effects. The HQ cannot be translated to a probability that adverse effects will occur, and is unlikely to be proportional to adverse health effect outcomes in a population

.

Screening for potentially significant acute inhalation exposures also followed the HQ approach. We divided the maximum estimated acute exposure by each available short

- term threshold value to develop an array of HQ values relative to the various acute endpoints and thresholds. In general, when none of these HQ values are greater than one, there is no potential for acute risk. In those cases where HQ values above one are seen, additional information is used to determine if there is a potential for significant acute risks.Draft Risk Assessment for the Of f

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28 2.7.2 Mixtures
Since most or all receptors in these assessments receive exposures to multiple pollutants

r ather than a single pollutant, we estimated the aggregate health risks associated with all the exposures from a particular source category combined.

To combine risks across multiple carcinogens, our assessments use the mixtures guidelines’ [ 28

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

In assessing noncancer hazard from chronic exposures, in cases where different pollutants
cause adverse health effects via com pletely different modes of action, it may be inappropriate to aggregate HQs. In consideration of these mode

- of

- action differences, the mixtures guidelines support aggregating effects of different substances in specific and limited ways.
To conform to the se guidelines, we aggregated non

- cancer HQs of HAP that act by similar toxic modes of action, or (where this information is absent) that affect the same target organ. This process creates, for each target organ, a target

- organ

- specific hazard index (TOSHI ), defined as the sum of hazard quotients for individual HAP that affect the same organ or organ system. A ll TOSHI calculations presented here were based exclusively on effects occurring
at the “ critical dose” (i.e., the lowest dose that produces adverse health effects). Although HQs associated with some pollutants have been aggregated into more than one TOSHI, this has been done only in cases where the critical dose affects more than one target organ

. Because impacts on organs or systems that occur abov e 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 inhalati on screening and the variable nature of emissions and potential exposures, acute impacts were screened on an individual pollutant basis, not using the TOSHI approach.

2.7.3 Facility

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

- wide” risks using

NEI data and modeling as described in Section 2.2. For the facilities in the OSWRO source category , we estimated the maximum inhalation cancer and chronic noncance r risks associated with all HAP emissions sources at the facility, including emissions sources that are not part of th is source category but are located within a contiguous area and are under common control. We analyzed risks due to the inhalation of HAP for the populations residing within 50 kilometers of each facility. The results of the facility

- wide assessment are
summarized below in the r isk characterization section of this document. The complete results of the facility

- wide assessment are provided in Appendix 5 of this document, Detailed Risk Modeling Results

.Draft Risk Assessment for the Of f

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29 2.7.4 MACT

- Allowable Risk

The emissions data in the data set for the OSWRO source category are estimates of actual emissions on an annual basis. The risk results presented in the following sections are b ased
on these actual emissions. For the OSWRO source category, estimates of MACT

- allowable emissions were also estimated, and the risk results based on tho se emissions are presented below as well. For more detail, please refer to the MACT

- Allowable memo in docket for this action ( MACT

- Allowable Emissions for the Off

- Site Waste and Recovery Operations Source

Cat egory , located in Docket EPA

- HQ

- OAR

- 2012

- 0360

. )



## 3 Risk Results for the OSWRO Source Ca tegor y

3.1 Source Category Description and Results

The O SWRO source category includes facilities that store, treat, recycle, or dispose of certain wastes, used oil, or used so lvents from off

- site locations. Specifically, facilities in the OSWRO source category handle off

- site material, which is defined as any material generated from commercial, industrial, agricultural, and mining operations or community activities that is recycled, reused, reprocessed, disca rded, or is being accumulated, stored, or treated (physically, chemically, biologically, or thermally) before being disc arded, discharged, or recycled. The activities that take place at OSWRO sources vary widely depending on the specific treatment, storag e, or other handling processes that are being conducted (e.g., treatment of wastewater, physical separation of waste mixtures, storage of wastes, reprocessing of wastes for recovery or recycling purposes, and other processes). Potential
HAP emission sourc es at OSWRO operations include tanks, surface impoundments, containers, oil

- water separators, process vents, equipment leaks, and individual drain systems
and oth er material conveyance systems.

The data set for the OSWRO source category contains 38 faci lities identified with a n OSWRO MACT code 806 in the 2005 National

- scale Air Toxics Assessment (NATA) National Emissions Inventory (NEI) , as explained in Section 2.1 of this document

. The 2005

NATA NEI was updated for this category with data from industry and enhanced quality assurance of facility and emission locations

. In the NEI, t hirty seven (37) of these facilities are identified as major sources one facility is identified as an area source , however we believe that all 38 facilities are major sources

.

The emissions for the O SWRO source category data set (of 38 facilities) are summarized in
Table 3.1

- 1 . The total HAP emissions for the source category are approximately 80 tons per

year. Based on these data, the HAP emitted in the largest quantities ac ross these 38 facilities

are toluene, methylene chloride, methanol, tetrachloroethene, xylenes (mixed), hydrochloric acid, methyl tert

- butyl ether, acetonitrile, methyl isobutyl ketone, chlorine, 1,1,1

- trichloroethane, ethyl benzene, acetaldehyde, glycol ethers, hexane, trichloroethylene, formaldehyde, styrene, propionaldehyde, benzene, 2,4

- toluene diamine, carbon tetrachloride, chloroform, ethylene dichloride, ethylene glycol, 1,2

- epoxybutane, naphthalene, carbon disulfide, 1,1,2

- tri chloroethane, vinyl acetate, phenol, hydrofluoric acid, chlorobenzene,Draft Risk Assessment for the Of f

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30 ethylene oxide, methylene diphenyl diisocyanate, cresols (mixed), nitrobenzene, acrylonitrile, vinylidene chloride, aniline, methyl methacrylate, propylene dichloride, phthalic anhydrid e, lindane (gamma

- hch), 2,4

- toluene diisocyanate, titanium tetrachloride, 2

- nitropropane, m

cresol (3

- methylphenol), p

- cresol (4

- methy p henol)

, dimethyl formamide, acetamide, and 2,4

- d, salts and esters . These 5 2 chemicals account for 99 percent of the tot al emissions by mass. Persistent and bioaccumulative HAP (PB HA P) 19 reported as emissions from these facilities
include p olycyclic o rganic ma tter ( analyzed as benzo(a)pyrene ), polychlorinated biphenyls, lindane (gamma

- hch), chlordane, hexachlorobenzene, me thoxychlor, toxaphene, heptachlor,
and trifluralin

. The following environmental HAP are emitted from the Off

- Site Waste and Recovery Operations source category and are included in the environmental risk screen: POM, hydrogen chloride and hydrogen fluorid e.

Table 3.1

- 1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk

Assessment and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting

HAP ( 38
facilities in 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?

Toluene 15 25 

 

 Methylene Chloride 11 21 

 

 

 Methanol 8 26 

 

 Tetrachloroethene 8 22 

 

 

 Xylenes (mixed) 7 24 

 

 Hydrochloric Acid 6 7 

 

 Methyl Tert

- butyl Ether 5 11 

 

 

 Acetonitrile 3 13 

 

 Methyl Isobutyl Ketone 3 24 

 Chlorine 2 3 

 

 1,1,1

- trichloroethane 2 9 

 

 Ethyl Benzene 1 21 

 

 

 Acetaldehyde 1 3 

 

 

 Glycol Ethers

  Glycol Ethers 1 8 

 

 Ethylene Glycol Ethyl Ether 0.002 2 

 

 Ethylene Glycol Methyl Ether 0.002 1 

 

 H exane 0.8 14 

 

 Trichloroethylene 0.6 16 

 

 

 Formaldehyde 0.4 12 

 

 

 Styrene 0.4 17 

 

 Propionaldehyde 0.3 2 

 



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

EPA

- 453K

- 04

- 001A, as referenced in the NPRM and provided on the EPA’s Technology Transfer Network website for Fate, Exposure, and Risk Assessment at http://www.epa.gov/ttn/fera/ris k_atra_vol1.html

.Draft Risk Assessment for the Of f

- Site Waste and Recovery Operations Source Category

-- May 2014 FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

31 Table 3.1

- 1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk

Assessment and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting
HAP ( 38
facilities in 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?

Benzene 0.3 15 

 

 

 2,4

- toluene Diamine 0.3 2 

 Carbon Tetrachloride 0.3 8 

 

 

 Chloroform 0.3 11 

 

 Ethylene Dichloride 0.3 8 

 

 

 Ethylene Glycol 0.3 9 

 1,2

- epoxybutane 0.2 2 

 

 Naphthalene 0.2 16 

 

 Carbon Disulfide 0.2 6 

 

 1,1,2

- trichloroethane 0.2 6 

 

 Vinyl Acetate 0.2 7 

 

 Phenol 0.2 10 

 

 Hydrofluoric Acid 0.1 4 

 

 Chlorobenzene 0.1 7 

 

 Ethylene Oxide 0.1 1 

 

 

 Methylene Diphenyl Diisocyanate 0.1 1 

 

 Cresols (mixed) 0.1 6 

 Nitrobenzene 0.1 6 

 

 Acrylonitrile 0.1 6 

 

 

 Vinylidene Chloride 0.1 2 

 Aniline 0.07 5 

 

 

 Methyl Methacrylate 0.06 6 

 

 Propylene Dichloride 0.05 4 

 Phthalic Anhydride 0.05 4 

 Lindane (gamma

- hch) 0.05 3 

 

 

 2,4

- toluene Diisocyanate 0.05 3 

 

 

 Titanium Tetrachloride 0.04 4 

 

 2

- nitropropane 0.04 3 

 

 M

- cresol (3

- methylphenol) 0.04 2 

 P

- cresol (4

- methy Phenol) 0.04 2 

 Dimethyl Formamide 0.04 9 

 

 Acetamide 0.04 2 

 2,4

- d, Salts And Esters 0.04 3

P

- dichlorobenzene 0.03 4 

 

 1,3

- butadiene 0.03 2 

 

 

 O

- cresol 0.03 1 

 Dichloroethyl Ether 0.03 2 

Draft Risk Assessment for the Of f

- Site Waste and Recovery Operations Source Category

-- May 2014 FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE

32 Table 3.1

- 1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk

Assessment and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting
HAP ( 38
facilities in 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?

Chlordane 0.03 5 

 

 

 Hexachlorobenzene 0.03 6 

 

 

 Hexachlorobutadiene 0.03 4 

 

 

 Hexachloroethane 0.02 5 

 1,4

- dioxane 0.02 3 

 

 

 Epichlorohydrin 0.02 4 

 

 

 Acetophenone 0.02 4 Methoxychlor 0.02 4 

 Maleic Anhydride 0.02 4 

 

 2,4

- dinitrotoluene 0.02 2 

 

 Dibutylphthalate 0.02 3 Ethyl Acrylate 0.02 6 

 Cumene 0.02 8 

 

 Isophorone 0.02 1 

 Polychlorinated b iphenyls 0.02 3 

 

 1,1,2,2

- tetrachloroethane 0.01 4 

 Vinyl Chloride 0.01 4 

 

 

 M

- xylene 0.01 4 

 

 Acrylamide 0.01 4 

 

 Toxaphene 0.01 3 

 

 Hexachlorocyclopentadiene 0.01 3 

 Bis(2

- ethylhexyl)phthalate 0.01 3 

 

 1,2,4

- trichlorobenzene 0.01 3 

 P

- xylene 0.01 2 

 

 Dibenzofuran 0.009 1 Carbaryl 0.008 3 Dimethyl Phthalate 0.008 3 Ethyl Carbamate 0.008 3 

 Acrylic Acid 0.008 4 

 

 Methyl Chloride 0.008 3 

 

 Triethylamine 0.008 4 

 

 Pentachlorophenol 0.007 2 

 

 Biphenyl 0.007 3 

 4

- nitrobiphenyl 0.007 1

N

- nitrosomorpholine 0.007 1 

 Nitrosodimethylamine 0.007 1 

 Heptachlor 0.007 5 

 

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33 Table 3.1

- 1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk

Assessment and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting
HAP ( 38
facilities in 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? Methyl Bromide 0.006 2 

 

 Pentachloronitrobenzene 0.006 1

O

- toluidine 0.006 3 

 4

- nitrophenol 0.005 1

O

- xylene 0.005 2 

 

 3,3'

- dimethylbenzidine 0.005 1

4,4'

- methylene Bis(2

- chloroaniline) 0.005 1 

 Dimethylcarbamoyl Chloride 0.005 1

Benzidine 0.005 2 

 

 2,4

- dinitrophenol 0.005 1 Ethyl Chloride 0.005 1 

 Ethylene Dibromide 0.004 2 

 

 

 3,3'

- dimethoxybenzidine 0.004 1
2,4,6

- trichlorophenol 0.004 1 

 Hydrazine 0.004 3 

 

 

 1,3

- propane Sultone 0.004 1 

 Captan 0.004 3
2,4,5

- trichlorophenol 0.003 1

Chlorobenzilate 0.003 1 

 Diethanolamine 0.003 2 

 Dimethyl Sulfate 0.002 3 

 Propylene Oxide 0.002 2 

 

 

 4,4'

- methylenedianiline 0.002 1 

 

 Ethylene Thiourea 0.002 1 

 

 Quinone 0.002 1 Allyl Chloride 0.002 1 

 

 

 Methyl Iodide 0.002 1 

 Benzyl Chloride 0.002 3 

 

 1,3

- dichloropropene 0.002 1 

 

 P

- dimethylaminoazobenzene 0.002 1 

 Ethylidene Dichloride 0.002 2 

 

 N,n

- dimethylaniline 0.001 2
1,2

- dibromo

- 3

- chloropropane 0.001 1 

 

 1,1

- dimethylhydrazine 0.001 1 

 1,2

- diphenylhydrazine 0.001 1 

 Benzotrichloride 0.001 1 Phosphorus, White 0.001 1Draft Risk Assessment for the Of f

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34 Table 3.1

- 1 Summary of Emissions from the OSWRO Source Category Used in the Residual Risk

Assessment and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting
HAP ( 38
facilities in 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? Hydroquinone 0.001 2 Polycyclic Organic Matter

  2

- acetylaminofluorene 0.001 1 

 

 Dichlorvos 0.0008 1 

 

 3,3'

- dichlorobenzidine 0.0007 1 

 Chloromethyl Methyl Ether 0.0006 1 

 Bromoform 0.0004 1 

 Styrene Oxide 0.0004 1 

 Acrolein 0.0002 2 

 

 Trifluralin 0.0001 2 

 Methyl Hydrazine 0.00003 1 

 Phosphine 0 1 

 



a Notes for how HAP were speciated for risk assessment:

 For emissions reported generically as “Glycol Ethers” or specific glycol ethers not found on EPA’s Technology Transfer Network for air toxics (see footnote b), emissions were treated as ethylene glycol methyl ether.

b Specific dose

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

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

.



### 3.2 Risk Cha racterization

This section presents the results of the risk assessment for the O SWRO source category based on the modeling methods described in the previous sections

. All baseline risk results are developed using the best estimates of actual HAP emission s summarized in the previous
section. The basic chronic inhalation risk estimates presented here are the maximum individual lifetime cancer risk, the maximum chronic hazard index, and the cancer incidence. We also present results from our acute inhalatio n impact screening in the form of maximum hazard quotients, as well as the results of our preliminary screen for potenti al 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 index 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 t he facility

- specific risk assessment results is available in Appendix 5 of this document, Draft Detailed Risk Modeling Results

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35 Table 3 .2

- 1 summarize s the chronic and acute inhalation risk results for this source category.
The re sults of the chronic inhalation cancer risk assessment for the OSWRO source category
estimate that the maximum lifetime individual cancer risks posed by these facilities could be as high as 9

- in

- 1 million. The major contributors to this risk are benzidine, and 2,4

- toluene
diamine . Approximately 210 ,000 people were estimated to have cancer risks at or above 1

- in

1 in a million as a result of the emissions from this source category . The maximum chronic

non

- cancer target organ specific hazard index (TOSHI) value for the source category could be
up to 0.6 associated with emissions of chlorine, indicating no significant potential for chronic

non

- cancer impacts.

Analysis of potential differences between chronic inhalation risks based on actual emiss ion levels and the maximum emissions allowed under the MACT standards (i.e., MACT

allowable emissions) was conducted. See the memo, MACT

- Allowable Emissions for the Off

Site Waste and Recovery Operations Source Category , for more details on the calculatio n of
these allowable risks. The maximum individual lifetime cancer risk based on allowable
emissions is estimated to be 20

- in

- 1 million, while the maximum chronic noncancer TOSHI
value is estimated to be 1.

Worst

- case acute hazard quotients ( HQs ) were calculated for every emitted HAP that has an
acute benchmark , based on actual emissions . For cases where the screening acute HQ was greater than 1, we further refined the estimates by determining the highest HQ value that might occur outside facilit y boundaries. Analysis of potential off

- site impacts for the OSWRO source category identified no facility with an acute value greater than 1

.

As presented above, t he PB

- HAP emitted by facilities in this category includ e polycyclic organic matter (POM) ( 2

- acetylaminofluorene analyzed as benzo(a)pyrene TEQ) ( 1 facilit y), polychlorinated biphenyls (3 facilities), hexachlorobenzene (6 facilities), chlordane (5 facilities), lindane (gamma hch) (3 facilities), methoxyclor (4 facilities), toxaphene (3 facilities), heptachlor (5 facilities), and trifluralin (2 facilities). To identify potential multipathway health risks from PB

- HAP other than lead, we first performed a screening analysis (Tier I ) that compared emissions of PB

- HAP emitted fro m the OSWRO source
category (based on actual emissions) to screening emission rates ( see section 2.5) , where those screening emission rates are available. Of the PB

- HAP emitted by this category, the POM compound 2

- acetylaminofluorene has a screening emission rate. The emissions of the

POM 2

- acetylaminofluorene were below the screening va lue for POM. The remaining PB

HAP do not currently have multipathway screening values and so are not evaluated for potential non

- inhalation risks. As shown in Table 3.1

- 1, these HAP are not emitted in appreciable quantities from off

- site waste and recove ry operations.

We conducted a screening

- level evaluation of the potential adverse environmental risks associated with emissions of the following environmental HAP from the Off

- Site Waste and Recovery Operations source category: POM, hydrogen chloride

, and hydrogen fluoride. The results of the environmental screening analysis are summarized in Table 3.2

- 2 . In our Tier I analysis, emissions of POM did not exceed the threshold emission rates for any of the ecological benchmarks (either the LOAEL or NOAEL ) for any facility in the source category

. Therefore, we did not conduct a Tier II environmental screening analysis. For hydrogenDraft Risk Assessment for the Of f

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36 fluoride and hydrogen chloride, the average modeled concentration around each facility (i.e., the average concentration of a ll off

- site data points in the modeling domain) did not exceed
the ecological benchmark s

. In addition , each individual modeled concentration of hydrogen chloride and hydrogen fluoride (i.e., each off

- site data point in the modeling domain) was
below the e cological benchmarks for all facilities.

Table 3.2

- 1 Summary of Source Category Level Inhalation Risks for OSWRO

Result HAP “Drivers” Facilities in Source Category

Number of Facilities Estimated to be in Source Category 20 38 n/a

Number of Facilities Identified in the NEI and
Modeled in Risk Assessment 38 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 9 benzidine, 2,4

- toluene diamine

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 0 n/a

Greater than or equal to 1 in 1 million 8 benzidine, 2,4

- toluene diamine

,

n itrosodimethylamine , n

n itrosomorpholine , e thylene oxide

, l indane (gamma

- HCH)

, h exachlorobenzene , h eptachlor

, f ormaldehyde , n itrobenzene , c arbon
tetrachloride , b enzene , h ydrazine

,

e thylene dichloride , e thyl carbamate

,

a cetamide , n aphthalene , a crylonitrile

, 2,4

- t oluene diisocyanate , c hlordane

, t oxaphene

, e thyl benzene

Chronic Noncancer Risks

Maximum Respiratory Hazard Index 0.6 chlorine

Num ber of Facilities with Maximum Respiratory Hazard Index:

Greater than 1 0 n/a

Acute Noncancer Results Maximum Acute Hazard Quotient 1 glycol ethers (REL)

Number of Facilities With Potential for Acute
Effects 0 n/a

Population Exposure Number of People Living Within 50 Kilometers

of Facilities Modeled 35,000,000 n/a

Number of People Exposed to Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a

20 As explained in Section 2.1 of this document, the list of facilities began with 53 facilities and there are 38 facilities included in the modeling file used for this risk assessment.Draft Risk Assessment for the Of f

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37 Table 3.2

- 1 Summary of Source Category Level Inhalation Risks for OSWRO

Result HAP “Drivers” Greater than or equal to 10 in 1 million 0 n/a Greater than or equal to 1 in 1 million 2 1 0 ,000 n/a

Number of People Exposed to Noncancer Respiratory Hazard Index:

Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.02 n/a

Contribution of HAP to Cancer Incidence:

Benzidine 7 3% n/a 2,4

- Toluene diamine 19 % n/a

Table 3.2

- 2 Summary of Environmental Risks Screen Results for OSWRO

Environmental

HAP Number of Facilities In Category Exceeding Percent of Modeled Area in Category Exceeding 2

Tier I Screen Tier II Screen 1 NOAEL LOAEL NOAEL LOAEL NOAEL LOAEL

PB

HAP POM None None

- - 0% 0%

Acid

Gases 3 HF NA N one

- - NA 0%

HCL 4 N A N one

- - NA 0%

NA

– Not Applicable.

1

- Tier II screen is performed for PB

- HAP when there are exceedances of the Tier I screen. The acid gas screen
is a one tier screen.

2

- A value of 0% indicates that none of the modeled data points exceeded the benchmark. For PB

- HAP the percent area is based on the Tier II results, if a Tier II an alysis is performed. Otherwise, the percent area is based

on the Tier I results.

3

– For HF, we evaluated two benchmarks, one from Canada and the other from the State of Washington. Although, they are both considered to be LOELs

- the level between a NO AEL and a LOAEL, we have listed the
results under the LOAEL column.

4

– For HCL, we evaluated one benchmark at the LOAEL level.

The facility

- wide MIR and TOSHI, available in Appendix 5 of this document ( Draft Detailed
Risk Results ) , are based on emission s, as collected in the NEI, from all emissions sources at the identified facilities. The results of the facility

- wide assessme nt are summarized in Table

3.2

- 3 . The results indicate that 1 7 facilities with OSWRO processes have facility

- wide cancer MIR gre ater than or equal to 1

- in

- 1 million. The maximum facility

- wide MIR is 20 0 in a
million due to emiss ions of beryllium compounds from cement manufacturing , with the OSWRO source category contributing less than 1 percent of the risk. The maximum facility

wide TOSHI is 4

, and occurs at 2 facilities. At one, the HI is driven mainly by emissions of chlorine from industrial inorganic chemical manufacturing processes and synthetic organic chemical manufacturing proc esses , while the other is driven mainly by emissions of berylliumDraft Risk Assessment for the Of f

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38 compounds from cement manufacturing

. In each instance, t he source category contributes less than 1 percent to the facility

- wide TOSHI.

Table 3.2

- 3 Source Category Contribution to Facility

- Wide Cancer Risks

OSWRO Number of Facilities Binned by Facility

- Wide MIR (in 1 million) Source Category MIR Contribution to Facility

- Wide

MIR < 1 1≤ MIR<10 10≤ MIR<100 > 100 Total

> 90% 7* 4 0 0 1 1
50

- 90% 4 3 0 0 7
10

- 50% 1 0 0 0 1
< 10% 9 5 4 1 1 9

Total 2 1 * 1 2 4 1 38 *

* Includes one facility for which both source category and facility

- wide modeled risk is 0.



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

4.1 Exposure Modeling Uncertainties

Although every effort has been made to identify all the relevant facilities and emission points, as well as to develop accurate estimates of the annual emission rates for all relevant HAP, the uncertainties in our emission inventory likely dominate the uncert ainties in our exposure modeling estimates. The chronic ambient modeling uncertainties are considered relatively small in comparison, since we are using EPA’s refined local dispersion model with site

specific parameters and reasonably r epresentative meteorology. If anything, the population exposure estimates are biased high by not accounting for short

- or long

- term population mobility, and by neglecting processes like deposition, plume depletion, and atmospheric degradation. Additional ly, estimates of the maximum individual risk (MIR) contain uncertainty , because they are deriv ed at census block centroid locations rather than actual
residences. This uncertainty is known to create potential underestimates and overestimates of
the actual MIR values for individual facilities, but, overall, it is not thought to have a significant impact on the estimated MIR for a source category. Finally, we did not factor in the possibility of a source closure occurring during the 70

- year chronic exposure period, leading to a potential upward bias in both the MIR and population risk estimates; nor did we factor in the possibility of population growth during the 70

- year chronic exposure period, leading to a potential downward bias in both the MIR and popula tion risk estimates.

A sensitivity analysis performed for the 1999 NATA found that the selection of the meteorology dataset location could result in a range of chronic ambient concentrations which varied from as much as 17% below the predicted value to as much as 84% higher than theDraft Risk Assessment for the Of f

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39 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 purpose ly biased the acute screening results high, considering that they depend upon the joint occurrence of independent factors, such as hourly emissions rates, meteorology and human activity patterns. Furthermore, in cases where multiple acute threshold values are considered scientifically acceptable we have chosen the most conservative of these threshold
values , erring on the side of overestimating potential health risks from acute exposures. In the cases where these results indicated the potential for exceed ing short

- term health thresholds, we have refined our assessment by developing a better understanding of the geography of the facility relative to potential exposure locations

.



### 4.2 Uncertainties in the Dose

- Response Relationships

In the sections that fol low, separate discussions are provided on uncertainty associated with cancer potency factors and for noncancer reference values. Cancer potency values are derived for chronic (lifetime) exposures. Noncancer reference values are generally derived for
chro nic exposures (up to a lifetime), 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 exposu re throughout the duration specified. 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.

Although every effort is made to identify peer

- review ed dose

- response values for all HAP
emitted by the source category included in an assessment , some HAP have no peer

- reviewed cancer potency values or reference values for chronic no n

- cancer or acute effects (inhalation or ingestion) . Since exposures to these pollutants cannot be included in a quantitative risk estimate, an understatement of risk for these pollutants at environmental exposure levels is possible.

Additionally, chroni c dose

- response values for certain compounds included in the assessment may be under EPA IRIS review and revised assessments may determine that these pollutants are more or less potent than currently thought. We will re

- evaluate risks if, as a result of t hese 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 atten d the development of cancer potency factors by CalEPA, the source of peer

- reviewed cancer potency factors
used where EPA

- developed values are not yet available. To place this discussion in context,Draft Risk Assessment for the Of f

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40 we provide a quote from the EPA’s Guidelines for Carcinog en Risk Assessment [ 30 ] (herein
referred to as Cancer Guidelines ). “The primary goal of EPA actions is protection of human health; accordingly, as an Agency policy, risk assessment procedures, including default options that are used in the absence of scientific data to the contrary, should be health 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). 21 In some circumstances, the true risk could be as low as zero; however, in other circumstances the risk could also be greater. 22 When developing an upper bound estimate of risk and to provide risk values that do not underestimate risk, EPA generally relies on conservative default approaches. 23 EPA also uses the upper bound (rather than lower bound or central) estimates in its assessments, although it
is no ted 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 expresse d qualitatively. Uncertainties may vary substantially among cancer risk assessments associated with exposures to different pollutants,

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

22 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.

23 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 correc t scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An Examination of EPA Risk Assessment Principles and Practices,

EPA/100/B

- 04/001 available at: http://www.epa.gov/osa/pdfs/ratf

- final.pdf.Draft Risk Assessment for the Of f

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41 since the assessments employ different databases with different strengths and limitations and the procedures employed ma y differ in how well they represent actual biological processes for
the assessed substance. EPA’s Risk Characterization Handbook also recommends that risk characterizations present estimates demonstrating the impact on the assessment of alternative
choice s, data, models and assumptions [ 31 ]. 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 experimenta l 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

tu mors would occur in humans. 24 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 specie s responses can lead to either under

- estimation or over

- estimation of human cancer risks.

(2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead to differences in risk predictions. For example, the measure of dose is commonly expressed in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, data may support development of a pharmacokinetic model for the absorption, distribution, metabolism and excretion of an agent, which may result in improved dose metrics (e.g., average blood concentration of the pollutant or the quantity of agent metabolized in the body). Quantitative uncertainties result when the appropriate choice of a dose metric is uncertain or when dose
metric estimates are them selves 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 differ ences in rates of process according to species size and empirical comparisons of toxicity between experimental animals and humans. For a particular pollutant, the quantitative difference in cancer potency between experimental animals and humans may be eit her greater than or less than that estimated by baseline scientific scaling predictions due to uncertainties associated with limitations in the
test data and the correctness of scaled estimates.

(4) EPA cancer risk estimates, whether based on epidemiolo gical or experimental animal data, are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which there is a specified excess risk of cancer, which is used as the point of departure (or POD) for
the remainder of the calculation. Statistical uncertainty in developing a POD using a benchmark dose (BMD) approach is generally addressed though use of the 95% lower confidence limit on the dose at which the specified excess risk occurs (the BMDL),

24 Per the EPA Cancer Guidelines: “The default option is that positive effects in animal cancer studies indicate that the agent under s tudy can have carcinogenic potential in humans.” and “Target organ concordance is not a prerequisite for evaluating the implications of animal study results for humans.”Draft Risk Assessment for the Of f

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42 decreasing the likelihood of understat ing risk. EPA has generally utilized the multistage model for estimation of the BMDL using cancer bioassay data (see further discussion below).

(5) Extrapolation from high to low doses is an important, and potentially large, source of uncertainty in canc er risk assessment. EPA uses different approaches to low dose risk assessment (i.e., developing estimates of risk for exposures to environmental doses of an agent from observations in experimental or epidemiological studies at higher dose) depending
on th e 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 calculat ed 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) o r 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 line ar dose

- response to be appropriate for pollutants that interact with DNA and induce mutations. Pollutants whose effects are additive to background biological processes in cancer development can also be predicted to have low

- dose linear responses, although the slope of this relationship may not be the same as the slope estimated by the straight line approach.

EPA most frequently utilizes a linear low

- dose extrapolation approach as a baseline 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 appropriately applied as part of EPA’s cancer risk assessment pro cess, provide an upper bound estimate of risk and generally provide a health protective approach. Note that another source of uncertainty is the
characterization of low

- dose nonlinear, non

- threshold relationships. The National Academy
of Sciences has enc ouraged the exploration of sigmoidal type functions (e.g., log

- probit models) in representing dose response relationships due to the variability in response within human populations. Another National Research Council (NRC) report [ 32 ] suggests that
models based on distributions of individual thresholds are likely to lead to sigmoidal

- shaped
dose

- response functions for a population. This report notes sources of variability in the human population: “One might expect these individual tolerances to vary exten sively in humans depending on genetics, coincident exposures, nutritional status, and various oth er susceptibility factors...” Thus, if a distribution of thresholds approach is considered for a carcinogen risk assessment, application would depend on abili ty of modeling to reflect the degree of variability in response in human populations (as opposed to responses in bioassays with genetically more uniform rodents). Note also that low dose linearity in risk can arise for reasons separate from population var iability: 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.Draft Risk Assessment for the Of f

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43 As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight line app roach from the BMDL. This is equivalent to using an upper confidence limit on the slope of the straight line extrapolation. The impact of the choice of the BMDL on bottom line risk estimates can be quantified by comparing risk estimates using the BMDL va lue to central estimate BMD values, although these differences are generally not a large contributor to uncertainty in risk assessment (Subramaniam et. al., 2006) [ 33 ]. It is important to note that earlier EPA assessments, including the majority of those f or 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 o n straight line extrapolation from a POD do not show large differences from those based on the upper confidence limit of the multistage
model.

(6) Cancer risk estimates do not generally make specific adjustments to reflect the variability in response with in the human population

— resulting in another source of uncertainty in assessments. In the diverse human population, some individuals are likely to be more sensitive to the action of a carcinogen than the typical individual, although compound

- specific
da ta to evaluate this variability are generally not available. There may also be important life stage differences in the quantitative potency of carcinogens and, with the exception of the recommendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic mode of action, risk assessments do not generally quantitatively address life stage differences. However, one approach used commonly in EPA assessments that may help address variability in response is to extrapolate human response from r esults observed in the most sensitive species and sex tested, resulting typically in the highest URE which can be supported by reliable data, thus supporting estimates that are designed not to underestimate risk in the face of uncertainty and variability.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure levels that are intended to be

health

- protective. That is, EPA and other organizations which develop noncancer reference values (e.g., the Agency for Toxic Substan ces 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 25 e.g., factors of 10 or 3,

25 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[D efault] 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 As sessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An examination of EPA Risk Assessment Principles and Practices,

EPA/100/B

- 04/001 available a t: http://www.epa.gov/osa/pdfs/ratf

- final.pdf

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44 used in the absence of compound

- specific data; where data are available, uncertainty factors

ma y also be developed using compound

- specific information. When data are limited, more assumptions are needed and more default factors are used. Thus there may be a greater tendency to overestimate risk

— in the sense that further study might support develop ment of reference values that are higher (i.e., less potent) because fewer default assumptions are needed. However, for some pollutants it is possible that risks may be underestimated.

For non

- cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) for exposures via ingestion, and a Reference Concentration (RfC) for inhalation exposures.
These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or of a continuous inha lation exposure (RfC) to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. 26 To derive values that are intended to be “without appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach [ 34 ],[ 35 ] which includes consideration of both uncertainty and variability.

EPA begins by evaluating all of the avail able 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 occurs at the lowest dose, often using statistical mod eling of the available data, and then determines the appropriate point of departure (POD) for derivation of the reference value. A POD is determined by (in order of preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of the dose or concentration at which the toxic response was not significantly elevated (no
observed adverse effect level

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

A series of downward adjustments using default UFs is then applied to the POD to estimate
the reference value [ 36 ] . While collectively termed “UFs”, these factors account for a number of different quantitative considerations when utilizing observed animal (usually rodent) or human toxicity data in a risk assessmen t. The UFs are intended to account for: (1) variation in susceptibility among the members of the human population (i.e., inter

- individual variability); (2) uncertainty in extrapolating from experimental animal data to humans (i.e., interspecies difference s); (3) uncertainty in extrapolating from data obtained in a study with
less

- than

- lifetime exposure (i.e., extrapolating from subchronic to chronic exposure); (4) uncertainty in extrapolating from a LOAEL in the absence of a NOAEL; and (5) uncertainty
when the database is incomplete or there are problems with applicability of available studies

. When scientifically sound, peer

- reviewed assessment

- specific data are not available, default adjustment values are s elected for the individual UFs. For each type o f 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

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45 interspecies extrapolation is not required) the associated UF is not used. The major adjustment steps are described mor e fully below.

1) Heterogeneity among humans is a key source of variability as well as uncertainty. Uncertainty related to human variation is considered in extrapolating doses from a subset or
smaller

- sized population, often of one sex or of a narrow ra nge of life stages (typical of occupational epidemiologic studies), to a larger, more diverse population. In the absence of pollutant

- specific data on human variation, a 10

- fold UF is used to account for uncertainty
associated with human variation. Human variation may be larger or smaller; however, data to examine the potential magnitude of human variability are often unavailable. In some situations, a smaller UF of 3 may be applied to reflect a known lack of significant variability among humans.

2) Ex trapolation 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

ex trapolated to estimate the human response. While there is long

- standing scientific support
for the use of animal studies as indicators of potential toxicity to humans , there are uncertainties in such extrapolations. In the absence of data to the contrary , the typical approach is to use the most relevant endpoint from the most sensitive species and the most sensitive sex in assessing risks to the average human. Typically

, compound specific data to evaluate relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty in this extrapolation. Size

- related differences (allometric relationships) indicate that typically humans are more sensitive than rodents when compared on a mg/kg/day basis. The default choice of 10 for the interspec ies 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 u ncertainties; however, such dosimetric adjustments are not always possible. Information may not be available to quantitatively assess toxicokinetic or toxicodynamic differences between animals and humans, and in many cases a 10

- fold UF (with separate fact ors of 3 for toxicokinetic and toxicodynamic components) is used to account for expected species differences and associated uncertainty in extrapolating from laboratory animals to humans in the derivation of a reference value. If information on one or
the other of these components is available and accounted for in the cross

- species extrapolation, a UF of 3 may be used for the remaining component.

3) In the case of reference values for chronic exposures where only data from shorter
durations are available (e.g., 90

- day subchronic studies in rodents) or when such data are judged more appropriate for development of an RfC, an additional UF of 3 or 10

- fold is typically applied unless the available scientific information supports use of a different value.

4) Toxicity data are typically limited as to the dose or exposure levels that have been tested in individual studies; in an animal study, for example, treatment groups may differ in exposure by up to an order of magnitude. The preferred approach to arrive at a POD is to use BMD analysis; however, this approach requires adequate quantitative results for a meaningfulDraft Risk Assessment for the Of f

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46 analysis, which is not always possible. Use of a NOAEL is the next preferred approach after BMD analysis in determining a POD for deriving a heal th effect reference value. However, many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3

- fold is often applied.

5) The database UF i s intended to account for the potential for deriving an underprotective RfD/RfC due to a data gap preventing complete characterization of the chemical’s toxicity. In the absence of studies for a known or suspected endpoint of concern, a
UF of 10 or 3

- fold is typically applied.

There is no RfD or other comparable chronic health benchmark value for lead compounds. Thus, to address multipathway human health and environmental risks associated with emissions of lead from these facilities, ambient lead concent rations were compared to the NAAQS for lead. In developing the NAAQS for lead, EPA considered human health evidence reporting adverse health effects associated with lead exposure, as well as an EPA conducted multipathway risk assessment that applied model s to estimate human exposures to
air

- related lead and the associated risk (73FR at 66979). EPA also explicitly considered the uncertainties associated with both the human health evidence and the exposure and risk analyses when developing the NAAQS for lead . For example, EPA considered uncertainties in the relationship between ambient air lead and blood lead levels (73FR at 66974), as well as uncertainties between blood lead levels and loss of IQ points in children (73FR at 66981). In considering the evide nce and risk analyses and their associated uncertainties, the EPA
Administrator noted his view that there is no evidence

- or risk

- based bright line that indicates a single appropriate level. Instead, he noted, there is a collection of scientific evidence a nd judgments and other information, including information about the uncertainties inherent in many relevant factors, which needs to be considered together in making this public health policy judgment and in selecting a standard level from a range of reason able values (73FR at 66998). In so doing, the Administrator decided that, a level for the primary lead standard of 0.15 μg/m 3 , in combination with the specified choice of indicator, averaging time, and form, is requisite to protect public health, includin g the health of sensitive groups, with an adequate margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and exposure analyses, and their associated uncertainties can be found in EPA’s final rule revising the lead NAAQS (73 FR 66970

- 66981, November 12, 2008).

We also note the uncertainties associated with the health

- based (i.e., primary) NAAQS are likely less than the uncertainties associated with dose

- response values developed for many of the other HAP, particularly those HAP for which no human health data exist. In 1988, EPA’s IRIS program reviewed the health effects data regarding lead and its inorganic compounds and determined that it would be inappropriate to develop an RfD for these compounds, saying, “A great deal of information on the health effects of lead has been obtained through
decades of medical observation and scientific research. This information has been assessed in the development of air and water quality criteria by the Agency's Office of Health and
Envi ronmental Assessment (OHEA) in support of regulatory decision

- making by the Office of Air Quality Planning and Standards (OAQPS) and by the Office of Drinking Water (ODW). By comparison to most other environmental toxicants, the degree of uncertaintyDraft Risk Assessment for the Of f

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47 abou t the health effects of lead is quite low. It appears that some of these effects, particularly changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral development, may occur at blood lead levels so low as to be essentia lly without a threshold. The Agency's RfD Work Group discussed inorganic lead (and lead compounds) at two meetings (07/08/1985 and 07/22/1985) and considered it inappropriate to develop an RfD for inorganic lead.” EPA’s IRIS assessment for Lead and compou nds (inorganic) (CASRN 7439

- 92

- 1), http://www.epa.gov/iris/subst/0277.htm

.

We note further that because of the multi

- pathway, multi

- media impacts of lead, the risk assessment supporting the NAAQS considered direct inhalation exposures and indirect air

related multi

- pathway exposures from industrial sources like primary and secondary lead smelting operations. It also considered background lead exposures from other sources (like
contaminated drinkin g water and exposure to lead

- based paints). In revising the NAAQS for lead, we note that the Administrator placed more weight on the evidence

- based framework and less weight on the results from the risk assessment, although he did find the risk estimates to be roughly consistent with and generally supportive of the evidence

- based framework applied in the NAAQS determination (73FR at 67004). Thus, when revising the NAAQS for lead to protect public health with an adequate margin of safety, EPA considered bot h the
evidence

- based framework and the risk assessment, albeit to different extents.

Acute noncancer assessment

Many of the UFs used to account for variability and uncertainty in the development of acute reference values are quite similar to those developed for chronic durations, but more often using individual UF values that may be less than 10. UFs are applied 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.Draft Risk Assessment for the Of f

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48 

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

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