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

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

To: Cortney Higgins

Cc: Palma, Ted; Lassiter, Penny; Thundiyil, Karen; Rimer, Kelly; Tierney, Jan Subject: Response to Interagency Comments on Petroleum Refinery Risk Report

Hi Cortney,

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

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

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## Draft Residual Risk Assessment for the Petroleum Refining Source
Sector

by EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation May 201 4Draft Risk Assessment for the Petroleum Refining Source Sector

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### Table of Contents

1 Introduction

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

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

................................ ................................ ........................ 4
2.2 Dispersion modeling for inhalation exposure assessment

................................ .......... 5
2.3 Estimating chronic human inhalation exposure

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

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

............................... 10
2.6 Dose

- response assessment

................................ ................................ ...................... 14
2.6.1 Sources of chronic dose

- response information

................................ ................. 14
2.6.2 Sources of acute dose

- response information

................................ ................ 25 24
2.7 Risk characterization

................................ ................................ .......................... 29 28
2.7.1 General

................................ ................................ ................................ ........ 29 28
2.7.2 Mixtures

................................ ................................ ................................ ...... 31 30
2.7.3 Facility

- wide Risks

................................ ................................ .......................... 31
2.7.4 MACT

- Allowable Risk

................................ ................................ ............... 32 31
3 Risk results for the petroleum refining source sector

................................ .................... 32 31
3.1 Source category emissions and results

................................ ................................ 32 31
3.2 Baseline risk characterization

................................ ................................ ................. 37
3.3 Post

- control risk characterization

................................ ................................ ........ 48 47
4 General discussion of uncertainties and how they have been addressed

..................... 49 48
4.1 Exposure modeling uncertainties

................................ ................................ ........ 49 48
4.2 Uncertainties in the dose

- response relationships

................................ ................. 50 49
5 References

................................ ................................ ................................ ................ 59 58

Index of Tables

Table 2.2

- 1 AERMOD version 12345 model options for RTR modeling

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

- 1 (A) Dose

- Response Values for

................................ ................................ ...... 18 17 Chronic Inhalation Exposure to Carcinogens

................................ ................................ .... 18 17
Table 2.6

- 1 (B) Dose

- Response Values for Chronic Oral Exposure to Carcinogens

......... 21 20
Table 2.6

- 2 (A) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

................................ ................................ ................................ ................................ ............. 21
Table 2.6

- 2 (B) Dose

- Response Values for Chronic Oral Exposure to Noncarcinogens

.... 25 24
Table 2.6

- 3 Dose

- Response Values for Acute Exposure

................................ ................... 27 26
Table 3.2

- 5 Source Category Contribution to Facility

- Wide

................................ ............. 48 46 Chronic Cancer Risks (Actual Emissions)

................................ ................................ ......... 48 46

Appendices

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

- term emission rates relative to long

- term emission

ratesDraft Risk Assessment for the Petroleum Refining Source Sector

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Appendix 4 Technical Support Document for TRIM

- Based Multipathway Tiered Screening

Methodology for RTR Appendix 5 Detailed Risk Modeling Results Appendix 6 Acute Impacts Refined Analysis Appen dix 7 Dispersion Model Receptor Revisions and Additions for the Petroleum

Refinery Source Sector Appendix 8 Development of the Chronic Screening Level for Carbonyl Sulfide Appendix 9 Refinery Emissions and Risk Estimates for Modeled “Allowable” Emissions Appendix 10 Technical Support Document: Human Health Multipathway Residual Risk

Assessment for the Petroleum Refineries Sector

- A Site Specific Analysis Appendix 11 Environmental Risk Screen

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model
AEGL Acute exposure guideline level
ASTDR US Agency for Toxic Substances and Disease Registry
CalEPA California Environmental Agency
CTE Central Tendency Estimate
ERPG Emergency Response Planning Guideline
HAP Hazardous Air Pollutant
H EM Human Exposure Model
HI Hazard index HQ Hazard quotient
IRIS Integrated Risk Information System
MACT Maximum Achievable Control Technology
MIR Maximum Individual Risk
MOA Mode of action
NAC National Advisory Committee NAAQS National Ambient Air Quality Standards
NATA National Air Toxics Assessment
NEI National Emissions Inventory
NPRM Notice of Proposed Rulemaking
PB

- HAP Persistent and Bioaccumulative

- HAP
POM Polycyclic organic matter
REL Reference exposure level
RfC Reference concentration
RfD Reference dose
RME Reasonable Maximum Exposure
RTR Risk and Technology
TOSHI Target

- organ

- specific hazard index
URE Unit risk estimateDraft Risk Assessment for the Petroleum Refining Source Sector

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### 1 Introduction

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

- stage regulatory process fo r 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., p etroleum refineries, pulp and paper mills, etc.) [ 1 ]. EPA has largely completed the initial Maximum Achievable Control Technology ( MACT ) standards as required under this provision. Under section 112(d)(6), EPA must review each of these technology

- based s tandards 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 environment al risks that remain after implementation of the MACT standards. If additional risk reductions are necessary to protect public health with an ample margin of safety or to prevent an adverse environmental effect, EPA must develop
standards to address these remaining risks. This second stage of the regulatory process is known as the residual risk stage. For each source category for which EPA issued MACT standards, the residual risk stage must be completed within eight years of promulgation of the
initial t echnology

- based standard.

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board (SAB) on the “Risk and Technology Review (RTR) Assessment Plan

, ” and in June of 2007,
we received a letter with the results of that consultation. Subsequent to the consultation, in
June of 2009

, a meeting was held with an SAB panel for a formal peer review of the “Risk and Technology Review (RTR) Assessment Methodologies” [ 2 ]. We received the final SAB report on this review in May of 2010 [ 3 ]. W here appropriate, we have responded to the key messages from this review in developing our current risk assessment s and we will be continuing our efforts to improve our assessments by incorporating updates based on the SAB recommendations as they are devel oped and become availa ble. Our responses to the key
recommendations of the SAB are outlined in a memo entitled, “EPA’s Actions in Response to Key Recommendations from the SAB Review of RTR risk Assessment Methodologies” [ 4 ].

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

- control scenario risk

assessment performed for the Petroleum Refining S ource Sector . The meth ods discussion
includes descriptions of the methods used to develop refined estimates of chronic inhalation exposures and human health risks for cancer and noncancer endpoints, as well as descriptions
of the methods used to screen for acute health risks, c hronic non

- inhalation health risks, and
adverse environmental effects

.



### 2 Methods

2.1 Emissions and source data
The first and primary source category for which regulations were developed, Petroleum
Refineries

- Other Sources Not Distinctly Listed (Refinery MACT 1), includes all emission sources from petroleum refinery process units except those that were expected to be regulated elsewhere, such as the NESHAP for Boilers and Process Heaters (40 CFR part 63 subpartDraft Risk Assessment for the Petroleum Refining Source Sector

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DDDDD). The Refinery MACT 1 rule, which focuses o n evaporative emissions, was published in 40 CFR part 63, subpart CC on August 18, 1995 (60 FR 43620) and specifically excludes three types of process vents: catalytic cracking unit (CCU) catalyst regeneration vents, catalytic reforming unit (CRU) catalys t regeneration vents, and sulfur plant vents. These specific vents are regulated by the NESHAP for Petroleum Refineries: Catalytic Cracking Units, Catalytic Reforming Units, and Sulfur Recovery Units (Refinery MACT 2) in 40 CFR part 63, subpart UUU. The Refinery MACT 2 standards, which focus on combustion sources, were promulgated on April 11, 2002 (67 FR 17762 . This analysis will evaluate the
risks associated with both the MACT 1 and MACT 2 emissions.

In support of the residual risk and technology rev iew required by CAA sections 112(f) and 112(d)(6) for this source sector, o n April 1, 2011 EPA sent out an information collection request (ICR) under the authority of Section 114 of the CAA to the petroleum refining industry

. The ICR requested available information regarding process equipment, control devices, point and fugitive emissions, practices used to control fugitive emissions, and other aspects of facility operations, including stack parameters and locations. Details on the development of the emi ssions and source data for this source category can be found in the
docket .[ 5 ] Section 3 below provides a summary of the emissions.



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

- and short

- term inhalation exposure concentrations and associated health risk s from each facility in the source category were estimated using the Human Exposure Model in combination with the American Meteorological Society/EPA Regulatory Model dispersion modeling system (HEM

- AERMOD, or HEM 3 ). The approach used in applying this modeling system is outlined below, and further details are provided in Appendix 1 to this document ( Technical Support Document for HEM3 Modeling )

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

The dispersion model in the HEM 3 system, AERMOD version 1 2345 (the version of
AERMOD that was available at the time of the risk analysis) , is a state

- of

- the

- science Gaussian plume dispersion model that is preferred by EPA for modeling point, area, and
volume s ources of continuous air emissions from facility applications [ 6 ]. Further details on AERMOD can be found in the AERMOD Users Guide [ 7 ]. The model is used to develop annual average ambient concentrations through the simulation of hour

- by

- hour dispersion from the emission sources into the surrounding atmosphere. Hourly emission rates used for this simulation are generated by evenly dividing the total annual emission rate from the inventory into the 8,760 hours of the year.

The first step in the applicati on of the HEM 3 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 Petroleum Refining Source Sector

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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 Poin t, area represented as pseudo point source

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

- supplied receptors

Terrain characterization Actual from USGS 1

- degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option No

Meteorology 1 year repres entative NWS from nearest site ( 824 stations)

In HEM3, meteorological data are ordinarily selected from a list of over 800 National Weather Service (NWS) surface observation stations across the continental United States, Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is selected a s representative of the conditions at the subject facility. W hen considering off

- site meteorological data most site specific dispersion

, EPA modeling guidelines suggest that modeling efforts employ up to five years of data to capture variability in weathe r patterns from year to year. However, because dispersion model runtimes using five years of meteorological data would be too long for RTR source categories with many sources, w e modeled only a single year, 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 applicable meteorological station was 22 miles. Appendix 2 to this document ( Meteorologica l Data Processing Using AERMET for
HEM3 ) provides a complete listing of stations and assumptions along with further details used in pro cessing the data through AERMET, the AERMOD meteorological data processing

program

. The document “ Risk and Technology R eview (RTR) Risk Assessment Methodologies: For Review by the EPA’s Science Advisory Board with Case Studies

– MACT I Petroleum Refining Sources and Portland Cement Manufacturing ” (US EPA, 2009) provides more details on these modeling approaches.

Begin ning with version 12345, AERMET allows for a minimum wind speed of 0.5 m/s to be utilized when processing monitoring stations that are equipped with sonic anemometers and for an adjustment to the surface friction velocity (u*). The public version of AERME T available at the time we conducted the modeling did not include the surface friction velocity adjustment. Also at the time, an updated version of AERMET (and AERMOD) was under development that incorporated further surface friction velocity adjustments t o AERMET version 12345. In anticipation of the update, EPA processed meteorological data using a pre

public release version of AERMET and incorporated the updated surface friction velocity Commented [TP1]: Modified text as per OMB suggestionDraft Risk Assessment for the Petroleum Refining Source Sector

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adjustment in the output. It was EPA’s judgement that the pre

- pub lic release version of AERMET would generate AERMOD ready meteorological data very close to that generated with the final public release version.

EPA has posted the AERMET meteorological data used in the refinery analysis on the EPA’s FERA (Fate, Expos ure, and Risk Analysis) website under the HEM model page. AERMET and AERMOD (version 13350) were released to the public in late December 2013 on the EPA’s Support Center for Regulatory Atmospheric Modeling (SCRAM) website.

While it was not feasible to r emodel the entire source category using the public released version of AERMOD and AERMET, we were able to compare modeling results for 14 refineries using the using meteorological data processed with the pre

- public release version of AERMET and data proces sed with the current 13350 version. In addition, the 13350 version of AERMOD was run with the meteorological data processed with the 13350 version of AERMET. The comparison was conducted by examining the maximum individual risk (MIR) at 14 refinery facil ities, including the 4 facilities with the highest risk, the 5 with the lowest risks, and 5 randomly selected facilities. The largest difference in MIR values between the runs was 3 percent for one facility. The other 13 facilities had differences in the ir MIR values between runs of less than 1 percent. These results of this comparison are presented in Appendix 5.

The HEM 3 system estimates ambient concentrations at the geographic centroids of census blocks (using the 20 1 0 Census) and at other receptor lo cations that can be specified by the

user. See Appendix 7 of this document ( Dispersion Model Receptor Revisions and Addition s for the Petroleum Refining Sector) for a discussion of user receptors and centroid location changes specific to this source categ ory. The model accounts for the effects of multiple facilities when estimating concentration impacts at each block centroid. When evaluating the risks associated with a particular source category we combined the impacts of all facilities
within the same source category, and assessed chronic exposure and risk for all census blocks with at least one resident (i.e., locations where people may reasonably be assumed to reside
rather than receptor points at the fenceline of a facility). Chronic ambient conc entrations were calculated as the annual average of all estimated short

- term (one

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

In contrast to the development of ambient concentrations for evaluating long

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

- c ase short

- term (one

- hour) concentrations were estimated both at the census block centroids and at points nearer the facility that represent locations where people may be present for short periods, but generally
no nearer than 100 meters from the center of the facility (note that for large facilities, this
100

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

- term emission rates were needed to screen for the potential for hazard via acute exposures, and
where ICR data only contains annual emission totals

. Commented [TP2]: Updated language as per OMB suggestionDraft Risk Assessment for the Petroleum Refining Source Sector

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The average hourly emissions rate used for chronic risk s modeling is defined as the total emissions for a year divided by the total number of operating hours in the year. If a source operated 8

, 760 hours per year this em issions rate would be appropriate for predicting potential acute impacts. However, many sources in this source sector emit on a more intermittent basis and thus specific hourly emissions may be higher than those utilized for annual or chronic
risks modeli ng. While hourly emissions data for each source are not available, in this
assessment, we utilized source category specific engineering judgment to determine what the peak hourly emissions for any given process could be. For processes in which no “enginee ring judgment ” information was available we utilized a generic fact or of ten times
actual annual emissions to estimate peak hourly emissions In addition, f or past RTR analyses, EPA developed a generic emissions adjustment factor of ten for acute screening which was
based on engineering judgment. Th is factor of ten and t t he petroleum refinery specific factors along with the generic factor of ten are discussed in Appendix 3

, ( Analysis of data on short

term emission rates relative to long

- term emission rates ) of this document

.

Census block elevations for HEM 3 modeling were determined nationally from the US Geological Service 1

- degree digital elevation model (DEM) data files, which have a spatial resolution of about 90 meters. Elevations of polar grid points used in estimating short

- and long

- term ambient conc entrations were assumed to be equal to the highest elevation of any census block falling within the polar grid sector corresponding to the grid point. If a sector does not contain any blocks, the model defaults the elevation to that of the nearest block. If an elevation is not provided for the emission source, the model uses the average elevation of
all sectors within the innermost model ring.

In addition to using receptor elevation to determine plume height, AERMOD adjusts the plume’s flow if nearby e levated hills are expected to influence the wind patterns. For details on how hill heights were estimated and used in the AERMOD modeling see Appendix 1 of
this document

.



### 2.3 Estimating chronic human inhalation exposure

We used the estimated annual aver age ambient air concentration of each HAP

, at each census
block centroid

, as a surrogate for the lifetime inhalation exposure concentration of all the people who reside in the census block. That is, the risk analysis did not consider either the
short

- term or long

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

We did not address short

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

- term activity w ould, on average, reduce risk estimates about 25 percent for particulate HAP; it will also reduce risk estimates for gaseous HAP, but typically by much less. Second, basing exposure estimates on average ambient concentrations at census block centroids may underestimate or overestimate actual exposure concentrations at some residences

. Further reducing exposure estimates for Commented [TP3]: Updated language as per
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the most highly exposed residents by modeling their short

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

We d id 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 ass essing cancer risk, we generally estimated three metrics; the maximum individual risk (MIR), which is defined as the risk associated with a lifetime of exposure at the highest concentration where people are likely to live ; the population risk distribution; and the cancer incidence. The assumption of not considering short or long

- term population mobility does not bias the
estimate of the theoretical MIR ( assumes a person stays in one location for 70 years) nor does
it affect the estimate of cancer incidence since the total population number remains the same. It does, however, affect the shape of the distribution of individual risks across the affected population, shifting it toward higher estimated individual risks at the upper end and reducing
the numbe r of people estimated to be at lower risks, thereby increasing the estimated number of people at specific risk levels.

When screening for potentially significant acute exposures, we used an estimate of the highest hourly ambient concentration at any o ff

- site location as the surrogate for the maximum potential acute exposure concentration for any individual. This was generally the Fenceline.



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

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

- case exposure . The result of this screening process is that either the faci lity being assessed poses no potential acute health risks (i.e., it “screens out”), or that it requires further , more refined assessment. A more refined acute assessment could u s e industry

- or site

- specific data on the temporal pattern of emissions, the l ayout of emission points at the facility, the boundaries of the facility, and /or the local meteorology. In some cases, all of these site

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

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

necessary. Commented [TP4]:

Commented [TP5]: Removed sentence as per OMB comments, Sentence was confusing and does not
add to discussion.

Commented [TP6]: Clarified as per OMB

commentDraft Risk Assessment for the Petroleum Refining Source Sector

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Acute health risk screening was performed for each facility as the first step. We used conservative assumptions for emission rates, meteorology, an d exposure location. We used the following worst

- case assumptions in our screening approach:

 Peak 1

- hour emissions were obtained from the ICR and based on the operating characteristics of refinery emission sources as described in Appendix 3.

 We assumed that the peak emissions occur at all emission points at the same time.

 For facilities with multiple emission points, 1

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

 Worst

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

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

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

- case 1

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

meters.

 The maximum impact was compared to mul tiple short

- term health benchmarks for the
HAP being assessed to determine if a possible acute health risk might exist. These benchmarks are described in section 2.6 of this report.

As mentioned above, when we identify acute impacts which exceed their re levant benchmarks, we pursue refining our acute screening estimates to the extent possible

. In some cases, this may include the use of a facility

- specific emissions multiplier to estimate the peak hourly emission rates from the average rates (rather than the default factor of 10). In other cases, this may entail determining the actual physical layout and boundaries of a facility to more accurately gauge where people might reasonably be exposed for an hour.

For the petroleum refinery source category, t he refinement included a review of the layout of the emission points at the facilities with the facility boundaries to determine the maximum
off

- site acute impact for the facilities that did not screen out during the initial run. We also
used petroleum re finery specific factor s , as described above. Refer to Appendices 5 and 6 for
the detailed results for these sites.



### 2.5 Multipathway human health and environmental risk analysis

The EPA conducted a screening analysis examining the potential for significant human health risks due to exposures via routes other than inhalation (i.e., ingestion). We first determined whether any sources in the source categories emitted any hazardous air pollutants known to be persistent and bio

- accumulative in environment (PB

- HA P) 1 . The PB

- HAP compounds or compound classes are identified for the screening from the EPA’s Air Toxics Risk

1 Although the two

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

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

- letter chemical symbol for lead is not used in this document).Draft Risk Assessment for the Petroleum Refining Source Sector

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Assessment Library [ 8 ]. With respect to PB

- HAP emissions other than lead, emissions were evaluated for potential non

- inhalation risks impacts u sing a Tiered screening approach. We first determined whether the facility

- specific emission rates of each of the emitted PB

– HAP were large enough to create the potential for significant non

- inhalation human health risks
under reasonable worst

- case condit ions. To facilitate this step, we developed emissions rate
thresholds for each PB

– HAP using a hypothetical upper

- end screening exposure scenario developed for use in conjunction with the EPA’s Total Risk Integrated Methodology. Fate, Transport, and Ecologi cal Exposure (TRIM.FaTE[ 9 ]) model. We conducted a sensitivity analysis on the screening scenario to ensure that its key design parameters would represent the upper end of the range of possible values, such that it would represent a conservative but not imp ossible scenario. The facility

- specific emissions rates of each of the PB

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

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

- inhalation pathways. We c all this application of the TRIM.FaTE model the Tier I TRIM

- Screen. For the purpose of developing emissions rates for our Tier I TRIM

- Screen, we derived
emission levels for each PB

- HAP (other than lead) at which the maximum excess lifetime
cancer risk wou ld be 1

- in

- 1 million or, for HAP that cause non

- cancer health effects, the maximum HQ would be 1. If the emissions rate of any PB

- HAP exceeds the Tier I screening emissions rate for any facility, we conduct a Tier II multi

- pathway screen. In the Tier II

sc reen, the location of each facility that exceeded the Tier I emission rate is used to refine the assumptions associated with the environmental scenario while maintaining the exposure scenario assumptions. We then adjust the risk

- based Tier I screening leve l for each PB

- HAP for each facility based on an understanding of how exposure concentrations estimated for the screening scenario change with meteorology and environmental assumptions. PB

- HAP emissions that do not exceed these new Tier II screening levels are considered to pose no unacceptable risks. When facilities exceed the Tier II screening levels, it does not mean that
multi

- pathway impacts are significant, only that we cannot rule out that possibility based on
the results of the screen. These facilit ies may be further evaluated for multi

- pathway risks using the TRIM.FaTE model and more site specific information. Appendix 4 of this document (Technical Support Document for TRIM

- Based Multipathway Tiered Screening Methodology for RTR) contains a complet e discussion of the multipathway Tier I and II screening approach. A detailed discussion of the site specific multipathway approach is discussed in Appendix 10, “Technical Support Document: Human Health Multipathway
Residual Risk Assessment for the Petr oleum Refineries Sector

– A Site Specific Analysis.”

In evaluating the potential multipathway risks from emissions of lead compounds, rather than developing a screening emission rate for them , we compared maximum estimated chronic atmospheric concentrations with the current National Ambient Air Quality Standard (NAAQS) for lead. Values below the NAAQS were considered to have a low potential for multipathway risks of any significance.

The NAAQS value, a public health policy judgment, incorpor ated the Agency’s most recent health evaluation of air effects of lead exposure for the purposes of setting a national ambient air quality standard. In setting this value, the Administrator promulgated a standard that was requisite to protect public healt h with an adequate margin of safety. We consider values below the level of the primary NAAQS to protect against multipathway risks because asDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 12

mentioned above, the primary NAAQS is set as to protect public health with an adequate margin of safety. However , ambient air lead concentrations above the NAAQS are considered to pose the potential for increased risk to public health. We consider this NAAQS assessment to be a refined analysis given: 1) the numerous health studies, detailed risk and exposure analys es, and level of external peer and public review that went into the development of the primary NAAQS for lead, combined with: 2) the site

- specific dispersion modeling used in this assessment to estimated ambient lead concentrations due to the source catego ry emissions. It should be noted, however, that this comparison does not account for possible population exposures to lead from sources other than the one being modeled; for example, via consumption of water from untreated local sources or ingestion of lo cally grown food. Nevertheless, the Administrator judged that such a standard would protect, with an adequate margin of safety, the health of children and other at

- risk populations against an array of adverse health effects, most notably including neurolo gical effects, particularly neurobehavioral and neurocognitive effects, in children (73 FR 67007). The Administrator, in setting the standard, also recognized that no evidence

- or risk based bright line indicated a single appropriate level. Instead a coll ection of scientific evidence and other information was used to select the standard from a range of reasonable values (73 FR 67006).

We further note that comparing ambient lead concentrations to the NAAQS for lead, considering the level, averaging time, f orm and indicator, also informs whether there is the potential for adverse environmental effects. This is because the secondary lead NAAQS, set to protect against adverse welfare effects (including adverse environmental effects), has the same averaging ti me, form, and level as the primary standard. Thus, ambient lead concentrations above the NAAQS for lead also indicate the potential for adverse
environmental effects.

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

 Five persistent bioaccumulative HAP (PB

- HAP)

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

 Two acid gases

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

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

- documented potential to cause direct damage to terrestrial plants.

For the environmental risk screening analysis, EPA first determined whether any facilities in
th e source category emitted any of the seven environmental HAP. If one or more of the seven environmental HAP evaluated are emitted by at least one facility in the source category we proceed to the second step of the evaluation.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 13

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

- cast environmental conditionals to determine whether the facility

- specific off

- site em ission 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 n ot evaluated further under the screening approach. If off

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

.

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

a djusted to account for local meteorology and the actual location of lakes in the vicinity of facilities that did not pass the Tier I screen. If off

- site emissions from a facility do not exceed
the Tier II thresholds, the facility passes the screen, and is typically not evaluated further. If
off

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

For acid gases, the environmental screening analysis evaluates the 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 modeling domain to ecological benchmarks for each of the acid gases. For purposes of ecologic al 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 i nvestigate factors such as the magnitude and characteristics of the area of exceedance (e.g., land use of exceedance area, size of exceedance area) to determine if
there is an adverse environmental effect.

For lead compounds, we currently do not have th e 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 s econdary lead NAAQS is a reasonable means of evaluating environmental risk because it is set to provide substantial protection against adverse welfare
effects which can include “effects on soils, water, crops, vegetation, man

- made materials, animals, wildl ife, weather, visibility and climate, damage to and deterioration of property, and hazards to transportation, as well as effects on economic values and on personal comfort and
well

- being.” 2

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

- made materials, animals, wildlife, weather, visibility and climate,Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 14

Ecological benchmarks included in the e nvironmental r isk s creen are presented in Appendix
11.



### 2.6 Dose

- r esponse a ssessment

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 emiss ions inventory for the petroleum refinery source sector were based on the EPA Office of Air Quality Planning and Standards’ (OAQPS) existing recommendations for HAP [ 10 ], also used for NATA [ 11 ]. This information has been obtained from various sources and p rioritized according to (1) conceptual consistency with EPA risk assessment guidelines and (2) level of peer review received. The prioritization process was aimed at incorporating into our assessments the best available science with respect to dose

- respon se information. The recommendations are based on the following sources, in order of priority :

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

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

as sessments typically provide a qualitative statement regarding the strength of scientific data and specify a reference concentration (RfC, for inhalation) or reference dose (RfD, for ingestion) to protect against effects other than cancer and/or a unit risk estimate (URE, for inhalation) or slope factor (SF, for ingestion) to estimate the probability of developing

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

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

- day ...” EPA disseminates dose

response assessment information in several forms, based on the level of review. The Integrated Risk Information System (IRIS) [ 12 ] is an EPA database that contains scientific
health assessment inf

ormation, 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 pub lic, and peer review by independent scientists external to EPA. EPA’s science policy approach , under the current carcinogen guidelines, is to use linear
low

- dose extrapolation as a default option for carcinogens for which the mode of action (MOA) has not been identified. We expect future EPA dose

- response assessments to

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

- being.” Commented [TP7]: Added Appendix 11 as per
OMB commentsDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 15

identify nonlinear MOAs where appropriate, and we will use those analyses (once they are peer reviewed) in our risk assessments. At this time, however, there are no available carcinogen d ose

- 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 L evels (MRLs) [ 13 ] for inhalation and oral exposure to many toxic substances. As stated on the ATSDR web site: “ Following discussions with scientists within the Department of Health and Human Services (HHS) and the EPA, ATSDR chose to adopt a practice simil ar to that of the EPA's Reference Dose (RfD) and Reference Concentration (RfC) for deriving substance specific health guidance levels for non neoplastic endpoints .” The MRL is defined as “an estimate of daily human exposure to a substance that is likely

t o be without an appreciable risk of adverse effects (other than cancer) over a specified duration of exposure.” ATSDR describes MRLs as substance

- specific estimates to be used by health assessors to select environmental contaminants for further evaluation

. Exposures above an MRL do not necessarily represent a threat, and MRLs are therefore not intended for use as predictors of adverse health effects or for setting cleanup levels.

3) California Environmental Protection Agency (CalEPA). The CalEPA Office of Environmental Health Hazard Assessment has developed dose

- response assessments for many substances, based both on carcinogenicity and health effects other than cancer. The process for developing these assessments is similar to that used by EPA to develop IRIS values and incorporates significant external scientific peer review. As cited in the CalEPA Technical Support Document for developing their chronic assessments [ 14 ] : “The guidelines for developing chronic inhalation exposure levels incorporate many

re commendations of the U.S. EPA [ 15 ] and NAS [ 16 ].” The non

- cancer information includes available inhalation health risk guidance values expressed as chronic inhalation reference exposure levels (RELs) [ 17 ]. CalEPA defines the REL as “the concentration
level at or below which no health effects are anticipated in the general human population.” CalEPA's quantitative dose

- response information on carcinogenicity by inhalation exposure is expressed in terms of the URE [ 18 ], defined similarly to EPA's URE.

In de veloping chronic risk estimates, we adjusted dose

- response values for some HAP based on professional judgment, as follows:

1) In the case of nickel compounds, to provide a health

- protective estimate of potential cancer risks, we used t he IRIS URE for nickel subsulfide in this assessment. Based on past scientific and technical considerations, the determination of the percent of nickel subsulfide was considered a major factor for estimating the extent and magnitude of the
risks of cancer due to nickel

- containing emissions. Nickel speciation information for some of the largest nickel

- emitting sources (including oil combustion, coal combustion, and others) suggested that at least 35 percent of total nickel emissions may be soluble compound s and that the URE for the mixture of inhaled nickel compounds (based on nickel subsulfide, and representative of pure insoluble crystalline nickel) could be derived to reflect the assumption that 65 percent of the total mass of nickel may be carcinogenic.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 16

Based on consistent views of major scientific bodies (i.e., National Toxicology Program (NTP) in their 12 th Report of the Carcinogens (ROC) [ 19 ]

, International Agency for Research on Cancer ( IARC ) [ 20 ] , and other international agencies) [ 21 ] that consider all nickel compounds to be carcinogenic, we currently consider all nickel compounds to have the potential of being carcinogenic to humans. The 12th Report of the Carcinogens states that the “combined results of epidemiological studies, mecha nistic studies, and carcinogenic studies in rodents support the concept that nickel compounds generate nickel ions in target cells at sites critical for carcinogenesis, thus allowing consideration and evaluation of these compounds as a single group.” Alth ough the precise nickel compound (or compounds) responsible for the carcinogenic effects in humans is not always clear,
studies indicate that nickel sulfate and the combinations of nickel sulfides and oxides encountered in the nickel refining industries ca use cancer in humans (these studies are summarized in a review by Grimsrud et al., 2010 [ 22 ] ). The major scientific bodies mentioned above have also recognized that there are differences in toxicity and/or carcinogenic potential across the different nickel compounds. In this inhalation risk assessment, to take a conservative approach, we have considered all nickel compounds to be as carcinogenic as nickel subsulfide and have applied the IRIS URE for nickel subsulfide without a factor to reflect the assumpt ion that 100 percent of the total mass of nickel may be as carcinogenic as pure nickel subsulfide

. In addition, given that there are
two additional URE values 3 derived for exposure to mixtures of nickel compounds, as a group, that are 2

- 3 fold lower than the IRIS URE for nickel subsulfide, the EPA also considers it reasonable to use a value that is 50 percent of the IRIS URE for nickel subsulfide for providing an estimate of the lower end of the plausible range of cancer potency values for different mixtur es of nickel compounds.

2) Where possible for emissions of unspecified mixtures of HAP categories such as metal compounds and POM, we apply category

- specific chemical speciation profiles appropriate to the source category to develop a composite dose

- r esponse value for the category.

3) Where POM emissions were not s pe ciated in t o individual compounds , we applied the

same s im plifying a ssumptions to assessments that are used in NATA [ 23 ]. The NATA approach partitions POM into eight different non

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

4) In the case of HAP categories such as glycol ethers and cyanide compounds, the mo st conservative dose

- response value of the chemical category is used as a surrogate for other compounds in the group for which dose

- response values are not available. This is done in order to examine, under conservative assumptions, whether these HAP that lack dose

response values may pose an unacceptable risk and require further examination, or screen
out from further assessment.

3 Two UREs (other than the current IRIS values) have been derived for nickel compounds as a group : one developed by the California Department of Health Services ( http://www.arb.ca.gov/toxics/id/summary/nickel_tech_b.pdf ) and the other by the Texas Commission on Environmental Quality ( http://www.epa.gov/ttn/atw/nata1999/99pdfs/healtheffectsinfo.pdf ). Commented [TP8]: In response to OMB
Comment: The approaches and rationale for the technical and
scientific considerations used to derive inhalation
cancer risks of emissions of nickel and the views of expert independent reviewers on EPA’s a pproach can
be found at http://cfpub.epa.gov/si/si_public_record_report.cfm?d irEntryId=238881 . In brief, EPA ’s current approach
is to use 100 percent of the current IRIS URE for
nickel subsulfide (rather than assuming that 65 percent of the total mass of emitted nickel might be of nickel subsulfide, as used in previous analyses) to
reflect the potential carcinogenicity of all forms of
nickel . The EPA also recognized that there are potential differences in toxicity and thus carcinogenic potential across the different nickel compounds, and given that there have been two URE values derived for exposure to mixtures of nickel compounds that are
2

- 3 fold lower than the IRIS URE for nickel subsulfide, the EPA also considers it reasonable to use a value that is 50 percent of the IRIS URE for nickel subsulfide for providing an estimate of the lower end of a plausible range of cancer potency
values for different mixtures of nickel co mpounds. Although the review focused primarily on cancer risk s associated with emissions containing nickel compounds, it is important to note that comparative quantitative analys e s across nickel compounds have
shown that nickel sulfate is as toxic or more toxic
than nickel subsulfide or nickel oxide which does not support the notion that the solubility of nickel compounds is a strong determinant of its toxicity

. 1

, 2 It is important to add that nickel is not a driver of carcinogenic risk in the current asse ssment, and therefore we do not present a range of cancer potency
for this chemical.

1 Haber LT, Allen BC, Kimmel CA. Non

- Cancer Risk Assessment for Nickel Compounds: Issues Associated
with Dose

- Response Modeling of Inhalation and Oral Exposures. Toxicol Sci. 1998. 43:213

- 229

. National Toxicology Program, Technical Report Series No. 454, Toxicology and carcinogenesis studies of nickel sulfate hexahydrate. Available online at http://ntp.niehs.nih.gov/ntp/htdocs/LT_rpts/tr454.pdf.

1 National Toxicology Prog ram, Technical Report Series No. 454, Toxicology and carcinogenesis studies of nickel sulfate hexahydrate. Available online at http://ntp.niehs.nih.gov/ntp/htdocs/LT_rpts/tr454.pdf.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 17

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

- response value for formald ehyde (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 assessments supporting regulatory
actions. S ubsequent research pu blished by EPA suggests that the CIIT model was not appropriate and

, in 2010

, EPA returned to using the 1991 IRIS value. The EPA has been working on revising the formaldehyde IRIS assessment and the National Academy of Sciences (NAS) completed its review of the EPA’s draft assessment in April of 2011 4 The
EPA will follow the NAS Report recommendations and will present results obtained by implementing the biologically

- based dose

- response (BBDR) model for formaldehyde. The EPA will compare these estimates with those currently presented in the External Review draft of the assessment and will discuss their strengths and weaknesses. As recommended by the NAS committee, appropriate sensitivity and uncertainty analyses will be an integral component of implement ing the BBDR model. In the interim, we will present findings using the 1991 IRIS value as a primary estimate ; EPA may also consider other information
as the science evolves.

6) A chronic screening level of 163 μ g/m3 was developed by EPA for carbonyl sulfide (COS) from a No Observed Adverse Effects Level (NOAEL) of 200 ppm based on brain lesions and neurophysiological alterations in rodents. A more detailed discussion of the studies used to develop the COS chronic screening level is provi ded in Appendix 8 of this document ( Development of the Chronic Screening Level for Carbonyl Sulfide ) . The screening level includes a total uncertainty factor (UF) of 3,000: 10 times for extrapolation for interspecies differences, 10 times for consider ation of intraspecies variability, 10 times for extrapolation from subchronic to chronic duration, and 3 times for
database insufficiencies. See Section 5 of this document for a detailed discussion of exposure modeling uncertainties.

The emissions inve ntory for the petroleum refinery source sector includes emissions of 135
HAP with availa b le ch r onic quantitative inhalation dose

- response values. Of these, 69 are classified as known, probably, or possible carcinogens, with quantitative cancer dose

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

- response values, and the source of each value are listed in Table 2. 6

- 1.A. The 14 compounds with
chronic oral cancer dose

- response values available (for which multipathw ay screening assessments were performed) are listed in Table 2.6

- 1.B. Ninety

- five HAP have quantitative inhalation chronic noncancer threshold values available; 7 of these 95 H AP, for which a multipathway assessment w as performed, also ha ve quantit ative oral chronic noncancer
threshold values availabl e. These 95 HAP, their threshold values, and the source of the value
are listed in Table 2.6

- 2.A and Table 2.6

- 2.B.

4 http://www.nap.edu/catalog.php?record_id=13142 Commented [TP9]: OMB asked if this was peer
reviewed. Response: While this value itself was not peer reviewed the underlying data has been peer reviewed. The SAB did suggest that we use the best available
science in our risks characterization. ORD believes
this is the best available science and thus it is appropriate to use as a screening l evel.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 18

Table 2.6

- 1 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens URE (unit risk estimate for cancer) 5 = cancer risk per μg/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of Research & Development, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California EPA Office of Environmental Health Hazard Assessment. HEAST = EPA Health Effects Assessment Tables.

Pollutant CAS Number 6 URE 5 (1/μg/m 3 ) Source

1,1,2,2

- Tetrachloroethane 79345 5

. 8 E

- 05 IRIS CAL 1,1,2

- Trichloroethane 79005 1.6E

- 05 IRIS 1,3

- Butadiene 106990 3.0E

- 05 IRIS 1,3

- Dichloropropene 542756 4.0E

- 06 IRIS 1,4

- Dichlorobenzene 106467 1.1E

- 05 CAL

2

- Nitroprop r ane 79469 5.6E

- 06 EPA OAQPS 7 Acetaldehyde 75070 2.2E

- 06 IRIS Acrylamide 79061 1.6E

- 04 IRIS Acrylonitrile 107131 6.8E

- 05 IRIS
Aniline 62533 1.6E

- 06 CAL
Arsenic 7440382 4.3E

- 03 IRIS
Benzene 8 71432 7.8E

- 06 IRIS

Benzidine 92875 0.1072 IRIS Beryllium 7440417 2.4E

- 03 IRIS Bis(2

- Ethylhexyl)Phthalate 117817 2.4E

- 06 CAL
Cadmium 7440439 1.8E

- 03 IRIS Chromium (VI) 18540299 1

. 2 E

- 02 IRIS
Dioxins/Furans: 9 1,2,3,4,6,7,8

- Heptachlorodibenzofuran 67562394 3

. 3 E

- 01 EPA ORD 1,2,3,4,6,7,8

- Heptachlorodibenzo

p

- d D ioxin 35822469 3.3E

- 01 EPA ORD 1,2,3,4,7,8,9

- Heptachlorodibenzofuran 55673897 3.3E

- 01 EPA ORD 1,2,3,4,7,8

- 70648269 3.3E+00 EPA ORD

5 The URE is the upper

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

6 Chemica l Abstract Services identification number. For groups of compounds that lack a CAS number we have used a surrogate 3

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

7 URE of 5.6 x 10

- 6 per ug/m 3 for 2

- nitropropane. This valu e was derived in 1999 by the Health Council of the Netherlands (available at: http://www.gr.nl/sites/default/files/OSH@13.PDF ), based
on induction of hepatocellular nodules in rats, and is consistent with weight

- of

- evidence determinations by the
U.S. Natio nal Toxicology Program (“reasonably anticipated to be a human carcinogen”) and the IARC (“possibly carcinogenic to humans”).

8 The EPA IRIS assessment for benzene provides a range of plausible UREs. This assessment used the highest value in that range, 7. 8E

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

- 06 per ug/m 3

. 9 Dioxins/Furans URE based on 2005 WHO evaluation of TEF ( http://www.who.int/foodsafety/chem/tef_update/en/ ); URE=Group URE x TEF; RfC = 2,3,7,8

- TCDD
RfC/TEF Formatted: SuperscriptDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 19

Table 2.6

- 1 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens URE (unit risk estimate for cancer) 5 = cancer risk per μg/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of Research & Development, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California EPA Office of Environmental Health Hazard Assessment. HEAST = EPA Health Effects Assessment Tables.

Pollutant CAS Number 6 URE 5 (1/μg/m 3 ) Source

Hexachlorodibenzofuran 1,2,3,4,7,8

- Hexachlorodibenzo

- p

d D ioxin 39227286 3.3E+00 EPA ORD 1,2,3,6,7,8

- Hexachlorodibenzofuran 57117449 3.3 E+00 EPA ORD 1,2,3,6,7,8

- Hexachlorodibenzo

- p

d D ioxin 57653857 3.3 E+00 EPA ORD 1,2,3,7,8,9

- Hexachlorodibenzofuran 72918219 3.3E+00 EPA ORD 1,2,3,7,8,9

- Hexachlorodibenzo

- p

d D ioxin 19408743 3.3E+00 EPA ORD 1,2,3,7,8

- Pentachlorodibenzofuran 57117416 9.9E

- 01 EPA ORD 1,2,3,7,8

- Pentachlorodibenzo

- p

d D ioxin 40321764 3

. 3 E+01 EPA ORD 2,3,4,6,7,8

- Hexachlorodibenzofuran 60851345 3.3 E+00 EPA ORD 2,3,4,7,8

- Pentachlorodibenzofuran 57117314 9.9 E+00 EPA ORD 2,3,7,8

- Tetrachlorodibenzofuran 51207319 3

. 3 E+00 EPA ORD 2,3,7,8

- Tetrachlorodibenzo

- p

d D ioxin 1746016 3

. 3 E+01 EPA ORD 1,2,3,4,6,7,8,9

- Octo chlorodibenzofuran 39001020 9.9E

- 03 EPA ORD 1,2,3,4,6,7,8,9

- Octo hlorodibenzo

p

- d D ioxin 3268879 9.9E

- 03 EPA ORD Ethyl Benzene 100414 2.5E

- 06 CAL Ethylene Dibromide 106934 6 .0E

- 04 IRIS Ethylene Dichloride 107062 2

. 6 E

- 05 IRIS 10 Ethylene Oxide 75218 8.8E

- 05 CAL Ethylidene Dichloride (1,1

- Dichloroethane) 75343 1.6E

- 06 CAL Formaldehyde 11 50000 1.3E

- 05 IRIS Methyl Tert

- Butyl Ether 1634044 2.6E

- 07 CAL Methylene Chloride 75092 1.3 E

- 07 IRIS Naphthalene 91203 3.4E

- 05 CAL
Nickel 7440020 4

. 8 E

- 04 EPA OAQPS 12

10 The EPA IRIS assessment for ethylene d ibromide provides a range of plausible UREs. This assessment used the highest value in that range, 6.0E

- 04 per ug/m 3

. The low end of the range is equal to 50% of the URE for ethyl ene d ibromide is 3.0E

- 04 per ug/m 3

. 11 The EPA has used the CIIT value (5.5x10

- 9 per mg/m 3 ) to characterize formaldehyde cancer risks in some
instances.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 20

Table 2.6

- 1 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens URE (unit risk estimate for cancer) 5 = cancer risk per μg/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, EPA ORD = EPA Office of Research & Development, EPA OAQPS = EPA Office of Air Quality Planning & Standards, CAL = California EPA Office of Environmental Health Hazard Assessment. HEAST = EPA Health Effects Assessment Tables.

Pollutant CAS Number 6 URE 5 (1/μg/m 3 ) Source

Nickel Oxide 1313991 4

. 8 E

- 04 EPA OAQPS 9 Polychlorinated Biphenyls 1336363 1 .0E

- 04 IRIS Polycyclic Organic Matte r 13 : 14

1

- Methylnaphthalene 90120 8

. 8 E

- 05 CAL

2

- Methylnaphthalene 91576 8

. 8 E

- 05 CAL

3

- Methylcholanthrene 56495 1

. 008 E

- 02 CAL 7,12

- Dimethylbenz[a] a A nthracene 57976 1. 136 E

- 01 CAL Acenaphthene 83329 8

. 8 E

- 05 CAL Acenaphthylene 208968 8

. 8 E

- 05 CAL Benz[a] a A nthracene 56553 1

. 76 E

- 04 CAL Benzo[a] p P yrene 50328 1

. 76 E

- 03 CAL Benzo[b] f F luoranthene 205992 1

. 76 E

- 04 CAL Benzo[e] p P yrene 192972 8

. 8 E

- 05 CAL Benzo[g,h,i,] p P erylene 191242 8

. 8 E

- 05 CAL Benzo[k] f F luoranthene 207089 1

. 76 E

- 04 CAL Chrysene 218019 1.76E

- 05 CAL Dibenzo[a,h] a A nthracene 53703 1

. 918 E

- 03 CAL Dibenzo[a,i] p P yrene 189559 1

. 76 E

- 02 CAL

Dibenz [a,j] a A cridine 224420 1. 76 E

- 04 CAL

Fluoranthene 206440 8

. 8 E

- 05 CAL
Fluorene 86737 8

. 8 E

- 05 CAL Indeno[1,2,3

- c,d] p P yrene 193395 1

. 76 E

- 04 CAL Perylene 198550 8

. 8 E

- 05 CAL
POM72002

- 8.8E

- 05 CAL, OAQPS 15

, Tetrachloroethene 127184 2.6 E

- 0 7 IRIS Trichloroethylene 79016 4.8 E

- 06 IRIS Vinyl Bromide 593602 3

. 2 E

- 05 HEAST Vinyl Chloride 75014 8.8E

- 06 IRIS

12 The EPA IRIS assessments for nickel compounds provide a range of plausible UREs. This assessment use d the highest value in that range which is equal to the URE for nickel subsulfide, 4.8E

- 04 per ug/m 3 . The low end of the range is equal to 50% of the URE for nickel subsulfide, 2.4E

- 04 per ug/m 3

. 13 POM without a chemical

- specific URE are assigned a URE associated with a mixture of POM compounds having a similar characteristics. Details of this method, also used in the National Air Toxics Assessments, are
available at http://www.epa.gov/ttn/atw/nata 2005/methods.html#pom

14 All POM act by a mutagenic mode

- of

- action, therefore the URE s have been adjusted by a factor of 1.6 (see section 2.7.1 for more details)

. 15 POM 72002 repr e sents un s peci fied POM. For more information on this group and the assigned URE see http://www.epa.gov/ttn/atw/nata1999/99pdfs/pomapproachjan.pdf Formatted: Font: 10 pt

Formatted: NormalDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 21

Table 2.6

- 1 ( B ) Dose

- Response Values for Chronic Oral Exposure to Carcinogens

SF (oral slope factor for cancer) = cancer risk per mg/kg/d of average lifetime exposure. Sources : IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Health Hazard Assessment, EPA ORD = EPA Office of Research and Development

Pollutant CAS Number 16 SF (1/mg/kg/d) Source Dioxin/Furans : Hexachlorodibenzo

- p

- dioxin 19408743 6200 IRIS 2,3,7,8

- Tetrachlorodibenzo

- p

- dioxin 1746016 150000 EPA ORD Polychlorinated biphenyls 1336363 2 IRIS Polycyclic Organic Matter : 3

- Methlycholanthrene 56495 22 CAL 7,12

- Dimethylbenz(a)anthracene 57976 250 CAL Benz[a]Anthracene 56553 1.2 CAL Benzo[a]Pyrene 50328 7.3 IRIS Benzo[b]Fluoranthene 205992 1.2 CAL Benzo[k]Fluoranthene 207089 1.2 CAL Chrysene 218019 0.12 CAL Dibenzo[a,h]Anthracene 53703 4.1 CAL Dibenzo(a,i)pyrene 189559 120 CAL Dibenz(a,j)acridine 224420 1.2 CAL Indeno[1,2,3

- c,d]Pyrene 193395 1.2 CAL

Table 2.6

- 2 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry, HEAST = EPA He alth Effects Assessment Tables, EPA OAQPS = EPA Office of Air Quality Planning & Standards, EPA ORD = EPA Office of Research and Development
Pollutant CAS Number 6 RfC (mg/m 3 ) Source 17

1,1,2

- Trichloroethane 79005 0.4 CAL 1,3

- Butadiene 106990 0.002 IRIS

- M 1,3

- Dichloropropene 542756 0.02 IRIS

- H 1,4

- Dichlorobenzene 106467 0.8 IRIS

- M

2

- Nitroproprane 79469 0.02 IRIS

- L Acetaldehyde 75070 0.009 IRIS

- L
Acetonitrile 75058 0.06 IRIS

- M
Acrolein 107028 0.00002 IRIS

- M Acrylamide 79061 0.006 IRIS

- M

16 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have used a surrogate 3

- digit identifier corresponding to the group’s position on t he CAA list of HAP.

17 The descriptors L (low), M (medium), and H (high) have been added for IRIS RfC values to indicate the overall level of confidence in the RfC value, as reported in the IRIS file.Draft Risk Assessment for the Petroleum Refining Source Sector

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Table 2.6

- 2 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry, HEAST = EPA He alth Effects Assessment Tables, EPA OAQPS = EPA Office of Air Quality Planning & Standards, EPA ORD = EPA Office of Research and Development
Pollutant CAS Number 6 RfC (mg/m 3 ) Source 17

Acrylonitrile 107131 0.002 IRIS

- M
Aniline 62533 0.001 IRIS

- L Antimony 7440360 0.0002 IRIS

- L
Arsenic 7440382 0.000015 CAL

Benzene 71432 0.03 IRIS

- M Beryllium 7440417 0.00002 IRIS

- M Bis(2

- Ethylhexyl)Phthalate 117817 0.01 CAL
Cadmium 7440439 0.00001 ATSDR
Carbon Disulfide 75150 0.7 IRIS

- M Carbonyl Sulfide 463581 0.163 EPA ORD 18

Chlorine 7782505 0.00015 ATSDR
Chlorobenzene 108907 1 CAL
Chloroform 67663 0.098 ATSDR Chromium (VI) 18540299 0.0001 IRIS

- M
Cobalt 7440484 0.0001 ATSDR
Cobalt Oxide 1307966 0.0001 ATSDR
Cresol s (mixed) 1319773 0.6 CAL

m

- Cresol 108394 0.6 CAL

o

- Cresol 95487 0.6 CAL

p

- Cresol 106445 0.6 CAL
Cumene 98828 0.4 IRIS

- M Hydrogen Cyanide 74908 0.0008 IRIS

– L /M
Diethanolamine 111422 0.003 CAL
Dioxin/Furans: 1,2,3,4,6,7,8

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

- Heptachlorodibenzo

- p

- Dioxin 35822469 0.000004 CAL 1,2,3,4,7,8,9

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

- Hexachlorodibenzofuran 70648269 0.000000 4 CAL 1,2,3,4,7,8

- Hexachlorodibenzo

- p

- Dioxin 39227286 0.000000 4 CAL 1,2,3,6,7,8

- Hexachlorodibenzofuran 57117449 0.000000 4 CAL 1,2,3,6,7,8

- Hexachlorodibenzo

- p

- Dioxin 57653857 0.000000 4 CAL 1,2,3,7,8,9

- Hexachlorodibenzofuran 72918219 0.000000 4 CAL 1,2,3,7,8,9

- Hexachlorodibenzo

- p

- Dioxin 19408743 0.000000 4 CAL 1,2,3,7,8

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

- Pentachlorodibenzo

- p

- Dioxin 40321764 0.0000000 4 CAL

18 A chronic screening level of 0.163 mg/m 3 was developed for carbonyl sulfide by EPA ORD from a No Observed Adverse Effects Level of 200 ppm based on brain lesions and neurophysiological alteration in rodents.Draft Risk Assessment for the Petroleum Refining Source Sector

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Table 2.6

- 2 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry, HEAST = EPA He alth Effects Assessment Tables, EPA OAQPS = EPA Office of Air Quality Planning & Standards, EPA ORD = EPA Office of Research and Development
Pollutant CAS Number 6 RfC (mg/m 3 ) Source 17

2,3,4,6,7,8

- Hexachlorodibenzofuran 60851345 0.000000 4 CAL 2,3,4,7,8

- Pentachlorodibenzofuran 57117314 0.000000 13 CAL 2,3,7,8

- Tetrachlorodibenzofuran 51207319 0.000000 4 CAL 2,3,7,8

- Tetrachlorodibenzo

- p

- Dioxin 1746016 0.0000000 4 CAL 1,2,3,4,6,7,8,9

- Oct o chlorodibenzofuran 39001020 0.00013 CAL 1,2,3,4,6,7,8,9

- Octo chlorodibenzo

- p

- Dioxin 3268879 0.00013 CAL Ethyl Chloride 75003 10 IRIS

- M Ethyl Benzene 100414 1 IRIS

- L Ethylene Dibromide 106934 0.009 IRIS

- M Ethylene Dichloride 107062 2.4 ATSDR Ethylene Glycol 107211 0.4 CAL Ethylene Oxide 75218 0.03 CAL Ethylidene Dichloride (1,1

- Dichloroethane) 75343 0.5 HEAST Formaldehyde 50000 0.0098 ATSDR Diethylene Glycol Monomethyl Ether 111773 0.02 IRIS

- M
Hexachloroethane 67721 0.0 3 IRIS

– L
Hexane 110543 0.7 IRIS

– M Hydrochloric Acid 7647010 0.02 IRIS

– L Hydrofluoric Acid 7664393 0.014 CAL
Lead 7439921 0.00015 EPA OAQPS Manganese 7439965 0.0003 ATSDR Elemental Gaseous Mercury 201 0.0003 IRIS

- M Gaseous Divalent Mercury 184 0.0003 IRIS

– M
Mercuric Chloride 7487947 0.0003 IRIS

– M Mercury (elemental) 7439976 0.0003 IRIS

– M
Mercuric Oxide 21908532 0.0003 IRIS

- M Particulate Divalent Mercury 202 0.0003 IRIS

- M
Methanol 67561 4 CAL Methyl Bromide 74839 0.005 IRIS

- H Methyl Chloride 74873 0.09 IRIS

- M Methyl Isobutyl Ketone 108101 3 IRIS

- L/M Methyl Tert

- Butyl Ether 1634044 3 IRIS

- M Methylene Chloride 75092 1 ATSDR Dimethyl formamide 68122 0.03 IRIS

- M Naphthalene 91203 0.003 IRIS

- M
Nickel 7440020 0.00009 ATSDR
Nickel Oxide 1313991 0.00002 CALDraft Risk Assessment for the Petroleum Refining Source Sector

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Table 2.6

- 2 ( A ) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances Disease Registry, HEAST = EPA He alth Effects Assessment Tables, EPA OAQPS = EPA Office of Air Quality Planning & Standards, EPA ORD = EPA Office of Research and Development
Pollutant CAS Number 6 RfC (mg/m 3 ) Source 17

Phenol 108952 0.2 CAL Propionaldehyde 123386 0.008 IRIS

– L/M
Selenium 7782492 0.02 CAL Styrene 100425 1 IRIS

- M

Tetrachloroethene 127184 0. 04 IRIS

– M
Toluene 108883 5 IRIS

- H Trichloroethylene 79016 0.002 IRIS

- H Triethylamine 121448 0.007 IRIS

- L Vinyl Bromide 593602 0.003 IRIS

- H Vinyl Chloride 75014 0.1 IRIS

- M Vinylidene Chloride 75354 0.2 IRIS

– H/M Xylenes (mixed) 1330207 0.1 IRIS

- M

m

- Xylene 108383 0.1 IRIS

- M

o

- Xylene 95476 0.1 IRIS

- M

p

- Xylene 106423 0.1 IRIS

- MDraft Risk Assessment for the Petroleum Refining Source Sector

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Table 2.6

- 2 ( B ) Dose

- Response Values for Chronic Oral Exposure to Noncarcinogens

RfD (reference dose) = an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects durin g a lifetime. Sources: IRIS = EPA Integrated Risk Information System, ATSDR = US Agency for Toxic Substances an d Disease Registry

Pollutant CAS Number RfD (mg/kg/d) Source 19 Cadmium compounds 7440439 0.0005 IRIS

- H

Mercuric chloride 20 7439976 0.0003 IRIS

- H Polycyclic Organic Matter (POM)

Anthracene 120127 0.3 IRIS

- L

Fluoranthene 206440 0.04 IRIS

- L

1

- Methylnaphthalene 90120 0.07 ATSDR

2

- Methylnaphthalene 91576 0.04 ATSDR 2,3,7,8

- Tetrachlorodibenzo

- p

- dioxin 1746016 0.0000000007 IRIS

- H

2.6.2 Sources of acute dose

- response information

Hazard identification and dose

- response assessment information for preliminary acute inhalation exposure assessments are based on the existing recommendations of OAQPS for HAP [ 24 ]

. Depending on availability, the results from screening acute assessments are compared to both “no effects” reference levels for the general public, such as the California Reference Exposure Levels (RELs), as well as emergency response levels, such as Acut e Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelines (ERPGs), with the recognition that the ultimate interpretation of any potential risks associated with an estimated exceedance of a particular reference level depends on the defi nition of that level and any limitations expressed therein. Comparisons among different available inhalation health effect reference values (both acute and chronic) for selected HAP can be
found in recently released EPA document s [ 25 ] [ 26 ]

.

California Acut e Reference Exposure Levels (RELs ). The California Environmental Protection 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

. [ 27 ]

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

19 The descriptors L (low), M (medium), and H (high) have been added for IRIS RfC values to indicate th e overall level of confidence in the RfC value, as reported in the IRIS file.

20 The multipathway exposure assessment for mercury included fate and transport analysis, that included separate oral exposure estimates for divalent mercury and methylmercury.Draft Risk Assessment for the Petroleum Refining Source Sector

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uncertainties, exceeding the REL does not automatically indicate an adverse health impact. ” Acute RELs are developed for 1

- hour (and 8

- hour) exposures. The values incorporate uncertainty factors s imilar to those used in deriving EPA’s Inhalation Reference Concentrations (RfCs) for chronic exposures (and, in fact, California also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory
Committee (NAC) on Acute Exposure Guideline Levels (NAC/AEGL) f or Hazardous
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 appli cation 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
do cument states that “the primary purpose of the AEGL program and the NAC/AEGL Committee is to develop guideline levels for once

- in

- a

- lifetime , short

- term exposures to airborne concentrations of acutely toxic, high

- priority chemicals.” In detailing the inte nded application of AEGL values, the document states that

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

- time emergency res ponse 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 th at the general population, including susceptible individuals, could experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. However, the effects are not disabling and are transient and reversible upon cessation of

exposure. ”

“ AEGL

- 2 is the airborne concentration (expressed as ppm or mg/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 effec ts 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, nonsensor y effects. With increasing airborne concentrations above each AEGL, there is a progressive increase in the likelihood of occurrence and the severity of effects described for each corresponding AEGL. Although the AEGL values represent threshold levels for the general public, including susceptible subpopulations, such as infants, children, the elderly, persons with asthma, and those withDraft Risk Assessment for the Petroleum Refining Source Sector

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other illnesses, it is recognized that individuals, subject to unique or idiosyncratic responses, could experience the ef fects described at concentration s below the corresponding AEGL.”

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [ 28 ] for acute exposures at three different levels of severity. These guidelines represent
concentrations for once in a lifetime exposure of the general population (but not particularly sensitive persons) for up to 1 hour associated with effects expected to be mild or transient (ERPG

- 1), irreversible or serious (ERPG

- 2), and potentially life

- threatening (ERPG

- 3).

ERPG values are described in their supporting documentation [ 29 ] as follows: “ERPGs are air concentration guidelines for single exposures to agents and are intended for use as tools to assess the adequacy of accident prevention and emergency response plans, including transportation emergency planning, community emergency response plans and incident prevention and mitigation.”

ERPG

- 1 and ERPG

- 2 values are defined by AIHA as follows:

“ ERPG

- 1 is the maximum airborne concentration below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing other than mild
transient adverse health effects or without perceiving a clearly defined, objectionable
odor. ”

“ ERPG

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

The emissions inventory for the petroleum refinery source sector includes emissions of 48
HAP with relevant and available quantitative acute dose

- response thre shold 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

(mg/m 3 ) 1,3

- Butadiene 106990 1500 12000 22 440 Acetaldehyde 75070 81 490 18 360 0.47
Acetonitrile 75058 22 540
Acrolein 107028 0.069 0.23 0.11 0.34 0.0025 Acrylonitrile 107131 10 130 22 77
Aniline 62533 30 46
Arsenic 7440382 0.0002
Benzene 71432 170 2600 160 480 1.3 Beryllium 7440417 0.025Draft Risk Assessment for the Petroleum Refining Source Sector

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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

(mg/m 3 ) Biphenyl 92524 61
Carbon Disulfide 75150 40 500 3.1 160 6.2 Carbonyl Sulfide 463581 140
Chlorine 7782505 1.5 5.8 2.9 8.7 0.21
Chlorobenzene 108907 46 690
Chloroform 67663 310 240 0.15
Cumene 98828 250 1500 Hydrogen Cyanide 74908 2.2 7.8 11 0.34 Ethyl Benzene 100414 140 4800 Ethylene Dibromide 106934 130 180 Ethylene Dichloride 107062 200 810 Ethylene Oxide 75218 81 90 Formaldehyde 50000 1.1 17 1.2 12 0.055 Diethylene Glycol Monomethyl Ether 111773 0.093
Hexane 110543 12000 Hydrochloric Acid 7647010 2.7 33 4.5 30 2.1 Hydrogen Fluoride 7664393 0.82 20 1.6 16 0.24 Elemental Gaseous Mercury 200 1.7 2 0.0006 Mercury (elemental) 7439976 1.7 2 0.0006
Methanol 67561 690 2700 260 1300 28 Methyl Bromide 74839 820 190 3.9 Methyl Chloride 74873 1900 830 Methyl Tert

- Butyl Ether 1634044 180 2100 Methylene Chloride 75092 690 1900 1000 2600 14 Dimethyl formamide 68122 270 6 300
Nickel 7440020 0.0002
Nickel Oxide 1313991 0.0002
Phenol 108952 58 89 38 190 5.8 Propionaldehyde 123386 110 620 Styrene 100425 85 550 210 1100 21
Tetrachloroeth ene 127184 240 1600 680 1400 20
Toluene 108883 750 4500 190 1100 37 Trichloroethylene 79016 700 2400 540 2700 Triethylamine 121448 2.8 Vinyl Chloride 75014 640 3100 1300 13000 180

m

- Xylene 108383 22

o

- Xylene 95476 22

p

- Xylene 106423 22 Xylenes (Mixture of o, m, and p Isomers) 1330207 560 4000 22Draft Risk Assessment for the Petroleum Refining Source Sector

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### 2.7 Risk c haracterization

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 [ 30 ] specifies that a risk characterization “be prepared in a manner that is clear, transparent, reasonable, and consistent with other risk
characterizations of similar scope prepared across programs in the Agency.” These principles of transparency and consistency have been reinforced by the Agency’s Risk Characterization
Handbook [ 31 ], in 2002 by the Agency’s information quality guidelines [ 32 ], and in the
OMB/OST P September 2007 Memorandum on Updated Principles for Risk Analysis [ 33 ]

, and are incorporated in these assessments.

Estimates of health risk are presented in the context of uncertainties and limitations in the data and methodology. Through our tiered, it erative 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 indivi dual cancer risks and noncancer hazards, as well as cancer incidence estimates) along with a discussion of the major uncertainties associated with their derivation to provide decision makers with the fullest picture of the assessment and its
limitations.

For each carcinogenic HAP included in an assessment that has a potency estimate available,
individu al and population cancer risks we re calculated by multiplying the corresponding lifetime average exposure estimate by the appropriate URE. This calculated c ancer 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 tha n predicted, and could be

zero.

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

- of

- action [ 34 ], we applied
EPA’s Supplemental Guidance for Assessing Susceptibility from Early

- Life Exposure to Carcinogens [ 35 ]

. This guidance has the effect o f 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 fo r these pollutants by a factor of 1.6. In addition, although only a
small fraction of the total POM emissions may be reported as individual compounds, EPA expresses carcinogenic potency for compounds in this group in terms of benzo[a]pyrene equivalence, based on evidence that carcinogenic POM have the same mutagenic mechanism
of action as does benzo[a]pyrene. For this reason

, EPA implem entation policy [ 36 ]Draft Risk Assessment for the Petroleum Refining Source Sector

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recommends applyi ng the Supplemental Guidance to all carcinogenic PAHs for which risk
estimates are based on relative potency. Accordingly, we applied the Supplemental Guidance to all unspeciated POM mixtures.

Increased cancer incidence for the entire receptor population within the area of analysis wa s estimated by multiplying the estimated lifetime ca ncer 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
estimate of the number of cancer cases per year.

In the case of benzene, the high end of the reported cancer URE range was used in our assessments to provide a conservative estimate of potential cancer risks. Use of the high end of the range provides risk estimates that are approximately 3.5 times higher than use of the equally plausible low end value. If the estimated benzene

– associated risks exceed 1 in a million, we also evaluate d the impact of using the low end of the URE range on our risk
results.

Unlike linear dose

- response assessment s 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 e stimated exposure divided by a reference level (e.g., the RfC). For a given HAP, exposures at or below the reference level (HQ≤1) are not likely to cause adverse health effects. As exposures increase above the reference level (HQs increasingly greater th an 1), the potential for adverse effects increases. For exposures predicted to be above the RfC, the risk characterization includes the degree of confidence ascribed to the RfC values for the compound(s) of concern (i.e., high, medium, or low confidence) and discusses the impact of this on possible health interpretations.

The risk characterization for chronic effects other than cancer is expressed in terms of the HQ for inhalation, calculated for each HAP at each census block centroid. As discussed abov e, 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 e ffects 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 ea ch 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 Petroleum Refining Source Sector

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2.7.2 Mixtures
Since most or all receptors in these assessments receive exposures to multiple pollutants rather than a single pollutant, we estimated the aggregate health risks associated with all the exposures from a particular source category combined.

To combine risks across multiple carcinogens, our assessments use the mixtures guidelines’ [ 37

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

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

- of

- action differences, the mixtures guidelines support aggregating effects of different substances in specific and limited ways. To conform to these guidelines , we aggregated no n

- 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 above the critical dose have not be en included in the TOSHI calculations, some TOSHIs may have been underestimated. As with the HQ, the TOSHI should not be interpreted as a probability of adverse effects, or as strict delineation of “safe” and “unsafe” levels. Rather, the TOSHI is another measure of the potential for adverse health outcomes associated with pollutant exposure, and needs to be interpreted carefully by health scientists and risk managers.

Because of the conservative nature of the acute inhalation screening and the variable nature of emissions and potential exposures, acute impacts were screened on an individual pollutant basis, not using the TOSHI approach.

2.7.3 Facility

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

- wide” risks using
the emissions data and modeling as described in Section 2.2. For the facilities in the petroleum refining source category, we estimated the maximum inhalation cancer and chronic noncancer risks associated with all HAP emissions sources at the facility, includ ing emissions sources that are not part of the source categories but are located within a contiguous area and
are under common control. We analyzed risks due to the inhalation of HAP for the populations residing within 50 kilometers of each facility. The results of the facility

- wide
assessment are summarized below in the risk characterization section of this document.Draft Risk Assessment for the Petroleum Refining Source Sector

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2.7.4 MACT

- Allowable Risk

The emissions data in the data set for the petroleum refining source category are estimates of
actual emissions on a n annual basis. For the petroleum refining source category, allowable
emissions were also estimated and inhalation assessment results obtained. The docket memo Refinery Emissions and Risk Estimates for Modeled “Allowable” Emissions provides a full explan ation of the development of these allowable emissions. as is described in Appendix
9 [ 39 ]



### 3 Risk r esults for the p etroleum r efining s ource s ector

3.1 Source c ategory emissions and r esults

The petroleum refining source sector consists of 14 2 facilities regulated under the r efinery
MACT 1 and MACT 2 standards. Petroleum refineries are facilities that engage in producing liquid petroleum gases (LPG), motor gasoline, jet fuels, kerosene, distillate fuel oils, residual fuel oils, lubricants, asphalt (bitume n), and other products through distillation of crude oil or through redistillation, cracking, or reforming of unfinished petroleum derivatives. The first and primary source category for which regulations were developed, Petroleum Refineries

– Other Source s Not Distinctly Listed (Refinery MACT 1), includes all emission sources from petroleum refinery process units except those that were expected to be regulated elsewhere, such as the NESHAP for Boilers and Process Heaters (40 CFR part 63 subpart DDDDD).
Th e Refinery MACT 1 rule, which focuses on evaporative emissions, was published in 40 CFR part 63, subpart CC on August 18, 1995 (60 FR 43620) and specifically excludes three types of process vents: catalytic cracking unit catalyst regeneration vents, catal ytic reforming unit catalyst regeneration vents, and sulfur plant vents. These specific vents are regulated by the NESHAP for Petroleum Refineries: Catalytic Cracking Units, Catalytic Reforming Units, and Sulfur Recovery Units (Refinery MACT 2) in 40 CFR part 63, subpart UUU. The Refinery MACT 2 standards, which focus on combustion sources, were promulgated on April 11, 2002 (67 FR 17762). This analysis will evaluate the risks associated with both the
MACT 1 and MACT 2 emissions.

We currently estimate that of the 1 48 Petroleum Refinery facilities operating in the U.S., that
142 of these are identified as major sources and 6 identified as area sources. Only the major
sources are included in this assessment.

The emissions for this source categor y data s et were obtained from the ICR, as mentioned above [ 5 ] . The emissions from the source category are summarized in Table 3.1

- 1. The total HAP emissions for the source category are approximately 1 7,2 00 tons per year. Based on these data, the HAP emitted in the largest quantities across these 142 facilities are: hydrogen cyanide, n

- hexane, toluene, xylenes (mixed), benzene, 2,2,4

- trimethylpentane, hydrochloric acid, hydrogen sulfide, ethyl benzene, methanol, carbonyl sulfide, styrene, naphthalene, formaldehyd e, cumene, methyl isobutyl ketone, p

- xylene, carbon disulfide, 1,3

- butadiene, methyl tert

- butyl ether, m

- xylene, o

- xylene, hydrofluoric acid, 2

- methylnapthalene, phenol, cresols (mixed), diethanolamine, acetaldehyde, methylene chloride, biphenyl, ethylene dibromide, and tetrachloroethene. These 32 HAP account for 99 percent of the total emissionsDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 33

by mass. Persistent and bioaccumulative HAP (PB HAP) 21 reported as emissions from these facilities include cadmium compounds, chlorinated dibenzodioxins and furans (analyzed as 2,3,7,8

- tetrachlorodibenzo

- p

- dioxin), mercury compounds, lead compounds, polychrorinated biphenyls (PCBs), and polycyclic organic matter (POM) (analyzed as benzo(a)pyrene). The following environmental HAP are emitted from the petroleum refin eries source category and are included in the environmental risk screen: lead compounds, mercury compounds, cadmium compounds, POM, chlorinated dibenzodioxins and furans, hydrogen chloride, and hydrogen fluoride.

Table 3.1

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

and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting HAP (148
facilities in
NPRM data set) Prioritized I nhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk
Estimate for Cancer? Reference

Concentration
for Chronic
Noncancer? Health

Benchmark Values for
Acute
Noncancer? Hydrogen Cyanide 3,682 80 

 


n

- H exane 2,513 142 

 

 Toluene 2,284 142 

 

 Xylenes (mixed) 1,840 139 

 

 Benzene 1,174 142 

 

 

 2,2,4

- T rimethylpentane 1,086 129 Hydrochloric Acid 931 98 

 

 Ethyl Benzene 491 141 

 

 

 Methanol 466 66 

 

 Carbonyl Sulfide 366 82 

 

 Styrene 345 114 

 

 Naphthalene 265 140 

 

 Formaldehyde 196 119 

 

 

 Cumene 163 135 

 

 Methyl Isobutyl Ketone 128 21 

 Carbon Disulfide 122 100 

 

 p

- X ylene 122 51 

 

 Methyl Tert

- butyl Ether 116 76 

 

 

 1,3

- butadiene 113 125 

 

 


m

- X ylene 108 74 

 


o

- X ylene 66 65 

 

 Hydrofluoric Acid 63 24 

 

 Polycyclic Organic Matter

  2

- methylnaphthalene 60 106 

 



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

- 453K

- 04

- 001A, as referenced in the NPRM and provided on the EPA’s Technology Transfer Network website for Fate, Exposure, and Risk Assessment at http://www.epa.gov/ttn/fera/risk_atra_vol1.html

.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 34

Table 3.1

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

and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting HAP (148
facilities in
NPRM data set) Prioritized I nhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk
Estimate for Cancer? Reference

Concentration
for Chronic
Noncancer? Health

Benchmark Values for
Acute
Noncancer?

Anthracene 16 110 

 Phenanthrene 14 109 

 Fluorene 8 104 

 

 Pyrene 3 101 

 Chrysene 3 106 

 

 Acenaphthene 2 103 

 

 Fluoranthene 2 104 

 

 POM 72002 1 5 

 

 Benzo(ghi)perylene 0.8 110 

 

 Benz[a]anthracene 0.6 106 

 

 Perylene 0.6 14 

 

 Benzo[a]pyrene 0.5 105 

 

 Benzo(e)pyrene 0.5 84 

 

 Indeno[1,2,3

- c,d]pyrene 0.5 104 

 

 1

- methylnaphthalene 0.4 1 

 

 Dibenzo[a,h]anthracene 0.2 106 

 

 Benzo[b]fluoranthene 0.2 105 

 

 Acenaphthylene 0.2 104 

 

 Benzo[k]fluoranthene 0.1 105 

 

 7,12

- dimethylbenz[a]anthracene 0.02 61 

 

 3

- methylcholanthrene 0.01 61 

 

 Dibenzo[a,i]pyrene 0.0002 1 

 

 Dibenz[a,j]acridine 0.0001 1 

 

 Phenol 59 117 

 

 Cresols (mixed) 58 97 

 Diethanolamine 49 31 

 Acetaldehyde 47 107 

 

 

 Methylene Chloride 43 8 

 

 

 Biphenyl 41 116 

 Ethylene Dibromide 27 12 

 

 

 Tetrachloroethene 22 31 

 

 

 2

- nitropropane 20 2 

 

 Acetonitrile 12 4 

 

 Chlorine 10 76 

 

 Nickel Compounds

  Nickel Compounds 9 103 

 

 

 Nickel Oxide 0.01 1 

 

 

 Acrylonitrile 9 2 

 

 

Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 35

Table 3.1

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

and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting HAP (148
facilities in
NPRM data set) Prioritized I nhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk
Estimate for Cancer? Reference

Concentration
for Chronic
Noncancer? Health

Benchmark Values for
Acute
Noncancer?
Aniline 7 44 

 

 

 Acrolein 6 104 

 

 Chlorobenzene 5 3 

 

 Antimony Compounds 5 97 

 Trichloroethylene 5 11 

 

 

 1,4

- dichlorobenzene 3 39 

 


o

- C resol 3 24 

 Ethylene Dichloride 3 13 

 

 

 Methyl Bromide 2 57 

 

 1,3

- dichloropropene 2 2 

 

 Selenium Compounds 2 99 

 Lead Compounds 1 101 c  Chromium Compounds

 Chromium (III) 1 98
Chromium (VI) 0.2 101 

 

 1,1,2

- trichloroethane 1 7 

 

 Manganese Compounds 1 97 

 Phosphorus, White 1 41

m

- C resol (3

- methylphenol) 1 21 

 Methyl Chloride 1 5 

 

 Chloroform 0.9 15 

 

 Vinyl Chloride 0.7 3 

 

 

 1,1,2,2

- tetrachloroethane 0.7 6 

 Ethyl Chloride 0.7 2 

 Mercury Compounds

   Mercury (elemental) 0.6 106 

 

 
Gaseous Divalent Mercury 0.08 106 

 

 Particulate Divalent Mercury 0.08 106 

 

 Mercuric Chloride 0.009 3 

 

 Mercuric Oxide 0.0001 1 

 

 Ethylidene Dichloride 0.6 2 

 

 Cadmium Compounds 0.5 97 

 

 

 Cobalt Compounds

  Cobalt Compounds 0.4 95 

 Cobalt Oxide 0.007 1 

 Arsenic Compounds 0.2 96 

 

 

 p

- C resol (4

- methy Phenol) 0.2 14 

 Bis(2

- ethylhexyl)phthalate 0.2 7 

 

Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 36

Table 3.1

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

and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting HAP (148
facilities in
NPRM data set) Prioritized I nhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk
Estimate for Cancer? Reference

Concentration
for Chronic
Noncancer? Health

Benchmark Values for
Acute
Noncancer?
Dibenzofuran 0.2 21
Nitrobenzene 0.2 1   Ethylene Oxide 0.1 1 

 

 

 Dibutylphthalate 0.1 5

Hexachloroethane 0.1 1 

 Beryllium Compounds 0.08 94 

 

 

 Triethylamine 0.06 2 

 

 Vinyl Bromide 0.03 1 

 

 Quinoline 0.02 2 Dimethyl Formamide 0.005 1 

 

 Acrylamide 0.004 2 

 

 Vinylidene Chloride 0.004 1 

 Benzidine 0.002 1 

 

 Diethylene Glycol Monomethyl Ether 0.001 1 

 

 Polychlorinated Biphenyls 0.001 57 

 
3,3'

- dimethylbenzidine 0.0009 1

  3,3'

- dimethoxybenzidine 0.0004 1

  N, N

- dimethylaniline 0.0004 1

  p

- P henylenediamine 0.0004 1

  Propionaldehyde 0.0004 3 

 

 Ethylene Glycol 0.0001 1 


o

- T oluidine 0.00009 1 

  Isophorone 0.00006 1

 

 Dioxins and Furans

 2,3,7,8

- tetrachlorodibenzo

- p

- dioxin 0.000002 52 

 

 

 1,2,3,4,6,7,8

- heptachlorodibenzofuran 0.000002 16 

 

 

 1,2,3,4,6,7,8

- heptachlorodibenzo

- p

- dioxin 0.000001 61 

 

 

 1,2,3,6,7,8

- hexachlorodibenzofuran 0.0000009 54 

 

 

 1,2,3,4,6,7,8,9

- octochlorodibenzo

- p

- dioxin 0.0000006 18 

 

 

 1,2,3,4,7,8

- hexachlorodibenzofuran 0.0000005 19 

 

 

 2,3,4,7,8

- pentachlorodibenzofuran 0.0000005 53 

 

 

 1,2,3,4,6,7,8,9

- octochlorodibenzofuran 0.0000004 13 

 

 

 2,3,4,6,7,8

- hexachlorodibenzofuran 0.0000003 13 

 

 

 1,2,3,7,8

- pentachlorodibenzofuran 0.0000002 17 

 

 

 1,2,3,4,7,8,9

- heptachlorodibenzofuran 0.0000001 14 

 

 

 2,3,7,8

- tetrachlorodibenzofuran 0.00000009 15 

 

 

 1,2,3,7,8,9

- hexachlorodibenzofuran 0.00000008 12 

 

 

 1,2,3,6,7,8

- hexachlorodibenzo

- p

- dioxin 0.00000008 11 

 

 

Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 37

Table 3.1

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

and Availability of Dose

- Response Values

HAP a Emissions (tpy) Number of

Facilities Reporting HAP (148
facilities in
NPRM data set) Prioritized I nhalation Dose

- Response Value Identified by OAQPS b

PB

HAP? Unit Risk
Estimate for Cancer? Reference

Concentration
for Chronic
Noncancer? Health

Benchmark Values for
Acute
Noncancer?
1,2,3,7,8

- pentachlorodibenzo

- p

- dioxin 0.00000007 15 

 

 

 1,2,3,7,8,9

- hexachlorodibenzo

- p

- dioxin 0.00000005 11 

 

 

 1,2,3,4,7,8

- hexachlorodibenzo

- p

- dioxin 0.00000003 13 

 

 



a Notes for how HAP were speciated for risk assessment:

 For most metals, emissions reported as the elemental metal are combined with metal compound emissions (e.g., “cadmium” emissions modeled as “cadmium & compounds”). In the absence of speciation information, we assume the reported mass is 100 percent metal.

 For emissions of certain chemicals or chemical groups classified as POM, some (not that are not already speciated) emissions were grouped into POM subgroups as found on EPA’s Technology Transfer Network website for the
2005 National

- Scale Air Toxics Assessment at http://www.epa.gov/ttn/atw/nata20 05/methods.html#pom ( Approach to Modeling POM)

. These POM subgroups (e.g., POM 72002) all have unit risk estimates for cancer,
and are considered PB

- HAP. Pollutants previously grouped under POM 73002, POM 74002, POM 75002, and
POM 76002 are listed individ ually in this table.

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

 For emissions re ported generically as “chromium” or “chromium & compound,” emissions are speciated “chromium (III) compounds” and “chromium (VI) compounds” according to the individual emitting process speciation profile for this source category. Chromium speciation profi les can be found on the EPA’s Technology

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

.

 For emissions reported generically as “m ercury” or “mercury & compounds,” emissions are speciated for this category as 80% “mercury (elemental)”, 10% “gaseous divalent mercury”, and 10% “particulate divalent mercury”

. Mercury speciation profiles can be found on the EPA’s Technology Transfer Net work website for emissions inventories at http://www.epa.gov/ttn/chief/net/2005inventory.html

.

b Specific dose

- response values for each chemical are identified on EPA’s Technology Transf er Network website for air toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html

c There is no reference concentration for lead. In considering noncancer hazards for lead in this assessment, we compared maximum annual ambient exposure estimates to the National Ambient Air Quality Standards (NAAQS) for lead (0.15 μg/m 3 ). These NAAQS for lead were reviewed with revisions adopted in October 2008 ( http://www.epa.gov/air/lead/actions.html ). The primary (health

- based) standard is a maximum or not

- to

- be

- exceeded, rolling
three

- month avera ge, measured as total suspended particles (TSP). The secondary (welfare

- based) standard is identical to the primary standard.



### 3.2 Baseline r isk c haracterization
This section presents the results of the baseline risk assessment for the p etroleum r efining

s our ce s ector based on the modeling methods described in the previous sections. All baseline risk results are developed using the best estimates of actual HAP emissions summarized in the previous section

. The basic chronic inhalation risk estimates presented here are the maximum individual lifetime cancer risk, the maximum chronic hazard index, and the cancer incidence. We also present results from our acute inhalation impact screening assessment in the form ofDraft Risk Assessment for the Petroleum Refining Source Sector

–

FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 38

maximum hazard quotients, as well as the result s of our preliminary screen for potential non

inhalation risks from PB

- HAP. Also presented are the HAP “drivers,” which are the HAP that collectively contribute 90 percent of the maximum cancer risk or maximum hazard at the highest exposure location , as w ell as our analysis of risks associated with the maximum
allowed emissions under the current MACT standards. Definitions of these and other relevant
risk

- related terms can be found on the 200 5 National

- Scale Air Toxics Assessment Glossary Web page

. A detailed summary of the facility

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

.

MACT

- level Inhalation Assessment Results

Table s 3 .2

- 1 and 3.2

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

. T he results of the chronic inhalation cancer risk assessment are that the maximum
lifetime individual cancer risk posed by the 14 2 facilities could be 6 0 in a million considering
both the maximum facility, and the entire source sector . Emissions of naphthalene and
benzene from process equipment leaks and storage tank s are the major contributors to the risk. The total estimated cancer incidence from this source category is 0.3 excess cancer cases per year, or one excess case in every 3 years. A pproximately 1 00

, 000 pe ople were estimated to have cancer risks above 10 in a million and approximatel y 5

, 0 0 0 ,000 peo p le were estimated
to have cancer risks above 1 in a million considering the 14 2 facilities in this source category

. The maximum chronic noncancer TOSHI value for the source category could be up to 0.9 driven by emissions of hydrogen cyanide f rom catalytic cracking unit vents

.

Analysis of potential differences between actual emissions levels and the maximum emissions
allowable under the MACT standards (i.e., MACT

- allowable emissions) were also calculated
for the source category

. MACT

- allowable emissions were estimated by using two different methods, a model plant approach (Refinery Emissions Model (REM), approach ) and an approach that combined the results of the actual and REM emissions estimates to develop a
more conservative allowable risk est imate.

Appendix 9 provides a memo that describes in details these two approaches as w ell as the risk estimates using from both approaches. Risk results from the inhalation risk assessment using
the MACT

- allowable emissions indicate that the maximum lifetim e individual cancer risk
could be high er than those from the actual an a lysis

, or 9 0 to 100 in a million, and that the
maximum chronic noncancer Hazard Index value is about 1. The total estimated cancer incidence from this source category considering allowa ble emissions is expected to range
between 0.4 and 0.6 ex cess cancer cases per year or one excess case in every 1.5 to 2.5 years. The REM model approach predicts that approximately 9 0 ,000 people were estimated to have
cancer risks above 10 in a million and approximatel y 7

, 0 00,000 peop le were estimated to
have cancer risks above 1 22

. Chronic noncancer risks from the MACT

- allowable emissions are expected to remain at or below 1.

22 Population risks from allowable emissions were only calculated for the model plant emissions (REM) approach. For the 138 facilities modeled using the modeled plant approach the population risks greater than 10

- in

- 1 million was estimated to be 90,000. If we consider the second approach to determining allowable emissions ( combined the results of the actual and REM
emissions estimates ) we estimate that the allowable population risksDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 39

Worst

- case acute hazard quotients (HQs) were calculated for every HAP shown in
Table 3.1

- 1 that has an acute benchmark , and the highest refin ed screening acute HQ value of
5 (based on the acute REL for nickel ) is shown in Table 3.2

- 1. This value includes a
refinement of determining the highest HQ value that is outside facility boundaries. It’s also important to note that the HQ of 5 for Nickel assumes that the primary source of the nickel emissions, the fluid catalytic cracking unit vent, was modeled with an hourly emissi ons multiplier of 60 times the annual emissions rate. There are also refined acute HQ values (based on RELs) greater than 1 for acetaldehyde, acrolein, arsenic compounds, benzene, and nickel compounds

. In all, six facilities are estimated to
have a refine d acute HQ (based on an REL ) greater than 1 (four of these facilities are 2 or less)

. No facilities are estimated to have a AEGL

- 1 greater than 1. Acute estimates for each

p l ant and pollutant are provided in Appendix 5 of this document, while refined estim ates are provided in Appendix 6 of this document ( Acute Impacts Refined Analysis ).

Table 3 .2

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

Result HAP “Drivers” Facilities in Source Category
Number of Facilities Estimated to be i n Source Category 14 2 n/a

Number of Facilities Identified by ICR and
Modeled in Risk Assessment 14 2 n/a

Cancer Risks
Maximum Individual Lifetime Cancer Risk (in 1 million) 6 0 naphthalene, benzene

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1
million 0 n/a

Greater than or equal to 10 in 1
million 48 naphthalene, benzene, ethyl benzene, ethylene dibromide, 7,12

- dimethylbenz[a]anthracene, benzidine, dibenzo[a,h]anthracene, benzo[a]pyrene, 1,1,2

- trichloroethane, 2

- methylnaphthalene, acetaldehyde, POM 72002, fluorene, benzo[b]fluoranthene, formaldehyde, 3

- methylcholanthrene, acrylonitrile, nickel compounds,
1

- methylnaphthalene, benz[a]anthracene, indeno[1,2,3

- c,d]pyrene, chrysene, arsenic compounds, tetrachloroethene, cadmium compounds, fluoranthene, benzo(ghi)perylene, chromium (VI) compounds, 1,3

- butad iene, 1,1,2,2

- tetrachloroethane, ethylene dichloride, 2

-

greater than 10

- in

- 1 million would be greater than 90,000 people. Further,the Further, the number of people above 1

- in

- 1 million would also be higher than the 7,000,000 estimated using the REM model.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 40

Table 3 .2

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

Result HAP “Drivers” nitropropane, acenaphthene, beryllium compounds, 2,3,7,8

- tetrachlorodibenzo

- p

dioxin, methyl tert

- butyl ether, benzo(e)pyrene

Greater than or equal to 1 in 1
million 11 1 naphthalene, benzene, ethyl benzene, ethylene dibromide, 7,12

- dimethylbenz[a]anthracene, benzidine, dibenzo[a,h]anthracene, benzo[a]pyrene, 1,1,2

- trichloroethane, 2

- methylnaphthalene, acetaldehyde, POM 72002, fluorene, benzo[b]fluoranthene, formaldehyde, 3

- methylcholanthrene, acrylonitrile, nickel compounds,
1

- methylnaphthalene, benz[a]anthracene, indeno[1,2,3

- c,d]pyrene, chrysene, arsenic compounds, tetrachloroethene, cadmium compounds, fluoranthene, benzo(ghi)perylene, chromium (VI) compounds, 1,3

- butadiene, 1,1,2,2

- tetrachloroethane, ethylene dichloride, 2

- nitropropane, acenaphthene, beryllium compounds, 2,3,7,8

- tetrachlorodibenzo

- p

dioxin, methyl tert

- butyl ether, benzo(e)pyrene

, ethylene oxide, p

dichlorobenzene, vinyl chloride, 1,3

- dichloropropene, perylene, aniline Chronic Noncancer Risks
Maximum Neu rological Hazard Index 0.9 hydrogen cyanide Number of Facilities with Maximum Neurological Hazard Index:
Greater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 23 5
2
2
2
2 nickel compounds (REL)

arsenic compounds (REL) acrolein (REL) benzene (REL) acetaldehyde (REL)
Number of Facilities With Potential for
Acute Effects 6 nickel compounds, arsenic compounds, acrolein, benzene, acetaldeyhyde Population Exposure Number of People Living Within 50
Kilometers of Facilities Modeled 8 3 ,000,000 n/a

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

Greater than or equal to 10 in 1
million 1 0 0 ,000 n/a

Greater than or equal to 1 in 1 5, 0 0 0,000 n/a

23 As shown in Tables 2.6.3 and 3.2

- 2 there are no AEGL or ERPG values for nickel or arsenic compounds. Additionally, ther e are no short

- term occupational values for these metals to compare to the REL values.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 41

Table 3 .2

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

Result HAP “Drivers”

million Number of People Exposed to Noncancer Neurological Hazard Index:
Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.3 n/a

Contribution of HAP to Cancer Incidence naphthalene 22% n/a
benzene 21% n/a
2

- m ethylnaphthalene 13% n/a
7

- 12

- dimethylbenz[a]anthracene 10% n/a

1,3

- butadiene 6 % n/a

n ickel compounds 5% n/a ethylene dibromide 5 % n/a ethyl benzene 4% n/a
b enzo[a]pyrene 2% n/a formaldehyde 2% n/a Contribution of Process to Cancer Incidence Coking unit vents & coke handling 31% n/a

Process equipment leaks 23% n/a
Wastewater treatment 1 2 % n/a Catalytic cracking unit vent 10% n/a

Storage tanks 7% n/a Cooling towers 6% n/a
Flares 5% n/a Marine vessel loading & unloading 2% n/a Catalytic reforming unit vents 1% n/a Refinery processes (other, general) 1% n/a

Incinerators 1% n/a

Table 3.2

- 2

. Summary of Refined Acute Results for Petroleum

Refining Source Sector

Refined Results Maximum Acute Hazard Quotients Acute Dose

- Response Values

HAP Max. 1

-

hr. Air Conc. (mg/m 3 ) Based on

REL Based on

AEGL

- 1/ ERPG

- 1 Based on

AEGL

- 2/ ERPG

- 2 REL

(mg/m 3 ) AEGL

- 1

(1

- hr) (mg/m 3 ) ERPG

- 1

(mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

- 2

(mg/m 3 )

Acetaldehyde 1.0 2 0.05 .003 0.47 81 18 490 360

Acrolein 0.00 5 2 0.1 0.03 0.0025 0.069 0.11 0.23 0.34Draft Risk Assessment for the Petroleum Refining Source Sector

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Arsenic compounds 0.00 04 2 na na 0.0002 na na na n a
Benzene 2.7 2 0.02 0.006 1.3 170 160 2600 480
Nickel compounds 0.00 1 5 na na 0.002 na na na na

Notes on Refined Process: 1) The initial screening was performed for all emitted HAP with available acute dose

- response values. Only those pollutants whose screening HQs were greater than 1 for at least one acute threshold value are shown in the table. 2) HAP with available acute dose

- response values which a re not in the table do not carry any potential for posing acute health risks, based on an analysis of currently available emissions data.

Notes on Acute Dose

- Response Values:
REL

– California EPA reference exposure level for no adverse effects. Most, b ut not all, RELs are for 1

- hour exposures.
AEGL

– Acute exposure guideline levels represent emergency exposure (1

- hour) limits for the general public.
AEGL

- 1 is the exposure level above which it is predicted that the general population, including suscepti ble individuals, could experience effects t hat are notable discomfort, but which are transient and reversible upon cessation of exposure.
AEGL

- 2 is the exposure level above which it is predicted that the general population, including susceptible individual s, could experience irreversible or other serious, long

- lasting adverse health effects of an impaired ability to escape.
EPRG

– Emergency Removal Program guidelines represent emergency exposure (1

- hour) limits for the general public.
ERPG

- 1 is the maximum level below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing other than mild, transient adverse health effects.
ERPG

- 2 is the maximum exposure below which it is believed that nearly all individuals co uld be exposed for up to 1 hour without experiencing or developing irreversible or other serious health effects or symptoms which could impair an individual’s abilit y to take protective action.

MACT

- level Multipathway Assessment Results

To identify potential multipathway health risks from PB

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

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

r ates (see section 2.5). The PB

- HAP emitted by facilities in this category include cadmium compounds (97 facilities)

, chlorinated dibenzo dioxins and furans (analyzed as 2,3,7,8

- tetrachlorodibenzo

- p

- dioxin TEQ) (78 facilities)

, polychlorinated biphenyls (58 facilities),

mercury compounds (106 facilities), and polycyclic organic matter ( POM ) (analyzed as benzo(a)pyrene toxicity equivalence or (TEQ) )(113 facilities)

.

Following the above approach, 1 facility emit ted cadmium compounds above the Tier I
screenin g level, 42 facilities emit ting chlorinated dibenzo dioxins and furans as 2,3,7,8

- tetrachlorodibenzo

- p

- dioxin TEQ above the Tier I screening level, 1 4 facilities emit mercury compounds above the Tier I screening level, and 5 7 facilities emit POM as benzo(a) pyrene TEQ above the screening level. Polychlorinated biphenyl is a PB

- HAP but does not currently have a multipathway screening value and so was not evaluated for potential non

- inhalation
risks. As shown in Table 3.1

- 1, this HAP is not emitted in apprecia ble quantities. Due to the theoretical construct of the screening model, these factors are not directly translatable into estimates of risk or hazard quotients for these facilities. Table 3.2

- 3 summarizes the results of this screening (Tier I

) comparison.

For the PB

- HAP that did not screen out during our initial “Tier I ” multipathway screening analysis, we refined our analysis somewhat by including some additional site

- specific information to develop an “intermediate” or Tier II screen. (See A ppendix 4 of this document
for more information about the Tier II screen.) The additional site

- specific information included the land use around the facilities, the location of fishable lakes, and local windDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 43

direction and speed. The result of this analys is was the development of site

- specific emission screening thresholds for cadmium, chlorinated dibenzo dioxins and furans

, POM and mercury.
Based on this Tier II screening analysis, as presented in Table 3.2

- 3, 1 facility’s emissions
remained above the scr eening threshold for cadmium with the highest at about 2 times the
threshold. Emissions from 23 facilities remained above the threshold for chlorinated
dibenzo dioxins and furans with the highest at about 4 0 times the threshold. No facility’s
emissions re mained above the threshold for mercury. For POM, 4 4 facility’s emissions
exceeded the site

- specific screening threshold for POM with the highest by a factor of about
3 0

. A T ier II exceedance cannot be equated with a risk value or a hazard quotient or in dex. Rather it represents a high

- end estimate of what the risk or hazard may be. For example, an exceedance of 2 for a non carcinogen can be interpreted to mean that we have high confidence that the hazard would be lower than 2. Similarly, an exceedance of 30 for a carcinogen means that we have high confidence that the risk is lower than 30

- in

- 1

- million. Our confidence comes from the conservative, or health

- protective, assumptions that are in the Tier II screen: we choose inputs from the upper end of the ra nge of possible values for the influential parameters used in the Tier II screen; and we assume that the exposed individual exhibits ingestion behavior that would lead to a high total exposure.

Table 3.2

- 3

. Summary of Multipathway Screening Results

for Petroleum Refining Source Sector

Tier I Tier II

PBHAP Num
Facilities Emitting
This
PBHAP (142 in

source category) Max

Emissions of
this PBHAP (TPY) Max

Emissions
of this PBHAP, Div by the Screening
Level Num

Facilities Exceeding
the Screening
Level of
this
PBHAP Max

Emissions
of this PBHAP, Div by the Screening
Level Num

Facilities Exceeding
the Screening
Level of
this
PBHAP Cadmium Compounds 97 6.05E

- 02 5 1 2 1

Chlorinated Dibenzodioxins and Furans as 2,3,7,8

- Tetrachlorodibenzo

- p

- dioxin 78 2.81E

- 09 100 42 40 23

Divalent Mercury 106 1.73E

- 03 5 14 1 0 Polycyclic Organic Matter as Benzo(a)Pyrene 11 3 2.58E

- 03 400 57 30 44

I n evaluating the potential for multipathway effects from emissions of lead, modeled
maximum annual lead concentrations were compared to the NAAQS for lead (0.15 μg/m 3 )

. Lead emissions were reported from 103 facilities. Results of this analysis estimate that with
the exception of one facility, the NAAQS for lead would not be exceeded by any facili ty. At the one facility , the lead NAAQS is exceeded 1.5 times at an on

- site location. Off

- site at this facility, the concentrations are below the NAAQS.

To gain a better understanding of the uncertainty associated with the multipathway Tier I and 2 screening analysis, a more refined multipathway case study using the TRIM.Fate model was conducted for a single petroleum refinery. The site, Marathon Ashland Petroleum facilityDraft Risk Assessment for the Petroleum Refining Source Sector

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(NEI6087) near Garyville in St. John the baptist Parish, Louisiana, was among those that
exceeded the Ti er I screen for any PB

- HAP and it was among the highest of the refineries that
exceeded a Tier II threshold for any PB

- HAP. It also was selected based on the feasibility, with respect to the modeling framework, of obtaining model parameters for the region surrounding the refinery. The exposure scenarios assessed for the selected facility are not necessarily representative of the highest potential exposures for human receptors from the petroleum refineries sector, but the results for exposures (and the ris ks calculated for those exposures) are anticipated to be among the highest that might be encountered for this source category. The approach, data, assumptions, and results of the site

- specific assessment are presented in Appendix 10 ( Technical Support Doc ument: Human Health Multipathway Residual Risk Assessment for the Petroleum Refineries Sector

– A site Specific Analysis ) of
this document.

As in the screening assessments, hypothetical farmer and angler scenarios were included in
the site

- specific ass essment, as well as children in different age ranges and adults. It is important to note that even during the refined multipathway analysis

, that no data exists to verify existence of either the farmer or angler scenario outlined below. These scenarios ar e included as part of the exercise of evaluating the uncertainty associated with the multipathway screens. The farmer scenario involves an individual living for a 70

- year lifetime on a farm
homestead in the vicinity of the source and consuming produce grow n on, and meat and animal prod ucts raised on, the farm. The individual also incidentally ingests surface soil at the location of the farm homestead. The angler scenario involves an individual who regularly consumes fish caught in freshwater lakes in the vicinity of the source of interest over the
course of a 70

- year lifetime. In addition, exposure estimates and risks for infants consuming contaminated breast milk were evaluated in the case of dioxins, with the assumption that the nursing mother was expos ed to chemicals via one of the two basic scenarios described above.

Variations of these two scenarios were evaluated using different assumptions regarding food source (i.e., location of the farm homestead or the water body from which fish are obtained), the age of the individual exposed (for non

- cancer hazards), the assumed ingestion rate of each food type, and other factors. In particular, a range of fish ingestion rates was evaluated to determine the possible health risks associated with that pathway.

Cancer risk estimates, as presen ted in table 3.2

- 4, from exposure to PAHs include an
incremental lifetime cancer risk of 2 in 1 million, with farm exposure at 90 th percentile ingestion rates driving the risk. Cancer results from exposure to dioxins also include an
incremental lifetime cancer risk of 2 in 1 million, with fish exposure by the adult female angler at 9 9 th percentile ingestion rates driving the risk. Non cancer HQs , also presented in
Table 3.2

- 4, did not exceed 1 for any scenario for expo sure to mercury or cadmium. For methyl mercury, the highest HQ was 0. 0 4 with the Child Age 1

- 2 group driving the risk

, while the highest noncancer HQ for cadmium w as 0.02 , also with the Child Age 1

- 2 group driving the risk. As explained in Appendix 4, th e scenarios included in the screening and refined assessments include children at different age ranges, as well as adults, and the Child Age 1

- 2 group has the highest risks for the noncancer endpoints [ 40 ].Draft Risk Assessment for the Petroleum Refining Source Sector

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Table 3.2

- 4. Summary of Refined Multipathway R esults for Marathon Ashland Petroleum f acility (NEI6087) St. John the B aptist Parish,
Louisiana

PB

- HAP Group Ratio of Emissions to the
Emission Screening

Threshold Site

- specific Hazard Quotient or Risk

Tier I Tier II Via Fish Only, Lac des

Allemands Via Farm Only, Farm_W_S Combined Fish + Farm

Mercury (non

- cancer) 2 0. 3 0.04 0.0001 0.04

Cadmium (non

- cancer) 0.3 0.05 0.02 0.0007 0.02

PAHs (cancer) 1 00 2 0 0. 4 2 2

Dioxins (cancer) 40 5 1 0.5 2

Total Incremental Lifetime Cancer Risk (PAH+Dioxin) 200 30 1 2 4

The site

- specific analysis for this facility showed that the potential risk was lower than the
Tier II screen for each pollutant over

- predicted t he potential risk when compared to the refined analysis results. In the site

- specific analysis, for mercury emissions, the potential HQ

was about 7 times lower than th e exceedance of the Tier II screen ing threshold . For cadmium emissions, the site

- specific results (HQ) are about 3 times lower than the exceedance of the
Tier II screening th reshold

. For PAH emissions, the site

- specific analysis had a cancer risk 1 4
times the exceedance of the Tier II screening threshold

. Finally, for the site

- specific analysis

, the cancer risk from emissions of dioxin s is 3 times lower than the exceedance o f the Tier II screening threshold

.

While this more refined assessment was only performed on a single facility, the results of this analysis lead us to the conclusion that if refined analyses were performed for other sites, the
risk estimates would consis tently be lower than those estimated by the Tier 1 and 2 analys e s. As shown in Table 3.2.

- 5, the overall trend when the analyses rely less on defaults and more
on site

- specific data is an increase in th e emissions threshold. For example, between the Tier
I and Tier II screens, the screening threshold for mercury emissions increased by 6 times. For this source category, the threshold for mercury increased by 45 times between the Tier I
screen and the site

- specific assessment.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 46

Table 3.2

– 5. Summary of Trends in Threshold Exceedances for the Multipathway Screening
and Site

- Specific Analyses

PB

- HAP Group Increase in Emissions Threshold (or Increase in Ration of Emissions to Screening Threshold)

Tier I to Tier II Tier II to Site

Specific Tier I to Site

Specific

Mercury 6 7 45

Cadmium 6 3 20

PAHs 4 1 4 58

Dioxins 8 3 2 3

Total Cancer 5 9 4 5

MACT

- level Environmental Assessment Results

We conducted a screening

- level evaluation of the potential adverse environmental risks
associated with emissions of the following environmental HAP from the petroleum refineries source category: lead compounds, mercury compounds, cadmium compounds, POM, chlorinated dibenzodioxins and furans, hydrogen chloride, and hydrogen fluoride. The results
of the env ironmental screening analysi s are summarized in Table 3.2

- 6

.

In the Tier I screening analysis for PB

- HAP (other than lead, which was evaluated differently as noted in section III.A.5 of this preamble) the individual modeled Tier I concentrations for

one facilit y in the source category exceeded soil ecological benchmarks for mercuric chloride. In addition, Tier I modeled concentrations for four facility exceeded sediment and soil ecological benchmarks for PAH. Therefore, we conducted a Tier II assessmen t. In the Tier II screening analysis for PB

- HAP none of the individual modeled concentrations for any facility in the source category exceeded any of the ecological benchmarks (either the LOAEL or NOAEL). For lead, we did not estimate any exceedances of the secondary lead NAAQS.

For hydrogen fluoride and hydrogen chloride, the average modeled concentration around each facility (i.e., the average concentration of all off

- site data points in the modeling domain) did not exceed the ecological benchmarks. In addition, each individual modeled concentration of hydrogen chloride and hydrogen fluoride (i.e., each off

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

Table 3.2

- 6

. Summary of Environmental Risk Screen Results for the Petrol eum Refineries Source Category

Environmental
HAP Number of Facilities In Category

Exceeding Percent of Modeled Area in CategoryDraft Risk Assessment for the Petroleum Refining Source Sector

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Exceeding 2

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

PB

HAP Pb None None None None 0% 0%

HgCl 2 NA 1 None None 0% 0%
Cd None None None None 0% 0%
PAH 4 None None None 0% 0%
Dioxin None None None None 0% 0%
Acid
Gases HF 3 NA None

- - NA 0%

HCL 4 NA None

- - NA 0%

NA

– Not Applicable.
1

- Tier II screen is performed for PB

- HAP when there are exceedances of the Tier I screen. The acid gas screen is a one tier screen.
2

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

- HAP the percent area is based on the Tier II results, if a Tier II analysis is performed. Otherwise, the percent area is based on the Tier I results.
3

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

- the level between a NOAEL and a LOAEL, we have listed the results under the LOAEL column.
4

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

Facility

- wide Inhalation Assessment Results

The facility

- wide chronic MIR and TOSHI, availab le in Appendix 5 , are based on emissions from all sources at the identified facilities. The results of the facility

- wide assessment for
cancer ris ks are summarized in Table 3.2

- 7 . The results indicate that 1 15 facilities with petroleum refining processes (covered by MACT 1 or MACT 2) have a facility

- wide cancer MIR greater than or equal to 1 in a million. The maximum facility

- wide cancer MIR is 70 in
a million , at one facility. The 70 in a million is mainly driven by naphthalene, chromium (VI) compounds , and arsenic compounds from storage tanks, fugitive dust/blasting/construction, and coking unit vents & coke handling processes. The maximum facility

- wide TOSHI for the source category is estimated to be 4, at one facility, mainly driven by emissions of chlorine
from catalytic reforming unit vents and cooling towers

.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 48

Table 3.2

- 7 Source Category Contribution to Facility

- Wide Chronic Cancer Risks (Actual Emissions)

P etroleum Refining Source Sector Number of Facilities Binned by Facility

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

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

> 90% 14 37 38 0 89
50

- 90% 9 20 12 0 41
10

- 50% 3 4 3 0 10 < 10% 1 0 1 0 2
Total 27 61 54 0 142



### 3.3 Post

- control risk characterization

As shown in Table 3.2

- 1 above, the baseline cancer risks (as shown in the Incidence Driver rows) are primarily driven by coking unit vents and coke handling and process equipment
leaks. Given this, using the same risk assessment methods described above, w e estimated
what the risks would be if all of the petroleum refinery facilities adopted control measures to
limit emissions from coking units, equipment leaks, and storage and loading processes in one
control scenario. This scenario includes an 8 9 6 percent reduction in HAP emissions from coking units , a 4 percent reduction in HAP emissions from equipment leaks , and a 40 51 percent reduction in HAP emissions from storage and loading processes

. (The scenario is
described in more detail in the emission s memo in the docket

. [5] ) Based on this control scenario, we estimated (based on use of the same modeling assumptions and methodologies used for the baseline risk assessment) that the maximum individual lifetime cancer risk for one facility would be re duced from 60 in a million to 50 in a million. These controls would reduce the cancer risk to the individual most exposed from 60

- in

- 1 million to 50

- in

- 1 million based on actual emissions at the facility where storage tank emissions were driving the risk. However, the post

- control MIR remains unchanged fo r the refinery source category

, at 60

- in 1

- million, because the several facilities combine for a n MIR of 60

- in

- 1 million at a census block location. The post

- control cancer risk is primarily driven by naphthalene, dibenzo[a,h]anthracene, and benzo[a]py rene from process equipment leaks

. The number of people estimated to have a cancer risk greater than or equal to 10 in a million would be
reduced from 10 0 ,000 people to 80 ,000 people. And, the number of people estimated to have a cancer risk greater than or equal to 1 in a million would be reduced from 5, 0 00,000 people

to 4

, 0 00,000 people. There is a similar percentage reduction in incidence ( 17 percent) ; however this is not readily apparent with the presentation of the results to one significant figure (0.3 both in the baseline and post

- control scenarios ).

A closer look at the controls driving the exposed population reductions shows that approximately 7, 300 people will have risks less tha n 10 in a million and 985,000 people will
fall below 1 in a million as a result of proposed del ayed coker units (DCU) controls. T he number of people with a cancer risk greater than 10

- in

- 1 million from storage tank emissionsDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 49

will be reduced from 3,000 to 6 0 and the number of people with a cancer risk greater than 1

- in

- 1 million from storage tank emissions will fall from 140,000 to 72,000 as a result of proposed storage tank controls. Similarly, a closer look at the controls driving the incidence

re ductions shows that approxim at ely 15 percent (0.05 incidence) of the incidence reduction is
attributable to proposed d elayed c oker u nits (DCU) controls and about 2 percent (0.01 incidence) from proposed storage vessel controls.

The results of the post

- control assessment also indicate that, based on actual emissions, there would be no reduction in chronic noncancer inhalation values because we did not identify any cost effective control technologies that would further reduce these risks. The re is a slight
reduct ion in acute noncancer inhalation values, with the maximum off

- site HQ reduced from 5 (actual emissions) to 3 (post

- control emissions) , based on the REL for nickel compounds.

Considering post

- control emissions of multipathway HAP, there are expected t o be minimal
reductions in PB

- HAP with the control scenario (see Appendix 5

- Table 4b)

.



### 4 General d iscussion of u ncertainties and h ow t hey h ave b een

a ddressed

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

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

- or long

- term population mobility, and by neglecting processes like deposition, plume depletion, and atmospheric degradation. Additionally, estimates of the MIR c ontain 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 population risk estimates.

A sensitivity analysis perform ed for the 1999 NATA found that the selection of the meteorology dataset location could result in a range of chronic ambient concentrations which
varied from as much as 17 percent below the predicted value to as much as 84 percent higher than the predicted value. This variability translates directly to the predicted exposures and risks in our assessment, indicating that the actual risks could vary from 17 percent lower to 84 percent higher than the predicted values.Draft Risk Assessment for the Petroleum Refining Source Sector

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We have purposely biased the acute scre ening results high, considering that they depend upon the joint occurrence of independent factors, such as hourly emissions rates, meteorology and human activity patterns. Furthermore, i n cases where multiple acute threshold values are
considered scientif

ically acceptable we have chosen the most conservative of these threshold
values , erring on the side of overestimating potential health risks from acute exposures. In the cases where these results indicated the potential for exceeding short

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



### 4.2 Uncertainties in the d ose - r esponse r elationships
In the sections that follow, separate discussions are pr ovided on uncertainty associated with cancer potency factors and for noncancer reference values. Cancer potency values are derived for chronic (lifetime) exposures. Noncancer reference values are generally derived for chronic exposures (up to a lifetime) , bu t may also be derived for acute (

- term (>24 hours up to 30 days), and subchronic (>30 days up to 10 percent of lifetime) exposure durations, all of which are derived based on an assumption of continuous exposure throughout the duratio n 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.

Alt hough 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 non

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

Additionally, chronic dose

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

- evaluate risks if, as a result of these reviews, a dose

- resp onse 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, we provide a quote from the EPA’s Guidelines for Carcinog en Risk Assessment [ 41 ] (herein
referred to as Cancer Guidelines ). “The primary goal of EPA actions is protection of human health; accordingly, as an Agency policy, risk assessment procedures, including default options that are used in the absence of scien tific data to the contrary, should be healthDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 51

protective.” The approach adopted in this document is consistent with this approach as
described in the Cancer Guidelines

.

For cancer endpoints EPA usually derives an oral slope factor for ingestion and a unit risk value for inhalation exposures. These values allow estimation of a lifetime probability of developing cancer given long

- term exposures to the pollutant. Depending on the pollutant being evaluated, EPA relies on both animal bioassay and epidemiologi cal studies to characterize cancer risk. As a science policy approach, consistent with the Cancer
Guidelines , EPA uses animal cancer bioassays as indicators of potential human health risk
when other human cancer risk data are unavailable.

Extrapolatio n of study data to estimate potential risks to human populations is based upon EPA’s assessment of the scientific database for a pollutant using EPA’s guidance documents and other peer

- reviewed methodologies. The EPA Cancer Guidelines describes the Agency ’s recommendations for methodologies for cancer risk assessment. EPA believes that cancer risk estimates developed following the procedures described in the Cancer Guidelines and outlined below generally provide an upper bound estimate of risk. That is, EPA’s upper bound estimates represent a “plausible upper limit to the true value of a quantity” (although this is usually not a true statistical confidence limit). 24 In some circumstances, the true risk could be as low as zero; however, in other circumsta nces the risk could also be greater. 25 When developing an upper bound estimate of risk and to provide risk values that do not underestimate risk, EPA generally relies on conservative default approaches. 26 EPA also uses the upper bound (rather than lower bound or central) estimates in its assessments, although it is noted that this approach can have limitations for some uses (e.g. priority setting, expected benefits analysis).

Such health risk assessments have associated uncertainties, some which may be considered quantitatively, and others which generally are expressed qualitatively. Uncertainties may vary substantially among cancer risk assessments associated with exposures t o different pollutants, since the assessments employ different databases with different strengths and limitations and the procedures employed may differ in how well they represent actual biological processes for the assessed substance. EPA’s Risk Characte rization Handbook also recommends that risk characterizations present estimates demonstrating the impact on the assessment of alternative

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

25 The exception to this is the URE for benzene, which is considered to cover a range of values, each end of
which is considered to be equally plausible, and which is based on maximum likelihood estimates.

26 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are generic approaches, based on general scientific knowledge a nd policy judgment, that are applied to various
elements of the risk

- assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions
are used to ensure that risk to chemicals is not underestim ated (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 Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 52

choices, data, models and assumptions [ 42 ]. Some of the major sources of uncertainty and variability in deriving cance r risk values are described more fully below.

(1) The qualitative similarities or differences between tumor responses observed in experimental animal bioassays and those which would occur in humans are a source of uncertainty in cancer risk assessment. In general, EPA does not assume that tumor sites observed in an experimental animal bioassay are necessarily predictive of the sites at which
tumors would occur in humans. 27 However, unless scientific support is available to show otherwise, EPA assumes t hat tumors in animals are relevant in humans, regardless of target organ concordance. For a specific pollutant, qualitative differences in species responses can
lead to either under

- estimation or over

- estimation of human cancer risks.

(2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead to differences in risk predictions. For example, the measure of dose is commonly expressed in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, da ta may support development of a pharmacokinetic model for the absorption, distribution, metabolism and excretion of an agent, which may result in improved dose metrics (e.g., average blood concentration of the pollutant or the quantity of agent metabolized in the body). Quantitative uncertainties result when the appropriate choice of a dose metric is uncertain or when dose metric estimates are themselves uncertain (e.g., as can occur when alternative pharmacokinetic models are available for a compound). U ncertainty in dose estimates may
lead to either over or underestimation of risk.

(3) For the quantitative extrapolation of cancer risk estimates from experimental animals to humans, EPA uses scaling methodologies (relating expected response to differences in physical size of the species), which introduce another source of uncertainty. These methodologies are based on both biological data on differences in rates of process according to species size and empirical comparisons of toxicity between experimental animals and humans. For a particular pollutant, the quantitative difference in cancer potency between experimental animals and humans may be either greater than or less than that estimated by baseline scientific scaling predictions due to uncertainties a ssociated with limitations in the
test data and the correctness of scaled estimates.

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which there is a specified excess risk of cancer, which is used as the point of departure (or POD) for the remainder of the calculation. Statistical uncertainty in developing a POD using a benchmark dose (BMD) approach is generally addressed tho ugh use of the 95 percent lower confidence limit on the dose at which the specified excess risk occurs (the BMDL), decreasing the likelihood of understating risk. EPA has generally utilized the multistage model for estimation of the BMDL using cancer bioa ssay data (see further discussion below).

27 Per the EPA Cancer Guidelines: “The default option is that positive effects in animal cancer studies indicate that the agent under study can have carcinogenic potential in humans.” and “Target organ concordance is not a prerequisite for evaluating the implications of animal study resu lts for humans.”Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 53

(5) Extrapolation from high to low doses is an important, and potentially large, source of uncertainty in cancer risk assessment. EPA uses different approaches to low dose risk assessment (i.e., developing estima tes of risk for exposures to environmental doses of an agent from observations in experimental or epidemiological studies at higher dose) depending on the available data and understanding of a pollutant’s mode of action (i.e., the manner in which a polluta nt 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 w hich a pollutant causes cancer) is a key consideration in determining how risks should be estimated
for low

- dose exposure. A reference value is calculated when the available mode of action data show the response to be nonlinear (e.g., as in a threshold re sponse). A linear low

- dose (straight line from POD) approach is used when available mode of action data support a linear (e.g., nonthreshold response) or as the most common default approach when a compound’s mode of action is unknown. Linear extrapolatio n can be supported by both pollutant

- specific data and broader scientific considerations. For example, EPA’s Cancer Guidelines generally
consider a linear dose

- response to be appropriate for pollutants that interact with DNA and
induce mutations. Polluta nts 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

approac h.

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 fa ce of uncertainty and variability. EPA believes that linear dose

- response models, when appropriately applied as part of EPA’s cancer risk assessment process, provide an upper bound estimate of risk and generally provide a health protective approach. Note that another source of uncertainty is the
characterization of low

- dose nonlinear, non

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

- probit models) in representing dose resp onse relationships due to the variability in response within human populations. Another National Research Council (NRC) report [ 43 ] suggests that models based on distributions of individual thresholds are likely to lead to sigmoidal

- shaped
dose

- response fu nctions for a population. This report notes sources of variability in the human population: “One might expect these individual tolerances to vary extensively in humans depending on genetics, coincident exposures, nutritional status, and various other

sus ceptibility factors...” Thus, if a distribution of thresholds approach is considered for a carcinogen risk assessment, application would depend on ability of modeling to reflect the degree of variability in response in human populations (as opposed to re sponses in bioassays with genetically more uniform rodents). Note also that low dose linearity in risk can arise for reasons separate from population variability: due to the nature of a mode of action and additivity of a chemical’s effect on top of backgr ound chemical exposures and biological

processes.

As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight line approach from the BMDL. This is equivalent to using an upper confidence limit on the slope of the straig ht line extrapolation. The impact of the choice of the BMDL on bottom lineDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 54

risk estimates can be quantified by comparing risk estimates using the BMDL value to central estimate BMD values, although these differences are generally not a large contributor t o uncertainty in risk assessment (Subramaniam et. al., 2006) [ 44 ]. It is important to note that earlier EPA assessments, including the majority of those for which risk values exist today, were generally developed using the multistage model to extrapolate d own to environmental dose levels and did not involve the use of a POD. Subramaniam et. al. (2006) also provide comparisons indicating that slopes based on straight line extrapolation from a POD do not show large differences from those based on the upper c onfidence limit of the multistage
model.

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

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

- specific data to evaluate this variability are generally not available. There may also be important life stage d ifferences in the quantitative potency of carcinogens and, with the exception of the recommendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic mode of action, risk assessments do not generally quantitatively address life stage differences. However, one approach used commonly in EPA assessments that may help address variability in response is to extrapolate human response from results observed in the most sensitive species and sex tested, resulting typically in the highest URE w hich 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 th at are intended to be
health

- protective. That is, EPA and other organizations which develop noncancer reference values (e.g., the Agency for Toxic Substances and Disease Registry

– ATSDR) utilize an approach that is intended not to underestimate risk in th e 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 fact ors are commonly default values 28 e.g., factors of 10 or 3, used in the absence of compound

- specific data; where data are available, uncertainty factors may also be developed using compound

- specific information. When data are limited, more

28 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are generic approaches, based on general scientific knowledge and policy judgment, that are applied to various
elements of the risk

- asses sment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An examination of EPA Risk Assessment Principles and Practices,
EPA/100/B

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

- final.pdf.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 55

assumptions are needed and more default factors are used. Thus there may be a greater tendency to overestimate risk

— in the sense that further study might support development of reference values that are higher (i.e., less potent) because fewer default assumptions are

nee ded. 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 e xposures. These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or of a continuous inhalation exposure (RfC) to the human population (including sensitive subgroups) that is likely to be wit hout an appreciable risk of deleterious effects during a lifetime. 29 To derive values that are intended to be “without appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach [ 45 ], [ 46 ] which includes consideration of both uncert ainty and variability.

EPA begins by evaluating all of the available peer

- reviewed literature to determine non

cancer endpoints of concern, evaluating the quality, strengths and limitations of the available studies. EPA typically chooses the relevant endpoint that occurs at the lowest dose, often using statistical modeling of the available data, and then determines the appropriate point of departure (POD) for derivation of the reference value. A POD is determined by (in order of preference): (1) a sta tistical estimation using the benchmark dose (BMD) approach; (2) use of the dose or concentration at which the toxic response was not significantly elevated (no
observed adverse effect level

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

A series of downward adjustments using default UFs is then applied to the POD to estimate
the reference value [ 47

] . While collectively termed “UFs”, these factors account for a number of different quantitative considerations when utilizing observed animal (usually rodent) or human toxicity data in a risk assessment. The UFs are intended to account for: (1) variation in susceptibility among the members of the human population (i.e., inter

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

- than

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

. When scientifically sound, peer

- reviewed assessment

- specific data are not available, default adjustment values are selected for the individual UFs. For each type of uncertainty (when relevant to the assessment) , EPA ty pically 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 adjustmen t is not relevant to an assessment (e.g., if applying human toxicity data and an interspecies extrapolation is not required) the associated UF is not used. The major adjustment steps are described more fully below.

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

29 See IRIS glossaryDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 56

smaller

- sized population, often of one sex or of a narrow range of life stages (typical of occupational epidemiolog ic 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

e xamine the potential magnitude of human variability are often unavailable. In some situations, a smaller UF of 3 may be applied to reflect a known lack of significant variability among humans.

2) Extrapolation from results of studies in experimental ani mals to humans is a necessary step for the majority of chemical risk assessments . When interpreting animal data, the concentration at the POD (e.g. NOAEL, BMDL) in an animal model (e.g. rodents) is extrapolated to estimate the human response. While there is long

- standing scientific support
for the use of animal studies as indicators of potential toxicity to humans , there are uncertainties in such extrapolations. In the absence of data to the contrary, the typical approach is to use the most relevant endp oint 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 extrapola tion. Size

- related differences (allometric relationships) indicate that typically humans are more sensitive than rodents when compared on a mg/kg/day basis. The default choice of 10 for the interspecies UF is consistent with these differences. For a s pe cific chemical, differences in species responses may be greater or less than this value

.

Pharmacokinetic models are useful to examine species differences in pharmacokinetic processing and associated uncertainties; however, such dosimetric adjustments are not always possible. Information may not be available to quantitatively assess toxicokinetic or toxicodynamic differences between animals and humans, and in many cases a 10

- fold UF (with separate factors of 3 for toxicokinetic and toxicodynamic components ) is used to account for expected species differences and associated uncertainty in extrapolating from laboratory animals to humans in the derivation of a reference value. If information on one or the other of these components is available and accounted f or 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 s uch 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 e xposure 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 r equires adequate quantitative results for a meaningful analysis, which is not always possible. Use of a NOAEL is the next preferred approach after BMD analysis in determining a POD for deriving a health effect reference value. However, many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3

- fold is often applied.Draft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 57

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

- fold is typically applied.

There is no RfD or other compar able chronic health benchmark value for lead compounds. Thus, to address multipathway human health and environmental risks associated with emissions of lead from this facility, ambient lead concentrations were compared to the NAAQS for lead. In developin g the NAAQS for lead, EPA considered human health evidence reporting adverse health effects associated with lead exposure, as well as an EPA conducted multipathway risk assessment that applied models to estimate human exposures to
air

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

- or risk

- based bright line that indicates a single appropriate level. Instead, he noted, there is a collection of scientific evidence and judgments and other information, including information about the uncertainties inherent in many relevant factors, which needs to be considered together in making this public health policy judgment and in selecting a standard level from a range of reasonable values (73FR at 66998). In so doing, the Administrat or 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, including the health of sensitive groups, with an adequate margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and exposure analyses, and their associated uncertainties can be found in EPA’s final rule revising the lead NAAQS (73 FR 66970

- 66981, November 12, 2008).

We also note the un certainties 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 obta ined through
decades of medical observation and scientific research. This information has been assessed in the development of air and water quality criteria by the Agency's Office of Health and Environmental Assessment (OHEA) in support of regulatory decis ion

- making by the Office of Air Quality Planning and Standards (OAQPS) and by the Office of Drinking Water (ODW). By comparison to most other environmental toxicants, the degree of uncertainty about the health effects of lead is quite low. It appears that some of these effects, particularly changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral development, may occur at blood lead levels so low as to be essentially without a threshold. The Agency's RfD Work Group discuss ed inorganic lead (and lead compounds) at two meetings (07/08/1985 and 07/22/1985) and considered it inappropriate to develop an RfD forDraft Risk Assessment for the Petroleum Refining Source Sector

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FOR PUBLIC COMMENT, DO NOT CITE OR QUOTE 58

inorganic lead.” EPA’s IRIS assessment for Lead and compounds (inorganic) (CASRN 7439

- 92

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

.

We note further that because of the multi

- pathway, multi

- media impacts of lead, the risk assessment supporting the NAAQS considered direct inhalation exposures and indirect 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 drinking water and exposure to lead

- based paints). In revising the NA AQS 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 e vidence

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

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

Acute noncancer assessment

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

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### 5 References

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

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

.

2 . US EPA, 2009. Risk and Technology Review (RTR) Risk Assessment Methodologies: For Review by the EPA’s Science Advisory Board with Case Studies

– MA CT I Petroleum Refining Sources and Portland Cement Manufacturing

. EPA

- 452/R

- 09

- 006. http://www.epa.gov/ttn/atw/rrisk/rtrpg.html.

3 . US EPA, 2010. SAB’s Response to EPA’s RTR Risk Assessment Methodologies. http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/E
PA

- SAB

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4 . US EPA, 2010. Memorandum from Dave Guinnup to Docket EPA

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- 09/a21627.htm

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– AERMOD. EPA

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03

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. http://www.epa.gov/scram001/7thconf/aermod/aermodugb.pdf

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10

. US EPA, 2012. Table 1. Prioritized Chronic Dose

- Response Values (5/21/12). Office of Air Quality Planning and Standards. http://www.epa.gov/ttn/atw/toxsource/table1.pdf

11 . US EPA, 2005. 1999 National Air Toxics Risk Assessment. http://www.epa.gov/ttn/atw/nata1999

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. US Environmental Protection Agency. Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation Dosimetry.
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.

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.

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- Specific Health Effect Reference Values for Inhalation Exposures [Final Report]. EPA/600/R

- 09/061, 2009. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003

26 U.S. EPA. Mn and BTEX Reference Value Arrays (Final Reports). U.S. EnvironmentalDraft Risk Assessment for the Petroleum Refining Source Sector

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Protection Agency, Washington, DC, EPA/600/R

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involved/AIHAGuidelineFoundation/EmergencyResponsePlanningGuidelines/Pages/default.aspx )

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.

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