Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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## 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
October 201 4Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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### Table of Contents

1 Introduction

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

2 Methods

................................ ................................ ................................ .............................. 6
2.1 Emissions and source data

................................ ................................ ........................... 6
2.2 Dispersion modeling for inhalation exposure assessment

................................ ........... 7
2.3 Estimating human inhalation exposure

................................ ................................ ..... 10
2.4 Acute Risk Screening and Refined Assessments

................................ ...................... 10
2.5 Multipathway human health and environmental risk screening

................................ 12
2.6 Dose

- Response Assessment

................................ ................................ ...................... 15
2.6.1 Sources of chronic dose

- response information

................................ .................. 15
2.6.2 Sources of acute dose

- response information

................................ ...................... 21
2.7 Risk Characterization

................................ ................................ ................................ 24
2.7.1 General

................................ ................................ ................................ ............... 24
2.7.2 Mixtures

................................ ................................ ................................ ............. 26
3 Risk Results for the Mineral Wool Production

................................ ............................ 27
3.1 Source Category Description and Results

................................ ................................ . 27
3.2 Risk Characterization

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

4 Risk Results for the Wool Fiberglass Manufacturing Source Category

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

4.1 Source Category Description and Results

................................ ................................ . 34
4.2 Risk Characterization

................................ ................................ ................................ 36
4.3 Auxiliary Risk Cha racterization

................................ ................................ ................ 43
5 General Discussion of Uncertainties and How They Have Been Addressed

................... 45
5.1 Exposure Modeling Uncertainties

................................ ................................ ............. 45
5.2 Uncertainties in the Dose

- Response Relationships

................................ ................... 46
5 References

................................ ................................ ................................ ........................ 55

Index of Tables

Table 2.2

- 1 AERMOD version 11103 model options for RTR modeling

.... Error! Bookmark
not defined.
Table 2.6

- 1 (a) Dose

- Response Values fo r Chronic Inhalation Exposure to Carcinogens

.... 20
Table 2.6

- 1 (b) Dose

- Response Values for Chronic Inhalation Exposure to Noncarcinogens

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

- 2 Dose

- Response Values for Acute Exposure

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

- 1 Summary of Emissions from the Mineral Wool Production Category and Availability of Dose

- Response Values

................................ ................................ .................... 28
Table 3.2

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

................................ ................................ ................................ ................................ 32
Table 4.2

- 1 Summary of Source Categor y Level Inhalation Risks for Wool Fiberglass Manufacturing

................................ ................................ ................................ .......................... 39
Table 4.2

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

................................ ................................ ................................ ................................ .................. 40
Table 4.2

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

................................ ................................ ........................... 44Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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 HEM 3 Modeling Appendix 3 Meteorological Data for HEM 3 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

Methodology for RTR Appendix 6 Detailed Risk Modeling Results Append ix 7 Acute Impacts Refined Analysis Appendix 8 Development of the Chronic Screening Level for Carbonyl Sulfide Appendix 9 Environmental Risk ScreenDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Index of Acronyms
AERMOD American Meteorological Society/EPA Regulatory Model

AEGL Acute exposure guide line 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 Integr ated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of action

NAC National Advisory Committee NAAQS National Ambient Air Quality Standard

NATA National Air Toxics Assessment

NEI National Emissi ons 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

- specifi c hazard index

URE Unit risk estimateDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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## 1 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.) [ 1 ]. EPA has largely completed the initial Maximum Achievable

Contro l 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 practice s,

processe s and control technologies.” In the second stage, EPA is required under section 112(f)(2) to assess the health and environmental risks that remain after implementation of the MACT standards. If additional risk reductions are necessary to prote ct 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 c ategory 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) o n 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” [ 2 ]. We received the final SAB report on this review in May of 2010 [ 3 ]. Where appropriate, we have responded to the key messages from this review in developing our current risk assessment s and we will be continuing our efforts to improve our 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” [ 4 ].

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 e nvironmental effects.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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## 2 Methods

2.1 Emissions and source data

Mineral Wool
The 2002 National Emissions In ventory (NEI) data served as the starting point for the mineral wool assessment. Using the process MACT code, 1 a subset of the NEI was developed that contained facility, process, and emissions data for each facility in the Mineral Wool
Production source c ategory. 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

prop osal 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 res ult, 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 Provision s vacature 2 , and a petition 3 raised to the court following the vacature of the Brick MACT 4 . 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 1 a , 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 a lso 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 t o, 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

so urces: 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

1 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.

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

3 SierraClub v. Stephen L. Johnson, Petition for Rulemaking

, January 14, 2009

4 SierraClub v. EPA

, 479 F. 3d 875 (D.C. Cir. March 13, 2007)Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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 co mbination 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

. T he 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. ”



### 2.2 Dispersion modeling for inhalation exposure ass essment

Both long

- and short

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

- AERMOD, or HEM3). The approach used in applying this modeling system is outlined below, and further details are provided in Appendix 2 to this document ( Technical Support Document for HEM3 Modeling ) . The HEM3 perfo rms 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 c omponents are discussed in
other subsections of Sections 2 and 3.

The dispersion model in the HEM3 system, AERMOD version 14134 (the version of AERMOD that was available at the time of the risk analysis), is a state

- of

- the

- science Gaussian plume dispersio n model that is preferred by EPA for modeling point, area, and volume sources of continuous air emissions from facility applications [ 5 ]. Further details on AERMOD can be found in the AERMOD Users Guide [ 6 ]. The model is used to develop annual average am bient 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
inven tory 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.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Table 2.2

- 1 AERMOD version 14134 model options for RTR modeling

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point, area r epresented as pseudo point source

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

- supplied receptors

Terrain characterization Actual from USGS 1

- degree DEM data

Building downwash Not Included

Plume deposi tion/depletion Not Included

Urban source option No

Meteorology 1 year representative NWS from nearest site ( 824 stations)

In HEM3, meteorological data are ordinarily selected from a list of over 800 National Weather Service (NWS) surface observation s tations 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. When considering off

- site meteorological data most site specific dis persion, EPA modeling guidelines suggest that modeling efforts employ up to five years of data to capture variability in weather patterns from year to year. However, because dispersion model runtimes using five years of meteorological data would be too lo ng for RTR source categories with many sources, we modeled only a single year, 2011. While the selection of a single year may result in under

prediction of long

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

prediction at others. F or each facility identified by its characteristic latitude and longitude coordinates, the closest meteorological station was used in the dispersion modeling. The average distance between a modeled facility and the applicable meteorological station was 22
miles. Appendix 3 to this document ( 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 AERMOD meteorological data process ing program. The document “Risk and Technology Review (RTR) Risk Assessment Methodologies: For Review by the EPA’s Science Advisory Board with Case Studies

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

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

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public release version of AERMET and incorporated the updated surface friction velocity adjustment in the o utput. It was EPA’s judgement that the pre

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

The HEM3 system estimates ambient concentrations at the geo graphic centroids of census blocks (using the 2010 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. When eva luating the risks associated with a particular source category we combined the impacts of all facilities within the same source category, and assessed chronic exposure and risk for all census blocks with at least one resident (i.e., locations where people may reasonably be assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient concentrations were calculated as the annual average
of all estimated short

- term (one

- hour) concentrations at each block centroid. Possible f uture 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 a mbient 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 represen t 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 shor t

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

The average hourly emissions rate used for chronic risk modeling is defined as the total
emissions for a year divided by the total number of operating hours in the year. If a source operated 8,760 hours per year this emissions rate would be appropriate for predicting potential acute impacts. While hourly emissions data for each source are not available, i n this assessment, we utilized source category specific engineering judgment to determine what the peak hourly emissions for any given process could be. For processes in which no “engineering judgment” information was available we utilized a generic facto r of ten times
actual annual emissions to estimate peak hourly emissions . T he generic factor of ten is discussed in Appendix 4 , ( Analysis of data on short

- term emission rates relative to long

- term
emission rates ) of this document.

Census block elevation s 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 am bient 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 neare st 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.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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In addition to using receptor elevation to determine plume height, AERMOD adjusts the plume’s flow i f 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 of
this document.



### 2.3 Estimating human inhalation exposure

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

- term or long

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

We did not address short

- term human activity, including indoor air concentrations, for two reasons. First, our experience with the NATA assessmen ts (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 percent for par ticulate HAP; it will also reduce risk estimates for gaseous HAP, but typically by much less. Second, basing exposure estimates on average ambient concentrations at census block centroids may underestimate or overestimate actual exposure concentrations at some residences.

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 assume d 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 where people are likely to live ; the popu lation risk distribution; and the cancer incidence. The assumption of not considering short or long

- term population mobility does not bias the
estimate of the theoretical MIR (assumes a person stays in one location for 70 years) nor does
it affect the est imate 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 co ncentration at any off

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



### 2.4 Acute Risk Screening and Refined Assessments

In establishing a scientifically defe nsible approach for the assessment of potential health risks due to acute exposures to HAP, we f ollowed the same general approach that has been used forDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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developing chronic health risk assessments under the residual risk program. That is, we developed a ti ered, 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 1 999.

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 t o the asse ssment. 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 th e facility being assessed poses no potential acute health risks (i.e., it “screens out”), or that it requires further , more refined assessment.
A more refined acute assessment could u s e industry

- or site

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

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

necessary.

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

- case assumptions in our screening approach:

 Peak 1

- hour emissions for the Wool Fiberglass Manufacturing category were assumed to equal 10 times the average 1

- hour emission rates. Peak 1

- hour emissio ns for the Mineral Wool Production category were assumed to equal 3 times the average 1

- hour
emission rates. (See discussion below.)

 For facilities with multiple emission points, peak 1

- hour emissions were assumed to occur at all emission points at the sa me 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

h our.

 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 as sumed to be located downwind at the point of maximum impact during this same worst

- case 1

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

meters.

 The maximum impact was compared to multiple short

- term health benchmarks for the

HAP being assessed to deter mine 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 to the extent possible

. In someDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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cases, this may entail determining the actual physical layout and boundaries of a facility to more accurately gauge where people might reasonably be exposed for an hour.

For the Mineral Wool Production source category we use d 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 Pro duction 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.



### 2.5 Multipathway human health and environmental risk screening

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

- accumulative in environment (PB

- HAP) 5 . The PB

- HAP compounds or compound classes are identified for the screening from the EPA’s Air Toxics Risk Assessment Library [ 7

]. With respect to PB

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

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

- specific emission rates of each of the emitted PB

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

- inhalation human health risks
under reasonable worst

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

– HAP using a hypothetical upper

- end screening exposure scena rio developed for use in conjunction with the EPA’s Total Risk Integrated Methodology. Fate, Transport, and Ecological Exposure (TRIM.FaTE[ 8 ]) model. We conducted a sensitivity analysis on the screening scenario to ensure that its key design parameters wou ld represent the upper end of the range of possible values, such that it would represent a conservative but not impossible scenario. The facility

- specific emissions rates of each of the PB

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

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

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

- Screen.

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

- Scree n, we derived
emission levels for each PB

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

- in

- 1 million or, for HAP that cause non

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

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

- pathway screen. In the Tier II screen, the location of each facility that exceeded the Tier I emission rate is used to refine the assumptions associated with the environment al scenario while maintaining the exposure scenario assumptions. We then adjust the risk

- based Tier I screening level for each PB

- HAP for each facility based on an understanding of how exposure concentrations estimated for the

5 Although the two

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

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

- letter chemical symbol for lead is not used in this document).Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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screening scenario change wit h meteorology and environmental assumptions. PB

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

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

- pathway risks using the TRIM.FaTE model and more site specific information. Appendix 5 of this
docum ent (Technical Support Document for TRIM

- Based Multipathway Tiered Screening Methodology for RTR) contains a complete discussion of the multipathway Tier I and II screening approach.

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

The NAAQS value, a public health policy judgment, incorporated the Agency’s most recent health evaluation of air effects of lead exposure for the purposes of setting a national ambient air quali ty standard. In setting this value, the Administrator promulgated a standard that was requisite to protect public health with an adequate margin of safety. We consider values below the level of the primary NAAQS to protect against multipathway risks beca use as mentioned above, the primary NAAQS is set as to protect public health with an adequate margin of safety. However, ambient air lead concentrations above the NAAQS are considered to pose the potential for increased risk to public health. We consider this NAAQS assessment to be a refined analysis given: 1) the numerous health studies, detailed risk and exposure analyses, and level of external peer and public review that went into the development of the primary NAAQS for lead, combined with: 2) the sit e

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

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

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

We further note that comparing ambient lead concentrations to the NAAQS for lead, considering the level, averaging time, form and indicator, also informs whether there is the potential for adverse environmental effects. This is because the secondary lead NA AQS, set to protect against adverse welfare effects (including adverse environmental effects), has the same averaging time, form, and level as the primary standard. Thus, ambient lead concentrations above the NAAQS for lead also indicate the potential for adverse
environmental effects.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Adverse E

nvironmental E

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

 Five persistent bioaccumulative HAP (PB

- HAP)

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

 Two acid gases

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

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

- documented potential to cause direct damage to terrestrial plants.

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

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

- cast environmental conditionals to determine whether the facility

- specific off

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

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

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

.

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

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

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

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

- tier screen that compares the average off

- site
ambient air concentration over the m odeling domain to ecological benchmarks for each of the acid gases. For purposes of ecological risk screening, EPA identifies a potential for adverse environmental effects to plant communities from exposure to acid gases when the average
concentration of the HAP around a facility exceeds the LOAEL ecological benchmark. In such cases, we further investigate factors such as the magnitude and characteristics of the areaDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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of exceedance (e.g., land use of exceedance area, size of exceedance area) to determine if
there is an adverse environmental effect.

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

- 3 AERMOD air dispersion model. To evaluate the potential for adverse environmental effects from lead, we compare the average modeled air emission concentrations of lead from each facility in the source category emission s to the level of the secondary National Ambient Air Quality Standard (NAAQS) for lead. The secondary lead NAAQS is a reasonable means of evaluating environmental risk because it is set to provide substantial protection against adverse welfare
effects whic h can include “effects on soils, water, crops, vegetation, man

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

- being.” 6

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

9

.



### 2.6 Dose

- Response Assessment

2.6.1 Sources of chronic dose

- response information

Dose

- response assessment (carcinogenic and non

- carcinogenic) fo r 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’ existin g recommendations for HAP [ 9 ], which

were also used for NATA [ 10 ]. This information has been obtained from various sources and prioritized according to (1) conceptual consistency with EPA risk assessment guidelines and (2) level of peer review received. T he 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 :

1) US Environmental Protection Age ncy (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 concentrat ion (RfC, for inhalation) or reference dose (RfD, for ingestion) to protect against effects other than cancer and/or a unit risk estimate (URE,

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

- made materials, animals, wildlife, weather, visibility and climate, damage to and deterioration of property, and h azards to transportation, as well as effects on economic values and on personal comfort and well

- being.”Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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for inhalation) or slope factor (SF, for ingestion) to estimate the probability of developing

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

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

- day ...” EPA disseminates dose

response assessment information in several forms, based on the level of review. The Integrated Risk Information System (IRIS) [ 11 ] 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 revi ew. 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. EPA’s science policy approach , under the current carcinogen guid elines, 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 th ose 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

.

2) US Agency for Toxic Substances and Disease R egistry (ATSDR). ATSDR, which is part of the US Department of Health and Human Services, develops and publishes Minimum Risk Levels (MRLs) [ 12 ] for inhalation and oral exposure to many toxic substances. As
stated on the ATSDR web site: “ Following discussi ons 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 le vels 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 adv erse health effects or for setting cleanup levels.

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

- response assessments for many substances, based both on carcinogenicity and health effects other than cancer. The process for developing these assessments is similar to that used by EPA to develop IRIS values and incorporates significant external scientific peer review. As cited in theDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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CalEPA Technical Support Document for developing their chronic assessments 7 : “The guidelines for developing chronic inhalation exposure levels incorporate many recommendations of the U.S. EPA [ 13 ] and NAS [ 14 ].” The non

- cancer information includes available inhalation health risk guidance value s expressed as chronic inhalation reference exposure levels (RELs) [ 15 ]. CalEPA defines the REL as “the concentration level at or below which no health effects are anticipated in the general human population.” CalEPA's quantitative dose

- response informati on on carcinogenicity by inhalation exposure is expressed in terms of the URE [ 16 ], 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:

1) In the case of HAP categories such as glycol ethers and cyanide compounds, the most
conservative dose

- response value of the chemical category i s used as a surrogate for other compounds in the group f or which dose

- response values are not available. This i s done in order to 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.

2) Where possible for emissions of unspecified mixtu res of HAP categories such as met al compounds and POM, we apply category

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

- response value for the category.

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

- response value for formaldehyde (5.5 x 10

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

- response value (1.3 x 10

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

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

. 8

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

- based dose

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

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

- Technical Support Document
for the Determination of Non

- cancer Chronic Referenc e 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 )

8 http://www.nap.edu/catalog.php?record_id=13142Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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4) In the case of nickel compounds, to provide a conservative estimate of potential cancer risks, we used the IRIS URE value for nickel subsulfide in this assessment. Based on past scientific and technical considerations, the determination of the percent of nic kel subsulfide was considered a major factor for estimating the extent and magnitude of the
risks of cancer due to nickel

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

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

Based on consistent views of major scientific bodies (i.e., National Toxicology Program (NTP) in their 12 th Report of the Carcinogens (ROC) 9 , Int ernational Agency for Research on Cancer (IARC) 10 , and other international agencies) 11 that consider all nickel compounds to be carcinogenic, we currently consider all nickel compounds to have the potential of being as carcinogenic to humans. The 12 th Repor t of the Carcinogens states that the “combined results of epidemiological studies, mechanistic studies, and carcinogenic studies in rodents support the concept that nickel compounds generate nickel ions in target cells at sites critical for carcinogenesis, thus allowing consideration and evaluation of these compounds as a single group.” Although the precise nickel compound (or compounds) responsible for the carcinogenic effects in humans is not always clear,
studies indicate that nickel sulfate and the com binations of nickel sulfides and oxides encountered in the nickel refining industries cause cancer in humans (these studies are summarized in a review by Grimsrud et al., 2010 12 ). The major scientific bodies mentioned above have also recognized that there are differences in toxicity and/or carcinogenic potential across the different nickel compounds.

In this inhalation risk assessment, to take a conservative approach, we considered all nickel compounds to have the same carcinogenic potential as nickel su bsulfide and used
the IRIS URE for nickel subsulfide to estimate risks due to all nickel emissions from the
source category. without a factor to reflect the assumption that 100 percent of the total mass of nickel may be as carcinogenic as pure nickel subsu lfide. In addition, given that
there are two additional URE 13 values derived for exposure to mixtures of nickel

9 National Toxicology Program (NTP), 2011. Report on carcinogens. 12 th ed. Research Triangle Park, NC: US Department of Health and Human Services (DHHS), Public Healt h Service. Available online at http://ntp.niehs.nih.gov/ntp/roc/twelfth/roc12.pdf

10 International Agency for Research on Cancer (IARC), 1990. IARC monographs on the evaluation of
carcino genic risks to humans. Chromium, nickel, and welding. Vol. 49. Lyons, France: International Agency for Research on Cancer, World Health Organization Vol. 49:256.

11 World Health Organization (WHO, 1991) and the Europea n Union’s Scientific Committee o n He alth and Environmental Risks (SCHER, 2006)

. 12 Grimsrud TK and Andersen A. Evidence of carcinogenicity in humans of water

- soluble nickel salts. J Occup Med Toxicol 2010, 5:1

- 7. Available online at http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2868037/?tool=pubmed

13 Two UREs (other than the current IRIS values) have been derived for nickel compounds as a group: one developed by the California Department of Health ServicesDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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compounds, as a group, that are 2

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

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

same s im plifying a ssumptions to assessments that are used in NATA [ 17 ]. 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.

6) A chronic screening level of 163 ug/m 3 was developed by EPA for carbonyl sulfide (COS) from a No Observed Adverse Effects Level (NOAEL) of 200 ppm based on brain lesions and neurophysiological al terations in r odents. 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: 10 times for extrapolation for interspecies differences, 10 times for consideration of intraspecies variability, 10 times for extrapolation from subchronic to chronic duration, and 3 times for
database insufficiencies. See section 5 of this document for a detailed discussion of exposure modeling un certainties.

The emissions inventory for the Wool Fiberglass Manufacturing and for the Mineral Wool
Production source categor ies includes emissions of 14 HAP with available chronic quantitative inhalation dose

- response values. These HAP, their dose

- res ponse values, and the
source of the values are listed in Tables 2.6

- 1 (a) and ( b ).

( http://www.arb.ca.gov/toxics/id/summary/nickel_tech_b.pdf ) and the other by the Texas Commission on Environmental Quality ( http://www.epa.gov/ttn/atw/nata1999/99pdfs/healtheffectsinfo.pdf ).Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Table 2.6

- 1 (a) Dose

- Response Values for Chronic Inhalation Exposure to Carcinogens

URE (unit risk estimate for cancer) 14 = cancer risk per μg/m 3 of average lifetime exposure. Sources: IRIS = EPA Integrated Risk Information System, CAL = California
EPA Office of Environmental Health Hazard Assessment.

Pollutant CAS Number 15 URE 16 (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 Formaldehyde a 50000 1.3E

- 05 IRIS

a

- The EPA has used the CIIT URE value, 5.5X10

- 9 per u g/m 3 , to characterize forma ldehyde cancer risk in
some instances.

14 The URE is the upper

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

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

- digi t identifier corresponding to the group’s position on the CAA list of HAPs.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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 contin uous 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, EPA OAQPS = EPA Office of Air Quality Planning
and Standards.

Pollutant CAS Number 6 RfC (mg/m3) Source 16

Arsenic compounds 7440382 1.5E

- 05 CAL Beryllium c ompounds 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 com pounds 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 0.00048 EPA OAQPS 17

Phenol 10952 0.2 CAL Selenium compounds 7782492 0.02 CAL

2.6.2 Sources of acu te 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 [ 18 ]

. 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 Emerg ency 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 expr essed therein. Comparisons among different available

16 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.

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

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

- 04 per ug/m 3

.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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inhalation health effect reference values (both acute and chronic) for selected HAPs can be
found in a n EPA document [ 19 ].

California Acute Reference Exposure Levels (RELs ). The California Environmenta l 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 ( ht tp://www.oehha.ca.gov/air/pdf/acuterel.pdf ) is defined by CalEPA as

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

. RELs are based on the most sensitive, relevant, adverse
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 uncertain ties, 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

Concentr ations (RfCs) for chronic exposures (and, in fact, California also has developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs ). AEGLs are developed by the National Advisory
Committee (NAC) on Acute Exposure Guideline Levels (NAC/AEGL) f or Hazard ous Substances , and then reviewed and published by the National Research Council A s described

in the Committee’s “Standing Operating Procedures (SOP) ” ( http://www.epa.gov/opptintr/aegl/pubs/sop.pd f ), 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 preparednes s 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 v alues 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 value s 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 carrie rs.”

The NAC/AEGL defines AEGL

- 1 and AEGL

- 2 as:

“ AEGL

- 1 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above which it is predicted that the general population, including susceptible individuals, could experience notable discom fort, irritation, or certain asymptomatic nonsensory effects. However, the effects are not disabling and are transient and reversible upon cessation of

exposure. ”Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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“ AEGL

- 2 is the airborne concentration (expressed as ppm or mg/m 3 ) of a substance above
whic h 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 expos ure 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 i ncrease 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 eld erly, persons with asthma, and those with other illnesses, it is recognized that individuals, subject to unique or idiosyncratic responses, could experience the effects described at concentration s below the corresponding AEGL.”

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene Association (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [ 21 ] for acute exposures at three different levels of severity. These guidelines represent
concentrations for once in a li fetime 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 value s ( http://www.aiha.org/insideaiha/GuidelineDevelopment/ERPG/Pages/default.aspx ) are described in their supporting documentation as follows: “ERPGs are air concentra tion guidelines for single exposures to agents and are intended for use as tools to assess the adequacy of accident prevention and emergency response plans, including transportation emergency planning, community emergency response plans and incident preven tion and mitigation.”

ERPG

- 1 and ERPG

- 2 values are defined by AIHA as follows:

“ ERPG

- 1 is the maximum airborne concentration below which it is believed that nearly all individuals could be exposed for up to 1 hour without experiencing other than mild

tr ansient 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 de veloping 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 in cludes emissions of 9 HAP with relevant and availableDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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 Ex posure

Pollutant CAS

Number AEGL

- 1

(1

- hr) (mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

1 (mg/m 3 ) ERPG

2 (mg/m 3 ) REL Arsenic compounds 7440382 0.0002 Beryllium com p ounds 7440417 0.025 Carbonyl sulfide 463581 140 Formaldehyde 50000 1.1 17 1. 2 1 2 0.05 5 Hydrochloric acid 7647010 2.7 33 4.5 30 2.1 Mercury (elemental) 7439976 1.7 2 0.0006

Methanol 67561 690 2700 260 1300 28

Nickel 7440020 0.00 02

Phenol 108952 58 89 3 8 190 5.8



### 2.7 Risk Characterization

2.7.1 General
The final product of the risk assess ment 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
charac terization 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 [ 22 ] specifies that a risk characterization “be prepared in a manner that is clear, transparent, reasonable, and consistent with other risk characterizations of similar scope prepared across progra ms in the Agency.” These principles of transparency and consistency have been reinforced by the Agency’s Risk Characterization

Handbook [ 23 ], in 2002 by the Agency’s information quality guidelines [ 24 ], and in the OMB/OSTP September 2007 Memorandum on Updat ed Principles for Risk Analysis 18 , and are incorporated in these assessments.

Estimates of health risk are presented in the context of uncertainties and limitations in the data and methodology. Through our tiered, iterative analytical approach, we have at tempted to reduce both uncertainty and bias to the greatest degree possible in these assessments, within

18 Memorandum f

or t he Heads o f Executive Departments a nd Agencies

- Updated Principles for Risk Analysis ( September 19, 2007 ), From Susan E. Dudley, Administrator, Office of Information and Regulatory Affairs,
Office of Ma nagement and Budget; and Sharon L. Hays, Associate Director and Deputy Director for Science, Office of Science and Technology Policy ( http://www.whitehouse.gov/ sites/default/ omb/ assets/omb/ memoranda/fy2007/m07

- 24.pdf )Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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 t he assessment that has a potency estimate available,
individu al and population cancer risks we re calculated by multiplying the corresponding lifetime average exposure estimate by the appropriate URE. This calculated cancer risk is defined as the upper

- bou nd probability of developing cancer over a 70

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

- Life Exposure to Carcinogens [ 26 ]

. This guidance has the effect of adjusting the URE by factors of 10 (for children aged 0

- 1), 3 (for children aged 2

- 15), or 1.6 (for 70 years of exposure beginning at birth), as needed in risk assessments . In this case, this has the effect of increasing the estimated life time risks for these pollutants by a factor of 1. 6. In addition, although only a
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 P OM have the same mutagenic mechanism
of action as does benzo[a]pyrene. For this reason

, EPA implem entation policy [ 27 ] recommends applyi ng the Supplemental Guidance to all carcinogenic PAHs for which risk estimates are based on relative potency. According ly, we applied the Supplemental Guidance to all unspeciated POM mixtures.

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

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

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

Unlike linear dose

- response assessments for cancer, noncancer health hazard s generally are not expressed as a probability of an adverse occurrence. Instead, “risk” for noncancer effects is expressed by comparing an exposure to a reference level as a ratio. The “hazard quotient” (HQ) is the estimated exposure divided by a refere nce level (e.g., the RfC). For a given HAP, exposures at or below the reference level (HQ≤1) are not likely to cause adverse healthDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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

r isk 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 ch ronic 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 sign ificant acute risks.

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

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

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

In a ssessing 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, th e 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) t hat 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. A ll TOSHI calculations pre sented 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 onl y 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 theDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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potential for adverse health outcomes associated with pollutant exposure, and needs t o 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
ba sis, not using the TOSHI approach.



### 3 Risk Results for the Mineral Wool Production

3.1 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 an d 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 mat erial 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 chamb er, in which air or a binder is drawn over the fibers, forming them into a screen; a curing oven that bonds th e fibers (for bonded products); and a cooling oven.

In 1997 when the mineral wool MACT rule was proposed, EPA estimated that there were 16 majo r 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, t hese 7 facilities emitted a reported total of

400 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 the se data, the HAP emitted in largest quantities in total from these facilities are carbonyl sulfide, formaldehyde, phenol, hydrochloric acid, methanol, and hydrogen fluoride ; emissions of these 6 pollutants account for 99

. 9 percent of the total HAP emissions by mas s from the data set. Carbonyl sulfide , hydro gen chlori de

, and hydrogen fluoride were reported
as an emission for all o f the facilities. Formaldehyde , methanol 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 , methanol and p henol are emitted only from bonded mineral wool fiber manufacturing, which includes emissions from the application of t he binder, curing, and cooling. Raw material feed rate s in mineral wool processes are essentially constant with minimal fluctuation (approximately ± 10 percent). Consequently, emissionsDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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also have minimal fluctuation [ 30 ]. 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.

The following environmental HAP are emitted from the Mineral Wool Production source category and are included in the environmental risk screen: lead, mercury (mercuric chloride and methyl mercury), cadmium, hydrogen chloride and hydrogen fluoride.

Table 3.1

- 1 Summary of Emissions from the Minera l Wool Production Category and Availability of

Dose

- Response Value s

HAP Emissions (tpy) Number

of
Facilities Reporting

HAP (7
facilities
in data set) Prioritized Inhalation Dose

- Response Value Identified by OAQPS a

PB

HAP? Unit Risk
Estimate for
Cancer? Reference

Concentration
for Noncancer? Health

Benchmark
Values for Acute
Noncancer?

Carbonyl Sulfide 2 6 4 .5 7 

Formaldehyde 4 7.9 3   

Phenol 3 6.2 3  

Hydrochloric acid 18.5 7  

Methanol 18 .2 3  

Hydrogen Fluoride 14.6 7

Selenium 0.28 7 

Manganese 0.14 7 

Chromium III 0.04 7

Lead 0.03 7  

Arsenic 0.03 7   

Nickel 0.02 7  

Antimony 0.002 7

Cadmium 0.002 7   

Cobalt 0.0013 7 

Elemental Gaseous Mercury 0.0005 6   

Chromium (VI) 0.0003 7  

Beryllium 0.0002 7   

Gaseous Divalent Mercu ry 0.0001 6 

Particulate Divalent Mercury 0.0001 6 

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 va lues for the HAP emitted from mineral wool production
facil ities. Specific dose

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

air toxics at h ttp://www.epa.gov/ttn/atw/toxsource/summary.html

.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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### 3.2 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 maxim um 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 fo r 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

. In addition, we present the results for a screening

- level evaluation of the potential adverse environmental risks associated with actual emissions.

Actual Emissions
Table s 3 .2

- 1 and 3.2

- 2 summarize the chronic and acute inhalation risk results for this source
category based on actu al emissions

. The results for the Mineral Wool Production source category indicate that maximum lifetime individual cancer risks could be as high as 10 in a million. The major contributor to th is risk is formaldehyde

. A pproximately 1 1

, 6 0 0 people

were es timated to have cancer risks above 1 in a million as a result of the emissions from 2
facilit ies . The maximum chronic non

- cancer TOSHI value for the source category could be
up to 0. 1 with emissions of formaldehyde dominating t hose impacts, indicating no sig nificant potential for chronic noncancer impacts.

Worst

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

- 1 that has an acute benchmark, and the high est acute HQ ( REL of 20 for formaldehyde ) is shown in Tabl e 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 M ineral W ool 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 unrefined acute HQ
value was 34. During refinement values located on site or in areas where the public would not be found for at least an hour were removed, yielding a refined acute HQ of 20. Table 3

. 2

- 2 provides more information on the acute risk estimates for formaldehyde, the onl y 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 Advi sory Board’s peer review of EPA’s RTR risk assessment methodologies 19 , 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 gap s 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

19 The SAB peer review of RTR Risk As sessment Methodologies is available at: http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/EPA

- SAB

- 10

- 007

- unsigned.pdfDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

Manufacturing Source Categories

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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 a s a second comparative measure. Historically, c omparisons 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 bec ause o ccupat ional 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 20

. As a result, f or mos t 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
exceeded 13

. Such is not the case when comparing the available acute inhala tion health effect reference values for formaldehyde 13

.

The worst

- case maximum estimated 1

- hour exposure to formaldehyde outside the facility
fence line for the mineral wool production source category is 1. 06 mg/m 3 . This estimated

worst

- case exposure exc eeds the 1

- hour REL by a factor of 20 (HQ REL = 20 ) and exceeds the

1

- hour AEGL

- 1 by a factor of 1 (HQ AEGL

- 1 = 1 ). T his exposure estimate exceed s the workplace ceiling level guideline for the formaldehyde value developed by National Institutes for Occupatio nal Safety and Health (NIOSH) 21 “for any 15 minute period in a work day” by a
factor of 9 (NIOSH REL

- ceiling value of 0.12 mg/m 3 ; HQ NIOSH = 9 ). T he estimate exceeds the value developed by the American Conference of Governmental Industrial Hygienists (ACGIH ) 22 as “not to be exceeded at any time” by a factor of 3 (ACGIH TLV

- ceiling value of 0.37 mg/m 3 ; HQ ACGIH = 3 ). Additionally, the estimated maximum acute exposure exceeds the Air Quality Guideline value that was developed by the World Health Organization 23 f or 30

- minute exposures by a factor of 1 1 (0.1 mg/m 3 ; HQ WHO = 1 1 )

.

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 ( 0.1 f or formaldehyde ) is shown in Table 3.2

- 1. There were no HIs greater than 1 for this
source category.

20 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

21 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

22 ACGIH (2001) Formaldehyde. In Documentation of the TLVs® and BEIs® with Other Worldw ide 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.

23 WHO (2000). Chapter 5.8 Formaldehyde, in Air Quality Guidelines for Europe, second edition. W orld Health Organization Regional Publications, European Series, No. 91. Copenhagen, Denmark. Available on

- line at http://www.euro.who.int/__data/assets/pdf_file/0005/74732/E 71922.pdf

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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. 24 The PB HAP s emitted by facilities in this category are lead, cadmium, and mercury . All lead, cadmium, and

mercury emissions were below the threshold level s , indicating no potential for significant
multi

- pathway risks from these facilities

.

We conducted a screening

- level evaluation of the potential adverse environmental risks associated with emissions of the following environmental HAP from the Mineral Wool
Production source category: lead, mercury, cadmium, hydrogen chloride and hydrogen fluoride. The results of the environmental screening analysis are summarized in Table 3.2

- 3.

In the Tier 1 screening analysis for PB

- HAP (other than lead, which was ev aluated differently
as noted below ) the individual modeled Tier 1 concentrations for mercury and cadmium did

not exceed any ecological benchmark for any facility in the source category. For lead, we did not estimate any exceedances of the secondary lead N AAQS.

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

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

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

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

MACT

- Allowable Emissions Analysis of potential differences between a ctual 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 3 0 in a million, and that the maximum chronic noncancer TOSHI value could be as high as 0. 4 at the MACT

- allowable emissions level.

Post

- RTR Emissions

P ost

- RT R emissions of formaldehyde are the same as actual emiss i ons. Therefore, the post

RTR risks will be the same as those described above for actual emissions.

24 ICF International. TRIM

- Based Multipathway Screening Scenario . Prepared for U.S. Environmental Protection Agency, Research Triangle Park, NC. October 2008.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Table 3.2

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

Based on Actual Emissions

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 Ind ividual Lifetime Cancer Risk (in 1 million) 1 0 25 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 1 formaldehyde

Greater than or e qual to 1 in 1 million 2 formaldehyde

Chronic Noncancer Risks

Maximum Hazard Index 0.1 formaldehyde

Num ber of Facilities with Maximum Respiratory Hazard Index:

Greater than 1 0 n/a

Refined Acute Noncancer Screening Results

Maximum Acute Hazard Quo tient [using scali ng factor of 3 ] 2 0

1 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 4,100,0 00 n/a Number of People Exposed to Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 1 n/a Greater than or equal to 1 in 1 million 11,600 n/a

Number of People Exposed to Noncancer Respiratory Haza rd Index:

Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.001 18 n/a Contribution of HAP to Cancer Incidence: Formaldehyde Arsenic compounds Cr (VI) Arsenic Compounds 82 %
16 %
1%
1% n/a

25 We note that the MIR for this source category would be 0. 001

- in

- 1 million if the CIIT URE for formaldehyde
had been used in the assessment. 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.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Table 3.2

- 2 Summary of Ref ined Acute Results for Mineral Wool Production Facilities
Based on Actual Emissions

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/m 3 ) AEGL

- 1 (1

-

hr) (mg /m 3 ) ERPG

- 1

(mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

2 (mg/m 3 )
HAP Max. 1

- hr.

Air Conc. (mg/m 3 )

Formaldehyde 1. 06 2 0 1 0.0 6 /0.09 0.055 1.1 1. 2 17 1 2

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

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

- response values which are not in the table do not carry any potential for posing acut e 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 exposu re 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 t hat are notable disc omfort, 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 c ould 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 develop ing irreversible or other serious health effects or symptoms which could impair an individual’s ability to take protective action.

Table 3.2

- 3 Summary of Environmental Risk Screen Results for the Mineral Wool

Production Source C ategory Based on Actual E missions

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

Tier 1 Screen Tier 2 Screen 1 NOAEL LOAEL NOAEL LOAEL NOAEL LOAEL

PB

HAP Pb None None NA NA 0% 0%

Hg NA None NA NA 0% 0%

Cd None None NA NA 0% 0%

Acid
Gases HF 3 NA None

- - NA 0%

HCL 4 NA None

- - NA 0%

NA

– Not Applicable.

1

- Tier 2 screen is performed for PB

- HAP when there are exceedances of the Tier 1 screen. The acid gas screen
is a one tier screen.

2

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

- HAP the percent area is based on the Tier 2 results, if a Tier 2 analysis is performed. Otherwise, the percent area is based
on the Tier 1 results.

3

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

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

4

– For HCL, we evaluated one benchmark at t he LOAEL level.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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### 4 Risk Results for the Wool Fiberglass Manufacturing Source Category

4.1 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. Typi cally, 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, an d 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, 199 9 (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 m anufacturing 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 State s by 6 companies operating 30 plants in 16 States. Ten of these facilities are major sources and 19

are area 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 me tals including hexavalent chromium.

The emissions for the Wool Fiberglass Manufacturing source category data set (of 29
facilities , 1 facility did not have emissions data ) are summarized in Table 4.1

- 1. The total
HAP emissions for the sou rce category a re 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 hydro gen chlori de . Emissions of these 5 HAP make up 99.9 percent o f 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.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Persistent and bioaccumulative HAP (PB HAP) reported as emissions from these facilities
include lead, cadmium, and mercury compounds

. 26

The following environmental HAP are emitted from the Wool Fiberglass Manufacturing source category and are included in the env ironmental risk screen: lead, mercury (mercuric chloride and methyl mercury), cadmium, hydrogen chloride and hydrogen fluoride.

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 OAQPS a

PB

HAP? Unit Risk
Estimate for
Cancer? Reference

Concentration
for Noncancer? Health

Benchmark
Values f or Acute
Noncancer?

Methanol 820 26 Y Y
Formaldehyde 618 26 Y Y Y

Phenol 403 26 Y Y
Hydrogen Fluoride 20 29 Hydrochloric acid 12 29 Y Y
Chromium (VI) 0.3 6 29 Y Y

Selenium 0.15 29 Y

Lead 0.14 29 Y Y
Manganese 0.13 29 Y

Nickel 0.12 29 Y Y

Chromium III 0.05 2 8

Arsenic 0.0 4 29 Y Y Y
Elemental Gaseous Mercury 0.04 29 Y Y Y
Antimony 0.04 29

Cadmium 0.02 29 Y Y Y

Cobalt 0.02 29 Y
Berylium 0.0 1 29 Y Y Y
Gaseous Divalent Mercury 0.005 29 Y

Particulate Diva lent 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 Tra nsfer Network website for the 2002 National

- Scale Air Toxics Assessment at http://www.epa.gov/nata2002/methods.html#pom ( Approach to Modeling POM ).

b Specific dose

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

.

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

EPa

- 453K

- 04

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

.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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### 4.2 Risk Characterization

This section presents the resul ts of the risk assessment for the W ool F iberglass Manufacturing
source category for three emissions scenarios

– actual, MACT

- Allowable , and post

- RTR
control. The basic chronic inhalation risk estimates presented here are the maximum
individual lifetime ca ncer 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

- inhalatio n 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. In addition, we present the results for a screening

- level evaluation of the potential adverse environmental risks associated with actual emissions.

Actual Emissions
Table s 4.2

- 1 and 4.2

- 2 summarize the chronic and acute inhalation risk results for this source
category based on actual emissions

. The results for the Wool Fiberglass Manufacturing source category indicate that maximum lifetime individual cancer risks could be as high as 2 0 in a million. The major contributor to the risk is formaldehyde . Approximately 650 ,000 people
were estimated to have canc er 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 potenti al for chronic noncancer impacts.

Worst

- case a cute 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 s creening 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 inform ation 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, an d in response to a key recommendation from the Science Advisory Board’s peer review of EPA’s RTR risk assessment methodologies 27 , 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 anticipat ed 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

27 The SAB peer review of RTR Risk Assessment Methodologies is available at: http://yosemite .epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/EPA

- SAB

- 10

- 007

- unsigned.pdfDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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, c omparisons of
the estimated maximum off

- site one

- hour exposure levels have not been typically made to occupational levels for the purpose of characte rizing public health risks in RTR assessments

. This is because o ccupat ional 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 28 . As a result, f or 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
exceeded 21 . Suc h is not the case when comparing the available acute inhalation health effect reference values for formaldehyde 21

.

The worst

- case maximum estimated 1

- hour exposure to formaldehyde outside the facility
fence line for the wool fiberglass manufacturing sourc e category is 1. 5 mg/m 3 . This estimated

worst

- case exposure exceeds the 1

- hour REL by a factor of 30 (HQ REL = 30) and the 1

- hour

AEGL

- 1 by 1 (HQ AEGL

- 1 = 1 ). T his exposure estimate also exceeds multiple workplace ceiling level guidelines for formaldehyde

, including the value developed by the American Conference of Governmental Industrial Hygienists (ACGIH) 29 as “not to be exceeded at any time” (ACGIH TLV

- ceiling value of 0.37 mg/m 3 ; HQ ACGIH = 4 ), and the value developed by the National Institutes for Occupa tional Safety and Health (NIOSH) 30 “for any 15 minute period in a work day” (NIOSH REL

- ceiling value of 0.12 mg/m 3 ; HQ NIOSH = 1 3 ). Additionally, the estimated maximum acute exposure exceeds the Air Quality Guideline value that was developed by the World He alth Organization 31 for 30

- minute exposures (0.1 mg/m 3 ; HQ WHO = 1 5 )

.

Chronic noncancer target organ specific hazard indices (HIs) were calculate d for every HAP
shown in Table 4.1

- 1 that has a chronic benchmark, and the highest t arget organ specific HI (0. 1 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. Repo rted emissions of PB HAP were compared to emission thresholds established by EPA for the purposes of the RTR risk

28 U.S. EPA. (2009) Chapter 2.9 Chemical Specific Reference Values for Formaldehyde in Graphical Arrays of
Chemical

- Specific Health Effect Reference Values for In halation 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

29 ACGIH (2001) Formaldehyde. In Documentation of the TLVs® and BE Is® 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.

30 National Institutes for Occupational Safety and Health (NIOSH). Occupat ional Safety and Health Guideline for Formaldehyde; http://www.cdc.gov/niosh/docs/81

- 123/pdfs/0293.pdf

31 WHO (2000). Chapter 5.8 Formaldehyde, in Air Quality Guidelines for Europe, second edition. World Health Organization Regional Publications, Europea n Series, No. 91. Copenhagen, Denmark. Available on

- line at http://www.euro.who.int/__data/assets/pdf_file/0005/74732/E71922.pdf

.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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assessments. 32 The PB HAP emitted by facilities in this category are lead, cadmium, and

mercury

. All lead, cadmium, and mercury emissions wer e below the threshold levels

, indicating no potential for significant multi

- pathway risks from these facilities

.

We conducted a screening

- level evaluation of the potential adverse environmental risks associated with emissions of the following environmenta l HAP from the Wool Fiberglass Manufacturing source category: lead, mercury, cadmium, hydrogen chloride and hydrogen fluoride. The results of the environmental screening analysis are summarized in Table 4.2

- 3.

In the Tier 1 screening analysis for PB

- H AP (other than lead, which was evaluated differently
as noted below ) the individual modeled Tier 1 concentrations for mercury and cadmium did

not exceed any ecological benchmark for any facility in the source category. For lead, we did not estimate any ex ceedances of the secondary lead NAAQS.

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

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

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

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

MACT

- Allowable Emissions Analysis o f 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 formaldeh yde 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 asses sment 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.

32 ICF International. TRIM

- Based Multipath way Screening Scenario . Prepared for U.S. Environmental Protection Agency, Research Triangle Park, NC. October 2008.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Table 4.2

- 1 Summary of Source Cat egory Le vel Inhalation Risks for Wool Fiberglass

Manufacturing Based on Actual Emissions

Result HAP “Drivers”

Number of Facilities Estimated to be i n Source Category 30 n/a

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

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 20 33 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 millio n 3 formaldehyde, Cr (VI)

Greater than or equal to 1 in 1 million 12 formaldehyde, Cr (VI), Ni, As

Chronic Noncancer Risks

Maximum Respiratory Hazard Index 0. 1 formaldehyde

Num ber of Facilities with Maximum Respiratory Hazard Index:

Greater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 30

1 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 Ki lometers
of Facilities Modeled 30, 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 6,900 n/a Greater than or equal to 1 in 1 million 1,200,000 n/a

Number o f People Exposed to Noncancer Respiratory Hazard Index:

Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.0 7 26 n/a

Contribution of HAP to Cancer Incidence Formaldehyde Cr (VI) Arsenic Compounds 75 %
24 %
1% n/a

33 We note that the MIR for this source category would change to 10 in a million (driven by Cr(VI)) if the CIIT URE for formaldehyde had b een used in the assessment, and 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.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Table 4.2

- 2 Summary of Refined Acute Results for Wool Fiberglass Manufacturing
Facilities Based on Actual Emissions

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/m 3 ) AEGL

- 1

(1

- hr) (mg/m 3 ) ERPG

- 1

(mg/m 3 ) AEGL

- 2

(1

- hr) (mg/m 3 ) ERPG

- 2

(mg/m 3 )

HAP Max. 1

- hr.

Air Conc. (mg/m 3 )

Formaldehyde 1.5 30 1 0.1 0.055 1.1 1. 2 17 1 2

Notes on Refined Process: 1) 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. 2) HAP with available acute dose

- response values which are not in the table do not car ry 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 experien ce effects t hat are notable discomfort, but which are transient and reversible upon cessation of exposure.

AEGL

- 2 is the exposure level above which it is predicted that the general population, including susceptible individuals, could experience irreversibl e 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 believ ed 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 abilit y to take protective action.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Table 4 .2

- 3 Summary of Environmental Risk Screen Results for the Wool Fiberglass

Manufact uring Source C ategory Based on Actual Emissions

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

Tier 1 Screen Tier 2 Screen 1 NOAEL LOAEL NOAEL LOAEL NOAEL LOAEL

PB

HAP Pb None None NA NA 0% 0%

Hg NA None NA NA 0% 0%

Cd None None NA NA 0% 0%

Acid

Gases HF 3 NA None

- - NA 0%

HCL 4 NA None

- - NA 0%

NA

– Not Applicable.

1

- Tier 2 screen is performed for PB

- HAP when there are exceedances of the Tier 1 screen. The acid gas screen
is a one tier screen.

2

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

- HAP the percent area is based on the Tier 2 results, if a Tier 2 analysis is performed. Otherwise, the percent area is based
on the Tier 1 results.

3

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

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

4

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

Post

- RTR Emissions
Table 4.2

- 4 summarize s the chronic and acute inhalation risk results for this source category based on post

- RTR control emissions

. The MIR from Wool Fiberglass Manufacturing
emiss ions will be reduced from 20

- in

- 1 million to 5

- in

- 1 million after implementation of this proposal . In addition, the acute noncancer HQ for formaldehyde based on the REL will be
reduced from 30 to 7

. T he number of individuals exposed to cancer risks above 10

- in

- 1 million will be reduced from 6,900 for actual emissions to 0 for this proposal, and the number of individuals exposed to cancer risks above 1

- in

- 1 million will be reduced from 1.2 million for actual emissions to 21,000 for this proposal.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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T abl e 4.2

- 4 Summary of Source Category Le vel Inhalation Risks for Wool Fiberglass Manufacturing

– Post

- RTR Control

Result HAP “Drivers”

Number of Facilities Estimated to be i n Source Category 30 n/a

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

Cancer Risks Maximum Individual Lifetime Cancer Risk (in 1 million) 5 Formaldehyde, Cr (VI)

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

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

Greater than or equal to 1 in 1 million 9 formaldehyde, Cr (VI), Ni, As

Chronic Noncancer Risks

Maximum Respiratory Hazard Index 0.03 formaldehyde

Num ber of Facilities with Maximum Respiratory Hazard Index:

Gre ater than 1 0 n/a Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 7

0.3 formaldehyde (REL)

formaldehyde (AEGL

- 1,
ERPG

- 1)

Number of Facilities With Potential for Acute
Effects 5 formaldehyde

Population Exposure Number of People Living Within 50 Kilometers
of Facilities Modeled 30,000,000 n/a

Number of People Exposed to Cancer Risk: Greater than or equal to 100 in 1 million 0 n/a Greater than or equal to 10 in 1 million 0 n/a Greater than or equal to 1 in 1 million 21,000 n/a

Nu mber of People Exposed to Noncancer Respiratory Hazard Index:

Greater than 1 0 n/a Estimated Cancer Incidence (excess cancer cases per year) 0.01 26 n/a

Contribution of HAP to Cancer Incidence Formaldehyde Cr (VI) Arsenic Compounds
Nickel
Cadmium 73%
18%
5%
3%
1% n/aDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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### 4.3 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 2 0 in a million based on act ual emissions. The major contributor to this cancer risk is formaldehyde, although c hromium (VI) is also a risk driver. Chromium i s emitted from the furnace refractory brick as it breaks down over time. The greatest amount of c hromium (VI) is emitted fr om 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 corrosi on protect ion. Refractory bricks in the glass melting industry are typically composed of Al 2 O 3 , Al 2 0 3

- SiO 2 , ZrO 2 , with or without Cr 2 O 3 added, and dense

Cr 2 O 3 .[ 31

, 32 ] Refractory brick breaks down over time, and therefore, must be replaced periodically (approximatel y 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 c hromium in the Wool Fiberglass Manufacturing Industry, it is
reasonable to assume t hat 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

in dividual lifetime cancer risks of the o ther 28 Wool Fiberglass facilit ies switching to high

c hromium brick. For the auxiliary risk characterization analysis it was assumed that the Cr (VI) would be emitted from the other facilities at the same as rate (in lbs Cr (VI) emitted per ton of glass pulled) as for the K2 furnace at the Certainteed Facility in Kansas City, Kansas.

The results of the auxiliary analysis (Table 4. 3

- 1 ) show that 4 facilities would have maximum individual lifetime cancer risks greate r than 100 in a million, with the highest facility at 4 00 in
a million. Under this scenario

, 5 4 ,000 people would be exposed to risks of greater than 10 in
a million and over 2.2 million people would be exposed to cancer risks of greater than 1 in a
millio n

.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Table 4. 3

- 1 Summary of Source Category Le vel Cancer Risks for the Wool Fiberglass Manufacturing Auxiliary Analysis

Result HAP “Drivers”

Number of Facilities Estimated to be i n 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) 4 00 Cr (VI)

Number of Facilities with Maximum Individual Lifetime Cancer Risk: Greater than or equal to 100 in 1 million 4 Cr (VI), formal dehyde Greater than or equal to 10 in 1 million 24 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 200 n/a Greater than or equal to 10 in 1 million 54 ,000 n/a Greater than or equal to 1 in 1 million 2,200,000 n/a Estimated Cancer Incidence (excess cancer cases per year) 0. 1 4 n/a

Contribution of HAP to Cancer Incidence Formaldehyde Cr (VI) 18 %
82 % n/aDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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

5.1 Exposure Modeling Uncertainties

Although every effort has been made to identify al l 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 analysis . The chronic ambient modeling uncertainties are considered relatively small in comparison, since we are using EPA’s refined local dispersion model with site

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

- or long

- term population mobility, and by neglecting processes like deposition, plume depletion, and atmospheric degradation. Additionally, estimates of the MIR contain uncertainty , because they are deriv ed at ce nsus 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 t he meteorology dataset location could result in a range of chronic ambient concentrations which
varied from as much as 17 percent below the predicted value to as much as 84 percent higher than the predicted value. This variability translates directly to the predicted exposures and risks in our assessment, indicating that the actual risks could vary from 17% 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 threshold
values , erring on the side of overestimating potential health risks from acute exposures. In the cases where these results indicated the potential for exceeding short

- term health thresholds, we have refined our assessment by developing a better understanding of the geography of the facility relative to potential exposure locations.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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### 5.2 Uncertainties in the Dose

- Response Relationships

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

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

Although every effort is made to identify peer

- review ed dose

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

- reviewed cancer potency values or reference values for chronic non

- cancer or acute effects (inhalation or ingestion) . Since exposures to thes e 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 b e 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 th e 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 t his discussion in context, we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [ 33 ] (herein
referred to as Cancer Guidelines ). “The primary goal of EPA actions is protection of human health; accordingly, as an Agency policy, risk as sessment 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

.

Fo r 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 o n 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 CancerDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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Guidelines , EPA uses animal cancer bioassays as indicators of potential h uman 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

an d 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 Guideli nes 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). 34 In so me circumstances, the true risk could be as low as zero; however, in other circumstances the risk could also be greater. 35 When developing an upper bound estimate of risk and to provide risk values that do not underestimate risk, EPA generally relies on c onservative default approaches. 36 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 analysi s).

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 exposu res 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 Cha racterization Handbook also recommends that risk characterizations present estimates demonstrating the impact on the assessment of alternative choices, data, models and assumptions [ 34 ]. 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 assessme nt. In general, EPA does not assume that tumor sites observed in an experimental animal bioassay are necessarily predictive of the sites at which

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

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

36 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 jud gment, 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 optio n 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 evalu ating 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 (althoug h defaults are not intended to overtly overestimate risk). See EPA 2004 An Examination of EPA Risk Assessment Principles and Practices,

EPA/100/B

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

- final.pdf.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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tumors would occur in humans. 37 However, unless scientific support is available to show otherwise, EPA assum es 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) Uncertain ties 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 metabol ized 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 differe nces 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 experime ntal 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 uncertainti es 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 estim ate 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 bioassa y 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 whic h a

37 Per the EPA Cancer Guidelines: “The defaul t 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 human s.”Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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 respo nse). 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 c an 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 th at 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 respons e relationships due to the variability in response within human populations. Another National Research Council (NRC) report [ 35 ] suggests that models based on distributions of individual thresholds are likely to lead to sigmoidal

- shaped
dose

- response funct ions 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

suscep tibility 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 respo nses 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 backgroun d 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

u ncertainty in risk assessment (Subramaniam et. al., 2006) [ 36 ]. 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 notDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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show large differences from those based on the upper conf idence 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 huma n 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 diff erences 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 dif ferences. 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 whic h 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 f ace 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 38 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 nee ded 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 expo sures.

38 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 bes t 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

a ppropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly overestimate risk). See EPA 2004 An examination of EPA Risk Assessment Principles and Practices,

EPA/100/B

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

- final.pdf.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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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 withou t an appreciable risk of deleterious effects during a lifetime. 39 To derive values that are intended to be “without appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach [ 37 ],[ 38 ] which includes consideration of both uncertaint y 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 endp oint 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 statist ical 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 (LOAE L).

A series of downward adjustments using default UFs is then applied to the POD to estimate
the reference value [ 39 ] . While collectively termed “UFs”, these factors account for a number of different quantitative considerations when utilizing observed a nimal (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 adjust ment 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 P OD. 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 associa ted 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 subse t 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 t o 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

39 See IRIS glossaryDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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situations, a smaller UF of 3 may be applied to refl ect 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 t he 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
uncertaintie s 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 d ata 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 s pecific chemical, differences in species responses may be greater or less than this value

.

Pharmacokinetic models are useful to examine s pecies 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 anima ls 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 t he 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 chron ic 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 availab le 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 app roach 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 LOA EL, 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 f or a known or suspected endpoint of concern, a
UF of 10 or 3

- fold is typically applied.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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

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

- or risk

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

- 66981, November 12, 2008).

We also note the uncertainties associated with the health

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

- respons e values developed for many of the other HAP, particularly those HAP for which no human health data exist. In 1988, EPA’s IRIS program reviewed the health effects data regarding lead and its inorganic compounds and determined that it would be inappropria te to develop an RfD for these compounds, saying, “A great deal of information on the health effects of lead has been obtained through

decades of medical observation and scientific research. This information has been assessed in the development of air and water quality criteria by the Agency's Office of Health and Environmental Assessment (OHEA) in support of regulatory decision

- making by the Office of Air Quality Planning and Standards (OAQPS) and by the Office of Drinking Water (ODW). By comparison to mo st other environmental toxicants, the degree of uncertainty about the health effects of lead is quite low. It appears that some of these effects, particularly changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral
deve lopment, may occur at blood lead levels so low as to be essentially without a threshold. The Agency's RfD Work Group discussed inorganic lead (and lead compounds) at two meetings (07/08/1985 and 07/22/1985) and considered it inappropriate to develop an RfD for inorganic lead.” EPA’s IRIS assessment for Lead and compounds (inorganic) (CASRN 7439

- 92

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

.

We note further that because of the multi

- pathway, multi

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

related multi

- pathway exposures from industrial sources like primary and secondary leadDraft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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smelting operations. It also considered background l ead exposures from other sources (like contaminated drinking water and exposure to lead

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

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

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

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

Acute noncancer assessment

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

specific or health effect

- specific information (e.g., simple irrita tion 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) heteroge neity 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 a pplied 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 d eveloped 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. W here relevant to the estimated exposures, the
lack of threshold va lues at different levels of severity should be factored into the risk characterization as potential uncertainties.Draft Risk Assessment for the Mineral Wool Production and Woo l Fiberglass

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## 5 References

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27

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