Draft Residual Risk Assessment for the Mineral Wool Production and Wool
Fiberglass Manufacturing Source Categories

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

September 2011

Table of Contents

  TOC \o "1-3" \h \z \u    HYPERLINK \l "_Toc300562949"  1	Introduction
 PAGEREF _Toc300562949 \h  4

  HYPERLINK \l "_Toc300562950"  2	Methods	  PAGEREF _Toc300562950 \h  5

  HYPERLINK \l "_Toc300562951"  2.1	Emissions and source data	  PAGEREF
_Toc300562951 \h  5

  HYPERLINK \l "_Toc300562952"  2.2	Dispersion modeling for inhalation
exposure assessment	  PAGEREF _Toc300562952 \h  6

  HYPERLINK \l "_Toc300562953"  2.3	Estimating human inhalation exposure
  PAGEREF _Toc300562953 \h  9

  HYPERLINK \l "_Toc300562954"  2.4	Acute Risk Screening and Refined
Assessments	  PAGEREF _Toc300562954 \h  9

  HYPERLINK \l "_Toc300562955"  2.5	Multipathway and environmental risk
screening	  PAGEREF _Toc300562955 \h  11

  HYPERLINK \l "_Toc300562956"  2.6	Dose-Response Assessment	  PAGEREF
_Toc300562956 \h  12

  HYPERLINK \l "_Toc300562957"  2.6.1	Sources of chronic dose-response
information	  PAGEREF _Toc300562957 \h  12

  HYPERLINK \l "_Toc300562958"  2.6.2	Sources of acute dose-response
information	  PAGEREF _Toc300562958 \h  16

  HYPERLINK \l "_Toc300562959"  2.7	Risk Characterization	  PAGEREF
_Toc300562959 \h  19

  HYPERLINK \l "_Toc300562960"  2.7.1	General	  PAGEREF _Toc300562960 \h
 19

  HYPERLINK \l "_Toc300562961"  2.7.2	Mixtures	  PAGEREF _Toc300562961
\h  21

  HYPERLINK \l "_Toc300562962"  3	Risk Results for the Mineral Wool
Production	  PAGEREF _Toc300562962 \h  22

  HYPERLINK \l "_Toc300562963"  3.1	Source Category Description and
Results	  PAGEREF _Toc300562963 \h  22

  HYPERLINK \l "_Toc300562964"  3.2	Risk Characterization	  PAGEREF
_Toc300562964 \h  23

  HYPERLINK \l "_Toc300562965"  4	Risk Results for the Wool Fiberglass
Manufacturing Source Category	  PAGEREF _Toc300562965 \h  28

  HYPERLINK \l "_Toc300562966"  4.1	Source Category Description and
Results	  PAGEREF _Toc300562966 \h  28

  HYPERLINK \l "_Toc300562967"  4.2	Risk Characterization	  PAGEREF
_Toc300562967 \h  30

  HYPERLINK \l "_Toc300562968"  4.3	Auxiliary Risk Characterization
PAGEREF _Toc300562968 \h  35

  HYPERLINK \l "_Toc300562969"  5	General Discussion of Uncertainties
and How They Have Been Addressed	  PAGEREF _Toc300562969 \h  37

  HYPERLINK \l "_Toc300562970"  5.1	Exposure Modeling Uncertainties
PAGEREF _Toc300562970 \h  37

  HYPERLINK \l "_Toc300562971"  5.2	Uncertainties in the Dose-Response
Relationships	  PAGEREF _Toc300562971 \h  38

  HYPERLINK \l "_Toc300562972"  5	References	  PAGEREF _Toc300562972 \h
46

Index of Tables

  TOC \h \z \t "Caption" \c    HYPERLINK \l "_Toc302113817"  Table 2.2-1
 AERMOD version 11103 model options for RTR modeling	  PAGEREF
_Toc302113817 \h  7

  HYPERLINK \l "_Toc302113818"  Table 2.6-1  (a)  Dose-Response Values
for Chronic Inhalation Exposure to Carcinogens	  PAGEREF _Toc302113818
\h  15

  HYPERLINK \l "_Toc302113819"  Table 2.6-1  (b)  Dose-Response Values
for Chronic Inhalation Exposure to Noncarcinogens	  PAGEREF
_Toc302113819 \h  16

  HYPERLINK \l "_Toc302113820"  Table 2.6-2  Dose-Response Values for
Acute Exposure	  PAGEREF _Toc302113820 \h  19

  HYPERLINK \l "_Toc302113821"  Table 3.1-1  Summary of Emissions from
the Mineral Wool Production Category and Availability of Dose-Response
Values	  PAGEREF _Toc302113821 \h  23

  HYPERLINK \l "_Toc302113822"  Table 3.2-1  Summary of Source Category
Level Inhalation Risks for Mineral Wool Production	  PAGEREF
_Toc302113822 \h  27

  HYPERLINK \l "_Toc302113823"  Table 4.2-1  Summary of Source Category
Level Inhalation Risks for Wool Fiberglass Manufacturing	  PAGEREF
_Toc302113823 \h  34

  HYPERLINK \l "_Toc302113824"  Table 4.2-2  Summary of Refined Acute
Results for Wool Fiberglass Manufacturing Facilities	  PAGEREF
_Toc302113824 \h  35

  HYPERLINK \l "_Toc302113825"  Table 4.2-3  Summary of Source Category
Level Cancer Risks for the Wool Fiberglass Manufacturing Auxiliary
Analysis	  PAGEREF _Toc302113825 \h  36

Appendices

Appendix 1	Emissions Inventory Support Memorandum

Appendix 1a - Emissions Data Used in Residual Risk Modeling for Mineral
Wool Production

Appendix 1b - Emissions Data Used in Residual Risk Modeling for Wool
Fiberglass Manufacturing

Appendix 2	Technical Support Document for HEM3 Modeling

Appendix 3	Meteorological Data for HEM3 Modeling

Appendix 4	Analysis of data on short-term emission rates relative to
long-term emission rates

Appendix 5	Technical Support Document for TRIM-Based Multipathway
Screening Scenario for RTR: Summary of Approach and Evaluation

Appendix 6	Detailed Risk Modeling Results

Appendix 7	Acute Impacts Refined Analysis

Appendix 8	Development of the Chronic Screening Level for Carbonyl
Sulfide

Index of Acronyms

AERMOD	American Meteorological Society/EPA Regulatory Model

AEGL		Acute exposure guideline level

ASTDR	US Agency for Toxic Substances and Disease Registry

CalEPA	California Environmental Agency

ERPG		Emergency Response Planning Guideline

HAP		Hazardous Air Pollutant

HEM		Human Exposure Model

HI		Hazard index

HQ		Hazard quotient

IRIS		Integrated Risk Information System

MACT		Maximum Achievable Control Technology

MIR		Maximum Individual Risk

MOA		Mode of action

NAC		National Advisory Committee

NATA 	National Air Toxics Assessment

NEI		National Emissions Inventory

NPRM		Notice of Proposed Rulemaking

PB-HAP	Persistent and Bioaccumulative - HAP

POM		Polycyclic organic matter

REL		Reference exposure level

RfC		Reference concentration

RfD		Reference dose

RTR		Risk and Technology

TOSHI		Target-organ-specific hazard index

URE		Unit risk estimate

Introduction

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

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

This document contains the methods and the results of baseline risk
assessments (i.e., after the implementation of the respective MACT
standards) performed for the Wool Fiberglass Manufacturing and Mineral
Wool Production source categories.  The methods discussion includes
descriptions of the methods used to develop refined estimates of chronic
inhalation exposures and human health risks for cancer and noncancer
endpoints, as well as descriptions of the methods used to screen for
acute health risks, chronic non-inhalation health risks, and adverse
environmental effects.  Since the screening assessments indicated low
potential for chronic non-inhalation health effects or environmental
impacts, including effects to threatened and endangered species, no
further refinement of these assessments was performed.

Methods

Emissions and source data

Mineral Wool

The 2002 National Emissions Inventory (NEI) data served as the starting
point for the mineral wool assessment.  Using the process MACT code, a
subset of the NEI was developed that contained facility, process, and
emissions data for each facility in the Mineral Wool Production source
category.  Those data were based on an emission factor developed from
one source test; emissions were estimated for all facilities based on
their production data reported in NEI, and were supplemented with other
emissions estimates in NEI.  In the 2008 proposal EPA requested comment
and new data that could inform that proposal.  After proposal, EPA
learned that the one plant for which we had test data had closed, some
facilities were missing from the NEI and others, listed in NEI, had
since closed.  As a result, EPA decided to collect 2010 industry process
and source test data under an information collection request that would
inform the risk review, the technology review (under 112(d)(6)), start
up and shutdown issues that emerged after the General Provisions
vacature, and a petition raised to the court following the vacature of
the Brick MACT.  These data underwent an extensive QA/QC procedure, and
revisions were made to the dataset as necessary.  The Mineral Wool ICR
emissions data and modifications made to the NEI data are discussed in
the Appendix 1a, entitled “Emissions Data Used in Residual Risk
Modeling for Mineral Wool Production.”

Wool Fiberglass

A voluntary ICR was sent out in March 2010 to the 29 wool fiberglass
facilities currently operating in the US.  ICR responses from all the
facilities were compiled in the project database and included
information on each facility, process, process equipment, control
equipment, costs, and HAP emissions.  Facility-specific production rate
information was also included and was claimed as confidential business
information (CBI), which resulted in much of the project database being
treated as CBI.

Emissions test data provided by the wool fiberglass industry varied
widely by facility.  Companies were allowed to, in lieu of new testing,
submit existing and well documented test data that was representative of
current operations and used the recommended test methods. A number of
facilities submitted existing test reports on one or more of the
following emission sources: glass melting furnaces, curing ovens,
forming, and collection operations. In order to fill data gaps in
existing data, new test data was also required.  Companies were,
however, allowed to test a subset of facility operations, if the
facilities were able to demonstrate that the tested subset was
representative of the untested subset.  Test results were typically
presented as three test runs and provided in units of mass of pollutant
per mass of production (e.g., lbs of HAP/ton of glass pulled).  A
combination of new and existing test data was used to populate the wool
fiberglass residual risk modeling file.  Using the glass pull rates
(generally given in tons of glass pulled/day) that each facility
provided in its ICR response and the source emission rates (lb/ton) from
emission testing, annual emissions (tpy) were calculated for each
pollutant and emission source.  For each source, stack heights,
diameters and coordinates were compiled from ICR responses and then sent
to each facility for confirmation.

The Wool Fiberglass ICR emissions data and modifications made to the NEI
data are discussed in the Appendix 1b, entitled “Emissions Data Used
in Residual Risk Modeling for Wool Fiberglass Manufacturing.”

Dispersion modeling for inhalation exposure assessment

Both long- and short-term inhalation exposure concentrations and
associated health risk from each facility in the source category of
interest were estimated using the Human Exposure Model in combination
with the American Meteorological Society/EPA Regulatory Model dispersion
modeling system (HEM3).  The approach used in applying this modeling
system is outlined below, and further details are provided in Appendix
2.  The HEM3 performs three main operations: atmospheric dispersion
modeling, estimation of individual human exposures and health risks, and
estimation of population risks.  This section focuses on the dispersion
modeling component.  The exposure and risk characterization components
are discussed in other subsections of Sections 2 and 3.

The dispersion model in the HEM3 system, AERMOD version 11103, is a
state-of-the-science Gaussian plume dispersion model that is preferred
by EPA for modeling point, area, and volume sources of continuous air
emissions from facility applications [].  Further details on AERMOD can
be found in the AERMOD Users Guide [].  The model is used to develop
annual average ambient concentrations through the simulation of
hour-by-hour dispersion from the emission sources into the surrounding
atmosphere.  Hourly emission rates used for this simulation are
generated by evenly dividing the total annual emission rate from the
inventory into the 8,760 hours of the year.

The first step in the application of the HEM3 modeling system is to
predict ambient concentrations at locations of interest.  The AERMOD
model options employed are summarized in Table 2.2-1 and are discussed
further below.

Table   STYLEREF 2 \s  2.2 -  SEQ Table \* ARABIC \s 2  1   AERMOD
version 11103 model options for RTR modeling

Modeling  Option	Selected Parameter for chronic exposure

Type of calculations	Hourly Ambient Concentration

Source type	Point,  area represented as pseudo point source

Receptor orientation	Polar (13 rings and 16 radials)

Discrete  (census block centroids)

Terrain characterization	Actual from USGS 1-degree DEM data

Building downwash	Not Included

Plume deposition/depletion	Not Included

Urban source option	No

Meteorology	1 year representative NWS from nearest site (over 200
stations)

In HEM3, meteorological data are ordinarily selected from a list of over
200 National Weather Service (NWS) surface observation stations across
the continental United States, Alaska, Hawaii, and Puerto Rico.  In most
cases the nearest station is selected as representative of the
conditions at the subject facility.  Ideally, when considering off-site
meteorological data most site specific dispersion modeling efforts will
employ up to five years of data to capture variability in weather
patterns from year to year.  However, because we had an insufficient
number of appropriately formatted model input files derived from
available meteorological data, we modeled only a single year, typically
1991.  While the selection of a single year may result in
under-prediction of long-term ambient levels at some locations, likewise
it may result in over-prediction at others.  For each facility
identified by its characteristic latitude and longitude coordinates, the
closest meteorological station was used in the dispersion modeling.  The
average distance between a modeled facility and the applicable
meteorological station was 40 miles (72 km).  Appendix 3 (Meteorological
Data Processing Using AERMET for HEM3) provides a complete listing of
stations and assumptions along with further details used in processing
the data through AERMET.  The sensitivity of model results to the
selection of the nearest weather station and the use of one year of
meteorological data is discussed in “Risk and Technology Review (RTR)
Risk Assessment Methodologies” [2].

The HEM3 system estimates ambient concentrations at the geographic
centroids of census blocks (using the 2000 Census), and at other
receptor locations that can be specified by the user.  The model
accounts for the effects of multiple facilities when estimating
concentration impacts at each block centroid.  Typically we combined
only the impacts of facilities within the same source category, and
assessed chronic exposure and risk only for census blocks with at least
one resident (i.e., locations where people may reasonably be assumed to
reside rather than receptor points at the fenceline of a facility).
Chronic ambient concentrations were calculated as the annual average of
all estimated short-term (one-hour) concentrations at each block
centroid.  Possible future residential use of currently uninhabited
areas was not considered.  Census blocks, the finest resolution
available in the census data, are typically comprised of approximately
40 people or about ten households.

In contrast to the development of ambient concentrations for evaluating
long-term exposures, which was performed only for occupied census
blocks, worst-case short-term (one-hour) concentrations were estimated
both at the census block centroids and at points nearer the facility
that represent locations where people may be present for short periods,
but generally no nearer than 100 meters from the center of the facility
(note that for large facilities, this 100-meter ring could still contain
locations inside the facility property).  Since short-term emission
rates were needed to screen for the potential for hazard via acute
exposures, and since the NEI contains only annual emission totals, we
generally apply the assumption to all source categories that the maximum
one-hour emission rate from any source is ten times the average annual
hourly emission rate for that source.

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

Census block elevations for HEM3 modeling were determined nationally
from the US Geological Service 1-degree digital elevation model (DEM)
data files, which have a spatial resolution of about 90 meters.
Elevations of polar grid points used in estimating short- and long-term
ambient concentrations were assumed to be equal to the highest elevation
of any census block falling within the polar grid sector corresponding
to the grid point.  If a sector does not contain any blocks, the model
defaults the elevation to that of the nearest block.  If an elevation is
not provided for the emission source, the model uses the average
elevation of all sectors within the innermost model ring.

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

Estimating human inhalation exposure

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

We did not address short-term human activity for two reasons.  First,
our experience with the  NATA assessments (which modeled daily activity
using EPA’s HAPEM model) suggests that, given our current
understanding of microenvironment concentrations and daily activities,
modeling short-term activity would, on average, reduce risk estimates
about 25% for particulate HAPs; it will also reduce risk estimates for
gaseous HAPs, but typically by much less.  Second, basing exposure
estimates on average ambient concentrations at census block centroids
may underestimate or overestimate actual exposure concentrations at some
residences.  Further reducing exposure estimates for the most highly
exposed residents by modeling their short-term behavior could add a
systematic low bias to these results.

We did not address long-term migration nor population growth or decrease
over 70 years, instead basing the assessment on the assumption that each
person’s predicted exposure is constant over the course of their
lifetime which is assumed to be 70 years.  In assessing cancer risk, we
generally estimated three metrics; the maximum individual risk (MIR),
which is defined as the risk associated with a lifetime of exposure at
the highest concentration; the population risk distribution; and the
cancer incidence.  The assumption of not considering short or long-term
population mobility does not bias the estimate of the theoretical MIR
nor does it affect the estimate of cancer incidence since the total
population number remains the same.  It does, however, affect the shape
of the distribution of individual risks across the affected population,
shifting it toward higher estimated individual risks at the upper end
and reducing the number of people estimated to be at lower risks,
thereby increasing the estimated number of people at specific risk
levels.

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

Acute Risk Screening and Refined Assessments

In establishing a scientifically defensible approach for the assessment
of potential health risks due to acute exposures to HAP, we followed the
same general approach that has been used for developing chronic health
risk assessments under the residual risk program.  That is, we developed
a tiered, iterative approach.  This approach to risk assessment was
endorsed by the National Academy of Sciences in its 1993 publication
“Science and Judgment in Risk Assessment” and subsequently was
adopted in the EPA’s “Residual Risk Report to Congress” in 1999.

The assessment methodology is designed to eliminate from further
consideration those facilities for which we have confidence that no
acute adverse health effects of concern will occur.  To do so, we use
what is called a tiered, iterative approach to the assessment.  This
means that we begin with a screening assessment, which relies on readily
available data and uses conservative assumptions that in combination
approximate a worst-case exposure.  The result of this screening process
is that either the facility being assessed poses no acute health risks
(i.e., it “screens out”), or that it requires further, more refined
assessment.  A refined assessment could use industry- or site-specific
data on the temporal pattern of emissions, the layout of emission points
at the facility, the boundaries of the facility, and/or the local
meteorology.  In some cases, all of these site-specific data would be
needed to refine the assessment; in others, lesser amounts of
site-specific data could be used to determine that acute exposures are
not a concern, and significant additional data collection would not be
necessary.

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

Peak 1-hour emissions were assumed to equal 10 times the average 1-hour
emission rates.

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

For facilities with multiple emission points, 1-hour concentrations at
each receptor were assumed to be the sum of the maximum concentrations
due to each emission point, regardless of whether those maximum
concentrations occurred during the same hour.

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

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

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

As mentioned above, when we identify acute impacts which exceed their
relevant benchmarks, we pursue refining our acute screening estimates.
For the Mineral Wool Production source category we used a refined
emissions multiplier of 3 to estimate the peak hourly emission rates
from the average rates.  Refer to a separate memorandum in the docket
for a detailed description of how the refined emissions multiplier was
developed for the Mineral Wool Production source category.  For the Wool
Fiberglass Manufacturing source category data were not available to
develop a refined emissions multiplier, therefore, the default emissions
multiplier of 10 was used.

Multipathway and environmental risk screening

The potential for significant human health risks due to exposures via
routes other than inhalation (i.e., multipathway exposures) was screened
by first determining whether any sources emitted any hazardous air
pollutants known to be persistent and bioaccumulative in the environment
(PB-HAP).  The PB-HAP compounds or compound classes are identified for
the screening from the EPA’s Air Toxics Risk Assessment Library [].
Examples of PB-HAP are cadmium compounds, chlordane, chlorinated
dibenzodioxins and furans, DDE, heptachlor, hexachlorobenzene,
hexachlorocyclohexane, lead compounds, mercury compounds, methoxychlor,
polychlorinated biphenyls, polycyclic organic matter (POM), toxaphene,
and trifluralin.  Emissions of lead, cadmium, and mercury were
identified in the emissions inventories for both the Mineral Wool
Production and Wool Fiberglass Manufacturing source categories.

These PB-HAP emissions were evaluated for potential non-inhalation risks
and adverse environmental impacts using our recently-developed screening
scenario which was developed for use with the TRIM.FaTE model.  This
screening scenario uses environmental media outputs from the
peer-reviewed TRIM.FaTE to estimate the maximum potential ingestion
risks for any specified emission scenario by using a generic
farming/fishing exposure scenario that simulates a subsistence
environment.  The screening scenario retains many of the ingestion and
scenario inputs developed for EPA’s Human Health Risk Assessment
Protocols (HHRAP) for hazardous waste combustion facilities.  In the
development of the screening scenario a sensitivity analysis was
conducted to ensure that its key design parameters were established such
that environmental media concentrations were not underestimated, and to
also minimize the occurrence of false positives for human health
endpoints.  See Appendix 5 for a complete discussion of the development
and testing of the screening scenario, as well as for the values of
facility-level emission rates developed for screening potentially
significant multi-pathway impacts.  For the purpose of developing
emission rates for our multi-pathway screening, we derived emission
levels for each PB HAP at which the maximum human health risk would be 1
in a million for lifetime cancer risk or a hazard quotient of 1.0 for
noncancer impacts.

In evaluating the potential multi-pathway risks from emissions of lead
compounds, rather than developing a screening emission rate for them, we
compared maximum estimated chronic (3-month average) atmospheric
concentrations with the current National Ambient Air Quality Standard
(NAAQS) for lead.  Values below the NAAQS were considered to have a low
potential for multi-pathway risks.

None of the facilities in the Mineral Wool Production or the Wool
Fiberglass Manufacturing source categories reported emissions of PB HAP
that were greater than the emission thresholds.   Therefore,
multi-pathway exposures and environmental risks were deemed negligible
and no further analysis was performed.

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

Dose-Response Assessment

Sources of chronic dose-response information

Dose-response assessment (carcinogenic and non-carcinogenic) for chronic
exposure (either by inhalation or ingestion) for the HAPs reported in
the emissions inventories for Wool Fiberglass Manufacturing and for
Mineral Wool Production  sources were based on the EPA Office of Air
Quality Planning and Standards’ existing recommendations for HAPs [],
also used for NATA [].  This information has been obtained from various
sources and prioritized according to (1) conceptual consistency with EPA
risk assessment guidelines and (2) level of peer review received.  The
prioritization process was aimed at incorporating into our assessments
the best available science with respect to dose-response information.
The recommendations are based on the following sources, in order of
priority:

US Environmental Protection Agency (EPA).  EPA has developed
dose-response assessments for chronic exposure for many of the
pollutants in this study.  These assessments typically provide a
qualitative statement regarding the strength of scientific data and
specify a reference concentration (RfC, for inhalation) or reference
dose (RfD, for ingestion) to protect against effects other than cancer
and/or a unit risk estimate (URE, for inhalation) or slope factor (SF,
for ingestion) to estimate the probability of developing cancer.  The
RfC is defined as an “estimate (with uncertainty spanning perhaps an
order of magnitude) of a continuous inhalation exposure to the human
population (including sensitive subgroups) that is likely to be without
an appreciable risk of deleterious effects during a lifetime.”  The
RfD is “an estimate (with uncertainty spanning perhaps an order of
magnitude) of a daily oral exposure to the human population (including
sensitive subgroups) that is likely to be without an appreciable risk of
deleterious effects during a lifetime.”   The URE is defined as “the
upper-bound excess cancer risk estimated to result from continuous
lifetime exposure to an agent at a concentration of 1 µg/m3 in air.”
The SF is “an upper bound, approximating a 95% confidence limit, on
the increased cancer risk from a lifetime exposure to an agent. This
estimate, [is] usually expressed in units of proportion (of a
population) affected per mg/kg-day…”  EPA disseminates dose-response
assessment information in several forms, based on the level of review.
The Integrated Risk Information System (IRIS) [] is an EPA database that
contains scientific health assessment information, including
dose-response information. All IRIS assessments since 1996 have also
undergone independent external peer review.  The current IRIS process
includes review by EPA scientists, interagency reviewers from other
federal agencies, and the public, and peer review by independent
scientists external to EPA.  New IRIS values are developed and old IRIS
values are updated as new health effects data become available.  Refer
to the “IRIS Track” website for detailed information on status and
scheduling of current individual IRIS assessments and updates (
HYPERLINK "http://cfpub.epa.gov/ncea/iristrac/index.cfm"
http://cfpub.epa.gov/ncea/iristrac/index.cfm ).  EPA’s science policy
approach, under the current carcinogen guidelines, is to use linear
low-dose extrapolation as a default option for carcinogens for which the
mode of action (MOA) has not been identified.  We expect future EPA
dose-response assessments to identify nonlinear MOAs where appropriate,
and we will use those analyses (once they are peer reviewed) in our risk
assessments.  At this time, however, there are no available carcinogen
dose-response assessments for inhalation exposure that are based on a
nonlinear MOA.

US Agency for Toxic Substances and Disease Registry (ATSDR).  ATSDR,
which is part of the US Department of Health and Human Services,
develops and publishes Minimum Risk Levels (MRLs) [] for inhalation and
oral exposure to many toxic substances.  As stated on the ATSDR web
site: “Following discussions with scientists within the Department of
Health and Human Services (HHS) and the EPA, ATSDR chose to adopt a
practice similar to that of the EPA's Reference Dose (RfD) and Reference
Concentration (RfC) for deriving substance specific health guidance
levels for non neoplastic endpoints.”  The MRL is defined as “an
estimate of daily human exposure to a substance that is likely to be
without an appreciable risk of adverse effects (other than cancer) over
a specified duration of exposure.”  ATSDR describes MRLs as
substance-specific estimates to be used by health assessors to select
environmental contaminants for further evaluation.  Exposures above an
MRL do not necessarily represent a threat, and MRLs are therefore not
intended for use as predictors of adverse health effects or for setting
cleanup levels.

California Environmental Protection Agency (CalEPA).  The CalEPA Office
of Environmental Health Hazard Assessment has developed dose-response
assessments for many substances, based both on carcinogenicity and
health effects other than cancer.  The process for developing these
assessments is similar to that used by EPA to develop IRIS values and
incorporates significant external scientific peer review.  As cited in
the CalEPA Technical Support Document for developing their chronic
assessments: “The guidelines for developing chronic inhalation
exposure levels incorporate many recommendations of the U.S. EPA [] and
NAS [].”  The non-cancer information includes available inhalation
health risk guidance values expressed as chronic inhalation reference
exposure levels (RELs) [].  CalEPA defines the REL as “the
concentration level at or below which no health effects are anticipated
in the general human population.”  CalEPA's quantitative dose-response
information on carcinogenicity by inhalation exposure is expressed in
terms of the URE [], defined similarly to EPA's URE.

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

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

Where possible for emissions of unspecified mixtures of HAP categories
such as metal compounds and POM, we apply category-specific chemical
speciation profiles appropriate to the source category to develop a
composite dose-response value for the category.

μg/m3) was based on better science than the IRIS dose-response value
(1.3 x 10-5 per μg/m3), and we switched from using the IRIS value to
the CIIT value in risk assessments supporting regulatory actions.  Based
on subsequent published research, however, EPA changed its determination
regarding the CIIT model and in 2010 the EPA returned to using 1991 IRIS
value. [US EPA, 2010.] [ ]  EPA has been working on revising the
formaldehyde IRIS assessment and the National Academy of Sciences (NAS)
completed its review of the EPA’s draft assessment in May of 2011 and
EPA has been working on revising the formaldehyde assessment
(http://www.nap.edu/catalog.php?record_id=13142).  EPA is reviewing the
public comments and the NAS independent scientific peer review.  EPA
will follow the NAS Report recommendations and will present results
obtained by implementing the BBDR model for formaldehyde.  EPA will
compare these estimates with those currently presented in the External
Review draft of the assessment and will discuss their strengths and
weaknesses.  As recommended by the NAS committee, appropriate
sensitivity and uncertainty analyses will be an integral component of
implementing the BBDR model.  The draft IRIS assessment will be revised
in response to the NAS peer review and public comments and the final
assessment will be posted on the IRIS database.  In the interim, we will
present findings using the 1991 IRIS value as a primary estimate, and
may also consider other information as the science evolves.

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

A chronic screening level of 163 ug/m3was developed for carbonyl sulfide
(COS) from a No Observed Adverse Effects Level (NOAEL) of 200 ppm based
on brain lesions and neurophysiological alterations in rodents.  A more
detailed discussion of the studies used to develop the COS chronic
screening level is provided in Appendix 8.  The screening level includes
a total uncertainty factor (UF) of 3,000: 10x for extrapolation for
interspecies differences, 10x for consideration of intraspecies
variability, 10x for extrapolation from subchronic to chronic duration,
and 3x for database insufficiencies.  See section 5 of this document for
a detailed discussion of exposure modeling uncertainties.

The chronic screening level for COS is used only as a screening level
assessment to identify areas with significant inhalation risk potential.
 A high COS chronic risk based on the screening level does not
necessarily indicate that further action is required.

The emissions inventory for the Wool Fiberglass Manufacturing and for
the Mineral Wool Production source categories includes emissions of 14
HAP with available chronic quantitative inhalation dose-response values.
 These HAP, their dose-response values, and the source of the values are
listed in Tables 2.6-1 (a) and (b).

Table 2.6-1  (a)  Dose-Response Values for Chronic Inhalation Exposure
to Carcinogens

URE (unit risk estimate for cancer) = cancer risk per μg/m3 of average
lifetime exposure.  Sources: IRIS = EPA Integrated Risk Information
System, CAL = California EPA Office of Environmental Health Hazard
Assessment.

Pollutant	CAS Number	URE5

 (1/μg/m3)	Source

Arsenic compounds	7440382	4.3E-03	IRIS

Beryllium compounds	7440417	2.4E-03	IRIS

Cadmium compounds	7440439	1.8E-03	IRIS

Chromium (VI) compounds	18540299	1.2E-02	IRIS

Formaldehydea	50000	1.3E-05	IRIS

The EPA has used the CIIT URE value, 5.5X10-9 per mg/m3, to characterize
formaldehyde cancer risk in some instances.

Table 2.6-1  (b)  Dose-Response Values for Chronic Inhalation Exposure
to Noncarcinogens

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

Pollutant	CAS Number6	RfC

(mg/m3)	Source

Arsenic compounds	7440382	1.5E-05	CAL

Beryllium compounds	7440417	2.0E-05	IRIS - M

Cadmium compounds	7440439	1.0E-05	ATSDR-D

Carbonyl sulfide	463581	0.163	ORD Screening

Chromium (VI) compounds	18540299	1.0E-04	IRIS - M

Formaldehyde	50000	0.0098	ATSDR

Hydrochloric acid	7647010	0.02	IRIS - L

Lead compounds	7439921	1.5E-04	EPA OAQPS

Manganese	7439965	5.0E-05	IRIS - M

Methanol	67561	4	CAL

Mercury (elemental)	7439976	3.0E-4	IRIS - M

Nickel compounds	7440020	9.0E-05	ATSDR

Phenol	10952	0.2	CAL

Selenium compounds	7782492	0.02	CAL

Sources of acute dose-response information

Hazard identification and dose-response assessment information for
preliminary acute inhalation exposure assessments are based on the
existing recommendations of OAQPS for HAPs [].  Depending on
availability, the results from screening acute assessments are compared
to both “no effects” reference levels for the general public, such
as the California Reference Exposure Levels (RELs), as well as emergency
response levels, such as Acute Exposure Guideline Levels (AEGLs) and
Emergency Response Planning Guidelines (ERPGs), with the recognition
that the ultimate interpretation of any potential risks associated with
an estimated exceedance of a particular reference level depends on the
definition of that level and any limitations expressed therein.
Comparisons among different available inhalation health effect reference
values (both acute and chronic) for selected HAPs can be found in an EPA
document [].

California Acute Reference Exposure Levels (RELs).  The California
Environmental Protection Agency (CalEPA) has developed acute
dose-response reference values for many substances, expressing the
results as acute inhalation Reference Exposure Levels (RELs).

The acute REL ( HYPERLINK "http://www.oehha.ca.gov/air/pdf/acuterel.pdf"
http://www.oehha.ca.gov/air/pdf/acuterel.pdf ) is defined by CalEPA as
“the concentration level at or below which no adverse health effects
are anticipated for a specified exposure duration [].  RELs are based on
the most sensitive, relevant, adverse health effect reported in the
medical and toxicological literature.  RELs are designed to protect the
most sensitive individuals in the population by the inclusion of margins
of safety.  Since margins of safety are incorporated to address data
gaps and uncertainties, exceeding the REL does not automatically
indicate an adverse health impact.”  Acute RELs are developed for
1-hour (and 8-hour) exposures. The values incorporate uncertainty
factors similar to those used in deriving EPA’s Inhalation Reference
Concentrations (RfCs) for chronic exposures (and, in fact, California
also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs).  AEGLs are developed by the
National Advisory Committee (NAC) on Acute Exposure Guideline Levels
(NAC/AEGL) for Hazardous Substances, and then reviewed and published by
the National Research Council  As described in the Committee’s
“Standing Operating Procedures (SOP)” ( HYPERLINK
"http://www.epa.gov/opptintr/aegl/pubs/sop.pdf"
http://www.epa.gov/opptintr/aegl/pubs/sop.pdf ), AEGLs “represent
threshold exposure limits for the general public and are applicable to
emergency exposures ranging from 10 min to 8 h.”  Their intended
application is “for conducting risk assessments to aid in the
development of emergency preparedness and prevention plans, as well as
real time emergency response actions, for accidental chemical releases
at fixed facilities and from transport carriers.”  The document states
that “the primary purpose of the AEGL program and the NAC/AEGL
Committee is to develop guideline levels for once-in-a-lifetime,
short-term exposures to airborne concentrations of acutely toxic,
high-priority chemicals.”  In detailing the intended application of
AEGL values, the document states that, “It is anticipated that the
AEGL values will be used for regulatory and nonregulatory purposes by
U.S. Federal and State agencies, and possibly the international
community in conjunction with chemical emergency response, planning, and
prevention programs.  More specifically, the AEGL values will be used
for conducting various risk assessments to aid in the development of
emergency preparedness and prevention plans, as well as real-time
emergency response actions, for accidental chemical releases at fixed
facilities and from transport carriers.”

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

“AEGL-1 is the airborne concentration (expressed as ppm or mg/m3) 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.”

“AEGL-2 is the airborne concentration (expressed as ppm or mg/m3) of a
substance above which it is predicted that the general population,
including susceptible individuals, could experience irreversible or
other serious, long-lasting adverse health effects or an impaired
ability to escape.”

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

Emergency Response Planning Guidelines (ERPGs).  The American Industrial
Hygiene Association (AIHA) has developed Emergency Response Planning
Guidelines (ERPGs) [] for acute exposures at three different levels of
severity.  These guidelines represent concentrations for exposure of the
general population (but not particularly sensitive persons) for up to 1
hour associated with effects expected to be mild or transient (ERPG-1),
irreversible or serious (ERPG-2), and potentially life-threatening
(ERPG-3).

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

ERPG-1 and ERPG-2 values are defined by AIHA as follows:

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

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

The emissions inventory for the Wool Fiberglass Manufacturing and for
the Mineral Wool Production source categories includes emissions of 9
HAP with relevant and available quantitative acute dose-response
threshold values.  These HAPs, their acute threshold values, and the
source of the value are listed below in Table 2.6-2.

Table 2.6-2  Dose-Response Values for Acute Exposure

Pollutant	CAS Number	AEGL-1

(1-hr)

(mg/m3)	AEGL-2

(1-hr)

(mg/m3)	ERPG-1

(mg/m3)	ERPG-2

(mg/m3)	REL

Arsenic compounds	7440382

	0.0002

Beryllium compounds	7440417

0.025

	Carbonyl sulfide	463581

140

	Formaldehyde	50000	1.1	17	1.1	17	0.055

Hydrochloric acid	7647010	2.7	33	2.7	33	2.1

Mercury (elemental) 	7439976

1.7

2	0.0006

Methanol	67561	690	2700	690	2700	28

Nickel	7440020

	0.006

Phenol	108952	58	89	58	89	5.8

Risk Characterization

General

The final product of the risk assessment is the risk characterization,
in which the information from the previous steps is integrated and an
overall conclusion about risk is synthesized that is complete,
informative, and useful for decision makers.  In general, the nature of
this risk characterization depends on the information available, the
application of the risk information and the resources available.  In all
cases, major issues associated with determining the nature and extent of
the risk are identified and discussed.  Further, the EPA
Administrator’s March 1995 Policy for Risk Characterization []
specifies that a risk characterization “be prepared in a manner that
is clear, transparent, reasonable, and consistent with other risk
characterizations of similar scope prepared across programs in the
Agency.”  These principles of transparency and consistency have been
reinforced by the Agency’s Risk Characterization Handbook [], in 2002
by the Agency’s information quality guidelines [], and in the OMB/OSTP
September 2007 Memorandum on Updated Principles for Risk Analysis, and
are incorporated in these assessments.

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

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

For EPA’s list of carcinogenic HAPs that act by a mutagenic
mode-of-action [], we applied EPA’s Supplemental Guidance for
Assessing Susceptibility from Early-Life Exposure to Carcinogens [].
This guidance has the effect of adjusting the URE by factors of 10 (for
children aged 0-1), 3 (for children aged 2-15), or 1.6 (for 70 years of
exposure beginning at birth), as needed in risk assessments.  In this
case, this has the effect of increasing the estimated life time risks
for these pollutants by a factor of 1.6.  In addition, although only a
small fraction of the total POM emissions may be reported as individual
compounds, EPA expresses carcinogenic potency for compounds in this
group in terms of benzo[a]pyrene equivalence, based on evidence that
carcinogenic POM have the same mutagenic mechanism of action as does
benzo[a]pyrene.  For this reason, EPA implementation policy []
recommends applying the Supplemental Guidance to all carcinogenic PAHs
for which risk estimates are based on relative potency.  Accordingly, we
applied the Supplemental Guidance to all unspeciated POM mixtures.

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

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

The risk characterization for chronic effects other than cancer is
expressed in terms of the HQ for inhalation, calculated for each HAP at
each census block centroid.  As discussed above, RfCs incorporate
generally conservative uncertainty factors in the face of uncertain
extrapolations, such that an HQ greater than one does not necessarily
suggest the onset of adverse effects.  The HQ cannot be translated to a
probability that adverse effects will occur, and is unlikely to be
proportional to adverse health effect outcomes in a population.

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

Mixtures

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

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

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

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

Risk Results for the Mineral Wool Production

Source Category Description and Results

Mineral wool is a fibrous, glassy substance made from natural rock (such
as basalt), blast furnace slag, or other similar materials and
consisting of silicate fibers typically 4 to 7 micrometers in diameter.
In the mineral wool manufacturing process, rock and/or blast furnace
slag and other raw materials (e.g., gravel) are melted in a furnace
(cupola) using coke as fuel.  The molten material is then formed into
fiber.  Mineral wool is manufactured as either a “bonded” product
that incorporates a binder to increase structural rigidity or a less
rigid “nonbonded” product.  The production of bonded mineral wool
involves the application of a HAP-based binder to the fiber, where the
binder is typically composed of a phenol-formaldehyde resin, water,
urea, silane, ammonia, and ammonium sulfate.  The application of binder
is followed by thermosetting in a curing oven and cooling of the
finished product.  Sources that manufacture only nonbonded fibers would
not include the processes of binder application and curing.   Emission
sources at mineral wool production facilities include the cupola furnace
where the mineral charge is melted;  a blow chamber, in which air or a
binder is drawn over the fibers, forming them into a screen;  a curing
oven that bonds the fibers (for bonded products);  and a cooling oven.

In 1997 when the mineral wool MACT rule was proposed, EPA estimated that
there were 16 major source mineral wool production facilities in the
United States that would be subject to the rule.  Currently, there are
seven mineral wool production facilities nationwide.  Based on emissions
data collected from the industry, these 7 facilities emitted a reported
total of 462 tons/year of HAP into the atmosphere.  Refer to Appendix 1
for details on how the emissions inventory was developed.

Table 3.1-1 summarizes the emissions for the Mineral Wool Production
source category.  Based on these data, the HAP emitted in largest
quantities in total from these facilities are carbonyl sulfide,
formaldehyde, phenol, hydrochloric acid, and hydrogen fluoride;
emissions of these 5 pollutants account for 99.8 percent of the total
HAP emissions by mass from the data set.  Carbonyl sulfide, hydrochloric
acid, and hydrogen fluoride were reported as an emission for all of the
facilities.  Formaldehyde and phenol are also emitted in large
quantities, but from fewer facilities; no more than three facilities
report emissions of any one of these HAP.  Formaldehyde and phenol are
emitted only from bonded mineral wool fiber manufacturing, which
includes emissions from the application of the binder, curing, and
cooling.  Raw material feed rates in mineral wool processes are
essentially constant with minimal fluctuation (approximately ± 10
percent).  Consequently, emissions also have minimal fluctuation [].  In
refining the acute risk assessment, a short-term emissions multiplier of
3 was used to estimate the maximum hazard from acute exposures.  See
separate memo on the Mineral Wool Acute Factor in the project docket for
a detailed description of how the refined emissions multiplier was
developed for the Mineral Wool Production source category.  Emissions of
PB HAP reported in the data set for the mineral wool production source
category include lead, cadmium, and mercury compounds.

Table 3.1-1  Summary of Emissions from the Mineral Wool Production
Category and Availability of Dose-Response Values

HAP	Emissions (tpy)	Number of Facilities Reporting HAP (7 facilities in
data set) 	Prioritized Inhalation Dose-Response Value Identified by
OAQPSa	PB-HAP?

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

	Carbonyl Sulfide	224	7

	Y

	Phenol	177	3

Y	Y

	Hydrochloric acid	23	7

Y	Y

	Formaldehyde	20	3	Y	Y	Y

	Hydrogen Fluoride	17	7

Selenium	0.28	7

Y

Methanol	0.16	3

Y	Y

	Manganese	0.14	7

Y

Chromium III	0.04	7

Lead	0.03	7

Y

Y

Arsenic	0.03	7	Y	Y	Y

	Nickel	0.024	7

Y	Y

	Antimony	0.002	7

Cadmium	0.002	7	Y	Y

Y

Cobalt	0.0013	7

Y

Elemental Gaseous Mercury	0.0005	6

Y	Y	Y

Chromium (VI)	0.0003	7	Y	Y

Berylium	0.0002	7	Y	Y	Y

	Gaseous Divalent Mercury	0.0001	6

Y

Particulate Divalent Mercury	0.0001	6

Y

a Tables 2.6-1 (a) and (b) of this report contain the URE and RfC values
for the HAP emitted from mineral wool production facilities.  Table
2.6-2 of this report contains the acute noncancer values for the HAP
emitted from mineral wool production facilities. Specific dose-response
values for each chemical are identified on EPA’s Technology Transfer
Network website for air toxics at  HYPERLINK
"http://www.epa.gov/ttn/atw/toxsource/summary.html"
http://www.epa.gov/ttn/atw/toxsource/summary.html .

Risk Characterization

This section presents the results of the risk assessment for the Mineral
Wool Production source category.  The basic chronic inhalation risk
estimates presented here are the maximum individual lifetime cancer
risk, the maximum chronic hazard index, and the cancer incidence.  We
also present results from our acute inhalation impact screening in the
form of maximum hazard quotients, as well as the results of our
preliminary screen for potential non-inhalation risks from PB HAP.  Also
presented are the HAP “drivers,” which are the HAP that collectively
contribute 90 percent of the maximum cancer risk or maximum hazard index
at the highest exposure location.

Tables 3.2-1 and 3.2-2 summarize the chronic and acute inhalation risk
results for this source category.  The results for the Mineral Wool
Production source category indicate that maximum lifetime individual
cancer risks could be as high as 4 in a million.  The major contributor
to this risk is formaldehyde.  Approximately 1,650 people were estimated
to have cancer risks above 1 in a million as a result of the emissions
from 1 facility.  The maximum chronic non-cancer TOSHI value for the
source category could be up to 0.04 with emissions of formaldehyde
dominating those impacts, indicating no significant potential for
chronic noncancer impacts.

Worst-case screening acute hazard quotients (HQs) were calculated for
every HAP shown in Table 3.1-1 that has an acute benchmark, and the
highest acute HQ (REL of 8 for formaldehyde) is shown in Table 3.2-1.  A
refined emissions multiplier of 3 was used to estimate the peak hourly
emission rates from the average rates.  Refer to a separate memorandum
in the docket for a detailed description of how the refined emissions
multiplier was developed for the Mineral Wool Production source
category.  For cases where the screening acute HQ was greater than 1, we
further refined the estimates by determining the highest HQ value that
is outside facility boundaries.  In this case, the refined analysis did
not change the acute analysis results.  Table 3.2-2 provides more
information on the acute risk estimates for formaldehyde, the only HAP
that had a worst-case screening acute HQ greater than 1 for any
benchmark.

To better characterize the potential health risks associated with
estimated worst-case acute exposures to HAP, and in response to a key
recommendation from the Science Advisory Board’s peer review of
EPA’s RTR risk assessment methodologies, we examine a wider range of
available acute health metrics than we do for our chronic risk
assessments.  This is in response to the acknowledgement that there are
generally more data gaps and inconsistencies in acute reference values
than there are in chronic reference values.  By definition, the acute
CA-REL represents a health-protective level of exposure, with no risk
anticipated below those levels, even for repeated exposures; however,
the health risk from higher-level exposures is unknown.  Therefore, when
a CA-REL is exceeded and an AEGL-1 or ERPG-1 level is available (i.e.,
levels at which mild effects are anticipated in the general public for a
single exposure), we have used them as a second comparative measure.
Historically, comparisons of the estimated maximum off-site one-hour
exposure levels have not been typically made to occupational levels for
the purpose of characterizing public health risks in RTR assessments.
This is because occupational ceiling values are not generally considered
protective for the general public since they are designed to protect the
worker population (presumed healthy adults) for short duration (<15
minute) increases in exposure.  As a result, for most chemicals, the
15-minute occupational ceiling values are set at levels higher than a
one-hour AEGL-1, making comparisons to them irrelevant unless the AEGL-1
or ERPG-1 levels are exceeded13.  Such is not the case when comparing
the available acute inhalation health effect reference values for
formaldehyde13.

The worst-case maximum estimated 1-hour exposure to formaldehyde outside
the facility fence line for the mineral wool production source category
is 0.47 mg/m3.  This estimated worst-case exposure exceeds the 1-hour
REL by a factor of 8 (HQREL = 8) and is below the 1-hour AEGL-1
(HQAEGL-1 = 0.4).  This exposure estimate does not exceed the AEGL-1, or
exceed the workplace ceiling level guideline for the formaldehyde value
developed by National Institutes for Occupational Safety and Health
(NIOSH) “for any 15 minute period in a work day” (NIOSH REL-ceiling
value of 0.12 mg/m3; HQNIOSH = 4).  The estimate is at the value
developed by the American Conference of Governmental Industrial
Hygienists (ACGIH) as “not to be exceeded at any time” (ACGIH
TLV-ceiling value of 0.37 mg/m3; HQACGIH = 1).  Additionally, the
estimated maximum acute exposure exceeds the Air Quality Guideline value
that was developed by the World Health Organization for 30-minute
exposures (0.1 mg/m3; HQWHO = 5).

Chronic noncancer target organ specific hazard indices (HIs) were
calculated for every HAP shown in Table 3.1-1 that has a chronic
benchmark, and the highest target organ specific HI (0.04 for
formaldehyde) is shown in Table 3.2-1.  There were no HIs greater than 1
for this source category.

We conducted a screening-level evaluation of the potential human health
risks associated with emissions of PB HAP.  Reported emissions of PB HAP
were compared to emission thresholds established by EPA for the purposes
of the RTR risk assessments.   The PB HAPs emitted by facilities in this
category are lead, cadmium, and mercury.  All lead, cadmium, and mercury
emissions were below the threshold levels, indicating no potential for
significant multi-pathway risks from these facilities.

Analysis of potential differences between actual emissions levels and
the maximum emissions allowable under the MACT standards indicated that
MACT allowable emission levels may be up to 3 times greater than actual
emissions levels.  Considering this difference, the risk results from
the inhalation risk assessment indicate that the maximum excess lifetime
individual cancer risk could be up to 10 in a million, and that the
maximum chronic noncancer TOSHI value could be as high as 0.1 at the
MACT-allowable emissions level.

Table 3.2-1  Summary of Source Category Level Inhalation Risks for
Mineral Wool Production

Result	HAP “Drivers”

Facilities in Source Category

Number of Facilities Estimated to be in Source Category	7	n/a

Number of Facilities Identified in the NEI and Modeled in Preliminary
Risk Assessment	7	n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 1 million)	4	formaldehyde

Number of Facilities with Maximum Individual Lifetime Cancer Risk:

	Greater than or equal to 100 in 1 million	0	n/a

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

	Greater than or equal to 1 in 1 million	1	formaldehyde

Chronic Noncancer Risks

Maximum Hazard Index 	0.04	formaldehyde

Number of Facilities with Maximum Respiratory Hazard Index:

	Greater than 1	0	n/a

Refined Acute Noncancer Screening Results

Maximum Acute Hazard Quotient [using scaling factor of 3]	8

0.4

	formaldehyde (REL)

formaldehyde (AEGL-1, ERPG-1))

Number of Facilities With Potential for Acute Effects	1	formaldehyde

Population Exposure

Number of People Living Within 50 Kilometers of Facilities Modeled
3,700,000	n/a

Number of People Exposed to Cancer Risk:

	Greater than or equal to 100 in 1 million	0	n/a

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

	Greater than or equal to 1 in 1 million	1,700	n/a

Number of People Exposed to Noncancer Respiratory Hazard Index:

	Greater than 1	0	n/a

Estimated Cancer Incidence (excess cancer cases per year)	0.000418	n/a

Contribution of HAP to Cancer Incidence:

     Formaldehyde

     Arsenic compounds

	64%

33%

	n/a

Table 3.2-2  Summary of Refined Acute Results for Mineral Wool
Production Facilities

Refined Results	MAXIMUM ACUTE HAZARD QUOTIENTS	ACUTE DOSE-RESPONSE
VALUES

	Based on REL	Based on AEGL-1/

ERPG-1	Based on AEGL-2/

ERPG-2	REL

(mg/m3)	AEGL-1 (1-hr) (mg/m3)	ERPG-1 (mg/m3)	AEGL-2

(1-hr)

(mg/m3)	ERPG-2 (mg/m3)

HAP	Max. 1-hr. Air Conc. (mg/m3)

Formaldehyde	0.47	8	0.4	0.027	0.055	1.1	1.1	17	17

Notes on Refined Process:

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

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

Notes on Acute Dose-Response Values:

 	REL – California EPA reference exposure level for no adverse
effects.  Most, but not all, RELs are for 1-hour exposures.

	AEGL – Acute exposure guideline levels represent emergency exposure
(1-hour) limits for the general public.

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

AEGL-2 is the exposure level above which it is predicted that the
general population, including susceptible individuals, could experience
irreversible or other serious, long-lasting adverse health effects of an
impaired ability to escape.

	EPRG – Emergency Removal Program guidelines represent emergency
exposure (1-hour) limits for the general public.

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

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

Risk Results for the Wool Fiberglass Manufacturing Source Category

Source Category Description and Results

Wool fiberglass is manufactured in a process that forms thin fibers from
molten glass. A typical wool fiberglass manufacturing line consists of
the following processes: (1) Preparation of molten glass, (2) formation
of fibers into a wool fiberglass mat, (3) curing the binder-coated
fiberglass mat, (4) cooling the mat (not always present), and (5)
backing, cutting, and packaging.  Typically, the binder consists of a
solution of phenol-formaldehyde resin, water, urea, lignin, silane, and
ammonia. Wool fiberglass products are primarily used as thermal and
acoustical insulation for buildings, automobiles, aircraft, appliances,
ductwork, and pipes. Other uses include liquid and air filtration.
Approximately 90 percent of the wool fiberglass currently produced is
for building insulation products.

The NESHAP for the Wool Fiberglass Manufacturing source category was
promulgated on June 14, 1999 (62 FR 31695) and codified at 40 CFR part
63, subpart DDD.  The 1999 NESHAP (40 CFR 63.1381) defines a “wool
fiberglass manufacturing facility” as “any facility manufacturing
wool fiberglass on a rotary spin manufacturing line or on a flame
attenuation manufacturing line.”  The MACT rule for the Wool
Fiberglass Manufacturing source category does not apply to facilities
that manufacture mineral wool from rock, slag, and other similar
materials.  Wool fiberglass is currently manufactured in the United
States by 6 companies operating 29 plants in 16 States.  Nine of these
facilities are not considered major sources.

HAP are emitted from wool fiberglass glass-melting furnaces, including
arsenic, chromium, and lead.  Organic HAP (formaldehyde, phenol, and
methanol) are released from RS forming, curing, and cooling processes
and FA forming and curing processes.  Formaldehyde, phenol, and methanol
are emitted from wool fiberglass plants that use HAP in their binders.
Some furnaces also emit high risk metals including hexavalent chromium.

The emissions for the Wool Fiberglass Manufacturing source category data
set (of 29 facilities) are summarized in Table 4.1-1.  The total HAP
emissions for the source category are approximately 1,874 tons per year.
 Based on these data, the HAP emitted in the largest quantities across
these 29 facilities are: methanol, formaldehyde, phenol, hydrogen
fluoride, and hydrochloric acid.  Emissions of these 5 HAP make up 99.93
percent of the total emissions by mass.  For the Wool Fiberglass
Manufacturing source category, data were not available to develop a
refined emissions multiplier.  Therefore, the default emissions
multiplier of 10 was used for the acute risk analysis.  Persistent and
bioaccumulative HAP (PB HAP) reported as emissions from these facilities
include lead, cadmium, and mercury compounds.

Table 4.1-1  Summary of Emissions from the Wool Fiberglass Manufacturing
Category and Availability of Dose-Response Values

HAP	Emissions (tpy)	Number of Facilities Reporting HAP (29 facilities in
data set) 	Prioritized Inhalation Dose-Response Value Identified by
OAQPSa	PB-HAP?

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

	Phenol	403	26

Y	Y

	Hydrochloric acid	12	29

Y	Y

	Formaldehyde	618	26	Y	Y	Y

	Hydrogen Fluoride	20	29

Selenium	0.15	29

Y

Methanol	820	26

Y	Y

	Manganese	0.13	29

Y

Chromium III	0.05	29

Lead	0.14	29

Y

Y

Arsenic	0.05	29	Y	Y	Y

	Nickel	0.12	29

Y	Y

	Antimony	0.04	29

Cadmium	0.02	29	Y	Y

Y

Cobalt	0.02	29

Y

Elemental Gaseous Mercury	0.04	29

Y	Y	Y

Chromium (VI)	0.52	29	Y	Y

Berylium	0.009	29	Y	Y	Y

	Gaseous Divalent Mercury	0.005	29

Y

Particulate Divalent Mercury	0.005	29

Y

a Notes for how HAP were speciated for risk assessment:

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

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

Risk Characterization

This section presents the results of the risk assessment for the Wool
Fiberglass Manufacturing source category.  The basic chronic inhalation
risk estimates presented here are the maximum individual lifetime cancer
risk, the maximum chronic hazard index, and the cancer incidence.  We
also present results from our acute inhalation impact screening in the
form of maximum hazard quotients, as well as the results of our
preliminary screen for potential non-inhalation risks from PB HAP.  Also
presented are the HAP “drivers,” which are the HAP that collectively
contribute 90 percent of the maximum cancer risk or maximum hazard index
at the highest exposure location.

Tables 4.2-1 and 4.2-2 summarize the chronic and acute inhalation risk
results for this source category. The results for the Wool Fiberglass
Manufacturing source category indicate that maximum lifetime individual
cancer risks could be as high as 40 in a million.  The major contributor
to the risk is Chromium (VI).  Approximately 849,000 people were
estimated to have cancer risks above 1 in a million as a result of the
emissions from 15 facilities.  The maximum chronic non-cancer TOSHI
value for the source category could be up to 0.2 with emissions of
formaldehyde dominating those impacts, indicating no significant
potential for chronic noncancer impacts.

Worst-case acute hazard quotients (HQs) were calculated for every HAP
shown in Table 4.1-1 that has an acute benchmark, and the highest acute
HQ REL of 30  for formaldehyde is shown in Table 4.2-1.  For cases where
the screening acute HQ was greater than 1, we further refined the
estimates by determining the highest HQ value that is outside facility
boundaries.  In this case, the refined analysis did not change the acute
analysis results.  Table 4.2-2 provides more information on the acute
risk estimates for formaldehyde, the only HAP that had a worst-case
screening acute HQ greater than 1 for any benchmark.

To better characterize the potential health risks associated with
estimated worst-case acute exposures to HAP, and in response to a key
recommendation from the Science Advisory Board’s peer review of
EPA’s RTR risk assessment methodologies, we examine a wider range of
available acute health metrics than we do for our chronic risk
assessments.  This is in response to the acknowledgement that there are
generally more data gaps and inconsistencies in acute reference values
than there are in chronic reference values.  By definition, the acute
CA-REL represents a health-protective level of exposure, with no risk
anticipated below those levels, even for repeated exposures; however,
the health risk from higher-level exposures is unknown.  Therefore, when
a CA-REL is exceeded and an AEGL-1 or ERPG-1 level is available (i.e.,
levels at which mild effects are anticipated in the general public for a
single exposure), we have used them as a second comparative measure.
Historically, comparisons of the estimated maximum off-site one-hour
exposure levels have not been typically made to occupational levels for
the purpose of characterizing public health risks in RTR assessments.
This is because occupational ceiling values are not generally considered
protective for the general public since they are designed to protect the
worker population (presumed healthy adults) for short duration (<15
minute) increases in exposure.  As a result, for most chemicals, the
15-minute occupational ceiling values are set at levels higher than a
one-hour AEGL-1, making comparisons to them irrelevant unless the AEGL-1
or ERPG-1 levels are exceeded21.  Such is not the case when comparing
the available acute inhalation health effect reference values for
formaldehyde21.

The worst-case maximum estimated 1-hour exposure to formaldehyde outside
the facility fence line for the wool fiberglass manufacturing source
category is 1.92 mg/m3.  This estimated worst-case exposure exceeds the
1-hour REL by a factor of 30 (HQREL = 30) and the 1-hour AEGL-1
(HQAEGL-1 = 2).  This exposure estimate also exceeds multiple workplace
ceiling level guidelines for formaldehyde, including the value developed
by the American Conference of Governmental Industrial Hygienists (ACGIH)
as “not to be exceeded at any time” (ACGIH TLV-ceiling value of 0.37
mg/m3; HQACGIH = 5), and the value developed by the National Institutes
for Occupational Safety and Health (NIOSH) “for any 15 minute period
in a work day” (NIOSH REL-ceiling value of 0.12 mg/m3; HQNIOSH = 16).
Additionally, the estimated maximum acute exposure exceeds the Air
Quality Guideline value that was developed by the World Health
Organization for 30-minute exposures (0.1 mg/m3; HQWHO = 19).

Chronic noncancer target organ specific hazard indices (HIs) were
calculated for every HAP shown in Table 4.1-1 that has a chronic
benchmark, and the highest target organ specific HI (0.2 for
formaldehyde) is shown in Table 4.2-1.  There were no HIs greater than 1
for this source category.

For this source category, EPA conducted a screening-level evaluation of
the potential human health risks associated with emissions of PB HAP.
Reported emissions of PB HAP were compared to emission thresholds
established by EPA for the purposes of the RTR risk assessments.  The PB
HAP emitted by facilities in this category are lead, cadmium, and
mercury.  All lead, cadmium, and mercury emissions were below the
threshold levels, indicating no potential for significant multi-pathway
risks from these facilities.

Analysis of potential differences between actual emissions levels and
the maximum emissions allowable under the MACT standards indicated that
MACT allowable emission levels may be up to 3 times greater than actual
emissions levels for phenol, methanol, and formaldehyde emissions.  For
hexavalent chromium emissions the allowable emissions are equal to
actual emissions since there is no hexavalent chromium emission limit in
the MACT standard.  Considering this difference, the risk results from
the inhalation risk assessment indicate that the maximum excess lifetime
individual cancer risk could be up to 60 in a million, and that the
maximum chronic noncancer TOSHI value could be as high as 0.5 at the
MACT-allowable emissions level.

Table 4.2-1  Summary of Source Category Level Inhalation Risks for Wool
Fiberglass Manufacturing

Result

HAP “Drivers”

Number of Facilities Estimated to be in Source Category	29	n/a

Number of Facilities Identified in NEI and Modeled in Preliminary Risk
Assessment	29	n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 1 million)	40	Cr (VI),
formaldehyde

Number of Facilities with Maximum Individual Lifetime Cancer Risk:

	Greater than or equal to 100 in 1 million	0	n/a

	Greater than or equal to 10 in 1 million	2	formaldehyde, Cr (VI)

	Greater than or equal to 1 in 1 million	15	formaldehyde, Cr (VI), Ni,
As

Chronic Noncancer Risks

Maximum Respiratory Hazard Index	0.2	formaldehyde

Number of Facilities with Maximum Respiratory Hazard Index:

	Greater than 1	0	n/a

Acute Noncancer Screening Results

Maximum Acute Hazard Quotient	30

2	formaldehyde (REL)

formaldehyde (AEGL-1, ERPG-1)

Number of Facilities With Potential for Acute Effects	7	formaldehyde

Population Exposure

Number of People Living Within 50 Kilometers of Facilities Modeled
27,000,000	n/a

Number of People Exposed to Cancer Risk:

	Greater than or equal to 100 in 1 million	0	n/a

	Greater than or equal to 10 in 1 million	11,641	n/a

	Greater than or equal to 1 in 1 million	849,000	n/a

Number of People Exposed to Noncancer Respiratory Hazard Index:

	Greater than 1	0	n/a

Estimated Cancer Incidence (excess cancer cases per year)	0.0526	n/a

Contribution of HAP to Cancer Incidence

     Formaldehyde

     Cr (VI)

     Arsenic Compounds	52%

47%

1%	n/a

Table 4.2-2  Summary of Refined Acute Results for Wool Fiberglass
Manufacturing Facilities

Refined Results	MAXIMUM ACUTE HAZARD QUOTIENTS	ACUTE DOSE-RESPONSE
VALUES

	Based on REL	Based on AEGL-1/

ERPG-1	Based on AEGL-2/

ERPG-2	REL

(mg/m3)	AEGL-1

(1-hr) (mg/m3)	ERPG-1 (mg/m3)	AEGL-2

(1-hr)

(mg/m3)	ERPG-2 (mg/m3)

HAP	Max. 1-hr. Air Conc. (mg/m3)

Formaldehyde	1.77	30	2	0.1	0.055	1.1	1.1	17	17

Notes on Refined Process:

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

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

Notes on Acute Dose-Response Values:

 	REL – California EPA reference exposure level for no adverse
effects.  Most, but not all, RELs are for 1-hour exposures.

	AEGL – Acute exposure guideline levels represent emergency exposure
(1-hour) limits for the general public.

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

AEGL-2 is the exposure level above which it is predicted that the
general population, including susceptible individuals, could experience
irreversible or other serious, long-lasting adverse health effects of an
impaired ability to escape.

	EPRG – Emergency Removal Program guidelines represent emergency
exposure (1-hour) limits for the general public.

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

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

Auxiliary Risk Characterization

As indicated in Section 4.2, the maximum lifetime individual cancer
risks for the Wool Fiberglass Manufacturing source category could be as
high as 40 in a million based on actual emissions.  The major
contributor to this cancer risk is chromium (VI) that is emitted from
the furnace refractory brick as it breaks down over time.  The greatest
amount of chromium (VI) is emitted from the Certainteed Facility in
Kansas City, Kansas that uses a type of refractory brick that is almost
100% chromium.

Furnace refractory brick are essential to the structure and function of
the furnace, providing thermal insulation and corrosion protection.
Refractory bricks in the glass melting industry are typically composed
of Al2O3, Al203-SiO2, ZrO2, with or without Cr2O3 added, and dense
Cr2O3.[, ]  Refractory brick breaks down over time, and therefore, must
be replaced periodically (approximately every 7-14 years depending on
the type of brick).

Since there are currently no regulations preventing the use of high
chromium refractory brick or limiting emissions of chromium in the Wool
Fiberglass Manufacturing Industry, it is reasonable to assume that
another Wool Fiberglass Manufacturing facility might replace its current
furnace refractory brick with high chromium refractory brick sometime in
the future.   Therefore, we performed an auxiliary risk characterization
analysis to assess the maximum individual lifetime cancer risks of the
other 28 Wool Fiberglass facilities switching to high chromium brick.
For the auxiliary risk characterization analysis it was assumed that the
Cr (VI) emissions for each facility would be the same as that for the
Certainteed Facility in Kansas City, Kansas (420 lbs per year per
furnace of Cr(VI)).

The results of the auxiliary analysis (Table 4.2-3) show that 14
facilities would have maximum individual lifetime cancer risks greater
than 100 in a million, with the highest facility at 800 in a million.
Under this scenario, 460,000 people would be exposed to risks of greater
than 10 in a million and over 7 million people would be exposed to
cancer risks of greater than 1 in a million.

Table 4.2-3  Summary of Source Category Level Cancer Risks for the Wool
Fiberglass Manufacturing Auxiliary Analysis

Result

HAP “Drivers”

Number of Facilities Estimated to be in Source Category	29	n/a

Number of Facilities Identified in NEI and Modeled in Auxiliary Risk
Assessment	29	n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 1 million)	800	Cr (VI)

Number of Facilities with Maximum Individual Lifetime Cancer Risk:

	Greater than or equal to 100 in 1 million	14	Cr (VI), formaldehyde

	Greater than or equal to 10 in 1 million	28	Cr (VI), formaldehyde

	Greater than or equal to 1 in 1 million	29	Cr (VI), formaldehyde

Population Exposure

Number of People Living Within 50 Kilometers of Facilities Modeled
27,000,000	n/a

Number of People Exposed to Cancer Risk:

	Greater than or equal to 100 in 1 million	8,100	n/a

	Greater than or equal to 10 in 1 million	460,000	n/a

	Greater than or equal to 1 in 1 million	7,300,000	n/a

Estimated Cancer Incidence (excess cancer cases per year)	0.29	n/a

Contribution of HAP to Cancer Incidence

     Formaldehyde

     Cr (VI)     	6%

94%	n/a

General Discussion of Uncertainties and How They Have Been Addressed

Exposure Modeling Uncertainties

Although every effort has been made to identify all the relevant
facilities and emission points, as well as to develop accurate estimates
of the annual emission rates for all relevant HAP, the uncertainties in
our emission inventory likely dominate the uncertainties in our exposure
modeling estimates.  The chronic exposure modeling uncertainties are
considered relatively small in comparison, since we are using EPA’s
refined local dispersion model with site-specific parameters and
reasonably representative meteorology.  If anything, the population
exposure estimates are biased high by not accounting for short- or
long-term population mobility, and by neglecting processes like
deposition, plume depletion, and atmospheric degradation.  Additionally,
estimates of the maximum individual risk (MIR) contain uncertainty,
because they are derived at census block centroid locations rather than
actual residences.  This uncertainty is known to create potential
underestimates and overestimates of the actual MIR values for individual
facilities, but, overall, it is not thought to have a significant impact
on the estimated MIR for a source category.  Finally, we did not factor
in the possibility of a source closure occurring during the 70-year
chronic exposure period, leading to a potential upward bias in both the
MIR and population risk estimates; nor did we factor in the possibility
of population growth during the 70-year chronic exposure period, leading
to a potential downward bias in both the MIR and population risk
estimates.

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

We have purposely biased the acute screening results high, considering
that they depend upon the joint occurrence of independent factors, such
as hourly emissions rates, meteorology and human activity patterns.
Furthermore, in cases where multiple acute threshold values are
considered scientifically acceptable we have chosen the most
conservative of these assessments, erring on the side of overestimating
potential health risks from acute exposures.  In the cases where these
results indicated the potential for exceeding short-term health
thresholds, we have refined our assessment by developing a better
understanding of the geography of the facility relative to potential
exposure locations and the true variability of short-term emission
rates.

Uncertainties in the Dose-Response Relationships

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

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

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

Cancer assessment

The discussion of dose-response uncertainties in the estimation of
cancer risk below focuses on the uncertainties associated with the
specific approach currently used by the EPA to develop cancer potency
factors.  In general, these same uncertainties attend the development of
cancer potency factors by CalEPA, the source of peer-reviewed cancer
potency factors used where EPA-developed values are not yet available.
To place this discussion in context, we provide a quote from the EPA’s
Guidelines for Carcinogen Risk Assessment [] (herein referred to as
Cancer Guidelines).  “The primary goal of EPA actions is protection of
human health; accordingly, as an Agency policy, risk assessment
procedures, including default options that are used in the absence of
scientific data to the contrary, should be health protective.”  The
approach adopted in this document is consistent with this approach as
described in the Cancer Guidelines.

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

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

Such health risk assessments have associated uncertainties, some which
may be considered quantitatively, and others which generally are
expressed qualitatively.  Uncertainties may vary substantially among
cancer risk assessments associated with exposures to different
pollutants, since the assessments employ different databases with
different strengths and limitations and the procedures employed may
differ in how well they represent actual biological processes for the
assessed substance.  EPA’s Risk Characterization Handbook also
recommends that risk characterizations present estimates demonstrating
the impact on the assessment of alternative choices, data, models and
assumptions [].  Some of the major sources of uncertainty and
variability in deriving cancer risk values are described more fully
below.

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

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

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

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

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

EPA most frequently utilizes a linear low-dose extrapolation approach as
a baseline science-policy choice (a “default”) when available data
do not allow a compound-specific determination.  This approach is
designed to not underestimate risk in the face of uncertainty and
variability.  EPA believes that linear dose-response models, when
appropriately applied as part of EPA’s cancer risk assessment process,
provide an upper bound estimate of risk and generally provide a health
protective approach.  Note that another source of uncertainty is the
characterization of low-dose nonlinear, non-threshold relationships.
The National Academy of Sciences has encouraged the exploration of
sigmoidal type functions (e.g., log-probit models) in representing dose
response relationships due to the variability in response within human
populations.  Another National Research Council (NRC) report [] suggests
that models based on distributions of individual thresholds are likely
to lead to sigmoidal-shaped dose-response functions for a population.
This report notes sources of variability in the human population:
“One might expect these individual tolerances to vary extensively in
humans depending on genetics, coincident exposures, nutritional status,
and various other susceptibility factors...”   Thus, if a distribution
of thresholds approach is considered for a carcinogen risk assessment,
application would depend on ability of modeling to reflect the degree of
variability in response in human populations (as opposed to responses in
bioassays with genetically more uniform rodents).  Note also that low
dose linearity in risk can arise for reasons separate from population
variability: due to the nature of a mode of action and additivity of a
chemical’s effect on top of background chemical exposures and
biological processes.

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

(6) Cancer risk estimates do not generally make specific adjustments to
reflect the variability in response within the human population —
resulting in another source of uncertainty in assessments.  In the
diverse human population, some individuals are likely to be more
sensitive to the action of a carcinogen than the typical individual,
although compound-specific data to evaluate this variability are
generally not available.  There may also be important life stage
differences in the quantitative potency of carcinogens and, with the
exception of the recommendations in EPA’s Supplemental Cancer Guidance
for carcinogens with a mutagenic mode of action, risk assessments do not
generally quantitatively address life stage differences.  However, one
approach used commonly in EPA assessments that may help address
variability in response is to extrapolate human response from results
observed in the most sensitive species and sex tested, resulting
typically in the highest URE which can be supported by reliable data,
thus supporting estimates that are designed not to underestimate risk in
the face of uncertainty and variability.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure levels
that are intended to be health-protective. That is, EPA and other
organizations which develop noncancer reference values (e.g., the Agency
for Toxic Substances and Disease Registry – ATSDR) utilize an approach
that is intended not to underestimate risk in the face of uncertainty
and variability.  When there are gaps in the available information,
uncertainty factors (UFs) are applied to derive reference values that
are intended to be protective against appreciable risk of deleterious
effects.  Uncertainty factors are commonly default values e.g., factors
of 10 or 3, used in the absence of compound-specific data; where data
are available, uncertainty factors may also be developed using
compound-specific information.  When data are limited, more assumptions
are needed and more default factors are used.  Thus there may be a
greater tendency to overestimate risk—in the sense that further study
might support development of reference values that are higher (i.e.,
less potent) because fewer default assumptions are needed.  However, for
some pollutants it is possible that risks may be underestimated.

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

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

A series of downward adjustments using default UFs is then applied to
the POD to estimate the reference value  [].  While collectively termed
“UFs”, these factors account for a number of different quantitative
considerations when utilizing observed animal (usually rodent) or human
toxicity data in a risk assessment.  The UFs are intended to account
for: (1) variation in susceptibility among the members of the human
population (i.e., inter-individual variability); (2) uncertainty in
extrapolating from experimental animal data to humans (i.e.,
interspecies differences); (3) uncertainty in extrapolating from data
obtained in a study with less-than-lifetime exposure (i.e.,
extrapolating from subchronic to chronic exposure); (4) uncertainty in
extrapolating from a LOAEL in the absence of a NOAEL; and (5)
uncertainty when the database is incomplete or there are problems with
applicability of available studies.  When scientifically sound,
peer-reviewed assessment-specific data are not available, default
adjustment values are selected for the individual UFs.  For each type of
uncertainty (when relevant to the assessment), EPA typically applies an
UF value of 10 or 3 with the cumulative UF value leading to a downward
adjustment of 10-3000 fold from the selected POD.  An UF of 3 is used
when the data do not support the use of a 10-fold factor.  If an
extrapolation step or adjustment is not relevant to an assessment (e.g.,
if applying human toxicity data and an interspecies extrapolation is not
required) the associated UF is not used.  The major adjustment steps are
described more fully below.

	1) Heterogeneity among humans is a key source of variability as well as
uncertainty.  Uncertainty related to human variation is considered in
extrapolating doses from a subset or smaller-sized population, often of
one sex or of a narrow range of life stages (typical of occupational
epidemiologic studies), to a larger, more diverse population.  In the
absence of pollutant-specific data on human variation, a 10-fold UF is
used to account for uncertainty associated with human variation.  Human
variation may be larger or smaller; however, data to examine the
potential magnitude of human variability are often unavailable.  In some
situations, a smaller UF of 3 may be applied to reflect a known lack of
significant variability among humans.

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

Pharmacokinetic models are useful to examine species differences in
pharmacokinetic processing and associated uncertainties; however, such
dosimetric adjustments are not always possible.  Information may not be
available to quantitatively assess toxicokinetic or toxicodynamic
differences between animals and humans, and in many cases a 10-fold UF
(with separate factors of 3 for toxicokinetic and toxicodynamic
components) is used to account for expected species differences and
associated uncertainty in extrapolating from laboratory animals to
humans in the derivation of a reference value.  If information on one or
the other of these components is available and accounted for in the
cross-species extrapolation, a UF of 3 may be used for the remaining
component.

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

4) Toxicity data are typically limited as to the dose or exposure levels
that have been tested in individual studies; in an animal study, for
example, treatment groups may differ in exposure by up to an order of
magnitude.  The preferred approach to arrive at a POD is to use BMD
analysis; however, this approach requires adequate quantitative results
for a meaningful analysis, which is not always possible.  Use of a NOAEL
is the next preferred approach after BMD analysis in determining a POD
for deriving a health effect reference value.  However, many studies
lack a dose or exposure level at which an adverse effect is not observed
(i.e., a NOAEL is not identified).  When using data limited to a LOAEL,
a UF of 10 or 3-fold is often applied.

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

Acute noncancer assessment

Many of the UFs used to account for variability and uncertainty in the
development of acute reference values are quite similar to those
developed for chronic durations, but more often using individual UF
values that may be less than 10.  UFs are applied based on
chemical-specific or health effect-specific information (e.g., simple
irritation effects do not vary appreciably between human individuals,
hence a value of 3 is typically used), or based on the purpose for the
reference value (see the following paragraph).  The UFs applied in acute
reference value derivation include:  1) heterogeneity among humans; 2)
uncertainty in extrapolating from animals to humans; 3) uncertainty in
LOAEL to NOAEL adjustments; and 4) uncertainty in accounting for an
incomplete database on toxic effects of potential concern.  Additional
adjustments are often applied to account for uncertainty in
extrapolation from observations at one exposure duration (e.g., 4 hours)
to arrive at a POD for derivation of an acute reference value at another
exposure duration (e.g., 1 hour).

Not all acute reference values are developed for the same purpose and
care must be taken when interpreting the results of an acute assessment
of human health effects relative to the reference value or values being
exceeded.  Where relevant to the estimated exposures, the lack of
threshold values at different levels of severity should be factored into
the risk characterization as potential uncertainties.

References

 Assigning data with MACT codes allows EPA to determine reductions
attributable to the MACT program.  The NEI associates MACT codes
corresponding to MACT source categories with stationary major and area
source data.

  SierraClub v. EPA, 551 F. 3d 1019 (D.C. Cir. 2008), cert. denied, 130
S. Ct. 1735 (2010).

 SierraClub v. Stephen L. Johnson, Petition for Rulemaking, January 14,
2009

 SierraClub v. EPA, 479 F. 3d 875 (D.C. Cir. March 13, 2007)

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

 EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous
Waste Combustion Facilities;

http://www.epa.gov/epaoswer/hazwaste/combust/riskvol.htm#volume1

 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III -
Technical Support Document

for the Determination of Non-cancer Chronic Reference Exposure Levels.
Air Toxicology and Epidemiology Section, Office of Environmental Health
Hazard Assessment, California Environmental Protection Agency.  February
2000 (http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf)

 The URE is the upper-bound excess cancer risk estimated to result from
continuous lifetime exposure to an agent at a concentration of 1 μg/m3
in air.  URE’s are considered upper bound estimates meaning they
represent a plausible upper limit to the true value.

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

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

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

 The SAB peer review of RTR Risk Assessment Methodologies is available
at:
http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668
381/$File/EPA-SAB-10-007-unsigned.pdf

 U.S. EPA. (2009) Chapter 2.9 Chemical Specific Reference Values for
Formaldehyde in Graphical Arrays of Chemical-Specific Health Effect
Reference Values for Inhalation Exposures (Final Report). U.S.
Environmental Protection Agency, Washington, DC, EPA/600/R-09/061, and
available on-line at
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003

 National Institutes for Occupational Safety and Health (NIOSH).
Occupational Safety and Health Guideline for Formaldehyde;
http://www.cdc.gov/niosh/docs/81-123/pdfs/0293.pdf

 ACGIH (2001) Formaldehyde. In Documentation of the TLVs® and BEIs®
with Other Worldwide Occupational Exposure Values. ACGIH, 1300 Kemper
Meadow Drive, Cincinnati, OH 45240 (ISBN: 978-1-882417-74-2) and
available on-line at http://www.acgih.org.

 WHO (2000). Chapter 5.8 Formaldehyde, in Air Quality Guidelines for
Europe, second edition. World Health Organization Regional Publications,
European Series, No. 91. Copenhagen, Denmark. Available on-line at
HYPERLINK
"http://www.euro.who.int/__data/assets/pdf_file/0005/74732/E71922.pdf"
http://www.euro.who.int/__data/assets/pdf_file/0005/74732/E71922.pdf .

 ICF International.  TRIM-Based Multipathway Screening Scenario.
Prepared for U.S. Environmental Protection Agency, Research Triangle
Park, NC.  October 2008.

 We note that the MIR for this source category would be 0.7-in-1 million
if the CIIT URE for formaldehyde had been used in the assessment.  The
total cancer incidence would decrease by 64%.  There is an ongoing IRIS
reassessment for formaldehyde, and future RTR risk assessments will use
the cancer potency for formaldehyde that results from that reassessment.
 As a result, the current results may not match those of future
assessments.

 Persistent and bioaccumulative HAP are defined in the EPA’s Air
Toxics Risk Assessment Library, Volume 1, EPa-453K-04-001A, as
referenced in the ANPRM and provided on the EPA’s Technology Transfer
Network website for Fate, Exposure, and Risk Assessment at  HYPERLINK
"http://www.epa.gov/ttn/fera/risk_atra_vol1.html"
http://www.epa.gov/ttn/fera/risk_atra_vol1.html .

 The SAB peer review of RTR Risk Assessment Methodologies is available
at:
http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668
381/$File/EPA-SAB-10-007-unsigned.pdf

 U.S. EPA. (2009) Chapter 2.9 Chemical Specific Reference Values for
Formaldehyde in Graphical Arrays of Chemical-Specific Health Effect
Reference Values for Inhalation Exposures (Final Report). U.S.
Environmental Protection Agency, Washington, DC, EPA/600/R-09/061, and
available on-line at
http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003

 ACGIH (2001) Formaldehyde. In Documentation of the TLVs® and BEIs®
with Other Worldwide Occupational Exposure Values. ACGIH, 1300 Kemper
Meadow Drive, Cincinnati, OH 45240 (ISBN: 978-1-882417-74-2) and
available on-line at http://www.acgih.org.

 National Institutes for Occupational Safety and Health (NIOSH).
Occupational Safety and Health Guideline for Formaldehyde;
http://www.cdc.gov/niosh/docs/81-123/pdfs/0293.pdf

 WHO (2000). Chapter 5.8 Formaldehyde, in Air Quality Guidelines for
Europe, second edition. World Health Organization Regional Publications,
European Series, No. 91. Copenhagen, Denmark. Available on-line at
HYPERLINK
"http://www.euro.who.int/__data/assets/pdf_file/0005/74732/E71922.pdf"
http://www.euro.who.int/__data/assets/pdf_file/0005/74732/E71922.pdf .

 ICF International.  TRIM-Based Multipathway Screening Scenario.
Prepared for U.S. Environmental Protection Agency, Research Triangle
Park, NC.  October 2008.

 We note that the MIR for this source category would not change if the
CIIT URE for formaldehyde had been used in the assessment, although the
total cancer incidence would decrease by 52%.  The MIR for the source
category would remain at 40 due to Cr (VI).  There is an ongoing IRIS
reassessment for formaldehyde, and future RTR risk assessments will use
the cancer potency for formaldehyde that results from that reassessment.
 As a result, the current results may not match those of future
assessments.

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

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

 According to the NRC report Science and Judgment in Risk Assessment
(NRC, 1994) “[Default] options are generic approaches, based on
general scientific knowledge and policy judgment, that are applied to
various elements of the risk-assessment process when the correct
scientific model is unknown or uncertain.”  The 1983 NRC report Risk
Assessment in the Federal Government: Managing the Process defined
default option as “the option chosen on the basis of risk assessment
policy that appears to be the best choice in the absence of data to the
contrary” (NRC, 1983a, p. 63).  Therefore, default options are not
rules that bind the agency; rather, the agency may depart from them in
evaluating the risks posed by a specific substance when it believes this
to be appropriate.  In keeping with EPA’s goal of protecting public
health and the environment, default assumptions are used to ensure that
risk to chemicals is not underestimated (although defaults are not
intended to overtly overestimate risk). See EPA 2004 An Examination of
EPA Risk Assessment Principles and Practices, EPA/100/B-04/001 available
at: http://www.epa.gov/osa/pdfs/ratf-final.pdf.

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

  According to the NRC report Science and Judgment in Risk Assessment
(NRC, 1994) “[Default] options are generic approaches, based on
general scientific knowledge and policy judgment, that are applied to
various elements of the risk-assessment process when the correct
scientific model is unknown or uncertain.”  The 1983 NRC report Risk
Assessment in the Federal Government: Managing the Process defined
default option as “the option chosen on the basis of risk assessment
policy that appears to be the best choice in the absence of data to the
contrary” (NRC, 1983a, p. 63). Therefore, default options are not
rules that bind the agency; rather, the agency may depart from them in