## Residual Risk Assessment for 7 Source Categories: Printing and Publishing Marine Tank Vessel Loading Operations
Pharmaceuticals Production Epichlorohydrin Elastomers Polybutadiene Rubber Styrene Butadiene
Nitrile Butadiene

by EPA’s Office of Air Qualit y Planning and Standards
Office of Air and Radiation January 20112



### Table of Contents

1 Introduction .................................................................................................................. ........... 5

2 Methods........................................................................................................................ ........... 6
2.1 Emissions and source data ................................................................................................ 6

2.2 Dispersion modeling for inhala tion exposure assessment ................................................ 6

2.3 Estimating human inhalation exposure ............................................................................ 9

2.4 Acute risk screening and refined assessments ................................................................ 10

2.5 Multipathway and environmen tal risk screening ........................................................... 11

2.6 Dose-response assessment.............................................................................................. 12
2.6.1 Sources of chronic dose-response information ....................................................... 12

2.6.2 Sources of acute dose-response information ........................................................... 21

2.7 Risk characterization ...................................................................................................... 26

2.7.1 General .................................................................................................................... 26

2.7.2 Mixtures .................................................................................................................. 27

2.7.3 Facility-wide risks ................................................................................................... 28

3 Results summaries and risk characteri zations for the 7 source categories ........................... 28

3.1 Printing and publishing .................................................................................................. 29

3.1.1 Source category descrip tion and results .................................................................. 29

3.1.2 Risk characterization ............................................................................................... 35

3.2 Marine tank vessel loading ............................................................................................. 37

3.2.1 Source category descrip tion and results .................................................................. 37

3.2.2 Risk characterization ............................................................................................... 42

3.3 Pharmaceuticals production ........................................................................................... 43

3.3.1 Source category descrip tion and results .................................................................. 43

3.3.1 Risk characterization ............................................................................................... 47

3.4 Epichlorohydrin elastomers production ......................................................................... 51

3.4.1 Source category descrip tion and results .................................................................. 51

3.4.2 Risk characterization ............................................................................................... 52

3.5 Polybutadiene rubber production ................................................................................... 55

3.5.1 Source category descrip tion and results .................................................................. 55

3.5.2 Risk characterization ............................................................................................... 56

3.6 Styrene butadiene rubber and latex production .............................................................. 59

3.6.1 Source category descrip tion and results .................................................................. 59

3.6.2 Risk characterization ............................................................................................... 61

3.7 Nitrile butadiene r ubber production ............................................................................... 63

3.7.1 Source category descrip tion and results .................................................................. 63

3.7.2 Risk characterization ............................................................................................... 64

4 General discussion of uncertainties a nd how they have been addressed .............................. 66

4.1 Exposure modeling uncertainties ................................................................................... 66

4.2 Uncertainties in the dose -response relationships ........................................................... 67

5 References .................................................................................................................... ......... 753

Index of Tables

Table 2.2-1 AERMOD version 09292 model options for RTR II modeling ................................. 7 Table 2.6-1.A Dose-Response Values for Chr onic Inhalation Exposure to Carcinogens ........... 17 Table 2.6-2.A Dose-Response Values for Chroni c Inhalation Exposure to Noncarcinogens ..... 19 Table 2.6-2.B Dose-Response Values for Chr onic Oral Exposure to Noncarcinogens ............... 21 Table 3.1-1 Summary of Emissions and Availability of Dose-Response Values for the Printing and Publishing Source Category ................................................................................................ ... 31 Table 3.1-2 Summary of Sour ce Category Level Risks for Printing and Publishing .................. 33 Table 3.1-3 Summary of Ac ute Refined Results for Printing and Publishing ............................. 34 Table 3.1-4 Source Category Contribution to Facility-Wide Cancer Risks – Printing and Publishing .................................................................................................................... ................. 36 Table 3.2-1 Summary of Emissions and Availability of Dose-Response Values for the Marine Tank Vessel Loading Operations Source Category ...................................................................... 39 Table 3.2-2 Summary of Sour ce Category Level Risks for Marine Tank Vessel Loading Operations .................................................................................................................... ................. 41 Table 3.2-3 Source Category Contribution to Faci lity-Wide Cancer Risks – Marine Tank Vessel

............................................................................................................................... ........................ 42 Table 3.3-1 Summary of Emi ssions and Availability of Dose-Response Values for the Pharmaceuticals Production Source Category .............................................................................. 45 Table 3.3-2 Summary of Source Categor y Level Risks for Pharmaceuticals .............................. 48 Table 3.3-3 Summary of Ac ute Refined Results for Pharmaceuticals Production ...................... 50 Table 3.3-4 Summary Category Contribution to Facility-W ide Cancer Risks - Pharmaceuticals

............................................................................................................................... ........................ 51 Table 3.4-1 Summary of Emi ssions and Availability of Dose-Response Values for the Epichlorohydrin Elastomers Production Source Category ........................................................... 52 Table 3.4-2 Summary of Sour ce Category Level Risks for Epichlorohydrin Elastomers
Production .................................................................................................................... ................. 54 Table 3.4-3 Source Category Contribution to Faci lity-Wide Cancer Risks - Epichlorohydrin ... 55 Table 3.5-1 Summary of Emi ssions and Availability of Dose-Response Values for the Polybutadiene Rubber Source Category ....................................................................................... 56 Table 3.5-2 Summary of Source Category Level Risks for Pol ybutadiene Rubber Production .. 58 Table 3.5-2 Source Category Contribution to Faci lity-Wide Cancer Risks - Polybutadiene ...... 59 Table 3.6-1 Summary of Emissions and Availa bility of Dose-Response Values for Styrene
Butadiene Rubber and Latex Production ...................................................................................... 60 Table 3.6-2 Summary of Source Category Level Risks for Styrene Butadiene – Rubber and
Latex Production .............................................................................................................. ............. 62 Table 3.6-2 Source Category Contribution to Facility-Wide Cancer Risks - Styrene ................. 63 Table 3.7-1 Summary of Emissions and Availa bility of Dose-Response Values for Nitrile
Butadiene Rubber Production ................................................................................................... .... 64 Table 3.7-2 Summary of Source Category Level Risks for Nitr ile Butadiene Rubber Production

............................................................................................................................... ........................ 65 Table 3.7-2 Source Category Contribution to Facil ity-Wide Cancer Risks – Nitrile Butadiene . 664

Appendices

Appendix 1 Emissions Inventory Support Memorandums Appendix 2 Technical Support Docu ment for HEM-AERMOD Modeling Appendix 3 Meteorological Da ta for HEM-AERMOD Modeling Appendix 4 Analysis of data on short-term emi ssion rates relative to long-term emission rates Appendix 5 TRIM-Based Multipathway Screening Scenario Appendix 6 Detailed Risk Modeling Results Appendix 7 Acute Impacts Re fined Analysis Figures

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model AEGL Acute exposure guideline level ASTDR US Agency for Toxic Substances and Disease Registry CalEPA California Environmental Agency ERPG Emergency Response Planning Guideline
HAP Hazardous Air Pollutant HEM Human Exposure Model
HI Hazard index HQ Hazard quotient IRIS Integrated Risk Information System MACT Maximum Achievable Control Technology
MOA Mode of action
NATA National Air Toxics Assessment NEI National Emissions Inventory POM Polycyclic organic matter REL Reference exposure level
RfC Reference concentration
RfD Reference dose TOSHI Target-organ-specific hazard index
URE Unit risk estimate5



### 1 Introduction

Section 112 of the Clean Air Act (CAA) establ ishes a two-stage regu latory process for addressing emissions of hazardous air pollutants ( HAPs) from stationary sources. In the first stage, section 112(d)(2) requires the Environmental Protection Agency (EPA, or the Agency) to develop technology-based standa rds for categories of industr ial sources (e.g., petroleum refineries, pulp and paper mills, etc.) [ 1 ]. EPA has largely completed the initial Maximum Achievable Control Technology (MACT) standa rds as required under this provision. Under section 112(d)(6), EPA must review each of thes e technology-based standards at least every eight years and revise a standar d, as necessary, “taki ng into account developments in practices, processes and control technologi es.” In the second stage, EPA is required under section 112(f)(2) to assess the health and environmental risks that remain after implementation of the
MACT standards. If additional risk reductions ar e necessary to protect public health with an ample margin of safety or to prevent an a dverse environmental effect, EPA must develop standards to address these remaining risks. Th is second stage of the re gulatory process is known as the residual risk stage. For each source ca tegory for which EPA issued MACT standards, the residual risk stage must be completed within eight years of promulgation of the initial technology-based standard.

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board (SAB) on the “Risk and Technology Review (RTR) Assessm ent Plan” and in June of 2007, we received
a letter with the results of that consultation. Subsequent to th e consultation, in July of 2009, a meeting was held with an SAB panel for a formal peer review of the “Risk and Technology Review (RTR) Assessm ent Methodologies” [ 2 ]. We received the final SAB report on this review in May of 2010 [ 3 ]. Where appropriate, we have re sponded to the key messages from this review in developing our current risk asse ssments and we will be continuing our efforts to improve our assessments by incorporating updates based on the SAB recommendations as they are developed and become available. Our respons es to the key recommendations of the SAB are
outlined in a memo entitled “EPA’s Actions in Response to Key Recommendations of the SAB
Review of RTR Risk A ssessment Methodologies” [ 4 ].

This document contains the methods and the result s of baseline risk assessments (i.e., after the implementation of the respective MACT standard ) performed for 7 source categories. The 7 source categories are:

Printing and Publishing Marine Tank Vessel Loading
Pharmaceuticals Production Epichlorohydrin Elastomers Polybutadiene Rubber Styrene Butadiene
Nitrile Butadiene6

The methods discussion includes de scriptions of the methods used to develop refined estimates of chronic inhalation exposures and human hea lth risks for both cancer and noncancer endpoints, as well as descriptions of the methods used to screen for acute hea lth risks, chronic noninhalation health risks, and adverse environmental effect s. Since none of the screening assessments indicated any significant potential fo r chronic non-inhalation health effects, or environmental impacts including effects to th reatened and endangered species, no further refinement of these assessments was performed. Screening assessments indicated a concern for
acute health effects for all 5 of the source categories. Thus, a more refined analysis for acute exposure impacts for 5 source categories was performed.



### 2 Methods

2.1 Emissions and source data
Data from the 2005 National Emissions Inventory (NEI) which were used and published as part of the 2005 National-Scale Air Toxics Assessment ( NATA) served as the st arting point for this
assessment. The 2005 NEI contains information on actual emissions during the entire 2005 base year. Using the process MACT code 1 , we developed a subset of th is inventory that contains emissions and facility data for each of the 3 s ource categories addressed. Next, we performed an engineering review of the information using EP A engineers who were directly involved in the development of the MACT standards for these 7 source categories, and/or who have extensive knowledge of the characteristics of these indus tries. NEI data was updated with industry supplied data as available. The goal of the e ngineering review was to identify readily-apparent limitations and issues with the emissions data (p articularly those that would greatly influence risk estimates) and to make changes to the data set where possible to address these issues and
decrease the uncertainties associated with the assessment.

Details on the development of the emissions a nd source data for thes e source categories are
discussed in Section 3. The emissions data and modifications made to the NEI data are discussed in the Appendix 1, entitled “Emi ssions Inventory Support Memorandums.”



### 2.2 Dispersion modeling for in halation exposure assessment
Both long- and short-term inhalation exposure co ncentrations and associated health risk from each facility in each of the s ource categories of interest we re estimated using the Human Exposure Model in combination with the Amer ican Meteorological So ciety/EPA Regulatory Model dispersion modeling system (HEM-AERMOD) . The approach used in applying this modeling system is outlined below, and furt her details are provided in Appendix 2. HEMAERMOD performs three main operations: at mospheric dispersion modeling, estimation of individual human exposures and health risks, an d 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.

1 The tagging of data with MACT codes allows EPA to de termine reductions attributable to the MACT program. The NEI associates MACT codes corresponding to MACT source categories with stationary major and area source data. MACT codes may be assigned either at the process level or at the site level in the point source data (e.g., the MACT code for municipal waste combustors (MWCs) is assigned at the site level whereas the MACT code for petroleum refinery catalytic cracking is assigned at the process level).7

The dispersion model in the HEM-AERMOD sy stem, AERMOD version 09292, is a state-ofthe-science Gaussian plume disp ersion model that is preferred by EPA for modeling point, area,
and volume sources of continuous air em issions from facility applications [ 5 ]. Further details on AERMOD can be found in the AERMOD Users Guide [ 6 ]. The model is used to develop annual average ambient concentration through the si mulation of hour-by-hour dispersion from the
emission sources into the surr ounding atmosphere. Hourly em ission rates used for this simulation are generated by evenly dividing the to tal annual emission rate from the inventory into the 8,760 hours of the year.

The first step in the application of the HEM-AERMOD modeling system is to predict ambient
concentrations at locations of interest. The AERMOD model op tions employed are summarized
in Table 2.2-1 and are discussed further below.

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

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point, area represented as pseudo point source

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

Terrain characterization Actual from USGS 1-degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option No

Meteorology 1 year representative NW S from nearest site (158 stations)

In HEM-AERMOD, meteorological data are ordinarily select ed from a list of 158 National Weather Service (NWS) surface observation stat ions across the continental United States, Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is se lected as representative of the conditions at the subject facility. Ideally, when consider ing off-site meteorological data most site specific dispersion modeling efforts will employ up to five years of data to capture variability in weather patterns fr om year to year. However, because we had insufficient number of appropriately formatted model input files de rived from available meteorological data, we modeled only a single year, typical ly 1991. While the selection of a single year may result in under-prediction of long-term ambient levels at some locations, likewis e it may result in overprediction at others. For each f acility identified by its charac teristic latitude and longitude coordinates, the closest meteorol ogical station was used in the dispersion modeling. The average distance between a modeled facility and the appl icable meteorological station was 40 miles (72 km). Appendix 3 (Meteorological Data Processing Using AERMET for HEM-AERMOD) provides a complete listing of stations and assumptions along with further details used in processing the data through AERMET. The sensitivity of model results to the selection of the8

nearest weather station a nd the use of one year of meteorologi cal data is discussed in “Risk and Technology Review (RTR) Risk Assessment Methodologies” [ 2 ].

The HEM-AERMOD system estimates ambient con centrations at the ge ographic centroids of census blocks (using the 2000 Census), and at othe r receptor locations that can be specified by
the user. The model accounts for the effects of multiple facilities when estimating concentration impacts at each block centroid. Typically we co mbined only the impacts of facilities within the same source category, and assessed chronic exposure and risk only for census blocks with at least one resident (i.e., locations where people may reasonably be assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient con centrations were calculated as the annual average of all estimated short-term (one -hour) concentrations at each block centroid. Possible future residential use of currently uninh abited areas was not consid ered. Census blocks,
the finest resolution available in the census data, are typically comprised of approximately 40 people or about ten households.

In contrast to the developmen t of ambient concentrations fo r evaluating long-term exposures, which was performed only for occupied censu s blocks, worst-case short-term (one-hour)
concentrations were estimated both at the census bl ock centroids and at poin ts nearer the facility that represent locations where people may be pr esent for short periods, but generally no nearer than 100 meters from the center of the facility (n ote that for large facilities, this 100-meter ring
could still contain locations inside the facility property). Sinc e short-term emission rates were needed to screen for the potential for hazard via acute exposures, and since the NEI contains only annual emission totals, we applied the general assumption to all source categories that the maximum one-hour emission rate from any sour ce was ten times the average annual hourly
emission rate for that source.

The average hourly emissions rate is defined as the total emissions for a year divided by the total number of operating hours in the year. This choi ce of a factor of ten for screening was originally based on engineering judgment. To develop a mo re robust peak-to-mean emissions factor, and in response to one of the key messages from the SAB consultation on our RTR Assessment Plan, we performed an analysis using a short-term emi ssions dataset from a number of sources located in Texas (originally reported on by Allen et al. 2004)[ 7]. In that report, the Texas Environmental Research Consortium Project compared hourly a nd annual emissions data for volatile organic compounds for all facilities in a heavily-industr ialized 4-county area (Harris, Galveston, Chambers, and Brazoria Counties, TX) over an eleven-month time period in 2001. We obtained the dataset and performed our own analysis, fo cusing that analysis on sources which reported emitting high quantities of HAP over short period s of time (see Appendix 4, “Analysis of data on
short-term emission rates relativ e to long-term emission rates”). Most peak emission events
were less than twice the annual av erage, the highest was a factor of 74 times the annual average,
and the 99 th percentile ratio of peak h ourly emission rate to the a nnual hourly emission rate was 9. Based on these results, we chose the factor of ten for all initial screening; it is intended to cover routinely-variab le emissions as well as start up, shutdown, and malfunction (SSM)
emissions. While there are some documented emissi on excursions above this level, our analysis
of the data from the Texas Environmental Resear ch Consortium suggests that this factor should cover more than 99% of the short-term peak gaseous or volatile HAP emissions from typical
industrial sources.9

Census block elevations for HEM-AERMOD modeling were determ ined nationally from the US Geological Service 1-degree digita l elevation model (DEM) data files, which have a spatial resolution of about 90 meters. Elevations of polargrid points used in estimating short- and longterm ambient concentrations were assumed to be equal to the highest elevation of any census block falling within the polar grid sector corres ponding to the grid point. If a sector does not contain any blocks, the model defa ults to the elevation to that of the nearest block. If the elevation is not provided for th e emission source, the model takes the average elevation of all sectors of the nearest model ring.

In addition to using receptor elevation to dete rmine plume height, AERMOD adjusts the plume’s flow if nearby elevated hills are expected to influence the wind pa tterns. For details on how hill heights were estimated and used in th e AERMOD modeling see Appendix 2.



### 2.3 Estimating human inhalation exposure

We used the annual average ambient air concentration of each HAP at each census block centroid as a surrogate for the lifetime inhalati on exposure concentration of all the people who
reside in the census block. That is, this risk analysis did not c onsider either the short-term or long-term behavior (mobility) of the exposed populations and its poten tial influence on their

exposure.

We did not address short-term human activity for two reasons. First, our experience with the 1996, 1999, 2002, and 2005 NATA assessments (which modeled daily activity using EPA’s HAPEM model ) suggests that, given our cu rrent understanding of microenvironment concentrations and daily activit ies, modeling short-term activity would, on average, reduce risk estimates about 25% for particul ate HAPs; it will also reduce ri sk estimates for gaseous HAPs, but typically by much less. Second, basi ng exposure estimates on average ambient
concentrations at census block centroids may underestimate or overestimate actual exposure
concentrations at some residences. Further reducing exposure estimates for the most highlyexposed residents by modeling their short-term beha vior could add a systematic low bias to these
results.

We did not address long-term mi gration nor population growth or decrease over 70 years, instead basing the assessment on the assumption that each person’s predicted exposur e is constant over
the course of their lifetime which is assumed to be 70 years. In assessing cancer risk, we generally estimated three metrics; the maximum individual risk (MIR) which is defined as the risk associated with a lifetime of exposure at the highest concentr ation, the population risk distribution, and the cancer incidence. This a ssumption of not consider ing short or long-term population mobility does not bias the estimate of the theoretical MIR nor does it affect the
estimate of cancer incidence si nce the total population number re mains the same. It does, however, affect the shape of th e distribution of individual risk s across the affected population, shifting it toward higher estimat ed individual risks at the upper end and reducing the number of people estimated to be at lower risks, thereby biasing the risk estimates high.10

When screening for potentially significant acute exposures, we used an estimate of the highest hourly ambient concentration at any off-site lo cation as the surrogate for the maximum potential acute exposure concentration for any individual.



### 2.4 Acute risk screening and refined assessments

In establishing a scientifically defensible approa ch for the assessment of potential health risks due to acute exposures to HAP, we followed the same general appr oach that has been used for developing chronic health risk assessments under the residual risk program. That is, we developed a tiered, iterative approach. This a pproach to risk assessment was endorsed by the National Academy of Sciences in its 1993 pub lication “Science and Judgment in Risk Assessment” and subsequently was adopted in th e EPA’s “Residual Risk Report to Congress” in

1999.

The assessment methodology is designed to eliminat e from further consider ation those facilities
for which we have confidence that no acute advers e health effects of concern will occur. To do so, we use what is called a tiere d, iterative approach to the asse ssment. This means that we began with a screening assessment, which relies on readily available data and uses conservative assumptions that in combination approximate a wors t-case exposure. The re sult of this screening process is that either the facility being assesse d poses no acute health risks (i.e., it “screens out”), or that it requires further, more refined assessm ent. A refined assessment could use industry- or site-specific data on the temporal pattern of emissions, the layout of emission points at the facility, the boundaries of the fac ility, and/or the local meteorology. In some cases, all of these site-specific data would be need ed to refine the assessment; in others, lesser amounts of sitespecific data could be used to determine that acute exposures are not a concern, and significant additional data collection would not be necessary.

Acute health risk screening was performed as the first step. We used conservative assumptions for emission rates, meteorology, and exposure location. We used the following worst-case assumptions in our screening approach:

• Peak 1-hour emissions were assumed to equa l 10 times the average 1-hour emission rates.

• For facilities with multiple emission points, peak 1-hour emissions were assumed to occur at all emission points at the same time.

• For facilities with multiple emission points, 1- hour concentrations at each receptor were
assumed to be the sum of the maximum c oncentrations due to each emission point, regardless of whether those maximum concen trations occurred dur ing the same hour.

• Worst-case meteorology (from one year of lo cal meteorology) was assumed to occur at the same time the peak emission rates o ccur. The recommended EPA local-scale dispersion model, AERMOD, is used for simulating atmospheric dispersion.

• A person was assumed to be located downwind at the point of maximum impact during this same 1-hour period, but no near er to the source than 100 meters.

• The maximum impact was compared to multiple short-term health benchmarks for the chemical being assessed to determine if a possi ble acute health risk might exist. These
benchmarks are described in section 2.6 of this report.11

As mentioned above, when we identify acute imp acts which exceed their relevant benchmarks, we pursue refining our acute screen ing estimates. In some cases, this includes use of a refined emissions multiplier to estimate the peak hourly em ission rates from the average rates. For the source categories in the document, we conducted a review of the layout of emission points at the facilities with the facility bounda ries to determine the maximum off-site acute impact for the
facilities that did not screen out during the initial model run. Refer to Appendix 7 for the
detailed results for these sites.



### 2.5 Multipathway and environmental risk screening

The potential for significant human health risks due to exposures via routes other than inhalation (i.e., multipathway exposures) or adverse environmental impacts were screened by first determining whether any sources emitted any hazardous air pollutants known to be persistent and bioaccumulative in the environment (PB-HAP). The PB-HAP compounds or compound classes are identified for the screening from the EP A’s Air Toxics Risk Assessment Library [ 8 ]. Examples of PB-HAP are cadmium compounds, chlordane, chlorinate d dibenzodioxins and furans, DDE, heptachlor, hexach lorobenzene, hexachlorocyclohe xane, lead compounds, mercury compounds, methoxychlor, polychlor inated biphenyls, polycyclic organic matter (POM), toxaphene, and trifluralin. Emi ssions of POM, lead, cadmium, and mercury were identified in the emissions inventory for the source cat egories included in this document.

These emissions were evaluated for potential non-inhalation risks and adverse environmental impacts using our recently-devel oped screening scenario which was developed for use with the

TRIM.FaTE 2 model. This screening s cenario uses environmental media outputs from the peerreviewed TRIM.FaTE to estimate the maximum potential ingestion risks for any specified emission scenario by using a generic farming/ fishing exposure scenario that simulates a subsistence environment. The screening scenar io retains many of the ingestion and scenario inputs developed for EPA’s Human Health Risk Assessment Protocols (HHRAP) for hazardous
waste combustion facilities. 3 In the development of the screen ing scenario a sensitivity analysis
was conducted to ensure that its key design parameters were estab lished such that environmental media concentrations were not underestimated, and to also minimize th e occurrence of false positives for human health endpoints. See A ppendix 5 for a complete discussion of the development and testing of the screening scenario, as well as for the values of facility-level de

minimis emission rates developed for screening pote ntially significant multi-pathway impacts. For the purpose of developing de minimis emission rates for our multi-pathway screening, we
derived emission levels for each PB HAP at whic h the maximum human health risk would be 1
in a million for lifetime cancer ri sk or a hazard quotient of 1.0 for noncancer impacts. In evaluating the potential multi-pathway risks from emissions of lead compounds, rather than developing a de minimis emission rate, we compared maximum estimated chronic (3-month average) atmospheric concentrations with the current National Ambient Air Quality Standard (NAAQS) for lead. Values below the NAAQS were considered to have a low potential for multi-pathway risks of any significance.

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

3 EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous Waste Combustion Facilities; http://www.epa.gov/epaoswer/hazwa ste/combust/riskvol.htm#volume112

In all instances, modeling of emissions of cad mium, mercury, and POM associated with the 7 source categories using our screening scenar io indicated that human exposures via noninhalation pathways were well below levels of c oncern for cancer risk or noncancer hazard. For the purposes of this screening assessment, th e levels of concern below which risks were considered insignificant were 1 in a million for lifetime cancer risk and a hazard quotient of 1.0 for noncancer impacts. In evaluating emissions of lead compounds, since an ingestion reference
dose has not been established for chronic noncan cer effects, we comp ared maximum chronic atmospheric concentrations with the current National Ambient Air Quality Standard (NAAQS) for lead (0.15 ug/m3) and noted that all impact s are well below this value, allowing us to conclude that potential multipathway risks fr om lead compounds are insignificant.

Additionally, we evaluated the potential for significan t ecological exposures to non PB-HAP
from exceedances of chronic human health inhala tion thresholds in the ambient air near these
facilities. Human health dose -response threshold values are generally derived from studies conducted on laboratory animals (such as rodent s) and developed with the inclusions of uncertainty factors that could be as high as 3000. As a result, these human threshold values are often significantly lower than the level expected to cause an adverse effect in an exposed rodent.
It should be noted that there is a scarcity of data on the direct atmospheric impact of these HAPs on other receptors, such as plants, birds, and wild life. Thus, if the maximum inhalation hazard in an ecosystem is below the level of concern fo r humans, we have generally concluded that mammalian receptors should be at no risk of ad verse effects due to inhalation exposures from non PB-HAP, and have assured that other ecological receptors are also not at any significant risk from direct atmospheric impact. In some isolat ed cases where we have data indicating potential adverse impacts on plants, birds, or other wild life due to the direct atmospheric impacts of specific HAPs, we note that as an uncertainty and, where possible, re fine our analysis by comparing our modeled impacts to available thre shold values from the scientific literature.



### 2.6 Dose-response assessment

2.6.1 Sources of chronic do se-response information
Dose-response assessment information (carcinog enic and non-carcinogenic) for chronic exposure (either by inhalation or ingestio n) for the HAPs reported in the emissions inventory were based on the EPA Office of Air Quality Planning and Standards’ existing recommendations for HAPs [ 9 ], also used for NATA 1999, 2002, and 2005 [ 10 ]. This information has been obtained from various sources and prioritized according to (1) conceptual consistency with EPA risk assessment guidelines and (2) level of peer re view received. The prioritization process was aimed at incorporating into our assessments th e best available science with respect to doseresponse information. The recommendations ar e 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 th e pollutants in this risk assessment. These assessments typically provide a qualitative statem ent regarding the strength of scientific data and specify a reference concentration (RfC, fo r inhalation) or reference dose (RfD, for ingestion) to protect against e ffects other than cancer and/or a unit risk estimate (URE, for13

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 exposur e to the human population (including sensitive subgroups) that is likely to be without an appr eciable risk of deleterious effects during a lifetime”. The RfD is “an estimate (with un certainty spanning perhaps an order of magnitude) of a daily oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable ri sk of deleterious effect s during a lifetime.” The URE is defined as “the upper-bound excess cancer risk estimate d to result from continuous lifetime exposure to an agent at a concentration of 1 μg/m 3 in air.” The SF is “an upper bound, approximating a 95% confidence limit, on th e increased cancer risk from a lifetime exposure to an agent. This estimate, [is] us ually expressed in units of proportion (of a population) affected per mg/kg-day...” EPA disseminates dose-response assessment information in several forms, based on the level of review. The Integrated Risk Information System (IRIS) [ 11 ] is an EPA database that contains sc ientific health asse ssment information, including dose-response informa tion. All IRIS assessments since 1996 have also undergone independent external peer review. The cu rrent IRIS process includes review by EPA scientists, interagency reviewer s from other federal agencies, and the public, and peer review by independent scientists extern al to EPA. New IRIS values are developed and old IRIS values are updated as new health effects data become available. Refer to the “IRIS Track”
website for detailed information on status and scheduling of current individual IRIS assessments and updates ( http://cfpub.epa.gov/n cea/iristrac/index.cfm ). EPA’s science policy approach, under the current carci nogen guidelines, is to use lin ear low-dose extrapolation as a default option for carcinogens for which the m ode of action (MOA) has not been identified. We expect future EPA dose-response assessm ents to identify nonlinear MOAs where appropriate, and we will use those analyses ( once they are peer reviewed) in our risk assessments. At this time, however, ther e are no available carc inogen dose-response assessments for inhalation exposure that are based on a nonlinear MOA

.

2) US Agency for Toxic Substances and Disease Registry (ATSDR). ATSDR, which is part of the US Department of Health and Human Se rvices, develops and publishes Minimum Risk Levels (MRLs) [ 12 ] for inhalation and oral exposure to many toxic substances. As stated on the ATSDR web site: “Following discussions with scientists within the Department of Health and Human Services (HHS) and th e EPA, ATSDR chose to adopt a practice similar to that of the EPA's Reference Dose (RfD) and Referen ce Concentration (RfC) for deriving substance specific health guidance levels for non neoplas tic endpoints.” The MR L is defined as “an estimate of daily human exposure to a substance th at is likely to be without an appreciable risk of adverse effects (other than cancer) ov er a specified duration of exposure”. ATSDR describes MRLs as substance-specific estimates to be used by health assessors to select
environmental contaminants for further ev aluation. Exposures above an MRL do not necessarily represent a threat, and MRLs are th erefore 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 ha s developed dose-response assessments for many substances, based both on carcinogenicity a nd health effects other than cancer. The process for developing these assessments is si milar to that used by EPA to develop IRIS14

values and incorporates significan t external scientific peer review. As cited in the CalEPA Technical Support Document for de veloping their chronic assessments 4 : “The guidelines for developing chronic inhalation exposure levels incorporate many recommendations of the U.S. EPA [ 13 ] and NAS [ 14 ].” The non-cancer information includes available inhalation health risk guidance values expressed as chr onic inhalation reference exposure levels (RELs) [ 15 ]. CalEPA defines the REL as “the concen tration level at or below which no adverse
health effects are antic ipated in the general human populat ion.” CalEPA's quantitative doseresponse information on carcinogenicity by inhala tion exposure is expressed in terms of the URE [ 16 ], defined similarly to EPA's URE.

In developing chronic risk estimates, we adjust ed dose-response values for some HAPs based on professional judgment, as follows:

1) In the case of HAP categories such as glyc ol ethers and cyanide compounds, the most conservative dose-response value of the chemical category is used as a surrogate for other compounds in the group for which dose-response values were not available. This is done in order to examine, under conservative assump tions, whether these HAPs that lack doseresponse values may pose an unacceptable risk and require further examination, or screen
from further assessment.

2) Where possible for emissions of unspecified mixtures of HAP categories such as metal compounds and POM, we applied category-specif ic chemical speciati on profiles appropriate to the source category to develop a composite dose-response value for the category.

3) In 2004, EPA determined that the CIIT dos e-response value for formaldehyde (5.5 x 10 -9 per

μ g/m 3 ) was based on better science than th e IRIS dose-response value (1.3 x 10 -5 per μ g/m 3 ), and we switched from using the IRIS value to the CIIT value in risk assessments supporting regulatory actions. This determination was based on a substantial body of research on the inhalation dosimetry for formaldehyde in rode nts and primates by the CIIT Centers for Health Research (formerly the CIIT), with a focu s on use of rodent data for refinement of the quantitative cancer dose-response assessment [ 17

, 18

, 19 ]. The CIIT’s risk assessment of formaldehyde incorporated mechanistic and dosimetric information on formaldehyde. However, recent research published by EPA i ndicates that, when the CIIT’s two-stage modeling assumptions are varied, resulting do se-response estimates can vary by several orders of magnitude [ 18, 19, 20, 20 ]. These findings are not su pportive of interpreting the CIIT model results as providing a conservative (health-protective) estimate of human risk [ 21 ]. The recent EPA research also examined the contribution of the two-stage modeling for formaldehyde towards characterizing the relative weights of key events in the mode-of-action of a carcinogen. For example, in the EPA research, the model-based inference in the published CIIT study that formaldehyde’s direct mutagenic action is not relevant to the compound’s tumorigenicity was found not to hol d under variations of modeling assumptions [ 22 ]. Additionally, in 2007, the California Envi ronmental Protection Agency considered a

4 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III - Technical Support Document
for the Determination of Noncancer Chronic Referen ce Exposure Levels. Air Toxicology and Epidemiology Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. February 2000 (http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf)15

petition to use the CIIT URE value rather than its 1992 cancer risk value of 6 X 10 -6 per ug/m 3 . After consideration and cons ultation with their Scientific Review Panel of Toxic Air Contaminants, they decided not to change from their 1992 value [ 23

, 24 ]. As a result of these findings, EPA no longer considers the CIIT URE value to be health protective, and we are again using the Agency’s current value on IRIS, which was last revised in 1991, and which is more than 2000 times greater than th e CIIT value. We not e that a new IRIS reassessment has been drafted and sent to the NAS for review. The NAS review is expected to be completed by March of 2011.

4) The IRIS URE for nickel inhalation was derive d from evidence of the carcinogenic effects of insoluble nickel compounds in crystalline form. Soluble nickel species, and insoluble species in amorphous form, do not appear to produce ge notoxic effects by the same toxic mode of action as insoluble crystalline nickel. Nickel speciation information for some of the largest nickel-emitting sources (including oil combustion, coal combustion, and others) suggests that
at least 35% of total nickel emissions may be soluble com pounds. The remaining insoluble
nickel emissions are not well-ch aracterized. Consistent with this limited information, this assessment will conservatively assume that 65% of emitted nickel is insoluble and that all insoluble nickel is crystalline. The ni ckel URE (based on nickel subsulfide, and representative of pure in soluble crystalline nickel) was adjust ed to reflect an assumption that 65% of the total mass of nickel may be carci nogenic. The noncancer dose-response values were not adjusted because noncan cer effects of nickel are not thought to be limited to the crystalline, insoluble form.

5) A substantial proportion of POM reported to EPA’s national em ission inventory (NEI) were not speciated into individual compounds. As a result, it was necessary to apply the same simplifying assumptions to this assessment that were used for the 1999 NATA study [ 25 ]. The NATA approach partitions POM into eight different non-overlapping “groups” that were modeled as separate pollutants. Each POM group comprises POM species of similar carcinogenic potency, for which we can apply the same URE.

6) 

### For 2 carcinogenic substances, (isophoron e and propylene dichloride) that lack
inhalation assessments from the sources eval uated in this document, oral carcinogenic potency estimates were converted to inhala tion UREs. The conversion from oral risk (per mg/kg/d oral intake) to inhalation risk (per μ g/m 3 

### inhaled) was based on EPA’s standard assumptions of a 70-kg body mass and 20 m 3 

### /d inhalation rate, as follows:

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

### ) CPS = Carcinogenic potency slope for ingestion (risk per mg oral intake per kg body mass per day) 

## ( ) ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

× ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

× × ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

⋅ = ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ −

−

g mg

d m kg d kg

mg CPS

m

g URE μ μ

1000 1 20 70 1 3 1 1

316



### EPA understands that conversion of oral dose-response information to inhalation exposure may add significant uncertainty to the resulting ri sk estimates. However, the
alternative to this would have been to omit these substances from quantitative
inhalation risk estimates a ltogether, thereby making a de facto assumption of zero carcinogenic potency. For the purposes of th e residual risk assessment, EPA prefers to use the approach described above to sc reen these carcinogen s for their potential
contributions to risk. If a substance is determined to be a potentially important contributor to risk, it will be prioritized for further dose-response development through EPA’s IRIS process.

The emissions inventories for the 7 source categori es include emissions of 85 HAP. Of these, 34 are classified as known, proba ble, or possible carcinogens, wi th quantitative cancer doseresponse values available. These 34 HAP, thei r quantitative inhalation chronic cancer doseresponse values, and the source of each value ar e listed in Table 2.6-1.A. The POM compounds with chronic oral cancer dose-response values available (for which multipathway screening assessments were performed) are listed in Table 2.6-1.B.

The emissions inventories for the 7 source ca tegories include emissions of 75 HAP with quantitative inhalation chronic noncancer thresh old values available; two of these HAP (cadmium and mercury), for which multipathway assessments were performed, also have quantitative oral chronic noncancer threshold values available. These 75 HAP, their threshold values, and the source of the value are lis ted in Table 2.6-2.A and Table 2.6-2.B.17

Table 2.6-1.A Dose-Response Values for Ch ronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) = cancer risk per μ g/m 3 of average lifetime exposure. Sources : IRIS = EPA Integrated Risk Information System, CAL = Ca lifornia EPA Office of Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards, Conv. Oral = Converted from an oral dose-response assessment.

Pollutant CAS
Number 5 URE (1/ μ g/m 3 ) Source
1,3-Butadiene 106990 3.0E-05 IRIS
1,4-Dioxane 123911 7.7E-06 CAL 2-Nitropropane 79469 5.6E-06 EPA OAQPS 2,4-Toluene diisocyanate 584849 1.1E-05 CAL Acetaldehyde 75070 2.2E-06 IRIS

Acetamide 60355 2.0E-05 CAL Acrylonitrile 107131 6.8E-05 IRIS Allyl chloride 107051 6.0E-06 CAL

Aniline 62533 1.6E-06 CAL Arsenic compounds 7440382 4.3E-03 IRIS

Benzene 6 71432 7.8E-06 IRIS Beryllium compounds 7440417 2.4E-03 IRIS Bis(2-ethylhexyl)phthalate 117817 2.4E-06 CAL Cadmium compounds 7440439 1.8E-03 IRIS

Carbon tetrachloride 56235 6.0E-6 IRIS Chromium (VI) compounds 18540299 1.2E-02 IRIS Epichlorohydrin 106898 1.2E-06 IRIS Ethyl benzene 100414 2.5E-06 CAL Ethylene dichloride 107062 2.6E-05 IRIS Ethylene oxide 75218 8.8E-05 CAL Formaldehyde 50000 1.3E-05 IRIS Hydrazine 302012 4.9E-03 IRIS Isophorone 78591 2.7E-07 Conv. Oral 7
Methyl tert-butyl ether 1634044 2.6E-07 CAL Methylene chloride 75092 4.7E-07 IRIS Naphthalene 91203 3.4E-05 CAL Nickel compounds 7440 020 1.6E-04 EPA OAQPS 8

p-Dichlorobenzene 106467 1.1E-05 CAL Polycyclic organic matter (POM) 246 11 EPA OAQPS 11
- Benzo(a)anthracene 56553 1.0E-04 EPA OAQPS 9

5 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have used a surrogate 3-digit identifier corresponding to the group’s position on the CAA list of HAPs.

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

. 7 No inhalation unit risk estimates were available for this compound. Therefore we converted from an IRIS oral potency slope of 0.00095 per mg/kg/d. UREs that are converted from the oral route to the inhalation route of exposure are considered highly uncertain, and are only used in cases where no other URE is available.

8 65% of the IRIS URE for nickel refinery dust, as explained above.18

Table 2.6-1.A Dose-Response Values for Ch ronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) = cancer risk per μ g/m 3 of average lifetime exposure. Sources : IRIS = EPA Integrated Risk Information System, CAL = Ca lifornia EPA Office of Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards, Conv. Oral = Converted from an oral dose-response assessment.

Pollutant CAS
Number 5 URE (1/ μ g/m 3 ) Source - Benzo(a)pyrene 50328 1.0E-03 EPA OAQPS 11
- Benzo(b)fluoranthene 205992 1.0E-04 EPA OAQPS 11
- Benzo(k)fluoranthene 207089 1.0E-04 EPA OAQPS 11
- Chrysene 218019 1.0E-05 EPA OAQPS 11
- Dibenz(a,h)anthracene 53703 1.0E-03 EPA OAQPS 11
- Indeno(1,2,3-cd)pyrene 193395 1.0E-04 EPA OAQPS 11
Propylene dichloride 78875 1.9E-05 Conv. Oral 10
Propylene oxide 75569 3.7E-06 IRIS Tetrachloroethylene 127184 5.9E-06 CAL Trichloroethylene 79016 2.0E-06 CAL Vinyl chloride 75014 8.8E-06 IRIS

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 lif etime exposure. Sources : IRIS = EPA Integrated Risk Information System, CAL = Ca lifornia EPA Office of Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality Planning and Standards.

Pollutant CAS
Number 11 SF (1/mg/kg/d) Source Polycyclic organic matter (POM) 12 246 0.5 EPA OAQPS - Benzo(a)anthracene 56553 1 EPA OAQPS - Benzo(a)pyrene 50328 10 EPA OAQPS - Benzo(b)fluoranth ene 205992 1 EPA OAQPS - Benzo(k)fluoranth ene 207089 1 EPA OAQPS - Chrysene 2180 19 0.1 EPA OAQPS - Dibenz(a,h)anthrac ene 53703 10 EPA OAQPS

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

9 Assigned the URE associated with a mixture of POM compounds having a similar potency. Details of this method,
also used in the 1999 National Air Toxics Assessment, are available at http://www.epa.gov/ttn/atw/nata19 99/99pdfs/pomapproachjan.pdf

10 No inhalation unit risk estimates were available for this compound. Therefore we converted from a oral potency slope of 0.068 per mg/kg/d. UREs that are converted from the oral route to the inhalation route of exposure are considered highly uncertain, an d are only used in cases where no other URE is available.

11 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have used a surrogate 3-digit identifier corresponding to the group’s position on the CAA list of HAPs.

12 Includes other unspeciated PO M emissions (e.g., total PAH).19

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 i nhalation 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 and Disease Registry.

Pollutant CAS
Number RfC (mg/m 3 ) Source 13

1,1,1-Trichloroethane 71556 5 IRIS 1,2-Epoxybutane 106887 0.02 IRIS -- M
1,2,4-Trichlorobenze ne 120821 0.2 HEAST
1,3-Butadiene 106990 0.002 IRIS -- M
1,4-Dioxane 123911 3.6 ATSDR 2-Nitropropane 79469 0.02 IRIS 2,4-Toluene diisocyanate 584849 0.00007 IRIS -- M Acetaldehyde 75070 0.009 IRIS -- L

Acetonitrile 75058 0.06 IRIS -- M

Acrolein 107028 0.00002 IRIS -- M Acrylic acid 79107 0.001 IRIS -- M Acrylonitrile 107131 0.002 IRIS -- M Allyl chloride 107051 0.001 IRIS -- L

Aniline 62533 0.001 IRIS Arsenic compounds 7440382 0.000015 CAL

Benzene 71432 0.03 IRIS -- M Beryllium compounds 7440417 0.00002 IRIS -- M Bis(2-ethylhexyl)phthalate 117817 0.01 CAL Cadmium compounds 7440439 0.00001 ATSDR

Carbon disulfide 75150 0.7 IRIS -- M

Carbon tetrachloride 56235 0.1 IRIS

Chlorine 7782505 0.00015 ATSDR

Chlorobenzene 108907 1 CAL

Chloroform 67663 0.098 ATSDR Chromium compounds 14 7440473 0.0001 - Chromium (VI) compounds 18540299 0.0001 IRIS -- M Cobalt compounds 7440484 0.0001 ATSDR Cresols (mixed) 1319773 0.6 CAL

Cumene 98828 0.4 IRIS -- M Cyanide compounds 15 57125 0.003 IRIS -- L

Diethanolamine 111422 0.003 CAL Dimethyl formamide 68122 0.03 IRIS -- M

13 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.

14 Chromium compounds are converted to Chromium (VI) compounds by source category specific ratio.

15 The value for hydrogen cyan ide used as a surrogate.20

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 i nhalation 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 and Disease Registry.

Pollutant CAS
Number RfC (mg/m 3 ) Source 13
Epichlorohydrin 106898 0.001 IRIS -- M Ethyl benzene 100414 1 IRIS -- L Ethylene dichloride 107062 2.4 ATSDR Ethylene glycol 107211 0.4 CAL Ethylene oxide 75218 0.03 CAL Formaldehyde 50000 0.0098 ATSDR Glycol ethers 18 171 0.02 IRIS -- M - 2-Butoxyethyl acetate 16 112072 0.02 IRIS -- M - Ethylene glycol ethy l ether 110805 0.2 IRIS -- M - Ethylene glycol methyl ether 109864 0.02 IRIS -- M - Diethylene glycol monobutyl ether 18 112345 0.02 IRIS -- M - n-Hexyl carbitol 18 112594 0.02 IRIS -- M Hydrazine 302012 0.0002 CAL Hydrochloric acid 7647010 0.02 IRIS -- L Hydrofluoric acid 7664393 0.014 CAL Hydrogen cyanide 74908 0.003 IRIS -- L Isophorone 78591 2 CAL Lead compounds 7439921 0.00015 EPA OAQPS Manganese compounds 7439965 0.00005 IRIS -- M Mercury (elemental) 7439976 0.0003 IRIS -- M

Methanol 67561 4 CAL Methyl chloride 74873 0.09 IRIS -- M Methyl isobutyl ketone 108101 3 IRIS -- L/M Methyl methacrylate 80626 0.7 IRIS -- M/H Methyl tert-butyl ether 1634044 3 IRIS -- M Methylene chloride 75092 1 ATSDR Methylene diphenyl diisocyanate 101688 0.0006 IRIS -- M Naphthalene 91203 0.003 IRIS -- M

n-Hexane 110543 0.7 IRIS -- M Nickel compounds 7440020 0.00009 ATSDR p-Dichlorobenzene 106467 0.8 IRIS -- M

Phenol 108952 0.2 CAL Phosgene 75445 0.0003 IRIS -- M Phthalic anhydride 85449 0.02 CAL Propylene dichloride 78875 0.004 IRIS -- M Propylene oxide 75569 0.03 IRIS -- M

16 The value for ethylene glycol methyl ether was used as a surrogate.21

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 i nhalation 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 and Disease Registry.

Pollutant CAS
Number RfC (mg/m 3 ) Source 13
Selenium compounds 7782492 0.02 CAL Styrene 100425 1 IRIS -- M

Tetrachloroethene 127184 0.27 ATSDR

Toluene 108883 5 IRIS -- H Trichloroethylene 79016 0.6 CAL Triethylamine 121448 0.007 IRIS -- L Vinyl acetate 108054 0.2 IRIS -- H Vinyl chloride 75014 0.1 IRIS -- M Vinylidene chloride 75354 0.2 IRIS -- M Xylenes (mixed) 19 1330207 0.1 IRIS -- M - m-Xylene 17 108383 0.1 IRIS -- M - o-Xylene 19 95476 0.1 IRIS -- M - p-Xylene 19 106423 0.1 IRIS -- M

Table 2.6-3.B Dose-Response Values for Chronic Oral Exposure to Noncarcinogens

RfD (reference dose) = an estimate (wit h uncertainty spanning perhaps an order of magnitude) of a continuous oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a
lifetime. Sources : IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health Assessment, ATSDR = US Agency for Toxic Substances and Disease Registry.

Pollutant CAS Number RfD (mg/kg/d) Source 18

Cadmium compounds 7440439 0.0005 IRIS – H

Mercuric chloride 19 7439976 0.0003 IRIS – H - Methyl mercury 21 22967926 0.0001 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 exis ting recommendations of OAQPS for HAPs [ 26 ]. Depending on availability, the results from scre ening acute assessments are compared to both

17 The RfC for mixed xylenes was used as a surrogate.

18 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.

19 The multipathway exposure assessment for mercury included fate and transport analysis, that included separate oral exposure estimates for divalent mercury and methylmercury.22

“no effects” reference levels for the general public, such as the California Reference Exposure Levels (RELs), as well as emergency response le vels, such as Acute Exposure Guideline Levels (AEGLs) and Emergency Response Planning Guidelin es (ERPGs), with the recognition that the ultimate interpretation of any potential risks as sociated with an estim ated exceedance of a particular reference level depends on the defini tion of that level and a ny limitations expressed therein. Comparisons among different available i nhalation health effect reference values (both acute and chronic) for selected HAPs can be f ound in an EPA document (Reference: U.S. EPA. Graphical Arrays of Chemical-Specific Health E ffect Reference Values for Inhalation Exposures [Final Report]. (U.S. Envir onmental Protection Agency, Wash ington, D.C., EPA/600/R-09/061, 2009. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003.)

California Acute Reference Exposure Levels (RELs ). The California Environmental Protection Agency (CalEPA) has developed acute dose-resp onse reference values for many substances, expressing the results as Acute inhala tion Reference Exposure Levels (RELs). The acute REL ( http://www.oehha.ca.gov/air/pdf/acuterel.pdf ) is defined by CalEPA as “the
concentration level at or below which no a dverse 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 litera ture. RELs are designed to protect the most sensitive individuals in the pop ulation by the inclusion of margins of safety. Since margins of safety are incorporated to address data gaps and uncertainties, exceeding the REL does not automatically indicate an adverse health impact.” Acute RELs are developed for 1-hour (and 8-hour) exposures. Th e values incorporate uncertainty factors similar to those used in deriving EPA’s Inha lation Reference Concentrations (RfCs) for chronic exposures (and, in fact, Califor nia also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory Committee (NAC) on Acute Exposure Guide line Levels (NAC/AEGL) for Hazardous Substances, and then reviewed and published by the National Research Council As described in the Committee’s “Standing Operating Procedures (SOP)” ( http://www.epa.gov/op ptintr/aegl/pubs/sop.pdf ), AEGLs “represent threshold exposure limits for the general public and are applicable to emer gency exposures ranging from 10 min to 8 h.” Their intended application is “for conducting risk assessments to aid in the development of emergency preparedness and prevention plans, as well as real time emergency response actions,
for accidental chemical releases at fixed faciliti es and from transport carriers.” The document states that “the primary purpose of the AE GL program and the NAC/AEGL Committee is to develop guideline levels for once-in -a-lifetime, short-term exposures to airborne concentrations of acutely toxic, high-priority chemicals.” In detailing the intended applic ation 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 St ate agencies, and possi bly the international community in conjunction with chemical em ergency response, planning, and prevention programs. More specifically, the AEGL valu es will be used for conducting various risk assessments to aid in the development of emerge ncy preparedness and prevention plans, as well as real-time emergency response actions, for accident al chemical releases at fixed facilities and from transport carriers.”

The NAC-AEGL defines AEGL-1 and AEGL-2 as:23

“AEGL-1 is the airborne concentr ation (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that th e general population, including su sceptible individuals, could experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. However, the effects are not disabling and ar e transient and revers ible upon cessation of exposure.”

“AEGL-2 is the airborne concentr ation (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that th e general population, including su sceptible individuals, could experience irreversible or other serious, long-la sting adverse health e ffects or an impaired ability to escape.”

“Airborne concentrations below AEGL-1 repr esent exposure levels that can produce mild and progressively increa sing but transient and nondisabling od or, taste, and sensory irritation or certain asymptomatic, nonsensory effects. With increasing airborne concentrations above each AEGL, there is a progressive increase in th e likelihood of occurrence and the severity of effects described for each corresponding AE GL. Although the AEGL values represent threshold levels for the general public, including susceptible subpopulations, such as infants, children, the elderly, persons with asthma, and t hose with other illnesses, it is recognized that individuals, subject to unique or idiosyncratic responses, could experience the effects
described at concentrations below the corresponding AEGL.”

Emergency Response Pla nning Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergenc y Response Planning Guidelines (ERPGs) [ 28 ] for acute exposures at three different levels of severity. These guidelines represent concentrations for exposure of the general population (but not pa rticularly sensitive persons) for up to 1 hour associated with effects expected to be mild or transient (ERPG-1), irreversible or serious (ERPG2), and potentially life-threatening (ERPG-3).

ERPG values ( http://www.aiha.org/1documents/Committees/ERP-erpglevels.pdf ) are described in their supporting documentation as follows : “Emergency Response Planning Guidelines (ERPGs) were developed for emergency planning and are intended as health based guideline concentrations for single exposures to chemical s. These guidelines (i.e., the ERPG Documents and ERPG values) are intended for use as planni ng tools for assessing the adequacy of accident prevention and emergency response plans, includ ing transportation emergency planning and for developing community emergency response plan s. The emphasis is on ERPGs as planning values: When an actual chemical emergency occurs there is seldom time to measure airborne
concentrations and then to take action.”

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 wi thout experiencing other than mild transient
adverse health effects or w ithout perceiving a clearly de fined, objectionable odor.”

“ERPG-2 is the maximum airborne concentration below which it is believed that nearly all24

individuals could be exposed for up to 1 hour wi thout experiencing or de veloping irreversible or other serious health effects or symptoms whic h could impair an individual's ability to take protective action.”

The emissions inventories for the 7 source categori es include emissions of 59 HAP with relevant and available quantitative acute dose-response thres hold values. These HAPs, their acute threshold values, and the source of the va lue are listed below in Table 2.6-3.

Table 2.6- 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 )
1,1,1-Trichloroethane 71556 1300 3300 1300 3300 68
1,3-Butadiene 106990 1500 12000 1500 12000
1,4-Dioxane 123911 61 1200 3 2,4-Toluene diisocyanate 584849 0.14 0.59 0.14 1.1 Acetaldehyde 75070 81 490 81 490 0.47

Acetonitrile 75058 22 540

Acrolein 107028 0.069 0.23 0.069 0.23 0.0025 Acrylic acid 79107 4.4 140 4.4 140 6 Acrylonitrile 107131 10 130 22 77 Allyl chloride 107051 8.8 170 9.4 130 Arsenic compounds 7440382 0.0002

Benzene 71432 170 2600 170 2600 1.3 Beryllium compounds 7440417 0.025 Biphenyl 92524 61

Carbon disulfide 75150 40 500 40 500 6.2

Carbon tetrachloride 56235 280 1200 280 1200 1.9

Chlorine 7782505 1.5 5.8 1.5 5.8 0.21

Chloroacetic acid 79118 26

Chlorobenzene 108907 46 690

Chloroform 67663 310 310 0.15

Cumene 98828 250 1500 Cyanide compounds 20 57125 2.2 7.8 7.8 0.34 Dimethyl formamide 68122 270 6 270 Dimethyl sulfate 77781 0.12 0.62 Epichlorohydrin 106898 22 91 22 91 1.3 Ethyl acrylate 140885 34 150 34 150 Ethylene dichloride 107062 200 810 Ethylene glycol Ethylene oxide 75218 81 81 Formaldehyde 50000 1.1 17 1.1 17 0.055 Glycol ethers 21 171 0.093

20 Acute values for hydrogen cyanide were used as surrogates.

21 The value for ethylene glycol methyl ether (0.093) was used as a surrogate for glycol ether compounds without an REL value and for unspeciated glycol ethers.25

Table 2.6- 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 ) - 2-Butoxyethyl acetate 112072 0.093 - Diethylene glycol monobutyl ether 112345 0.093 - Diethylene glycol monoethyl ether 111900 0.093 - Ethylene glycol ethyl ether 110805 0.37 - Ethylene glycol ethyl ether acetate 111159 0.14 - Ethylene glycol methyl ether 21 109864 0.093 - n-Hexyl carbitol 112594 0.093 - Phenyl cellosolve 122996 0.093 - Propyl cellosolve 2807309 0.093 Hydrazine 302012 0.13 17 0.13 17 Hydrochloric acid 7647010 2.7 33 2.7 33 2.1 Hydrofluoric acid 7664393 0.82 20 0.82 20 0.24 Hydrogen cyanide 74908 2.2 7.8 7.8 0.34 Mercury (elemental) 7439976 1.7 2 0.0006

Methanol 67561 690 2700 690 2700 28 Methyl chloride 74873 1900 1900 Methyl iodide 74884 150 290 Methyl methacrylate 80626 70 490 Methyl tert-butyl ether 1634044 180 2100 Methylene chloride 75092 690 1900 690 1900 14 Methylene diphenyl diisocyanate 101688 0.2 2

n-Hexane 110543 12000 Nickel compounds 7440020 0.006

Phenol 108952 58 89 58 89 5.8 Phosgene 75445 1.2 1.2 0.004 Propylene oxide 75569 170 690 170 690 3.1 Styrene 100425 85 550 85 550 21

Tetrachloroethene 127184 240 1600 240 1600 20

Toluene 108883 750 4500 750 1900 37 Trichloroethylene 79016 700 2400 700 2400 Triethylamine 121448 2.8 Vinyl acetate 108054 24 630 18 260 Vinyl chloride 75014 640 3100 640 3100 180 Xylenes (mixed) 1330207 560 4000 22 - m-Xylene 108383 560 4000 22 - p-Xylene 106423 560 4000 22 - o-Xylene 95476 560 4000 2226



### 2.7 Risk characterization

2.7.1 General

The final product of the risk asse ssment is the risk characteriza tion, in which the information from the previous steps is integrated and an overa ll conclusion about risk is synthesized that is complete, informative, and useful for decision ma kers. In general, the nature of this risk characterization depends on the information availabl e, the application of the risk information and
the resources available. In al l cases, major issues associated with determining the nature and
extent of the risk are identified and discusse d. Further, the EPA Administrator’s March 1995 Policy for Risk Characterization [ 29 ] specifies that a risk charact erization “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 [ 30 ], in 2002 by the Agency’s information quality guidelines [ 31 ], and in the OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis 22 , and are incorporated in these

assessments.

Estimates of health risk are pres ented in the context of uncertainties and limitations in the data and methodology. Through our tiered, iterative analytical approach, we have attempted to reduce both uncertainty and bias to the greatest degree possible in these assessments, within the limitations of available time and resources. We provide summaries of risk metrics for each source category (including maxi mum individual cancer risks and noncancer hazards, as well as cancer incidence estimates) along with a discussi on of the major uncertain ties associated with their derivation to provide decision makers with the fullest picture of the assessment and its
limitations.

For each carcinogenic HAP included in this assessment that has a potency estimate available, individual and population cancer risks were calc ulated by multiplying the corresponding lifetime average exposure estimate by the appropriate URE. This calculated cancer risk is defined as the upper-bound probability of developing cancer over a 70-year period (i.e., the assumed human lifespan) at that exposure. Because UREs fo r most HAPs are upper-bound estimates, actual risks at a given exposure level may be lower than predicted, and could be zero.

For EPA’s list of carcinogenic HAPs th at act by a mutagenic mode-of-action [ 32 ], we applied

EPA’s Supplemental Guidance for Asse ssing Susceptibility from Early-Life Exposure to Carcinogens [ 33 ]. This guidance has the effect of adjusting the URE by factors of 10 (for children aged 0-1), 3 (for children aged 2-15), or 1.6 (for 70 years of exposure beginning at birth), as needed in risk assessments. In this cas e, this has the effect of increasing the estimated life time risks for these pollutants by a factor of 1.6. In addi tion, although only a small fraction of the total POM emissions may be repor ted as individual co mpounds, EPA expresses carcinogenic potency for compounds in this group in terms of benzo[a]pyren e equivalence, based

22 Memorandum for the Heads of Executive Departments and Agencies - Updated Principles for Risk Analysis (September 19, 2007), From Susan E. Dudley, Administrato r, Office of Information and Regulatory Affairs, Office of Management and Budget; and Sharon L. Hays, Associat e Director and Deputy Director for Science, Office of Science and Technology Policy (http://www.wh itehouse.gov/omb/memoranda/fy2007/m07-24.pdf)27

on evidence that carcinogenic POM have the same mutagenic mechanism of action as does benzo[a]pyrene. For this reas on, EPA implementation policy [ 34 ] recommends applying the Supplemental Guidance to all carcinogenic PAHs for which risk estimates are based on relative potency. Accordingly, we applied the Supplemental Guidance to all unspeciated POM mixtures.

Increased cancer incidence for the entire receptor population with in the area of analysis was estimated by multiplying the estimated lifetime cancer risk for each census block by the number of people residing in that block, then summing the results for the entire modeled domain. This lifetime population incidence estimate was divide d by 70 years to obtain an estimate of the number of cancer cases per year.

In the case of benzene, the high end of th e reported cancer URE range was used in our assessment to provide a conservative estimate of pot ential cancer risks. Use of the high end of the range provides risk estimates that are approxi mately 3.5 times higher than use of the equallyplausible low end value. If the estimated benzene–associated risks exceed 1 in a million, we also evaluated the impact of us ing the low end of the URE range on our risk results.

Unlike linear dose-response assessments for cance r, 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 referen ce level as a ratio. The “hazard quotient” (HQ) is the estimated exposure divided by a refere nce level (e.g., the RfC). For a given HAP, exposures at or below the reference level (HQ ≤ 1) are not likely to cause adverse health effects. As exposures increase above the reference level (HQs increasingly greater than 1), the potential for adverse effects increases. For exposures predicted to be above the RfC, the risk characterization includes the degree of confid ence 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 cens us block centroid. As discussed above, RfCs incorporate generally conservative uncertainty fa ctors 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 a dverse effects will occur, and is unlikely to be proportional to adverse health e ffect outcomes in a population.

Screening for potentially significan t acute inhalation exposures also followed the HQ approach. We divided the maximum estimated acute exposure by each available short-term threshold value to develop an array of HQ values relative to the various acute endpoints and thresholds. In general, when none of these HQ values are greater than one, there is no potential for acute risk. In those cases where HQ values above one are seen , additional information is used to determine if there is truly a potential for significant acute risks.

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.28

To combine risks across multiple carcinogens, our assessments use the EPA mixtures guidelines’ [ 35
, 36 ] default assumption of additivity of effect s, and combined risks by summing them using the independence formula in the mixtures guidelines.

In assessing noncancer hazard from chronic exposu res, in cases where different pollutants cause adverse health effects via completely different modes of action, it ma y be inappropriate to aggregate HQs. In consideration of these mode -of-action differences, the mixtures guidelines support aggregating effects of diffe rent substances in specific and limited ways. To conform to these guidelines, we aggregated non-cancer HQs of HAPs that act by similar toxic modes of action, or (where this information is absent) that affect the same target organ. This process creates, for each target organ, a target-organ-sp ecific hazard index (TOSHI), defined as the sum of hazard quotients for individual HAPs that affect the same organ or organ system. All TOSHI calculations presented here were based exclusively on effects o ccurring at the “critical dose” (i.e., the lowest dose that produces adverse health effects). Al though 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 ta rget organ. Because impacts on organs or systems that occur above the critical dose have not been included in the TOSHI calculations, some TOSHIs may have been underestimated. As with the HQ, the TOSHI should not be interpreted as a probability of adverse effects, or as strict delineation of “safe” and “unsafe” levels. Rather, the TOSHI is another measure of the potential for adverse health outcomes associated with pollutant exposure, and needs to be interpreted carefully by health scientists and risk managers.

Because of the conservative nature of the acute inhalation screening and th e 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 developed using emissions data from the 2005 NEI. For th e facilities in these source categories, we extracted from the results, based on facility ID , estimates of all HAP emissions sources at the facility, including emissions sources that are not part of the source categories but that are located within a contiguous area and are under common cont rol. We then analyzed risks due to the inhalation of the HAP for the populations residing within 50 kilometers of each facility. The results of these facility-wide assessments are summarized below in the individual source category Risk Characterization sections of this do cument. The complete results of the facilitywide assessments are provided in Table 2 (assoc iated with the source cat egory of interest) of Appendix 6.



### 3 Results summaries and risk char acterizations for the 7 source categories

In this section, the results of the risk a ssessments for each of the 7 source categories are presented separately. Each subsection includes the following information for each source
category:29

1) A narrative description of th e source category, including a discussion of the processes
involved and the number of facilities EPA knows or expects are affected by the MACT standard;

2) A table of emissions for the entire category showing HAP emitted, total source category emission rates for each HAP, and numbers of fa cilities reporting emissions of each HAP;

3) A table summarizing the chronic inhalation risk results showing the number of facilities modeled, the number of people within 50 km, the MIR for the entire source category, the
number of facilities for wh ich the facility-specific MIR exceeds specific cancer and noncancer benchmarks, the number of people for whom the risks exceed the same benchmarks, the estimated total cancer inci dence, and identifying the specific HAPs contributing the most to those risks (HAPs iden tified as “drivers” include those contributing the most to the risk metric, up to 90% of its value). In addition, this table indicates the maximum HQ from the acute inhalation screen ing and an indication of how many facilities showed HQ values above 1;

4) In those cases where the acute inhalation scr eening showed an HQ value greater than 1 for any combination of source and pollutant, a table summarizing the acute screening results showing available acute dose-response values for each affected pollutant, for three effect levels (REL, AEGL-1/ERPG-1, and AEGL-2/E RPG-2), if available, the maximum acute screening exposure estimated, a nd the associated HQ values;

5) A narrative summarizing the risk ch aracterization for that category.

Detailed accounting of the changes made to the i nventory for each source category as a result of the engineering reviews and comments received can be found in Appendix 1. Detailed source category facility-level results fo r both chronic and acute inhalation risk assessments and facilitywide results of the chronic inhalation risk asse ssments for each of the 7 source categories can be found in Appendix 6.



### 3.1 Printing and publishing

3.1.1 Source category description and results

The printing and publishing source category includes facilities that use ro togravure, flexography, and other methods, such as lithography, letterpres s, and screen printing, to print a variety of substrates, including paper, plasti c film, metal foil, and vinyl. The MACT standards focused on those facilities that perform publication rotogr avure printing, product an d package rotogravure printing, and wide-web flexographi c printing. Publication rotogra vure printing refers to printing using a rotogravure press of va rious paper products, including catalogs, magazines, direct mail advertisements, display advertisements, misce llaneous brochures and other advertisements, newspaper sections and inserts, periodicals, and telephone directories. Product and packaging rotogravure printing entails the pr oduction, on a rotogravure press, of any printed substrate not30

otherwise defined as publication rotogravure printing. This includes (but is not limited to) folding cartons, flexible packaging, labels and wrappers, gift wraps, wall and floor coverings, upholstery, decorative laminates, and tissue prod ucts. Wide-web flexographic printing is a technique for printing substrates of 18 inches or wider in which the applied pattern is raised above the printing plate and the image carrier is ma de of rubber or other elastomeric materials. The wide-web flexographic presses are used to pr int flexible and rigid packaging; newspapers, magazines, and directories; pape r towels, tissues, and similar pr oducts; and printed vinyl shower curtains and wallpaper. Research and laboratory facilities are not subject to the provisions of the MACT standards unless they are co-l ocated with production lines.

The MACT rule applies to HAP pr esent in the inks, ink extenders, solvents, coatings, varnishes, primers, adhesives, and other materials applie d with rotogravure and wide-web flexographic presses. HAP emissions from printing and publishi ng facilities in this source category can vary depending on the type of HAP present in the inks, solvents, etc., mentioned above. HAP emissions can also vary depending on the operati ng hours of the facility. Some sources operate twenty-four hours a day, seven days a week, wh ile other sources operate less frequently.

In rotogravure printing, a gravure plate or cylinder is used to a llow fluid inks to flow from the cells to the substrate at high press speeds. In ad dition to inks, other materials such as adhesives, primers, coatings, and varnishes may be applied with rotogravure presses. These materials dry by evaporation as the substrate passes through hot air dryers. For publication rotogravure printers, facilities use toluene/ xylene based ink systems and opera te solvent recovery systems based on carbon adsorption with steam regene ration. Emission sources at publication rotogravure printing facilities in clude evaporation of HAP (solve nts) from inks and coatings, solvents used for press cleaning, and stor age of inks, coatings, and solvents.

Product and packaging rotogravure differs from publication rotogravure with respect to the materials used (i.e., product and packaging rotogravure uses a wide r variety of ink systems, color sets, and materials applied) and applicable control devices. C onsequently, the control of HAP emissions, which originate from the inks and other applied materials (e.g., adhesives and coatings), varies across facilities. Some facilities use a variety of thermal and catalytic oxidizers
as well as activated carbon based solvent recovery systems, while others comply without using control devices by using low HAP content material s. Emission sources at product and packaging rotogravure facilities include evaporation of HAP (solvents) from inks, co atings and adhesives, solvents used for press cleaning, and storage of inks, coatings, adhesives, and solvents.

Flexographic inks include both wa terborne and solvent-based syst ems that are used to achieve sufficient ink fluidity. Waterbor ne inks contain a relatively lo w proportion of HAP, principally ethylene glycol and glycol ethers . Waterborne inks that contai n no HAP are available for some applications. Most solvent-based flexographic in ks contain few or no HAP. Emission sources at wide-web flexographic printing f acilities include eva poration of HAP (solvents) from inks, coatings and adhesives, solvents used for press cl eaning, and storage of inks, coatings, adhesives,
and solvents.

At the time of MACT promulgation in 1995, EP A estimated that there were approximately 200 publication rotogravure, product and packaging ro togravure, and wide-web flexographic printing31

facilities nationwide that would be subject to th ese MACT regulations. After further review by
EPA to remove area source faci lities from the data set, we now believe the Printing and Publishing source category to be comprised of 172 facilities emitting a reported combined total of 7,460 tons/year of HAP into the atmosphere . Refer to Appendix 1 for details on how the emissions inventory wa s developed.

Table 3.1-1 summarizes the emissions for the Prin ting and Publishing Industry source category. Based on the data set, the HAP emitted in largest quantities from these sources are toluene, glycol ethers, methanol, xylenes, methyl isobut yl ketone, hexane, et hyl benzene, methyl chloroform, and ethylene glycol. Total emissions from these nine HAP account for 99 percent of
the mass emitted across all 172 faci lities. On an individual HAP ba sis, toluene is reported as emitted from 97 facilities (56 percent). Persiste nt and bioaccumulative HAP (PB HAP) reported in the data set for this source category include emissions of cadmium, lead, and mercury at very
low levels.

Tables 3.1-2 and 3.1-3 provide information summarizing health risks for this source category.

Table 3.1-1 Summary of Emissions and Availability of Dose-Response Values for the Printing and Publishing Source Category

HAP a Emissions (tpy) Number of
Facilities Reporting HAP (172 facilities in data set) Prioritized Inhalation Dose -Response Value Identified by OAQPS b PBHAP? Unit Risk
Estimate for

Cancer? Reference
Concentration
for Noncancer? Health Benchmark
Values for Acute
Noncancer?
Toluene 6,605 97 Υ Υ Glycol Ethers 172 44 Υ Υ Xylenes (Mixture of o, m, and p Isomers) 145 55 Υ Υ

Methyl Isobutyl Ketone 140 32 Υ

Methanol 114 56 Υ Υ

Hexane 84 25 Υ Υ Ethyl Benzene 57 22 Υ Υ Methyl Chloroform 54 9 Υ Υ Ethylene Glycol 41 28 Υ Υ Diethylene Glycol Monobutyl
Ether 15 6 Υ Υ

Diethylene Glycol Monoethyl
Ether 11 7 Υ Υ

Vinyl Acetate 9 12 Υ Υ Ethylene Glycol Methyl Ether 3 9 Υ Υ N,N-Dimethylformamide 2 2 Υ Υ Methylene Chloride 2 6 Υ Υ Υ

Diethanolamine 1 6 Υ Hydrochloric Acid 0.8 1 Υ Υ Formaldehyde 0.7 16 Υ Υ Υ Bis(2-Ethylhexyl)Phthalate 0.6 2 Υ Υ Hydroquinone 0.6 4

Cumene 0.4 8 Υ Υ32

Table 3.1-1 Summary of Emissions and Availability of Dose-Response Values for the Printing and Publishing Source Category

HAP a Emissions (tpy) Number of
Facilities Reporting HAP (172 facilities in data set) Prioritized Inhalation Dose -Response Value Identified by OAQPS b PBHAP? Unit Risk
Estimate for

Cancer? Reference
Concentration
for Noncancer? Health Benchmark
Values for Acute
Noncancer? m-Xylene 0.4 1 Υ N-Hexyl Carbitol 0.3 1 Υ Isophorone 0.2 2 Υ Υ 4,4'-Methylenediphenyl Diisocyanate 0.1 1 Υ Υ

Triethylamine 0.1 3 Υ Υ Dimethyl Phthalate 0.06 2 Methyl Methacrylate 0.05 1 Υ Υ

Benzene 6 0.03 6 Υ Υ Υ Naphthalene 0.03 4 Υ Υ

Cellosolve Acetate 0.02 1 Υ Υ Dibutyl Phthalate 0.02 1 Phenyl Cellosolve 0.02 3 Υ Υ

Phenol 0.01 1 Υ Υ

Carbon Tetrachloride 0.01 1 Υ Υ Υ

Chlorobenzene 0.008 1 Υ Υ Acrylic Acid 0.002 3 Υ Υ 2,4-Toluene Diisocyanate 0.001 3 Υ Υ Υ Ethyl Acrylate 0.0004 1 Υ Chromium (VI) Compounds 0.00004 2 Υ Υ Nickel & Compounds 0.00002 2 Υ Υ Cadmium & Compounds 0.00001 2 Υ Υ Υ
1,4-Dichlorobenzene 0.00001 2 Υ Υ Lead Compounds (Inorganic) 0.000005 2 Υ Υ Styrene 0.000004 1 Υ Υ Manganese & Compounds 0.000004 2 Υ Mercury & Compounds 0.000003 2 Υ Υ Υ Arsenic & Compounds (Inorganic Including Arsine) 0.000002 2 Υ Υ Υ

POM72002 0.0000003 2 Υ Υ

a Notes for how HAP were speciated for risk assessment:

• For emissions of any chemicals or chemical groups classified as polycyclic organic matter (POM), emissions were grouped into POM subgroups as found on EPA’s Technology Transfer Network website for the 2002 National-Scale
Air Toxics Assessment at http://www.epa.gov/na ta2002/methods.html#pom . ( Approach to Modeling POM ).

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

b Specific dose-response values for each chem ical are identified on EPA’s Technology Transfer Network website for air toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html

.33

Table 3.1-2 Summary of Source Category Le vel Risks for Printing and Publishing

Result HAP “Drivers” Facilities in Source Category Number of Major Source Facilities Estimated to be in Source Category 172 n/a

Number of Facilities Identified in NEI and
Modeled 172 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 4 ethyl benzene

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 0 n/a Greater than or equal to 1 in 1 million 1 ethyl benzene

Chronic Noncancer Risks Maximum Respiratory Hazard I ndex 0.08 ethylene glycol Number of Facilities with Maximu m Respiratory Hazard Index:
Greater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 20

1

1 toluene (REL) toluene (AEGL-1) toluene (ERPG-1)

Number of Facilities With Potential for Acute
Effects 7 toluene

Acute Noncancer Refined Results

Maximum Acute Hazard Quotient 10
0.5

0.5 toluene (REL) toluene (AEGL-1) toluene (ERPG-1)

Number of Facilities With Potential for Acute
Effects 6 toluene

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 118,000,000 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 0 n/a Greater than or equal to 1 in 1 million 300 n/a Number of People Exposed to Respiratory Hazard Index : Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.0006 n/a

Contribution of HAP to Cancer Incidence ethyl benzene 70% n/a formaldehyde 28%34Table 3.1-3 Summary of Acute RefinedResults for Printing and PublishingRefined Results MAXIMUM ACUTE HAZARD QUOTIENTS ACUTE DOSE-RESPONSE VALUESHAPMax. 1-hr. AirConc.(mg/m3)Based on RELBased onAEGL1/ERPG-1Based onAEGL2/ERPG-2REL(mg/m3)AEGL-1(1-hr)(mg/m3)ERPG-1(mg/m3)AEGL-2(1-hr)(mg/m3)ERPG-2(mg/m3)toluene 384 10 0.5/0.5 0.2/0.3 37 750 750 4500 1900Notes on Process:1)Acute screening was performed for all emitted HAP with availableacute dose-response values. Where acute screening HQ values exceeded 1, refined analysis wasperformed. Only those pollutants whose refined HQs were equal to or greater than 1for at least one acute threshold value areshown in the table.2)HAP with available acutedose-response values which are not in the table donot carry any potential forposing acute health risks, based on an analysis of currentlyavailable emissions data.Notes on Acute Dose-Response Values:REL – California EPA reference exposure level for no adverseeffects. Most, but not all RELs are for 1-hour exposures.AEGL – Acute exposure guideline levels represent emergency exposure (1-hour) limits for the general public.AEGL-1 is the exposure level above which itis predicted that the general population, including susceptible individuals, couldexperience effects that are notablediscomfort, but which are transient andreversible upon cessation of exposure.AEGL-2 is the exposure level above which itis predicted that the general population, including susceptible individuals, couldexperience irreversible or other serious,long-lasting adverse health effects oran impaired ability to escape.ERPG – Emergency RemovalProgram 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, transientadverse health effects.ERPG-2 is the maximum exposure below which it is believed that nearlyall individuals could be exposed for up to 1 hour without experiencing or developingirreversible or other serious health effects or symptoms which could impair an individual’s ability to take protective action.35

3.1.2 Risk characterization

There were 172 facilities identified as being a part of this sour ce category, and they were all
included in the assessment. The results of th e risk assessment showed the highest individual cancer risk to be 4-in-1 million, with this cancer risk being led by emissions of ethyl benzene. Based on information obtained during the comment pe riod, we believe the risk for this facility is now below 1-in-a million. All other facilities in this source category are below 1-in-a
million. Cancer incidence associated with the inhalation of emissions from facilities in this source category is 0.0006 cases per year.

Chronic noncancer risks were not identified as significant. The maximum estimated chronic noncancer hazard index was 0.08, and its magnit ude was dominated by the contribution from ethylene glycol emissions. This value is well below 1, an exposure level generally considered to be without appreciable health risks.

The MACT-allowable emissions from this source category could be up to five times greater than the actual emissions. Applying this scali ng factor, results in a potential MIR of 20 and
HI of 0.4.

The screening assessment for acute impacts suggests that short-term toluene concentrations at seven of the publication rotogr avure facilities modeled could exceed acute thresholds, assuming worst-case meteorological conditions are present, using our default assumption that the maximum hourly emissions of toluene exceed the average hourly emission rate by a factor of ten, and using a default source to receptor di stance of 100 m. Emissions of toluene showed the potential to create maximum hourly concentr ations which could exceed the acute REL by a factor of 20 (HQ REL = 20) and potentially reach th e level of the AEGL-1 (HQ AEGL-1 = 1). For the publication rotogravure facilities that exc eeded acute toluene thresholds in the screening assessment, we refined the assessm ent by plotting receptors on facility aerial photographs and determining maximum offsite concentrations. Once we performed these refinements, estimated maximum offsite concentra tions were seen to exceed the acute REL at six publication rotogravure facilities. The hi ghest offsite concentra tion exceeds the REL by a
factor of 10 and is about ha lf of the AEGL-1 value (HQ REL = 10, HQ AEGL-1 = 0.5). This occurs near a public road north of a facility . At this facility, meteorological conditions leading to offsite exceedances of the REL could occur as freq uently as 90 hours per year, or about 1 percent of the time. At the facility wh ere we estimate the REL to be most frequently exceeded, the maximum REL exceedance is by a f actor of 4, and meteorological conditions leading to offsite exceedances of the REL could occur as freque ntly as 138 hours per year, or about 2 percent of the time. Further, experts on this source category sugges t that the factor of 10 multiplier (used in the acute risk screening) is most likely high for publication rotogravure printing. They suggest that a more appropriate multiplier would be in the range of 5 or less. Using a multiplier of 5 (or less) would reduce the estimated acute impacts by half (or more) from the values presented. Details on the re fined acute assessment can be found in Appendix

7.36

While our assessment did identify some emissi ons of PB-HAP from this source category, none of these emissions are anticipated to pos e any potential multipathway risks based on our application of the PB-HAP screening scen ario developed using the TRIM.FaTE model (Appendix 5). Thus, our assessment did not iden tify any potential for this source category to pose significant chronic non-inhalation risks, nor did we identify any potential for adverse environmental impacts.

Based on our technical knowledge of this so urce category and the lack of comments on our understanding of the source category proposed in the NPRM, we have a high degree of confidence that our assessment covers the majori ty of the source categor y (at least 90% of the total facilities) and that we ha ve accurately characterized the em issions. As such, we believe that the exposure portion of our assessment accu rately represents maximum chronic inhalation exposures and total population exposures for the purpose of estimating cancer incidence.
Since we did not refine our population exposure assessment to account for residential moves over the course of 70 years or the possibility of facility closures, our estimates of the magnitudes of individual risks in the exposed population are likely overestimates, and our estimates of the total number of peopl e exposed are likely underestimates.

The facility-wide MIR and HI available in Appe ndix 6 are based on emissions, as identified in the NEI database, from all emissions sources at the identified facilities. The maximum facility-wide risks are estimated to be a cance r MIR of 20 in a million and a hazard index (HI) of 20, which occur at different facilities. The source category contribution to the facility-wide
risk at both facilities is less than 1% for MI R and HI. Subsequently after the risk modeling was complete, we received data that identified an error in emissions that caused the highest facility-wide HI value (20). After reviewing the updated emissions and assessing the risk, the HI dropped significantly. The next highest facility-wide HI is 2 associated with another facility. The source category contribution to the HI risk at this facility is less than 1%.

Table 3.1-4 Source Category Contribution to Facility-Wide Cancer Risks – Printing and Publishing

Printing and Publishing Number of Fa cilities Binned by Facility-Wide MIR (in 1 million) Source Category MIR Contribution to Facility-Wide

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

> 90% 29 1 0 0 30
50-90% 3 0 0 0 3
10-50% 6 0 0 0 6
< 10% 123 9 1 0 133

Total 161 10 1 0 17237



### 3.2 Marine tank vessel loading

3.2.1 Source category description and results

Marine tank vessel loading operati ons are facilities that load and unload liquid commodities in bulk, such as crude oil, gasoline and other fuel s, and some chemicals and solvent mixtures. The cargo is pumped from the terminal's larg e, above-ground storage tanks through a network of pipes and into a storage compartment (ta nk) on the vessel. Most marine tank vessel loading operations are associated with petroleum refineries or synthetic organic chemical manufacturers, or are independe nt terminals. Marine vessel loading operations located at petroleum refineries are not in cluded in this source category; their emissions are regulated by the MACT standard for the petroleum refine ry source category. Using Army Corps of Engineers information, we estimated that th ere were around 800 marine tank vessel loading and unloading operations in the y ear 2000; however, many of these f acilities are not subject to the Marine Vessels MACT regulation because th ey are not at major sources of HAP, do not load or unload any HAPs, or because they only load liquids in containers such as drums, which are not subject to this MACT. We estim ate there are about 300 ma jor source facilities
with MTVLO. 23

During marine tank vessel loading operations, HAP emissions can occur as the liquid that is being loaded into the vessel di splaces vapors from the vessel's tank. The major HAP emission points for marine tank vessel lo ading operations include open tank hatches and overhead vent systems. Vent systems collect vapors displaced during loading and route them to a vertical pipe or stack. The vapors are released well a bove the height of the deck with an upward velocity to help isolate the vapors from the deck. Other possible emission points are hatch covers or domes, pressure-vacuum relief valves, seals, and vents. Emissions may also occur during ballasting (i.e., the pro cess of drawing ballast as wa ter into a cargo hold).

In reviewing Version 1.0 of the 2002 NEI (Feb ruary 2006), we developed the initial marine vessel data set by identifying facilities with a marine tank vessel opera tion MACT code. EPA engineers subsequently reviewed the data set and identified several marine tank vessel loading operations that were located at petroleum refineries and thus should not be included in the
data set for the marine tank ve ssel loading source category.

The data set contains information for 152 fac ilities with a total of 411 tons/year of HAP
emissions. While the 152 facili ties included in our assessment represent about half of the approximately 300 major source facilities with MTVLO expected to be in the category, we believe the sample of 152 facilities to be represen tative of the 300 facilities. Thus we used the site-specific assessment of the 152 (which incl udes, on average, the higher (by more than twice) MTVLO emissions from all facilities wi th) to obtain our best estimate of the maximum individual risk for the entire category and then develop an estimate of the total cancer incidence associated with the category by multip lying the incidence for the 152 facilities by a factor of 2 (or roughly 300 divided by 152). Fo r further information on how our analysis of

23 See emission memo for estimates of facilities. Augu st 12, 2010, “Update Emissions Data Used in Residual Risk Modeling for the Marine Tank Vessel Loading Operations Source Category,” Karen Schaffner, RTI International, to Stephen Shedd and Mary Tom Kissell, EPA. Docket item.38

the emissions inventory supports this determ ination of representativeness and how the emissions inventory changed, see the Emissions Inventory Support Memoranda in Appendix

1.

Table 3.2-1 summarizes the emissions for the ma rine tank vessel loading operations source category. Based on these data, the HAP emitted in largest quantities in total from these sources are hexane, methyl tert -butyl ether, toluene, methanol, benzene, xylene compounds, butadiene, styrene, cumene, ethylene di chloride, naphthalene, ethyl benzene, trichloroethylene, acrylonitrile tetrachl oroethylene, propylene oxide, vinyl acetate, acetaldehyde, and chloroform. The total emissions for these 19 HAP account for 99 percent of the mass emitted across the source categor y. Hexane, toluene, xylene compounds, and benzene are reported as emissions from at least 102 of the 152 representati ve facilities in the data set (67 percent). Persistent and bio accumulative HAP (PB HAP) emissions reported in
the data set for the marine tank vessel load ing operation source category are POM, cadmium, mercury compounds, and lead.

Table 3.2-2 provides information summarizing health risks for this source category.39

Table 3.2-1 Summary of Emissions and Ava ilability of Dose-Response Values for the Marine Tank Vessel Loading Operations Source Category

HAP a Emissions (tpy) Number of
Facilities Reporting HAP (152 facilities in data set) Prioritized Inhalation Dose-Response Value Identified by OAQPS b

PBHAP? Unit Risk
Estimate for

Cancer? Reference
Concentration

for Chronic
Noncancer? Health
Benchmark
Values for Acute
Noncancer?

Hexane 87 104 Υ Υ Methyl Tert-Butyl Ether 62 12 Υ Υ Υ

Toluene 46 111 Υ Υ

Methanol 48 25 Υ Υ

Benzene 42 105 Υ Υ Υ Xylenes (Mixture of o, m, and p Isomers) 31 102 Υ Υ

1,3-Butadiene 27 5 Υ Υ Υ
Styrene 23 27 Υ Υ

Cumene 10 28 Υ Υ Ethylene Dichloride 6 8 Υ Υ Υ Naphthalene 8 20 Υ Υ Ethyl Benzene 5 47 Υ Υ Trichloroethylene 3 4 Υ Υ Υ Acrylonitrile 2 7 Υ Υ Υ Tetrachloroethylene 2 8 Υ Υ Υ Propylene Oxide 2 3 Υ Υ Υ Vinyl Acetate 2 7 Υ Υ Acetaldehyde 1 2 Υ Υ Υ

Chloroform 1 2 Υ Υ Glycol Ethers 0.5 3 Υ Υ
2,2,4-Trimethylpentane 0.4 12 Methylene Chloride 0.4 1 Υ Υ Υ Methyl Methacrylate 0.3 3 Υ Υ
Biphenyl 0.2 12 Υ
m-Xylene 0.2 2 Υ Υ

Phenol 0.2 16 Υ Υ

Aniline 0.2 2 Υ Υ Υ Methyl Isobutyl Ketone 0.2 2 Υ Ethylene Glycol 0.1 21 Υ o-Xylene 0.09 2 Υ Υ Ethyl Acrylate 0.08 2 Υ 2-Nitropropane 0.08 2 Υ Υ Acrylic Acid 0.06 3 Υ Υ Vinyl Chloride 0.04 1 Υ Υ Υ 1-Chloro-2,3- Epoxypropane 0.02 1 Υ Υ Υ

1,2-Epoxybutane 0.02 1 Υ

Carbon Tetrachloride 0.02 1 Υ Υ Υ40

HAP a Emissions (tpy) Number of
Facilities Reporting HAP (152 facilities in data set) Prioritized Inhalation Dose-Response Value Identified by OAQPS b

PBHAP? Unit Risk
Estimate for

Cancer? Reference
Concentration

for Chronic
Noncancer? Health
Benchmark
Values for Acute
Noncancer?

Cellosolve Solvent 0.01 1 Υ Υ Ethylene Glycol Monoethyl Ether 0.007 1 Υ Υ

Cresols (mixed) 0.005 12 Υ Dimethyl Formamide 0.006 1 Υ Υ Formaldehyde 0.003 1 Υ Υ Υ

Chlorobenzene 0.002 1 Υ Υ Hydrochloric Acid 0.001 1 Υ Υ

Diethanolamine 0.001 1 Υ Methylene Diphenyl Diisocyanate 0.001 1 Υ Υ

Propylene Dichloride 0.0006 1 Υ Υ
1,2,4-Trichlorobenzene 0.0006 1 Υ

Chlorine 0.0005 1 Υ Υ Diethylene Glycol Monoethyl Ether 0.0005 1 Υ

o-Cresol 0.0005 1 Υ

POM 71002 0.0002 2 Υ p-Xylene 0.0001 1 Υ Υ Manganese & Compounds 0.00006 1 Υ Lead & Compounds 0.00002 1 Υ Υ

Chromium 0.00001 1 Υ

Nickel 0.000009 1 Υ Υ

Arsenic 0.000006 1 Υ Υ Cadmium Compounds 0.000003 1 Υ Υ Mercury Compounds 0.000003 1 Υ Υ Selenium Compounds 0.000002 1 Υ Beryllium Compounds 0.000001 1 Υ Υ Υ

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 “cad mium & compounds”).

• For emissions reported generically as “chromium” or “chromium & compounds,” emissions are speciated for this category as 75 percent “chromium (III) compounds” and 25 percent “chrom ium (VI) compounds.” Chromium speciation profiles can be found on the EPA’s Technology Transfer Network we bsite for emissions inventories at http://www.epa.gov/ttn/chi ef/net/2002inventory.html

.

• For emissions of any chemicals or chemical groups classified as polycyclic organic matter (POM), emissions were grouped into POM subgroups as found on EPA’s Technology Tr ansfer Network website for the 2002 National-Scale Air
Toxics Assessment at http://www.epa.gov/nata2002/methods.html#pom . ( Approach to Modeling POM ).

• For emissions reported generically as “Glyco l 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.

b Specific dose-response values for each chem ical are identified in section 2.6.41

Table 3.2-2 Summary of Source Category Leve l Risks for Marine Tank Vessel Loading Operations

Result HAP “Drivers” Facilities in Source Category Number of Facilities Estimated to be Subject to MACT in Source Category 300 n/a

Number of Facilities Identified in NEI and
Modeled in NPRM Risk Assessment 152 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) from any Facility in the Category 50 24 benzene, 1,3-butadiene

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 1 benzene, 1,3-butadiene Greater than or equal to 1 in 1 million 2 benzene, 1,3-butadiene

Chronic Noncancer Risks Maximum Reproductive Hazard Index 0.8 1,3-butadiene Number of Facilities with Maxi mum Reproductive Hazard Index:
Greater than 1 0 n/a Acute Noncancer Screening Results Maximum Acute Hazard Quotient 19 benzene (REL)

Number of Facilities With Potential for Acute
Effects 2 glycol ethers, benzene

Acute Noncancer Refined Results Maximum Acute Hazard Quotient 1 benzene (REL)

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

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 61,000,000 n/a

Number of People Exposed to Cancer Risk: 25
Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 9,000 n/a Greater than or equal to 1 in 1 million 513,000 n/a Number of People Exposed to Noncancer Immunological Hazard Index:
Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.04 n/a

Contribution of HAP to Cancer Incidence 1,3-butadiene 59% n/a
benzene 21% n/a naphthalene 14% n/a acrylonitrile 4% n/a ethylene dichloride 2% n/a

24 These results are based on 2005 data. As a result of data obtained during the proposal comment period, we believe today’s MIR is below 1-in-1 milli on for all facilities in the source category.

25 Risk was scaled up to represent the universe of poten tial facilities from the 152 facilities in the data base to 300 facilities or a factor of 2 (300/152).42

3.2.2 Risk characterization

The maximum individual cancer risk estimat ed for the Marine Vessel Loading source category is about 50 in a million. One facility had a maximum individual risk greater than 1 in a million, and this was primarily due to emissions of benzene and 1,3-butadiene. For the facility, we estimated that there are approxima tely 513,000 people with individual cancer risk
levels at or above 1 in a million. We also estim ated that the total cancer incidence associated
with the inhalation of HAP emissions from this source category is 0.04 ca ses per year or about 1 case every 5 years. These results are base d on 2005 data. As a result of data obtained during the proposal comment period, we believe today’s MIR is below 1-in-1 million for all facilities in the source category.

Chronic noncancer risks were determined to be insignificant, with a maximum chronic noncancer hazard index of 0.8, dominated by the contribution from 1,3-butadiene emissions. Additionally, our acute screening assessment iden tified two facilities with the potential for
acute risks above 1. One facili ty had an acute screening value of 5 at the REL level due to glycol ether emissions, and the other facility had an acute screening value of 19 at the REL
level due to benzene emissions. After the refine d analyses were performed the facility with an acute value of 5 for glycol ethers reduced to an acute value below 1, and the facility with
an acute value of 19 for benzene reduced to 1.49 (rounded to 1). Refer to Appendix 7 for
details on the refined assessment.

While our assessment did identify some emissi ons of PB-HAP from this source category, none of these emissions were anticipated to pose any potential multipathway risks based on our application of the PB-HAP screening s cenario developed using the TRIM.FaTE model (Appendix 5). Thus, our assessment did not iden tify any potential for this source category to pose significant chronic non-inhalation risks, nor did we identify any potential for adverse environmental impacts.

The results of the facility-wide assessments are summarized in Table 3.2-3. The results
indicate that 35 facilities cont aining Marine Tank Vessel Loadi ng Operations have a facilitywide cancer MIR greater than 1 in a million. The maximum facility-wide cancer MIR is 90 in a million, with the source category contributing less than 1 percent. There are also 6 facilities with a facility-wide TOSHI value greater than 1. The maximum facility-wide TOSHI value of 4 (reproductive system), has a source category contribution of less than 1%. In general, the contribution of the source category to elevated facility-wide cancer or noncancer risks is low throughout the facilities in this source category.

Table 3.2-3 Source Category Contribution to Facility-Wide Cancer Risks – Marine Tank
Vessel

Marine Tank Vessel Number of Facilities Binned by Facility-Wide MIR (in 1 million) Source Category MIR Contribution to Facility-Wide <1 1 ≤ MIR<10 10 ≤ MIR<100 > 100 Total43

MIR

> 90% 68 0 1 0 69
50-90% 3 0 1 0 4
10-50% 5 2 0 0 7
< 10% 39 20 13 0 72

Total 115 22 15 0 152

Analysis of potential differences between act ual emission levels and the maximum emissions
allowable under the MACT standards indicated that MACT allowable em ission levels may be up to 3 times greater than actual emission levels. Considering this difference, the risk results
from the inhalation risk assessment indicate that the maximum excess lifetime individual cancer risk could be up to 150 in a million, and that the maximum chronic noncancer TOSHI value could be as high as 2 at the MACT-allowable emissions level. In reality for the facility with the source category risk of 50, we believe the actual and allowable emissions to be the

same.



### 3.3 Pharmaceuticals production

3.3.1 Source category description and results

The pharmaceutical manufacturing process consis ts of chemical production operations that produce drugs and medication. These operations include chemical synthesis (deriving a drug’s active ingredient) and chemical formula tion (producing a drug in its final form). During pharmaceutical manufacturing operations, HAP emissions can occur from breathing and withdrawal losses from chemical storage ta nks, venting of process vessels, leaks from piping and equipment used to transfer HAP compounds (equipment leaks), and volatilization
of HAP from wastewater streams. HAP emitted from the pharmaceutical manufacturing process include hydrochloric acid, and a ra nge of volatile organic compounds, such as methylene chloride, methanol, N,N-dimethyl formamide, and toluene, among others. Pharmaceutical operations are typically batch pro cesses and highly plant-specific. We believe that there are 27 pharmaceutical manufacturing faci lities subject to the MACT regulations.

The data set for Pharmaceuticals Production co ntains emissions and facility data for the 27 facilities thought to be currently in operation and subject to the MACT standard. Only the emissions from these 27 facilities, totaling about 1,056 tons/year, we re included in our assessment. Refer to Appendix 1 for details on ho w the emissions inventory was developed.

Table 3.3-1 summarizes the emissions for the Pharmaceuticals Production data set. Based on the modeled data set, the HAP emitted in larges t quantities in total from these sources are methylene chloride, methanol, acetonitrile, toluen e, hexane, ethylene glyc ol, methyl tert-butyl ether, hydrochloric acid, N,N-dimethylformam ide, ethylene dichloride, xylenes, hydrogen fluoride, methyl chloride, triethylamine, met hyl isobutyl ketone, and chloroform. These 16 HAP account for 99 percent of the mass of HAP emissions in the data set for the Pharmaceuticals Production source category. Metha nol is reported as emissions from 23 of the 27 facilities (85 percent) in the data set. Methylene chloride, aceton itrile, and toluene are reported as emitted by at least 15 facilities (56 percent) each. Persistent and bioaccumulative44

HAP (PB HAP) 26 emissions in the data set for the pharmaceutical manufacturing source category include lead, mercury, and cadmium compounds as well as a range of polynuclear aromatic hydrocarbons (PAH).

Tables 3.3-2 and 3.3-3 provide information su mmarizing the health risks results for this
source category.

26 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 ANPRM 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

.45

Table 3.3-1 Summary of Emissions and Availability of Dose-Response Values for the Pharmaceuticals Production Source Category

HAP a Emissions (tpy) Number of
Facilities Reporting HAP (27
facilities in

data set) Prioritized Inhalation Dose-Response Value Identified by OAQPS b PBHAP

? Unit Risk
Estimate for

Cancer? Reference
Concentration
for Noncancer? Health
Benchmark
Values for Acute
Noncancer? Methylene Chloride 388 19 Υ Υ Υ

Methanol 322 23 Υ Υ

Acetonitrile 91 15 Υ Υ

Toluene 90 18 Υ Υ

Hexane 44 12 Υ Ethylene Glycol 36 2 Υ Methyl Tert-Butyl Ether 31 8 Υ Υ Υ Hydrochloric Acid 11 11 Υ Υ N,N-Dimethylformamide 11 9 Υ Υ Ethylene Dichloride 7 3 Υ Υ Υ Xylenes (Mixture of o, m, and p Isomers) 5 8 Υ Υ

Hydrogen Fluoride 5 2 Υ Υ Triethylamine 3 7 Υ Υ Methyl Chloride 3 3 Υ Υ Methyl Isobutyl Ketone 2 3 Υ

Chloroform 2 5 Υ Υ Ethyl Benzene 1 6 Υ Glycol Ethers 1 4 Υ Υ Cyanide & Compounds 0.6 5 Υ Formaldehyde 0.6 7 Υ Υ Υ Hydrogen Cyanide 0.5 1 Υ Υ Acetaldehyde 0.3 2 Υ Υ Υ Allyl Chloride 0.2 1 Υ Υ Υ

Benzene 0.2 5 Υ Υ Υ

Chloroacetic Acid 0.1 1 Υ Lead & Compounds 0.1 3 Υ Υ Manganese & Compounds 0.1 3 Υ

Chlorobenzene 0.09 3 Υ Υ Phosgene 0.08 1 Υ Υ

Cumene 0.06 1 Υ Υ 1-Chloro-2,3-Epoxypropane 0.05 2 Υ Υ Υ

Phenol 0.03 3 Υ Υ Acetophenone 0.02 2

Lead 0.01 2 Υ Υ p-Dioxane 0.01 1 Υ Υ Υ Hydrazine 0.009 1 Υ Υ Υ Methyl Iodide 0.008 1 Υ Quinoline 0.008 1 Phthalic Anhydride 0.004 1 Υ Υ46

Table 3.3-1 Summary of Emissions and Availability of Dose-Response Values for the Pharmaceuticals Production Source Category

HAP a Emissions (tpy) Number of
Facilities Reporting HAP (27
facilities in

data set) Prioritized Inhalation Dose-Response Value Identified by OAQPS b PBHAP

? Unit Risk
Estimate for

Cancer? Reference
Concentration
for Noncancer? Health
Benchmark
Values for Acute
Noncancer?
PAH, total 0.004 2 Υ Υ Dimethyl Sulfate 0.002 1 Υ Benzo[g,h,i]Perylene 0.0009 3 Υ Υ Cadmium & Compounds 0.0006 2 Υ Υ Υ Ethylene Glycol Methyl
Ether 0.0004 1 Υ Υ

Mercury & Compounds 0.00003 1 Υ Υ Υ

Acetamide 0.000002 1 Υ

Acrolein 0.0000006 1 Υ Υ Naphthalene 0.00000004 1 Υ Υ Chromium (VI) 0.00000002 1 Υ Υ

Phenanthrene 0.000000001 1 Υ Υ Nickel & Compounds 0.0000000003 1 Υ Υ Υ Pyrene 0.0000000003 1 Υ Υ

Fluoranthene 0.0000000002 1 Υ Υ

Fluorene 0.0000000002 1 Υ Υ Chromium & Compounds 0.0000000002 1 Υ Υ Arsenic & Compounds (Inorganic Including Arsine) 0.00000000003 1 Υ Υ Υ

Anthracene 0.00000000002 1 Υ Υ Cobalt & Compounds 0.00000000001 1 Υ Acenaphthene 0.00000000001 1 Υ Υ Acenaphthylene 0.00000000001 1 Υ Υ Benz[a]Anthracene 0.00000000001 1 Υ Υ Benzo[b]Fluoranthene 0.00000000001 1 Υ Υ Benzo[k]Fluoranthene 0.00000000001 1 Υ Υ Chrysene 0.00000000001 1 Υ Υ Indeno[1,2,3-c,d]Pyrene 0.00000000001 1 Υ Υ Benzo[a]Pyrene 0.000000000008 1 Υ Υ Dibenzo[a,h]Anthr acene 0.0000 00000008 1 Υ Υ Selenium & Compounds 0.0000000000004 1 Υ Beryllium & Compounds 0.0000000000002 1 Υ Υ Υ

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 “cad mium & compounds.”

b Specific dose-response values for each chemical are identif ied in Section 2.6.47

3.3.1 Risk characterization

This section presents the results of the ri sk assessment for the Pharmaceuticals Production source category. The basic chronic inhalation ri sk estimates presented here are the maximum individual lifetime cancer risk, the maximum chr onic hazard index, and the cancer incidence. We also present results from our acute inhalati on impact assessments in the form of maximum hazard quotients, as well as the results of our screen for potential non-inhalation risks from PB HAP. Also presented are the HAP “dri vers,” which are the HAP that collectively contribute 90 percent of the maximum cancer ri sk or maximum hazard at the highest exposure location, as well as a summary of the results of our facility-wide assessments and our analysis
of risks associated with the maximum allowed emissions under the current MACT standards. A detailed summary of the facility-specific risk assessment results is av ailable in Appendix 6.

Tables 3.3-1 and 3.3-2 summarize the preliminar y chronic and acute inha lation risk results for this source category. The maximu m individual cancer risk estimated for the 27 facilities in the Pharmaceutical Production source category is about 3 in a million. Four facilities
showed a maximum individual cancer risk a bove 1 in a million. The major pollutants contributing to these risks were ethylene dich loride, methylene chloride, and hydrazine. For these facilities, we estimated that there are a pproximately 0 people with individual cancer risk levels at or above 10 in a million and 2,000 peopl e with individual cancer risk levels at or
above 1 in a million. We also estimated that the total cancer incidence associated with the
inhalation of HAP emissions from the Phar maceuticals Production source category is 0.0008 cases per year or about 8 cases every 10,000 years. The emission source associated with the highest incidence for this source category is pr ocess vents, accounting for about 60% of the
total cancer incidence.

Chronic noncancer risks were determined to be insignificant, with a maximum chronic noncancer hazard index of 0.2, dominated by th e contribution from manganese emissions. Our acute screening assessment identified 1 f acility with potential acute impact concerns associated with acetonitrile emissions, indicating that this facility had the potential to exceed the AEGL-1 level by a factor of 2. The acute screening also identified 4 facilities with a potential to exceed the REL level for 5 po llutants – methylene chloride, methanol, acetonitrile, glycol ether, and chloroform.48

Table 3.3-2 Summary of Source Categor y Level Risks for Pharmaceuticals

Result HAP “Drivers” Facilities in Source Category Number of Facilities Estimated to be Subject to MACT in Source Category 27 n/a

Number of Facilities Identified in NEI and
Modeled in Risk Assessment 27 27 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 3 ethylene dichloride

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 0 n/a

Greater than or equal to 1 in 1 million 4 ethylene dichloride, methylene chloride, hydrazine

Chronic Noncancer Risks Maximum Neurological Hazard Index 0.2 manganese compounds Number of Facilities with Maximu m Neurological Hazard Index:
Greater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 4

2

0.06 methylene chloride (REL) acetonitrile (AEGL-1) acetonitrile (AEGL-2)

Number of Facilities With Potential for Acute
Effects 4 methylene chloride, methanol, , chloroform, glycol ethers, acetonitrile

Acute Noncancer Refined Results

Maximum Acute Hazard Quotient 2

0.5 chloroform (REL) acetonitrile (AEGL-1)

Number of Facilities With Potential for Acute
Effects 2 glycol ethers, chloroform

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 36,000,000 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 0 n/a Greater than or equal to 1 in 1 million 2,000 n/a Number of People Exposed to Neurological Hazard Index : Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.0008 n/a

Contribution of HAP to Cancer Incidence

27 After the risk assessment was completed, it was learned that the Bristol Myers Squibb facility in Barceloneta, PR closed in 2009. Because the facility was operating at the time of the assessment, it remains in the data set at this time. It does not have the highest maximum individual lifetime cancer risk estimate, the highest hazard index estimate, or the highest acute hazard quotient estimate.49

Result HAP “Drivers” methylene chloride 58% n/a Hydrazine 20% n/a ethylene dichloride 14% n/a

For the facilities that exceeded acute thresholds in the screen ing assessment, we refined the assessment by plotting receptors on facility aerial photographs and determining maximum offsite concentrations. Once we performed thes e refinements, the estimated maximum offsite HQ value for methanol dropped to 0.9 (based on the REL), for acetonitrile the value dropped to 0.5 (AEGL-1), and for methylene chloride the HQ value dropped to 1 (based on the REL). Only the estimated maximum offsite concentrations of chloroform and glycol ether were seen

to potentially exceed acute REL values at two faciliti es (maximum HQ REL = 2), and there were no exceedances of the next highest th reshold value for chloroform, the AEGL-2 (HQ AEGL-2 = 0.001) or glycol ether. Meteorological conditions leading to offsite exceedances
of the REL could occur as frequently as 13 hours pe r year, or about 0.1 percent of the time.
Details on the refined acute asse ssment can be found in Appendix 7.

Our assessment did identify some emissions of PB-HAP from this source category. Lead emissions at one facility were close to, but be low, our screening range level of 350 lb/yr. Since our screening level is based on the lo west end of the proposed range for a possible revised lead NAAQS, we believe lead emissions at this facil ity do not pose any significant potential for multipathway risks. None of the other emissions were seen to pose any potential for multipathway risks based on the application of the PB-HAP screening scenario developed using the TRIM.FaTE model (see Appendix 5 for details). Thus, our assessment did not identify any potential for this source category to pose significant chro nic non-inhalation risks, nor did we identify any potential fo r adverse environmental impacts.

Based on our direct interaction wi th the facilities in this source category and on the lack of comments to the contrary to our NPRM, we have a high degree of confidence that our assessment covers the entire source category an d that we have accurately characterized the emissions. As such, we believe that the e xposure portion of our assessment reasonably represents maximum chronic inhalation exposur es and total population exposures for the purpose of estimating cancer incidence.50Table 3.3-3 Summary of Acute Refined Results for Pharmaceuticals ProductionRefined ResultsMAXIMUM ACUTE HAZARDQUOTIENTSACUTE DOSE-RESPONSE VALUESHAPMax. 1-hr.Air Conc.(mg/m3)Based onRELBased onAEGL-1/ERPG-1Based onAEGL-2/ERPG-2REL(mg/m3)AEGL-1(1-hr)(mg/m3)ERPG-1(mg/m3)AEGL-2(1-hr)(mg/m3)ERPG-2(mg/m3)acetonitrile 10 n/a 0.5 0.02 22 540chloroform 0.3 2 n/a 0.001 0.15 310 310glycol ethers 0.2 2 n/a n/a 0.093methanol 25 1 0.1 0.001 28 690 690 2700 2700methylene chloride 18 1 0.08 0.001 14 690 690 1900 1900Notes on Process:1)The screening was performed for all emitted HAP with available acute dose-response values. Onlythose pollutants whose screening HQs were greater than 1 for at leastone acute threshold valueare shown in the table.2)HAP with available acutedose-response values which are not in the table donot carry any potential forposing acute health risks, based on an analysis of currentlyavailable emissions data.Notes on Acute Dose-Response Values:REL – California EPA reference exposure level for no adverseeffects. Most, but not all,RELs are for 1-hour exposures.AEGL – Acute exposure guideline levels represent emergency exposure (1-hour) limits for the general public.AEGL-1 is the exposure level above which it is predicted that the general population, including susceptible individuals, could experience effects that are notablediscomfort, but which are transient andreversible upon cessation of exposure.AEGL-2 is the exposure level above which itis predicted that the general population, including susceptible individuals, couldexperience irreversible or other serious,long-lasting adverse health effects ofan impaired ability to escape.ERPG – Emergency RemovalProgram 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, transientadverse health effects.ERPG-2 is the maximum exposure below which itis believed that nearly all individuals could be exposed for up to 1 hour withoutexperiencing or developingirreversible or other serious health effects or symptoms which could impair an individual’s ability to take protective action.51

The facility-wide MIR and HI available in Appe ndix 6 are based on emissions, as identified in the NEI database, from all emissions sources at the identified facilities. The results of the facility-wide MIR are summarized in Table 3.3-4. The maximum facility-wide risks are estimated to be a cancer MIR of 40 in a million and a HI of 0.8, both of which occur at the same facility. The source category contribution to the facility-wide risk at this facility is minimal; the cancer MIR is 0.005 in a million and the maximum noncancer HI is zero for respiratory/neurological and 0.00001 for liver. In contrast, th ere are other facilities where the source category impacts dominate the facility-wid e risk. For example, one of the facilitieswith the highest cancer source category MIR (3 in a million) contributes 75% to its facilitywide cancer MIR of 4 in a million.

Table 3.3-4 Summary Category Contribution to Facility-Wide Cancer Risks -
Pharmaceuticals

Pharmaceuticals Production Number of Fa cilities Binned by Facility-Wide MIR (in 1 million) Source Category MIR Contribution to Facility-Wide

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

> 90% 6 1 0 0 7
50-90% 7 4 0 0 11
10-50% 0 1 0 0 1
< 10% 5 2 1 0 8

Total 18 8 1 0 27

Analysis of potential differences between act ual emission levels and the maximum emissions
allowable under the MACT standards indicated that MACT allowable em ission levels may be up to 25% greater than actual emission levels. Considering this difference, the risk results
from the inhalation risk assessment indicate that the maximum excess lifetime individual cancer risk could be up to 4 in a million, a nd that the maximum chronic noncancer TOSHI value could be as high as 0.3 at th e MACT-allowable emissions level.



### 3.4 Epichlorohydrin el astomers production

3.4.1 Source category description and results

Epichlorohydrin elastomers are widely us ed in the automotive industry. The main epichlorohydrin elastomers are polyepichlorohydrin, epi-ethylene oxide (EO) copolymer, epiallyl glycidyl ether (AGE) copolymer, and epi-EO-AGE terpolymer. The primary HAP emitted during production are epichlorohydrin and to luene. Sources of HAP emissions for the epichlorohydrin elastomer source category in clude raw material storage vessels, front-end52

process vents, back-end process operations, wast ewater operations, and equipment leaks. The majority of the emissions come from equipment leaks. The process "front-end" includes prepolymerization, reaction, stripp ing, and material recovery ope rations; and the process "backend" includes all operations af ter stripping (predominately drying and finishing). When EPA developed the proposed MACT rule in 1995, only one facility was identified for the epichlorohydrin elastomer production source category.

From information gathered during the MACT development and in more recent contacts with the industry, the number of operating major sour ce facilities with pro cesses belonging in the Epichlorohydrin Elastomers Production source ca tegory is one. EPA identified this one facility in Version 1.0 of the 2002 NEI (Feb ruary 2006). Based on existing NEI data of MACT codes, SCC codes, and pollutants emitted, EPA then identified the processes at each facility believed to be in the Epichlorohydr in Elastomers Production source category, and replaced the information in the NEI for these pr ocesses with data collected directly from the industry in 2004 as part of pre liminary residual risk efforts. The data for this one facility comprised the data set for this source categor y with a total of 106 tons/year HAP emitted into the atmosphere. We believe that this one facility represents the complete source category, with a total of 106 tons/year HAP emitted into th e atmosphere. This facility was the only one included in the assessment. Refer to Appendix 1 for details on how the emissions inventory changed.

Table 3.4-1 summarizes the emissions for th e Epichlorohydrin Elastomers Production source category. Emissions of toluene, the primary solvent in the process, account for over 99 percent of the total emissions. Epichlorohydrin represents a much smaller percent of the total emissions, as most of this monomer reacts in th e process to form the final product and is not available to be emitted to the atmosphere. No persistent and bioaccumulative HAP (PB HAP) emissions were reported for this facility.

Table 3.4-2 provides information summarizing hea lth risks results for this source category.

Table 3.4-1 Summary of Emissions and Ava ilability of Dose-Response Values for the Epichlorohydrin Elastomers Production Source Category

HAP Emissions (tpy) Number
of
Facilities Reporting

HAP (1 facility in data set) Prioritized Inhalation Dose-Response Value Identified by OAQPS a

PBHAP? Unit Risk
Estimate
for
Cancer? Reference
Concentration
for Noncancer? Health Benchmark
Value for Acute

Noncancer?

Toluene 44 1 Υ Υ Epichlorohydrin 0.4 1 Υ Υ Υ Ethylene Oxide 0.09 1 Υ Υ Υ

3.4.2 Risk characterization53

This section presents the results of the risk assessment for the Epichlorohydrin Elastomers Production source category. The ba sic chronic inhalation risk estim ates presented here are the maximum individual lifetime cancer risk, the ma ximum chronic hazard index, and the cancer incidence. We also present results from our acute inhalation impact assessments in the form of maximum hazard quotients, as well as the re sults of our screen for potential non-inhalation risks from PB HAP. Also presented are th e HAP “drivers,” which are the HAP that collectively contribute 90 percent of the ma ximum cancer risk or maximum hazard at the highest exposure location, as well as a summary of the results of our facility-wide assessments and our analysis of risks associated with the maximum allowed emissions under the current MACT standards. A detailed summary of the f acility-specific risk assessment results is available in Appendix 6.

Table 3.4-1 summarizes the preliminary chronic and acute inhalation risk results for this source category. The maximum individual cancer risk estimated for the 1 facility in the Epichlorohydrin Elastomers Production source ca tegory is about 10 in a million. The major pollutants contributing to these risks were ethylene oxide a nd epichlorohydrin. For the facility, we estimated th at there are approximately 90 people with individual cancer
risk levels at or above 10 in a million and 800 people with individual ca ncer risk levels at
or above 1 in a million. We also estimated th at the total cancer incidence associated with
the inhalation of HAP emissions from th e Epichlorohydrin Elastomers Production source category is 0.0001 cases per year or about 1 case every 10,000 years. The emission source associated with the highest incidence for this source category is equipment leaks, accounting for about 75% of th e total cancer incidence.

Chronic noncancer risks were determined to be insignificant, with a maximum chronic noncancer hazard index of 0.1, dominated by the contribution from epichlorohydrin emissions. Our assessment did not identify any potential for this source category to pose significant acute inhalation risk s, chronic non-inhalation risks, or adverse environmental impacts.54

Table 3.4-2 Summary of Source Category Leve l Risks for Epichlorohydrin Elastomers
Production

Result HAP “Drivers” Facilities in Source Category Number of Major Source Facilities Estimated to be in Source Category 1 n/a

Number of Facilities Identified in NEI and
Modeled in Risk Assessment 1 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 10 a ethylene oxide

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 1 ethylene oxide Greater than or equal to 1 in 1 million 1 ethylene oxide

Chronic Noncancer Risks Maximum Respiratory Hazard Index 0.1 epichlorohydrin Number of Facilities with Maximu m Respiratory Hazard Index:
Greater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 0.2

0.01

0.003 epichlorohydrin (REL) epichlorohydrin (AEGL-1) ethylene oxide (ERPG-2)

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

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 218,000 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 90 n/a Greater than or equal to 1 in 1 million 800 n/a Number of People Exposed to Respiratory Hazard Index : Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.0001 n/a

Contribution of HAP to Cancer Incidence ethylene oxide 98% n/a epichlorohydrin 2% n/a

Notes:

a The highest maximum individual lifetime can cer risk for any epichlorohydrin elastomers facility was estimated as 30 in 1 milli on. However, the coordinates given for southwest corner of the area source (i.e ., the fugitive emissions) are belie ved to be incorrect, so the r esults using those coordinates are not reported. The maximum risks presented in th e table are those estimated using the best estimate of the emis sion point’s actual
location.

The facility-wide MIR and HI available in Appe ndix 6 are based on emissions, as identified in the NEI database, from all emissions sources at the identified facility. The results of the facility-wide MIR are summarized in Table 3.4- 3. The maximum facility-wide risks at the one55

facility with an operating epichlorohydrin elastomers process are estimated to be a cancer
MIR of 10 in a million and a noncancer HI of 0. 5. The source category contribution to the facility-wide risk at this facility is 100% for the MIR and 20% for the HI.

Table 3.4-3 Source Category Contribution to Facility-Wide Cancer Risks - Epichlorohydrin

Epichlorohydrin Elastomers
Production Number of Facilities Binned by Facility-Wide MIR (in 1 million) Source Category MIR Contribution to Facility-Wide

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

> 90% 1 1
50-90%

10-50%

< 10%

Total 1 1

The MACT-allowable emissions from this source category are estimated to be approximately the same as the modeled actual emissions; therefore, the risk results are equal.



### 3.5 Polybutadiene rubber production

3.5.1 Source category description and results

Polybutadiene rubber (PBR) is a homopolymer of 1,3-butadiene (i.e., 1,3-butadiene is the only monomer used in the production of th is polymer), and the PBR production source category includes any facility that polymeri zes 1,3-butadiene. Both the solution and emulsion polymerization processes are used to produce PBR, and the process can be conducted as either a batch or continuous pro cess. If the solution process is employed, the reaction is conducted in an organic solv ent (hexane or toluen e), which helps to dissipate heat generated by th e reaction and control the reaction rate. The primary HAP emitted during production include hexane, 1,3-butadiene, styrene, and toluene. Sources of HAP emissions include raw material storag e vessels, front-end process vents, back-end process operations, wastewater operations, and equipment leak s. The majority of the emissions come from back-end process operatio ns. The process "fr ont-end" includes prepolymerization, reaction, stri pping, and material recovery operations; and the process "back-end" includes all operations after stri pping (predominately drying and finishing). Most of the PBR manufactured in the U.S. is used in the production of tires in the
construction of the tread and sidewalls. PBR is also used as a modifier in the production of other polymers and resins (e.g., polystyr ene). When EPA developed the MACT rule,
five facilities were identified for the PBR source category.

From information gathered during the MA CT development and from more recent contacts with the industry, we estimated that there are five major source facilities with56

processes belonging in the Po lybutadiene Rubber Production s ource category. Refer to Appendix 1 for details on how the emissi ons inventory was developed.

Table 3.5-1 summarizes the emissions for the Polybutadiene Rubber Production source category data set. Of the five facilities, three utilize hexane as the solvent in their solution process, one facility uses toluene as its solvent, and the fifth uses a non-HAP organic solvent. Based on the data, the total HAP emissions by mass fr om these facilities are dominated by hexane and toluene that account for 70 and 23 percent of the total emissions, respectively. Styrene and 1,3-but adiene are reported as emissions from all five facilities and collectively account for about four percent of the total emissions. No persistent and bioaccumulative HAP (PB HAP) were reported fo r the facilities.

Table 3.5-2 provides information summarizing health risks for this source category.

Table 3.5-1 Summary of Emissions and Ava ilability of Dose-Response Values for the Polybutadiene Rubber Source Category

HAP a Emissions (tpy) Number
of
Facilities Reporting

HAP (5
facilities
in data

set) Prioritized Inhalation Dose -Response Value Identified by OAQPS

PBHAP? Unit Risk
Estimate for

Cancer? Reference
Concentration for
Noncancer? Health Benchmark
Values for Acute
Noncancer?

Hexane 1,584 4 Υ Υ

Toluene 510 2 Υ Υ
1,3-Butadiene 74 5 Υ Υ Υ
Styrene 68 5 Υ Υ Ethyl Benzene 23 1 Υ

Chlorobenzene 2 1 Υ Υ

Methanol 0.07 1 Υ Υ

Nickel 0.0007 1 Υ Υ Υ

3.5.2 Risk characterization

The maximum individual cancer risk estimated for the 5 facilities in the Polybutadiene Rubber Production source category is about 30 in a million, with this cancer risk being dominated by emissions of 1,3-butadiene. For these facilities, we estimated that there are approximately 20 people with individual cancer ri sk levels at or above 10 in a million, and 24,000 people with individual cancer risk levels at or above 1 in a million. We also estimated
that the total cancer incidence associated with the inhalation of these emissions is 0.003 cases per year, or about 3 cases every 1,000 year s. Even though “back-end” processes are the highest source of emissions, the emission source a ssociated with the highest incidence for this source category is “front end” process vents, accounting for about 50% of the total cancer
incidence.57

Chronic noncancer risks were determined to be insignificant, with a maximum chronic noncancer hazard index of 0.3, dominated by the contribution from 1,3-butadiene emissions. Our acute screening assessment identified 1 f acility with potential acute impacts of concern based on its toluene emissions, which indicate d the potential to exceed the acute REL by a factor of 12 (HQ REL = 10). Since the acute screening an alysis showed an acute value over 1 for this facility, a refined analysis was performe d. The results of this refinement showed the acute for this one facility would be at an REL of 1. Therefore, it is unlikely that offsite
concentrations near these facilities would resu lt in a significant acute exposure. Details on the refined acute assessment can be found in Appe ndix 7. Our assessment did not identify any potential for this source categor y to pose significant chronic non-inhalation risks or adverse environmental impacts.58

Table 3.5-2 Summary of Source Category Level Risks for Polybutadiene Rubber
Production

Result HAP “Drivers” Facilities in Source Category Number of Major Source Facilities Estimated to be in Source Category 5 n/a

Number of Facilities Identified in NEI and
Modeled in Risk Assessment 5 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 30 28 1,3-butadiene

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 2 1,3-butadiene Greater than or equal to 1 in 1 million 4 1,3-butadiene

Chronic Noncancer Risks Maximum Reproductive Hazard Index 0.3 1,3-butadiene Number of Facilities with Maximu m Reproductive Hazard Index:
Greater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 12

0.6

0.2 toluene (REL) toluene (AEGL-1) toluene (ERPG-2)

Number of Facilities With Potential for Acute
Effects 1 toluene

Acute Noncancer Refined Results Maximum Acute Hazard Quotient 1 toluene (REL)

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

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 1,700,000 n/a

Number of People Exposed to Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 20 n/a Greater than or equal to 1 in 1 million 24,000 n/a Number of People Exposed to Reproductive Hazard Index : Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.003 n/a

Contribution of HAP to Cancer Incidence 1,3-butadiene 98% n/a ethyl benzene 2% n/a

28 The individual source category risk is 20 in a million; however because of the close proximity of 2 facilities in the source category the highest predicted MIR fo r the source category is 30 in a million.59

The facility-wide MIR and HI available in Appe ndix 6 are based on emissions, as identified in the NEI database, from all emissions sources at the identified facility. The results of the facility-wide MIR are summarized in Table 3.5- 3. The maximum individual risk (MIR) and hazard index (HI) presented in the spreadsheet are based on emissions, as identified in the database, from all emissions sources at the id entified facility. The maximum facility-wide risks at the one facility with an operating st yrene butadiene process are estimated to be a
cancer MIR of 30 in a million a nd an HI of 0.3. The sour ce category contribution to the facility-wide risk at this facility is 90% for both the MIR and the HI.

Table 3.5-3 Source Category Contribution to Facility-Wide Cancer Risks - Polybutadiene

Polybutadiene Rubber Production Number of Facilities Binned by Facility-Wide MIR (in 1 million) Source Category MIR Contribution to Facility-Wide MIR <1 1 ≤ MIR<10 10 ≤ MIR<100 > 100 Total

> 90% 2 2 4
50-90%

10-50% 1 1
< 10%

Total 3 2 5

The MACT-allowable emissions from this source category are estimated to be approximately the same as the modeled actual emissions; therefore, the risk results are equal.



### 3.6 Styrene butadiene rubb er and latex production

3.6.1 Source category description and results

The styrene butadiene rubber and latex production source category includes any facility that manufactures copolymers consis ting of styrene and butadiene monomer units. This source category is divided into three subcategorie s due to technical pr ocess and HAP emission differences: (1) the production of styrene-buta diene rubber by emulsion, (2) the production of styrene-butadiene rubber by solution, and (3) the production of latex. Styrene-butadiene rubber is coagulated and dried, while late x is not. For both styrene-butadiene rubber processes, the monomers used are styrene and 1,3-butadiene; either process can be conducted as a batch or a continuous process.

The production of styrene butadiene rubber by emulsion is conducted in water containing monomers (styrene and 1,3-butad iene) and polymerization agents . Sources of HAP emissions for the emulsion subcategory include raw materi al storage vessels, front-end process vents, back-end process operations, wastewater operati ons, and equipment leaks. Most of the emissions come from back-end process operatio ns. The process "fr ont-end" includes prepolymerization, reaction, stripp ing, and material recovery ope rations; and the process "backend" includes all operations af ter stripping (predominately dryi ng and finishing). The primary HAP emitted by emulsion styrene butadiene rubber production are styrene and 1, 3-butadiene.60

Emulsion styrene butadiene rubber is used in the production of tires and other automobile parts, adhesives, floor tiles, gask ets, belts, hoses, and other products.

The production of styrene butadiene rubber is conducted in a so lution composed of hydrocarbon solvents, monomers, and polymerizati on agents. These facilities use hexane or
toluene as a solvent. Sources of HAP emi ssions for the solution subcategory include raw material storage vessels, front-end process ve nts, back-end process operations, wastewater operations, and equipment leaks. Most of the emissions come from back-end process operations (70 percent of total emissions at the time of MACT promulgation). The primary HAP emitted by production of solution styrene butadiene rubber are hexane, 1, 3-butadiene, styrene, and toluene. These products are used in footwear , conveyor belts, tires, hoses, flooring and adhesives.

Styrene butadiene latex is produced by the emulsion process (i.e., in water containing monomers and polymerization agents) in a proc ess similar to that used to make styrene butadiene by emulsion; however, at styrene butadiene latex faci lities, the final product is a latex and not a dried solid. The primary HAP emitted by styrene butadiene latex production are styrene and 1,3-butadiene. Sources of HAP emissions include raw material storage vessels, front-end process vent s, wastewater operations, and equipment leaks.

We continue to believe that there are six facili ties nationwide in this source category with a combined total of 303 tons/year of HAP emitted to the atmosphere. Refer to Appendix 1 for details on how the emissions inventory was developed.

Table 3.6-1 summarizes the emissions for the Styrene Butadiene Rubber and Latex Production source category data set. Styrene, 1,3-butadiene, ethyl benzene, xylenes, and carbon disulfide account for 99 percent of the em issions by mass. Styrene is the largest fraction of the total emissions by mass (90 percent) and is emitted by all 6 facilities. 1,3-butadiene is also reported as an emissi on by all 9 facilities and accounts for most of the remaining mass emitted (about 5 percent). No persistent and bioaccumulative HAP (PB HAP) were reported by the facilities.

Table 3.6-2 provides informati on summarizing the health risks results for this source
category.

Table 3.6-1 Summary of Emissions and Availability of Dose-Response Values for Styrene Butadiene Rubber and Latex Production

HAP Emissions (tpy) Number of
Facilities Reporting HAP

(6 facilities in data set) Prioritized Inhalation Dose-Response Value Identified by OAQPS a

PBHAP? Unit Risk
Estimate for

Cancer? Reference
Concentration
for Noncancer? Health
Benchmark
Values for Acute
Noncancer? Styrene 275 6 Υ Υ
1,3-Butadiene 14 6 Υ Υ Υ Ethyl Benzene 4 4 Υ Xylenes (Mixture of o, 4 2 Υ Υ61

m, and p Isomers)

Carbon Disulfide 3 1 Υ Υ Acrylic Acid 0.8 3 Υ Υ

Toluene 0.7 2 Υ Υ

Benzene 0.7 1 Υ Υ Υ

Methanol 0.6 1 Υ Υ Acrylonitrile 0.1 1 Υ Υ Υ Vinylidene Chloride 0.05 1 Υ Hydrochloric Acid 0.04 1 Υ Υ Ethyl Acrylate 0.04 1 Υ Methyl Methacrylate 0 1 Υ Υ

3.6.2 Risk characterization

The maximum individual cancer risk estimated fo r the 6 facilities in the Styrene Butadiene Rubber and Latex Production source category is a bout 10 in a million, with this cancer risk being dominated by emissions of 1,3-butadiene. For these facilities, we estimated that there are approximately 3 people with individual cancer risk levels at or above 10 in a million, and 25,000 people with individual cancer risk levels at or above 1 in a million. We also estimated
that the total cancer incidence as sociated with the inhalation of these emissions is 0.004 cases per year, or about 2 cases ever y 500 years. Even though “back-e nd” processes are the highest source of emissions, the emission source associated with the highest incidence for this source category is “front end” process vents, accounti ng for about 50% of the total cancer incidence.

Chronic noncancer risks were determined to be insignificant, with a maximum chronic noncancer hazard index of 0.2, dominated by the contribution from 1,3-butadiene emissions. Our acute screening assessment identified 1 f acility with potential acute impacts of concern based on its styrene emissions, which indicate d the potential to exceed the acute REL by a factor of 2 (HQ REL = 2). Since the acute screening anal ysis showed an acu te value over 1 for this facility, a refined analysis was performed. The results of this refinement showed the acute for this one facility would to be below 1 (HQ REL = 0.4). Details on the refined acute assessment can be found in Appendix 7. Our asse ssment did not identify any potential for this source category to pose significant chronic non- inhalation risks or adverse environmental impacts.62

Table 3.6-2 Summary of Source Category Leve l Risks for Styrene Butadiene – Rubber
and Latex Production

Result HAP “Drivers” Facilities in Source Category Number of Major Source Facilities Estimated to be in Source Category 6 n/a

Number of Facilities Identified in NEI and
Modeled in Risk Assessment 6 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 10 1,3-butadiene

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 1 1,3-butadiene Greater than or equal to 1 in 1 million 4 1,3-butadiene, acrylonitrile

Chronic Noncancer Risks Maximum Reproductive Hazard Index 0.2 1,3-butadiene Number of Facilities with Maximu m Reproductive Hazard Index:
Greater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 2

0.6

0.09 styrene (REL) styrene (AEGL-1) styrene (AEGL-2)

Number of Facilities With Potential for Acute
Effects 1 styrene

Acute Noncancer Refined Results Maximum Acute Hazard Quotient 0.4 styrene (REL)

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

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 6,700,000 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 3 n/a Greater than or equal to 1 in 1 million 25,000 n/a Number of People Exposed to Reproductive Hazard Index : Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.004 n/a

Contribution of HAP to Cancer Incidence 1,3-butadiene 98% n/a ethyl benzene 1% n/a

The facility-wide MIR and HI available in Appe ndix 6 are based on emissions, as identified in the NEI database, from all emissions sources at th e identified facilities. The facility with the maximum facility-wide risks is estimated to ha ve a cancer MIR of 70 in a million and an HI63

of 1. The source category contribution to the facili ty-wide risk at this fa cility is about 5% for the MIR and 10% for the HI. The facility with th e next highest MIR is 40 in a million with an HI of 1. The source category contribution to the facility wide MIR is 5% and 10% for the HI.

Table 3.6-3 Source Category Contribution to Facility-Wide Cancer Risks - Styrene

Styrene Butadiene Rubber and
Latex Production Number of Facilities Binned by Facility-Wide MIR (in 1 million) Source Category MIR Contribution to Facility-Wide MIR <1 1 ≤ MIR<10 10 ≤ MIR<100 > 100 Total

> 90% 1 1
50-90% 2 2
10-50% 1 1
< 10% 2 2

Total 1 2 3 6

The MACT-allowable emissions from this source category are estimated to be approximately the same as the modeled actual emissions; therefore, the risk results are equal.



### 3.7 Nitrile butadiene rubber production

3.7.1 Source category description and results

Nitrile butadiene rubber (NBR) is a copolymer of 1,3-butadiene a nd acrylonitrile, and the NBR production source category includes any fac ility that polymerizes 1,3-butadiene and acrylonitrile. The emulsion, bulk, or solvent pr ocesses can be used to produce NBR. Either a continuous or a batch process can be used in production of NBR. In the manufacturing of NBR, the initial polymerization and stripping steps are similar to those used in the production of latex, except that polymerization of latex is typically a higher c onversion reaction. The major difference between these two production pro cesses is that in th e production of nitrile butadiene rubber, the polymer is coagulated and dried, while in the production of latex, the stripped latex is simply blended with other sp ecialty ingredients to produce the final nitrile butadiene latex product. The dr ying and finishing steps that make up the back-end processes for nitrile butadiene rubber are significant s ources of HAP emissions. Other sources of HAP
emissions include raw material storage vessels, front-end process vents, wastewater operations, and equipment leaks. The proce ss "front-end" includes pre-polymerization, reaction, stripping, and material recovery operations; and the pr ocess "back-end" includes all operations after stripping (predominately dryi ng and finishing). Depending on its specific composition, NBR can be resistant to oil and chem icals, a property that facilitates its use in disposable gloves, hoses, seals, and a variety of automotive app lications. In 1995, four active
facilities were iden tified that produced nitrile butadiene rubber. At one facility, the NBR equipment was also used to produce styrene- butadiene by the emulsion process (SBRE), as well as styrene-butadiene latex (SBL). When EPA developed the MACT rule, four facilities
were identified for the nitrile butadiene rubbe r production source category. From more recent contacts with the industry, it is estimated that there is only one major source facility with processes belonging in the N itrile Butadiene Rubber Produc tion source category.64

The total emissions in the data set were 1.8 tons/year of HAP emitted to the atmosphere from the one remaining facility. Refer to Appendix 1 for details on how the emissions inventory was developed.

Table 3.7-1 summarizes the emissions for th e Nitrile Butadiene Rubber Production source category data set. 1,3-butadiene and acrylon itrile account for over 99 percent of the total HAP emissions. No persistent and bioaccumulative HAP (PB HAP) were emitted by the facilities in this source category.

Table 3.7-2 provides informati on summarizing the health risks results for this source
category.

Table 3.7-1 Summary of Emissions and Availability of Dose-Response Values for Nitrile
Butadiene Rubber Production

HAP Emissions (tpy) Number of
Facilities Reporting HAP

(1 facility in

data set) Prioritized Inhalation Dose-Response Value Identified by OAQPS

PBHAP? Unit Risk
Estimate for

Cancer? Reference
Concentration
for
Noncancer? Health
Benchmark
Values for Acute
Noncancer?
1,3-Butadiene 0.9 1 Υ Υ Υ Acrylonitrile 0.9 1 Υ Υ Υ

3.7.2 Risk characterization

The maximum individual cancer risk estimated fo r the one facility in the Nitrile Butadiene Rubber Production source category is about 2 in a million, with this cancer risk being dominated by emissions of acrylonitrile. For th is facility, we estimated that there are no people with individual cancer risk levels at or above 10 in a million, and 70 people with
individual cancer risk le vels at or above 1 in a million. We also estimated that the total cancer
incidence associated with the inhalation of th ese emissions is 0.0004 cases per year, or less than 1 case every 1,000 years.

Chronic noncancer risks were determined to be insignificant, with a maximum chronic noncancer hazard index of 0.009, dominated by the contribution from 1,3-butadiene emissions. Our acute screening assessment re sulted in no potential acute risk above 1.65

Table 3.7-2 Summary of S ource Category Level Risks for Nitrile Butadiene Rubber
Production

Result HAP “Drivers” Facilities in Source Category Number of Major Source Facilities Estimated to be in Source Category 1 n/a

Number of Facilities Identified in NEI and
Modeled in Risk Assessment 1 n/a

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 2 acrylonitrile, 1,3-butadiene

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 0 n/a Greater than or equal to 1 in 1 million 1 acrylonitrile, 1,3-butadiene

Chronic Noncancer Risks Maximum Reproductive Hazard Index 0.009 1,3-butadiene Number of Facilities with Maximu m Reproductive Hazard Index:
Greater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 0.001

0.00009 acrylonitrile (AEGL-1) acrylonitrile (ERPG-2)

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

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 1,000,000 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 0 n/a Greater than or equal to 1 in 1 million 70 n/a Number of People Exposed to Reproductive Hazard Index : Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.0004 n/a

Contribution of HAP to Cancer Incidence acrylonitrile 72% n/a 1,3-butadiene 28% n/a

The facility-wide MIR and HI available in Appe ndix 6 are based on emissions, as identified in the NEI database, from all emissions sources at the identified facility. The maximum facilitywide risks at the one facility with an operating nitrile butadiene process are estimated to be a
cancer MIR of 5 in a million and an HI of 0.03. The source category contribution to the facility-wide risk at this facility is about 30% for both the MIR and HI.66

Table 3.7-3 Source Category Contribution to Fa cility-Wide Cancer Risks – Nitrile Butadiene

Nitrile Butadiene Rubber
Production Number of Facilities Binned by Facility-Wide MIR (in 1 million) Source Category MIR Contribution to Facility-Wide MIR <1 1 ≤ MIR<10 10 ≤ MIR<100 > 100 Total

> 90%

50-90%

10-50% 1 1
< 10%

Total 1 1

The MACT-allowable emissions from this source category are estimated to be approximately the same as the modeled actual emissions; therefore, the risk results are equal.



### 4 General discussion of uncertainties and how they have been
addressed

While each of the source-category-specific secti ons presented earlier in this document discuss specific uncertainties unique to each cat egory, the following ge neral discussion of uncertainties applies to all of them.

4.1 Exposure modeling uncertainties

Although every effort has been made to identify a ll the relevant facilities and emission points, as well as to develop accurate estimates of the annual emission rates for all relevant HAP, the uncertainties in our emission inventory likely dominate the uncertainties in our exposure modeling estimates. The chronic exposure modeli ng uncertainties are considered relatively small in comparison, since we are using EPA’s refined local dispersion model with reasonably representative meteorology. It is po ssible that population exposure estimates are also biased slightly higher by not accounting fo r short- or long-term population mobility, and by neglecting processes like de position, plume depletion, and atmospheric degradation. Additionally, estimates of the maximum individu al risk (MIR) contain uncertainty, because they are derived at census bloc k centroid locations rather than actual residences. This uncertainty is known to create potential underes timates 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 chro nic 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 peri od, leading to a potential
downward bias in both the MIR and population risk estimates.

A sensitivity analysis performed for the 1999 NATA found that th e selection of the meteorology dataset location could result in a ra nge of chronic ambient concentrations which67

varied from as much as 17% below the predic ted value to as much as 84% higher than the predicted value. This va riability translates directly to the predicted exposures and risks in our assessment, indicating that the actual risks could vary from 17 % lower to 84% higher than the predicted values.

We have purposely biased the acute screening results high, consideri ng that they depend upon the joint occurrence of independent factors, su ch as hourly emissions rates, meteorology and human activity patterns. Furthermore, in cas es where multiple acute threshold values are considered scientifically accep table we have chosen the most conservative of these assessments, erring on the side of overestimating potential health risks from acute exposures. In the cases where these results indicated the potential for exceeding short-term health thresholds, we have refined our assessme nt by developing a better understanding of the geography of the facility relative to potential exposure locations and the true variability of
short-term emission rates. In each of these cases, we have determined that this refined
information reduced the likelihood of acute health concerns.

4.2 Uncertainties in the do se-response relationships

In the sections that follow, se parate discussions are provided on uncertainty associated with cancer potency factors and for noncancer reference values. Cancer potency values are derived for chronic (lifetime) exposures. Noncancer reference values are generally derived for chronic exposures (up to a lifetime), but may also be derived for acute (

 <24 hours), short-term (>24 hours up to 30 days), and subchronic (> 30 days up to 10% of lifetime) exposure durations, all of which are derived based on an assumption of con tinuous exposure throughout the duration specified. For the purposes of assess ing all potential health risks associated with
the emissions included in this assessment, we rely on both ch ronic (cancer and noncancer) and acute (noncancer) benchmarks, which are described in more detail below.

Although every effort is made to identify p eer-reviewed dose-respons e values for all HAPs emitted by the sources included in this assessment, some HAP have no peer-reviewed cancer potency values or reference values for chroni c non-cancer or acute effects (inhalation or ingestion). Since exposures to these pollutants cannot be incl uded in a quantitative risk estimate, an understatement of risk for these po llutants at environmental exposure levels is possible.

Additionally, chronic dose -response values for certain compo unds included in this assessment may be under EPA IRIS review and revised asse ssments may determine that these pollutants are more or less potent than curr ently thought. We will re-evaluate risks if, as a result of these reviews, a dose-response metric changes enough to indicate that the risk assessment may significantly mischaracterize human health risk.

Cancer assessment

The discussion of dose-response uncertainties in the estimation of cancer risk below focuses on the uncertainties associated with the specifi c approach currently used by the EPA to develop cancer potency factors. In general, these same uncertainties attend the development68

of cancer potency factors by CalEPA, the sour ce of peer-reviewed cancer potency factors used where EPA-developed values are not yet ava ilable. To place this discussion in context, we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment .[ 37 ] (herein
referred to as Cancer Guidelines ). “The primary goal of EPA actions is prot ection of human health; accordingly, as an Agency policy, ri sk assessment procedures, including default options that are used in the absence of scien tific data to the cont rary, should be health protective.” The approach adopt ed in this document is consis tent with this approach as
described in the Cancer Guidelines

.

For cancer endpoints EPA usually derives an oral slope factor for inge stion and a unit risk value for inhalation exposures. These values allow estimation of a lifetime probability of developing cancer given long-term exposures to the pollutant. Depending on the pollutant being evaluated, EPA relies on both animal bioassay and epidemiological studies to
characterize cancer risk. As a science policy approach, consistent with the Cancer
Guidelines , EPA uses animal cancer bioassays as i ndicators of potential human health risk
when other human cancer risk data are unavailable.

Extrapolation of study data to estimate poten tial 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 ri sk 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). 29 In some circumstances, the true risk could be as low as zero; howev er, in other circumstances the risk could also be greater. 30 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. 31 EPA also uses the upper bound (rather than lower bound or centr al) estimates in its assessments, although it is noted that this approach can have limitations for some uses (e.g. priority setting, expected benefits analysis).

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

30 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.

31 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “ [Default] options are generic approaches, based on general scientific knowle dge and policy judgment, that are applied to various elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions
are used to ensure that risk to chemicals is not under estimated (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://w ww.epa.gov/osa/pdfs/ratf-final.pdf.69

Such health risk assessments have associated uncertainties, some wh ich may be considered quantitatively, and others which generally are ex pressed qualitatively. Uncertainties may vary substantially among cancer risk a ssessments associated with expos ures to different pollutants, since the assessments employ different database s with different strengt hs and limitations and the procedures employed may differ in how well they represent actual biological processes for
the assessed substance. EPA’s Risk Characterization Handbook also recommends that risk characterizations present estimat es demonstrating the impact on the assessment of alternative choices, data, models and assumptions [ 38 ]. Some of the major sources of uncertainty and variability in deriving cancer risk valu es are described more fully below.

(1) The qualitative similarities or differen ces between tumor responses observed in experimental animal bioassays and those wh ich would occur in humans is a source of uncertainty in cancer risk assessment. In ge neral, EPA does not assume that tumor sites observed in an experimental animal bioassay ar e necessarily predictive of the sites at which
tumors would occur in humans. 32 However, unless scientific support is availa ble to show otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target organ concordance. For a specific pollutant, quali tative differences in species responses can
lead to either under-estimation or over-e stimation of human cancer risks.

(2) Uncertainties regarding the most appropr iate 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 concentrati on of the pollutant. However, data may support development of a pharmacokinetic model for the absorption, distribution, metabolism and ex cretion 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 uncerta inties result when the appropriate choice of a
dose metric is uncertain or when dose metric es timates are themselves uncertain (e.g., as can occur when alternative pharmacokinetic models are available for a compound). Uncertainty in dose estimates may lead to eith er over or underestimation of risk.

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

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which there is a specified excess risk of cancer, which is used as the point of departure

32 Per the EPA Cancer Guidelines: “The default option is that positive effects in animal cancer studies indicate that the agent under study can have carcinogenic potential in humans.” and “Target organ concordance is not a prerequisite for evaluating the implications of animal study results for humans.”70

(or POD) for the remainder of the calculation. Statistical uncertainty in developing a POD using a benchmark dose (BMD) approach is ge nerally addressed though use of the 95% lower confidence limit on the dose at which the sp ecified excess risk occurs (the BMDL), decreasing the likelihood of understating risk. EPA has generally utilized the multistage model for estimation of the BMDL using cancer bioassay data (see furt her discussion below).

(5) Extrapolation from high to low doses is an important, and potentially large, source of uncertainty in cancer risk assessment. EP A uses different approaches to low dose risk assessment (i.e., developing estimates of risk for exposures to environmental doses of an agent from observations in experimental or ep idemiological studies at higher dose) depending
on the available data and understa nding of a pollutant’s mode of action (i.e., the manner in which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use of reliable, compound-specific, bi ologically-based risk models when feasible; however, such models are rarely available. The mode of action for a pollutant (i.e., the manner in which a pollutant causes cancer) is a key considerati on in determining how ri sks should be estimated for low-dose exposure. A reference value is calculated when the available mode of action data show the response to be nonlinear (e.g., as in a threshold response). A linear low-dose (straight line from POD) approach is used when available mode of action data support a linear (e.g., nonthreshold response) or as the most common default approach when a compound’s mode of action is unknown. Linear extrapolatio n can be supported by both pollutant-specific
data and broader scientific cons iderations. For example, EPA’s Cancer Guidelines generally consider a linear dose-response to be appropria te for pollutants that interact with DNA and
induce mutations. Pollutants whose effects ar e additive to background biological processes in cancer development can also be predicted to have low-dose linear responses, although the slope of this relationship may not be the same as the slope estimated by the straight line approach.

EPA most frequently utilizes a linear low-dose ex trapolation approach as a baseline sciencepolicy choice (a “default”) when available data do not allow a compound-specific determination. This approach is designed to not underestimate risk in the face of uncertainty and variability. EPA believes that linear dos e-response models, when appropriately applied as part of EPA’s cancer risk assessment proc ess, provide an upper bound estimate of risk and generally provide a health protec tive approach. Note that another source of uncertainty is the
characterization of low-dose non linear, non-threshold relationships. The National Academy of Sciences has encouraged the exploration of sigmoidal type functions (e.g., log-probit models) in representing dose res ponse relationships due to the variability in response within human populations. A recent National Research Council report (NRC, 2006) 33 suggests that
models based on distributions of individual thresholds are likely to lead to sigmoidal-shaped dose-response functions for a popul ation. This report notes so urces of variability in the human population: “One might expect these in dividual tolerances to vary extensively in humans depending on genetics, co incident exposures, nutritional status, and various other susceptibility factors...” Thus , if a distribution of thresholds approach is considered for a carcinogen risk assessment, application would depend on ability of modeling to reflect the degree of variability in respons e in human populations (as opposed to responses in bioassays

33 NRC (National Research Council) 2006. Assessing the Human Health Risks of Trichloroethylene. National Academies Press, Washington DC71

with genetically more uniform rodents). Note al so that low dose linearity in risk can arise for reasons separate from population variability: du e to the nature of a mode of action and additivity of a chemical’s effect on top of background chemical exposures and biological

processes.

As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight line approach from the BMDL. This is equiva lent to using an upper confidence limit on the slope of the straight line extrap olation. The impact of the choice of the BMDL on bottom line risk estimates can be quantified by comparing ri sk estimates using the BMDL value to central estimate BMD values, although these differences are generally not a large contributor to uncertainty in risk assessment (Subramaniam et. al., 2006) [ 39 ]. It is important to note that earlier EPA assessments, including the majority of those for which risk values exist today, were generally developed using the multistage model to extrapolate down to environmental
dose levels and did not involve the use of a P OD. Subramaniam et al (2006) also provide comparisons indicating that slopes based on st raight line extrapolation from a POD do not show large differences from those based on the upper confidence limit of the multistage
model.

(6) Cancer risk estimates do not generally make specific adjustments to reflect the variability in response within the human population — resulting in another source of uncertainty in assessments. In the diverse hum an population, some individuals are likely to
be more sensitive to the action of a carci nogen than the typical individual, although compound-specific data to evaluate this variability are generally not available. There may also be important life stage differences in th e 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, ri sk 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 te sted, resulting typically in the highest URE which can be supported by reliable data, thus supporting estimates that are designed not to
underestimate risk in the face of uncertainty and variability.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure leve ls that are intended to be health-protective. That is, EPA and other or ganizations which develop noncancer reference values (e.g., the Agency for Toxic Substances and Disease Registry – ATSDR) utilize an approach that is intended not to underestimate risk in the face of uncertainty and variability. When there are gaps in the available informa tion, uncertainty factors (UFs) are applied to
derive reference values that are intended to be protective against appreciable risk of deleterious effects. Uncertainty factors are commonly default values 34 e.g., factors of 10 or 3,

34 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are generic approaches, based on general scientific knowle dge and policy judgment, that are applied to various elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to72

used in the absence of compound-specific data; wh ere data are available, uncertainty factors may also be developed using compound-specific in formation. When data are limited, more assumptions are needed and more default fact ors are used. Thus there may be a greater tendency to overestimate risk—in the sense th at further study might support development of reference values that are higher (i.e., less potent) because fewer default assumptions are needed. However, for some pollutants it is possible that risks ma y be underestimated.

For non-cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) for exposures via ingestion, and a Reference C oncentration (RfC) for inhalation exposures. These values provide an estimate (with uncerta inty spanning perhaps an order of magnitude) of daily oral exposure (RfD) or of a conti nuous inhalation exposure (RfC) to the human population (including sensitive subgroups) that is lik ely to be without an appreciable risk of deleterious effects during a lifetime. 35 To derive values that are intended to be “without appreciable risk,” EPA’s met hodology relies upon an uncertain ty factor (UF) approach [ 40 ],[ 41 ] which includes consideration of both uncertainty and variability.

EPA begins by evaluating all of the availabl e peer-reviewed literature to determine noncancer endpoints of concern, ev aluating the quality, strengths and limitations of the available studies. EPA typically chooses th e relevant endpoint that occu rs at the lowest dose, often using statistical modeling of the available data, and then determines the appropriate point of departure (POD) for derivation of the reference va lue. A POD is determined by (in order of preference): (1) a statistical estimation using the benchmark dos e (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 defau lt UFs is then applied to the POD to estimate the reference value [ 42 ]. While collectively termed “U Fs”, these factors account for a number of different quantitative consideratio ns 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 fr om experimental animal data to humans (i.e., interspecies differences); (3) uncertainty in ex trapolating from data obtained in a study with less-than-lifetime exposure (i.e., extrapolati ng 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 pr oblems with applicability of available studies. When scientifically sound, peer-reviewed assess ment-specific data are not available, default adjustment values are selected for the indivi dual UFs. For each type of uncertainty (when relevant to the assessment), EPA typically applie s an UF value of 10 or 3 with the cumulative

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 under estimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An examination of EPA Risk Assess ment Principles and Practices, EPA/100/B-04/001 available at: http://w ww.epa.gov/osa/pdfs/ratf-final.pdf.

35 See IRIS glossary73

UF value leading to a downward adjustment of 10-3000 fold from the selected POD. An UF of 3 is used when the data do not support the use of a 10-fold factor. If an extrapolation step or adjustment is not relevant to an assessment (e.g., if applyi ng 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 sour ce of variability as well as uncertainty. Uncertainty related to human variation is consid ered in extrapolating doses from a subset or smaller-sized population, often of one sex or of a narrow range of life stages (typical of occupational epidemiologic studies), to a larger , more diverse population. In the absence of pollutant-specific data on human variation, a 10 -fold UF is used to account for uncertainty
associated with human variation. Human variatio n may be larger or smaller; however, data to examine the potential magnitude of human va riability are often una vailable. In some situations, a smaller UF of 3 ma y be applied to reflect a known l ack of significant variability among humans.

2) Extrapolation from results of studie s in experimental animals to humans is a necessary step for the majority of chemical risk assessments. When interpreting animal data, the concentration at the POD (e.g. NOAEL, BM DL) in an animal model (e.g. rodents) is extrapolated to estimate the human response. While there is long-sta nding scientific support
for the use of animal studies as indicators of potential toxicity to humans, there are uncertainties in such extrapolations. In the absence of data to the contrary, the typical approach is to use the most relevant endpoint from the most sensitive species and the most sensitive sex in assessing risks to the averag e human. Typically, compound specific data to evaluate relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty in this extrapolation. Size-related differences (allometric relationships) indicate that typically
humans are more sensitive than rodents when compared on a mg/kg/day basis. The default choice of 10 for the interspecies UF is consis tent with these differe nces. For a specific chemical, differences in species responses may be greater or less than this value.

Pharmacokinetic models are useful to examine species differences in pharmacokinetic processing and associated uncertainties; however , such dosimetric adjustments are not always possible. Information may not be available to quantitatively asse ss toxicokinetic or toxicodynamic differences between animals a nd 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 as sociated 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 availabl e and accounted for in the cross-species extrapolation, a UF of 3 may be used for the remaining component.

3) In the case of reference values for ch ronic exposures where only data from shorter durations are available (e.g., 90- day subchronic studies in rodent s) or when such data are judged more appropriate for development of an RfC, an additional UF of 3 or 10-fold is typically applied unless th e available scientific information supports use of a different value.74

4) Toxicity data are typically limited as to the dose or exposure levels that have been tested in individual studies; in an animal st udy, for example, treatment groups may differ in exposure by up to an order of magnitude. The pref erred approach to arrive at a POD is to use BMD analysis; however, this approach requires ad equate 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 wh ich an adverse effect is not observed (i.e., a NOAEL is not identified). When using data lim ited to a LOAEL, a UF of 10 or 3-fold is often applied.

5) The database UF is intended to a ccount for the potential for deriving an underprotective RfD/RfC due to a data gap pr eventing complete char acterization of the chemical’s toxicity. In the absence of studies for a known or suspected endpoint of concern, a UF of 10 or 3-fold is typically applied.

Acute noncancer assessment

Many of the UFs used to account for variability and uncertainty in the development of acute reference values are quite similar to those de veloped for chronic durations, but more often using individual UF values that may be less than 10. UFs are applied based on chemicalspecific or health effect-specific informati on (e.g., simple irritation effects do not vary appreciably between human indivi duals, hence a value of 3 is t ypically used), or based on the purpose for the reference value (see the followi ng paragraph). The UFs applied in acute reference value derivation include: 1) he terogeneity 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 da tabase on toxic effects of potential concern. Additional adjustments are often applied to a ccount for uncertainty in extrapolation from observations at one exposure dura tion (e.g., 4 hours) to arrive at a POD for derivation of an
acute reference value at another ex posure 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 asse ssment of human health effects relative to the reference value or values being exceeded. Wh ere relevant to the estimated exposures, the
lack of threshold values at di fferent levels of severity shoul d be factored into the risk characterization as poten tial uncertainties.75



### 5 References

1 . US EPA, 2006. Emission Standards for Hazardous Air Pollutants. http://www.epa.gov/ttn /atw/mactfnlalph.html

.

2 US EPA, 2009. Risk and Technology Revi ew (RTR) Risk Assessm ent Methodologies: For

Review by the EPA’s Science Advisory Board wi th Case Studies – MACT I Petroleum Refining
Sources and Portland Cement Ma nufacturing. EPA-452/R-09-006. http://www.epa.gov/ttn/a tw/rrisk/rtrpg.html.

3 . US EPA, 2010. SAB’s Response to EPA’s RTR Risk Assessment Methodologies.

http://yosemite.epa.gov/ sab/sabproduct.nsf/4AB3966E 263D943A8525771F00668381 /$File/EP A-SAB-10-007-unsigned.pdf

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