not perform a multipathway exposure assessment. Where we do not perform
an analysis, we state that we do not and provide the reason. While we
present all of our risk assessment methods, we only present risk
assessment results for the analyses actually conducted (see section
III.B of this preamble).
    The EPA conducts a risk assessment that provides estimates of the
MIR for cancer posed by the HAP emissions from each source in the
source category, the HI for chronic exposures to HAP with the potential
to cause noncancer health effects, and the HQ for acute exposures to
HAP with the potential to cause noncancer health effects. The
assessment also provides estimates of the distribution of cancer risk
within the exposed populations, cancer incidence, and an evaluation of
the potential for an adverse environmental effect. The eight sections
that follow this paragraph describe how we estimated emissions and
conducted the risk assessment. The docket for this rulemaking contains
the following documents which provide more information on the risk
assessment inputs and models: Residual Risk Assessment for the SOCMI
Source Category in Support of the 2023 Risk and Technology Review
Proposed Rule and Residual Risk Assessment for the Polymers & Resins I
Neoprene Production Source Category in Support of the 2023 Risk and
Technology Review Proposed Rule. The methods used to assess risk (as
described in the eight primary steps below) are consistent with those
described by the EPA in the document reviewed by a panel of the EPA's
SAB in 2009; \25\ and described in the SAB review report issued in
2010. They are also consistent with the key recommendations contained
in that report.
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    \25\ U.S. EPA. Risk and Technology Review (RTR) Risk Assessment
Methodologies: For Review by the EPA's Science Advisory Board with
Case Studies--MACT I Petroleum Refining Sources and Portland Cement
Manufacturing, June 2009. EPA-452/R-09-006. https://www3.epa.gov/airtoxics/rrisk/rtrpg.html.
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1. How did we estimate actual emissions and identify the emissions
release characteristics?
    As previously discussed, we updated the risk assessment in this
action for the SOCMI and Neoprene Production source categories because
these source categories have sources that emit EtO and/or chloroprene.
The SOCMI and Neoprene Production source category facility lists were
developed as described in section II.C of this preamble and consist of
207 HON facilities and one neoprene production facility.\26\ For the
207 HON facilities, only 195 had reported HAP emissions in the 2017
NEI, and we note that two facilities included in the 207 are new/under
construction and were not operating in 2017. The emissions modeling
input files were developed using the EPA's 2017 NEI. However, in a few
instances where facility-specific

data were not available or not reflective of current controls in the
2017 NEI, we attempted to obtain data from a more recent dataset (e.g.,
review of emissions inventory data from our CAA section 114 request,
more recent inventories submitted to states, or 2018 NEI). Of note, for
the one neoprene production facility (which is also part of the SOCMI
source category), we used the 2019 emissions inventory that was
provided to the EPA from our CAA section 114 request. The NEI data were
also used to develop the other parameters needed to perform the risk
modeling analysis, including the emissions release characteristics,
such as stack heights, stack diameters, flow rates, temperatures, and
emission release point locations. For further details on the
assumptions and methodologies used to estimate actual emissions, see
Appendix 1 of the document titled Residual Risk Assessment for the
SOCMI Source Category in Support of the 2023 Risk and Technology Review
Proposed Rule, which is available in the docket for this rulemaking.
---------------------------------------------------------------------------

    \26\ The one neoprene production facility also has collocated
HON emissions sources from the production of chloroprene.
---------------------------------------------------------------------------

2. How did we estimate MACT-allowable emissions?
    The available emissions data in the RTR emissions dataset include
estimates of the mass of HAP emitted during a specified annual time
period. These ``actual'' emission levels are often lower than the
emission levels allowed under the requirements of the current MACT
standards. The emissions allowed under the MACT standards are referred
to as the ``MACT-allowable'' emissions. We discussed the consideration
of both MACT-allowable and actual emissions in the final Coke Oven
Batteries RTR (70 FR 19992, 19998-19999, April 15, 2005) and in the
proposed and final HON RTR (71 FR 34421, 34428, June 14, 2006, and 71
FR 76603, 76609, December 21, 2006, respectively). In those actions, we
noted that assessing the risk at the MACT-allowable level is inherently
reasonable since that risk reflects the maximum level facilities could
emit and still comply with national emission standards. We also
explained that it is reasonable to consider actual emissions, where
such data are available, in both steps of the risk analysis, in
accordance with the 1989 Benzene NESHAP approach. (54 FR 38044.)
    For this analysis, we have determined that the actual emissions
data are reasonable estimates of the MACT-allowable emissions levels
for the SOCMI source category, as we are not generally aware of any
situations in which a facility is conducting additional work practices
or operating a control device such that it achieves a far greater
emission reduction than required by the NESHAP. For the Neoprene
Production source category, we do know that some emission sources
(e.g., process vents) are being controlled beyond the current level of
the NESHAP standards. However, because there is only one facility in
the source category and because we are proposing to require these same
control requirements in this action, we consider these to be part of
the baseline actual emissions. We are also not aware of the neoprene
production facility over-controlling fugitive emission sources, which
tend to be the predominant risk drivers for this source category. We
note that because of the difficulty and uncertainty around comparing
fugitive emissions reported in emission inventories (i.e., assumptions
and engineering calculations are generally used for fugitive emissions
in emissions inventories since it is not practicable to measure them
due to technological and economic limitations) to the MACT standards
for both the SOCMI and Neoprene Production source categories and
whether facilities are better controlling these emissions sources since
they tend to drive risks, a separate assessment of risk for allowable
emissions appears unnecessary given the finding that risks are
unacceptable based on actual emissions (see section III.B of this
preamble). For further details on the assumptions and methodologies
used to estimate MACT-allowable emissions, see Appendix 1 of the
document titled Residual Risk Assessment for the SOCMI Source Category
in Support of the 2023 Risk and Technology Review Proposed Rule, which
is available in the docket for this rulemaking.
3. How do we conduct dispersion modeling, determine inhalation
exposures, and estimate individual and population inhalation risk?
    Both long-term and short-term inhalation exposure concentrations
and health risk from the source category addressed in this proposal
were estimated using the Human Exposure Model (HEM).\27\ The HEM
performs three primary risk assessment activities: (1) Conducting
dispersion modeling to estimate the concentrations of HAP in ambient
air, (2) estimating long-term and short-term inhalation exposures to
individuals residing within 50 kilometers (km) (~31 miles) of the
modeled sources, and (3) estimating individual and population-level
inhalation risk using the exposure estimates and quantitative dose-
response information.
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    \27\ For more information about HEM, go to https://www.epa.gov/fera/risk-assessment-and-modeling-human-exposure-model-hem.
---------------------------------------------------------------------------

a. Dispersion Modeling
    The EPA's American Meteorological Society/EPA Regulatory Model
dispersion modeling system (AERMOD), used by the HEM, is one of the
EPA's preferred models for assessing air pollutant concentrations from
industrial facilities.\28\ To perform the dispersion modeling and to
develop the preliminary risk estimates, HEM draws on three data
libraries. The first is a library of meteorological data, which is used
for dispersion calculations. This library includes hourly surface and
upper air observations for years ranging from 2016-2019 from over 800
meteorological stations, selected to provide coverage of the United
States and Puerto Rico. A second library of United States Census Bureau
census block \29\ internal point locations and populations provides the
basis of human exposure calculations (U.S. Census, 2010). In addition,
for each census block, the census library includes the elevation and
controlling hill height, which are also used in dispersion
calculations. A third library of pollutant-specific dose-response
values is used to estimate health risk. These are discussed below.
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    \28\ U.S. EPA. Revision to the Guideline on Air Quality Models:
Adoption of a Preferred General Purpose (Flat and Complex Terrain)
Dispersion Model and Other Revisions (70 FR 68218, November 9,
2005).
    \29\ A census block is the smallest geographic area for which
census statistics are tabulated.
---------------------------------------------------------------------------

b. Risk From Chronic Exposure to HAP
    In developing the risk assessment for chronic exposures, we use the
estimated annual average ambient air concentrations of each HAP emitted
by each source in the source category. The HAP air concentrations at
each nearby census block centroid located within 50 km (~31 miles) of
the facility are a surrogate for the chronic inhalation exposure
concentration for all the people who reside in that census block. A
distance of 50 km is consistent with both the analysis supporting the
1989 Benzene NESHAP (54 FR 38044) and the limitations of Gaussian
dispersion models, including AERMOD.
    For each facility, we calculate the MIR as the cancer risk
associated with a continuous lifetime (24 hours per day, 7 days per
week, 52 weeks per year, 70 years) exposure to the maximum
concentration at the centroid of each inhabited census block. We
calculate individual cancer risk by multiplying the estimated lifetime
exposure to the

ambient concentration of each HAP (in micrograms per cubic meter
([mu]g/m\3\) by its URE. The URE is an upper-bound estimate of an
individual's incremental risk of contracting cancer over a lifetime of
exposure to a concentration of 1 microgram of the pollutant per cubic
meter of air. For residual risk assessments, we generally use UREs from
the EPA's IRIS. For carcinogenic pollutants without IRIS values, we
look to other reputable sources of cancer dose-response values, often
using California EPA (CalEPA) UREs, where available. In cases where
new, scientifically credible dose-response values have been developed
in a manner consistent with EPA guidelines and have undergone a peer
review process similar to that used by the EPA, we may use such dose-
response values in place of, or in addition to, other values, if
appropriate. The pollutant-specific dose-response values used to
estimate health risk are available at https://www.epa.gov/fera/dose-response-assessment-assessing-health-risks-associated-exposure-hazardous-air-pollutants.
    To estimate individual lifetime cancer risks associated with
exposure to HAP emissions from each facility in the source category, we
sum the risks for each of the carcinogenic HAP \30\ emitted by the
modeled facility. We estimate cancer risk at every census block within
50 km of every facility in the source category. The MIR is the highest
individual lifetime cancer risk estimated for any of those census
blocks. In addition to calculating the MIR, we estimate the
distribution of individual cancer risks for the source category by
summing the number of individuals within 50 km of the sources whose
estimated risk falls within a specified risk range. We also estimate
annual cancer incidence by multiplying the estimated lifetime cancer
risk at each census block by the number of people residing in that
block, summing results for all of the census blocks, and then dividing
this result by a 70-year lifetime.
---------------------------------------------------------------------------

    \30\ The EPA's 2005 Guidelines for Carcinogen Risk Assessment
classifies carcinogens as: ``carcinogenic to humans,'' ``likely to
be carcinogenic to humans,'' and ``suggestive evidence of
carcinogenic potential.'' These classifications also coincide with
the terms ``known carcinogen, probable carcinogen, and possible
carcinogen,'' respectively, which are the terms advocated in the
EPA's Guidelines for Carcinogen Risk Assessment, published in 1986
(51 FR 33992, September 24, 1986). In August 2000, the document,
Supplemental Guidance for Conducting Health Risk Assessment of
Chemical Mixtures (EPA/630/R-00/002), was published as a supplement
to the 1986 document. Copies of both documents can be obtained from
https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=20533&CFID=70315376&CFTOKEN=71597944. Summing
the risk of these individual compounds to obtain the cumulative
cancer risk is an approach that was recommended by the EPA's SAB in
their 2002 peer review of the EPA's National Air Toxics Assessment
(NATA) titled NATA--Evaluating the National-scale Air Toxics
Assessment 1996 Data--an SAB Advisory, available at https://
yosemite.epa.gov/sab/sabproduct.nsf/
214C6E915BB04E14852570CA007A682C/$File/ecadv02001.pdf.
---------------------------------------------------------------------------

    To assess the risk of noncancer health effects from chronic
exposure to HAP, we calculate either an HQ or a target organ-specific
hazard index (TOSHI). We calculate an HQ when a single noncancer HAP is
emitted. Where more than one noncancer HAP is emitted, we sum the HQ
for each of the HAP that affects a common target organ or target organ
system to obtain a TOSHI. The HQ is the estimated exposure divided by
the chronic noncancer dose-response value, which is a value selected
from one of several sources. The preferred chronic noncancer dose-
response value is the EPA RfC, defined as ``an estimate (with
uncertainty spanning perhaps an order of magnitude) of a continuous
inhalation exposure to the human population (including sensitive
subgroups) that is likely to be without an appreciable risk of
deleterious effects during a lifetime'' (https://iaspub.epa.gov/sor_internet/registry/termreg/searchandretrieve/glossariesandkeywordlists/search.do?details=&vocabName=IRIS%20Glossary). In cases where an RfC
from the EPA's IRIS is not available or where the EPA determines that
using a value other than the RfC is appropriate, the chronic noncancer
dose-response value can be a value from the following prioritized
sources, which define their dose-response values similarly to the EPA:
(1) The Agency for Toxic Substances and Disease Registry (ATSDR)
Minimal Risk Level (https://www.atsdr.cdc.gov/mrls/); (2) the CalEPA
Chronic Reference Exposure Level (REL) (https://oehha.ca.gov/air/crnr/notice-adoption-air-toxics-hot-spots-program-guidance-manual-preparation-health-risk-0); or (3) as noted above, a scientifically
credible dose-response value that has been developed in a manner
consistent with the EPA guidelines and has undergone a peer review
process similar to that used by the EPA. The pollutant-specific dose-
response values used to estimate health risks are available at https://www.epa.gov/fera/dose-response-assessment-assessing-health-risks-associated-exposure-hazardous-air-pollutants.
c. Risk From Acute Exposure to HAP That May Cause Health Effects Other
Than Cancer
    For each HAP for which appropriate acute inhalation dose-response
values are available, the EPA also assesses the potential health risks
due to acute exposure. For these assessments, the EPA makes
conservative assumptions about emission rates, meteorology, and
exposure location. As part of our efforts to continually improve our
methodologies to evaluate the risks that HAP emitted from categories of
industrial sources pose to human health and the environment,\31\ we
revised our treatment of meteorological data to use reasonable worst-
case air dispersion conditions in our acute risk screening assessments
instead of worst-case air dispersion conditions. This revised treatment
of meteorological data and the supporting rationale are described in
more detail in the documents titled Residual Risk Assessment for the
SOCMI Source Category in Support of the 2023 Risk and Technology Review
Proposed Rule and Residual Risk Assessment for the Polymers & Resins I
Neoprene Production Source Category in Support of the 2023 Risk and
Technology Review Proposed Rule, and in Appendix 5 of the report:
Technical Support Document for Acute Risk Screening Assessment, which
are available in the docket for this rulemaking. This revised approach
has been used in this proposed rule and in all other RTR rulemakings
proposed on or after June 3, 2019.
---------------------------------------------------------------------------

    \31\ See, e.g., U.S. EPA. Screening Methodologies to Support
Risk and Technology Reviews (RTR): A Case Study Analysis (Draft
Report, May 2017. (https://www3.epa.gov/ttn/atw/rrisk/rtrpg.html).
---------------------------------------------------------------------------

    To assess the potential acute risk to the maximally exposed
individual, we use the peak hourly emission rate for each emission
point,\32\ reasonable worst-case air dispersion conditions (i.e., 99th
percentile), and the point of highest off-site exposure. Specifically,
we assume that peak emissions from the source category and reasonable
worst-case air dispersion conditions co-occur

and that a person is present at the point of maximum exposure.
---------------------------------------------------------------------------

    \32\ In the absence of hourly emission data, we develop
estimates of maximum hourly emission rates by multiplying the
average actual annual emissions rates by a factor (either a
category-specific factor or a default factor of 10) to account for
variability. This is documented in Residual Risk Assessment for the
SOCMI Source Category in Support of the 2023 Risk and Technology
Review Proposed Rule, Residual Risk Assessment for the Polymers &
Resins I Neoprene Production Source Category in Support of the 2023
Risk and Technology Review Proposed Rule, and in Appendix 5 of the
report: Technical Support Document for Acute Risk Screening
Assessment. All three of these documents are available in the docket
for this rulemaking.
---------------------------------------------------------------------------

    To characterize the potential health risks associated with
estimated acute inhalation exposures to a HAP, we generally use
multiple acute dose-response values, including acute RELs, acute
exposure guideline levels (AEGLs), and emergency response planning
guidelines (ERPG) for 1-hour exposure durations, if available, to
calculate acute HQs. The acute HQ is calculated by dividing the
estimated acute exposure concentration by the acute dose-response
value. For each HAP for which acute dose-response values are available,
the EPA calculates acute HQs.
    An acute REL is defined as ``the concentration level at or below
which no adverse health effects are anticipated for a specified
exposure duration.'' \33\ Acute RELs are based on the most sensitive,
relevant, adverse health effect reported in the peer-reviewed medical
and toxicological literature. They are designed to protect the most
sensitive individuals in the population through the inclusion of
margins of safety. Because margins of safety are incorporated to
address data gaps and uncertainties, exceeding the REL does not
automatically indicate an adverse health impact. AEGLs represent
threshold exposure limits for the general public and are applicable to
emergency exposures ranging from 10 minutes to 8 hours.\34\ They are
guideline levels for ``once-in-a-lifetime, short-term exposures to
airborne concentrations of acutely toxic, high-priority chemicals.''
Id. at 21. The AEGL-1 is specifically defined as ``the airborne
concentration (expressed as ppm (parts per million) or mg/m\3\
(milligrams per cubic meter)) of a substance above which it is
predicted that the general population, including susceptible
individuals, could experience notable discomfort, irritation, or
certain asymptomatic nonsensory effects. However, the effects are not
disabling and are transient and reversible upon cessation of
exposure.'' The document also notes that ``Airborne concentrations
below AEGL-1 represent exposure levels that can produce mild and
progressively increasing but transient and nondisabling odor, taste,
and sensory irritation or certain asymptomatic, nonsensory effects.''
Id. AEGL-2 are defined as ``the airborne concentration (expressed as
parts per million or milligrams per cubic meter) of a substance above
which it is predicted that the general population, including
susceptible individuals, could experience irreversible or other
serious, long-lasting adverse health effects or an impaired ability to
escape.'' Id.
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    \33\ CalEPA issues acute RELs as part of its Air Toxics Hot
Spots Program, and the 1-hour and 8-hour values are documented in
Air Toxics Hot Spots Program Risk Assessment Guidelines, Part I, The
Determination of Acute Reference Exposure Levels for Airborne
Toxicants, which is available at https://oehha.ca.gov/air/general-info/oehha-acute-8-hour-and-chronic-reference-exposure-level-rel-summary.
    \34\ National Academy of Sciences, 2001. Standing Operating
Procedures for Developing Acute Exposure Levels for Hazardous
Chemicals, page 2. Available at https://www.epa.gov/sites/production/files/2015-09/documents/sop_final_standing_operating_procedures_2001.pdf. Note that the
National Advisory Committee for Acute Exposure Guideline Levels for
Hazardous Substances ended in October 2011, but the AEGL program
continues to operate at the EPA and works with the National
Academies to publish final AEGLs (https://www.epa.gov/aegl).
---------------------------------------------------------------------------

    ERPGs are developed, by the American Industrial Hygiene Association
(AIHA), for emergency planning and are intended to be health-based
guideline concentrations for single exposures to chemicals. The ERPG-1
is the maximum airborne concentration, established by AIHA, below which
it is believed that nearly all individuals could be exposed for up to 1
hour without experiencing other than mild transient adverse health
effects or without perceiving a clearly defined, objectionable odor.
Similarly, the ERPG-2 is the maximum airborne concentration,
established by AIHA, below which it is believed that nearly all
individuals could be exposed for up to one hour without experiencing or
developing irreversible or other serious health effects or symptoms
which could impair an individual's ability to take protective action.
    An acute REL for 1-hour exposure durations is typically lower than
its corresponding AEGL-1 and ERPG-1. Even though their definitions are
slightly different, AEGL-1s are often the same as the corresponding
ERPG-1s, and AEGL-2s are often equal to ERPG-2s. The maximum HQs from
our acute inhalation screening risk assessment typically result when we
use the acute REL for a HAP. In cases where the maximum acute HQ
exceeds 1, we also report the HQ based on the next highest acute dose-
response value (usually the AEGL-1 and/or the ERPG-1).
    For the SOCMI and Neoprene Production source categories, we did not
use a default acute emissions multiplier of 10, but rather, we used
process level-specific acute emissions multipliers, generally ranging
from a factor of 2 to 10 as was done in past chemical and petrochemical
residual risk reviews such as for the 2015 the Petroleum Refinery
Sector rule, 2020 MON RTR, 2020 EMACT RTR, and 2020 OLD NESHAP RTR,
where similar emission sources and standards exist. These refinements
are discussed more fully in Appendix 1 of the document titled Residual
Risk Assessment for the SOCMI Source Category in Support of the 2023
Risk and Technology Review Proposed Rule, which is available in the
docket for this rulemaking.
    In our acute inhalation screening risk assessment, acute impacts
are deemed negligible for HAP for which acute HQs are less than or
equal to 1, and no further analysis is performed for these HAP. In
cases where an acute HQ from the screening step is greater than 1, we
assess the site-specific data to ensure that the acute HQ is at an off-
site location. For these source categories, the data refinements
employed consisted of reviewing satellite imagery of the locations of
the maximum acute HQ values to determine if the maximum was off
facility property. For any maximum value that was determined to be on
facility property, the next highest value that was off facility
property was used. These refinements are discussed more fully in the
documents titled Residual Risk Assessment for the SOCMI Source Category
in Support of the 2023 Risk and Technology Review Proposed Rule and
Residual Risk Assessment for the Polymers & Resins I Neoprene
Production Source Category in Support of the 2023 Risk and Technology
Review Proposed Rule, which are available in the docket for this
rulemaking.
4. How do we conduct the multipathway exposure and risk screening
assessment?
    The EPA conducts a tiered screening assessment examining the
potential for significant human health risks due to exposures via
routes other than inhalation (i.e., ingestion). We first determine
whether any sources in the source categories emit any HAP known to be
persistent and bioaccumulative in the environment, as identified in the
EPA's Air Toxics Risk Assessment Library (see Volume 1, Appendix D, at
https://www.epa.gov/fera/risk-assessment-and-modeling-air-toxics-risk-assessment-reference-library).
    For the Neoprene Production source category, we did not identify
emissions of any PB-HAP in the reported emissions inventory. Because we
did not identify reported PB-HAP emissions, we could not undertake the
three-tier human health risk screening assessment of PB-HAP that we
discuss below and which was conducted for the SOCMI source category.
However, for dioxins we used the results of the SOCMI source category
human health screening assessment at facilities with higher dioxin
emission rates than the

ones proposed for the Neoprene Production source category to
qualitatively assess the potential for human health risks.
    For the SOCMI source category, we identified PB-HAP emissions of
arsenic compounds, cadmium compounds, dioxins, polycyclic organic
matter (POM), and mercury, so we proceeded to the next step of the
evaluation. Except for lead, the human health risk screening assessment
for PB-HAP consists of three progressive tiers. In a Tier 1 screening
assessment, we determine whether the magnitude of the facility-specific
emissions of PB-HAP warrants further evaluation to characterize human
health risk through ingestion exposure. To facilitate this step, we
evaluate emissions against previously developed screening threshold
emission rates for several PB-HAP that are based on a hypothetical
upper-end screening exposure scenario developed for use in conjunction
with the EPA's Total Risk Integrated Methodology.Fate, Transport, and
Ecological Exposure (TRIM.FaTE) model. The PB-HAP with screening
threshold emission rates are arsenic compounds, cadmium compounds,
chlorinated dibenzodioxins and furans, mercury compounds, and POM.
Based on the EPA estimates of toxicity and bioaccumulation potential,
these pollutants represent a conservative list for inclusion in
multipathway risk assessments for RTR rules. (See Volume 1, Appendix D
at https://www.epa.gov/sites/production/files/2013-08/documents/volume_1_reflibrary.pdf.) In this assessment, we compare the facility-
specific emission rates of these PB-HAP to the screening threshold
emission rates for each PB-HAP to assess the potential for significant
human health risks via the ingestion pathway. We call this application
of the TRIM.FaTE model the Tier 1 screening assessment. The ratio of a
facility's actual emission rate to the Tier 1 screening threshold
emission rate is a ``screening value.''
    We derive the Tier 1 screening threshold emission rates for these
PB-HAP (other than lead compounds) to correspond to a maximum excess
lifetime cancer risk of 1-in-1 million (i.e., for arsenic compounds,
polychlorinated dibenzodioxins and furans, and POM) or, for HAP that
cause noncancer health effects (i.e., cadmium compounds and mercury
compounds), a maximum HQ of 1. If the emission rate of any one PB-HAP
or combination of carcinogenic PB-HAP in the Tier 1 screening
assessment exceeds the Tier 1 screening threshold emission rate for any
facility (i.e., the screening value is greater than 1), we conduct a
second screening assessment, which we call the Tier 2 screening
assessment. The Tier 2 screening assessment separates the Tier 1
combined fisher and farmer exposure scenario into fisher, farmer, and
gardener scenarios that retain upper-bound ingestion rates.
    In the Tier 2 screening assessment, the location of each facility
that exceeds a Tier 1 screening threshold emission rate is used to
refine the assumptions associated with the Tier 1 fisher and farmer
exposure scenarios at that facility. A key assumption in the Tier 1
screening assessment is that a lake and/or farm is located near the
facility. As part of the Tier 2 screening assessment, we use a U.S.
Geological Survey (USGS) database to identify actual waterbodies within
50 km (~31 miles) of each facility and assume the fisher only consumes
fish from lakes within that 50 km zone. We also examine the differences
between local meteorology near the facility and the meteorology used in
the Tier 1 screening assessment. We then adjust the previously-
developed Tier 1 screening threshold emission rates for each PB-HAP for
each facility based on an understanding of how exposure concentrations
estimated for the screening scenario change with the use of local
meteorology and the USGS lakes database.
    In the Tier 2 farmer scenario, we maintain an assumption that the
farm is located within 0.5 km (~0.3 miles) of the facility and that the
farmer consumes meat, eggs, dairy, vegetables, and fruit produced near
the facility. We may further refine the Tier 2 screening analysis by
assessing a gardener scenario to characterize a range of exposures,
with the gardener scenario being more plausible in RTR evaluations.
Under the gardener scenario, we assume the gardener consumes home-
produced eggs, vegetables, and fruit products at the same ingestion
rate as the farmer. The Tier 2 screen continues to rely on the high-end
food intake assumptions that were applied in Tier 1 for local fish
(adult female angler at 99th percentile fish consumption \35\) and
locally grown or raised foods (90th percentile consumption of locally
grown or raised foods for the farmer and gardener scenarios \36\). If
PB-HAP emission rates do not result in a Tier 2 screening value greater
than 1, we consider those PB-HAP emissions to pose risks below a level
of concern. If the PB-HAP emission rates for a facility exceed the Tier
2 screening threshold emission rates, we may conduct a Tier 3 screening
assessment.
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    \35\ Burger, J. 2002. Daily consumption of wild fish and game:
Exposures of high end recreationists. International Journal of
Environmental Health Research, 12:343-354.
    \36\ U.S. EPA. Exposure Factors Handbook 2011 Edition (Final).
U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-09/
052F, 2011.
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    There are several analyses that can be included in a Tier 3
screening assessment, depending upon the extent of refinement
warranted, including validating that the lakes are fishable, locating
residential/garden locations for urban and/or rural settings,
considering plume-rise to estimate emissions lost above the mixing
layer, and considering hourly effects of meteorology and plume-rise on
chemical fate and transport (a time-series analysis). If necessary, the
EPA may further refine the screening assessment through a site-specific
assessment.
    In evaluating the potential multipathway risk from emissions of
lead compounds, rather than developing a screening threshold emission
rate, we compare maximum estimated chronic inhalation exposure
concentrations to the level of the current National Ambient Air Quality
Standard (NAAQS) for lead.\37\ Values below the level of the primary
(health-based) lead NAAQS are considered to have a low potential for
multipathway risk.
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    \37\ In doing so, the EPA notes that the legal standard for a
primary NAAQS--that a standard is requisite to protect public health
and provide an adequate margin of safety (CAA section 109(b))--
differs from the CAA section 112(f) standard (requiring, among other
things, that the standard provide an ``ample margin of safety to
protect public health''). However, the primary lead NAAQS is a
reasonable measure of determining risk acceptability (i.e., the
first step of the 1989 Benzene NESHAP analysis) since it is designed
to protect the most susceptible group in the human population--
children, including children living near major lead emitting
sources. 73 FR 67002/3; 73 FR 67000/3; 73 FR 67005/1. In addition,
applying the level of the primary lead NAAQS at the risk
acceptability step is conservative, since that primary lead NAAQS
reflects an adequate margin of safety.
---------------------------------------------------------------------------

    For further information on the multipathway assessment approach,
see the documents titled Residual Risk Assessment for the SOCMI Source
Category in Support of the 2023 Risk and Technology Review Proposed
Rule and Residual Risk Assessment for the Polymers & Resins I Neoprene
Production Source Category in Support of the 2023 Risk and Technology
Review Proposed Rule, which are available in the docket for this
rulemaking.
5. How do we assess risks considering emissions control options?
    In addition to assessing baseline inhalation risks and screening
for potential multipathway risks, we also estimate risks considering
the potential

emission reductions that would be achieved by the control options under
consideration. In these cases, the expected emission reductions are
applied to the specific HAP and emission points in the RTR emissions
dataset to develop corresponding estimates of risk and incremental risk
reductions.
6. How do we conduct the environmental risk screening assessment?
a. Adverse Environmental Effect, Environmental HAP, and Ecological
Benchmarks
    The EPA conducts a screening assessment to examine the potential
for an adverse environmental effect as required under section
112(f)(2)(A) of the CAA. Section 112(a)(7) of the CAA defines ``adverse
environmental effect'' as ``any significant and widespread adverse
effect, which may reasonably be anticipated, to wildlife, aquatic life,
or other natural resources, including adverse impacts on populations of
endangered or threatened species or significant degradation of
environmental quality over broad areas.''
    The EPA focuses on eight HAP, which are referred to as
``environmental HAP,'' in its screening assessment: six PB-HAP and two
acid gases. The PB-HAP included in the screening assessment are arsenic
compounds, cadmium compounds, dioxins/furans, POM, mercury (both
inorganic mercury and methyl mercury), and lead compounds. The acid
gases included in the screening assessment are hydrochloric acid (HCl)
and hydrofluoric acid (HF).
    HAP that persist and bioaccumulate are of particular environmental
concern because they accumulate in the soil, sediment, and water. The
acid gases, HCl and HF, are included due to their well-documented
potential to cause direct damage to terrestrial plants. In the
environmental risk screening assessment, we evaluate the following four
exposure media: terrestrial soils, surface water bodies (includes
water-column and benthic sediments), fish consumed by wildlife, and
air. Within these four exposure media, we evaluate nine ecological
assessment endpoints, which are defined by the ecological entity and
its attributes. For PB-HAP (other than lead), both community-level and
population-level endpoints are included. For acid gases, the ecological
assessment evaluated is terrestrial plant communities.
    An ecological benchmark represents a concentration of HAP that has
been linked to a particular environmental effect level. For each
environmental HAP, we identified the available ecological benchmarks
for each assessment endpoint. We identified, where possible, ecological
benchmarks at the following effect levels: probable effect levels,
lowest-observed-adverse-effect level, and no-observed-adverse-effect
level. In cases where multiple effect levels were available for a
particular PB-HAP and assessment endpoint, we use all of the available
effect levels to help us to determine whether ecological risks exist
and, if so, whether the risks could be considered significant and
widespread.
    For further information on how the environmental risk screening
assessment was conducted, including a discussion of the risk metrics
used, how the environmental HAP were identified, and how the ecological
benchmarks were selected, see Appendix 9 of the documents titled
Residual Risk Assessment for the SOCMI Source Category in Support of
the 2023 Risk and Technology Review Proposed Rule and Residual Risk
Assessment for the Polymers & Resins I Neoprene Production Source
Category in Support of the 2023 Risk and Technology Review Proposed
Rule, which are available in the docket for this rulemaking.
b. Environmental Risk Screening Methodology
    For the environmental risk screening assessment, the EPA first
determined whether any facilities in the SOCMI and Neoprene Production
source categories emitted any of the environmental HAP. For the
Neoprene Production source category, we did not identify reported
emissions of any of the six environmental HAP included in the screen.
Because we did not identify reported environmental HAP emissions from
the neoprene source category, we could not proceed to the second step
of the evaluation as discussed below for the HON. However, for dioxins
we used the results of the SOCMI source category environmental risk
screening assessment at facilities with higher dioxin emission rates
than the ones proposed for the Neoprene Production source category to
qualitative assess the potential for adverse environmental effects.
    For the SOCMI source category, we identified reported emissions of
arsenic compounds, cadmium compounds, dioxins, POM, and mercury.\38\
Because one or more of the environmental HAP evaluated are emitted by
at least one facility in the SOCMI source category, we proceeded to the
second step of the evaluation.
---------------------------------------------------------------------------

    \38\ We note that in many instances, we did not have sufficient
information to parse out emissions from HON processes from facility-
wide emissions inventories, thus we took a conservative approach and
modeled facility-wide emissions as if they were all from the SOCMI
source category.
---------------------------------------------------------------------------

c. PB-HAP Methodology
    The environmental screening assessment includes six PB-HAP, arsenic
compounds, cadmium compounds, dioxins/furans, POM, mercury (both
inorganic mercury and methyl mercury), and lead compounds. With the
exception of lead, the environmental risk screening assessment for PB-
HAP consists of three tiers. The first tier of the environmental risk
screening assessment uses the same health-protective conceptual model
that is used for the Tier 1 human health screening assessment.
TRIM.FaTE model simulations were used to back-calculate Tier 1
screening threshold emission rates. The screening threshold emission
rates represent the emission rate in tons of pollutant per year that
results in media concentrations at the facility that equal the relevant
ecological benchmark. To assess emissions from each facility in the
category, the reported emission rate for each PB-HAP was compared to
the Tier 1 screening threshold emission rate for that PB-HAP for each
assessment endpoint and effect level. If emissions from a facility do
not exceed the Tier 1 screening threshold emission rate, the facility
``passes'' the screening assessment, and, therefore, is not evaluated
further under the screening approach. If emissions from a facility
exceed the Tier 1 screening threshold emission rate, we evaluate the
facility further in Tier 2.
    In Tier 2 of the environmental screening assessment, the screening
threshold emission rates are adjusted to account for local meteorology
and the actual location of lakes in the vicinity of facilities that did
not pass the Tier 1 screening assessment. For soils, we evaluate the
average soil concentration for all soil parcels within a 7.5-km radius
for each facility and PB-HAP. For the water, sediment, and fish tissue
concentrations, the highest value for each facility for each pollutant
is used. If emission concentrations from a facility do not exceed the
Tier 2 screening threshold emission rate, the facility ``passes'' the
screening assessment and typically is not evaluated further. If
emissions from a facility exceed the Tier 2 screening threshold
emission rate, we evaluate the facility further in Tier 3.
    As in the multipathway human health risk assessment, in Tier 3 of
the environmental screening assessment, we examine the suitability of
the lakes

around the facilities to support life and remove those that are not
suitable (e.g., lakes that have been filled in or are industrial
ponds), adjust emissions for plume-rise, and conduct hour-by-hour time-
series assessments. If these Tier 3 adjustments to the screening
threshold emission rates still indicate the potential for an adverse
environmental effect (i.e., facility emission rate exceeds the
screening threshold emission rate), we may elect to conduct a more
refined assessment using more site-specific information. If, after
additional refinement, the facility emission rate still exceeds the
screening threshold emission rate, the facility may have the potential
to cause an adverse environmental effect.
    To evaluate the potential for an adverse environmental effect from
lead, we compared the average modeled air concentrations (from HEM-3)
of lead around each facility in the source category to the level of the
secondary NAAQS for lead. The secondary lead NAAQS is a reasonable
means of evaluating environmental risk because it is set to provide
substantial protection against adverse welfare effects which can
include ``effects on soils, water, crops, vegetation, man-made
materials, animals, wildlife, weather, visibility and climate, damage
to and deterioration of property, and hazards to transportation, as
well as effects on economic values and on personal comfort and well-
being.''
d. Acid Gas Environmental Risk Methodology
    The environmental screening assessment for acid gases evaluates the
potential phytotoxicity and reduced productivity of plants due to
chronic exposure to HF and HCl. The environmental risk screening
methodology for acid gases is a single-tier screening assessment that
compares modeled ambient air concentrations (from AERMOD) to the
ecological benchmarks for each acid gas. To identify a potential
adverse environmental effect (as defined in section 112(a)(7) of the
CAA) from emissions of HF and HCl, we evaluate the following metrics:
the size of the modeled area around each facility that exceeds the
ecological benchmark for each acid gas, in acres and square km; the
percentage of the modeled area around each facility that exceeds the
ecological benchmark for each acid gas; and the area-weighted average
screening value around each facility (calculated by dividing the area-
weighted average concentration over the 50-km modeling domain by the
ecological benchmark for each acid gas). For further information on the
environmental screening assessment approach, see Appendix 9 of the
documents titled Residual Risk Assessment for the SOCMI Source Category
in Support of the 2023 Risk and Technology Review Proposed Rule and
Residual Risk Assessment for the Polymers & Resins I Neoprene
Production Source Category in Support of the 2023 Risk and Technology
Review Proposed Rule, which are available in the docket for this
rulemaking.
7. How do we conduct facility-wide assessments?
    To put the source category risks in context, we typically examine
the risks from the entire ``facility,'' where the facility includes all
HAP-emitting operations within a contiguous area and under common
control. In other words, we examine the HAP emissions not only from the
source category emission points of interest, but also emissions of HAP
from all other emission sources at the facility for which we have data.
For these source categories, we conducted the facility-wide assessment
using a dataset compiled from the 2017 NEI and other emissions
information discussed in section II.C of this preamble. Once a quality
assured source category dataset was available, it was placed back with
the remaining records from the emissions inventory for that facility
(which in most instances was 2017 NEI data). The facility-wide file was
then used to analyze risks due to the inhalation of HAP that are
emitted ``facility-wide'' for the populations residing within 50 km
(~31 miles) of each facility, consistent with the methods used for the
source category analysis described above. For these facility-wide risk
analyses, the modeled source category risks were compared to the
facility-wide risks to determine the portion of the facility-wide risks
that could be attributed to the source category addressed in this
proposal. We also specifically examined the facility that was
associated with the highest estimate of risk and determined the
percentage of that risk attributable to the source category of
interest. The documents titled Residual Risk Assessment for the SOCMI
Source Category in Support of the 2023 Risk and Technology Review
Proposed Rule and Residual Risk Assessment for the Polymers & Resins I
Neoprene Production Source Category in Support of the 2023 Risk and
Technology Review Proposed Rule, available through the docket for this
rulemaking, provide the methodology and results of the facility-wide
analyses, including all facility-wide risks and the percentage of
source category contribution to facility-wide risks.
8. How do we conduct community-based risk assessments?
    In addition to the source category and facility-wide risk
assessments, we also assessed the combined inhalation cancer risk from
all local stationary sources of HAP for which we have emissions data.
Specifically, we combined the modeled impacts from the facility-wide
assessment (which includes category and non-category sources) with
other nearby stationary point source model results. The facility-wide
emissions used in this assessment are discussed in section II.C of this
preamble. For the other nearby point sources, we used AERMOD model
results with emissions based primarily on the 2018 NEI. After combining
these model results, we assessed cancer risks due to the inhalation of
all HAP emitted by point sources for the populations residing within 10
km (~6.2 miles) of HON facilities. In the community-based risk
assessment, the modeled source category and facility-wide cancer risks
were compared to the cancer risks from other nearby point sources to
determine the portion of the risks that could be attributed to the
source category addressed in this proposal. The document titled
Residual Risk Assessment for the SOCMI Source Category in Support of
the 2023 Risk and Technology Review Proposed Rule, which is available
in the docket for this rulemaking, provides the methodology and results
of the community-based risks analyses.
9. How do we consider uncertainties in risk assessment?
    Uncertainty and the potential for bias are inherent in all risk
assessments, including those performed for this proposal. Although
uncertainty exists, we believe that our approach, which used
conservative tools and assumptions, ensures that our decisions are
health and environmentally protective. A brief discussion of the
uncertainties in the RTR emissions datasets, dispersion modeling,
inhalation exposure estimates, and dose-response relationships follows
below. Also included are those uncertainties specific to our acute
screening assessments, multipathway screening assessments, and our
environmental risk screening assessments. A more thorough discussion of
these uncertainties is included in the documents titled Residual Risk
Assessment for the SOCMI Source Category in Support of the 2023 Risk
and Technology Review

Proposed Rule and Residual Risk Assessment for the Polymers & Resins I
Neoprene Production Source Category in Support of the 2023 Risk and
Technology Review Proposed Rule, which are available in the docket for
this rulemaking. If a multipathway site-specific assessment was
performed for these source categories, a full discussion of the
uncertainties associated with that assessment can be found in Appendix
11 of that document, Site-Specific Human Health Multipathway Residual
Risk Assessment Report.
a. Uncertainties in the RTR Emissions Datasets
    Although the development of the RTR emissions datasets involved
quality assurance/quality control processes, the accuracy of emissions
values will vary depending on the source of the data, the degree to
which data are incomplete or missing, the degree to which assumptions
made to complete the datasets are accurate, errors in emission
estimates, and other factors. The emission estimates considered in this
analysis generally are annual totals for certain years, and they do not
reflect short-term fluctuations during the course of a year or
variations from year to year. The estimates of peak hourly emission
rates for the acute effects screening assessment were based on an
emission adjustment factor applied to the average annual hourly
emission rates, which are intended to account for emission fluctuations
due to normal facility operations.
b. Uncertainties in Dispersion Modeling
    We recognize there is uncertainty in ambient concentration
estimates associated with any model, including the EPA's recommended
regulatory dispersion model, AERMOD. In using a model to estimate
ambient pollutant concentrations, the user chooses certain options to
apply. For RTR assessments, we select some model options that have the
potential to overestimate ambient air concentrations (e.g., not
including plume depletion or pollutant transformation). We select other
model options that have the potential to underestimate ambient impacts
(e.g., not including building downwash). Other options that we select
have the potential to either under- or overestimate ambient levels
(e.g., meteorology and receptor locations). On balance, considering the
directional nature of the uncertainties commonly present in ambient
concentrations estimated by dispersion models, the approach we apply in
the RTR assessments should yield unbiased estimates of ambient HAP
concentrations. We also note that the selection of meteorology dataset
location could have an impact on the risk estimates. As we continue to
update and expand our library of meteorological station data used in
our risk assessments, we expect to reduce this variability.
c. Uncertainties in Inhalation Exposure Assessment
    Although every effort is made to identify all of 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 the exposure assessment. Some uncertainties in our
exposure assessment include human mobility, using the centroid of each
census block, assuming lifetime exposure, and assuming only outdoor
exposures. For most of these factors, there is neither an under nor
overestimate when looking at the maximum individual risk or the
incidence, but the shape of the distribution of risks may be affected.
With respect to outdoor exposures, actual exposures may not be as high
if people spend time indoors, especially for very reactive pollutants
or larger particles. For all factors, we reduce uncertainty when
possible. For example, with respect to census-block centroids, we
analyze large blocks using aerial imagery and adjust locations of the
block centroids to better represent the population in the blocks. We
also add additional receptor locations where the population of a block
is not well represented by a single location.
d. Uncertainties in Dose-Response Relationships
    There are uncertainties inherent in the development of the dose-
response values used in our risk assessments for cancer effects from
chronic exposures and noncancer effects from both chronic and acute
exposures. Some uncertainties are generally expressed quantitatively,
and others are generally expressed in qualitative terms. We note, as a
preface to this discussion, a point on dose-response uncertainty that
is stated in the EPA's 2005 Guidelines for Carcinogen Risk Assessment;
namely, that ``the primary goal of EPA actions is protection of human
health; accordingly, as an Agency policy, risk assessment procedures,
including default options that are used in the absence of scientific
data to the contrary, should be health protective'''(the EPA's 2005
Guidelines for Carcinogen Risk Assessment, page 1-7). This is the
approach followed here as summarized in the next paragraphs.
    Cancer UREs used in our risk assessments are those that have been
developed to generally provide an upper bound estimate of risk.\39\
That is, they represent a ``plausible upper limit to the true value of
a quantity'' (although this is usually not a true statistical
confidence limit). In some circumstances, the true risk could be as low
as zero; however, in other circumstances the risk could be greater.\40\
Chronic noncancer RfC and reference dose values represent chronic
exposure levels that are intended to be health-protective levels. To
derive dose-response values that are intended to be ``without
appreciable risk,'' the methodology relies upon an uncertainty factor
(UF) approach,\41\ which considers uncertainty, variability, and gaps
in the available data. The UFs are applied to derive dose-response
values that are intended to protect against appreciable risk of
deleterious effects.
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    \39\ IRIS glossary (https://ofmpub.epa.gov/sor_internet/registry/termreg/searchandretrieve/glossariesandkeywordlists/search.do?details=&glossaryName=IRIS%20Glossary).
    \40\ An 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.
    \41\ See A Review of the Reference Dose and Reference
Concentration Processes, U.S. EPA, December 2002, and Methods for
Derivation of Inhalation Reference Concentrations and Application of
Inhalation Dosimetry, U.S. EPA, 1994.
---------------------------------------------------------------------------

    Many of the UFs used to account for variability and uncertainty in
the development of acute dose-response values are quite similar to
those developed for chronic durations. Additional adjustments are often
applied to account for uncertainty in extrapolation from observations
at one exposure duration (e.g., 4 hours) to derive an acute dose-
response value at another exposure duration (e.g., 1 hour). Not all
acute dose-response values are developed for the same purpose, and care
must be taken when interpreting the results of an acute assessment of
human health effects relative to the dose-response value or values
being exceeded. Where relevant to the estimated exposures, the lack of
acute dose-response values at different levels of severity should be
factored into the risk characterization as potential uncertainties.
    Uncertainty also exists in the selection of ecological benchmarks
for the environmental risk screening assessment. We established a
hierarchy of preferred benchmark sources to allow selection of
benchmarks for each environmental HAP at each ecological assessment
endpoint. We searched for

benchmarks for three effect levels (i.e., no-effects level, threshold-
effect level, and probable effect level), but not all combinations of
ecological assessment/environmental HAP had benchmarks for all three
effect levels. Where multiple effect levels were available for a
particular HAP and assessment endpoint, we used all of the available
effect levels to help us determine whether risk exists and whether the
risk could be considered significant and widespread.
    Although we make every effort to identify appropriate human health
effect dose-response values for all pollutants emitted by the sources
in this risk assessment, some HAP emitted by these source categories
are lacking dose-response assessments. Accordingly, these pollutants
cannot be included in the quantitative risk assessment, which could
result in quantitative estimates understating HAP risk. To help to
alleviate this potential underestimate, where we conclude similarity
with a HAP for which a dose-response value is available, we use that
value as a surrogate for the assessment of the HAP for which no value
is available. To the extent use of surrogates indicates appreciable
risk, we may identify a need to increase priority for an IRIS
assessment for that substance. We additionally note that, generally
speaking, HAP of greatest concern due to environmental exposures and
hazard are those for which dose-response assessments have been
performed, reducing the likelihood of understating risk. Further, HAP
not included in the quantitative assessment are assessed qualitatively
and considered in the risk characterization that informs the risk
management decisions, including consideration of HAP reductions
achieved by various control options.
    For a group of compounds that are unspeciated (e.g., groups of
compounds that we do not know the exact composition of like glycol
ethers), we conservatively use the most protective dose-response value
of an individual compound in that group to estimate risk. Similarly,
for an individual compound in a group (e.g., ethylene glycol diethyl
ether) that does not have a specified dose-response value, we also
apply the most protective dose-response value from the other compounds
in the group to estimate risk.
e. Uncertainties in Acute Inhalation Screening Assessments
    In addition to the uncertainties highlighted above, there are
several factors specific to the acute exposure assessment that the EPA
conducts as part of the risk review under section 112 of the CAA. The
accuracy of an acute inhalation exposure assessment depends on the
simultaneous occurrence of independent factors that may vary greatly,
such as hourly emissions rates, meteorology, and the presence of a
person. In the acute screening assessment that we conduct under the RTR
program, we assume that peak emissions from the source category and
reasonable worst-case air dispersion conditions (i.e., 99th percentile)
co-occur. We then include the additional assumption that a person is
located at this point at the same time. Together, these assumptions
represent a reasonable worst-case actual exposure scenario. In most
cases, it is unlikely that a person would be located at the point of
maximum exposure during the time when peak emissions and reasonable
worst-case air dispersion conditions occur simultaneously.
f. Uncertainties in the Multipathway and Environmental Risk Screening
Assessments
    For each source category, we generally rely on site-specific levels
of PB-HAP or environmental HAP emissions to determine whether a refined
assessment of the impacts from multipathway exposures is necessary or
whether it is necessary to perform an environmental screening
assessment. This determination is based on the results of a three-
tiered screening assessment that relies on the outputs from models--
TRIM.FaTE and AERMOD--that estimate environmental pollutant
concentrations and human exposures for five PB-HAP (dioxins, POM,
mercury, cadmium, and arsenic) and two acid gases (HF and HCl). For
lead, we use AERMOD to determine ambient air concentrations, which are
then compared to the secondary NAAQS standard for lead. Two important
types of uncertainty associated with the use of these models in RTR
risk assessments and inherent to any assessment that relies on
environmental modeling are model uncertainty and input uncertainty.\42\
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    \42\ In the context of this discussion, the term ``uncertainty''
as it pertains to exposure and risk encompasses both variability in
the range of expected inputs and screening results due to existing
spatial, temporal, and other factors, as well as uncertainty in
being able to accurately estimate the true result.
---------------------------------------------------------------------------

    Model uncertainty concerns whether the model adequately represents
the actual processes (e.g., movement and accumulation) that might occur
in the environment. For example, does the model adequately describe the
movement of a pollutant through the soil? This type of uncertainty is
difficult to quantify. However, based on feedback received from
previous EPA SAB reviews and other reviews, we are confident that the
models used in the screening assessments are appropriate and state-of-
the-art for the multipathway and environmental screening risk
assessments conducted in support of RTRs.
    Input uncertainty is concerned with how accurately the models have
been configured and parameterized for the assessment at hand. For Tier
1 of the multipathway and environmental screening assessments, we
configured the models to avoid underestimating exposure and risk. This
was accomplished by selecting upper-end values from nationally
representative datasets for the more influential parameters in the
environmental model, including selection and spatial configuration of
the area of interest, lake location and size, meteorology, surface
water, soil characteristics, and structure of the aquatic food web. We
also assume an ingestion exposure scenario and values for human
exposure factors that represent reasonable maximum exposures.
    In Tier 2 of the multipathway and environmental screening
assessments, we refine the model inputs to account for meteorological
patterns in the vicinity of the facility versus using upper-end
national values, and we identify the actual location of lakes near the
facility rather than the default lake location that we apply in Tier 1.
By refining the screening approach in Tier 2 to account for local
geographical and meteorological data, we decrease the likelihood that
concentrations in environmental media are overestimated, thereby
increasing the usefulness of the screening assessment. In Tier 3 of the
screening assessments, we refine the model inputs again to account for
hour-by-hour plume-rise and the height of the mixing layer. We can also
use those hour-by-hour meteorological data in a TRIM.FaTE run using the
screening configuration corresponding to the lake location. These
refinements produce a more accurate estimate of chemical concentrations
in the media of interest, thereby reducing the uncertainty with those
estimates. The assumptions and the associated uncertainties regarding
the selected ingestion exposure scenario are the same for all three
tiers.
    For the environmental screening assessment for acid gases, we
employ a single-tiered approach. We use the modeled air concentrations
and compare those with ecological benchmarks.
    For all tiers of the multipathway and environmental screening
assessments,

our approach to addressing model input uncertainty is generally
cautious. We choose model inputs from the upper end of the range of
possible values for the influential parameters used in the models, and
we assume that the exposed individual exhibits ingestion behavior that
would lead to a high total exposure. This approach reduces the
likelihood of not identifying high risks for adverse impacts.
    Despite the uncertainties, when individual pollutants or facilities
do not exceed screening threshold emission rates (i.e., screen out), we
are confident that the potential for adverse multipathway impacts on
human health is very low. On the other hand, when individual pollutants
or facilities do exceed screening threshold emission rates, it does not
mean that impacts are significant, only that we cannot rule out that
possibility and that a refined assessment for the site might be
necessary to obtain a more accurate risk characterization for the
source category.
    The EPA evaluates the following HAP in the multipathway and/or
environmental risk screening assessments, where applicable: arsenic,
cadmium, dioxins/furans, lead, mercury (both inorganic and methyl
mercury), POM, HCl, and HF. These HAP represent pollutants that can
cause adverse impacts either through direct exposure to HAP in the air
or through exposure to HAP that are deposited from the air onto soils
and surface waters and then through the environment into the food web.
These HAP represent those HAP for which we can conduct a meaningful
multipathway or environmental screening risk assessment. For other HAP
not included in our screening assessments, the model has not been
parameterized such that it can be used for that purpose. In some cases,
depending on the HAP, we may not have appropriate multipathway models
that allow us to predict the concentration of that pollutant. The EPA
acknowledges that other HAP beyond these that we are evaluating may
have the potential to cause adverse effects and, therefore, the EPA may
evaluate other relevant HAP in the future, as modeling science and
resources allow.

G. How does the EPA perform the NESHAP technology review and NSPS
review?

1. NESHAP Technology Review
    Our technology review primarily focuses on the identification and
evaluation of developments in practices, processes, and control
technologies that have occurred since the previous HON, P&R I, and P&R
II technology reviews were promulgated. Where we identify such
developments, we analyze their technical feasibility, estimated costs,
energy implications, and non-air environmental impacts. We also
consider the emission reductions associated with applying each
development. This analysis informs our decision of whether it is
``necessary'' to revise the CAA section 112 emissions standards. In
addition, we consider the appropriateness of applying controls to new
sources versus retrofitting existing sources. For this exercise, we
consider any of the following to be a ``development'':
     Any add-on control technology or other equipment that was
not identified and considered during development of the original MACT
standards;
     Any improvements in add-on control technology or other
equipment (that were identified and considered during development of
the original MACT standards) that could result in additional emissions
reduction;
     Any work practice or operational procedure that was not
identified or considered during development of the original MACT
standards;
     Any process change or pollution prevention alternative
that could be broadly applied to the industry and that was not
identified or considered during development of the original MACT
standards; and
     Any significant changes in the cost (including cost
effectiveness) of applying controls (including controls the EPA
considered during the development of the original MACT standards).
    In addition to reviewing the practices, processes, and control
technologies that were considered at the time we originally developed
the HON, P&R I, and P&R II, we review a variety of data sources in our
investigation of potential practices, processes, or controls to
consider. We also review the NESHAP and the available data to determine
if there are any unregulated emissions of HAP within the source
categories, and evaluate these data for use in developing new emission
standards. When reviewing MACT standards, we also address regulatory
gaps, such as missing standards for listed air toxics known to be
emitted from the source category. See sections II.C and II.D of this
preamble for information on the specific data sources that were
reviewed as part of the technology review.
2. NSPS Review
    As noted in the section II.A.2 of this preamble, CAA section 111
requires the EPA, at least every 8 years to review and, if appropriate
revise the standards of performance applicable to new, modified, and
reconstructed sources. If the EPA determines that it is appropriate to
review the standards of performance, the revised standards must reflect
the degree of emission limitation achievable through the application of
the BSER considering the cost of achieving such reduction and any non-
air quality health and environmental impact and energy requirements.
CAA section 111(a)(1).
    In reviewing an NSPS to determine whether it is ``appropriate'' to
revise the standards of performance, the EPA evaluates the statutory
factors, which may include consideration of the following information:
     Expected growth for the source category, including how
many new facilities, reconstructions, and modifications may trigger
NSPS in the future.
     Pollution control measures, including advances in control
technologies, process operations, design or efficiency improvements, or
other systems of emission reduction, that are ``adequately
demonstrated'' in the regulated industry.
     Available information from the implementation and
enforcement of current requirements indicating that emission
limitations and percent reductions beyond those required by the current
standards are achieved in practice.
     Costs (including capital and annual costs) associated with
implementation of the available pollution control measures.
     The amount of emission reductions achievable through
application of such pollution control measures.
     Any non-air quality health and environmental impact and
energy requirements associated with those control measures.
    In evaluating whether the cost of a particular system of emission
reduction is reasonable, the EPA considers various costs associated
with the particular air pollution control measure or a level of
control, including capital costs and operating costs, and the emission
reductions that the control measure or particular level of control can
achieve. The Agency considers these costs in the context of the
industry's overall capital expenditures and revenues. The Agency also
considers cost-effectiveness analysis as a useful metric and a means of
evaluating whether a given control achieves emission reduction at a
reasonable cost. A cost-effectiveness analysis allows comparisons of
relative costs and outcomes (effects) of two or more options. In
general, cost-effectiveness is a measure of the

outcomes produced by resources spent. In the context of air pollution
control options, cost effectiveness typically refers to the annualized
cost of implementing an air pollution control option divided by the
amount of pollutant reductions realized annually.
    After the EPA evaluates the statutory factors, the EPA compares the
various systems of emission reductions and determines which system is
``best,'' and therefore represents the BSER. The EPA then establishes a
standard of performance that reflects the degree of emission limitation
achievable through the implementation of the BSER. In doing this
analysis, the EPA can determine whether subcategorization is
appropriate based on classes, types, and sizes of sources, and may
identify a different BSER and establish different performance standards
for each subcategory. The result of the analysis and BSER determination
leads to standards of performance that apply to facilities that begin
construction, reconstruction, or modification after the date of
publication of the proposed standards in the Federal Register. Because
the NSPS reflect the BSER under conditions of proper operation and
maintenance, in doing its review, the EPA also evaluates and determines
the proper testing, monitoring, recordkeeping and reporting
requirements needed to ensure compliance with the emission standards.
    See section II.C of this preamble for information on the specific
data sources that were reviewed as part of this action.

III. Proposed Rule Summary and Rationale

A. What are the results of the risk assessment and analyses?

    As previously discussed, we conducted risk assessments for the
SOCMI and Neoprene Production (within P&R I) source categories. We
previously identified EtO as a cancer risk driver from facilities with
HON-subject processes in the first risk assessment we conducted in
2006. However, the EPA's IRIS inhalation URE for EtO was revised in
2016,\43\ based on new data, showing EtO to be more carcinogenic than
previously understood (i.e., resulting in a URE 60 times greater than
the previous URE over a 70-year lifetime). Additionally, the EPA's IRIS
inhalation URE for chloroprene was finalized in 2010 (there was no
previous URE).\44\ Chloroprene is emitted from some HON-subject
processes (e.g., chloroprene production, other chlorinated SOCMI
chemical production processes), but is mostly emitted from neoprene
production processes subject to P&R I. We briefly present results of
the risk assessments below and in more detail in the documents titled
Residual Risk Assessment for the SOCMI Source Category in Support of
the 2023 Risk and Technology Review Proposed Rule and Residual Risk
Assessment for the Polymers & Resins I Neoprene Production Source
Category in Support of the 2023 Risk and Technology Review Proposed
Rule, which are available in the docket for this rulemaking.
---------------------------------------------------------------------------

    \43\ U.S. EPA. Evaluation of the Inhalation Carcinogenicity of
Ethylene Oxide (CASRN 75-21-8) In Support of Summary Information on
the Integrated Risk Information System (IRIS). December 2016. EPA/
635/R-16/350Fa. Available at: https://cfpub.epa.gov/ncea/iris/iris_documents/documents/toxreviews/1025tr.pdf.
    \44\ U.S. EPA. Toxicological Review of Chloroprene (CASRN 126-
99-8) In Support of Summary Information on the Integrated Risk
Information System (IRIS). September 2010. EPA/635/R-09/010F.
Available at: https://iris.epa.gov/static/pdfs/1021tr.pdf.
---------------------------------------------------------------------------

1. Chronic Inhalation Risk Assessment Results
a. SOCMI Source Category
    The results of the chronic baseline inhalation cancer risk
assessment, which are estimated using modeling and is the case for all
risk results presented here and in subsequent sections, indicate that,
based on estimates of current actual and allowable emissions, the MIR
posed by the source category is 2,000-in-1 million, driven by EtO
emissions from PRDs (74 percent) and equipment leaks (20 percent). The
total estimated cancer incidence based on actual and allowable emission
levels is 2 excess cancer cases per year. EtO emissions contribute 89
percent of the total cancer incidence. Within 50 km (~31 miles) of HON-
subject facilities, the population exposed to cancer risk greater than
100-in-1 million for HON actual and allowable emissions is
approximately 87,000 people, and the population exposed to cancer risk
greater than or equal to 1-in-1 million is approximately 7.2 million
people. Of the 195 facilities that were assessed for risk, 8 facilities
have an estimated maximum cancer risk greater than 100-in-1 million. In
addition, the maximum modeled chronic noncancer TOSHI for the source
category based on actual and allowable emissions is estimated to be 2
(for respiratory effects) at two different facilities (from maleic
anhydride emissions at one facility and chlorine emissions at another
facility). Approximately 83 people are estimated to be exposed to a
TOSHI greater than 1. See Table 1 of this preamble for a summary of the
HON inhalation risk assessment results.

                      Table 1--SOCMI Source Category Inhalation Risk Assessment Results Based on Actual and Allowable Emissions \1\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                 Maximum       Estimated population at increased
                                 Number of     individual               risk of cancer             Estimated  annual                     Refined maximum
        Risk assessment          facilities  cancer risk (- -------------------------------------- cancer  incidence   Maximum chronic   screening acute
                                    \2\       in-1 million)                                         (cases per year)   noncancer TOSHI    noncancer HQ
                                                   \3\       >100-in-1 million   >=1-in-1 million
--------------------------------------------------------------------------------------------------------------------------------------------------------
SOCMI Source Category.........          195           2,000  87,000 (50 km)...  7.2 million (50                    2  2 (maleic         HQREL = 3
                                                                                km).                                  anhydride).       (chlorine).
                                                                                2 (chlorine)....  HQREL = 3
                                                                                (acrolein).
Facility-wide \4\.............          195           2,000  95,000 (50 km)...  8.9 million (50                    2  4 (chlorine,
                                                                                km).                                  acrylic acid,
                                                                                and
                                                                                acrylonitrile).
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ Actual emissions equal allowable emissions; therefore, actual risks equal allowable risks.
\2\ There are 207 HON facilities; however, only 195 of these facilities are included in the risk assessment based on available data, which corresponds
  to 222 Emission Information System (EIS) facility IDs.
\3\ Maximum individual excess lifetime cancer risk due to HAP emissions.
\4\ See ``Facility-Wide Risk Results'' in section III.A.5 of this preamble for more details on this risk assessment.

b. Neoprene Production Source Category
    The results of the chronic baseline inhalation cancer risk
assessment indicate that, based on estimates of current actual and
allowable emissions, the MIR posed by the Neoprene Production source
category within P&R I is 500-in-1 million, driven by chloroprene
emissions from maintenance vents (67 percent), storage vessels (11
percent), wastewater (8 percent), and equipment leaks (4 percent).\45\
The total estimated cancer incidence based on actual and allowable
emission levels is 0.05 excess cancer cases per year, or 1 cancer case
every 20 years. Within 50 km (~31 miles) of the one facility in this
source category, the population exposed to cancer risks greater than
100-in-1 million for actual and allowable emissions is approximately
2,100 people, and the population exposed to cancer risks greater than
or equal to 1-in-1 million is approximately 690,000 people. In
addition, the maximum modeled chronic noncancer TOSHI for the source
category based on actual and allowable emissions is estimated to be
0.05 (for respiratory effects) from chloroprene emissions. See Table 2
of this preamble for a summary of the neoprene production inhalation
risk assessment results.
---------------------------------------------------------------------------

    \45\ We note that chloroprene (and all other HAP) emissions from
HON processes co-located at the neoprene production facility result
in an MIR of 90-in-1 million.

               Table 2--Neoprene Production Source Category Inhalation Risk Assessment Results Based on Actual and Allowable Emissions \1\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                 Maximum       Estimated population at increased
                                 Number of     individual               risk of cancer             Estimated  annual                         Maximum
        Risk assessment          facilities  cancer risk (- -------------------------------------- cancer  incidence   Maximum chronic   screening acute
                                    \2\       in-1 million)                                         (cases per year)   noncancer TOSHI    noncancer HQ
                                                   \3\       >100-in-1 million   >=1-in-1 million
--------------------------------------------------------------------------------------------------------------------------------------------------------
Neoprene Production Source                1             500  2,100 (50 km)....  690,000 (50 km)..               0.05  0.05              HQREL = 0.3
 Category.                                                                                (chloroprene).    (chloroform).
Facility-wide \4\.............            1             600  2,300 (50 km)....  890,000 (50 km)..               0.06  0.3 (chlorine)..
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ Actual emissions equal allowable emissions; therefore, actual risks equal allowable risks.
\2\ Number of facilities evaluated in the risk analysis.
\3\ Maximum individual excess lifetime cancer risk due to HAP emissions.
\4\ See ``Facility-Wide Risk Results'' in section III.A.5 of this preamble for more details on this risk assessment.

2. Screening Level Acute Risk Assessment Results
a. SOCMI Source Category
    As presented in Table 1 of this preamble, the estimated worst-case
off-site acute exposures to emissions from the SOCMI source category
result in a maximum modeled acute noncancer HQ of 3 based on the RELs
for chlorine and acrolein. HON process emissions from two other
facilities result in acute noncancer HQs of 2 based on the RELs for
formaldehyde and chloroform. Detailed information about the assessment,
including evaluation of the screening-level acute risk assessment
results, is provided in the main body and Appendix 10 of the document
titled Residual Risk Assessment for the SOCMI Source Category in
Support of the 2023 Risk and Technology Review Proposed Rule, which is
available in the docket for this rulemaking.
b. Neoprene Production Source Category
    As presented in Table 2 of this preamble, the estimated worst-case
acute exposures to emissions from the Neoprene Production source
category result in a maximum modeled acute noncancer HQ of 0.3 based on
the REL for chloroform. Detailed information about the assessment is
provided in the document titled Residual Risk Assessment for the
Polymers & Resins I Neoprene Production Source Category in Support of
the 2023 Risk and Technology Review Proposed Rule, which is available
in the docket for this rulemaking.
3. Multipathway Risk Screening Results
a. SOCMI Source Category
    For the SOCMI source category, 71 facilities emitted at least 1 PB-
HAP, including arsenic, cadmium, dioxins, mercury, and POMs.\46\
Emissions of these PB-HAP from each facility were compared to the
respective pollutant-specific Tier 1 screening emission thresholds. The
Tier 1 screening analysis indicated 9 facilities exceeded the Tier 1
emission threshold for arsenic, 3 facilities for cadmium, 9 facilities
for dioxins, 9 facilities for mercury, and 20 facilities for POM.
---------------------------------------------------------------------------

    \46\ Note that while the multipathway risk screening results
includes metals (e.g., arsenic, cadmium, mercury, arsenic) and POMs,
the EPA in most instances used a conservative approach and modeled
whole facility emissions inventories for the SOCMI source category.
This means that emissions from other source categories were included
for this analysis, and we have no information suggesting that metals
or POMs are emitted from HON processes. See Appendix 1 of the
document titled Residual Risk Assessment for the SOCMI Source
Category in Support of the 2023 Risk and Technology Review Proposed
Rule, which is available in the docket for this rulemaking for more
details about development of the risk modeling file.
---------------------------------------------------------------------------

    For facilities that exceeded the Tier 1 multipathway screening
threshold emission rate for one or more PB-HAP, we used additional
facility site-specific information to perform a Tier 2 multipathway
risk screening assessment. The Tier 2 assessment resulted in a maximum
Tier 2 noncancer screening value of 60 from methyl mercury and 2 for
cadmium based on the fisher scenario and a cancer screening value of
100 from POM for the gardener scenario. The Tier 2 assessment indicated
the maximum arsenic and dioxin cancer screening values were 30 and 2,
respectively, for the gardener scenario, and therefore no further
screening was performed.
    For mercury and cadmium, a Tier 3 screening assessment was
conducted for the fisher scenario while a Tier 3 screening assessment
was conducted for POM for the gardener scenario. In the Tier 3
screening for the fisher scenario, lakes near the facilities were
reviewed on aerial photographs to ensure they were accessible for
fishing. Any lakes not accessible were removed from the assessment.
After conducting the Tier 3 assessment, the screening values for
mercury and cadmium remained at 60 and 2, respectively.
    The Tier 3 gardener scenario was refined by identifying the
location of the residence most impacted by POM emissions from the
facility as opposed to the worst-case near-field location used in the
Tier 2 assessment. Based on these Tier 3 refinements to the gardener
scenario, the maximum Tier 3 cancer screening value for POM was 20.
    An exceedance of a screening threshold emission rate in any of the
tiers cannot be equated with a risk value or an HQ (or HI). Rather, it
represents

a high-end estimate of what the risk or hazard may be. For example, a
screening value of 2 for a non-carcinogen can be interpreted to mean
that the Agency is confident that the HQ would be lower than 2.
Similarly, a Tier 2 cancer screening value of 7 means that we are
confident that the cancer risk is lower than 7-in-1 million. Our
confidence comes from the conservative, or health-protective,
assumptions encompassed in the screening tiers: the Agency chooses
inputs from the upper end of the range of possible values for the
influential parameters used in the screening tiers, and the Agency
assumes that the exposed individual exhibits ingestion behavior that
would lead to a high total exposure.
    The EPA determined that it is not necessary to go beyond the Tier 3
lake analysis or conduct a site-specific assessment for cadmium,
mercury, or POM. The EPA compared the Tier 2 screening results to site-
specific risk estimates for five previously assessed source categories.
These are the five source categories, assessed over the past 4 years,
which had characteristics that make them most useful for interpreting
the HON screening results. For these source categories, the EPA
assessed fisher and/or gardener risks for arsenic, cadmium, and/or
mercury by conducting site-specific assessments. The EPA used AERMOD
for modeling air dispersion and Tier 2 screens that used multi-facility
aggregation of chemical loading to lakes where appropriate. These
assessments indicated that cancer and noncancer site-specific risk
values were at least 50 times lower than the respective Tier 2
screening values for the assessed facilities, with the exception of
noncancer risks for cadmium for the gardener scenario, where the
reduction was at least 10 times (refer to EPA Docket ID: EPA-HQ-OAR-
2017-0015 and EPA-HQ-OAR-2019-0373 for a copy of these reports).\47\
---------------------------------------------------------------------------

    \47\ EPA Docket records (EPA-HQ-OAR-2017-0015): Appendix 11 of
the Residual Risk Assessment for the Taconite Manufacturing Source
Category in Support of the Risk and Technology Review 2019 Proposed
Rule; Appendix 11 of the Residual Risk Assessment for the Integrated
Iron and Steel Source Category in Support of the Risk and Technology
Review 2019 Proposed Rule; Appendix 11 of the Residual Risk
Assessment for the Portland Cement Manufacturing Source Category in
Support of the 2018 Risk and Technology Review Final Rule; Appendix
11 of the Residual Risk Assessment for the Coal and Oil-Fired EGU
Source Category in Support of the 2018 Risk and Technology Review
Proposed Rule; and EPA Docket: (EPA-HQ-OAR-2019-0373): Appendix 11
of the Residual Risk Assessment for Iron and Steel Foundries Source
Category in Support of the 2019 Risk and Technology Review Proposed
Rule.
---------------------------------------------------------------------------

    Based on our review of these analyses, if the Agency was to perform
a site-specific assessment for the SOCMI Source Category, the Agency
would expect similar magnitudes of decreases from the Tier 2 SVs. As
such, given the conservative nature of the screens and the level of
additional refinements that would go into a site-specific multipathway
assessment, were one to be conducted, we are confident that the HQ for
ingestion exposure, specifically cadmium and mercury through fish
ingestion, is at or below 1. For POM, the maximum cancer risk under the
rural gardener scenario would likely decrease to below 1-in-1 million.
Further details on the Tier 3 screening assessment can be found in
Appendix 10-11 of Residual Risk Assessment for the SOCMI Source
Category in Support of the 2023 Risk and Technology Review Proposed
Rule.
    In evaluating the potential for multipathway risk from emissions of
lead, we compared modeled annual lead concentrations to the primary
NAAQS for lead (0.15 [micro]g/m\3\). The highest annual lead
concentration of 0.004 [micro]g/m\3\ is well below the NAAQS for lead,
indicating low potential for multipathway risk of concern due to lead
emissions.
    Detailed information about the assessment is provided in the
document titled Residual Risk Assessment for the SOCMI Source Category
in Support of the 2023 Risk and Technology Review Proposed Rule, which
is available in the docket for this rulemaking.
b. Neoprene Production Source Category
    As mentioned above, we did not identify reported PB-HAP emissions
from the Neoprene Production source category, and we could not
undertake the three-tier human health risk screening assessment that
was conducted for the SOCMI source category. However, we note that we
would expect dioxins likely to be formed by combustion controls used to
control chlorinated chemicals such as chloroprene from this source
category. As no facility exceeded a Tier 2 screening value for dioxins
in the HON multipathway risk screening assessment, including 4 HON
facilities with dioxin emission rates higher than the standard being
proposed for dioxins for the Neoprene Production source category (and 1
HON facility with a dioxins emission rate approximately 20 times higher
than the proposed Neoprene Production emission limit), we would expect
multipathway risk from dioxins from the Neoprene Production source
category to screen lower than they are for the SOCMI source category
after compliance with the proposed dioxin limit occurs.
4. Environmental Risk Screening Results
a. SOCMI Source Category
    As described in section III.A of this preamble, we conducted a
screening assessment for adverse environmental effects for the SOCMI
source category. The environmental screening assessment included the
following HAP: arsenic, cadmium, dioxin, methyl mercury, divalent
mercury, and POMs.\48\
---------------------------------------------------------------------------

    \48\ Note that while the environmental risk screening results
includes metals (e.g., arsenic, cadmium, mercury, arsenic) and POMs,
the EPA in most instances used a conservative approach and modeled
whole facility emissions inventories for the SOCMI source category.
This means that emissions from other source categories were included
for this analysis, and we have no information suggesting that metals
or POMs are emitted from HON processes. See Appendix 1 of the
document titled Residual Risk Assessment for the SOCMI Source
Category in Support of the 2023 Risk and Technology Review Proposed
Rule, which is available in the docket for this rulemaking for more
details about development of the risk modeling file.
---------------------------------------------------------------------------

    In the Tier 1 screening analysis for PB-HAP (other than lead, which
was evaluated differently), arsenic emissions had no exceedances for
any ecological benchmark. The maximum Tier 1 screening value was 200
for methyl mercury emissions for the surface soil No Observed Adverse
Effects Level (NOAEL) avian ground insectivores benchmark. The other
pollutants (cadmium, dioxins, POMs, divalent mercury, methyl mercury)
had Tier 1 screening values above various benchmarks. Therefore, a Tier
2 screening assessment was performed for cadmium, dioxins, POMs,
divalent mercury, and methyl mercury emissions.
    In the Tier 2 screen, cadmium, dioxins, and POM emissions did not
exceed any ecological benchmark. The following Tier 2 screening values
were exceeded for methyl mercury emissions: a screening value of 5 for
the fish-eating birds NOAEL benchmark (specifically for the small duck
called the merganser), a screening value of 2 for the maximum allowable
toxicant level for the merganser, and a screening value of 3 for avian
ground insectivores (woodcock). The following Tier 2 screening values
were exceeded for divalent mercury emissions: a screening value of 4
for a sediment threshold level and a screening value of 2 for an
invertebrate threshold level. All of the Tier 2 exceedances for the
merganser and sediment benchmarks are the result of emissions from 3
facilities acting on the same lake. The invertebrate and

insectivore soil benchmarks are the result of emissions from 1
facility.
    Since there were Tier 2 exceedances, we conducted a Tier 3
environmental risk screen. In the Tier 3 environmental risk screen, we
looked at aerial photos of the lake being impacted by mercury emissions
from the three HON-subject facilities. The aerial photos show that the
``lake'' is located in an industrialized area, has been channelized,
and largely filled/drained. Therefore, it was determined that this
``lake'' would not support a fish population. We also looked at aerial
photos of the facility that was driving the invertebrate and
insectivore Tier 2 soil exceedances due to mercury emissions. The
aerial photos show that the facility is located in a heavily
industrialized area with the nearest ``natural areas'' being located
more than 1500 meters from the facility. We re-calculated the soil
screening values with the industrial areas removed and calculated a
maximum Tier 3 soil screen value for mercury of 1.
    We did not estimate any exceedances of the secondary lead NAAQS.
The highest annual lead concentration of 0.004 [micro]g/m\3\ is well
below the NAAQS for lead, indicating low potential for environmental
risk of concern due to lead emissions.
    We also conducted an environmental risk screening assessment
specifically for acid gases (i.e., HCl and HF) for the SOCMI source
category. For HCl and HF, the average modeled concentration around each
facility (i.e., the average concentration of all off-site data points
in the modeling domain) did not exceed any ecological benchmark. In
addition, each individual modeled concentration of HCl and HF (i.e.,
each off-site data point in the modeling domain) was below the
ecological benchmarks for all facilities.
    Based on the results of the environmental risk screening analysis,
we do not expect an adverse environmental effect as a result of HAP
emissions from this source category. Detailed information about the
assessment is provided in the document titled Residual Risk Assessment
for the SOCMI Source Category in Support of the 2023 Risk and
Technology Review Proposed Rule, which is available in the docket for
this rulemaking.
b. Neoprene Production Source Category
    As mentioned above, because we did not identify reported PB-HAP
emissions, we did not undertake the environmental risk screening
assessment of PB-HAP for the Neoprene Production source category.
However, we note that no facility exceeded a Tier 2 screening value for
dioxins in the HON environmental risk screening assessment, including 4
HON facilities with dioxin emission rates higher than those being
proposed for the Neoprene Production source category and 1 HON facility
with a dioxin emission rate approximately 20 times higher than the
proposed emission limits for the Neoprene Production source category.
    Furthermore, we conducted an environmental risk screening
assessment for acid gases (i.e., HCl and HF) for the Neoprene
Production source category; however, there were no reported emissions
of HF at this facility. For HCl, the average modeled concentration
around the facility (i.e., the average concentration of all off-site
data points in the modeling domain) did not exceed any ecological
benchmark. In addition, each individual modeled concentration of HCl
(i.e., each off-site data point in the modeling domain) was below the
ecological benchmarks for the facility. Detailed information about the
assessment is provided in the document titled Residual Risk Assessment
for the Polymers & Resins I Neoprene Production Source Category in
Support of the 2023 Risk and Technology Review Proposed Rule, which is
available in the docket for this rulemaking.
5. Facility-Wide Risk Results
a. HON Facilities
    We conducted an assessment of facility-wide (or ``whole facility'')
risk as described above to characterize the source category risk in the
context of whole facility risk. We estimated whole facility risks using
the NEI-based data described in section III.C of this preamble. The
maximum lifetime individual cancer risk posed by the 195 modeled
facilities (there are 207 HON facilities; however, only 195 of these
facilities are included in the risk assessment based on available data,
which corresponds to 222 EIS facility IDs) based on whole facility
emissions is 2,000-in-1 million with EtO emissions from PRDs (74
percent) and equipment leaks (20 percent) from SOCMI source category
emissions driving the risk. The total estimated cancer incidence based
on facility-wide emission levels is 2 excess cancer cases per year. EtO
emissions contribute 81 percent and chloroprene emissions contribute 3
percent of the total cancer incidence. Within 50 km (~31 miles) of HON-
subject facilities, the population exposed to cancer risk greater than
100-in-1 million for HON facility-wide emissions is approximately
95,000 people, and the population exposed to cancer risk greater than
or equal to 1-in-1 million is approximately 8.9 million people. The
maximum chronic noncancer TOSHI posed by whole facility emissions is
estimated to be 4 (for respiratory effects) due mostly (98 percent) to
emissions from 2 facilities. Emissions from one facility contribute to
83 percent of the TOSHI, with approximately 60 percent of the total
TOSHI from non-source category emissions of chlorine and another 15
percent from source category emissions of chlorine. Emissions from the
second facility contribute to 15 percent of the TOSHI, with
approximately 11 percent of the total TOSHI from source category
emissions of acrylic acid and 2 percent from source category emissions
of acrylonitrile. Approximately 1,100 people are estimated to be
exposed to a TOSHI greater than 1 due to whole facility emissions.
b. Neoprene Production Facility
    We also performed a facility-wide assessment for the facility in
the Neoprene Production source category to characterize the source
category risk in the context of whole facility risk. Note that this
facility was also included the HON facility-wide risk assessment
because it has HON sources as well as neoprene production sources (see
section III.A.5.a of this preamble). The maximum lifetime individual
cancer risk posed by the one neoprene production facility based on
whole facility emissions is 600-in-1 million driven by chloroprene
emissions from maintenance vents (66 percent total, 55 percent from
neoprene production sources and 11 percent from HON sources), storage
vessels (9 percent total, all from neoprene production sources),
equipment leaks (7 percent total, 3 percent from neoprene production
sources and 4 percent from HON sources), and wastewater (7 percent, all
from neoprene production sources). The total estimated cancer incidence
based on facility-wide emission levels is 0.06 excess cancer cases per
year, or 1 case approximately every 17 years. Within 50 km (~31 miles)
of the Neoprene Production facility, the population exposed to cancer
risk greater than 100-in-1 million for facility-wide emissions is
approximately 2,300 people, and the population exposed to cancer risk
greater than or equal to 1-in-1 million is approximately 890,000
people. The maximum chronic noncancer TOSHI posed by whole facility
emissions is estimated to be 0.3 (for respiratory effects) due to
chlorine emissions.
6. Community-Based Risk Assessment
    We also conducted a community-based risk assessment for HON-subject

facilities (which includes the one neoprene production facility). The
goal of this assessment is to estimate cancer risk from HAP emitted
from all local stationary point sources for which we have emissions
data. We estimated the overall inhalation cancer risk due to emissions
from all stationary point sources impacting census blocks within 10 km
(~6.2 miles) of the 195 HON facilities. Specifically, we combined the
modeled impacts from category and non-category HAP sources at HON
facilities, as well as other stationary point source HAP emissions.
Within 10 km of HON-subject facilities, we identified 2,700 non-source
category facilities that could potentially also contribute to HAP
inhalation exposures.
    We first looked at what the maximum risk is for communities around
SOCMI facilities. The results indicate that the community-level maximum
individual cancer risk is the same as in the source category MIR and
maximum risk for the facility-wide assessment, 2,000-in-1 million. The
assessment estimated that essentially all (greater than 99.9 percent)
of the MIR is attributable to emissions from the SOCMI source category.
We then looked at what the communities' risks are from all emissions
sources for which we had data. Within 10 km, the population exposed to
cancer risks greater than 100-in-1 million from all nearby emissions is
approximately 104,000. For comparison, approximately 87,000 people have
cancer risks greater than 100-in-1 million due to HON emissions and
approximately 95,000 people have cancer risks greater than 100-in-1
million due to HON facility-wide emissions (see Table 3 of this
preamble). The overall cancer incidence for this exposed population
(i.e., populations with risks greater than 100-in-1 million living
within 10 km of HON facilities) is 0.5, with 91 percent of the cancer
incidence from HON processes, 7 percent from non-HON processes at HON
facilities (a total of 98 percent from HON facilities), and 2 percent
from other nearby stationary point sources that are not HON facilities.
    The population exposed to cancer risks greater than or equal to 1-
in-1 million in the community-based assessment is approximately 5.8
million people. For comparison, approximately 2.8 million people have
cancer risks greater than or equal to 1-in-1 million due to HON process
emissions and approximately 3.2 million people have cancer risks
greater than 1-in-1 million due to HON facility-wide emissions (see
Table 3 of this preamble). The overall cancer incidence for this
exposed population (i.e., people with risks greater than or equal to 1-
in-1 million and living within 10 km of HON facilities) is 2, with 69
percent of the incidence due to emissions from HON processes, 16
percent from emissions of non-HON processes at HON facilities (that is,
a total of 85 percent from emissions from HON facilities) and 15
percent from emissions from other nearby stationary sources that are
not HON facilities.
    After the controls proposed in this action are implemented for both
the SOCMI and Neoprene Production source categories (see section
III.B.2), the community-level maximum individual cancer risk will be
reduced to the same as the facility-wide assessment, 1,000-in-1
million, from non-HON processes emitting ethylene oxide at a single
facility. The assessment estimated that 98 percent of the MIR is
attributable to emissions from non-HON processes at a HON facility. The
population (within 10 km of HON facilities) exposed to cancer risks
greater than 100-in-1 million from all nearby emissions will be
significantly reduced from 104,000 people to 4,200 people; a 96 percent
reduction from the baseline. The populations exposed to cancer risks
greater than 100-in-1 million from the SOCMI source category and
facility-wide emissions are similarly reduced, from 87,000 people to 0
for source category emissions and from 95,000 to 2,500 for facility-
wide emissions (see Table 3 of this preamble). Furthermore, the overall
cancer incidence for this exposed population is expected to be reduced
from 0.5 to 0.02. The percentage of the cancer incidence due to
emissions of HON processes is reduced from 91 percent to 9 percent. The
percentage of the cancer incidence due to emissions of non-HON
processes at HON facilities and emissions from other nearby stationary
sources proportionately shifts to 57 percent and 34 percent
respectively. EtO emissions across these sources remain the largest
source of incidence, accounting for 89 percent of the overall cancer
incidence for this exposed population.
    The post-control population exposed to cancer risks greater than or
equal to 1-in-1 million, 5.8 million people, would remain approximately
the same as the baseline. In comparison, after the controls proposed in
this action, the number of people with risks greater than or equal to
1-in-1 million due to source category emissions would reduce from 2.8
million to 2.5 million and due to facility-wide emissions from 3.2
million to 3.1 million (see Table 3 of this preamble). The lack of
change from the baseline is largely due to the impacts from non-HON
processes at HON facilities and from other nearby stationary sources
maintaining the risks greater than or equal to 1-in-1 million for the
exposed population. However, the overall cancer incidence for this
exposed population is expected to be reduced from 2 to 0.7. The
percentage of the cancer incidence from HON processes is expected to
decrease from 69 to 38 percent. The cancer incidence from non-HON
processes at HON facilities and from other nearby stationary sources
are expected to proportionately shift to 29 percent and 32 percent,
respectively.
    Overall, the proposed emission reductions in this rule provide a
substantial reduction in risks to the communities living around HON
facilities. The number of people at cancer risks greater than 100-in-1
million is reduced from 104,000 people to 4,200 people, a 96 percent
reduction. EtO emissions are by far the largest source of remaining
risk in the community-based risk assessment, accounting for 85 percent
across all sources. Moving forward, the EPA expects to continue to
address EtO emissions for other chemical sector source categories.

    Table 3--Inhalation Cancer Risk Assessment Results for Communities Living Within 10 km of HON Facilities
----------------------------------------------------------------------------------------------------------------
                                              Maximum         Estimated population at increased risk of cancer
                                            individual    ------------------------------------------------------
            Risk assessment              cancer risk (-in-
                                            1 million)          >100-in-1 million           >=1-in-1 million
----------------------------------------------------------------------------------------------------------------
                                             Baseline (Pre-Control)
----------------------------------------------------------------------------------------------------------------
SOCMI Source Category..................             2,000  87,000 (10 km)............  2.8 million (10 km).
Facility-wide..........................             2,000  95,000 (10 km)............  3.2 million (10 km).
Community..............................             2,000  104,000 (10 km)...........  5.8 million (10 km).
----------------------------------------------------------------------------------------------------------------

                            After Implementation of Proposed Controls (Post-Control)
----------------------------------------------------------------------------------------------------------------
SOCMI Source Category..................               100  0 (10 km).................  2.5 million (10 km).
Facility-wide \1\......................             1,000  2,500 (10 km).............  3.1 million (10 km).
Community..............................             1,000  4,200 (10 km).............  5.8 million (10 km).
----------------------------------------------------------------------------------------------------------------
\1\ Facility-wide post-control risks include proposed controls for the SOCMI and Neoprene Production source
  categories.

B. What are our proposed decisions regarding risk acceptability, ample
margin of safety, and adverse environmental effect?

1. Risk Acceptability Under the Current MACT Standards
    As noted in section II.D of this preamble, we weigh a wide range of
health risk measures and factors in our risk acceptability
determination, including the cancer MIR, the number of persons in
various cancer and noncancer risk ranges, cancer incidence, the maximum
noncancer TOSHI, the maximum acute noncancer HQ, the extent of
noncancer risks, the distribution of cancer and noncancer risks in the
exposed population, and risk estimation uncertainties (54 FR 38044,
September 14, 1989).
    Under the current MACT standards for the SOCMI source category, the
risk results indicate that the MIR is 2,000-in-1 million, driven by
emissions of EtO, and well above 100-in-1 million, which is the
presumptive limit of acceptability. The estimated incidence of cancer
due to inhalation exposures is 2 excess cancer case per year. The
population estimated to be exposed to cancer risks greater than 100-in-
1 million is approximately 87,000, and the population estimated to be
exposed to cancer risks greater than or equal to 1-in-1 million is
approximately 7.2 million. The estimated maximum chronic noncancer
TOSHI from inhalation exposure for this source category is 2 for
neurological effects. The acute risk screening assessment of reasonable
worst-case inhalation impacts indicates a maximum acute HQ of 3.
    Under the current MACT standards for the Neoprene Production source
category, the risk results indicate that the MIR is 500-in-1 million,
driven by emissions of chloroprene, and is above 100-in-1 million, the
presumptive limit of acceptability. The estimated incidence of cancer
due to inhalation exposures is 0.05 excess cancer case per year. The
population estimated to be exposed to cancer risks greater than 100-in-
1 million is approximately 2,100, and the population estimated to be
exposed to cancer risks greater than or equal to 1-in-1 million is
approximately 690,000 million. The estimated maximum chronic noncancer
TOSHI from inhalation exposure for this source category is 0.05 for
neurological effects, indicating low likelihood of adverse noncancer
effects from long-term inhalation exposures. The acute risk screening
assessment of reasonable worst-case inhalation impacts indicates a
maximum acute HQ of 0.3. Therefore, we conclude that adverse effects
from acute exposure to emissions from this category are not
anticipated.
    Considering all of the health risk information and factors
discussed above, particularly the high MIR for both the SOCMI and
Neoprene Production source categories, the EPA proposes that the risks
for both source categories are unacceptable. As noted in section II.A
of this preamble, when risks are unacceptable, under the 1989 Benzene
NESHAP approach and CAA section 112(f)(2)(A), the EPA must first
determine the emissions standards necessary to reduce risk to an
acceptable level, and then determine whether further HAP emissions
reductions are necessary to provide an ample margin of safety to
protect public health or to prevent, taking into consideration costs,
energy, safety, and other relevant factors, an adverse environmental
effect. Therefore, pursuant to CAA section 112(f)(2), we are proposing
certain standards for emission sources of EtO in the HON and certain
standards for emission sources of chloroprene from the Neoprene
Production source category that are more protective than the current
HON and P&R I MACT standards.
2. Proposed Controls To Address Unacceptable Risks
    As previously discussed, we conducted risk assessments of the SOCMI
and Neoprene Production source categories because the 2016 revisions to
the EPA's IRIS inhalation URE for EtO and the 2010 development of the
EPA's IRIS inhalation URE for chloroprene showed that both these
pollutants are more toxic than previously known.
    For the SOCMI source category, we identified EtO as the cancer risk
driver from HON sources. We are aware of 15 HON facilities reporting
more than 0.1 tpy of EtO emissions in their emissions inventories from
HON processes and two other facilities that are new or under
construction with HON processes that we expect will exceed this
threshold (but for which we do not yet have emissions inventory
information). Of these 17 facilities, 12 facilities produce and emit
EtO, which is a process subject to the HON MACT standards. In addition,
all 17 of these facilities have additional HON processes that use and
emit EtO in the production of glycols, glycol ethers, or ethanolamines.
From our residual risk assessment, eight facilities with emissions of
EtO from various HON processes have cancer risks above 100-in-1
million, and many different emission sources drive risk at these
facilities. Thus, in order to reduce emissions of EtO from HON
processes, the EPA is proposing more stringent control requirements for
process vents, storage vessels, equipment leaks, heat exchange systems,
wastewater, maintenance vents, flares, and PRDs that emit or have the
potential to emit EtO. As discussed later in this preamble, we are
proposing that these requirements that will reduce risk to an
acceptable level also provide an ample margin of safety to protect
public health, and that no additional requirements are needed to
prevent an adverse environmental effect.
    For the Neoprene Production source category, we identified
chloroprene as the HAP cancer risk driver from the only facility in the
Neoprene Production source category. Thus, in order to reduce risk
posed by emissions from

neoprene production processes to an acceptable level, the EPA is
proposing more stringent control requirements for process vents,
storage vessels, wastewater, maintenance vents, and PRDs that emit or
have the potential to emit chloroprene. Also, as discussed later in
this preamble, we are proposing that these requirements that will
reduce risk to an acceptable level also provide an ample margin of
safety to protect public health, and that no additional requirements
are needed to prevent an adverse environmental effect.
    We discuss the control options we evaluated for reducing EtO
emissions from HON processes in section III.B.2.a of this preamble and
discuss the control options we evaluated for reducing chloroprene
emissions from P&R I processes producing neoprene in section III.B.2.b
of this preamble.
a. EtO Controls for HON Processes
i. Process Vents and Storage Vessels
    Emissions of EtO can occur from several types of gas streams
associated with HON processes, such as distillation columns, evaporator
vents, and vacuum operations, as well as during vapor displacements and
heating losses. HON storage vessels are used to store liquid and
gaseous feedstocks for use in a process, as well as to store liquid and
gaseous products from a process. EtO is typically stored under pressure
as a liquified gas, but may also be found in small amounts in
atmospheric storage vessels storing liquid products that are formed
with ethylene oxide as a reactant in their production. Typical
emissions from atmospheric storage tanks occur from working and
breathing losses while pressure vessels are considered closed systems
and, if properly maintained and operated, should have virtually no
emissions. In some instances, pressurized vessels also could use a
blanket of inert gas, most often nitrogen, to maintain a non-
decomposable vapor space, and continuous purge of vapor space from non-
loading operations could also lead to emissions from storage vessels.
    The current HON standards divide process vents into Group 1 process
vents, which require control, and Group 2 process vents, which
generally do not require controls provided they do not exceed Group 1
thresholds. All HON Group 1 and Group 2 process vents are continuous.
The Group 1 and Group 2 designations for process vents are based on
volumetric flow rate, total organic HAP concentration, and the TRE
index value.\49\ The current HON standard requires uncontrolled Group 1
process vents to reduce total organic HAP emissions by 98 percent by
weight by venting emissions through a closed vent system to any
combination of control devices or to vent emissions through a closed
vent system to a flare. We provide more details about process vents in
our technology review discussion (see section III.C.3 of this
preamble).
---------------------------------------------------------------------------

    \49\ See section III.C.3.a of this preamble for a description of
the TRE index value and how the concept is currently used in the
HON.
---------------------------------------------------------------------------

    Similarly, the current HON standards divide storage vessels into
Group 1 storage vessels, which require control, and Group 2 storage
vessels, which generally do not require controls provided they do not
exceed Group 1 thresholds. The Group 1 and Group 2 designation for
storage vessels is based on the volume of the storage vessel and MTVP
of the material stored. Group 1 storage vessels are those with
capacities between 75 m\3\ and 151 m\3\ and a MTVP greater than or
equal to 13.1 kPa, and those with capacities greater than or equal to
151 m\3\ and a MTVP greater than or equal to 5.2 kPa. The current HON
standards require Group 1 storage vessels to reduce total HAP emissions
by 95 percent (or 90 percent if the storage vessel was installed on or
before December 31, 1992) by venting emissions through a closed vent
system to any combination of control devices or to vent emissions
through a closed vent system to a flare. Owners and operators of Group
1 storage vessels storing a liquid with a MTVP of total organic HAP
less than 76.6 kPa are also allowed to reduce organic HAP by utilizing
an IFR, an EFR, an EFR converted to an IFR, routing the emissions to a
process or a fuel gas system, or vapor balancing. For Group 1 storage
vessels storing a liquid with a MTVP of total organic HAP greater than
or equal to 76.6 kPa, owners and operators can reduce organic HAP
emissions by 95 percent by venting emissions through a closed vent
system to any combination of control devices, control emissions by
routing them to a process or a fuel gas system, or by using vapor
balancing. Pressure vessels (operating in excess of 204.9 kPa without
emissions to the atmosphere) may also store materials with EtO. For
storage vessels, the HON allows use of a design evaluation instead of a
performance test to determine the percent reduction of control devices
for any quantity of total uncontrolled organic HAP emissions being sent
to the control device. We provide more details about storage vessels in
our technology review discussion (see section III.C.2 of this preamble)
    Results of our risk assessment indicate that two HON facilities
present cancer risks greater than 100-in-1 million just from EtO
emissions from process vent sources. At one of the two facilities, EtO
risk from process vent emission sources emitted through PRDs is
approximately 75 percent of the facility's total SOCMI source category
risk of 2000-in-1 million. At the other facility, EtO risk from process
vent emission sources is approximately 20 percent of the facility's
total SOCMI source category risk of 500-in-1 million. Additionally, EtO
from storage vessels accounts for approximately 70-in-1 million of the
source category MIR of 2,000-in-1 million risk. To understand how to
best address risk within the SOCMI source category, we reviewed
information from our CAA section 114 request for this rulemaking (see
section II.C of this preamble) and identified six facilities that
measured EtO emissions from 14 emission points associated with process
vents and storage vessels. The information gathered for these emission
points indicates that HON sources with EtO emissions from process vents
and storage vessels typically use combustion devices (e.g., thermal
oxidizers) to control EtO emissions. Of these 14 emission points, seven
are controlled by either a thermal incinerator, regenerative thermal
oxidizer, vapor combustion unit, or catalytic oxidation unit; three are
controlled by a scrubber; and the remaining four are uncontrolled.
Based on results from the risk assessment, we determined that the
current MACT standards for HON process vents and storage vessels do not
result in sufficient reductions of EtO emissions to reduce risk to an
acceptable level, and, therefore, we evaluated available control
technologies with a higher level of control, as discussed below.
    In the MON final RTR (see 85 FR 49084, August 12, 2020), the EPA
evaluated options to control EtO emissions from process vents and
storage tanks ``in ethylene oxide service'' \50\ regardless of whether
the emission source is classified as Group 1 or Group 2. To reduce EtO
emissions from MON process vents and storage

tanks in EtO service, the EPA finalized a requirement to either: (1)
Vent emissions through a closed-vent system to a control device that
reduces EtO by greater than or equal to 99.9 percent by weight or to a
concentration less than 1 ppmv for each process vent and storage tank
vent (or, for multiple process vents, to less than 5 lb/yr for all
combined process vents); or (2) vent emissions through a closed-vent
system to a flare meeting the flare operating requirements discussed in
section III.D.1 of this preamble.
---------------------------------------------------------------------------

    \50\ In the MON, a process vent in ethylene oxide service means
each batch and continuous process vent in a process that, when
uncontrolled, contains a concentration of greater than or equal to 1
ppmv undiluted ethylene oxide, and when combined, the sum of all
these process vents would emit uncontrolled, ethylene oxide
emissions greater than or equal to 5 lb/yr (2.27 kg/yr); a storage
vessel in ethylene oxide service means a storage tank of any
capacity and vapor pressure storing a liquid that is at least 0.1